A molecular portrait of microsatellite instability across multiple cancers

Microsatellite instability (MSI) refers to the hypermutability of short repetitive sequences in the genome caused by impaired DNA mismatch repair. Although MSI has been studied for decades, large amounts of sequencing data now available allows us to examine the molecular fingerprints of MSI in greater detail. Here, we analyse ∼8,000 exomes and ∼1,000 whole genomes of cancer patients across 23 cancer types. Our analysis reveals that the frequency of MSI events is highly variable within and across tumour types. We also identify genes in DNA repair and oncogenic pathways recurrently subject to MSI and uncover non-coding loci that frequently display MSI. Finally, we propose a highly accurate exome-based predictive model for the MSI phenotype. These results advance our understanding of the genomic drivers and consequences of MSI, and our comprehensive catalogue of tumour-type-specific MSI loci will enable panel-based MSI testing to identify patients who are likely to benefit from immunotherapy.

[1]  K. Kinzler,et al.  Clues to the pathogenesis of familial colorectal cancer. , 1993, Science.

[2]  W. Bodmer,et al.  Genetic steps in colorectal cancer , 1994, Nature Genetics.

[3]  K. Kinzler,et al.  APC mutations in colorectal tumors with mismatch repair deficiency. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[4]  J. Herman,et al.  Incidence and functional consequences of hMLH1 promoter hypermethylation in colorectal carcinoma. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Somatic mutations in mitochondrial DNA do not associate with nuclear microsatellite instability in gastrointestinal cancer. , 2000, Gastroenterology.

[6]  S. Bull,et al.  Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer. , 2000, The New England journal of medicine.

[7]  P. Peltomäki,et al.  Endometrial and colorectal tumors from patients with hereditary nonpolyposis colon cancer display different patterns of microsatellite instability. , 2002, The American journal of pathology.

[8]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[9]  Lawrence J. Burgart,et al.  Development of a Fluorescent Multiplex Assay for Detection of MSI-High Tumors , 2004, Disease markers.

[10]  A. Chapelle,et al.  Genetic predisposition to colorectal cancer , 2004, Nature Reviews Cancer.

[11]  J. Jiricny The multifaceted mismatch-repair system , 2006, Nature Reviews Molecular Cell Biology.

[12]  C. Croce,et al.  A microRNA expression signature of human solid tumors defines cancer gene targets , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[13]  H. Morreau,et al.  Diagnostic Approach and Management of Lynch Syndrome (Hereditary Nonpolyposis Colorectal Carcinoma): A Guide for Clinicians , 2006, CA: a cancer journal for clinicians.

[14]  C. Clevenger,et al.  Nek3 kinase regulates prolactin-mediated cytoskeletal reorganization and motility of breast cancer cells , 2007, Oncogene.

[15]  D. Bonthron,et al.  Extensive gene conversion at the PMS2 DNA mismatch repair locus , 2007, Human mutation.

[16]  Juliane C. Dohm,et al.  Substantial biases in ultra-short read data sets from high-throughput DNA sequencing , 2008, Nucleic acids research.

[17]  T. Sellers,et al.  Systematic Review and Meta-analysis of Ovarian Cancers: Estimation of Microsatellite-High Frequency and Characterization of Mismatch Repair Deficient Tumor Histology , 2008, Clinical Cancer Research.

[18]  C. Mayr,et al.  Widespread Shortening of 3′UTRs by Alternative Cleavage and Polyadenylation Activates Oncogenes in Cancer Cells , 2009, Cell.

[19]  T. Frebourg,et al.  Tumor-infiltrating lymphocytes in colorectal cancers with microsatellite instability are correlated with the number and spectrum of frameshift mutations , 2009, Modern Pathology.

[20]  Suet Yi Leung,et al.  Heritable somatic methylation and inactivation of MSH2 in families with Lynch syndrome due to deletion of the 3′ exons of TACSTD1 , 2009, Nature Genetics.

[21]  Saverio Brogna,et al.  Nonsense-mediated mRNA decay (NMD) mechanisms , 2009, Nature Structural &Molecular Biology.

[22]  M. Fassan,et al.  Microsatellite instability and hMLH1 and hMSH2 expression in renal tumors. , 2010, Oncology reports.

[23]  S. Gruber,et al.  Microsatellite instability in colorectal cancer—the stable evidence , 2010, Nature Reviews Clinical Oncology.

[24]  H. Hakonarson,et al.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.

[25]  M. DePristo,et al.  A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.

[26]  N. Wentzensen,et al.  Frequency of mismatch repair deficiency in ovarian cancer: a systematic review This article is a US Government work and, as such, is in the public domain of the United States of America. , 2011, International journal of cancer.

[27]  Lynda Chin,et al.  Spectrum of somatic mitochondrial mutations in five cancers , 2012, Proceedings of the National Academy of Sciences.

[28]  A. D’Andrea,et al.  A DNA Repair Pathway–Focused Score for Prediction of Outcomes in Ovarian Cancer Treated With Platinum-Based Chemotherapy , 2012, Journal of the National Cancer Institute.

[29]  M. Kuroki,et al.  ALPK2 is crucial for luminal apoptosis and DNA repair-related gene expression in a three-dimensional colonic-crypt model. , 2012, Anticancer research.

[30]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of human colon and rectal cancer , 2012, Nature.

[31]  Peter J. Park,et al.  The Landscape of Microsatellite Instability in Colorectal and Endometrial Cancer Genomes , 2013, Cell.

[32]  Benjamin J. Raphael,et al.  Mutational landscape and significance across 12 major cancer types , 2013, Nature.

[33]  J. Bhak,et al.  Comprehensive genome- and transcriptome-wide analyses of mutations associated with microsatellite instability in Korean gastric cancers , 2013, Genome research.

[34]  Steven A. Roberts,et al.  Mutational heterogeneity in cancer and the search for new cancer-associated genes , 2013 .

[35]  A. McKenna,et al.  Evolution and Impact of Subclonal Mutations in Chronic Lymphocytic Leukemia , 2012, Cell.

[36]  Max Kuhn,et al.  Applied Predictive Modeling , 2013 .

[37]  A. Sivachenko,et al.  Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples , 2013, Nature Biotechnology.

[38]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[39]  Steven J. M. Jones,et al.  Integrated genomic characterization of endometrial carcinoma , 2013, Nature.

[40]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of gastric adenocarcinoma , 2014, Nature.

[41]  K. Søreide,et al.  Prevalence and implications of elevated microsatellite alterations at selected tetranucleotides in cancer , 2014, British Journal of Cancer.

[42]  C. Sander,et al.  Genome-wide analysis of non-coding regulatory mutations in cancer , 2014, Nature Genetics.

[43]  Kristian Cibulskis,et al.  RNF43 is frequently mutated in colorectal and endometrial cancers , 2014, Nature Genetics.

[44]  Scott Boyer,et al.  Introducing Conformal Prediction in Predictive Modeling. A Transparent and Flexible Alternative to Applicability Domain Determination , 2014, J. Chem. Inf. Model..

[45]  Kai Ye,et al.  MSIsensor: microsatellite instability detection using paired tumor-normal sequence data , 2014, Bioinform..

[46]  Ben Lehner,et al.  Differential DNA mismatch repair underlies mutation rate variation across the human genome , 2015, Nature.

[47]  Christopher D. Heinen,et al.  Milestones of Lynch syndrome: 1895–2015 , 2015, Nature Reviews Cancer.

[48]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[49]  Niko Välimäki,et al.  CTCF/cohesin-binding sites are frequently mutated in cancer , 2015, Nature Genetics.

[50]  Manolis Kellis,et al.  Large-scale epigenome imputation improves data quality and disease variant enrichment , 2015, Nature Biotechnology.

[51]  Martin L. Miller,et al.  Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer , 2015, Science.

[52]  T. Aparicio,et al.  PD-1 blockade in tumors with mismatch-repair deficiency , 2015 .

[53]  A. Butte,et al.  Systematic pan-cancer analysis of tumour purity , 2015, Nature Communications.

[54]  B. Teh,et al.  MSIseq: Software for Assessing Microsatellite Instability from Catalogs of Somatic Mutations , 2015, Scientific Reports.

[55]  J. Wolchok,et al.  Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma. , 2015, The New England journal of medicine.

[56]  Michael Q. Zhang,et al.  Integrative analysis of 111 reference human epigenomes , 2015, Nature.

[57]  Jay Shendure,et al.  Classification and characterization of microsatellite instability across 18 cancer types , 2016, Nature Medicine.

[58]  James R. Eshleman,et al.  Microsatellite Instability as a Biomarker for PD-1 Blockade , 2016, Clinical Cancer Research.