WO2020175903A1 - 간암 재발 예측용 dna 메틸화 마커 및 이의 용도 - Google Patents

간암 재발 예측용 dna 메틸화 마커 및 이의 용도 Download PDF

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WO2020175903A1
WO2020175903A1 PCT/KR2020/002727 KR2020002727W WO2020175903A1 WO 2020175903 A1 WO2020175903 A1 WO 2020175903A1 KR 2020002727 W KR2020002727 W KR 2020002727W WO 2020175903 A1 WO2020175903 A1 WO 2020175903A1
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Prior art keywords
liver cancer
methylation
recurrence
cancer
liver
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English (en)
French (fr)
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김영준
김다원
김태유
이광웅
하정실
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Lepidyne Co Ltd
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Lepidyne Co Ltd
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Priority to CN202080017304.2A priority Critical patent/CN113544288B/zh
Priority to EP20762970.0A priority patent/EP3950960A4/en
Priority to JP2021550256A priority patent/JP7340879B2/ja
Priority to SG11202109382SA priority patent/SG11202109382SA/en
Priority to US17/434,675 priority patent/US12467097B2/en
Publication of WO2020175903A1 publication Critical patent/WO2020175903A1/ko
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    • 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
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    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/118—Prognosis of disease development
    • 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

Definitions

  • the present invention relates to a DNA methylation marker for predicting recurrence of liver cancer, and its use, using one point of greater than or equal to the methylation level of genomic DNA according to the prognosis of liver cancer.
  • liver cancer is a primary liver cancer (hepatocellular carcinoma; Hepatocellular carcinoma (hepatoma) and cancers of other tissues can be divided into metastatic liver cancer that has spread to the liver. More than 90% of liver cancers are primary liver cancer, and it is commonly understood that the term liver cancer refers to primary liver cancer.
  • radical cure means treatment that completely eliminates the cancer itself, and includes liver resection, liver transplantation, and high-frequency heat treatment.
  • carotid chemoembolization, radiation therapy, and chemotherapy are performed.
  • these treatments can cure the cancer itself. Because it is difficult to go, the purpose of the examination is to provide radical treatment through early detection. In the case of liver resection surgery, about 50% of patients experience recurrence of cancer, because the liver that remains after the resection is also exposed to hepatitis other than the normal liver.
  • the prognosis of liver cancer refers to predicting the various conditions of a patient according to liver cancer, such as the possibility of cure of liver cancer after diagnosis of liver cancer, the possibility of recurrence after treatment, and the possibility of survival of the patient. This means the severity of the disease, It depends on various conditions, such as the time of diagnosis and the course of treatment. Liver cancer can be treated efficiently only when various treatment methods are appropriately applied depending on the prognosis. For example, it is aggressive for patients whose prognosis is expected to be favorable. Dangerous treatment methods, such as chemotherapy, surgery, and radiation therapy, that may cause serious side effects to the patient need to be avoided, and relatively moderate, conservative, and safe treatment methods should be selected. Conversely, it is predicted that the prognosis will be poor. For those patients who become eligible, it is necessary to actively mobilize treatment methods such as chemotherapy, surgery, and radiation to increase the duration or probability of survival.
  • An object of the present invention is to provide a composition for predicting recurrence of liver cancer containing a DNA methylation marker and a method for predicting the recurrence of liver cancer using the same.
  • composition for predicting recurrence of liver cancer comprising at least one DNA methylation marker selected from the group consisting of the indicated DNA methylation markers.
  • the DNA methylation markers represented by the above sequence numbers to 4 are CG loci symbols (Illumina ® Infinium Human Megra- lation 850K bead array CpG
  • liver cancer refers to cancer occurring in liver tissue.
  • liver cancer hepatocellular carcinoma, hepatoma
  • metastatic liver cancer in which cancers of other tissues have metastasized to the liver.
  • Liver cancer treatment includes liver resection, liver transplantation, hyperthermia therapy, and Various treatment methods such as carotid artery chemoembolization are used, but the 5-year survival rate is only 33.6% (average from 2011 to 2015; statistics from the Ministry of Health and Welfare), and the recurrence rate is also 70%.
  • liver cancer has a low 5-year survival rate and a significantly higher recurrence rate, so a method to predict recurrence is needed.
  • DNA methylation refers to the covalent attachment of a methyl group to the C5-position of the cytosine base in genomic DNA.
  • the level of methylation for example all genome regions and some non- It refers to the amount of methylation present in the DNA base sequence in the genomic region, and in the present invention refers to the degree of methylation of the DNA methylation marker represented by SEQ ID NOs: 1 to 4. Methylation in the DNA methylation markers of SEQ ID NOs: 1 to 4 above. It can occur throughout the sequence.
  • the composition for predicting recurrence of early stage cancer may be a composition containing one or more, two or more, three or more or four of the DNA methylation markers.
  • the composition for predicting recurrence of liver cancer. May contain DNA methylation markers cg21325760, eg 10544510, cg06702718 and cgl5997204, one each, and a combination of two, cg21325760 and eg 10544510; cg21325760 and cg06702718; cg21325760 and
  • composition for predicting recurrence of early stage cancer may contain three DNA methylation markers, for example cg21325760, eg 10544510 and cg06702718; cg21325760, eg 10544510 and eg 15997204; cg21325760 cg06702718 and eg 15997204; or eg 10544510, cg06702718 and cgl5997204.
  • composition for predicting recurrence of early-stage cancer may contain all of the DNA methylation marker cg21325760, eg 10544510, cg06702718 and eg 15997204.
  • the DNA methylation marker cgl5997204 is a marker present in the MYT1L gene, and the MYT1L (Myelin Transcription Factor 1 Like) gene encodes a transcription factor belonging to the C-C-H-C zinc finger protein.
  • MYT1L Myelin Transcription Factor 1 Like
  • the DNA methylation marker cg21325760 is MAGEL2
  • the present inventors isolated genomic DNA from liver cancer tissue and then confirmed the level of methylation with an Illumina ® Infinium Human Merelation 850K bead array.
  • an Illumina ® Infinium Human Merelation 850K bead array As a result, according to the level of methylation, two liver cancer tissues were identified. It was confirmed that the two groups were classified into groups, and it was found that there was a remarkable difference in the recurrence rate of liver cancer.
  • DNA methylation markers whose methylation levels were significantly different were confirmed by machine learning techniques such as random forest, and the above was confirmed. DNA methylation markers were discovered (see Table 3).
  • the present invention was completed by confirming that the accuracy of predicting recurrence of liver cancer converged to 1. ( Figure 5 and Table 2).
  • the phase cancer is hepatocellular carcinoma arising from the hepatocyte itself or other
  • Hepatocellular carcinoma accounts for about 90% of malignant tumors occurring in the liver, and is common in Korea, Japan, Southeast Asia, and China. Occurs in most cases with cirrhosis, but in some cases chronic type B or
  • liver cancer a patient with liver cancer, that is, liver cancer.
  • Silver hepatectomy, hyperthermia therapy, carotid chemoembolization, and percutaneous ethanol injection may be used, but are not limited thereto.
  • the composition for predicting the prognosis of early-stage cancer is in the form of a kit for predicting recurrence of liver cancer, which additionally contains reagents necessary for confirming the methylation level of DNA methylation markers. 2020/175903 can be implemented.
  • One aspect of this invention provides a method for predicting recurrence of liver cancer comprising the following steps:
  • the DNA methylation markers represented by the above sequence numbers to 4 are respectively 00 locus symbols (11111111 Nyota ® 11 11 1111 13 ⁇ 41111 Ta11] ⁇ [6 ⁇ ! 4 ⁇ 011 8501 (Bead array CpG)
  • the liver tissue to be analyzed may be a liver cancer tissue isolated from the subject to be analyzed, a hepatocellular carcinoma tissue, a metastatic liver cancer, or a metastatic cancer tissue at the site where liver cancer has metastasized, preferably, hepatocellular carcinoma. It may be a tissue.
  • the method of separating the tissue between the analysis targets from the analysis target object may use methods such as transdermal biopsy and jugular vein biopsy known in the technical field to which the present invention belongs.
  • the method for predicting the prognosis of liver cancer may be a method of confirming methylation of at least two DNA methylation markers in a step (ratio).
  • the present inventors can predict the recurrence of liver cancer.
  • the DNA methylation marker of the present invention is used singly, the prognosis of liver cancer has excellent performance, but if multiple uses are used, the performance is remarkably excellent. Therefore, the DNA methylation marker of the present invention is single or plural. Dogs can be combined and used to predict liver cancer recurrence.
  • 0 ⁇ 06702718 and 0 5997204 can each be used as a single marker, a combination of two markers ⁇ 21325760 and 10544510; 0 ⁇ 21325760 and 0 ⁇ 06702718; 0 ⁇ 21325760 and
  • the method for predicting the prognosis of liver cancer is that the methylation level of the DNA methylation marker identified in the sample to be analyzed after step (0) is the methylation of normal liver tissue. If it is lower than the 2020/175903 PCT/KR2020/002727 level, it may further include a step of judging that the recurrence probability of liver cancer is high.
  • the method of checking the methylation level of a DNA methylation marker is known in the art: PCR, methylation specific PCR, real time methylation specific PCR, methylated DNA specific binding Protein PCR, quantitative PCR, DNA chip, pyro-sequencing, commercially available chips, etc. can be used, but are not limited thereto.
  • the use of the DNA methylation marker for predicting recurrence of liver cancer of the present invention makes it possible to easily predict the recurrence of liver cancer, provides a more personalized treatment for patients at high risk of recurrence of liver cancer, and provides clinical information to avoid unnecessary overdose treatment. Can provide.
  • Figure 3 is methylation group 1 (MG1) and methylation group 2 (MG2) obligation-re-occurrence period
  • FIG. 4 shows the importance of variables in methylation group 1 (MG1) and methylation group 2 (MG2).
  • variable importance plot (varlmpPlot) (A)
  • B the process of selecting the top 50 probes involved in the methylation group classification
  • FIG. 5 shows the results of confirming the predictive efficiency of liver cancer prognosis according to the number of probes involved in methylation group classification as an AUC (area under the curve) value.
  • FIG. 6 shows the normal sample (N), methylation group 1 (MG1) and methylation group 2 (MG2)
  • liver cancer verification cohort data produced by the probe involved in methylation group classification.
  • FIG. 8 shows the results of classifying liver cancer data published on the cancer genome atias (TCGA) as a probe involved in methylation group classification.
  • HCC hepatocellular carcinoma
  • the reason for excluding patients who recurrence within one year is that HCC resection is incorrect in the case of early recurrence, or recurrence is often due to reasons other than liver cancer. This is because it does not meet the purpose of.
  • MagListoTM 5M genome DNA line kit (Bioneer) was used according to the manufacturer's instructions from frozen HCC samples obtained from the remaining 140 patients.
  • an Illumina Infinium Human Merelation EPIC 850K BeadChip (Illumina) analysis was performed with the Illumina iScan System (Illumina, CA, USA) according to the manufacturer's standard protocol.
  • the Illumina Infinium Human Measurement EPIC BeadChips contain DNA methylation values for more than 850,000 CpG sites for the resolution of every single nucleotide.
  • pre-processing the methylated data using the minfi R package from the open software R (https://cran.r-project.org/bin/windows/base/; version 3.3.2) Specifically, the raw IDAT file of the HCC sample was processed, background correction and dye deviations were corrected. After that, methylation and By measuring the signal intensity of the unmethylated probe, the DNA methylation value of each probe was quantified as a b-value ranging from 0 (unmethylated) to 1 (completely methylated). Next, for all samples, Data quality control was performed, and all 140 samples passed the quality control standard. Finally, methylation data was normalized using a functional normalization method to reduce the batch effect problem.
  • M-value log((b-value)/ (l-(b-value)))
  • M-value was used for consensus clustering, and b-value was used for heat map visualization and box plot generation.
  • Consensus Clustering is ConcensusClusterPlus (https://bioconductor.org/)
  • HCC tumor samples are divided into four training cohorts. (cohort) and 1 test cohort randomly divided into 5 times
  • the present inventors constructed a random forest model, and the expected ratio of each group was predicted by the confusion matrix (predicted vs observed samples). , The performance of each model is based on the area under the curve (AUC), sensitivity, and specificity values.
  • the present inventors measured the importance value of each probe, taking into account the Gini index, the overall reduction in probe impurity, and the dot chart of the importance of the variable measured by the random forest. As a result, the present inventors measured the importance value of each probe. They discovered the top 50 probes that can classify HCC samples into methylation groups 1 and 2 (hereinafter referred to as MG1 and MG2, respectively) (Fig. 4). After comparing the performance efficiency of one probe and the top 50 probes, Considering the AUC value, the minimum number of probes with maximum efficiency 2020/175903 1»(:1/10 ⁇ 020/002727 confirmed.
  • Gene ontology aM pathway analysis The present inventors searched various pathways and performed gene ontology analysis using innateDB (http://www.innatedb.com/). In the above innateDB, gene ontology biological biology was performed. Gene Ontology biological processes, KEGG (Kyoto Encyclopedia of Genes and Genomes), and Reactome resources were used. The significant cutoff criterion was P-value ⁇ 0.05.
  • MG1 has a long period of non-reoccurrence (RFS), while MG2 has a short non-reoccurrence zone, so the prognosis is poor.
  • the top 50 probes are catabolic processes, neurotransmitter secretion, regulation of molecular function, Wnt signaling pathway, cell migration regulation, mRNA metabolism process, small GTPase mediated signaling, gene expression regulation, It was related to the regulation of apoptosis process. [79] [Table 1]
  • Marker refers to the targeted methylation site
  • MG2 (gray) was able to confirm that the level of methylation was about 50% or less compared to that of normal liver tissue (Fig. 6;
  • the X-axis is the selected marker, the V-axis is the value indicating the level of methylation).
  • liver cancer patients were classified into groups (Pre_MGl and Pre_MG2) (Fig. 8A). It was found that the group had different prognosis (Fig. 8B).

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Abstract

본 발명은 간암의 예후에 따라 DNA 메틸화 수준이 상이한 점을 이용한, 간암 재발 예측용 DNA 메틸화 마커에 관한 것으로, 상기 마커를 사용하면 간암의 재발 여부를 용이하게 예측할 수 있고, 간암 재발 위험이 높은 환자에게 보다 개인화된 치료법을 제공하고 불필요한 과다 치료를 피하기 위한 임상 정보를 제공할 수 있다.

Description

2020/175903 1»（：1/10公020/002727 명세서
발명의명칭:간암재발예측용 DNA메틸화마커및이의용도 기술분야
[1] 본발명은간암의예후에따라게놈 DNA의메틸화수준이상이한점을이용한 간암의재발예측용 DNA메틸화마커및이의용도에관한것으로,
구체적으로는간암환자의치료후정상간조직에서간암의재발여부를 예측하기위한 DNA메틸화마커에관한것이다.
배경기술
[2] 간암（liver cancer）은크게간세포자체로부터발생한원발성간암（간세포암; hepatocellular carcinoma, hepatoma）과다른조직의암이간으로전이되어온 전이성간암으로구분할수있다.간암의약 90%이상은원발성간암이고,흔히 간암이라함은원발성간암을지칭하는것으로이해된다.통계청이 2018년
9월에발표한’ 2017사망원인통계’에따르면 2017년인구 10만명기준암으로 사망한사람은 153.9명으로전년대비 1.0명（0.6%）증가했다.암사망률은 폐암（35.1명）,간암（20.9명）,대장암（17.1명）,위암（15.7명）,췌장암（11.3명）순으로 높았다.
[3] 다른암과마찬가지로간암의치료도크게근치적치료와보존적치료가있다. 여기서근치란암자체를완전히없애는치료를의미하며간절제수술,간이식 , 고주파열치료등이 있다.또한이러한치료가불가한경우경동맥화학색전술, 방사선치료,항암치료를하게된다.그러나이러한치료로는완치가거의 어렵기때문에조기발견을통해근치적치료를하는것이검진의목적이다. 간절제수술의경우약 50%의환자에서암재발을경험하게되는데,그이유는 절제되고남아있는간도정상적인간이아닌간염에노출되어있기때문이다.
[4] 간암의예후（prognosis）는간암이진단된이후에간암의완치가능성,치료후 재발가능성,환자의생존가능성등간암에따른환자의각종상태를예측하는 것을의미하며,이는질병의심각성,진단시점,치료경과등의다양한조건에 의존하여달라진다.간암은그예후에따라적합하게다양한치료방법이 적용되어야만효율적인치료가가능하다.예를들어 ,예후가양호할것으로 예측되는환자들에대해서는공격적인화학치료나수술,방사선치료등 환자에게심각한부작용을야기할가능성이 있는위험한치료방법은지양할 필요가있고,상대적으로온건하고보존적이며안전한치료방법을선택하여야 한다.반대로예후가불량할것으로예측되는환자들에대해서는화학치료나 수술,방사선치료와같은치료방법을적극적으로동원하여생존의기간이나 확률을높이고자시도하여야한다.
[5] 그러나간암환자의예후를정확하게예측하는것은종래의기술로는매우 어렵다.예후의정확한예측을위해서는환자들을위험군별로분류하는 분석방법이필요한데,현재까지는간암의 예후를정확하게예측할수있는수단 없이진단시의임상병리학적인간암의단계와 1차적외과치료에만의존하여 예후를판단하고있는실정이다.
[6] 본발명자들은이러한문제를해결하고자노력한결과,간암조직의 DNA
메틸화데이터를근거로간암환자의 예후를예측할수있는방법을마련하였다. 발명의상세한설명
기술적과제
[7] 본발명의목적은 DNA메틸화마커를포함하는간암의재발예측용조성물과 이를이용한간암의재발가능성을예측하는방법을제공하는것이다.
과제해결수단
[8] 상기목적을달성하기위하여 ,본발명의일양상은서열번호 1내지 4로
표시되는 DNA메틸화마커로이루어진군에서선택되는하나이상의 DNA 메틸화마커를포함하는간암의재발예측용조성물을제공한다.
[9] 본발명에서 ,상기서열번히내지 4로표시되는 DNA메틸화마커는각각 CG 유전자좌기호 (Illumina® Infinium HumanMe比 lylation 850K비드어레이 CpG
ID)로표시되는 DNA메틸화마커인 cg21325760, eg 10544510, cg06702718및 cgl5997204를의미한다.
[1이 본명세서에사용된용어 , "간암 (liver cancer)”은간조직에발생하는암을
종칭하는용어로,간세포자체에서발생한원발성간암 (간세포암; hepatocellular carcinoma, hepatoma)과다른조직의암이간으로전이되어온전이성간암으로 구분할수있다.간암치료에는간절제술,간이식,고주파열치료술,경동맥 화학색전술등다양한치료법이사용되고있으나, 5년생존율이 33.6%(2011년 내지 2015년평균;보건복지부통계)밖에되지않고,재발률또한 70%에이른다. 다른암종에비해간암은 5년생존율은낮고,재발률은상당히높기때문에재발 여부를예측할수있는방법이필요하다.
[11] 본명세서에사용된용어, "DNA메틸화 (DNA methylation)”는게놈 DNA에서 시토신염기의 C5 -위치에메틸기가공유결합한것을의미한다.메틸화수준은 예를들면모든게놈영역및일부비-게놈영역내의 DNA염기서열에존재하는 메틸화의양을의미하며,본발명에서는서열번호 1내지 4로표시되는 DNA 메틸화마커의메틸화정도를의미한다.상기서열번호 1내지 4의 DNA메틸화 마커에서메틸화는서열전체에걸쳐일어날수있다.
[12] 본발명에서 ,상기간암의재발예측용조성물은상기 DNA메틸화마커중에서 1개이상, 2개이상, 3개이상또는 4개를포함하는조성물일수있다.구체적으로 상기간암의재발예측용조성물은 DNA메틸화마커 cg21325760, eg 10544510, cg06702718및 cgl5997204를각각한개씩포함할수있고,두개의조합인 cg21325760및 eg 10544510; cg21325760및 cg06702718; cg21325760및
eg 15997204; eg 10544510및 cg06702718; eg 10544510및 eg 15997204;또는 cg06702718및 eg 15997204조합을포함할수있다.또한,상기간암의재발 예측용조성물은세개의 DNA메틸화마커를포함할수있으며,예를들어 cg21325760, eg 10544510및 cg06702718; cg21325760, eg 10544510및 eg 15997204; cg21325760 cg06702718및 eg 15997204;또는 eg 10544510, cg06702718및 cgl5997204의조합을포합할수있다.아울러,상기간암의재발예측용조성물은 DNA메틸화마커 cg21325760, eg 10544510, cg06702718및 eg 15997204모두를 포함할수있다.
[13] 본발명에서,상기 DNA메틸화마커 cgl5997204는 MYT1L유전자에존재하는 마커로서 MYT1L (Myelin Transcription Factor 1 Like)유전자는 C-C-H-C징크 핑거단백질에속하는전사인자를코딩한다. TCGA(The Cancer Genome Atias)에 공개된데이터에따르면다양한암에서 MYT1L이발현되나,이유전자의메틸화 수준과간암의재발여부와의상관관계에대해서는아직까지명확히알려진 바가없다.
[14] 본발명에서，상기 DNA메틸화마커 cg21325760은 MAGEL2
(MAGE(melanoma-as sociated antigen) family member L2)유전자에존재하고, TCGA데이터에따르면정소암에서많이발현되나,이유전자의메틸화수준과 간암의재발여부와의상관관계에대해서는아직까지명확히알려진바가없다.
[15] 본발명의일구체예에서 ,본발명자들은간암조직에서게놈 DNA를분리한후 Illumina® Infinium HumanMe比 lylation 850K비드어레이로메틸화수준을 확인하였다.그결과,메틸화수준에따라간암조직이두그룹으로분류되는 것을확인하였고,상기두그룹이간암의재발률에있어현저한차이가있음을 알수있었다.이후두그룹에서메틸화수준이현저히차이나는 DNA메틸화 마커를랜덤포레스트등의기계학습기법으로확인하여상기 DNA메틸화 마커를발굴하였다 (표 3참조).또한,하나의 DNA메틸화마커보다 4개의 DNA 메틸화마커를같이사용하는경우,간암의재발예측의정확도가 1에수렴하는 것을확인하여본발명을완성하였다 (도 5및표 2).
[16] 본발명에서 ,상기간암은간세포자체로부터발생한간세포암또는다른
조직의암이간으로전이되어온전이성간암일수있으나,바람직하게는 간세포암일수있다.간세포암 (hepatocellular carcinoma)은간에서발생하는악성 종양의약 90%를차지하며,우리나라와일본,동남아시아,중국등지에서많이 발생한다.대부분간경변증이있는상태에서발생하나,일부는만성 B형또는
C형간염으로인해발생하기도한다.
[17] 본명세서에사용된용어,’’재발 (relapse)’’은간암환자에서간암을치료한후 간에서다시비정상적인세포증식,즉,간암이발생하는것을의미한다.상기 간암환자의치료방법은간절제술,고주파열치료술,경동맥화학색전술, 경피적에탄올주입술등이사용될수있으나,이에제한되지않는다.
[18] 본발명에서 ,상기간암의예후예측용조성물은 DNA메틸화마커의메틸화 수준확인에필요한시약등을추가로포함하는간암의재발예측용키트형태로 2020/175903 구현될수있다.
[19]
[2이 본발명의 일양상은하기단계를포함하는간암의 재발예측방법을제공한다:
[21] ）분석 대상간조직에서 게놈 DNA를분리하는단계 ;
[22] ）서열번호 1내지 4로표시되는 DNA메틸화마커로이루어진군에서
선택되는하나이상의 DNA메틸화마커의 메틸화수준을검출하는단계;및
[23] （0）상기검출된 DNA메틸화마커의 메틸화수준을정상간조직에서 검출한 DNA메틸화마커의 메틸화수준과비교하는단계.
[24] 본발명에서 ,상기서열번히내지 4로표시되는 DNA메틸화마커는각각 00 유전자좌기호（11111111뇨따® 11 11 1111 1¾1111따11]ᆻ[6比!）4^011 8501（비드어레이 CpG
II））로표시되는 DNA메틸화마커인 0§21325760, 10544510, 0§06702718및
0은15997204를의미한다.
[25] 본발명의 일구체예에서 ,상기분석 대상간조직은분석 대상개체에서분리된 간암조직 ,간세포암조직 ,전이성 간암또는간암이 전이된부위의 전이암 조직일수있으며 ,바람직하게는간세포암조직일수있다.상기분석 대상간 조직을분석 대상개체에서분리하는방법은본발명이속하는기술분야에 알려져 있는경피생검 ,경정맥 생검등의 방법을사용할수있다.
[26] 본발명의 일구체예에서 ,상기 간암의 예후예측방법은단계（비에서최소 2개 이상의 DNA메틸화마커의 메틸화를확인하는방법일수있다.본발명자들은 간암의 재발여부를예측할수있는 4개의 DNA메틸화마커（프로브）를
발굴하였고（표 2참조）,마커의수에 따른간암재발예측의성능을평가하였다. 평가결과,마커가 2개 이상인경우정확도,민감도등의성능이 0.9에수렴하고 마커의수가 3개 이상인경우에는간암재발예측성능이 1에수렴하는것을 확인하였다（도 5）.
[27] 이결과로부터본발명의 DNA메틸화마커는단일로사용되어도간암예후 예즉성능이우수하나,복수개사용하는경우에는그성능이 현저히우수한것을 알수있다.따라서，본발명의 DNA메틸화마커는단일또는복수개가조합되어 간암재발예측용도로사용될수있다.
[28] 구체적으로,본발명의 DNA메틸화마커는。은21325760, 10544510,
0§06702718및 0 5997204가각각단일의마커로사용될수있고,두개마커의 조합 ^21325760및 10544510; 0§21325760및 0§06702718; 0§21325760및
15997204; 10544510및 0§06702718; 10544510및 15997204;또는 0§06702718및 15997204）또는세 개마커의조합 §21325760, 10544510및
0§06702718; 0§21325760, 10544510및 15997204; 0§21325760 0§06702718및
15997204;또는 10544510, 0§06702718및。 5997204）으로사용될수있다. 또한,상기 네개마커모두를조합하여사용할수있다.
[29] 본발명의 일구체예에서 ,상기 간암의 예후예측방법은단계（0）이후분석 대상샘플에서확인한 DNA메틸화마커의 메틸화수준이 정상간조직의 메틸화 2020/175903 PCT/KR2020/002727 수준보다낮은경우간암의재발가능성이높은것으로판별하는단계를추가로 포함할수있다.
[3이 본발명에서 , DNA메틸화마커의메틸화수준을확인하는방법은당업계에 알려진 PCR,메틸화특이 PCR(methylation specific PCR),실시간메틸화특이 PCR(real time methylation specific PCR),메틸화 DNA특이적결합단백질을 이용한 PCR,정량 PCR, DNA칩 ,파이로시퀀싱 ,상업적으로판매되는칩등으로 수행될수있으나,이에제한되는것은아니다.
[31] 본발명자들은간암이재발한환자 (MG2)에서는상기 DNA메틸화마커의
메틸화수준이정상간조직 (N)보다현저히낮은것을확인하였는바 (도 3, 7및 8),상기 DNA메틸화마커는간암의재발예측용도로유용하게사용될수있다. 발명의효과
[32] 본발명의간암재발예측용 DNA메틸화마커를사용하면간암의재발여부를 용이하게예측할수있고,간암재발위험이높은환자에게보다개인화된 치료법을제공하고불필요한과다치료를피하기위한임상정보를제공할수 있다.
도면의간단한설명
[33] 도 1은간세포암샘플 (A; n= 140))및정상간샘플 (B ; n=96)에서분리한 DNA의 메틸화수준을확인한결과를보여준다.
[34] 도 2는간세포암샘플 (n=140)을예후에따라메틸화그룹 1(MG1; n=81)및
메틸화그룹 2(MG2; n=59)로분류한후 DNA의메틸화패턴에따라각샘플을 컨센서스클러스터링방법으로분류한결과를보여준다.
[35] 도 3은메틸화그룹 1(MG1)및메틸화그룹 2(MG2)의무-재발생존기간
(recurrence free survival, RFS)을확인한결과를보여준다
[36] 도 4는메틸화그룹 1(MG1)및메틸화그룹 2(MG2)에서변수중요도
늘랏 (variable importance plot, varlmpPlot)을확인한후 (A),메틸화그룹분류에 관여하는상위 50개프로브를선별하는과정을보여준다 (B).
[37] 도 5는메틸화그룹분류에관여하는프로브의개수에따른간암예후예측 효율을 AUC(area under the curve)값으로확인한결과를보여준다.
[38] 도 6은정상간샘플 (N),메틸화그룹 1(MG1)및메틸화그룹 2(MG2)에서
메틸화그룹분류에관여하는프로브의메틸화수준을확인한결과를보여준다.
[39] 도 7은메틸화그룹분류에관여하는프로브로자체적으로생산한간암검증 코호트데이터를분류한결과를나타낸다.
[40] 도 8은메틸화그룹분류에관여하는프로브로 TCGA(the cancer genome atias)에 공개된간암데이터를분류한결과를나타낸다.
발명의실시를위한형태
[41] 이하하나이상의구체예를실시예를통하여보다상세하게설명한다.그러나, 이들실시예는하나이상의구체예를예시적으로설명하기위한것으로본 발명의범위가이들실시예에한정되는것은아니다.
[42]
[43] 실험방법
[44] 1.간세포암환자모집
[45] 본발명과관련하여수행된연구는서울대학교병원 (Seoul National University of Hospital)검토위원회의승인을받고,모든환자로부터서면동의서를받아 진행하였다. 2011년부터 2016년까지서울대학교병원외과에서간세포암 (hepatocellular carcinoma;이하, HCC로기재함)절제술을받은 184명의환자를 모집하고,수술후 CT스캔을통해깨끗한미세경계 (microscopic margins)및 종양의완전절제를확인하였다.상기환자들은정기적으로병원을방문하여 혈청종양마커,알파-태아단백 (a-fetoprotein, AFP)수치,조영 CT스캔 (contrast CT scans)또는자기공명영상 (magnetic resonance imaging, MRI)을포함하는표준 프로토콜을기반으로 3개월마다재발 (recurrence)여부를모니터링받았다.재발 여부는조기 (£1년)및후기 (>1년)재발로분류하였으며, HCC절제술후 1년 이내에재발한환자는제외시켰다.인구통계학적데이터와임상병리학적 특징은병원차트에서확인하였고,상기환자들은절제술이후사망할때까지 추적조사를받았다. 1년이내에재발한환자를제외한이유는조기재발의경우 HCC절제술이잘못되었거나,간암이외의이유로재발하는경우가많아암치료 후순수히정상간에서새로운암이재발하는데관여하는마커를발굴하기위한 본발명의목적에부합하지않기때문이다.
[46]
[47] 2.메틸화데이터생성
[48] 상기 182명의 HCC환자중에서수술후 1년이내에 HCC가재발한 42명은 분석에서제외하였다.남은 140명의환자에서수득한냉동 HCC샘플로부터 제조사의지시에따라 MagListo™ 5M게놈 DNA주줄키트 (Bioneer)를사용하여 DNA를추출하였다.각샘플마다 500 ng의 DNA를사용하여제조사의표준 프로토콜에따라 Illumina iScan System (Illumina, CA, USA)과함께 Illumina Infinium HumanMe比 lylation EPIC 850K BeadChip (Illumina)분석을수행하였다. 상기 Illumina Infinium HumanMe比 lylation EPIC BeadChips은모든단일 뉴클레오타이드의분해능 (resolution)을위해 85만개이상의 CpG사이트에대한 DNA메틸화값을포함한다.
[49]
[5이 3. DNA메틸화데이터가공
[51] 상기 2에서 Illumina Infinium HumanMethylation EPIC BeadChips으로얻은
데이터에대하여공개소프트웨어인 R늘랫픔 (https://cran.r-project.org/bin/ windows/base/;버전 3.3.2)에서 minfi R패키지를사용하여메틸화데이터에대한 사전-가공 (pre-processing)을수행하였다.구체적으로 HCC샘플의원본 (raw) IDAT파일을가공하고,배경보정및염료편차를정정하였다.이후메틸화및 비메틸화 (unmethylated)프로브의신호강도를측정하여각프로브의 DNA 메틸화값을 0 (비메틸화)내지 1 (완전메틸화)범위의 b-값 (b-value)으로 정량화하였다.다음으로모든샘플에대해데이터품질관리를수행하였으며, 140개샘플모두품질관리기준을통과했다.마지막으로,메틸화데이터는배치 효과문제 (batch effect problem)를줄이기위해기능적정규화방법 (functional normalization method)을사용하여정규화시켰다.
[52]
[53] 4. DNA메틸화값 (methylation values)
[54] 메틸화 b-값은통계분석을위해하기수학식 1에따라 M-값으로변환시켰다.
[55] [수학식 1]
[56] M-값 =log((b-값)/ (l-(b-값)))
[57] M-값은컨센서스클러스터링 (consensus clustering)에사용하고, b-값은히트맵 시각화및박스플롯생성에사용하였다.
[58]
[59] 5.컨센서스클러스터링
[60] 컨센서스클러스터링은 ConcensusClusterPlus (https://bioconductor.org/
packages/release/bioc八 dgnettes八〕 onsensusClusterPlus/inst八 ioc八〕 onsensusClusterPlus. pdf)를사용하여 HCC소그룹을확인하기위해수행하였다.입력값 (input)으로는 상위 3, 000개의가장가변적인프로브 (중앙값절대편차 (median absolute deviation, MAD))(MAD 3K)를사용하였다.
[61]
[62] 6.예후마커 (prognostic marker)선별
[63] 랜덤포레스트 (Random Forest)방법은비선형효과 (nonlinear effects)를
모델링하기위해개발된기계학습알고리즘을기반으로한다.본발명자들은 R 플랫폼의 랜덤포레스트 R패키지를사용하여좋거나나쁜예후를갖는 HCC 그룹을구별할수있는프로브를발굴하였고, HCC종양샘플을 4개의트레이닝 코호트 (cohort)와 1개의테스트코호트로무작위로나누어 5배교차
검증 (five-fold cross validation)을수행하였다.수행결과,본발명자들은랜덤 포레스트모델을구축하였고,각그룹의예상비율은혼돈행렬 (confusion matrix) (예측된샘플 vs관찰된샘플)에의해예측되었고,각모델의성능은곡선 아래면적 (area under the curve, AUC),민감도및특이도값에기초하여
측정하였다.
[64] 본발명자들은지니인덱스 (Gini index),프로브불순도 (impurity)의전체적감소 및랜덤포레스트로측정한변수중요도의도트차트를고려하여각프로브의 중요도값을측정하였다.그결과,본발명자들은 HCC샘플을메틸화그룹 1및 2(이하,각각 MG1및 MG2로기재함)로분류할수있는상위 50개의프로브를 발굴하였다 (도 4).이후하나의프로브와상위 50개프로브의성능효율을 비교하면서 AUC값을고려하여최대효율을지닌프로브의최소개수를 2020/175903 1»（：1/10公020/002727 확인하였다.
7.유전자온톨로지 및경로분석 (Gene ontology aM pathway analysis) 본발명자들은 innateDB (http://www.innatedb. com/)를사용하여다양한경로 검색 및유전자온톨로지분석을수행하였다.상기 innateDB에서는유전자 온톨로지 생물학적과정 (Gene Ontology biological processes), KEGG (Kyoto Encyclopedia of Genes and Genomes)및리액톰리소스 (Reactome resources)를 사용하였다.유의미한컷오프기준은 P-값＜0.05이었다.
8]
[69 ] 9.통계분석
이 범주형 변수 (categorical variable)의통계분석은피어슨카이 (¾2)검정또는피셔 정확검증을사용하여수행하였다.무-재발생존 (relapse-free survival, RFS)의 중간기간은카플란-메이어 방법으로계산하였고,서로다른그룹간의비교는 로그순위법 (log-rank tests)으로수행하였다. 실험결과
1.환자선별및기본특성
182명의 HCC환자중에서수술후 1년이내에 HCC가재발한 42명은분석에서 제외하였다. 140개 HCC샘플의 메틸화를확인한결과, HCC샘플은샘플간에 메틸화의 변이가큰반면,정상조직은메틸화가거의 일정하게나타나는것을 알수있었다 (도 1).
2. MG1과 MG2의 메틸화프로파일비교
] ] ] ] 140개 HCC샘플을 DNA메틸화패턴에 따라분류한결과,메틸화그룹 l(n=81) 7724565631
777777776666 및그룹 2(n=59)(이하,각각 MG1및 MG2로기재함)로나눠지는것을
확인하였다 (도 2의 A).또한, MG2의 메틸화프로파일은비종양성간조직의 메틸화프로파일과가장상이하였고, MG1의 메틸화프로파일은비종양성 간조직의 메틸화프로파일과유사하였다 (도 2의 B). MG1은무-재발생존 (RFS) 기간이 긴반면, MG2는무-재발생존이짧아서 예후가나쁜것을알수
있었다 (도 3)
[78] 이러한후성적 변화는신호전달, MAPK (mitogen-activated protein kinase)및 G 단백질-결합수용체 (GPCR)신호전달경로와관련이 있었다 (표 1).본
발명자들이상기그룹의 GO(gene ontology)시스템에 기초하여 일련의
유전자들을해석할때,상위 50개프로브는이화과정,신경전달물질분비,분자 기능의조절, Wnt신호전달경로,세포이동조절, mRNA대사과정,작은 (small) GTPase매개신호전달,유전자발현조절,세포사멸과정의조절과관련이 있었다. [79] [표 1]
Figure imgf000011_0001
[8이
[81] 3. HCC재발예측마커선별
[82] 변수중요도늘랏 (variable importance plot, varlmpPlot)을이용하여 HCC샘늘을 MG1및 MG2로분류할수있는상위 50개의프로브를발굴하였다 (도 4).이후 프로브수에따른성능효율을비교하면서 AUC(area under the curve)값을 고려하여최대효율을지닌프로브의최소개수를선택하였다.그결과,프로브 개수가 3개이상인경우간암재발예측의정확도 (accuracy)가 1에수렴하는것을 알수있었다 (도 5및표 2).아래표 2에기재된문자는각각정확도 (Accu.), 민감도 (Sen.)및특이도 (Spec.)를의미한다. 2020/175903
[83] [표 2]
Figure imgf000012_0001
[84] 상기표 2의결과를바탕으로최종적으로아래표 3에기재된프로브를 선별하였으며,프로브는중요도값이높은순서로기재하였다.
[85] [표 3]
Figure imgf000012_0002
[86] 아래표 4에표 3에기재된프로브의서열을기재하였다. 2020/175903
[87] [표 4]
Figure imgf000013_0002
마커가표적하는메틸화부위를의미함
Figure imgf000013_0001
[91] 랜덤포레스트방법을사용하여표 3에기재된프로브에대하여메틸화수준을 확인한결과,정상간조직（녹색）은메틸화수준이거의 100%에근접하고일정한 수준이며, ^1（31（적색）은정상간조직과유사한메틸화수준을보인반면,
MG2（회색）는메틸화수준이정상간조직에비해약 50%이하인것을확인할수 있었다（도 6; X축은선별된마커， V축은메틸화수준을의미하는 값）.
[92] 또한, 140개 ^0샘플을무작위로훈련데이터와검증데이터로나누고,표 3의프로브로다시테스트한결과,기존의 MG1은다시 MG1으로분류되고, 기존의 MG2또한다시 MG2로분류되는것을확인할수있었다（표 5）. 2020/175903 PCT/KR2020/002727
[93] [표 5]
Figure imgf000014_0001
본발명자가자체적으로생산한간암코호트데이터를상기표 3의프로브로 검증하였다.그결과,메틸화수준에따라간암코호트데이터가두개의 그룹（Pre_MGl및 Pre_MG2）으로분류되고, Pre_MG2에서재발율이높은것을 확인할수있었다（도 7의 A）.또한, RFS를확인한결과, Pre_MG2에비해 Pre_MGl의 RFS가유의하게긴것을확인할수있었다（p=0.0136;도 7의 B）.이 결과는본발명의프로브로간암의재발여부를성공적으로예측할수있음을 의미한다.
[96] 또한,표 3의프로브로공개데이터베이스인 TCGA（the cancer genome atlas） 간암데이터에대하여동일하게검증한결과,간암환자들이그룹（Pre_MGl및 Pre_MG2）으로분류되고（도 8의 A）,이들그룹은예후가상이한것을알수 있었다（도 8의 B）.
] ]
9945

Claims

2020/175903 1»（：1/10公020/002727 청구범위
［청구항 1］ 서열번호 1내지 4로표시되는 DNA메틸화마커로이루어진군에서
선택되는하나이상의 DNA메틸화마커를포함하는간암의재발예측용 조성물.
［청구항 2］ 제 1항에 있어서 ,상기간암의재발예측용조성물은 2개이상의 DNA
메틸화마커를포함하는것인,간암의재발예측용조성물.
［청구항 3］ 제 1항에 있어서,상기간암은간세포암（hepatocellular。0］선11011따）인것인, 간암의재발예측용조성물.
［청구항 4］ 제 1항에 있어서 ,상기간암의재발예측용조성물은간암환자의치료후 정상간에서간암의재발예후를예측하는것인,간암의재발예측용 조성물.
［청구항 5］ 知）분석대상간조직시료에서게놈 DNA를분리하는단계 ;
）서열번호 1내지 4로표시되는 DNA메틸화마커로이루어진군에서 선택되는하나이상의 DNA메틸화마커의메틸화수준을검출하는단계; 및
（0）상기검출된 DNA메틸화마커의메틸화수준을정상간조직에서 검출한메틸화수준과비교하는단계를포함하는,간암의재발예측방법. ［청구항 6］ 제 5항에 있어서 ,상기간암의재발예측방법은단계（비에서최소 2개
이상의 DNA메틸화마커의메틸화를확인하는것인,간암의재발예측 방법.
［청구항 7］ 제 5항에 있어서 ,상기간암의재발예측방법은단계（0）이후분석대상간 조직에서확인한 DNA메틸화마커의메틸화수준이정상간조직의 메틸화수준보다낮은경우간암의재발가능성이높은것으로판별하는 단계를추가로확인하는것인,간암의재발예측방법.
PCT/KR2020/002727 2019-02-28 2020-02-26 간암 재발 예측용 dna 메틸화 마커 및 이의 용도 Ceased WO2020175903A1 (ko)

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