Ivan P Gorlov1, Olga Y Gorlova2, Christopher I Amos3. 1. The Geisel School of Medicine, Department of Biomedical Data Science, Dartmouth College, HB7936, One Medical Center Dr., Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756, United States. Electronic address: ivan.p.gorlov@dartmouth.edu. 2. The Geisel School of Medicine, Department of Biomedical Data Science, Dartmouth College, HB7936, One Medical Center Dr., Dartmouth-Hitchcock Medical Center, Lebanon, NH 03756, United States. 3. Department of Medicine, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States.
Abstract
BACKGROUND: Usually, genes with a higher-than-expected number of somatic mutations in tumor samples are assumed to be cancer related. We identified genes with a fewer-than-expected number of somatic mutations - "untouchable genes". METHODS: To predict the expected number of somatic mutations, we used a linear regression model with the number of mutations in the gene as an outcome, and gene characteristics, including gene size, nucleotide composition, level of evolutionary conservation, expression level and others, as predictors. Analysis of residuals from the regression model was used to compare the observed and predicted number of mutations. RESULTS: We have identified 19 genes with a less-than-expected number of loss-off-function (nonsense, frameshift or pathogenic missense) mutations - i.e., untouchable genes. The number of silent or neutral missense mutations in untouchable genes was equal or higher than the expected number. Many mucins, including MUC16, MUC17, MUC6, MUC5AC, MUC5B, and MUC12, are untouchable. We hypothesized that untouchable mucins help tumor cells to avoid immune response by providing a protective coat that prevents direct contact between effector immune cells, e.g., cytotoxic T-cells, and tumor cells. Survival analysis of available TCGA data demonstrated that overall survival of patients with low (below the median) expression of untouchable mucins was better compared to patients with high expression of untouchable mucins. Aside from mucins, we have identified a number of other untouchable genes. CONCLUSIONS: Untouchable genes may be ideal targets for cancer treatment since suppression of untouchable genes is expected to inhibit survival of tumor cells.
BACKGROUND: Usually, genes with a higher-than-expected number of somatic mutations in tumor samples are assumed to be cancer related. We identified genes with a fewer-than-expected number of somatic mutations - "untouchable genes". METHODS: To predict the expected number of somatic mutations, we used a linear regression model with the number of mutations in the gene as an outcome, and gene characteristics, including gene size, nucleotide composition, level of evolutionary conservation, expression level and others, as predictors. Analysis of residuals from the regression model was used to compare the observed and predicted number of mutations. RESULTS: We have identified 19 genes with a less-than-expected number of loss-off-function (nonsense, frameshift or pathogenic missense) mutations - i.e., untouchable genes. The number of silent or neutral missense mutations in untouchable genes was equal or higher than the expected number. Many mucins, including MUC16, MUC17, MUC6, MUC5AC, MUC5B, and MUC12, are untouchable. We hypothesized that untouchable mucins help tumor cells to avoid immune response by providing a protective coat that prevents direct contact between effector immune cells, e.g., cytotoxic T-cells, and tumor cells. Survival analysis of available TCGA data demonstrated that overall survival of patients with low (below the median) expression of untouchable mucins was better compared to patients with high expression of untouchable mucins. Aside from mucins, we have identified a number of other untouchable genes. CONCLUSIONS: Untouchable genes may be ideal targets for cancer treatment since suppression of untouchable genes is expected to inhibit survival of tumor cells.
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Authors: Robert E Thurman; Eric Rynes; Richard Humbert; Jeff Vierstra; Matthew T Maurano; Eric Haugen; Nathan C Sheffield; Andrew B Stergachis; Hao Wang; Benjamin Vernot; Kavita Garg; Sam John; Richard Sandstrom; Daniel Bates; Lisa Boatman; Theresa K Canfield; Morgan Diegel; Douglas Dunn; Abigail K Ebersol; Tristan Frum; Erika Giste; Audra K Johnson; Ericka M Johnson; Tanya Kutyavin; Bryan Lajoie; Bum-Kyu Lee; Kristen Lee; Darin London; Dimitra Lotakis; Shane Neph; Fidencio Neri; Eric D Nguyen; Hongzhu Qu; Alex P Reynolds; Vaughn Roach; Alexias Safi; Minerva E Sanchez; Amartya Sanyal; Anthony Shafer; Jeremy M Simon; Lingyun Song; Shinny Vong; Molly Weaver; Yongqi Yan; Zhancheng Zhang; Zhuzhu Zhang; Boris Lenhard; Muneesh Tewari; Michael O Dorschner; R Scott Hansen; Patrick A Navas; George Stamatoyannopoulos; Vishwanath R Iyer; Jason D Lieb; Shamil R Sunyaev; Joshua M Akey; Peter J Sabo; Rajinder Kaul; Terrence S Furey; Job Dekker; Gregory E Crawford; John A Stamatoyannopoulos Journal: Nature Date: 2012-09-06 Impact factor: 49.962