JP5659342B2 - Method and kit for detection of malignant pleural mesothelioma - Google Patents

Description

  The present invention relates to methods and kits for the detection of malignant pleural mesothelioma based on abnormal DNA methylation.

  Malignant pleural mesothelioma (MPM) is an invasive tumor associated with asbestos exposure (Non-patent Documents 1 and 2). About 10,000 to 15,000 patients are newly diagnosed with MPM every year worldwide, and the number of patients is expected to increase within the next 20 years (Non-patent Documents 3 to 5). Inhalation of asbestos is a well-known risk factor, and early diagnosis of MPM is desired, but the absence of clinical symptoms and lack of useful diagnostic markers at an early stage makes early diagnosis difficult. Furthermore, MPM is sometimes pathologically difficult to distinguish from lung adenocarcinoma (AdCa) and may require additional immunohistochemical staining with an antibody panel (Non-Patent Document 6). Because of these difficulties and lack of effective treatment, many patients die within 2 years of diagnosis despite treatment (Non-Patent Documents 4, 7, and 8). Therefore, further molecular analysis of MPM is urgently needed to identify markers that are effective for accurate early diagnosis.

  The central mechanism by which MPM develops remains unclear. Several genetic abnormalities are thought to be involved in MPM, and such abnormalities include, for example, deletion of the p16 locus and mutation of the NF2 gene (Non-Patent Documents 9 to 11). Recent total transcriptome sequencing has estimated that about 6 genes transcribed are mutated in individual MPMs, which means that only a few genetic mutations cause MPM (Non-patent Document 12). Based on the above reports, gene mutations are infrequent in MPM, and mechanisms other than gene mutations are thought to be involved in MPM tumorigenesis.

  Epigenetic transcriptional control, particularly dysregulation of promoter DNA methylation, is frequently observed in human malignant tumors (Non-patent Document 13). Furthermore, the relationship between abnormal DNA methylation and inflammation has been described in many cancers (Non-patent Document 14). Asbestos does not directly induce malignant transformation of cultured human mesothelial cells (Non-patent Documents 15 and 16). It has also been found that chronic inflammation is caused by asbestos exposure (Non-patent Document 17). That is, the possibility that DNA methylation is involved in the onset of MPM is strongly suspected. However, there is currently limited information on DNA methylation abnormalities in MPM (Non-Patent Documents 18 to 20).

  Incidentally, Patent Documents 1, 2, and 3 that utilize an antibody against a specific polypeptide and a difference in the expression level of a specific gene are known as documents related to diagnosis or prognosis prediction of mesothelioma.

JP2007-071849 Special table 2008-505862 Special table 2003-524021

Robinson BW, Musk AW, Lake RA.Malignant mesothelioma. Lancet 2005; 366: 397-408 Pass HI, Vogelzang N, Hahn S, Carbone M. Malignant pleural mesothelioma. Curr Probl Cancer 2004; 28: 93-174 Tsiouris A, Walesby RK.Malignant pleural mesothelioma: current concepts in treatment. Nat Clin Pract Oncol 2007; 4: 344-52 Robinson BW, Lake RA. Advances in malignant mesothelioma. N Engl J Med 2005; 353: 1591-603 Bianchi C, Bianchi T. Malignant mesothelioma: global incidence and relationship with asbestos.IndHealth 2007; 45: 379-87 Abutaily AS, Addis BJ, Roche WR.Immunohistochemistry in the distinction between malignant mesothelioma and pulmonary adenocarcinoma: a critical evaluation of new antibodies.J Clin Pathol 2002; 55: 662-8 Vogelzang NJ, Rusthoven JJ, Symanowski J, et al. Phase III study of pemetrexed in combination with cisplatin versus cisplatin alone in patients with malignant pleural mesothelioma. J Clin Oncol 2003; 21: 2636-44 van Meerbeeck JP, Gaafar R, Manegold C, et al. Randomized phase III study of cisplatin with or without raltitrexed in patients with malignant pleural mesothelioma: an intergroup study of the European Organization for Research and Treatment of Cancer Lung Cancer Group and the National Cancer Institute of Canada. J Clin Oncol 2005; 23: 6881-9 Cheng JQ, Jhanwar SC, Klein WM, et al. P16 alterations and deletion mapping of 9p21-p22 in malignant mesothelioma.Cancer Res 1994; 54: 5547-51.10. Sekido Y, Pass HI, Bader S, et al. Neurofibromatosis type 2 (NF2) gene is somatically mutated in mesothelioma but not in lung cancer.Cancer Res 1995; 55: 1227-31 Sekido Y, Pass HI, Bader S, et al. Neurofibromatosis type 2 (NF2) gene is somatically mutated in mesothelioma but not in lung cancer.Cancer Res 1995; 55: 1227-31 Bianchi AB, Mitsunaga SI, Cheng JQ, et al. High frequency of inactivating mutations in the neurofibromatosis type 2 gene (NF2) in primary malignant mesotheliomas.Proc Natl Acad Sci U S A 1995; 92: 10854-8 Sugarbaker DJ, Richards WG, Gordon GJ, et al.Transcriptome sequencing of malignant pleural mesothelioma tumors.Proc Natl Acad Sci U S A 2008; 105: 3521-6 Jones PA, Baylin SB.The fundamental role of epigenetic events in cancer.Nat Rev Genet 2002; 3: 415-28 Perwez Hussain S, Harris CC. Inflammation and cancer: an ancient link with novel potentials.Int J Cancer 2007; 121: 2373-80 Xu L, Flynn BJ, Ungar S, et al. Asbestos induction of extended lifespan in normal human mesothelial cells: interindividual susceptibility and SV40 T antigen.Carcinogenesis 1999; 20: 773-83 Bocchetta M, Di Resta I, Powers A, et al. Human mesothelial cells are unusually susceptible to simian virus 40-mediated transformation and asbestos cocarcinogenicity.Proc Natl Acad Sci U S A 2000; 97: 10214-9 Yang H, Bocchetta M, Kroczynska B, et al. TNF-alpha inhibits asbestos-induced cytotoxicity via a NF-kappaB-dependent pathway, a possible mechanism for asbestos-induced oncogenesis.Proc Natl Acad Sci U S A 2006; 103: 10397-402 Toyooka S, Pass HI, Shivapurkar N, et al. Aberrant methylation and simian virus 40 tag sequences in malignant mesothelioma. Cancer Res 2001; 61: 5727-30 Tsou JA, Galler JS, Wali A, et al. DNA methylation profile of 28 potential marker loci in malignant mesothelioma. Lung Cancer 2007; 58: 220-30 Tsou JA, Shen LY, Siegmund KD, et al.Distinct DNA methylation profiles in malignant mesothelioma, lung adenocarcinoma, and non-tumor lung.Lung Cancer 2005; 47: 193-204

  The object of the present invention is to provide a method for the detection of malignant pleural mesothelioma.

  To understand more about DNA methylation in MPM, we have developed a methylated CpG island amplification microarray (MCAM) (Shen L, Kondo Y, Guo Y, et al. PLoS Genet 2007; 3 : 2023-36) was used to perform extensive screening for abnormally methylated genes in MPM. MCAM enables the successful detection of methylated genes not only in cancer tissues but also in normal tissues and provides highly efficient and reproducible results. In addition, the inventors examined AdCa methylation to compare the role of DNA methylation abnormalities in two types of breast cancer. Analysis of DNA methylation profile shows that abnormal DNA methylation is less frequent in MPM compared to AdCa, and AdCa frequently methylates common genes among cases, but MPM It was clearly shown that there are few common methylated genes. The above results were examined in detail, and among the hypermethylated genes found in MCAM, three genes that were specifically methylated by MPM but not AdCa were identified. These genes should serve as early diagnostic markers for MPM.

Therefore, in summary, the present invention includes the following features.
The present invention, in the first aspect, is a method for detecting malignant pleural mesothelioma, wherein in a biological sample from a subject, at least selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene Detecting the methylation of one gene, and determining that the gene is a malignant pleural mesothelioma when the gene is methylated.

  In the second aspect, the present invention also relates to a method for determining the prognosis of a subject suffering from malignant pleural mesothelioma, comprising a TMEM30B gene, a KAZALD1 gene, and a MAPK13 gene in a biological sample from the subject. Measuring the degree of methylation of at least one gene selected from the group, wherein the prognosis of the disease is good when the degree of methylation of the gene is low compared to the degree of methylation of subjects with poor prognosis And providing the above method.

  In each of the above two invention embodiments, the above method detects or measures the methylation of the base sequence of the CpG region of the TMEM30B gene, KAZALD1 gene, or MAPK13 gene promoter.

  In another embodiment, the base sequence of the CpG region of the promoter includes the base sequence shown in SEQ ID NO: 78, 79 or 80, or a deletion, substitution or addition of one or several bases in the base sequence. And a base sequence having promoter activity.

In another embodiment, the methylation is detected by a methylation specific PCR method.
In another embodiment, a primer for use in the PCR method described above is a deletion, substitution or substitution of one or several bases in the base sequence shown in SEQ ID NO: 78, 79 or 80, or in the base sequence. A sequence consisting of consecutive 17 to 35 bases in the base sequence containing an addition and having promoter activity is selected as a methylation specific primer and / or an unmethylation specific primer.

  In another embodiment, the sample is serum, pleural effusion, bronchial lavage fluid or affected tissue.

In the third aspect, the present invention is a kit for use in any one of the above methods, wherein methylation of at least one gene selected from the group consisting of a TMEM30B gene, a KAZALD1 gene, and a MAPK13 gene is performed. A kit comprising the following primer set for methylation-specific PCR that can be measured is provided.
Methylation specific primer for TMEM30B gene
TTGGGAGGGTGTGGGTATTGTTC (SEQ ID NO: 66)
ACGCGCGAACTAACCGAAT (SEQ ID NO: 67)
CTGGGAGGGTGTGGGCACTGCTCG (SEQ ID NO: 81)
CGAGTAGTTTTCGGGTTTGC (SEQ ID NO: 95)
ACCGACGCGCGAACTAAC (SEQ ID NO: 96)
Unmethylated specific primer for TMEM30B gene
GGAATTGGGAGGGTGTGGGTATTGTTT (SEQ ID NO: 68)
ACCTCCCTCTCCACACCAC (SEQ ID NO: 69)
GGAACTGGGAGGGTGTGGGCACTGCT (SEQ ID NO: 82)
TGAGTAGTTTTTGGGTTTGT (SEQ ID NO: 97)
ACCATAACACTCCAAATCATAACA (SEQ ID NO: 98)
Methylation specific primer for KAZALD1 gene
GCGGGTCGTAGTATTTGTCG (SEQ ID NO: 70)
AACAAAACCAACCACCTTCG (SEQ ID NO: 71)
CGGGTCGTAGTATTTGTC (SEQ ID NO: 85)
GGTAAGTTTGCGGTCGTTTTC (SEQ ID NO: 99)
AACAAAACCAACCACCTTCG (SEQ ID NO: 100)
Unmethylated specific primer for KAZALD1 gene
TTATTTGTGGGTTGTAGTATTTGTT (SEQ ID NO: 72)
AAACCAACCACCTTCATCTCC (SEQ ID NO: 73)
TTATTCGCGGGTCGTAGTATTTGTC (SEQ ID NO: 86)
GTGGGTAAGTTTGTGGTTG (SEQ ID NO: 101)
AACAAAACCAACCACCTTCATCT (SEQ ID NO: 102)
Methylation specific primers for MAPK13 gene
CGTGTTTTCGACGTACGTCGGTAGC (SEQ ID NO: 74)
ACCGCTAAATAACCCCGAAA (SEQ ID NO: 75)
CGTGTCCCCGACGCACGTCGGCAGC (SEQ ID NO: 89)
Unmethylated specific primer for MAPK13 gene
GGTTTTGTTGGGTAGTTTT (SEQ ID NO: 76)
TCCCACCTACCAACTCACC (SEQ ID NO: 77)
GGTCCCGCTGGGCAGCCC (SEQ ID NO: 90)

  The present invention provides a method for detecting malignant pleural mesothelioma that makes it possible to distinguish malignant pleural mesothelioma from lung cancer. This method is based on measuring the methylation of at least one gene selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene.

This figure shows the MCAM analysis and its effectiveness in malignant mesothelioma cell lines. FIG. 1A is an overview of MCAM. DNA from cancer or normal tissue was digested sequentially with SmaI and XmaI. After amplification of the methylated DNA fragment, the MCA product was labeled with Cy5 (red) for cancer tissue and Cy3 (green) for normal tissue, and then used for promoter microarray. This figure shows the MCAM analysis and its effectiveness in malignant mesothelioma cell lines. FIG. 1B shows a comparison of MCAM signal ratio and methylation level. The Y axis shows the signal ratio of MCAM in each gene. Methylation levels determined by pyrosequencing analysis were expressed as absolute variables. The horizontal line indicates an MCAM signal ratio of 2.0. This figure shows the MCAM analysis and its effectiveness in malignant mesothelioma cell lines. FIG. 1C shows representative pyrograms of three hypermethylated genes. Regions shown in gray indicate CpG sites quantified by each gene, and the% methylation of each site is shown above the peak. The calculated value of the average methylation at the CpG site is shown in parentheses. This figure shows the MCAM analysis and its effectiveness in malignant mesothelioma cell lines. FIG. 1D shows the reactivation of hypermethylated genes by inhibition of DNA methylation or histone deacetylation. Genes in normal mesothelial tissue (Normal) and ACC-MESO-1 (Meso1) after treatment with PBS (Control, C) or 5-Aza-dC (D), or Trichostatin A (T) Expression was measured by quantitative-PCR. The relative value of mRNA expression of each gene relative to GAPDH is shown on the Y axis (left column). 5-Aza-dC treatment effectively reactivated the silenced gene. The Y axis in the right column shows the relative value of RNA expression of treated cells relative to the control. Error bars on the graph indicate standard deviation from 3 experiments. This figure shows a scatter plot analysis of signal intensity (log scale) between normal mesothelial and normal lung tissue (A), between MPM and AdCa (B), and between MPM and liver cancer (C). The multiple correlation determination coefficient (R ² ) of the linear regression model is shown for each analysis. This figure shows the results of MCAM analysis in MPM and AdCa patients. The upper column of FIG. 3A shows DNA methylation from 40 samples (20 samples of MPM are shown in blue boxes and 20 samples of AdCa are shown in white boxes) using all 6,161 genes (Y axis). An overview of the dendrogram and heat map of hierarchical cluster analysis of data is presented. Each cell in the matrix represents the DNA methylation status of a gene in an individual sample. The red and green colors in the cell reflect the high and low methylation levels, respectively. Here, the methylation level is shown as a scale bar below the matrix (log2 conversion scale). Cases with less than 300 genes methylated with MPM are indicated by black circles. Among AdCa cases, cases in which more than 950 genes are methylated are indicated by white diamond boxes. The middle column shows the subclass classification in each tumor using a hierarchical cluster. 20 samples of MPM were analyzed using all 6,161 genes. The Y axis shows the similarity between cases. The black circle shows the same MPM case as in the figure above. Boxes indicate histological subtypes of MPM, thin line hatching, thick line hatching, black and white boxes represent epithelium, biphasic, sarcoma-like and specialized types, respectively. The bottom column shows AdCa clustering, where the gray and white boxes indicate smokers and non-smokers, respectively. The Y axis shows the similarity between cases. The open diamond box shows the same AdCa case as in the figure above. This figure shows the results of MCAM analysis in MPM and AdCa patients. FIG. 3B shows the number of methylated genes in each case. Dashed lines represent the average number of methylated genes (387 genes and 544 genes for MPM and AdCa, respectively). This figure shows the results of MCAM analysis in MPM and AdCa patients. FIG. 3C shows the number of genes (Y axis) commonly methylated by the number of cases x (X axis) in MPM (gray bar) or AdCa (black bar). This figure shows the results of MCAM analysis in MPM and AdCa patients. FIG. 3D shows a Kaplan-Meier analysis of MPM patient survival. MPM patients were divided into two groups according to the number of methylated genes. Statistical comparison of survival rates by log rank statistics between the two groups showed that cases with high methylation (dashed line, patients with 387 or more genes), but cases with low methylation (solid line, 387) Patients with less genes; P = 0.01), indicating poorer survival. This figure shows the identification of methylation specific for MPM. FIG. 4A shows hierarchical clustering (8 genes and 34 genes for MPM and AdCa, respectively) performed using 42 specifically methylated genes in each tumor. This figure shows the identification of methylation specific for MPM. FIG. 4B shows a diagram of the promoters of the three selected genes. Each perpendicular represents a single CpG site. The transcription start site (arrow), exon 1 position (grey box), restriction enzyme site (arrowhead), and MSP assay position (bar) are indicated. This figure shows the identification of methylation specific for MPM. FIG. 4C shows MSP analysis of TMEM30B, KAZALD1 and MAPK13 with 10 MPM samples and 10 AdCa samples used for MCAM analysis. DNA methylation was detected in MPM cases. In contrast, only one obscure methylation band was detected in patient 6's TMEM30B gene. M, methylated form; UM, unmethylated form; P, methylated positive control (M) is SssI-treated DNA, and unmethylated control (UM) is DNA derived from normal lymphocytes; N, Does not contain DNA template. This figure shows the identification of methylation specific for MPM. FIG. 4D shows MSP analysis (10 MPM and 30 AdCa) of patients from another cohort. M, UM and N have the same meaning as in 4C above; S, SssI-treated DNA.

(Detection of malignant pleural mesothelioma)
The present invention is a method for detecting malignant pleural mesothelioma, wherein in a biological sample from a subject, methylation of at least one gene selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene Wherein the method is determined to be malignant pleural mesothelioma when the gene is methylated.

  As used herein, malignant pleural mesothelioma is a tumor of the mesothelial cells that make up the pleura and is thought to develop due to inhalation of asbestos associated with long-term exposure to asbestos (asbestos). Common symptoms of malignant pleural mesothelioma include pleural effusion, chest pain, cough, and dyspnea. In addition, the hyaluronic acid content in pleural fluid tends to be high.

  DNA methylation has been proposed as a powerful marker for MPM diagnosis (Toyooka S, Pass HI, Shivapurkar N, et al., Cancer Res 2001; 61: 5727-30; Tsou JA, Shen LY, Siegmund KD, et al., Lung Cancer 2005; 47: 193-204.18, 20). However, previous studies on the methylation status of malignant pleural mesothelioma (MPM) and lung adenocarcinoma (AdCa), although there is a difference in the frequency, the aberrant methylation of the candidate marker to some extent in both MPM and AdCa It was shown to be detected. Furthermore, no specific methylation marker for MPM has ever been reported. This time, we analyzed the DNA methylation profile in the whole genome region simultaneously with MPM and AdCa, and that abnormal methylation at a specific locus was frequently detected in MPM, and three genes (MEM30B KAZALD1 and MAPK13 genes) were found to be specifically methylated by MPM.

  TMEM30B has been reported as a highly methylated gene in human melanoma cell lines by the methylation-sensitive representational difference analysis method (Furuta J, Nobeyama Y, Umebayashi Y, Otsuka F, Kikuchi K, Ushijima T ., Cancer Res 2006; 66: 6080-637).

  KAZALD1 is involved in osteoblast proliferation during bone formation and regeneration (Shibata Y, Tsukazaki T, Hirata K, Xin C, Yamaguchi A., Biochem Biophys Res Commun 2004; 325: 1194-20038).

  MAPK13 is a member of the MAP kinase family and was found to be dysregulated in immune deficiencies, centromere region destabilization, and facial abnormalities (Ehrlich M, Sanchez C, Shao C, et al., Autoimmunity 2008; 41: 253-71).

  By detecting methylation of three specific genes (TMEM30B gene, KAZALD1 gene and MAPK13 gene), the present invention can easily determine whether it is malignant pleural mesothelioma or lung adenocarcinoma. Among these cancers that could not be differentiated, malignant pleural mesothelioma could be specifically detected. That is, the present invention provides a genetic marker that enables detection of malignant pleural mesothelioma. It should be noted that abnormal methylation of KAZALD1 and MAPK13 genes among these genes has never been reported in human cancer.

  In the present specification, the subject includes a human patient suffering from malignant pleural mesothelioma or a human suspected of having the disease.

  In the present specification, the biological sample includes, for example, serum, pleural effusion, bronchial lavage fluid, or affected tissue (particularly pleural tissue) collected from a subject ex vivo and optionally pretreated.

  The base sequences of the above three genes of the present invention can be obtained, for example, by accessing the following registration numbers from GenBank (US NCBI).

For human TMEM30B gene, NW_925561, NT_025437, etc.
For the human KAZALD1 gene, NW_924884, NT_030059, etc.
For the human MAPK13 gene, NW_923073, NT_007592 and the like.

  In the method of the present invention, methylation of at least one of the above genes is detected.

  A preferred methylation site on the gene is the CpG region of the promoter of the TMEM30B gene, KAZALD1 gene or MAPK13 gene, and methylation of the base sequence in this region is detected or measured. The CpG region of the promoter of these genes includes, for example, (1) a nucleotide sequence represented by SEQ ID NO: 78, 79 or 80, or (2) deletion or substitution of one or several bases in the nucleotide sequence. Or a nucleotide sequence containing an addition, or a nucleotide sequence having at least 95%, preferably at least 97%, more preferably at least 98% identity with the nucleotide sequence and having a promoter activity .

  As used herein, a “promoter CpG region” is a region rich in CG sequences, eg, a region containing about 20-35% or more C + G bases. “Promoter activity” refers to an activity that controls transcription of a gene.

“Several” as used herein refers to an integer in the range of 2-10.
As used herein, “identity” includes the number of gaps when two base sequences are aligned with or without introducing gaps so that the degree of identity is maximized. It means the percentage (%) of the number of identical (ie, matching) bases relative to the total number of bases.

  Methylation in the method of the present invention is performed by, for example, methylation-specific PCR (JG Herman et al., Proc. Natl. Acad. Sci. USA 1996, 93: 9821-9826; CA Eads et al., Nucleic Acids Res. 2000, 28: E32; K. Rand et al., Methods 2002, 27: 114-120; DT Akey et al., Genomics 2002, 80: 376-384). The level of methylation can be measured by, for example, the pyrosequencing method (S. Colella et al., Biotechniques 2003, 35: 146-150; J. Tost et al., Biotechniques 2003, 35: 152-156). .

  Methylation-specific PCR (MSP) is a method for examining the presence or absence of methylation by performing PCR using DNA treated with sodium bisulfite as a template. Sodium bisulfite converts cytosine on DNA to uracil, but this conversion reaction does not occur in methylated cytosine (methylation at the 5 ′ position of the cytosine residue of CpG).

  Two types of PCR primers are used: a methylation specific primer set that is amplified when methylated and an unmethylated specific primer set that is amplified when not methylated. Specifically, as described above, these primers can be selected on the basis of the gene sequence of the promoter CpG region that controls transcription, and can be prepared by using, for example, an automatic DNA synthesizer.

  As for the primer for use in the PCR method, for example, the base sequence shown in SEQ ID NO: 78, 79 or 80, or a base sequence containing a deletion, substitution or addition of one or several bases in the base sequence In the base sequence having at least 95%, preferably at least 97%, more preferably at least 98% identity with the base sequence, and in the base sequence having promoter activity, 17 to A sequence consisting of 35 bases, preferably 20-30 bases, can be selected as a methylation specific primer and / or an unmethylation specific primer.

  After amplification by PCR, the presence or absence of methylation is determined by comparing the ratio of amplification products from these two primer sets. That is, when an amplification product by a methylation specific primer is detected in a test sample, it is determined that the gene in question is methylated. This primer is effective in amplifying and detecting a sequence close to the original sequence. On the other hand, the unmethylated specific primer is effective in detecting a sequence changed by treatment with sodium bisulfite. Furthermore, PCR amplification is performed regardless of the presence or absence of methylation as a qualitative evaluation of DNA after treatment with sodium bisulfite of a test sample, for example, LINE1 primer (for example, LINE1-Fwd: TTTTAAAGTTGTTAGATAGGGATATTTAAGTTTGTA (SEQ ID NO: 91); LINE1- When using a primer such as Rev: AAAAACCTACCTACCTCTATAAACTCCACC (SEQ ID NO: 92)), quantitative diagnosis of methylated DNA is possible by the ratio of (amplification product by methylation-specific primer) to (amplification product by LINE1 primer).

  Furthermore, in addition to the PCR described above, quantitative PCR can also be performed, which can be used to eliminate the influence caused by nonspecific amplification of normal DNA. Examples of primers for quantitative PCR are: SEQ ID NO: 83 (methylated primer), SEQ ID NO: 84 (unmethylated primer) for TMEM30B gene, SEQ ID NO: 87 (methylated primer), SEQ ID NO: 88 (for KAZALD1 gene) Unmethylated primer).

  The primer set that can be used in the present invention is a base sequence of human TMEM30B gene (NW_925561, NT_025437, etc.), human KAZALD1 gene (NW_924884, NT_030059, etc.), or human MAPK13 gene (NW_923073, NT_007592, etc.), preferably each of these genes About 17 to about 35 bases, preferably about 20 to 30 including at least one methylated CpG in the base sequence of the CpG region of the promoter, more preferably the base sequence comprising SEQ ID NO: 78, 79 or 80 An arbitrarily selected primer consisting of a base sequence is included.

Non-limiting examples of the above primer set are as follows.
Methylation specific primers for the TMEM30B gene:
TTGGGAGGGTGTGGGTATTGTTC (SEQ ID NO: 66)
ACGCGCGAACTAACCGAAT (SEQ ID NO: 67)
CTGGGAGGGTGTGGGCACTGCTCG (SEQ ID NO: 81)
CGAGTAGTTTTCGGGTTTGC (SEQ ID NO: 95)
ACCGACGCGCGAACTAAC (SEQ ID NO: 96)
Unmethylated specific primer for TMEM30B gene
GGAATTGGGAGGGTGTGGGTATTGTTT (SEQ ID NO: 68)
ACCTCCCTCTCCACACCAC (SEQ ID NO: 69)
GGAACTGGGAGGGTGTGGGCACTGCT (SEQ ID NO: 82)
TGAGTAGTTTTTGGGTTTGT (SEQ ID NO: 97)
ACCATAACACTCCAAATCATAACA (SEQ ID NO: 98)
Methylation specific primer for KAZALD1 gene
GCGGGTCGTAGTATTTGTCG (SEQ ID NO: 70)
AACAAAACCAACCACCTTCG (SEQ ID NO: 71)
CGGGTCGTAGTATTTGTC (SEQ ID NO: 85)
GGTAAGTTTGCGGTCGTTTTC (SEQ ID NO: 99)
AACAAAACCAACCACCTTCG (SEQ ID NO: 100)
Unmethylated specific primer for KAZALD1 gene
TTATTTGTGGGTTGTAGTATTTGTT (SEQ ID NO: 72)
AAACCAACCACCTTCATCTCC (SEQ ID NO: 73)
TTATTCGCGGGTCGTAGTATTTGTC (SEQ ID NO: 86)
GTGGGTAAGTTTGTGGTTG (SEQ ID NO: 101)
AACAAAACCAACCACCTTCATCT (SEQ ID NO: 102)
Methylation specific primers for MAPK13 gene
CGTGTTTTCGACGTACGTCGGTAGC (SEQ ID NO: 74)
ACCGCTAAATAACCCCGAAA (SEQ ID NO: 75)
CGTGTCCCCGACGCACGTCGGCAGC (SEQ ID NO: 89)
Unmethylated specific primer for MAPK13 gene
GGTTTTGTTGGGTAGTTTT (SEQ ID NO: 76)
TCCCACCTACCAACTCACC (SEQ ID NO: 77)
GGTCCCGCTGGGCAGCCC (SEQ ID NO: 90)

  On the other hand, the pyrosequencing method is a method for determining a bisulfite conversion sequence of a specific CpG site in this region after PCR amplification of a target region on a gene. In this method, the C to T ratio of individual sites is quantitatively determined based on the amount of C and T incorporation during sequence extension. Specifically, this method can be performed with a Qiagen Pyrosequencer.

For PCR conditions, a general method can be used. That is, in PCR, about 20 to 40 cycles are performed with denaturation, annealing, and extension reactions as one cycle. Denaturation is a process in which double-stranded template DNA is separated into single strands by heating, for example, at 94 to 96 ° C. for about 5 seconds to about 10 minutes. Annealing is a step of annealing a forward primer or a reverse primer on each side of a single-stranded template DNA, and is performed by heating at about 50 to 65 ° C. for about 5 seconds to 60 seconds. The extension reaction is a step of synthesizing DNA by extending a primer along a template DNA, and is usually performed by heating at 72 to 77 ° C. for about 30 seconds to 10 minutes. The solvent for PCR is an Mg ²⁺ containing buffer, to which a thermostable DNA polymerase enzyme (for example, Taq polymerase) and dNTPs (N = A, T, G, C) are added. At the beginning of the PCR cycle, for example, heating may be performed at 94 to 96 ° C. for about 30 seconds to 10 minutes, or at the end of the final cycle at 72 to 77 ° C. for about 2 to 10 minutes. Good. Suitable PCR conditions vary depending on the primer. For example, the annealing temperature of the TMEM30B methylated primer is 55 ° C., and the non-methylated primer is 65 ° C. It is convenient to use an amplification device such as a thermal cycler for PCR.

  PCR products can be visualized on ethidium bromide stained, 6% polyacrylamide gels or 3% agarose gels.

  According to the method of the present invention, when at least one of the above genes is methylated, it is determined as malignant pleural mesothelioma. Since these genes are not methylated in lung adenocarcinoma, malignant pleural mesothelioma can be easily differentiated from lung adenocarcinoma by detecting the methylation of these genes.

(Measure prognosis of subjects with malignant pleural mesothelioma)
The present invention further relates to a method for determining the prognosis of a subject suffering from malignant pleural mesothelioma, wherein the biological sample from the subject is at least selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene Measuring the degree of methylation of one gene, and determining that the prognosis of the disease is good when the degree of methylation of the gene is lower than the degree of methylation of a subject with a poor prognosis I will provide a.

  According to the present invention, the prognosis of a subject suffering from malignant pleural mesothelioma can be determined by measuring the degree of methylation of any of the above three genes, that is, the level of methylation. This is based on the abnormal methylation of the gene when the prognosis for the tumor is poor. Conversely, when the prognosis is good, the level of methylation of the gene is relatively low compared to the case of a poor prognosis.

  As a method for determining the prognosis, in order to measure the degree of methylation of at least one human gene selected from the group consisting of the MEM30B gene, the KAZALD1 gene and the MAPK13 gene, for example, the above methylation-specific PCR method and / or Alternatively, the pyrosequencing method can be used. Examples of these methods and primers are as described above.

  As described above, the biological sample is specifically serum, pleural effusion, bronchial lavage fluid or affected tissue (particularly pleural tissue).

(kit)
The present invention further provides a kit for use in any of the above methods, and is capable of measuring methylation of at least one gene selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene. A kit comprising the following primer set for methylation specific PCR is provided.
Primer set:
Methylation specific primer for TMEM30B gene
TTGGGAGGGTGTGGGTATTGTTC (SEQ ID NO: 66)
ACGCGCGAACTAACCGAAT (SEQ ID NO: 67)
CTGGGAGGGTGTGGGCACTGCTCG (SEQ ID NO: 81)
CGAGTAGTTTTCGGGTTTGC (SEQ ID NO: 95)
ACCGACGCGCGAACTAAC (SEQ ID NO: 96)
Unmethylated specific primer for TMEM30B gene
GGAATTGGGAGGGTGTGGGTATTGTTT (SEQ ID NO: 68)
ACCTCCCTCTCCACACCAC (SEQ ID NO: 69)
GGAACTGGGAGGGTGTGGGCACTGCT (SEQ ID NO: 82)
TGAGTAGTTTTTGGGTTTGT (SEQ ID NO: 97)
ACCATAACACTCCAAATCATAACA (SEQ ID NO: 98)
Methylation specific primer for KAZALD1 gene
GCGGGTCGTAGTATTTGTCG (SEQ ID NO: 70)
AACAAAACCAACCACCTTCG (SEQ ID NO: 71)
CGGGTCGTAGTATTTGTC (SEQ ID NO: 85)
GGTAAGTTTGCGGTCGTTTTC (SEQ ID NO: 99)
AACAAAACCAACCACCTTCG (SEQ ID NO: 100)
Unmethylated specific primer for KAZALD1 gene
TTATTTGTGGGTTGTAGTATTTGTT (SEQ ID NO: 72)
AAACCAACCACCTTCATCTCC (SEQ ID NO: 73)
TTATTCGCGGGTCGTAGTATTTGTC (SEQ ID NO: 86)
GTGGGTAAGTTTGTGGTTG (SEQ ID NO: 101)
AACAAAACCAACCACCTTCATCT (SEQ ID NO: 102)
Methylation specific primers for MAPK13 gene
CGTGTTTTCGACGTACGTCGGTAGC (SEQ ID NO: 74)
ACCGCTAAATAACCCCGAAA (SEQ ID NO: 75)
CGTGTCCCCGACGCACGTCGGCAGC (SEQ ID NO: 89)
Unmethylated specific primer for MAPK13 gene
GGTTTTGTTGGGTAGTTTT (SEQ ID NO: 76)
TCCCACCTACCAACTCACC (SEQ ID NO: 77)
GGTCCCGCTGGGCAGCCC (SEQ ID NO: 90)

  In addition to the primers described above, the kit of the present invention includes, for example, a buffer, a heat-resistant DNA polymerase enzyme, dNTPs (N = A, T, C, G), instructions for use, etc. necessary for PCR. be able to. Primers can be packaged alone or in combination.

(Example)
The present invention will be specifically described by the following examples, but the scope of the present invention is not limited by these examples.

<Materials and methods>
cell
MPM cells (ACC-MESO-1) (Usami N, Fukui T, Kondo M, et al. Cancer Sci 2006; 97: 387-94) and non-malignant mesothelial cells (MeT-5A) are used for analysis did. MeT-5A is available as ATCC CRL-9444 from ATCC (American Type Culture Collection, Rockville, MD, USA). ACC-MESO-1 was prepared at 37 ° C in RPMI-1640 medium (Sigma-Aldrich, St Louis, MO) supplemented with 10% fetal calf serum (Invitrogen, Carlsbad, CA, USA) and antibiotic-antimycotic (Invitrogen). The cells were cultured in a humid incubator containing 5% CO ₂ . MeT-5A was cultured according to the conditions of the ATCC instructions.

Tissue sample
31 MPM samples and 51 AdCa samples (all from Japanese patients), Aichi Cancer Center Hospital, Nagoya University Hospital, Nagoya Daiichi Red Cross Hospital, Nagoya Daini Red Cross Hospital, Kasugai Municipal Hospital, Ogaki Municipal Obtained from hospitals and Okayama Industrial Hospital. Samples and clinical data were collected after approval by the appropriate institutional review group and written informed consent from all patients.

DNA preparation Genomic DNA was extracted using a standard phenol-chloroform method. Fully methylated DNA was prepared by treating genomic DNA with M. SssI methylase (New England Biolabs, Ipswich, Mass.). Briefly, 5 μg of DNA was added to 20 μM M. SssI methylase, 320 μM S-adenosylmethionine (SAM, New England Biolabs) and NEB buffer 2 (New England Biolabs) for a total of 300 μl 37 Incubated at 0 ° C. During the incubation, the same amounts of M. SssI methylase and SAM were added once more to ensure DNA methylation reaction. Unmethylated DNA was prepared by treating genomic DNA with phi29 DNA polymerase (GenomiPhi DNA Amplification Kit; Amersham Biosciences, Uppsala, Sweden) according to the manufacturer's instructions.

Methylated CpG island amplified microarray (MCAM)
We performed 20 samples of MPM (45-78 years, average age 59.1 years) and 20 samples of AdCa (44-76 years, average age 62.8 years) for MCAM analysis. The detailed protocol of MCM followed the method described so far (Shen L, Kondo Y, Guo Y, et al. PLoS Genet 2007; 3: 2023-3621; Gao W, Kondo Y, Shen L, et al., Carcinogenesis 2008; 29: 1901-10). Briefly, 2 μg genomic DNA was digested with 100 U methylation sensitive restriction endonuclease SmaI (New England Biolabs). This enzyme cleaves unmethylated DNA leaving a blunt end (CCC / GGG). The DNA was then digested with 50 U methylation-insensitive restriction endonuclease XmaI. This enzyme leaves a sticky end (C / CCGGG). An adapter was bound to the sticky end. The adapters are oligonucleotides RMCA12 (5′-CCGGGCAGAAAG-3 ′ (SEQ ID NO: 93)) and RMCA24 (5′-CCACCGCCATCCGAGCCTTTCTGC-3 ′ (SEQ ID NO: 94)) (Toyota, M. et al., Cancer Res. 59: 2307-2312, 1999) was incubated at 65 ° C. for 2 minutes and then cooled to room temperature in 60 minutes. Digested DNA was ligated to the adapter using T4 DNA ligase (Invitrogen, Carlsbad, Calif.) And amplified by PCR using RMCA24 primer. PCR conditions were such that the adapter-bound DNA fragment was overhanged by heating at 72 ° C for 5 minutes, followed by heating at 95 ° C for 3 minutes, followed by 95 ° C for 1 minute and 77 ° C for 3 minutes. Minutes were cycled 25 times, and finally an extension reaction was performed at 72 ° C. for 10 minutes. We used an Agilent Technologies custom promoter array (G4497A, Agilent Technologies, Santa Clara, Calif.) Containing 15,134 probes corresponding to 6,161 unique genes. This array has been demonstrated for effectiveness in previous studies with MCAM (Gao W, Kondo Y, Shen L, et al., Carcinogenesis 2008; 29: 1901-10). The microarray protocol used heretofore was used (Gao W, Kondo Y, Shen L, et al., Carcinogenesis 2008; 29: 1901-10). Briefly, the MCA product was labeled with cancer tissue-derived DNA with Cy5 (red) and normal tissue-derived DNA with Cy3 (green). As normal controls, 2 samples of normal mesothelial tissue DNA for MPM or 5 samples of normal lung tissue DNA for AdCa were used. After labeling with a dye, the labeled sample was hybridized to the array together with human Cot-1 DNA (Invitrogen). The array was washed according to the manufacturer's protocol, then scanned using an Agilent scanner and analyzed using Feature Extraction software. Normalization was performed using a linear per-array algorithm according to the manufacturer's protocol (Agilent Technologies).

Hierarchical Clustering Analysis Method Clustering analysis was performed using a hierarchical clustering method (Eisen MB, Spellman PT, Brown PO, Botstein D., Proc Natl Acad Sci USA 1998; 95: 14863-8). For sample clustering, Cluster 3.0 software (http://rana.lbl.gov/EisenSoftware.htm) or Minitab 15 statistical software (http://www.minitab.com) Similarities were calculated based on measurements of DNA methylation signal intensity in all genes. Dendrograms and heat maps were created using TreeView software (http://rana.lbl.gov/EisenSoftware.htm).

Methylation analysis We performed bisulfite treatment by the method reported so far (Kondo Y, Shen L, Suzuki S, et al. Hepatol Res 2007; 37: 974-83; Yang AS, Estecio MR, Doshi K, Kondo Y, Tajara EH, Issa JP. Nucleic Acids Res 2004; 32: e38). Briefly, 3 μM sodium bisulfite (pH 5.0) was added to 2 μg of genomic DNA and incubated at 50 ° C. for 16 hours. DNA was purified using Wizard Miniprep Column (Promega, Madison, Wis.), Precipitated with ethanol, and redissolved in 30 μl of purified water. DNA methylation level was determined by quantitative methylation analysis using the pyrosequencing method (Pyrosequencing AB, Uppsala, Sweden) (Colella S, Shen L, Baggerly KA, Issa JP, Krahe R., Biotechniques 2003; 35: 146-5027). Was analyzed. In each assay, an experiment that mixes positive controls (samples after SssI treatment) and negative controls (samples after amplification of the entire genome using GenomiPhi V2) at the set-up stage is performed without annealing. The optimum temperature was determined. The experiment was repeated and reproducibility was evaluated. (Shen L, Guo Y, Chen X, Ahmed S, Issa JP. Biotechniques 2007; 42: 48-5828). Methylation specific PCR (MSP) was also performed on TMEM30B, KAZALD1 and MAPK13 genes. PCR products were visualized on 6% polyacrylamide gels or 3% agarose gels stained with ethidium bromide. The primer sequences and PCR conditions for pyrosequencing and MSP are shown in Tables 1A-1C.

  All primers were designed so that the methylation status of CpG within 0.5 kb from the transcription start site can be assayed.

After culturing the cells with trichostatin A and 5Aza-dC treated cells in medium for 12-24 hours, the cells were either 1) 5 μM 5-aza-2′-deoxycytidine (5Aza-dC; Sigma-Aldrich) or phosphate buffer Treat with saline for 72 hours (at this time medium containing 5Aza-dC or phosphate buffered saline was changed every 24 hours) or 2) 300 nM trichostatin A (TSA; MP Biomedicals, Solon, OH) or an equal volume of ethanol for 24 hours.

Quantitative reverse transcription-polymerase chain reaction analysis RNA was extracted from total RNA using TRIzol (Invitrogen). 2 μg of RNA was reverse transcribed using MPMLV (Promega). SYBR GREEN Quantitative reverse transcription-PCR was performed three times on the target gene (Applied Biosystems, Foster City, CA). The primer sequences for Q-PCR are shown in Table 1B.

Statistical analysis The relationship between methylation status and clinicopathological changes was determined using the Mann-Whitney U test, Fisher's exact test or Kruskal-Wallis test using the StadView software (version 5.0; Abacus Concepts, Berkeley, CA). Was used for analysis. As the linear regression model, Stata version 8 (College Station, TX) was used. All of the P values were two-sided and P <0.05 was considered statistically significant. Survival curves were generated using the Kaplan-Meier method. Overall survival was calculated between the day of surgery and death.

<Result>
We first performed MCAM to analyze the methylation profile of the malignant mesothelioma cell line ACC-MESO-1. After the methylated fragment is amplified by MCA, the MCA product is labeled with Cy5 (ACC-MESO-1) or Cy3 (normal mesothelial tissue) and cohybridized with a microarray (including 15,134 probes corresponding to 6,161 genes). Soybean (FIG. 1A). To date, the inventors have confirmed that Cy5 / Cy3 signal ratios of 2.0 or higher in MCAM were consistent with methylation positive in pyrosequencing analysis (Gao W, Kondo Y, Shen L, et al., Carcinogenesis 2008; 29 : 1901-10). In order to evaluate the effectiveness of MCAM analysis in ACC-MESO-1 cells, 19 genes showing high, medium or low signal intensity were randomly selected and methylation level was examined by pyrosequencing method. 11 out of 14 genes with a Cy5 / Cy3 signal ratio of 2.0 or higher were positive for methylation in the pyrosequencing analysis (at least 15% methylation level in ACC-MESO-1 and at least the methylation level in normal mesothelial tissue 4 out of 5 genes with a Cy5 / Cy3 signal ratio of 2.0 or less but methylation negative (methylation level less than 15% in MPM cells and / or normal) The methylation level was less than 1 / 1.5 of the skin tissue). The high correlation between MCAM and pyrosequencing analysis (specificity 80%; sensitivity 86%) is similar to that shown in previous studies (Shen L, Kondo Y, Guo Y, et al., PLoS Genet 2007; 3: 2023-36 .: Gao W, Kondo Y, Shen L, et al., Carcinogenesis 2008; 29: 1901-10), confirmed in this cell (Figure 1B and Table 2) . Using this criterion, the 971 gene methylated with ACC-MESO-1 was identified.

  Next, in order to investigate the relationship between DNA methylation of these genes and gene expression in MPM, ACC-MESO-1 was converted to a DNA methyltransferase inhibitor, 5-aza-2'-deoxycytidine (5-Aza- dC) or histone deacetylase inhibitor, trichostatin A (TSA), and examined the expression of three identified genes C9orf106, EDG4 and MPMPL1 (FIGS. 1C and 1D). In ACC-MESO-1, the expression of these genes was suppressed, while the expression level was high in normal mesothelial tissue. The present inventors observed significant gene re-expression by 5-Aza-dC, but the efficacy was poor with TSA treatment. This indicates that suppression of expression of these genes is due to DNA methylation.

In co-hybridization of MCA products from normal mesothelial DNA (mixture of 2 cases) and normal lung tissue DNA (mixture of 4 cases), we found that the methylation status was in high agreement (R ² = 0.87, figure 2A) was confirmed. This indicates that tissue-specific methylation is rare in these two normal tissues. Next, in order to evaluate the difference in methylation profiles of MPM and AdCa, MCA products from MPM DNA (mixture of 4 cases) and AdCa DNA (mixture of 4 cases) were co-hybridized, and part of the gene was We found that each tumor showed a different methylation profile (R ² = 0.77, FIG. 2B). Interestingly, the present inventors examined the methylation profile of liver cancer (mixed 4 cases) and MPM, and found that both the lung and liver originated from the endoderm, but MPM and AdCa It was found that more different genes were methylated in MPM and liver cancer (R ² = 0.26) than in the difference in methylation target genes (Fig. 2C).

  To compare the DNA methylation profiles in the entire genomic region of MPM and AdCa, we analyzed 20 cases of MPM and 20 cases of AdCa using MCAM. All heat maps of MPM and AdCa using 6,161 genes show that AdCa appears to be methylated more frequently than MPM, and some cases of AdCa are extensively methylated (FIG. 3A). MPM and AdCa were classified into different subgroups according to their DNA methylation profiles. There were two exceptional cases in the MPM, mainly in the AdCa subgroup.

  Next, MPM and AdCa were individually analyzed by hierarchical clustering using 6,161 genes to examine whether DNA methylation status affects clinicopathological properties in MPM and AdCa. MPM was divided into two subgroups according to the number of DNA methylation genes. That is, one subgroup was four cases with the number of methylated genes as low as 300 genes or less, and all the cases were epithelial types. These data indicate that DNA methylation affects the phenotype of MPM during tumorigenesis. Hierarchical clustering analysis allowed AdCa to be divided into four subgroups. One subgroup consisted of 6 cases of AdCa, which were cases with a higher number of methylated genes than other cases of AdCa (911 genes vs 387 genes, P = 0.001). Most of the subgroup's cases were smokers (5/6 smokers; average pack age, 68.6 ± 22.9).

  We counted genes that are methylated in MPM and AdCa. There are less than 700 genes that are methylated in MPM, which accounts for approximately 11% of the 6,161 CpG present on the microarray. In addition, the average number of methylated genes in MPM cases was 387 (range, 120 to 755; FIG. 3B), while AdCa had 544 genes (range, 133 to 1212).

  The genes that are commonly methylated in AdCa and MPM were compared. Genes commonly methylated in 10 cases of MPM are very rare (less than 40 genes), but in 10 cases of AdCa, more than 80 genes were commonly methylated. This indicates that there are few genes that are commonly methylated in each MPM case (P = 0.001, FIG. 3C). Tables 3 and 4 list the methylated genes for each tumor.

  Table 5 shows the relationship between the number of methylated genes and clinicopathological parameters in MPM and AdCa.

  In AdCa, smokers had significantly more methylated genes than non-smokers (728 genes vs 360 genes, P = 0.02). Smokers with MPM also tend to have more methylation genes than non-smokers (366 genes vs 261 genes, P = 0.2), indicating that smoking affects MPM DNA methylation Is shown. In contrast, asbestos exposure had little effect on DNA methylation in MPM (MPM with and without asbestos exposure was 386 genes vs 320 genes).

  Patients with advanced colorectal cancer with high frequency of DNA methylation have been reported to have a poor prognosis (Shen L, Catalano PJ, Benson AB, 3rd, O'Dwyer P, Hamilton SR, Issa JPClin Cancer Res 2007; 13: 6093-829). The present inventors divided MPM patients into two groups, that is, a group with more methylated genes than the average (387 genes) and a group with fewer methylated genes, and examined the relationship between survival rate and methylation. Patients who died due to surgical complications or 2 patients who died due to surgical complications were excluded. Patients in the group with fewer methylated genes than the average number of methylated genes (n = 11) had significantly longer survival than those in the group with more methylated genes than the average (n = 7) (mean Survival time, 22 months vs 8 months, P = 0.01) (Figure 3D). The overall mean survival of the entire MPM patient population was 11.7 months.

  DNA methylation has been shown to be a powerful marker for cancer diagnosis (Belinsky SA, Nat Rev Cancer 2004; 4: 707-1730). To identify specific DNA methylation markers for MPM diagnosis, we first selected 8 genes from MCAM analysis. In this analysis, at least 4 cases of MPM were selected that showed positive methylation (Cy5 / Cy3> 2.0) and all AdCa cases showed negative methylation (FIG. 4A). Interestingly, if you select a gene using the same criteria of methylation positive in at least 4 cases of AdCa and methylation negative in all cases of MPM, there are more genes (34 genes) in AdCa, This indicates that more methylated genes are present in AdCa (FIG. 4A). The present inventors confirmed the methylation of the gene by MSP, and confirmed that three genes, namely transmembrane protein 30B (TMEM30B), Kazal type serine protease inhibitor domain 1 (KAZALD1) and mitogenic activation protein kinase 13 (MAPK13) was found to be a methylation marker specific for MPM (FIGS. 4B and 4C). In MPM cases analyzed by MCAM analysis, DNA methylation, DNA methylation by MSP, 11 (58%) cases, 8 (42%) of 19 cases of MPM in each of TMEM30B gene, KAZALD1 gene and MAPK13 gene ) Cases and 2 (11%) cases. However, with AdCa, only one obscure methylation band was detected in the TMEM30B gene.

  To ascertain whether these methylation markers could be differentiated in another population of MPM patients, we obtained and analyzed another 10 cases of MPM from another institution (FIG. 4D). DNA methylation was detected in 5 (50%), 7 (70%) and 2 (20%) cases of 10 cases of MPM in each of TMEM30B gene, KAZALD1 gene and MAPK13 gene. DNA methylation of these three genes was analyzed in a total of 31 cases of MPM and 51 cases of AdCa (19 cases of MPM samples and 19 cases of AdCa samples were the population used in the MCAM analysis). DNA methylation was detected in MPM in 17 cases (55%) for TMEM30B, 16 cases (52%) for KAZALD1, and 4 cases (13%) for MAPK13, whereas DNA methylation was detected in AdCa (Figures 4C and 4D). As a differential diagnosis of AdCa and MPM, when at least one of the three genes was methylated and diagnosed as MPM, its sensitivity and specificity were 77% and 100%, respectively.

  Furthermore, among the sequences of the above three types of genes, in particular, by detecting or measuring the methylation or the degree of methylation of the sequence of the CpG island region of the promoter of these genes (SEQ ID NO: 78, 79 or 80), It was found that MPM can be detected more specifically. In addition, those that are effective as PCR primers used for the analysis are, for example, TMEM30B gene methylation-specific primers such as SEQ ID NO: 66, SEQ ID NO: 67, SEQ ID NO: 81, SEQ ID NO: 95, and / or SEQ ID NO: In the case of the primer of No. 96 and a non-methylation specific primer of the TMEM30B gene, for example, the primer of SEQ ID NO: 68, SEQ ID NO: 69, SEQ ID NO: 82, SEQ ID NO: 97, and / or SEQ ID NO: 98, and the KAZALD1 gene In the case of a methylation specific primer, for example, a primer of SEQ ID NO: 70, SEQ ID NO: 71, SEQ ID NO: 85, SEQ ID NO: 99, and / or SEQ ID NO: 100, and in the case of a non-methylation specific primer of the KAZALD1 gene, for example, a sequence No. 72, SEQ ID NO: 73, SEQ ID NO: 86, SEQ ID NO: 101, and / or primer of SEQ ID NO: 102, and in the case of a MAPK13 gene methylation specific primer, for example, SEQ ID NO: 7 4. A primer of SEQ ID NO: 75 and / or SEQ ID NO: 89, and in the case of a non-methylation specific primer of the MAPK13 gene, for example, it was a primer of SEQ ID NO: 76, SEQ ID NO: 77, and / or SEQ ID NO: 90.

<Discussion>
In this study, we used MCAM to analyze and compare methylation profiles in the entire genomic region of MPM and AdCa, and to examine the frequency of DNA methylation of specific genes in MPM . Previous reports have shown that MCAM can assess the methylation status of whole genome regions with high specificity and sensitivity (Shen L, Kondo Y, Guo Y, et al., PLoS Genet 2007; 3: 2023-36; Gao W, Kondo Y, Shen L, et al., Carcinogenesis 2008; 29: 1901-10); Estecio MR, Yan PS, Ibrahim AE, et al., Nat Genet 2005; 37: 853-62). However, since MCAM may detect significantly more abnormally methylated genes in tissue samples, we aimed at hypermethylated genes. In fact, the effectiveness of using ACC-MESO-1, an MPM cell, shows a good correlation between the signal ratio from MCAM and the methylation level assayed by bisulfite-pyrosequencing, Consistent with research results (Shen L, Kondo Y, Guo Y, et al., PLoS Genet 2007; 3: 2023-36; Gao W, Kondo Y, Shen L, et al., Carcinogenesis 2008; 29: 1901 -Ten). The target gene detected by MCAM analysis with ACC-MESO-1 was found to be reactivated by 5-Aza-dC and hypermethylated in MPM patients. This indicates that gene expression is suppressed by DNA methylation of these genes in MPM.

Although normal mesothelial and normal lung tissue originate from different germ layers (mesoderm and endoderm, respectively), their DNA methylation profiles are very similar (R ² = 0.87) This shows that there is little difference in tissue-specific methylation between these two normal tissues. Genome-wide methylation analysis of various normal tissues so far has shown that tissue-specific methylation is very rare and is consistent with our findings (Shen L, Kondo Y, Guo Y, et al., PLoS Genet 2007; 3: 2023-36; Estecio MR, Yan PS, Ibrahim AE, et al., Genome Res 2007; 17: 1529-36; Weber M, Davies JJ, Wittig D, et al., Nat Genet 2005; 37: 853-6221, 31, 32). In contrast, the differences in DNA methylation target genes between MPM and AdCa are much greater than in normal tissues, presumably because cancers in various tissues exhibit different methylation profiles (Esteller M, Corn PG, Baylin SB, Herman JG. Cancer Res 2001; 61: 3225-933). Interestingly, the methylation profile of MPM was more similar to AdCa compared to liver cancer, although both lung and liver originated from the endoderm. The reason for the similarity of DNA methylation between MPM and AdCa is not understood. Certain environmental factors that contribute to tumorigenesis, such as smoking, may have the same effect on DNA methylation abnormalities in both MPM and AdCa (Feinberg AP., Nature 2007; 447: 433-40) .

  Previous studies of DNA methylation abnormalities at several loci have shown that methylation does not occur in a wide range of genes in MPM compared to AdCa (Toyooka S, Pass HI, Shivapurkar N, et al., Cancer Res 2001; 61: 5727-30). This genome-wide (broad) DNA methylation analysis showed that DNA methylation is less frequent and less common in MPM than AdCa. The majority of MPMs had less than 700 genes methylated (average number of methylated genes, 387 ± 196 genes). This is in contrast to some cases of AdCa patients (mostly smokers (average pack age 67.3 ± 14.2), with a wide range of genes methylated (> 950 genes)). there were. It has been suggested that certain lung adenocarcinomas are susceptible to methylation and a phenotype called CpG island methylator phenotype (CIMP) (Toyota M, Ahuja N, Ohe-Toyota M, Herman JG , Baylin SB, Issa JP., Proc Natl Acad Sci USA 1999; 96: 8681-6; Suzuki M, Shigematsu H, Iizasa T, et al., Cancer 2006; 106: 2200-7). Our results showed that a subset of AdCa showed CIPM, whereas there was no such case group in MPM. When aberrant methylation occurs in MPM, continued inflammation by asbestos appears to be an inducer, but not as strong as smoking with AdCa. These data may reflect different mechanisms for the acquisition of aberrant DNA methylation during MPM and AdCa formation.

  DNA methylation has been proposed as a powerful marker for MPM diagnosis (Toyooka S, Pass HI, Shivapurkar N, et al., Cancer Res 2001; 61: 5727-30; Tsou JA, Shen LY, Siegmund KD, et al., Lung Cancer 2005; 47: 193-204). However, previous studies on the methylation status of MPM and AdCa show that although there is a difference in frequency, abnormal methylation of candidate markers is detected to some extent in both MPM and AdCa. Furthermore, no methylation marker specific for MPM has ever been reported. This time, we analyzed the DNA methylation profile of the entire genomic region with MPM and AdCa, and DNA methylation at specific loci was frequently detected in MPM, and three genes, namely TMEM30B, KAZALD1 and MAPK13 It was shown that the gene was specifically methylated with MPM. In particular, DNA methylation of the KAZALD1 and MAPK13 genes has never been reported in human cancers, but their abnormal methylation should serve as a useful marker to distinguish MPM from AdCa.

  In summary, when MPM and AdCa are compared by methylation analysis of the entire genomic region, these two malignancies each show a characteristic DNA methylation pattern, which appears to arise from differences in pathophysiological processes. It is. We now propose possible markers for the diagnosis of MPM. In addition, we found a subset of MPMs classified by methylation profiles associated with pathological findings. We also found that the prognosis of MPM patients with low frequency of DNA methylation was good. These facts indicate that DNA methylation abnormalities affect the clinical features of MPM. Thus, DNA methylation of the promoter CpG island and associated gene expression suppression play an important role in the development of MPM.

  The present invention provides a method for detecting malignant pleural mesothelioma that makes it possible to distinguish malignant pleural mesothelioma from lung cancer, and is particularly useful for the definitive diagnosis of malignant pleural mesothelioma caused by asbestos. It is.

Claims (8)

A method for assisting in the detection of malignant pleural mesothelioma , detecting methylation of at least one gene selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene in a biological sample from a subject And determining that the gene is malignant pleural mesothelioma when the gene is methylated.   A method for determining the prognosis of a subject suffering from malignant pleural mesothelioma, wherein the methyl of at least one gene selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene in a biological sample from the subject Measuring the degree of acetylation, and determining that the prognosis of the disease is good when the degree of methylation of the gene is lower than the degree of methylation of a subject with a poor prognosis.   The method according to claim 1 or 2, wherein methylation of the nucleotide sequence of the CpG region of the promoter of the TMEM30B gene, KAZALD1 gene or MAPK13 gene is detected or measured.   The base sequence of the CpG region of the promoter includes the base sequence shown in SEQ ID NO: 78, 79 or 80, or a deletion, substitution or addition of one or several bases in the base sequence, and has promoter activity. The method according to claim 3, comprising a nucleotide sequence having   The method according to any one of claims 1 to 4, comprising detecting the methylation by a methylation-specific PCR method.   Primers for use in the PCR method include deletion, substitution or addition of one or several bases in the base sequence shown in SEQ ID NO: 78, 79 or 80, or in the base sequence, and The method according to claim 5, wherein a sequence consisting of 17 to 35 consecutive nucleotides in the base sequence having promoter activity is selected as a methylation specific primer and / or an unmethylation specific primer.   The method according to any one of claims 1 to 6, wherein the sample is serum, pleural effusion, bronchial lavage fluid or affected tissue. A kit for use in the method according to any one of claims 1 to 7, wherein at least one gene selected from the group consisting of TMEM30B gene, KAZALD1 gene and MAPK13 gene is methylated or unmethylated A kit comprising the following primer set for methylation-specific PCR.
Methylation specific primer for TMEM30B gene
TTGGGAGGGTGTGGGTATTGTTC (SEQ ID NO: 66)
ACGCGCGAACTAACCGAAT (SEQ ID NO: 67)
CTGGGAGGGTGTGGGCACTGCTCG (SEQ ID NO: 81)
CGAGTAGTTTTCGGGTTTGC (SEQ ID NO: 95)
ACCGACGCGCGAACTAAC (SEQ ID NO: 96)
Unmethylated specific primer for TMEM30B gene
GGAATTGGGAGGGTGTGGGTATTGTTT (SEQ ID NO: 68)
ACCTCCCTCTCCACACCAC (SEQ ID NO: 69)
GGAACTGGGAGGGTGTGGGCACTGCT (SEQ ID NO: 82)
TGAGTAGTTTTTGGGTTTGT (SEQ ID NO: 97)
ACCATAACACTCCAAATCATAACA (SEQ ID NO: 98)
Methylation specific primer for KAZALD1 gene
GCGGGTCGTAGTATTTGTCG (SEQ ID NO: 70)
AACAAAACCAACCACCTTCG (SEQ ID NO: 71)
CGGGTCGTAGTATTTGTC (SEQ ID NO: 85)
GGTAAGTTTGCGGTCGTTTTC (SEQ ID NO: 99)
AACAAAACCAACCACCTTCG (SEQ ID NO: 100)
Unmethylated specific primer for KAZALD1 gene
TTATTTGTGGGTTGTAGTATTTGTT (SEQ ID NO: 72)
AAACCAACCACCTTCATCTCC (SEQ ID NO: 73)
TTATTCGCGGGTCGTAGTATTTGTC (SEQ ID NO: 86)
GTGGGTAAGTTTGTGGTTG (SEQ ID NO: 101)
AACAAAACCAACCACCTTCATCT (SEQ ID NO: 102)
Methylation specific primers for MAPK13 gene
CGTGTTTTCGACGTACGTCGGTAGC (SEQ ID NO: 74)
ACCGCTAAATAACCCCGAAA (SEQ ID NO: 75)
CGTGTCCCCGACGCACGTCGGCAGC (SEQ ID NO: 89)
Unmethylated specific primer for MAPK13 gene
GGTTTTGTTGGGTAGTTTT (SEQ ID NO: 76)
TCCCACCTACCAACTCACC (SEQ ID NO: 77)
GGTCCCGCTGGGCAGCCC (SEQ ID NO: 90)

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