29
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Exome-wide analysis of bi-allelic alterations identifies a Lynch phenotype in The Cancer Genome Atlas

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Cancer susceptibility germline variants generally require somatic alteration of the remaining allele to drive oncogenesis and, in some cases, tumor mutational profiles. Whether combined germline and somatic bi-allelic alterations are universally required for germline variation to influence tumor mutational profile is unclear. Here, we performed an exome-wide analysis of the frequency and functional effect of bi-allelic alterations in The Cancer Genome Atlas (TCGA).

          Methods

          We integrated germline variant, somatic mutation, somatic methylation, and somatic copy number loss data from 7790 individuals from TCGA to identify germline and somatic bi-allelic alterations in all coding genes. We used linear models to test for association between mono- and bi-allelic alterations and somatic microsatellite instability (MSI) and somatic mutational signatures.

          Results

          We discovered significant enrichment of bi-allelic alterations in mismatch repair (MMR) genes and identified six bi-allelic carriers with elevated MSI, consistent with Lynch syndrome. In contrast, we find little evidence of an effect of mono-allelic germline variation on MSI. Using MSI burden and bi-allelic alteration status, we reclassify two variants of unknown significance in MSH6 as potentially pathogenic for Lynch syndrome. Extending our analysis of MSI to a set of 127 DNA damage repair (DDR) genes, we identified a novel association between methylation of SHPRH and MSI burden.

          Conclusions

          We find that bi-allelic alterations are infrequent in TCGA but most frequently occur in BRCA1/2 and MMR genes. Our results support the idea that bi-allelic alteration is required for germline variation to influence tumor mutational profile. Overall, we demonstrate that integrating germline, somatic, and epigenetic alterations provides new understanding of somatic mutational profiles.

          Electronic supplementary material

          The online version of this article (10.1186/s13073-018-0579-5) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references24

          • Record: found
          • Abstract: found
          • Article: not found

          Cancer etiology. Variation in cancer risk among tissues can be explained by the number of stem cell divisions.

          Some tissue types give rise to human cancers millions of times more often than other tissue types. Although this has been recognized for more than a century, it has never been explained. Here, we show that the lifetime risk of cancers of many different types is strongly correlated (0.81) with the total number of divisions of the normal self-renewing cells maintaining that tissue's homeostasis. These results suggest that only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions. The majority is due to "bad luck," that is, random mutations arising during DNA replication in normal, noncancerous stem cells. This is important not only for understanding the disease but also for designing strategies to limit the mortality it causes. Copyright © 2015, American Association for the Advancement of Science.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention

            Cancers are caused by mutations that may be inherited, induced by environmental factors, or result from DNA replication errors (R). We studied the relationship between the number of normal stem cell divisions and the risk of 17 cancer types in 69 countries throughout the world. The data revealed a strong correlation (median = 0.80) between cancer incidence and normal stem cell divisions in all countries, regardless of their environment. The major role of R mutations in cancer etiology was supported by an independent approach, based solely on cancer genome sequencing and epidemiological data, which suggested that R mutations are responsible for two-thirds of the mutations in human cancers. All of these results are consistent with epidemiological estimates of the fraction of cancers that can be prevented by changes in the environment. Moreover, they accentuate the importance of early detection and intervention to reduce deaths from the many cancers arising from unavoidable R mutations.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              TP53 Variations in Human Cancers: New Lessons from the IARC TP53 Database and Genomics Data.

              TP53 gene mutations are one of the most frequent somatic events in cancer. The IARC TP53 Database (http://p53.iarc.fr) is a popular resource that compiles occurrence and phenotype data on TP53 germline and somatic variations linked to human cancer. The deluge of data coming from cancer genomic studies generates new data on TP53 variations and attracts a growing number of database users for the interpretation of TP53 variants. Here, we present the current contents and functionalities of the IARC TP53 Database and perform a systematic analysis of TP53 somatic mutation data extracted from this database and from genomic data repositories. This analysis showed that IARC has more TP53 somatic mutation data than genomic repositories (29,000 vs. 4,000). However, the more complete screening achieved by genomic studies highlighted some overlooked facts about TP53 mutations, such as the presence of a significant number of mutations occurring outside the DNA-binding domain in specific cancer types. We also provide an update on TP53 inherited variants including the ones that should be considered as neutral frequent variations. We thus provide an update of current knowledge on TP53 variations in human cancer as well as inform users on the efficient use of the IARC TP53 Database.
                Bookmark

                Author and article information

                Contributors
                arbuckle@ucsd.edu
                tideker@ucsd.edu
                hkcarter@ucsd.edu
                oharismendy@ucsd.edu
                nschork@jcvi.org
                Journal
                Genome Med
                Genome Med
                Genome Medicine
                BioMed Central (London )
                1756-994X
                14 September 2018
                14 September 2018
                2018
                : 10
                : 69
                Affiliations
                [1 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Biomedical Sciences Graduate Program, , University of California San Diego, ; La Jolla, CA USA
                [2 ]GRID grid.469946.0, Human Biology Program, , J. Craig Venter Institute, ; La Jolla, CA USA
                [3 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Division of Medical Genetics, Department of Medicine, , University of California San Diego, ; La Jolla, CA USA
                [4 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Moores Cancer Center, , University of California San Diego, ; La Jolla, CA USA
                [5 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Cancer Cell Map Initiative (CCMI), , University of California San Diego, ; La Jolla, CA USA
                [6 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Division of Biomedical Informatics, Department of Medicine, , University of California San Diego, ; La Jolla, CA USA
                [7 ]ISNI 0000 0004 0507 3225, GRID grid.250942.8, Department of Quantitative Medicine and Systems Biology, , The Translational Genomics Research Institute, ; Phoenix, AZ USA
                [8 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, Departments of Family Medicine and Public Health and Psychiatry, , University of California San Diego, ; La Jolla, CA USA
                Article
                579
                10.1186/s13073-018-0579-5
                6138910
                c28ed64e-c5d6-4c0f-82f9-e05d070e2662
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 7 March 2018
                : 30 August 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: T32GM008666
                Award ID: UL1TR001442
                Award ID: U24AG051129
                Award ID: U19G023122
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Molecular medicine
                cancer genomics,cancer germline,cancer predisposition,tcga,microsatellite instability,lynch syndrome,mutational signatures

                Comments

                Comment on this article