WO2025081094A2 - Procédés, kits et systèmes pour déterminer l'état er d'un cancer et procédés de traitement du cancer sur la base de ceux-ci - Google Patents

Procédés, kits et systèmes pour déterminer l'état er d'un cancer et procédés de traitement du cancer sur la base de ceux-ci Download PDF

Info

Publication number
WO2025081094A2
WO2025081094A2 PCT/US2024/051117 US2024051117W WO2025081094A2 WO 2025081094 A2 WO2025081094 A2 WO 2025081094A2 US 2024051117 W US2024051117 W US 2024051117W WO 2025081094 A2 WO2025081094 A2 WO 2025081094A2
Authority
WO
WIPO (PCT)
Prior art keywords
cancer
positive
sample
subject
negative
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/US2024/051117
Other languages
English (en)
Other versions
WO2025081094A3 (fr
Inventor
Matthew FREEDMAN
Sylvan BACA
Geoff Otto
Travis CLARK
Anthony D'IPPOLITO
Matthew EATON
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Precede Biosciences Inc
Dana Farber Cancer Institute Inc
Original Assignee
Precede Biosciences Inc
Dana Farber Cancer Institute Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Precede Biosciences Inc, Dana Farber Cancer Institute Inc filed Critical Precede Biosciences Inc
Publication of WO2025081094A2 publication Critical patent/WO2025081094A2/fr
Publication of WO2025081094A3 publication Critical patent/WO2025081094A3/fr
Anticipated expiration legal-status Critical
Pending legal-status Critical Current

Links

Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/154—Methylation markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • Progesterone receptor (PR) expression in normal breast epithelium is regulated by ER (Jensen, Cancer (1980) 46:2759-2761). Presence of ER, PR and human epidermal growth factor receptor-2 (HER2) status in invasive breast carcinoma is now routinely estimated as these markers are considered to be important prognostic factors.
  • ER and PR status has been used for many years to determine a patient’s suitability for treatment with endocrine therapy (e.g., tamoxifen).
  • Such methods focus only on a small region at a single tumor site at a given time and therefore do not accurately capture tumor heterogeneity or receptor evolution and therefore only partially characterize the relevant patient population.
  • diagnostic methods for determining ER status including methods that are independent of IHC testing.
  • Improved diagnostic methods would also better support future clinical trials that seek to identify subpopulations of patients that respond to ER-targeted agents. They would also expand our understanding of the underlying biology of ER-positive cancer and help identify new treatments.
  • the present disclosure includes, among other things, histone modification measurements in cfDNA that are characteristic of ER-positive and ER-negative cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating an ER-positive and ER-negative cancers.
  • histone modification measurements in cfDNA can be used to detect or determine resistance of a cancer (e.g., breast, ovarian, or endometrial cancer) to a therapy or transformation of a cancer from one subtype to another.
  • the present disclosure includes exemplary genomic loci that are differentially modified in ER-positive vs. ER-negative cancer, e.g., breast, ovarian, or endometrial cancer.
  • histone methylation can be or include H3K4me3.
  • histone acetylation can be or include histone acetylation marks selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, or a combination thereof.
  • histone acetylation can be or include H3K27ac.
  • the present disclosure further relates, in various embodiments, to the measurement of transcription factor binding in cell-free DNA (cfDNA) to determine ER status.
  • cfDNA cell-free DNA
  • the present disclosure includes, among other things, transcription factor binding measurements in cfDNA that are characteristic of ER-positive cancers, which in various embodiments are useful, e.g., in detecting, monitoring, selecting treatment for, and/or treating an ER-positive cancer.
  • transcription factor binding measurements in cfDNA can be used to detect or determine resistance of a cancer (e.g., breast, ovarian, or endometrial cancer) to a therapy or transformation of a cancer from one subtype to another.
  • a cancer e.g., breast, ovarian, or endometrial cancer
  • histone acetylation corresponds and/or is correlated with transcription factor binding.
  • DNA methylation corresponds and/or is correlated with transcription factor binding.
  • a genomic locus is differentially bound by transcription factors if it is characterized by increased or decreased transcription factor binding as compared to a reference (e.g., a sample from an ER-negative or healthy subject). Increased or decreased
  • transcription factor binding can be or include, e.g., increased or decreased transcription factor binding as determined by various transcription factor binding assays known in the art.
  • the present disclosure provides a method of determining the ER status of a cancer in a subject, the method comprising: quantifying, at one or more genomic loci in a biological sample, optionally in cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) binding of one or more transcription factors, and/or (iv) DNA methylation.
  • cfDNA cell-free DNA
  • the one or more histone modifications are quantified using a histone modification assay that measures one or more of H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, H3K4me3, and pan-acetylation.
  • the histone modification assay detects H3K4me3 modifications.
  • the histone modification assay detects H3K27ac modifications.
  • chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), and a DNase hypersensitivity assay.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde-Assisted Isolation of Regulatory Elements sequencing
  • MNase-seq Merococcal Nuclease digestion with sequencing
  • binding of one or more transcription factors is quantified using a transcription factor binding assay that detects binding of one or more of p300, mediator complex, cohesin complex, RNA pol II, FOXA1, ESR1, PR, MYC, EN1, FOXM1, KLF4, AP-2, RARa, or RUNX1.
  • the transcription factor binding assay is selected from ChIP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
  • DNA methylation is quantified using Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq).
  • BS-Seq Bisulfite sequencing
  • WGBS Whole Genome Bisulfite Sequencing
  • MBD-seq Methyl-CpG-Binding Domain sequencing
  • the method comprises quantifying two or more of the following, each at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample obtained or derived from the subject: (i) one or more histone modifications, (ii) chromatin accessibility, (iii) transcription factor binding, and/or (iv) DNA methylation.
  • the method comprises quantifying two or more histone modifications, e.g., quantifying H3K4me3 and H3K27ac modifications.
  • the method comprises quantifying one or more histone modifications and DNA methylation, e.g., quantifying H3K4me3 and/or H3K27ac modifications and DNA methylation. In some embodiments, the method comprises quantifying H3K4me3 modifications, H3K27ac modifications and DNA methylation.
  • the biological sample is a liquid biopsy sample, e.g., a plasma sample, serum sample, or urine sample.
  • quantification of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has an ER- positive cancer.
  • quantification of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at the one or more genomic loci as compared to a reference indicates that the subject has an ER- negative cancer.
  • the cancer is breast cancer, ovarian cancer, or endometrial cancer. In some embodiments, the cancer is breast cancer.
  • the reference is a predetermined threshold, a measurement from a liquid biopsy sample, and/or a normalized value, optionally wherein the reference is a measurement from a liquid biopsy sample obtained from a cohort of subjects who have previously been determined to have an ER-negative cancer or to be cancer free.
  • cfDNA comprising H3K4me3 modifications is enriched using a method that comprises incubating a sample with an agent (e.g., an antibody) that binds H3K4me3 modifications;
  • agent e.g., an antibody
  • cfDNA comprising H3K27ac modifications is enriched using a method that comprises incubating a sample with an agent (e.g., an antibody) that binds H3K27ac modifications;
  • methylated cfDNA is enriched using a method that comprises incubating a sample with an agent (e.g., an antibody or a methyl binding domain) that binds methylated DNA.
  • an agent that binds H3K4me3 modifications, an agent that binds H3K27ac modifications, and/or an agent that binds methylated DNA can be attached (e.g., via a covalent or noncovalent bond) to a physical support (e.g., a bead, a magnetic bead, an agarose bead, or a magnetic epoxy bead) prior to incubating with a sample.
  • a physical support e.g., a bead, a magnetic bead, an agarose bead, or a magnetic epoxy bead
  • sequence reads are mapped to a reference genome, and one or more genomic loci correspond to sequence read peaks, wherein a sequence read peak corresponds to a region of the genome that has a higher number of sequence reads that the local background.
  • peaks in high noise regions are ignored when identifying genomic loci with a higher number of sequence reads than the local background.
  • peaks in regions likely to be artifactual are removed.
  • peaks that are less than 50 bp in length are removed.
  • peaks in regions with high levels of one or more epigenetic markers in white blood cells are removed.
  • a method comprises determining an ER-positive/ER- negative ratio score for two or more epigenetic biomarkers. In some embodiments, a method comprises determining an ER-positive/ER-negative ratio score for two or more epigenetic biomarkers, wherein the ER-positive/ER-negative ratio scores are combined. In some embodiments, a method comprises determining an ER-positive/ER-negative ratio score each of H3K4me3 modifications, H3K27ac modifications, and methylated DNA, and combining the ratio scores. In some embodiments, two or more ratio scores can be combined using fitted values determined using a logistic regression.
  • a method further comprises comparing one or more quantified epigenetic biomarkers to a reference, and wherein an increase or decrease in the one or more epigenetic markers as compared to the reference indicates that a subject has an ER- positive or an ER-negative cancer.
  • a sample comprises a detectable amount of ctDNA (e.g., wherein estimated tumor fraction is >3% for the cfDNA, e.g., as determined by iChorCNA).
  • the method comprises quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in Tables 1-3.
  • the method comprises quantifying H3K4me3 modifications for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1.
  • the method comprises quantifying H3K27ac modifications for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2. In some embodiments, the method comprises quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3.
  • the area under the receiver operating characteristic (AUROC) for determining if a subject has an ER-positive cancer vs. an ER-negative cancer is greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95).
  • the ER-positive cancer is an ER-positive cancer based on IHC testing and the ER-negative cancer is an ER-negative cancer based on IHC testing.
  • the subject has previously been determined to have cancer.
  • a sample is obtained from a subject having cancer wherein a biopsy of the cancer is not possible and/or feasible.
  • the present disclosure provides a method of treating a subject having a cancer, the method comprising: administering a cancer therapy to the subject based on the ER status of the cancer, wherein the ER status of the cancer has been determined using any one of the aforementioned methods of determining ER status.
  • the method further comprises determining the ER status of the cancer using any one of the aforementioned methods of determining ER status.
  • the cancer has been determined to be ER-positive and the cancer therapy comprises an ER-targeted agent.
  • the cancer therapy is one appropriate for an ER- negative cancer.
  • the cancer therapy does not comprise administering an ER-targeted agent.
  • the method further comprises determining the ER status of the cancer using any one of the aforementioned methods of determining ER status.
  • the cancer therapy comprises an ER-targeted agent.
  • the cancer therapy does not comprise administering an ER-targeted agent.
  • the present disclosure provides a method of monitoring the ER status of a cancer in a subject, and optionally treating the cancer, the method comprising: determining the ER status of the cancer using any one of the aforementioned methods of determining ER status at first and second time points.
  • the subject has been administered an ER-targeted agent after the first time point and before the second time point.
  • the method further comprises administering a cancer therapy, optionally an ER-targeted agent, to the subject based on the ER status of the cancer at the second time point, optionally wherein the type, dose and/or frequency of administration of the cancer therapy is adjusted based on the ER status of the cancer at the second time point.
  • the present disclosure provides a method of treating a subject having a cancer, the method comprising: administering an ER-targeted agent to the subject if the subject has been determined to have a validated epigenetic profile indicative of an ER-positive cancer based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject, and, if the subject has not been determined to a validated epigenetic profile indicative of an ER-positive cancer, not administering an ER-targeted agent, wherein the presence of the validated epigenetic profile has been determined using a validated classifier, wherein the validated classifier has been obtained by: (a) determining a genomic profile of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation in (i) one or more ER-positive cell lines or (ii) biological samples obtained from a first cohort of subjects who have previously been determined to have an ER
  • the classifier in step (d) was trained on two or more histone modification levels in the differential loci. In some embodiments, the two or more histone modification levels comprise H3K4me3 and H3K27ac modification levels. [0059] In some embodiments, the classifier in step (d) was trained on one or more histone modification levels and DNA methylation in the differential loci. In some embodiments, the one or more histone modification levels comprise H3K4me3 and/or H3K27ac modification levels. In some embodiments, the classifier in step (d) was trained using ridge regression, elastic- net regression, or lasso regression.
  • the kit comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample. In some embodiments, the kit comprises reagents for library preparation for sequencing. In some embodiments, the kit comprises reagents for sequencing. In some embodiments, the kit comprises instructions for determining if a subject has an ER-positive cancer.
  • the present disclosure provides a non-transitory computer readable storage medium encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to
  • the sequencer is configured to generate a Whole Genome Sequencing (WGS) data set from the sample.
  • the system further comprises a sample preparation device.
  • the sample preparation device is configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample.
  • the sample preparation device comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample.
  • the one or more genomic loci are selected from Tables 1-3.
  • the reagents comprise one or more methyl-binding domains for use in MBD-seq.
  • the device comprises reagents for isolation of cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample.
  • the device comprises reagents for library preparation for sequencing.
  • the sequencer comprises reagents for sequencing.
  • a method is for determining ER status of a cancer in a subject (e.g., patient).
  • the method may include receiving (e.g., by a processor of a computing device) one or more genomic profiles of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation for the subject.
  • the method may further include determining whether the subject has an epigenetic profile indicative of an ER- positive cancer by classifying the genomic profile using an ER classifier.
  • an ER classifier has been validated using liquid biopsy sample data.
  • a non-transitory computer readable storage medium may be encoded with a computer program, where the program may comprise instructions that when executed by one or more processors cause the one or more processors to perform operations to perform a method for determining ER status of a cancer in a subject (e.g., patient).
  • a computer system may include a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform a method for determining ER status of a cancer in a subject (e.g., patient).
  • a method of treating a subject having a cancer includes administering an ER-targeted agent to the subject, wherein the subject has been determined to have a validated epigenetic profile indicative of an ER-positive cancer based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject.
  • the presence of the validated epigenetic profile has been determined using a classifier (e.g., a validated classifier) according to a method for determining ER status of a cancer in a subject (e.g., patient).
  • genomic loci from Tables 1-3 for different modifications, namely (i) H3K4me3 modifications, (ii) H3K27ac modifications, (iii) DNA methylation (DNAme) or (iv) all of the above (All) and (b) using different subsets of genomic loci in Tables 1-3 for a particular modification, namely (i) all genomic loci with an absolute log2(fold-change) ⁇ 0.5, (ii) all genomic loci with an absolute log2(fold-change) ⁇ 1, (iii) all genomic loci with an absolute log2(fold-change) ⁇ 2, (iv) all genomic loci with an absolute log2(fold-change) ⁇ 3, and (v) all genomic loci with an absolute log2(fold-change) ⁇ 4.
  • Fig.2 shows representative, non-limiting graphs that demonstrate the accuracy of ER status (based on AUCROC) determination using the classifiers that were generated in accordance with Example 2.
  • Fig.3 (A) shows a heatmap representation of z-scored, ctDNA- and background- normalized counts at differential peaks (DE-seq, FDR ⁇ 0.05, log2(fold change) > 1) across ER +/- patients (status determined by IHC). Each row corresponds to signal observed in an individual patient, and each column represents an enhancer/promoter/MBD locus.
  • (B) shows ROC curves for an exemplary ER status classifier generated in accordance with Example 3 and applied to plasma samples obtained from patients previously diagnosed with metastatic breast cancer. ROC curves assessing performance of a regularized logistic regression model to classify
  • Fig.4 is a block diagram of an example network environment for use in the methods and systems described herein, according to illustrative embodiments of the present disclosure.
  • Fig.5 is a block diagram of an example computing device and an example mobile computing device, for use in illustrative embodiments of the present disclosure.
  • DETAILED DESCRIPTION [0079] The present disclosure is based, at least in part, on the demonstration that the ER status of a cancer in a subject can be determined by detecting and quantifying the presence of histone modifications and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from a liquid biopsy sample, e.g., a plasma sample obtained or derived from the subject.
  • cfDNA cell-free DNA
  • the present disclosure also encompasses methods where chromatin accessibility and/or binding of one or more transcription factors are detected at the one or more genomic loci instead of (or in addition to) histone modifications and/or DNA methylation.
  • the present disclosure is also based, at least in part, on the demonstration that genomic loci that are differentially modified based on different types of histone modifications (e.g., histone methylation marks such as H3K4me3 and histone acetylation marks such as H3K27ac) and/or DNA methylation can be combined into multimodal classifiers to determine ER status.
  • histone methylation marks such as H3K4me3
  • histone acetylation marks such as H3K27ac
  • DNA methylation can be combined into multimodal classifiers to determine ER status.
  • Estrogens are steroidal hormones that function as the primary female sex hormone. There are three major forms of estrogen, namely estrone (E1), estradiol (E2) and estriol (E3). Estradiol (E2) is the predominant estrogen in nonpregnant females, while estrone (E1) and estriol (E3) are primarily produced during pregnancy and following the onset of menopause, respectively. All estrogens are produced from androgens through actions of enzymes such as aromatase. Follicle-stimulating hormone and luteinizing hormone stimulate the synthesis of estrogen in the ovaries.
  • estrogens are also produced in smaller amounts by other tissues such as the liver, adrenal glands, and mammary gland.
  • PR progesterone receptor
  • ER ⁇ and ER ⁇ are members of the nuclear receptor superfamily of transcription factors that are characterized by highly conserved DNA- and ligand-binding domains (Wang et al., J Hematol Oncol (2017) 10:168).
  • the DNA binding domain which is extremely well conserved between ER ⁇ and ER ⁇ (97% homology), contains two functionally distinct zinc finger motifs that are responsible for specific DNA binding, as well as mediating receptor dimerization (Hewitt and Korach, Endocr Rev (2016) 39(5):664-675).
  • the unliganded ER has been shown to be present in a cytosolic complex with hsp90 and associated proteins, with ligand binding allowing dissociation from the hsp90 complex, receptor dimerization, nuclear localization and binding to estrogen response elements (EREs) in promoters of estrogen- regulated genes (Pratt and Toft, Endocr Rev (1997) 18:306-360).
  • EEEs estrogen response elements
  • Genome-wide chromatin immunoprecipitation studies have confirmed that the majority of ER-binding sites in estrogen responsive genes conform well to this consensus sequence (Welboren et al., EMBO J (2009) 28:1418-1428).
  • a subject has one or more biomarkers and/or risk factors for cancer, e.g., ER-positive cancer, e.g., ER-positive breast cancer, etc.
  • a human subject is identified as in need of ER status screening based on an initial cancer diagnosis, e.g., a breast cancer, etc. diagnosis.
  • a human subject is a subject
  • a sample from a subject e.g., a human can be obtained from a liquid biopsy.
  • a sample and/or reference is obtained from serum, plasma, or urine.
  • the sample is serum.
  • a sample comprises circulating tumor DNA (ctDNA).
  • a sample is derived from about 1 mL of blood obtained from the subject.
  • a sample is derived from about 0.5-5 mL of blood obtained from the subject, e.g., about 0.5 to about 2 mL, about 0.5 to 1.75 mL, about 0.5 to 1.5 mL, about 0.75 to 1.25 mL, about 0.9 to 1.1 mL, about 1 mL, about 2 mL, about 3 mL, about 4 mL, or about 5 mL of blood.
  • a sample is a sample of cell-free DNA (cfDNA).
  • cfDNA is typically found in human biofluids (e.g., plasma, serum, or urine) in short, double-stranded fragments.
  • cfDNA Circulating tumor DNA
  • ctDNA Circulating tumor DNA
  • ctDNA can be present in human biofluids bound to leukocytes and erythrocytes or not bound to leukocytes and erythrocytes.
  • Various tests for detection of tumor-derived ctDNA are based on detection of genetic or epigenetic modifications that are characteristic of cancer (e.g., of a relevant cancer).
  • ctDNA comprises less than 30%, less than 20%, or less than 10% of the cfDNA in the liquid biopsy sample obtained from the subject, e.g., less than 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2% or less than 1% of the cfDNA in the sample.
  • the percentage of ctDNA in the liquid biopsy sample is assessed using ichorCNA which estimates the percentage of ctDNA in a sample probabilistically (see Adalsteinsson et al., Nat Commun (2017) 8(1):1324 the entire contents of which are incorporated herein by reference).
  • a method comprises isolating DNA (e.g., cfDNA) from a liquid biopsy sample (e.g., from 1, 2, 3, 4, or 5 mL of a liquid biopsy sample).
  • a liquid biopsy sample e.g., from 1, 2, 3, 4, or 5 mL of a liquid biopsy sample.
  • nucleic acids can be isolated using, without limitation, standard DNA purification techniques, by direct gene capture (e.g., by clarification of a sample to remove assay-inhibiting agents and capturing a target nucleic acid, if present, from the clarified sample with a capture agent to produce a capture complex and isolating the capture complex to recover the target nucleic acid).
  • direct gene capture e.g., by clarification of a sample to remove assay-inhibiting agents and capturing a target nucleic acid, if present, from the clarified sample with a capture agent to produce a capture complex and isolating the capture complex to recover the target nucleic acid.
  • Samples include materials prepared by processes including, without limitation, steps such as concentration, dilution, adjustment of pH, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin, etc.), addition of preservatives, addition of calibrants, addition of protease inhibitors, addition of denaturants, desalting, concentration and/or extraction of sample nucleic acids, and/or amplification of sample nucleic acids (e.g., by PCR or other nucleic acid amplification techniques).
  • steps such as concentration, dilution, adjustment of pH, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin, etc.), addition of preservatives, addition of calibrants, addition of protease inhibitors, addition of denaturants, desalting, concentration and/or extraction of sample nucleic acids, and/or amplification of sample nucleic acids (e.g., by PCR or other nucleic
  • Separation and purification in the present disclosure may include any procedure known in the art, such as capillary electrophoresis (e.g., in capillary or on-chip) or chromatography (e.g., in capillary, column or on a chip).
  • Electrophoresis is a method that can be
  • Histone methylation is understood to increase or decrease expression of associated coding sequences, depending on which histone residue is methylated. Histone methylation is an essential modification that can cause monomethylation (me1), dimethylation (me2), and trimethylation (me3) of several amino acids, thus directly affecting heterochromatin formation, gene imprinting, X chromosome inactivation, and gene transcriptional regulation.
  • genomic locus can refer to, or be determined by or detected as, a comparative difference or change in modification status of one or more genomic loci between a first sample, condition, disease, or state and a second or reference sample, condition, disease, or state.
  • a reference is a normalized sample.
  • a reference is a measurement obtained from liquid biopsy samples obtained from a cohort of subjects who have previously been determined to have an ER-positive or ER-negative cancer, including, e.g., an ER-positive or ER-negative breast cancer.
  • a reference is a non-contemporaneous sample from the same source, e.g., a prior sample from the same source, e.g., from the same subject.
  • a reference for the accessibility status of one or more genomic loci can be the accessibility status of the one or more genomic loci (e.g., one or more differentially accessible genomic loci) in a sample (e.g., a sample from a subject), or a plurality of samples, known to represent a particular state (e.g., an ER-positive cancer or ER-negative cancer).
  • differential modification or differential accessibility can refer to a differential (e.g., between a sample and a reference) with an absolute log2(fold-change) that is greater than or equal to 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0 or more, or any range in between, inclusive, e.g., as measured according to an assay provided herein.
  • the log2(fold-change) values are based on ratios of ER-positive to ER-negative reads, i.e., positive log2(fold-change) values indicate that sequencing reads in a particular genomic locus are associated with an ER-positive status while a negative log2(fold-change) value indicates that sequencing reads in a particular genomic locus are associated with an ER-negative status.
  • Enhancers are genomic loci that can be differentially modified or differentially accessible in and/or between conditions, diseases, and other states. Enhancers are cis-acting DNA regulatory regions that are thought to bind trans-acting proteins that contribute to expression patterns of associated genes.
  • Chromatin ImmunoPrecipitation sequencing of histone modifications (e.g., acetylation) have identified millions of enhancers in mammalian genomes.
  • the number of active enhancers in any given cell type is estimated to be in the tens of thousands.
  • Certain transcription factors TFs
  • master transcription factors associate with active enhancers with important impacts on gene expression and cell function.
  • Certain such transcription factors preferentially associate with enhancers that regulate genes required for establishing cell identity and function, including enhancer domains known as “super-enhancers”.
  • master TFs can participate in inter-connected auto-regulatory circuitries or “cliques” that are self-reinforcing, show marked cell selectivity, and function to maintain cell state and/or cell survival.
  • Techniques for Detecting and Quantifying Histone Modifications and Transcription Factor Binding [0130] Various techniques of molecular biology are well known in the art and/or disclosed in the present application for detecting and quantifying histone modifications and/or transcription factor binding. In some embodiments, the methods, kits and systems of present disclosure involve the detection and quantification of histone modifications and/or transcription factor binding in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA. Chromatin ImmunoPrecipitation (ChIP) is one technique of
  • ChIP-chip, ChIP-exo, ChIP Re-ChIP, and ChIPmentation are other alternative techniques that could be used. [0131] ChIP can involve various steps including one or more of fixation, sonication, immunoprecipitation, and analysis of the immunoprecipitated DNA. ChIP has become a very widely used tissue-based technique for determining the in vivo location of binding sites of various transcription factors and histones.
  • ChIP helps to detect DNA-protein interactions that take place in living cells. More importantly, ChIP can be coupled to many commonly used molecular biology techniques such as PCR and real-time PCR, PCR with single-stranded conformational polymorphism, Southern blot analysis, Western blot analysis, cloning, and microarray. The resulting versatility has increased the potential of this technique. [0132] ChIP of tissue samples usually involves cross-linking of the chromatin-bound proteins by formaldehyde, followed by sonication or nuclease treatment to obtain small DNA fragments. Immunoprecipitation can be then carried out using specific antibodies to the DNA- binding protein of interest.
  • the DNA can be then released from the proteins and analyzed using various methods. ChIP has also been used to study RNA-protein interactions. X-ChIP methods utilize fixed chromatin fragmented by sonication, while the N-ChIP methods utilize native chromatin, which can be unfixed and nuclease digested. [0133]
  • the first step of the technique can be the cross-linking of DNA and proteins. Formaldehyde is one of the most used cross-linking agents.
  • formaldehyde can be the ease of reversibility of the cross-links and its ability to form bonds that span approximately 2 angstroms. This means that formaldehyde can bind molecules in close association with each other.
  • Harvested chromatin can be sonicated in one or more sonication cycles. DNA can be typically broken into to 100–500 bp fragments to pinpoint the location of the DNA sequence of interest.
  • An alternative to sonication can be nuclease digestion of the chromatin, e.g., in N- ChIP methods. Purification of chromatin can be achieved using a cesium chloride (CsCl) gradient centrifugation.
  • Chromatin can be enriched for a particular histone modification using an agent that binds the histone modification (e.g., immunoprecipitating using one or more antibodies that bind a target epitope).
  • an antibody used in ChIP can selectively bind a particular transcription factor or one or more particular histone modifications, such as one or more particular histone acetylation modifications or histone methylation modifications.
  • an antibody used to bind a target epitope can be a “pan” antibody (e.g., a pan- acetylation antibody, a pan-methylation antibody, an antibody that binds a group of histone modifications associated with increased transcription activation, and/or an antibody that binds a group of histone modifications associated with increased transcription repression).
  • the antibody against the protein of interest is allowed to bind to the protein-DNA complex, and the complex can be then precipitated.
  • Immunosorbants commonly used to separate the antigen-antibody complex from the lysate include salmon sperm DNA-protein A-Sepharose®, protein G, magnetic beads, and other engineered immunoprecipitation systems known to those of skill in the art.
  • Immunoprecipitated DNA can be eluted. Once the DNA of interest is isolated, many detection and quantification methods can be used to study the isolated gene fragments. Commonly utilized methods include PCR, real-time PCR, slot blot hybridization, microarray techniques, and deep or next-generation sequencing. ChIP-seq combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins.
  • ChIP chromatin immunoprecipitation
  • ChIP-seq can be used to map DNA-binding proteins, e.g., transcription factor binding sites and histone modifications in a genome-wide manner.
  • Cell-free Chromatin ImmunoPrecipitation sequencing involves applying ChIP-seq to samples that include cell-free DNA, e.g., liquid biopsy samples including cfDNA such as plasma samples including cfDNA (e.g., see Sadeh et al., Nat Biotechnol (2021) 39: 586–598 and Jang et al., Life Sci Alliance (2023) 6(12):e202302003 the entire contents of each of which are incorporated herein by reference).
  • cfChIP-seq uses
  • exemplary antibodies that bind H3K4me3 include PA5-27029 (available from Thermo Fisher Scientific in Waltham, MA) and C15410003 (available from Diagenode in Denville, NJ) and exemplary antibodies that bind H3K27ac include ab21623 or ab4729 (both available from Abcam in Cambridge, UK) and C15210016 (available from Diagenode in Denville, NJ).
  • the antibodies or antibody fragments can be covalently coupled to beads, e.g., epoxy beads.
  • the antibodies or antibody fragments can be non-covalently coupled to beads, e.g., Protein A or Protein G beads such as Dynabeads® Protein A or Dynabeads® Protein G beads.
  • a cfDNA library is then typically prepared from the captured cfDNA.
  • Library preparation can be done on-bead or after releasing the captured cfDNA by digestion of bound histones, e.g., using proteinase K.
  • the cfDNA library is then sequenced to generate reads of captured cfDNA sequences, e.g., by next-generation sequencing (NGS) as is known in the art.
  • NGS next-generation sequencing
  • the reads are then analyzed, e.g., aligned and counted using standard bioinformatic techniques as is known in the art.
  • a cfChIP-seq bioinformatic pipeline can include, e.g., alignment of sequence reads to a reference genome with BWA or Bowtie2.
  • Aligned reads can be used to call and quantify peaks as compared to a reference.
  • histone modifications at a given genomic loci can be quantified using sequencing data.
  • histone modifications can be quantified by counting the number of sequence reads that fall within a genomic loci (e.g., have at least one nucleotide overlapping with a genomic loci).
  • non-uniquely mapped and/or redundant sequence reads are discarded prior to quantifying histone modifications.
  • sequence reads that fall within high noise regions of the genome are ignored.
  • sequence reads are adjusted on the basis of sequencing depth prior to counting.
  • Adjusting on the basis of sequencing depth can include, e.g., quantile normalizing sequence reads to a common reference distribution.
  • sequence reads are adjusted on the basis of ChIP quality prior to counting.
  • sequence reads are normalized relative to aggregate counts across a set of regions (e.g., 1,000, 2,000,
  • CUT&Tag involves antibody-based binding of a target protein, e.g., transcription factor or histone modification of interest, where antibody incubation is directly followed by the shearing of the chromatin and library preparation (see Kaya-Okur et al., Nat Comm (2019) 10:1930).
  • a target protein e.g., transcription factor or histone modification of interest
  • a method described herein comprises attaching (e.g., ligating) DNA adapters to cfDNA.
  • DNA adapters can be attached prior to, during, or after enrichment for a histone modification.
  • a method comprises amplifying cfDNA after attaching DNA adapters.
  • the methods, kits and systems of the present disclosure involve the detection and quantification of chromatin accessibility in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde-Assisted Isolation of Regulatory Elements sequencing
  • MNase-seq Merococcal Nuclease digestion with sequencing
  • DNase hypersensitivity assays are exemplary techniques of molecular biology useful in detecting and quantifying chromatin accessibility in samples. Sono-Seq is another alternative method that could be used (see Auerbach et al., Proc Natl Acad USA (2009) 106(35):14926-14931).
  • FAIRE-seq is a method in which nucleosome-depleted regions of DNA (NDRs) are isolated from chromatin.
  • a typical FAIRE-seq assay can include a first step in which cells are fixed using formaldehyde so that histones are crosslinked to interacting DNA.
  • Crosslinked chromatin can then be sheared by sonication that generates protein-free DNA and protein- crosslinked DNA fragments.
  • Protein-free DNA can be isolated using a phenol–chloroform extraction: DNA crosslinked with protein stays in organic phase, while protein-free DNA stays in aqueous phase. Highly crosslinked DNA remains in the organic phase and the non-crosslinked DNA is pulled to the aqueous phase. Non-crosslinked DNA from the aqueous phase can then be amplified and sequenced. Reads enriched in the sequencing pool tend to have lower nucleosome and transcription factor binding and are therefore inferred to come from accessible regions.
  • NOMe-seq is a method to identify nucleosome-depleted regions of DNA (NDRs) with M.CviPI methyltransferase that methylates cytosine in GpC dinucleotides not protected by
  • a typical NOMe-seq protocol can include a step in which samples are treated with M.CviPI and S-adenosylhomocysteine (SAM) to methylate accessible GpC sites.
  • SAM S-adenosylhomocysteine
  • DNA is treated with bisulfite, which converts unmethylated cytosine to uracil using sodium bisulfite, while methylated cytosine is unaffected.
  • a library is generated using adapters and sequenced. Accessible chromatin is expected to have high levels of GpC m but low levels of C m pG. Therefore, NOMe-seq identifies NDRs using the two separate methylation analyses that serve as independent (but opposite) measures, providing matched chromatin designations for each regulatory element.
  • ATAC-seq uses hyperactive Tn5 transposase that preferentially cuts accessible chromatin regions and simultaneously inserts adapters to the fragmented region (Buenrostro et al., Nat Methods (2013) 10(12):1213-1218 the entirety of which is incorporated herein by reference).
  • a typical ATAC-seq assay can include a first step in which samples are incubated with Tn5 transposase. DNA can then be isolated and purified. DNA fragmented and tagged by Tn5 transposase can be purified and then amplified to generate a library and sequenced for analysis.
  • kits and systems of the present disclosure involve the detection and quantification of chromatin accessibility in samples, e.g., in liquid biopsy samples including cfDNA such as plasma samples including cfDNA.
  • Bisulfite sequencing (BS-Seq), Whole Genome Bisulfite Sequencing (WGBS), Methylated DNA ImmunoPrecipitation sequencing (MeDIP-seq), or Methyl-CpG-Binding Domain sequencing (MBD-seq) are exemplary techniques of molecular biology useful in detecting and quantifying chromatin accessibility in samples.
  • Reduced representation bisulfite sequencing (RRBS) is another alternative method that could be used (see Meissner et al., Nucleic Acids Res (2005) 33(18):5868-5877).
  • Illumina Infinium arrays could also be used to detect and quantify DNA methylation.
  • DNA methylation typically refers to the methylation of the 5’ position of cytosine (mC) by DNA methyltransferases (DNMT). It is a major epigenetic modification in humans and many other species. In mammals, most DNA methylations occur within the context of CpG dinucleotides. DNA methylation is thought to be a repressive chromatin modification. Aberrant methylation can lead to many diseases including cancers (Robertson, Nat Rev Genet (2005) 6:597–610 and Bergman and Cedar, Nat Struct Mol Biol (2013) 20:274–281).
  • BS-Seq Bisulfite sequencing
  • WGBS Whole-Genome Bisulfite Sequencing
  • genomic DNA is treated with sodium bisulfite and then sequenced, providing single-base resolution of methylated cytosines in the genome.
  • unmethylated cytosines are deaminated to uracil which, upon sequencing, are converted to thymidine.
  • methylated cytosines resist deamination and are read as cytosines. The location of the methylated cytosines can then be determined by comparing treated and untreated sequences.
  • an agent that binds methylated DNA is attached (e.g., via a covalent or noncovalent bond) to a physical support (e.g., a bead, a magnetic bead, an agarose bead, or a magnetic epoxy bead), wherein the attaching can be prior to, during, or after incubation with a sample.
  • a physical support e.g., a bead, a magnetic bead, an agarose bead, or a magnetic epoxy bead
  • ER-negative cancer are provided in Table 1 which shows the chromosomal coordinates of each genomic locus and its observed log2(fold-change) (ER-positive/ER-negative).
  • the genomic loci are sorted based on their chromosomal coordinates which are based on human genome build hg19.
  • a person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 1 be assessed for H3K4me3 modification. Instead, a subset of loci may be assessed for H3K4me3 modification.
  • Subsets of the genomic loci of Table 1 can be selected (e.g., for use in determining ER status) based on various performance criteria, e.g., to select genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)). Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier. Those of skill in the art will
  • the present disclosure particularly includes, among other things, subsets of the genomic loci of Table 1, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher.
  • the present disclosure also includes subsets of the genomic loci of Table 1, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 1 (or any subset thereof) are differentially H3K4me3 modified as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least one (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) of the top 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 are H3K27ac modified as compared to a reference (e.g., a sample from an ER-negative or healthy subject) (wherein, e.g., the “top” 10 loci refers to the loci with 10 highest absolute log2(fold-change) in Table 2).
  • a reference e.g., a sample from an ER-negative or healthy subject
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 10 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95,
  • ER-positive e.g., ER-positive
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 25 loci identified in Table 2 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from an ER- negative or healthy subject).
  • a reference e.g., a sample from an ER- negative or healthy subject.
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 50 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at least 30, at least 35, at least 40, at least 45, or 50) identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least five of the top 25 loci identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least five of the top 50 loci identified in Table 2 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 2 (or any subset thereof) in total are H3K27ac modified as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • differentially H3K27ac modified refers to an acetylation status characterized by an increase or decrease in a value measuring acetylation (e.g., of read counts and/or normalized read counts for a given genomic locus), and/or a mean, median and/or
  • 12366150v1 Attorney Docket No.2014191-0027 mode thereof, and/or a log thereof (e.g., log base 2 (log2)), of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4- fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, 25-fold, 30-fold, 35-fold, 40- fold, 45-fold, 50-fold, or greater, or any range in between, inclusive, such as 1% to 50%, 50% to 2-fold, 25% to 50-fold, 25% to 30-fold, 25% to 20-fold, 25% to 16-fold, 30% to 16-fold, 50% to 16-fold, 70% to 16-fold, 2-fold to 16-fold, 2.2-fold to 16-fold, 2.6-fold to 16-fold, 3-fold to 16- fold, 3.4
  • an increase or decrease in a value measuring acetylation can be, or is expressed as, a log2(fold-change), e.g., a log2(fold-change) of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 75%, 100%, 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, 10-fold, 15-fold, 20-fold, or greater, or any range in between, inclusive, such as an increase or decrease of 0.1-fold to 10- fold, 0.2-fold to 5-fold, 0.2-fold to 4.0-fold, 0.4-4.0-fold, 0.4-fold to 4.0-fold, 0.6-fold to 4.0- fold, 0.8-fold to 4.0-fold, 1.0-fold to 4.0-fold.1.2-fold to 4.0-fold.1.4-fold to 4.0-fold, 1.6
  • Genomic loci demonstrating differential DNA methylation in ER-positive vs. ER- negative cancer are provided in Table 3, which shows the chromosomal coordinates of each genomic locus and its observed log2(fold-change) (ER-positive/ER-negative). The genomic loci are sorted based on their chromosomal coordinates which are based on human genome build hg19.
  • Table 3 shows the chromosomal coordinates of each genomic locus and its observed log2(fold-change) (ER-positive/ER-negative). The genomic loci are sorted based on their chromosomal coordinates which are based on human genome build hg19.
  • a person of skill in the art will recognize that the methods disclosed herein do not require that every genomic locus listed in Table 3 be assessed for DNA methylation. Instead, a subset of loci may be assessed for DNA methylation. Subsets of the genomic loci of Table 3 can be selected (e.g., for use in determining ER status) based on various performance criteria,
  • genomic loci that demonstrate differential modification with a particular level of statistical significance and/or a particular threshold of differential between relevant states (e.g., a measured log2(fold-change)).
  • Subsets of the genomic loci may also be selected based on an algorithm, e.g., during the process of obtaining a classifier.
  • Those of skill in the art will appreciate that such subsets of loci of Table 3, and loci included in such subsets, are together, individually, and/or in randomly selected subsets, at least as informative (e.g., as statistically significant and/or reliable) for uses disclosed herein, e.g., for determining ER status.
  • the present disclosure particularly includes, among other things, subsets of the genomic loci of Table 3, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 or higher, 5.0 or higher, 4.5 or higher, 4.0 or higher, 3.5 or higher, 3.0 or higher, 2.5 or higher, 2.0 or higher, 1.9 or higher, 1.8 or higher, 1.7 or higher, 1.6 or higher, 1.5 or higher, 1.4 or higher, 1.3 or higher, 1.2 or higher, 1.1 or higher, 1.0 or higher, 0.9 or higher, 0.8 or higher, 0.7 or higher, 0.6 or higher, or 0.5 or higher.
  • the present disclosure also includes subsets of the genomic loci of Table 3, which have an absolute log2(fold-change) of 6.0 or higher, 5.5 to less than 6.0, 5.0 to less than 5.5, 4.5 to less than 5.0, 4.0 to less than 4.5, 3.8 to less than 4.0, 3.6 to less than 3.8, 3.4 to less than 3.6, 3.2 to less than 3.4, 3.0 to less than 3.2, 2.8 to less than 3.0, 2.6 to less than 2.8, 2.4 to less than 2.6, 2.2 to less than 2.4, 2.0 to less than 2.2, 1.8 to less than 2.0, 1.6 to less than 1.8, 1.4 to less than 1.6, 1.2 to less than 1.4, 1.0 to less than 1.2, 0.8 to less than 1.0, or 0.6 to less than 0.8.
  • a sample or subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) are differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least a number of loci identified in a Table 3 (or any subset thereof) having a lower bound selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, or 300 and an upper bound selected from 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 is found to be
  • a sample or subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least a percent of loci identified in Table 3 having a lower bound selected from 0.1%, 0.2%, 0.3%, 0.4%, 0.5%, 1%, 2%, 3%, 4%, 5%, or 10%, and an upper bound selected from 1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 75%, or 100% is found to be differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least one (e.g., at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10) of the top 3, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject) (wherein, e.g., the “top” 10 loci refers to the loci with 10 highest absolute log2(fold- change) in Table 3).
  • a reference e.g., a sample from an ER-negative or healthy subject
  • a subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 10 loci identified in Table 3 is differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 25 loci identified in Table 3 is differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • 12366150v1 Attorney Docket No.2014191-0027 subject from which the sample is obtained or derived, is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 50 loci identified in Table 3 is differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least five of the top 10 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least five of the top 25 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a subject from which the sample is obtained or derived is determined to have a particular ER status (e.g., ER-positive) if at least five of the top 50 loci identified in Table 3 are differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 10 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or 10) identified in Table 3 and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) in total are differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER-positive) if at least one of the top 25 loci identified in Table 3 (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or 25) and at least 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 150, 200, 250, 300, 350, 400, 450, 500, 750, 1000, 1500, 2000, 2500, or 3000 loci identified in Table 3 (or any subset thereof) in total are differentially DNA methylated as compared to a reference (e.g., a sample from an ER-negative or healthy subject).
  • a reference e.g., a sample from an ER-negative or healthy subject.
  • a sample or subject from which the sample is derived is determined to have a particular ER status (e.g., ER- positive) if at least one of the top 50 loci (e.g., at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, or at least 10, at least 15, at least 20, or at least 25, at
  • Responsiveness can be measured quantitatively (e.g., as in the case of tumor size; as in the case of measurement of histone modification, chromatin accessibility, transcription factor binding, or DNA methylation at one or more genomic loci; or as in the calculation of clinical benefit (CBR)), or qualitatively (e.g., by measures such as “pathological complete response” (pCR), “clinical complete remission” (cCR), “clinical partial remission” (cPR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD), or other qualitative criteria).
  • CBR clinical benefit
  • kits and systems can be used to detect the clinical efficacy of a course of therapy for cancer, e.g., breast, ovarian, or endometrial cancer.
  • a course of therapy for cancer e.g., breast, ovarian, or endometrial cancer.
  • methods and/or compositions of the present disclosure could be used to determine the presence, absence, or ER status of a cancer in a subject over the course of treatment.
  • compositions of the present disclosure could be used in conjunction with, or confirmed by, other means of determining the presence, absence, or ER status of a cancer including, for example measurements of tumor size or character by techniques such as CT, PET, mammogram, ultrasound, palpation, histology, caliper measurement after biopsy or surgical resection, or by various qualitative, quantitative, or semi quantitative scoring systems including without limitation based on IHC or ISH testing, residual cancer burden (Symmans et al., J Clin Oncol (2007) 25:4414-4422, incorporated by reference herein in its entirety) or Miller-Payne score (Ogston et al., Breast (2003) 12:320-327, incorporated by reference herein in its entirety) in a qualitative fashion like “pathological complete response” (pCR), “clinical complete remission” (cCR), “clinical partial remission” (cPR), “clinical stable disease” (cSD), or “clinical progressive disease”
  • treatment efficacy can be monitored, e.g., by using a method described herein to determine a decrease or increase in disease state signal, which can be useful, e.g., for determining whether an administered therapy is effective and/or whether a change in therapy should be made.
  • a cancer has gone into remission for a subject (e.g., the subject has minimal residual disease).
  • methods, kits, and systems described herein can be useful, e.g., for detecting reoccurrence of
  • methods, kits and systems for ER status determination provided herein can inform treatment and/or payment (e.g., reimbursement for or reduction of cost of medical care, such as detecting or treatment) decisions and/or actions, e.g., by individuals, healthcare facilities, healthcare practitioners, health insurance providers, governmental bodies, or other parties interested in healthcare cost.
  • payment e.g., reimbursement for or reduction of cost of medical care, such as detecting or treatment
  • decisions and/or actions e.g., by individuals, healthcare facilities, healthcare practitioners, health insurance providers, governmental bodies, or other parties interested in healthcare cost.
  • methods, kits and systems for ER status determination can inform decision making relating to whether health insurance providers reimburse a healthcare cost payer or recipient (or not), e.g., for (1) ER status determination itself (e.g., reimbursement for detecting otherwise unavailable, available only for periodic/regular detecting, or available only for temporally- and/or incidentally- motivated detecting); and/or for (2) treatment, including initiating, maintaining, and/or altering therapy, e.g., based on the determined ER status.
  • ER status determination e.g., reimbursement for detecting otherwise unavailable, available only for periodic/regular detecting, or available only for temporally- and/or incidentally- motivated detecting
  • treatment including initiating, maintaining, and/or altering therapy, e.g., based on the determined ER status.
  • methods, kits and systems for ER status determination provided herein are used as the basis for, to contribute to, or support a determination as to whether a reimbursement or cost reduction will be provided to a healthcare cost payer or recipient.
  • a party seeking reimbursement or cost reduction can provide results of ER status determination conducted in accordance with the present disclosure together with a request for such reimbursement or reduction of a healthcare cost.
  • a party making a determination as to whether or not to provide a reimbursement or reduction of a healthcare cost will reach a determination based in whole or in part upon receipt and/or review of results of ER status determination conducted in accordance with the present disclosure.
  • ER status determination using methods, kits and systems disclosed herein can be used in classifying subjects, samples, and/or tumors (e.g., breast cancer subjects, samples, and/or tumors).
  • methods, kits and systems disclosed herein can be used to generate a set of subjects, samples, and/or tumors identified according to the present methods, kits and systems each classified as corresponding to a particular ER status, and optionally using two or more of such classified subjects, samples, and/or tumors to identify biomarkers that distinguish the classes (i.e., distinguish the subjects, samples, and/or tumors according to their class, e.g., according to their ER status).
  • one or more samples obtained from a subject are analyzed by a method comprising enriching for cfDNA comprising a particular histone modification, wherein enriching is performed by a method that comprises incubating the sample with a reagent that specifically binds the histone modification being enriched for, and sequencing the enriched cfDNA.
  • ChIP-seq for a histone modification (e.g., H3K4me3 and/or H3K27ac).
  • Sequence reads e.g., ChIP-seq sequence reads
  • BWA Burrows-Wheeler Aligner
  • Non-uniquely mapping and redundant reads are optionally discarded.
  • MACS v2.1.1.20140616 can be used for sequence (e.g., ChIP-seq) peak calling with a q-value (FDR) threshold of 0.01.
  • Sequence (e.g., ChIP-seq) data quality can optionally be evaluated by any of one or more of a variety of measures, including total peak number, FRiP (fraction of reads in peak) score, number of high- confidence peaks (e.g., enriched > ten-fold over background), and percent of peak overlap with “blacklist” DHS peaks derived from the ENCODE project (Amemiya et al., Sci Rep (2019) 9(1):9354). If the sequence (e.g., ChIP-seq) data quality is below a particular threshold, the data may be discarded and the assay repeated.
  • measures including total peak number, FRiP (fraction of reads in peak) score, number of high- confidence peaks (e.g., enriched > ten-fold over background), and percent of peak overlap with “blacklist” DHS peaks derived from the ENCODE project (Amemiya et al., Sci Rep (2019) 9(1):9354). If the sequence
  • Sequence e.g., ChIP-seq
  • selected genomic loci that are differentially modified as provided herein for the relevant histone modification Tables 1-2
  • the number of reads overlapping the selected genomic loci for the relevant histone modification can be summed, e.g., in some embodiments all the genomic loci that are differentially modified with an absolute log2(fold-change) ⁇ 4.0 are selected.
  • the average number of reads in the local background of each ChIP-seq peak is subtracted to improve signal to noise.
  • a sequence read density for one or more histone modifications can be calculated by a method that comprises (1) summing background adjusted sequence counts at at one or more genomic loci and dividing the resulting sum by the total number of kilobases of the one or more genomic loci, or (2) for each genomic loci, determining the ratio of background adjusted fragment counts to the number of kilobases of the genomic loci, and then summing the ratios for each loci.
  • a method comprises determining an ER-positive/ ER-negative ratio score, e.g., by a method that comprises (a) calculating an ER-positive sequence read
  • an ER- positive sequence read density can be determined by a method that comprises calculating sequence read density using one or more genomic loci with an increased level of one or more epigenetic biomarkers in sample(s) obtained from one or more subjects with an ER -positive cancer as compared to one or more sample(s) obtained from subjects with an ER-negative cancer.
  • an ER -negative sequence read density can be determined by a method that comprises calculating sequence read density using one or more genomic loci with an increased level of one or more epigenetic biomarkers in sample(s) obtained from one or more subjects with an ER-negative cancer as compared to one or more sample(s) obtained from subjects with an ER-positive cancer.
  • an ER-positive/ER-negative ratio score is determined for H3K4me3 modifications.
  • an ER-positive/ER-negative ratio score is determined for H3K27ac modifications.
  • an ER-positive/ER- negative ratio score is determined for methylated DNA.
  • an ER- positive/ER-negative ratio score is determined for H3K4me3 modifications and H3K27ac modifications, H3K4me3 and methylated DNA, or H3K27ac and methylated DNA. In some embodiments, an ER-positive/ER-negative ratio score is determined for each of H3K4me3 modifications, H3K27ac modifications, and methylated DNA. In some embodiments, two or more ER-positive/ER-negative ratio scores for different epigenetic biomarkers can be combined. In some embodiments, each ratio score can be combined using fitted values that have been determined using a logistic regression. [0218] The data can then be log2-transformed and quantile normalized to match the distribution of the data used to train a classifier.
  • Normalized data can be used as input into a classifier that was trained using the same histone modification(s) and selected genomic loci. The classifier can then use inputted data to determine ER status of a subject’s cancer. It will be appreciated that this or similar approaches can be applied to assays of the present disclosure that quantify chromatin accessibility, transcription factor binding and/or DNA methylation.
  • multiple epigenetic biomarkers e.g., one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation
  • H3K4me3 and H3K27ac histone modifications are quantified in a single sample.
  • kits and systems for ER status determination of the present disclosure are at least for in vitro use. Accordingly, all aspects and embodiments of the present disclosure can be performed and/or used at least in vitro.
  • methods of the present disclosure can be implemented on and/or in conjunction with a computer program and computer system. In some embodiments, methods of the present disclosure can be implemented on and/or in conjunction with a non-transitory computer readable storage medium encoded with the computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform the method.
  • a computer system comprises a database for storage of genomic locus modification status and/or accessibility status data. Such stored profiles can be accessed and used to perform comparisons of interest at a later point in time.
  • exemplary program structures and computer systems described herein other, alternative program structures and computer systems will be readily apparent to the skilled artisan.
  • Solutions can be formulated, e.g., using distilled water, physiological saline, or an isotonic solution containing glucose and other supplements such as D- sorbitol, D-mannose, D-mannitol, or sodium chloride as an aqueous solution for injection, optionally in combination with a suitable solubilizing agent, for example, an alcohol such as ethanol and/or a polyalcohol such as propylene glycol or polyethylene glycol, and/or a nonionic surfactant such as polysorbate 80TM or HCO-50, and the like.
  • a suitable solubilizing agent for example, an alcohol such as ethanol and/or a polyalcohol such as propylene glycol or polyethylene glycol, and/or a nonionic surfactant such as polysorbate 80TM or HCO-50, and the like.
  • Route of administration can be parenteral, for example, administration by injection.
  • Administration by injection can be by intravenous injection, intramuscular injection, intraperitoneal injection, subcutaneous injection.
  • Administration can be systemic or local.
  • a composition described herein can be therapeutically delivered to a subject by way of local administration.
  • local administration or “local delivery,” can refer to delivery that does not rely upon transport of the composition or therapeutic agent to its intended target tissue or site via the vascular system.
  • the composition may be delivered by injection or implantation of the composition or therapeutic agent or by injection or implantation of a device containing the composition or therapeutic agent.
  • subcutaneous administration can be accomplished by means of a device, such as a syringe, a prefilled syringe, an auto-injector (e.g., disposable or reusable), a pen injector, a patch injector, a wearable injector, an ambulatory syringe infusion pump with subcutaneous infusion sets, or other device for combining with a therapeutic agent for subcutaneous injection.
  • a device such as a syringe, a prefilled syringe, an auto-injector (e.g., disposable or reusable), a pen injector, a patch injector, a wearable injector, an ambulatory syringe infusion pump with subcutaneous infusion sets, or other device for combining with a therapeutic agent for subcutaneous injection.
  • An injection system of the present disclosure may employ a delivery pen as described in U.S. Pat. No.5,308,341.
  • Pen devices most commonly used for self-delivery of insulin to patients with diabetes, are well known in the art. Such devices can include at least one injection needle, are typically pre-filled with one or more therapeutic unit doses of a solution that includes the therapeutic agent and are useful for rapidly delivering solution to a subject with as little pain as possible.
  • One medication delivery pen includes a vial holder into which a vial of a therapeutic or other medication may be received.
  • the pen may be an entirely mechanical device or it may be combined with electronic circuitry to accurately set and/or indicate the dosage of medication that is injected into the user. See, e.g., U.S. Pat.
  • a composition can be formulated for storage at a temperature below 0°C (e.g., -20°C or -80°C).
  • the composition can be formulated for storage for up to 2 years (e.g., one month, two months, three months, four months, five months, six months, seven months, eight months, nine months, 10 months, 11 months, 1 year, or 2 years) at 2-8°C (e.g., 4°C).
  • compositions including certain therapeutic agents can be administered as a fixed dose, or in a milligram per kilogram (mg/kg) dose.
  • an exemplary single dose of certain pharmaceutical compositions described herein can include certain therapeutic agents as described herein in an amount equal to, e.g., 0.001 to 1000 mg/kg, 1-1000 mg/kg, 1-100 mg/kg, 0.5-50 mg/kg, 0.1-100 mg/kg, 0.5-25 mg/kg, 1-20 mg/kg, and 1-10 mg/kg body weight.
  • Exemplary dosages of a composition described herein include, without limitation, 0.1 mg/kg, 0.5 mg/kg, 1 mg/kg, 2 mg/kg, 4 mg/kg, 8 mg/kg, or 20 mg/kg. The present disclosure is not limited to such ranges or dosages.
  • the present disclosure further includes methods of preparing pharmaceutical compositions of the present disclosure and kits including pharmaceutical compositions of the present disclosure.
  • therapeutic agents of the present disclosure can be administered to a subject in a course of treatment that further includes administration of one or more additional therapeutic agents or therapies that are not therapeutic agents (e.g., surgery or radiation).
  • Combination therapies of the present disclosure can include simultaneous exposure of a subject to therapeutic agents of two or more therapeutic regimens.
  • a therapeutic agent as described herein can be administered together with (e.g., at the same time and/or in the same composition as) an additional agent or therapy.
  • a therapeutic agent of the present disclosure can be administered separately from an additional therapeutic agent or therapy (e.g., at a different time and/or in a different composition than the additional therapeutic agent or therapy). Dosing regimens of a therapeutic agent and one or more additional therapeutic agents with which it is administered in combination can be coordinated or independently determined. In various embodiments, an additional therapeutic agent or therapy administered in combination with a therapeutic agent as described herein can be administered at the same time as therapeutic agent, on the same day as therapeutic agent, or in the same week as therapeutic agent. In various embodiments, an additional therapeutic agent or therapy administered in combination with a therapeutic agent as described herein can be administered such that administration of the
  • the administration frequency and/or dosage of one or more additional therapeutic agents can be the same as, similar to, or different from the administration frequency of a therapeutic agent.
  • the two or more regimens can be administered simultaneously; in some embodiments, such regimens can be administered sequentially (e.g., all “doses” of a first regimen are administered prior to administration of any doses of a second regimen); in some embodiments, such therapeutic agents are administered in overlapping dosing regimens.
  • administration of a therapeutic agent can be to a subject having previously received, scheduled to receive, or in the course of a treatment regimen including an additional cancer therapy.
  • Administration of a therapeutic agent can, in some instances, improve delivery or efficacy of another therapeutic agent or therapy with which it is administered in combination.
  • therapeutic agent combination therapies can demonstrate synergy and/or greater-than-additive effects between a therapeutic agent and one or more additional therapeutic agents with which it is administered in combination.
  • a therapeutic agent can be administered in any effective amount as determined independently or as determined by the joint action of therapeutic agent and any of one or more additional therapeutic agents or therapies administered.
  • Administration of the therapeutic agent may, in some embodiments, reduce the therapeutically effective dosage, required dosage, or administered dosage of the additional therapeutic agent or therapy relative to a reference regimen for administration of additional therapeutic agent or therapy or therapy absent the therapeutic agent.
  • a composition described herein can replace or augment other previously or currently administered therapy.
  • administration of one or more additional therapeutic agents or therapies can cease or diminish, e.g., be administered at lower levels.
  • Kits of the present disclosure can include, e.g., reagents such as buffers and/or antibodies useful in the detection and quantification of histone modifications.
  • a kit of the present disclosure can include at least one antibody that selective binds a histone modification selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, or H3K4me3, or pan acetylation.
  • kits of the present disclosure can include at least one antibody that selective binds H3K4me3 modifications. In certain embodiments, a kit of the present disclosure can include at least one antibody that selective binds H3K27ac modifications.
  • a kit of the present disclosure can include instructional materials disclosing or describing the use of the kit in a method of determining ER status and/or treatment disclosed herein.
  • a kit of the present disclosure can include one or more therapeutic agents useful in the treatment of cancer, e.g., as disclosed herein, optionally in combination with instruction materials for treatment of cancer, e.g., breast cancer, ovarian cancer, or endometrial cancer based on ER status.
  • a kit of the present disclosure comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tabled 1-3.
  • the kit comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1.
  • the kit comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2.
  • the kit comprises one or more antibodies for use in ChIP-seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac-modified histones.
  • the kit comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3.
  • the kit comprises one or more methyl-binding domains for use in MBD-seq.
  • the kit comprises one or more antibodies that can bind methylated DNA (e.g., for use in MeDIP).
  • the kit comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample.
  • the kit comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample.
  • the kit comprises reagents for
  • the kit comprises reagents for sequencing. In some embodiments, the kit comprises instructions for determining if a subject has an ER-positive cancer.
  • the present disclosure includes systems for detecting modification and/or accessibility of one or more genomic loci. In some embodiments, the present disclosure provides systems for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci. Systems of the present disclosure can include a sequencer configured to generate a sequencing dataset from a sample; and a non-transitory computer readable storage medium and/or a computer system.
  • the non-transitory computer readable storage medium is encoded with a computer program, wherein the program comprises instructions that when executed by one or more processors cause the one or more processors to perform operations to perform a method of the present disclosure.
  • the computer system comprises a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform a method of the present disclosure.
  • the sequencer is configured to generate a Whole Genome Sequencing (WGS) dataset from the sample.
  • the system also includes a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample.
  • the sample preparation device may include reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample.
  • reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci in cell-free DNA (cfDNA) from the biological sample, optionally the liquid biopsy sample.
  • Systems of the present disclosure can include, e.g., reagents such as buffers and/or antibodies useful in the detection and quantification of histone modifications.
  • a system of the present disclosure can include at least one antibody that selective binds a histone modification selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, or H3K4me3, or pan acetylation.
  • a system of the present disclosure can include at least one antibody that selective binds a histone modification selected from H3K9ac, H3K14ac, H3K18ac, H3K23ac, H3K27ac, H3K4me1, H3K4me2, or H3K4me3, or pan acetylation.
  • a system of the present disclosure can include at least one antibody that selective binds H3K4me3 modifications.
  • a system of the present disclosure can include at least one antibody that selective binds H3K27ac modifications.
  • a system of the present disclosure can include instructional materials disclosing or describing the use of the system in a method of determining ER status and/or treatment disclosed herein.
  • a system of the present disclosure comprises reagents for quantifying one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation at one or more genomic loci, wherein the one or more genomic loci are selected from Tabled 1-3.
  • the system comprises reagents for quantifying H3K4me3 for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1.
  • the system comprises reagents for quantifying H3K27ac for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2.
  • the system comprises one or more antibodies for use in ChIP- seq, optionally wherein the one or more antibodies specifically bind H3K4me3- or H3K27ac- modified histones.
  • the system comprises reagents for quantifying DNA methylation for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3.
  • the system comprises one or more methyl-binding domains for use in MBD-seq.
  • the system comprises reagents for isolation of cell-free DNA (cfDNA) from a liquid biopsy sample.
  • the sequencer comprises reagents for library preparation for sequencing.
  • the sequencer comprises reagents for sequencing.
  • the system comprises instructions for determining if a subject has an ER-positive cancer.
  • the cloud computing environment 400 may include one or more resource providers 402a, 402b, 402c (collectively, 402). Each resource provider 402 may include computing resources. In some implementations, computing resources may include any hardware and/or
  • the resource manager 406 may be connected to the resource providers 402 and the computing devices 404 over the computer network 408. In some implementations, the resource manager 406 may facilitate the provision of computing resources by one or more resource providers 402 to one or more computing devices 404.
  • the resource manager 406 may receive a request for a computing resource from a particular computing device 404.
  • the resource manager 406 may identify one or more resource providers 402 capable of providing the computing resource requested by the computing device 404.
  • the resource manager 406 may select a resource provider 402 to provide the computing resource.
  • the resource manager 406 may facilitate a connection between the resource provider 402 and a particular computing device 404. In some implementations, the resource manager 406 may establish a connection between a particular resource provider 402 and a particular computing device 404.
  • Fig.5 shows an example of a computing device 500 and a mobile computing device 550 that can be used in the methods and systems described in this disclosure.
  • the computing device 500 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers.
  • the mobile computing device 550 is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart-phones, and other similar computing devices.
  • the components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to be limiting.
  • the processor 502 can process instructions for execution within the computing device 500, including instructions stored in the memory 504 or on the storage device 506 to display graphical information for a GUI on an external input/output device, such as a display 516 coupled to the high-speed interface 508.
  • multiple processors and/or multiple buses may be used, as appropriate, along with multiple memories and types of memory.
  • multiple computing devices may be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system).
  • multiple computing devices may be connected, with each device providing portions of the necessary operations (e.g., as a server bank, a group of blade servers, or a multi-processor system).
  • the memory 504 is a non-volatile memory unit or units.
  • the memory 504 may also be another form of computer-readable medium, such as a magnetic or optical disk.
  • the storage device 506 is capable of providing mass storage for the computing device 500.
  • the storage device 506 may be or contain a computer- readable medium, such as a hard disk device, an optical disk device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. Instructions can be stored in an information carrier.
  • the high-speed interface 508 manages bandwidth-intensive operations for the computing device 500, while the low-speed interface 512 manages lower bandwidth-intensive operations. Such allocation of functions is an example only.
  • the high- speed interface 508 is coupled to the memory 504, the display 516 (e.g., through a graphics processor or accelerator), and to the high-speed expansion ports 510, which may accept various expansion cards (not shown).
  • the low-speed interface 512 is coupled to the storage device 506 and the low-speed expansion port 514.
  • the low-speed expansion port 514 which may include various communication ports (e.g., USB, Bluetooth®, Ethernet, wireless Ethernet) may be coupled to one or more input/output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.
  • the computing device 500 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a standard server 520, or multiple times in a group of such servers. In addition, it may be implemented in a personal computer such as a laptop computer 522. It may also be implemented as part of a rack server system 524. Alternatively, components from the computing device 500 may be combined with other components in a mobile device (not shown), such as a mobile computing device 550. Each of such devices may contain one or more of the computing device 500 and the mobile computing device 550, and an entire system may be made up of multiple computing devices communicating with each other.
  • the mobile computing device 550 includes a processor 552, a memory 564, an input/output device such as a display 554, a communication interface 566, and a transceiver 568, among other components.
  • the mobile computing device 550 may also be provided with a storage device, such as a micro-drive or other device, to provide additional storage.
  • a storage device such as a micro-drive or other device, to provide additional storage.
  • Each of the processor 552, the memory 564, the display 554, the communication interface 566, and the transceiver 568 are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.
  • the processor 552 can execute instructions within the mobile computing device 550, including instructions stored in the memory 564.
  • the processor 552 may be implemented as a chipset of chips that include separate and multiple analog and digital processors.
  • the processor 552 may provide, for example, for coordination of the other components of the mobile computing device 550, such as control of user interfaces, applications run by the mobile computing device 550, and wireless communication by the mobile computing device 550.
  • the processor 552 may communicate with a user through a control interface 558 and a display interface 556 coupled to the display 554.
  • the display 554 may be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology.
  • the display interface 556 may comprise appropriate circuitry for driving the display 554 to present graphical and other information to a user.
  • the control interface 558 may receive commands from a user and convert them for submission to the processor 552.
  • an external interface 562 may provide communication with the processor 552, so as to enable near area communication of the mobile computing device 550 with other devices.
  • the external interface 562 may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.
  • the expansion memory 574 may be provided as a security module for the mobile computing device 550, and may be programmed with instructions that permit secure use of the mobile computing device 550.
  • secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non- hackable manner.
  • the memory may include, for example, flash memory and/or NVRAM memory (non-volatile random access memory), as discussed below.
  • instructions are stored in an information carrier and, when executed by one or more processing devices (for example, processor 552), perform one or more methods, such as those described above.
  • the instructions can also be stored by one or more storage devices, such as one or more computer- or machine-readable mediums (for example, the memory 564, the expansion memory 574, or memory on the processor 552).
  • the instructions can be received in a propagated signal, for example, over the transceiver 568 or the external interface 562.
  • the mobile computing device 550 may communicate wirelessly through the communication interface 566, which may include digital signal processing circuitry where necessary.
  • the communication interface 566 may provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular), WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General Packet Radio Service), among others.
  • GSM voice calls Global System for Mobile communications
  • SMS Short Message Service
  • EMS Enhanced Messaging Service
  • MMS messaging Multimedia Messaging Service
  • CDMA code division multiple access
  • TDMA time division multiple access
  • PDC Personal Digital Cellular
  • WCDMA Wideband Code Division Multiple Access
  • CDMA2000 Code Division Multiple Access
  • GPRS General Packet Radio Service
  • a GPS (Global Positioning System) receiver module 570 may provide additional navigation- and location-related wireless data to the mobile computing device 550, which may be used as appropriate by applications running on the mobile computing device 550.
  • the mobile computing device 550 may also communicate audibly using an audio codec 560, which may receive spoken information from a user and convert it to usable digital information.
  • the audio codec 560 may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device 550.
  • Such sound may include sound from voice telephone calls, may include recorded sound (e.g., voice messages, music files, etc.) and may also include sound generated by applications operating on the mobile computing device 550.
  • the mobile computing device 550 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a cellular telephone 580. It
  • 12366150v1 Attorney Docket No.2014191-0027 may also be implemented as part of a smart-phone 582, personal digital assistant, or other similar mobile device.
  • Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
  • machine-readable medium and computer- readable medium refer to any computer program product, apparatus and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal.
  • machine-readable signal refers to any signal used to provide machine instructions and/or data to a programmable processor.
  • Systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact
  • a back end component e.g., as a data server
  • a middleware component e.g., an application server
  • a front end component e.g., a client computer having a graphical user interface or a Web browser through which a user can interact
  • a machine learning module refers to a computer implemented process (e.g., a software function) that implements one or more specific machine learning techniques, e.g., artificial neural networks (ANNs), e.g., convolutional neural networks (CNNs), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values.
  • ANNs artificial neural networks
  • CNNs convolutional neural networks
  • RNNs convolutional neural networks
  • a machine learning module is trained, e.g., to accomplish a specific task such as identifying certain response strings, values of determined parameters are fixed and the (e.g., unchanging, static) machine learning module is used to process new data (e.g., different from the training data) and accomplish its trained task without further updates to its parameters (e.g., the machine learning module does not receive feedback and/or updates).
  • available input data includes training data and validation data, e.g., where
  • training data is used during the training process to optimize a model, whereas validation data is used to check the accuracy of the model while operating on previously unseen data.
  • training data is divided into batches (e.g., portions) that is sequentially used (e.g., in random order) as sets of inputs to train a model.
  • a model is trained multiple times (e.g., epochs) on the entire set of training data.
  • machine learning modules may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, to dynamically update the machine learning module.
  • two or more machine learning modules may be combined and implemented as a single module and/or a single software application.
  • two or more machine learning modules may also be implemented separately, e.g., as separate software applications.
  • a machine learning module may be software and/or hardware.
  • a machine learning module may be implemented entirely as software, or certain functions of a ANN module may be carried out via specialized hardware (e.g., via an application specific integrated circuit (ASIC) and/or field programmable gate arrays (FPGAs)).
  • ASIC application specific integrated circuit
  • FPGAs field programmable gate arrays
  • machine learning modules implementing machine learning techniques may be composed of individual nodes (e.g. units, neurons).
  • a node may receive a set of inputs that may include at least a portion of a given input data for the machine learning module and/or at least one output of another node.
  • a node may have at least one parameter to apply and/or a set of instructions to perform (e.g., mathematical functions to execute) over the set of inputs.
  • node instructions may include a step to provide various relative importance to the set of inputs using various parameters, such as weights.
  • Non-limiting examples of the activation function include Rectified Linear Activation (ReLu), logistic (e.g., sigmoid), hyperbolic tangent (tanh), and softmax.
  • a node may have a capability of remembering previous states
  • the machine learning module comprises a deep learning architecture composed of nodes organized into layers.
  • a layer is a set of nodes that receives data input (e.g., weighted or non-weighted input), transforms it (e.g., by carrying out instructions, e.g., applying a set of functions e.g., linear and/or non-linear functions), and passes transformed values as output (e.g., to the next layer).
  • a machine learning module may be composed of at least one layer (e.g., ordered).
  • layers e.g., ordered
  • types of layers include convolutional layers (e.g., layers with a kernel, a matrix of parameters that is slid across an input to be multiplied with multiple input values to reduce them to a single output value); fully connected (FC) layers (e.g.
  • the performance of a machine learning module may be characterized by its ability to produce an output data with specific accuracy.
  • a training process is performed to find optimal parameters, such as weights, for each node in each layer of the machine learning module.
  • the training process of a machine learning module may involve using output data to calculate an objective function (e.g., cost function, loss function, error function) that needs to be optimized (e.g., minimized, maximized).
  • an objective function e.g., cost function, loss function, error function
  • a machine learning objective function may be a combination of a loss function and regularization parameter. The loss function is related to how well the output is able to predict the input.
  • objective function optimization of a machine learning module may involve finding at least one (e.g., all) of the present global optima (e.g., as opposed to local optima).
  • algorithm for objective function optimization follows principles of mathematical optimization for a multi-variable function and relies on achieving specific accuracy of the process.
  • Methods disclosed herein may utilize one or more machine-learned models as a classifier.
  • a machine-learned model may be or include an artificial neural network.
  • a machine- learned model may employ, for example, an attention-based model (e.g., a transformer model, such as, for example, a vision transformer), a transformer model (e.g., a vision transformer), a regression-based model (e.g., a logistic regression model), a regularization-based model (e.g., an elastic net model or a ridge regression model), an instance-based model (e.g., a support vector machine or a k-nearest neighbor model), a Bayesian-based model (e.g., a naive-based model or a Gaussian naive-based model), a clustering-based model (e.g., an expectation maximization model), an ensemble-based model (e.g., an adaptive boosting model, a random forest model, a bootstrap-aggregation model, or a gradient boosting machine model), or a neural-network-based model (e.g., a convolutional neural network, a recurrent neural network,
  • a machine-learned model used as a classifier is or is derived from a decision tree methodology, a neural boosted methodology, a bootstrap forest methodology, a boosted tree methodology, a k nearest neighbors methodology, a generalized regression forward selection methodology, a generalized regression pruned forward selection methodology, a fit stepwise methodology, a generalized regression lasso methodology, a generalized regression elastic net methodology, a generalized regression ridge methodology, a nominal logistic methodology, a support vector machines methodology, a discriminant methodology, a na ⁇ ve Bayes methodology, or a combination thereof.
  • a machine-learned model is or is derived from a decision tree methodology, a neural boosted methodology, a bootstrap forest methodology, a boosted tree methodology, a k nearest neighbors methodology, a generalized regression forward selection methodology, a generalized regression pruned forward selection methodology, a fit stepwise methodology, a generalized regression lasso methodology, a generalized regression elastic net methodology, a generalized regression ridge methodology, a nominal
  • a machine-learned model is or is derived from a decision tree methodology, a neural boosted methodology, a bootstrap forest methodology, a boosted tree methodology, a support vector machines methodology, or a combination thereof.
  • the term “about” can encompass a range of values that within 25%, 20%, 19%, 18%, 17%, 16%, 15%, 14%, 13%, 12%, 11%, 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, or within a fraction of a percent, of the referenced value.
  • “Accessibility Status” or “Chromatin Accessibility Status” As used herein, “accessibility status” or “chromatin accessibility status” of a genomic locus refers to the frequency with which DNA sequences corresponding to the genomic locus are identified in an assay for detection of accessible chromatin.
  • Antibody refers to a polypeptide that includes one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen (e.g., a heavy chain variable domain, a light chain variable domain, and/or one or more CDRs).
  • a particular antigen e.g., a heavy chain variable domain, a light chain variable domain, and/or one or more CDRs.
  • the term antibody includes, without limitation, human antibodies, non-human antibodies, synthetic and/or engineered antibodies, fragments thereof, and agents including the same.
  • Antibodies can be naturally occurring immunoglobulins (e.g., generated by an organism reacting to an antigen). Synthetic, non-naturally occurring, or engineered antibodies can be produced by recombinant engineering, chemical synthesis, or other artificial systems or methodologies known to those of skill in the art.
  • antibody can include (unless otherwise stated or clear from context) any art-known constructs or formats utilizing antibody structural and/or functional features including without limitation intrabodies, domain antibodies, antibody mimetics, Zybodies®, Fab fragments, Fab’ fragments, F(ab’)2 fragments, Fd’ fragments, Fd fragments, isolated CDRs or sets thereof, single chain antibodies, single-chain Fvs (scFvs), disulfide-linked Fvs (sdFv), polypeptide-Fc fusions, single domain antibodies (e.g., shark single domain antibodies such as IgNAR or fragments thereof), cameloid antibodies, camelized antibodies, masked antibodies (e.g., Probodies®), affybodies, anti-idiotypic (anti-Id) antibodies (including, e.g., anti-anti-Id antibodies), Small Modular ImmunoPharmaceuticals (SMIPs), single chain or Tandem diabodies (TandAb®), VHHs
  • SMIPs single
  • an antibody includes one or more structural elements recognized by those skilled in the art as a complementarity determining region (CDR) or variable domain.
  • CDR complementarity determining region
  • an antibody can be a covalently modified (“conjugated”) antibody (e.g., an antibody that includes a polypeptide including one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen, where the polypeptide is covalently linked with one or more of a therapeutic agent, a detectable moiety, another polypeptide, a glycan, or a polyethylene glycol molecule).
  • conjugated antibody e.g., an antibody that includes a polypeptide including one or more canonical immunoglobulin sequence elements sufficient to confer specific binding to a particular antigen, where the polypeptide is covalently linked with one or more of a therapeutic agent, a detectable moiety, another polypeptide, a glycan, or a polyethylene glycol molecule.
  • antibody sequence elements are humanized, primatized, chimeric, etc., as is known in the art.
  • An antibody including a heavy chain constant domain can be, without limitation, an antibody of any known class, including but not limited to, IgA, secretory IgA, IgG, IgE and IgM, based on heavy chain constant domain amino acid sequence (e.g., alpha ( ⁇ ), delta ( ⁇ ), epsilon ( ⁇ ), gamma ( ⁇ ) and mu ( ⁇ )).
  • IgG subclasses are also well known to those in the art and include but are not limited to human IgG1, IgG2, IgG3 and IgG4.
  • “Isotype” refers to the Ab class or subclass (e.g., IgM or IgG1) that is encoded by the heavy chain constant region genes.
  • a “light chain” can be of a distinct type, e.g., kappa ( ⁇ ) or lambda ( ⁇ ), based on the amino acid sequence of the light chain constant domain.
  • an antibody has constant region sequences that are characteristic of mouse, rabbit, primate, or human immunoglobulins. Naturally produced immunoglobulins are glycosylated, typically on the CH2 domain. As is known in the art, affinity and/or other binding attributes of Fc regions for Fc receptors can be modulated through glycosylation or other modification.
  • an antibody may lack a covalent modification (e.g., attachment of a glycan) that it would have if produced naturally.
  • a pan antibody is a pan-acetylation antibody (e.g., an antibody that can bind a histone, e.g., H3 that comprises at least one acetylated lysine, wherein the at least one acetylated lysine can be at any one of a plurality of amino acid positions, e.g., a pan-acetylation antibody can bind an H3 protein comprising an acetylated lysine at any position).
  • a pan antibody can bind one or more histone modifications that are associated with transcription activation.
  • a pan antibody can bind one or more histone modifications that are associated with transcription silencing.
  • an “antibody fragment” refers to a portion of an antibody or antibody agent as described herein, and typically refers to a portion that includes an antigen-binding portion or variable region thereof.
  • An antibody fragment can be produced by any means. For example, in some embodiments, an antibody fragment can be enzymatically or chemically produced by fragmentation of an intact antibody or antibody agent. Alternatively, in some embodiments, an antibody fragment can be recombinantly produced, i.e., by expression of an engineered nucleic acid sequence. In some embodiments, an antibody fragment can be wholly or partially synthetically produced.
  • two or more entities that are physically associated with one another are covalently linked to one another; in some embodiments, two or more entities that are physically associated with one another are not covalently linked to one another but are non- covalently associated, for example by means of hydrogen bonds, van der Waals interaction, hydrophobic interactions, magnetism, or a combination thereof.
  • Between or “From” As used herein, the term “between” refers to content that falls between indicated upper and lower, or first and second, boundaries, inclusive of the boundaries. Similarly, the term “from”, when used in the context of a range of values, indicates that the range includes content that falls between indicated upper and lower, or first and second, boundaries, inclusive of the boundaries.
  • biological sample typically refers to a sample obtained or derived from a biological source (e.g., a tissue or organism or cell) of interest, as described herein.
  • a biological source is or includes an organism, such as a human subject.
  • a biological sample is or includes a biological tissue or fluid.
  • a biological sample can be or include cells, tissue, or bodily fluid.
  • a biological sample is or includes DNA obtained from a single subject or from a plurality of subjects.
  • a biological sample can be a “primary sample” obtained directly from a biological source or can be a “processed sample”, i.e., a sample that was derived from a primary sample, e.g., via dilution, purification, mixing with one or more reagents, or any other processing step(s) as described herein.
  • diagnosing includes the act, process, and/or outcome of determining whether, and/or the qualitative of quantitative probability that, a subject has or will develop the condition, disease, or related state.
  • diagnosing can include a determination relating to
  • Differentially accessible describes a genomic locus for which chromatin accessibility status differs between a first condition or sample and a second condition or sample (e.g., a standard or reference).
  • a differentially accessible genomic locus can include a greater or smaller measured accessibility under a selected condition of interest, such as ER-positive state, as compared to a reference state, such as ER-negative state.
  • chromatin accessibility and/or transcription factor binding can be used as a measure of epigenetic modifications at a given locus.
  • the term “epigenetic marker” refers to an indicator of epigenetic state, and includes, e.g., epigenetic modifications (e.g., histone modifications and DNA methylation, transcription factor biding, chromatin accessibility.
  • the term “epigenetic biomarker” refers to an epigenetic marker that can be used in the detection of a disease or condition.
  • identity refers to the overall relatedness between polymeric molecules, e.g., between nucleic acid molecules (e.g., DNA molecules) and/or between polypeptide molecules. Methods for the calculation of a percent identity as between two provided sequences are known in the art.
  • % sequence identity refers to a relationship between two or more sequences, as determined by comparing the sequences. In the art, “identity” also means the degree of sequence relatedness between protein and nucleic acid sequences as determined by the match between strings of such sequences.
  • the percent identity between the two sequences is a function of the number of identical positions shared by the sequences, optionally accounting for the number of gaps, and the length of each gap, which may need to be introduced for optimal alignment of the two sequences.
  • the comparison of sequences and determination of percent identity between two sequences can be accomplished using a computational algorithm, such as BLAST (basic local alignment search tool). Sequence alignments and percent identity calculations may be performed using the Megalign program of the LASERGENE bioinformatics computing suite (DNASTAR, Inc., Madison, Wisconsin). Multiple alignment of the sequences
  • GCG Genetics Computer Group
  • BLASTP BLASTN
  • BLASTX Altschul et al., J Mol Biol (1990) 215:403-410
  • DNASTAR DNASTAR, Inc., Madison, Wisconsin
  • FASTA program incorporating the Smith-Waterman algorithm (Pearson, Comput Methods Genome Res [Proc Int Symp] (1994), Meeting Date 1992, 111-120. Eds. Suhai, Sandor. Plenum, New York, NY (the contents of each of which is separately incorporated herein by reference in its entirety).
  • a regulatory sequence can control or impact one or more aspects of gene expression (e.g., cell- type-specific expression, inducible expression, etc.).
  • subject refers to an organism, typically a mammal (e.g., a human).
  • a subject is suffering from a disease, disorder or condition (e.g., ER-positive cancer, e.g., ER-positive breast cancer, etc.).
  • a subject is susceptible to a disease, disorder, or condition.
  • a subject displays one or more symptoms or characteristics of a disease, disorder or condition.
  • a subject is not suffering from a disease, disorder or condition.
  • a subject does not display any symptom or characteristic of a disease, disorder, or condition.
  • a subject has one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition.
  • a subject is a subject that has been tested for a disease, disorder, or condition, and/or to whom therapy has been administered.
  • a human subject can be interchangeably referred to as a “patient” or “individual”.
  • therapeutic agent refers to any agent that elicits a desired pharmacological effect when administered to a subject.
  • an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population.
  • the appropriate population can be a population of model organisms or a human population.
  • an appropriate population can be defined by various criteria, such as a certain age group, gender, genetic background, preexisting clinical conditions, etc.
  • a therapeutic agent is a substance that can be used for treatment of a disease, disorder, or condition (e.g., ER-positive cancer, e.g., ER-positive breast cancer, etc.).
  • a therapeutic agent is an agent that has been or is required to be approved by a government agency before it can be marketed for administration to humans.
  • a therapeutic agent is an agent for which a medical prescription is required for administration to humans.
  • Therapeutically effective amount refers to an amount that produces the desired effect for which it is administered.
  • the term refers to an amount that is sufficient, when administered to a population suffering from or susceptible to a disease, disorder, and/or condition (e.g., ER- positive cancer, e.g., ER-positive breast cancer, etc.) in accordance with a therapeutic dosing regimen, to treat the disease, disorder, and/or condition.
  • a therapeutically effective amount is one that reduces the incidence and/or severity of, and/or delays onset of, one or more symptoms of the disease, disorder, and/or condition.
  • a therapeutically effective amount does not in fact require successful treatment be achieved in a particular individual.
  • a therapeutically effective amount may be that amount that provides a particular desired pharmacological response in a significant number of subjects when administered to patients in need of such treatment.
  • reference to a therapeutically effective amount may be a reference to an amount as measured in one or more specific tissues (e.g., a tissue affected by the disease, disorder or condition) or fluids (e.g., blood, saliva, serum, sweat, tears, urine, etc.).
  • tissue e.g., a tissue affected by the disease, disorder or condition
  • fluids e.g., blood, saliva, serum, sweat, tears, urine, etc.
  • a therapeutically effective amount of a particular agent or therapy may be formulated and/or administered in a single dose.
  • a therapeutically effective amount of a particular agent or therapy may be formulated and/or administered in a plurality of doses, for example, as part of a dosing regimen.
  • treatment refers to administration of a therapy that partially or completely alleviates, ameliorates, relieves, inhibits, delays onset of, reduces severity of, and/or reduces incidence of one or more symptoms, features, and/or causes of a particular disease, disorder, or condition, or is administered for the purpose of achieving any such result.
  • a “prophylactic treatment” includes a treatment administered to a subject who does not display signs or symptoms of a condition to be treated or displays only early signs or symptoms of the condition to be treated such that treatment is administered for the purpose of diminishing, preventing, or decreasing the risk of developing the condition. Thus, a prophylactic treatment functions as a preventative treatment against a condition.
  • a “therapeutic treatment” includes a treatment administered to a subject who displays symptoms or signs of a condition and is administered to the subject for the purpose of reducing the severity or progression of the condition.
  • the histone modification assay is selected from ChIP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing. 6.
  • chromatin accessibility is quantified using a chromatin accessibility assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing), NOMe-seq (Nucleosome Occupancy and Methylome sequencing), FAIRE-seq (Formaldehyde-Assisted Isolation of Regulatory Elements sequencing), MNase-seq (Micrococcal Nuclease digestion with sequencing), and a DNase hypersensitivity assay. 7.
  • ATAC-seq Assay of Transpose Accessible Chromatin sequencing
  • NOMe-seq Nucleosome Occupancy and Methylome sequencing
  • FAIRE-seq Formmaldehyde-Assisted Isolation of Regulatory Elements sequencing
  • MNase-seq Merococcal Nuclease digestion with sequencing
  • DNase hypersensitivity assay selected from ATAC-seq (Assay of Transpose Accessible Chromatin sequencing)
  • NOMe-seq Nucle
  • any one of embodiments 1-6 wherein the binding of one or more transcription factors is quantified using a transcription factor binding assay that detects binding of one or more of p300, mediator complex, cohesin complex, RNA pol II, FOXA1, ESR1, PR, MYC, EN1, FOXM1, KLF4, AP-2, RARa, or RUNX1.
  • the transcription factor binding assay is selected from ChIP-seq (Chromatin ImmunoPrecipitation sequencing), CUT&RUN (Cleavage Under Targets and Release Using Nuclease) sequencing, and CUT&Tag (Cleavage Under Targets and Tagmentation) sequencing.
  • the method of embodiment 14, comprising quantifying H3K4me3 modifications, H3K27ac modifications and DNA methylation.
  • the liquid biopsy sample is a plasma sample, serum sample, or urine sample.
  • the method comprises isolating DNA (e.g., cfDNA) from 1, 2, 3, 4, or 5 mL of the liquid biopsy sample (e.g., plasma sample). 18.
  • the cfDNA comprising H3K4me3 modifications is enriched using a method that comprises incubating the sample with an agent (e.g., an antibody) that binds H3K4me3 modifications;
  • the cfDNA comprising H3K27ac modifications is enriched using a method that comprises incubating the sample with an agent (e.g., an antibody) that binds H3K27ac modifications; and/or
  • methylated cfDNA is enriched using a method that comprises incubating the sample with an agent (e.g., an antibody or a methyl binding domain) that binds methylated DNA.
  • the method comprises incubating with two or more of the agent that binds H3K4 modifications, the agent that binds H3K27ac modifications, and the agent that binds methylated DNA, the sample is incubated with the two or more agents (a) in sequence, or (b) in parallel (e.g., wherein the sample is divided into fractions and each fraction is incubated with a different agent). 22. The method of any one of embodiments 18-21, wherein the sequencing is performed using a next generation sequencing method. 23.
  • the method comprises attaching (e.g., ligating) adapters to cfDNA obtained from the subject (e.g., attaching after cfDNA has been enriched for cfDNA comprising one or more H3K4me3 modifications, cfDNA comprising one or more H3K27ac modifications, and/or methylated cfDNA).
  • attaching e.g., ligating
  • the method comprises amplifying the plurality of converted DNA fragments after attaching adapters to the plurality of DNA fragments.
  • mapping sequence reads to a reference genome e.g., mapping sequence reads to a reference genome.
  • 12366150v1 Attorney Docket No.2014191-0027 wherein a sequence read peak corresponds to a region of the genome that has a higher number of sequence reads that the local background.
  • 28. The method of embodiment 27, wherein peaks in high noise regions are removed and/or where peaks in regions that having increased levels of one or more epigenetic markers in white blood cells are removed.
  • 29. The method of embodiments 27 or 28, wherein peaks in regions likely to be artifactual are removed.
  • 30 The method of any one of embodiments 27-29, wherein peaks that are less than 50 bp in length are removed. 31.
  • the method of any one of embodiments 18-30, wherein quantifying H3K4me3 modifications, H3K27ac modifications, and/or DNA methylation comprises summing the number of sequence reads having at least one nucleotide overlap the one or more genomic loci.
  • sequence reads are adjusting on the basis of sequencing depth (e.g., quantile normalizing sequence reads to a common reference distribution) and/or ChIP quality prior to summing.
  • sequence counts are normalized to aggregate counts in a given sample across a set of regions (e.g., 10,000 regions) previously determined to have DNAse hypersensitivity in most cell types. 34.
  • sequence read density is calculated by: (a) summing background adjusted sequence counts at each of the one or more genomic loci and dividing by the sum of the kilobases of the one or more genomic loci; or (b) for each genomic loci, dividing background adjusted fragment count by the number of kilobases of the genomic loci, and then summing for each loci. 38.
  • the one or more genomic loci include one or more genomic loci with an increased level of the one or more epigenetic biomarkers in (a) sample(s) obtained from a subject with an ER-positive cancer as compared to a sample obtained from a subject with an ER-negative cancer, and/or (b) sample(s) obtained from a subject with an ER-negative cancer as compared to a sample obtained from a subject with an ER-positive cancer. 39.
  • the method of embodiment 38 comprising calculating an ER-positive/ER-negative ratio score, by a method comprising: (a) calculating an ER-positive sequence read density by a method comprising summing background adjusted sequence counts at each of the one or more genomic loci with an increased level of one or more epigenetic biomarkers in sample(s) obtained from subjects with an ER-positive cancer as compared to samples obtained from subjects with ER-negative cancer; (b) calculating an ER-negative sequence read density by a method comprising summing background adjusted sequence counts at each of the one or more genomic loci with an increased level of the one or more epigenetic biomarkers in sample(s) obtained from subjects with an ER-negative cancer as compared to samples obtained from subjects with an ER-positive cancer; and (c) dividing the ER-positive sequence read density by the ER-negative sequence read density.
  • a system for determining the ER status of a cancer in a subject comprising a sequencer configured to generate a sequencing dataset from a sample; and a non-transitory computer readable storage medium of embodiment 79 and/or a computer system of embodiment 80.
  • WGS Whole Genome Sequencing
  • the system of embodiment 81 or 82 further comprising a sample preparation device configured to prepare the sample for sequencing from a biological sample, optionally a liquid biopsy sample.
  • the device comprises reagents for quantifying: (a) H3K4me3, e.g., for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 1; (b) H3K27ac, e.g., for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 2; (c) DNA methylation, e.g., for at least 5, 10, 20, 30, 40, or 50 genomic loci in Table 3; or (d) any combination of (a)-(c).
  • a method of determining the ER status of a cancer in a subject comprising: receiving (e.g., by a processor of a computing device) one or more genomic profiles of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation for the subject; and determining whether the subject has an epigenetic profile indicative of an ER-positive cancer by classifying (e.g., by the processor) the genomic profile using the ER classifier.
  • receiving e.g., by a processor of a computing device
  • one or more genomic profiles of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation for the subject e.g., by a processor of a computing device
  • the method comprising: receiving (e.g., by a processor of a computing device) one or more genomic profiles of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation for the subject; and determining whether
  • the one or more genomic profiles used to train the ER classifier comprise one or more genomic profiles generated by in silico diluting sequence data from ER-positive or ER-negative cell lines with sequence data obtained from healthy donor plasma samples so as to achieve a simulated ctDNA percentage ranging from 0.5% to 50%.
  • the method of embodiment 95 wherein the differential loci were identified by comparing genomic profiles of one or more histone modifications and/or DNA methylation in (i) one or more ER-positive cell lines and (ii) one or more ER-negative cell lines.
  • 97 The method of embodiment 95 or 96, wherein the ER classifier has been trained on the levels of one or more histone modifications, chromatin accessibility, binding of one or more transcription factors, and/or DNA methylation in the differential loci for the genomic profiles that were generated by in silico diluting sequence data from one or more ER-positive cell lines and sequence data obtained from liquid biopsy samples of healthy subjects.
  • ER classifier has been validated by selecting a threshold such that the validated classifier predicts ER-positive cancers with an area under the receiver operating characteristic (AUROC) greater than 0.5 (e.g., greater than 0.55, greater than 0.6, greater than 0.65, greater than 0.7, greater than 0.75, greater than 0.8, greater than 0.85, greater than 0.9, or greater than 0.95).
  • AUROC receiver operating characteristic
  • a computer system comprising a memory and one or more processors coupled to the memory, wherein the one or more processors are configured to perform operations to perform the method of any one of embodiments 92-110.
  • 113. A method of treating a subject having a cancer, the method comprising: administering an ER-targeted agent to the subject, wherein the subject has been determined to have a validated epigenetic profile indicative of an ER-positive cancer based on analysis of a biological sample, optionally of cell-free DNA (cfDNA) from a liquid biopsy sample, obtained or derived from the subject, wherein the presence of the validated epigenetic profile has been determined using a classifier (e.g., a validated classifier) according to a method of any one of embodiments 92-110.
  • a classifier e.g., a validated classifier
  • ER-positive cell lines ZR751, ZR7530, BT483, T47D, BT474, CAMA1, MCF7, HCC1428, and HCC1500.
  • ER-negative cell lines were used: BT549, DU4475, HS578T, BT20, UACC893, HCC38, HCC70, HCC202, HCC1143, HCC1187, HCC1419, HCC1599, HCC1806, HCC1954, HCC2157, HCC2218, and SKBR3.
  • Plasma samples were prepared from whole blood collected in EDTA blood collection tubes or Streck cell-free DNA BCT with 4-6 hours of collection and plasma was stored at -80 ⁇ C until use.
  • Whole blood was obtained from breast cancer patients under a protocol approved by an IRB. Breast cancer patients had previously been determined to be ER-positive or ER-negative. Informed content was obtained in each case and samples were de-identified.
  • Chromatin immunoprecipitation ChIP
  • Chromatin immunoprecipitation (ChIP) for histone marks (H3K4me3 and H3K27ac) in cell lines was performed using methods similar to those previously described in Schones et al., Cell (2008) 132(5):887-898, which is incorporated by reference herein in its entirety. Briefly, the cells were lysed and the chromatin was MNase digested to generate approximately 80% mononucleosomes. Nucleosomes were then incubated with antibodies that bind H3K4me3 modifications or H3K27ac modifications that were previously conjugated to magnetic epoxy beads (Invitrogen) with constant mild shaking overnight. The beads were then washed and rinsed.
  • ChIP-seq and DNA methylation data analysis [0329] ChIP-sequencing reads and MeDIP-sequencing reads were aligned to the human genome build hg19 using the Burrows-Wheeler Aligner (BWA) version 0.7.15. Non-uniquely mapping and redundant reads were discarded. MACS v2.2.7.1 was used for peak calling with a q- value (FDR) threshold of 0.01. Data quality was evaluated by a variety of measures, including
  • Example 2 ER status classifiers based on complex modeling of signals across different subsets of individual genomic loci that are differentiated based on ER-positive and ER- negative status [0330]
  • genomic loci likely to differentiate ER- positive and ER-negative samples based on H3K4me3 modification, H3K27ac modification or DNA methylation were first identified.
  • union peak maps were created by merging peak coordinates for all of the cell lines, removing regions likely to be artifactual (the ENCODE “blacklist” regions, see Amemiya et al., Sci Rep (2019) 9(1):9354) and discarding all peaks less than 50 bp in length.
  • Genomic loci that had differential analyte signal between ER-positive and ER-negative cell lines were determined using DESeq2 (Love et al., Genome Biol (2014) 15(12):550), with an FDR cutoff of 5%. These differential loci are shown in Table 1 (H3K4me3), Table 2 (H3K27ac) and Table 3 (DNA methylation).
  • genomic loci from Tables 1-3 for different modifications, namely (i) H3K4me3 modifications, (ii) H3K27ac modifications, (iii) DNA methylation (DNAme) or (iv) all of the above (All) and (b) using different subsets of genomic loci in Tables 1-3 for a particular modification, namely (i) all genomic loci with an absolute log2(fold-change) ⁇ 0.5, (ii) all genomic loci with an absolute log2(fold-change) ⁇ 1, (iii) all genomic loci with an absolute log2(fold-change) ⁇ 2, (iv) all genomic loci with an absolute log2(fold-change) ⁇ 3, and (v) all genomic loci with an absolute log2(fold-change) ⁇ 4.
  • Fig.2 shows a representative, non-limiting graphs that demonstrates the accuracy of ER status (based on AUCROC) determination using the classifiers that were generated in accordance with this Example.
  • Example 3 ER Status Determination in Plasma Samples [0334] The present example provides data demonstrating that technologies provided in the present disclosure can be used to determine ER status in a subject having cancer, using samples comprising cfDNA. In the present example, plasma samples from patients diagnosed with metastatic breast cancer were characterized. [0335] Plasma samples were obtained from 91 subjects.
  • Table 4 shows genes that were determined to be associated with ER status using the disclosed classifiers. As indicated below, genes previously associated with ER status (left column); genes previously shown to have a biological link, but not directly associated with ER
  • an ER classifier described herein measures an epigenomic marker (e.g., promoter, enhancer, or DNA methylation marker) associated with one or more of the genes listed in Table 4.
  • an epigenomic marker e.g., promoter, enhancer, or DNA methylation marker
  • Table 1 Exemplary genomic loci that are differentially H3K4me3 modified in ER-positive vs. ER-negative cancer.
  • Index Genomic locus log2(FC) Index Genomic locus log2(FC) 1 chr1:793725-794444 -1.41 676 chr13:99710786-99710933 1.60 2.00 3.08 2.44 1.72 1.59 2.20 2.87 3.23 1.80 1.91 2.59 1.86 1.95 1.91 1.73 1.54 1.61 1.02 1.75 1.86 1.66 1.85 2.12 1.76 1.72 2.40 2.12 3.27 2.01 0.62 1.65 0.57 0.55 1.54 2.30 1.55 2.62 2.35 2.02 1.96 2.14 0.51 2.39 0.62 Attorney Docket No.2014191-0027 Index Genomic locus log2(FC) Index Genomic locus log2(FC) 46 chr1:11761594-11762165 -2.11 721 chr14:55543845-55
  • compositions or methods are described as having, including, or comprising specific elements, it is to be understood that compositions or methods that consist essentially of, consist of, or do not comprise the recited elements are likewise hereby disclosed. All references cited herein are hereby incorporated by reference.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Organic Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Engineering & Computer Science (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Analytical Chemistry (AREA)
  • Zoology (AREA)
  • Genetics & Genomics (AREA)
  • Wood Science & Technology (AREA)
  • Physics & Mathematics (AREA)
  • Biotechnology (AREA)
  • Microbiology (AREA)
  • Molecular Biology (AREA)
  • Hospice & Palliative Care (AREA)
  • Biophysics (AREA)
  • Oncology (AREA)
  • Biochemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

La présente divulgation concerne, entre autres, des procédés, des kits et des systèmes pour déterminer l'état ER d'un cancer, par exemple, un cancer du sein. Dans divers modes de réalisation, la présente divulgation concerne l'utilisation d'une ou de plusieurs modifications d'histone, l'accessibilité de la chromatine, la liaison d'un ou de plusieurs facteurs de transcription et/ou la méthylation de l'ADN qui sont caractéristiques de l'état ER du cancer. Dans certains modes de réalisation, des modifications différentielles et/ou une accessibilité différentielle sont détectées et quantifiées au niveau d'un ou de plusieurs loci génomiques d'un échantillon biologique, par exemple, dans de l'ADN acellulaire (ADNcf) provenant d'un échantillon de biopsie liquide obtenu ou dérivé d'un sujet atteint d'un cancer. Dans divers modes de réalisation, un état ER déterminé est utile, par exemple, dans la sélection d'un traitement et/ou le traitement d'un cancer, par exemple, un cancer du sein.
PCT/US2024/051117 2023-10-13 2024-10-11 Procédés, kits et systèmes pour déterminer l'état er d'un cancer et procédés de traitement du cancer sur la base de ceux-ci Pending WO2025081094A2 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US202363590158P 2023-10-13 2023-10-13
US63/590,158 2023-10-13
US202463650860P 2024-05-22 2024-05-22
US63/650,860 2024-05-22

Publications (2)

Publication Number Publication Date
WO2025081094A2 true WO2025081094A2 (fr) 2025-04-17
WO2025081094A3 WO2025081094A3 (fr) 2025-08-07

Family

ID=93292057

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2024/051117 Pending WO2025081094A2 (fr) 2023-10-13 2024-10-11 Procédés, kits et systèmes pour déterminer l'état er d'un cancer et procédés de traitement du cancer sur la base de ceux-ci

Country Status (1)

Country Link
WO (1) WO2025081094A2 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2025245302A1 (fr) 2024-05-22 2025-11-27 Precede Biosciences, Inc. Procédés, kits et systèmes pour déterminer l'activité er d'un cancer et méthodes de traitement du cancer sur la base de ceux-ci

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5308341A (en) 1993-09-28 1994-05-03 Becton, Dickinson And Company Method of testing the dose accuracy of a medication delivery device
US6146361A (en) 1996-09-26 2000-11-14 Becton Dickinson And Company Medication delivery pen having a 31 gauge needle
US6192891B1 (en) 1999-04-26 2001-02-27 Becton Dickinson And Company Integrated system including medication delivery pen, blood monitoring device, and lancer
US6277099B1 (en) 1999-08-06 2001-08-21 Becton, Dickinson And Company Medication delivery pen
US7556615B2 (en) 2001-09-12 2009-07-07 Becton, Dickinson And Company Microneedle-based pen device for drug delivery and method for using same

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4320618A4 (fr) * 2021-04-08 2025-08-27 Fred Hutchinson Cancer Center Procédé d'analyse de données de séquence d'adn acellulaire pour examiner la protection du nucléosome et l'accessibilité de la chromatine

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5308341A (en) 1993-09-28 1994-05-03 Becton, Dickinson And Company Method of testing the dose accuracy of a medication delivery device
US6146361A (en) 1996-09-26 2000-11-14 Becton Dickinson And Company Medication delivery pen having a 31 gauge needle
US6200296B1 (en) 1996-09-26 2001-03-13 Becton Dickinson And Company 5mm injection needle
US6192891B1 (en) 1999-04-26 2001-02-27 Becton Dickinson And Company Integrated system including medication delivery pen, blood monitoring device, and lancer
US6277099B1 (en) 1999-08-06 2001-08-21 Becton, Dickinson And Company Medication delivery pen
US7556615B2 (en) 2001-09-12 2009-07-07 Becton, Dickinson And Company Microneedle-based pen device for drug delivery and method for using same

Non-Patent Citations (43)

* Cited by examiner, † Cited by third party
Title
"Biocomputing: Informatics and Genome Projects", 1994, ACADEMIC PRESS
"Computational Molecular Biology", 1988, OXFORD UNIVERSITY PRESS
"Sequence Analysis in Molecular Biology", 1987, ACADEMIC PRESS
ADALSTEINSSON ET AL., NAT COMM., 2017
ADALSTEINSSON ET AL., NAT COMMUN, vol. 8, no. 1, 2017, pages 1324
ADLANMERINI ET AL., PROC NATL ACAD SCI USA, vol. 111, 2014, pages 283 - 290
ALLRED ET AL., BREAST CANCER RES, vol. 6, 2004, pages 240 - 245
ALTSCHUL ET AL., J MOL BIOL, vol. 215, 1990, pages 403 - 410
AMEMIYA ET AL., SCI REP, vol. 9, no. 1, 2019, pages 9354
ANKER ET AL., CANCER AND METASTASIS REV, vol. 18, 1999, pages 65 - 73
ARNAL ET AL., PHYSIOL REV, vol. 97, 2017, pages 1045 - 1087
AUERBACH ET AL., PROC NATL ACAD USA, vol. 106, no. 35, 2009, pages 14926 - 14931
BERGMANCEDAR, NAT STRUCT MOL BIOL, vol. 20, 2013, pages 274 - 281
BUENROSTRO ET AL., NAT METHODS, vol. 10, no. 12, 2013, pages 1213 - 1218
FIEGL ET AL., CANCER RES, vol. 15, 2005, pages 1141 - 1145
FOLKERDDOWSETT, J CLIN ONCOL, vol. 28, 2010, pages 4038 - 4044
HEWITTKORACH, ENDOCR REV, vol. 39, no. 5, 2018, pages 664 - 675
HIGGINSSHARP, COMP APPL BIOSCI, vol. 5, no. 2, 1989, pages 151 - 153
IKEDA ET AL., ACTA PHARMACOL SIN, vol. 36, 2015, pages 24 - 31
J. R. ROBINSON: "Sustained and Controlled Release Drug Delivery Systems", 1978, MARCEL DEKKER, INC.
JANG ET AL., LIFE SCI ALLIANCE, vol. 6, no. 12, 2023, pages e202302003
JENSEN, CANCER, vol. 46, 1980, pages 2759 - 2761
KAYA-OKUR ET AL., NAT COMM, vol. 10, 2019, pages 1930
KNUTSON ET AL., J HEMATOL ONCOL, vol. 10, 2017, pages 168
LIN ET AL., BIOINFORMATICS, vol. 20, 2004, pages 1233 - 1240
LOVE ET AL., GENOME BIOL, vol. 15, no. 12, 2014, pages 550
MEISSNER ET AL., NUCLEIC ACIDS RES, vol. 33, no. 18, 2005, pages 5868 - 5877
OGSTON ET AL., BREAST, vol. 12, 2003, pages 320 - 327
OMARJEE ET AL., ONCOGENE, vol. 36, 2017, pages 2503 - 2514
PATHAK ET AL., CLIN CHEM, vol. 52, 2006, pages 1833 - 1842
PEARSON: "Comput Methods Genome Res [Proc Int Symp] (1994", 1992, OXFORD UNIVERSITY PRESS, pages: 111 - 120
PRATTTOFT, ENDOCR REV, vol. 18, 1997, pages 306 - 360
ROBERTSON, NAT REV GENET, vol. 6, 2005, pages 597 - 610
SADEH ET AL., NAT BIOTECHNOL, vol. 39, 2021, pages 586 - 598
SCHONES ET AL., CELL, vol. 132, no. 5, 2008, pages 887 - 898
SCHWARZENBACH ET AL., CLIN CANCER RES, vol. 15, 2009, pages 1032 - 1038
SCHWARZENBACH ET AL., NAT REV CANCER, vol. 11, 2011, pages 426 - 437
SKENE ET AL., NAT PROTOC, vol. 13, 2018, pages 1006 - 1019
SKENEHENIKOFF, ELIFE, vol. 6, 2017, pages 1 - 35
SYMMANS ET AL., J CLIN ONCOL, vol. 25, 2007, pages 4414 - 4422
WEBER ET AL., NAT GENET, vol. 37, 2005, pages 853 - 862
WELBOREN ET AL., EMBO J, vol. 28, 2009, pages 1418 - 1428
WUA ET AL., CLIN CHIM ACTA, vol. 321, 2002, pages 77 - 87

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2025245302A1 (fr) 2024-05-22 2025-11-27 Precede Biosciences, Inc. Procédés, kits et systèmes pour déterminer l'activité er d'un cancer et méthodes de traitement du cancer sur la base de ceux-ci

Also Published As

Publication number Publication date
WO2025081094A3 (fr) 2025-08-07

Similar Documents

Publication Publication Date Title
US10706954B2 (en) Systems and methods for identifying responders and non-responders to immune checkpoint blockade therapy
US11456056B2 (en) Methods of treating a subject suffering from rheumatoid arthritis based in part on a trained machine learning classifier
US20210174908A1 (en) Classification of tumor microenvironments
US20220319638A1 (en) Predicting response to treatments in patients with clear cell renal cell carcinoma
US20240161868A1 (en) System and method for gene expression and tissue of origin inference from cell-free dna
WO2025081094A2 (fr) Procédés, kits et systèmes pour déterminer l'état er d'un cancer et procédés de traitement du cancer sur la base de ceux-ci
EP4423301A1 (fr) Types de microenvironnement tumoral dans le cancer du sein
JP7772700B2 (ja) 神経膠芽腫を処置するための方法
AU2024358761A1 (en) Methods, kits and systems for determining the er status of cancer and methods for treating cancer based on same
AU2024357822A1 (en) Methods, kits and systems for determining the her2 status of cancer and methods for treating cancer based on same
WO2025245302A1 (fr) Procédés, kits et systèmes pour déterminer l'activité er d'un cancer et méthodes de traitement du cancer sur la base de ceux-ci
AU2024357837A1 (en) Methods, kits and systems for determining the status of lung cancer and methods for treating lung cancer based on same
WO2025081121A9 (fr) Procédés, kits et systèmes pour déterminer l'état du cancer du poumon et méthodes de traitement du cancer du poumon les utilisant
EP4137585A1 (fr) Signature de biomarqueurs informatifs du cancer
WO2025213150A1 (fr) Procédés, kits et systèmes de mesure de l'expression de psa et de psma et méthodes de traitement du cancer sur la base de ceux-ci
CA3065568C (fr) Systemes et procedes d'identification de repondeurs et de non-repondeurs a une therapie de blocage de points de controle immunitaires
WO2025111249A2 (fr) Procédés, kits et systèmes pour déterminer une différenciation sarcomatoïde d'un carcinome à cellules rénales et méthodes de traitement basées sur ceux-ci
WO2026055162A2 (fr) Procédés, kits et systèmes pour la détermination de l'état de sclérose en plaques et méthodes de traitement de la sclérose en plaques sur la base de ceux-ci
US20220154284A1 (en) Determination of cytotoxic gene signature and associated systems and methods for response prediction and treatment
WO2026050568A1 (fr) Procédés et utilisations pour le traitement du cancer à l'aide de conjugués anticorps-médicament

Legal Events

Date Code Title Description
WWE Wipo information: entry into national phase

Ref document number: AU2024358761

Country of ref document: AU