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Functional annotation of colorectal cancer susceptibility loci identifies MLH1 rs1800734 associated with MSI patients
  1. Gaoxiang Ma1,2,
  2. Yuqiu Ge1,2,
  3. Dongying Gu3,
  4. Mulong Du1,2,
  5. Haiyan Chu1,2,
  6. Jinfei Chen3,
  7. Zhengdong Zhang1,2,
  8. Meilin Wang1,2
  1. 1Department of Environmental Genomics, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
  2. 2Department of Genetic Toxicology, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China
  3. 3Department of Oncology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
  1. Correspondence to Dr Meilin Wang, Department of Environmental Genomics, School of Public Health, Nanjing Medical University, 101 Longmian Road, Nanjing, Nanjing 211166, China; mwang{at}njmu.edu.cn

https://doi.org/10.1136/gutjnl-2016-311543

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    Recently, we read the article by Ma et al with great interest. They conducted a comprehensive meta-analysis that nominated 62 variants in 50 candidate genes with high level of cumulative evidence for genetic susceptibility to colorectal cancer (CRC).1 Interestingly, the authors found that 10 variants in 7 genes were graded strong and moderate association with CRC risk. However, functional annotations of these variants remain largely unknown. To investigate their functional relevance, we annotated the variants and their high related single nucleotide polymorphisms (SNPs) (linkage disequilibrium, r2>0.9) using publicly available The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus datasets.

    After exclusion of the variants with minor allele frequency <0.05, a total of four SNPs (rs1801155, rs1569686, rs1800734 and rs2736100) were included in further analysis (table 1). We then evaluated the effect of risk alleles on gene epigenetic and expression alterations in CRC tumour tissues from TCGA. Three SNPs (rs1569686, rs1800734 and rs2736100) were identified as methylation quantitative trait loci (meQTL) in the 500 kb upstream and …

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