Knowledge Of Somatic Mutations Research Articles

Abstract 2280: Comparison of somatic mutations of whole exome sequencing data from black and white patients with esophageal adenocarcinoma

Abstract Introduction: Esophageal adenocarcinoma (EAC) is the most common histological subtype of esophageal cancer in western countries and shows poor prognosis and rapid growth. EAC is characterized by a strong male predominance and racial disparity. EAC is up to five-fold more common among whites than Blacks, yet Black patients with EAC have poorer survival rates. The reason for the racial disparity is still largely unknown. Knowledge of somatic mutations in EAC from recent DNA sequencing studies have shown EAC has a high mutation burden and distinct mutational signatures. However, knowledge of mutations in EAC regarding racial disparities is limited. Methods: In this study, we performed whole-exome sequencing of tumors obtained from 10 Black patients and 8 White patients with EAC. We performed Principal Component Analysis (PCA) by using subset of SNPs with FST>0.2. We performed mutational signature analysis using non-negative matrix factorization (NMF) and R package MutationalPatterns. We used the Wilcoxon rank-sum test to compare mutational signature contributions between racial groups and performed Fisher’s exact test to compare the gene-level somatic mutation counts between racial groups. All p-values were two sided and the significant level was 0.05. Results: We identified 5,281 variants for the PCA and found principal component 1 (PC1) was strongly associated with race. We identified 94,482 somatic mutations and found 3 mutational signatures (A, B and C). “Signature A” was strongly correlated with Signature 19 (cosine-similarity: 0.80, unknown etiology), “Signature B” was strongly correlated with Signatures 4 and 29 (cosine-similarity: 0.78 and 0.80 respectively, etiology: smoking and chewing tobacco), and “Signature C” was strongly correlated with Signature 1 (cosine-similarity: 0.82, etiology: aging). There were no statistically significant differences of the 3 mutational signatures between tumors from black and white patients in EAC. When decomposing mutation count matrix into a sum of known components, we identified 25 COSMIC signatures, and found Signature12 (unknown etiology) shows more contribution in Black patients than in White patients and the difference was statistically significant (p=0.0008, q=0.02). For gene-level analysis, we found TP53 was the most frequently mutated in EAC patients and ARID1A and SMAD4 were the second group of driver genes. There was no statistically significant difference between the gene-level mutations among blacks and whites (Fisher exact test, P>0.05). Conclusion: These results demonstrate that EAC from black patients are similar to cancers from white patients with respect to clinically actionable genomic alterations. Mutational signature 12 might be the characteristic gene mutation that contribute to the racial difference between Black and White EAC patients. Citation Format: Jing Zhao, Spiridon Tsavachidis, Christopher Amos, Aaron P. Thrift. Comparison of somatic mutations of whole exome sequencing data from black and white patients with esophageal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2280.

Abstract 580: The broad surveillance and unbiased detection of circulating tumor DNA using next-generation sequencing without a priori knowledge of somatic mutations is a prognostically significant biomarker in pancreatic ductal adenocarcinoma

Abstract Background. Detection of low frequency tumor-derived variants in circulating cell-free DNA (ccfDNA; i.e., circulating tumor DNA, ctDNA) without a priori knowledge of mutations in the matched solid tumor is confounded by next-generation sequencing (NGS) noise and constrained by theoretical and practical limitations associated with low DNA yield from plasma. Here, we leverage technical replicates (two libraries prepared and sequenced independently from each extracted ccfDNA sample) to simultaneously suppress NGS-associated errors and improve detection of ctDNA derived from pancreatic ductal adenocarcinomas (PDACs). Methods. Pre-operative ccfDNA and tumor DNA were acquired from 14 patients with PDAC (78.6% stage II-III) undergoing surgery aimed at complete total resection. For 11 patients, ccfDNA was also collected post-operatively within 100 days of surgery. Two technical replicates of ccfDNA libraries using molecular barcodes were independently generated using 2 mL plasma equivalents of ccfDNA for each library. Subsequently, libraries were capture-enriched using a 118 gene panel (~124 kb) and underwent NGS (paired-end, 125x2; HiSeq 2500). Consensus sequence determination and position-specific error modeling were coupled with restricting variant identification to nonreference alleles present in both patient replicates that corresponded to COSMIC-reported pathogenic mutations in PDAC. Results. PDAC-associated pathogenic mutations were detected in pre-operative ccfDNA in four genes (KRAS, TP53, SMAD4, ALK) from five patients (35.7%) with a variant allele frequency ranging from 0.08% to 1.59% (median: 0.25%). Of the nine ctDNA variants identified, five (55.6%) had a corresponding mutation in tumor DNA. The estimated median overall survival in patients with and without detection of pre-operative ctDNA was significantly different (312 vs. 826 days, respectively; χ2=5.3, P=0.0207). Using mutations identified in tumor tissue DNA to guide detection of pre-operative ctDNA yielded a similar survival analysis (369 vs 1,011 days, respectively; χ2=5.6, P=0.018). Detection of ctDNA in post-operative ccfDNA with or without guidance from tumor tissue mutations was not associated with outcomes. Applying the noise reduction strategy used to detect ctDNA in PDAC patients eliminated false positives from healthy controls. Conclusions. Acquisition of NGS data in replicate coupled with in silico error suppression strategies enabled detection of ctDNA without a priori knowledge of tumor variants, which overcomes a major obstacle limiting ccfDNA applications. Pre-operative ctDNA detected during a broad and untargeted survey of ccfDNA with NGS is a non-invasive, prognostic biomarker to help guide PDAC patient management. Citation Format: Kajsa E. Affolter, Sabine Hellwig, David A. Nix, Mary P. Bronner, Alun Thomas, Carrie L. Fuertes, Cindy L. Hamil, Ignacio Garrido-Laguna, Courtney L. Scaife, Sean J. Mulvihill, Hunter R. Underhill. The broad surveillance and unbiased detection of circulating tumor DNA using next-generation sequencing without a priori knowledge of somatic mutations is a prognostically significant biomarker in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 580.

Abstract 906: COSMIC: Describing the world’s knowledge of somatic mutations in cancer

Abstract COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk/cosmic) is a continual effort to integrate all available information on somatic mutations and other molecular alterations causing every form of human cancer. Being the world’s largest and most comprehensive database of somatic mutations in human cancer, it also provides web-based tools for exploration and interpretation of collected data. The content of the database is primarily obtained from the scientific literature by the team of experienced post-doctoral curators and combined with information from online sources, including the TCGA and ICGC. During thorough & exhaustive manual curation, all the available information about mutations and tumor samples (e.g. disease type, demographic data, treatments) are collected, standardized and integrated to allow for both creation of wide virtual cohorts and large-scale studies, as well as precise analysis at the level of a single sample, gene or mutation. The 87th release of COSMIC (Nov 2018) encompasses 5,992,260 coding mutations and 19,574 gene fusions, curated from 1,403,267 cancer samples, including 35,490 whole cancer exomes/genomes, primarily hand-curated data from 26,494 scientific publications. Additionally, COSMIC describes 1,179,545 Copy Number Variants, 9,147,833 gene expression variants, and 7,879,142 differentially methylated CPGs. In addition to this broad database, COSMIC includes a range of specialized projects highlighting specific aspects of cancer in order to emphasize events with a higher impact in disease etiology. This includes the Cancer Gene Census (http://cancer.sanger.ac.uk/census), which defines and describes genes (currently 719) and their dysfunctions driving oncogenesis, and characterizes their impact on hallmarks of cancer. COSMIC3D (http://cancer.sanger.ac.uk/cosmic3d) provides an interactive view of cancer mutations in the context of 3D protein structures, and predicts potential drug-binding sites. Significantly updated 4 times a year, COSMIC is available free-of-charge for academic and non-profit users via COSMIC webpage (http://cancer.sanger.ac.uk/cosmic) or to download through COSMIC downloads (http://cancer.sanger.ac.uk/cosmic/download). Citation Format: Simon Andrew Forbes, david beare, charalampos boutselakis, sally bamford, kate noble, claire rye, john tate, chai yin kok, charlie hathaway, laura ponting, christopher ramshaw, raymund stefancsik, samantha thompson, bhavana harsha, nidhi bindal, shicai wang, steven jupe, helen speedy, celestino creatore, peter fish, sari ward, charlotte cole, elisabeth dawson, zbyslaw sondka. COSMIC: Describing the world’s knowledge of somatic mutations in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 906.

COSMIC: integrating and interpreting the world's knowledge of somatic mutations in cancer

COSMIC: integrating and interpreting the world's knowledge of somatic mutations in cancer

Abstract 3284: COSMIC: Integrating and interpreting the world's knowledge of somatic mutations in cancer

Abstract COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk/cosmic) is a long-term sustainable effort to collect, standardise and integrate information on somatic mutations and other molecular alterations that cause human cancer. Being the world's largest and most comprehensive database of somatic mutations in cancer, it also provides web-based tools for exploration and interpretation of collected data. The content of the database is obtained primarily by careful curation of the scientific literature by a team of experienced post-doctoral curators, allowing mutations to be described across every form of human cancer at high resolution (covering 1,706 cancer phenotypes). This is then combined with data from a number of on-line sources, including the TCGA and ICGC web portals. During exhaustive manual curation, all the available information about mutations and samples (e.g. disease type, demographic data, treatments) are collected, standardised and integrated to allow for both creation of wide virtual cohorts and large-scale studies, as well as precise analysis at the level of a single sample, gene or mutation. To support investigations into how genes dysfunction to drive cancer, the 83rd release of COSMIC (Nov 2017) encompasses 5,366,273 coding mutations and 18,845 gene fusions in 1,343,214 cancer samples, hand-curated from 25,501 scientific publications, including 32,514 whole cancer genomes. Further curations support examination of gene dysregulation in cancer, including 16,961,605 non-coding variants, 1,180,789 Copy Number Variants, 9,176,464 gene expression variants, and 7,879,142 differentially methylated CpGs. Specialised COSMIC projects highlight specific knowledge of cancer in order to characterise events with a higher impact in disease aetiology. The Cancer Gene Census (http://cancer.sanger.ac.uk/census), currently defines and describes 699 genes, how their dysfunctions drive oncogenesis, and characterises their impact on hallmarks of cancer. COSMIC-3D (http://cancer.sanger.ac.uk/cosmic3d) provides an interactive view of cancer mutations in the context of 3D protein structures, and predicts potential drug-binding sites. Mutations causing drug resistance are now described as a new resource (http://cancer.sanger.ac.uk/cosmic/drug_resistance). To allow for the incorporation of new data exploration tools, the COSMIC web page layouts have been updated and their usability has been improved, giving more options to filter webpage content. COSMIC is significantly updated 4 times a year, and is available free-of-charge for academic and non-profit users via COSMIC webpage (http://cancer.sanger.ac.uk/cosmic) or to download through COSMIC downloads (http://cancer.sanger.ac.uk/cosmic/download) Citation Format: Zbyslaw Sondka, Sally Bamford, Charlotte G. Cole, Elisabeth Dawson, Laura Ponting, Raymund Stefancsik, Sari Ward, Harry C. Jubb, Sam Thompson, Dave Beare, Nidhi Bindal, Charambulos Boutselakis, Peter Fish, Bhavana Harsha, Chai Yin Kok, Chris Ramshaw, Claire Rye, John Tate, Shicai Wang, Peter J. Campbell, Simon A. Forbes. COSMIC: Integrating and interpreting the world's knowledge of somatic mutations in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3284.

Biomarkers in colorectal liver metastases.

Despite a 5-year overall survival rate of 58 per cent after liver resection for colorectal liver metastases (CLMs), more than half of patients develop recurrence, highlighting the need for accurate risk stratification and prognostication. Traditional prognostic factors have been superseded by newer outcome predictors, including those defined by the molecular origin of the primary tumour. This review synthesized findings in the literature using the PubMed database of articles in the English language published between 1998 and 2017 on prognostic and predictive biomarkers in patients undergoing resection of CLMs. Responses to preoperative chemotherapy define prognosis in patients undergoing CLM resection. There are differences by embryological origin too. Somatic mutations in the proto-oncogenes KRAS and NRAS are associated with positive surgical margins and tumour regrowth after ablation. Other mutations (such as BRAF) and co-occurring mutations in RAS/TP53 and APC/PIK3CA have emerged as important biomarkers that determine an individual patient's tumour biology and may be used to predict outcome after CLM resection. Knowledge of somatic mutations can guide the use of preoperative therapy, extent of surgical margin and selection for ablation alone.

Biochemical Classification of Disease-associated Mutants of RAS-like Protein Expressed in Many Tissues (RIT1)

RAS-like protein expressed in many tissues 1 (RIT1) is a disease-associated RAS subfamily small guanosine triphosphatase (GTPase). Recent studies revealed that germ-line and somatic RIT1 mutations can cause Noonan syndrome (NS), and drive proliferation of lung adenocarcinomas, respectively, akin to RAS mutations in these diseases. However, the locations of these RIT1 mutations differ significantly from those found in RAS, and do not affect the three mutational "hot spots" of RAS. Moreover, few studies have characterized the GTPase cycle of RIT1 and its disease-associated mutants. Here we developed a real-time NMR-based GTPase assay for RIT1 and investigated the effect of disease-associated mutations on GTPase cycle. RIT1 exhibits an intrinsic GTP hydrolysis rate similar to that of H-RAS, but its intrinsic nucleotide exchange rate is ∼4-fold faster, likely as a result of divergent residues near the nucleotide binding site. All of the disease-associated mutations investigated increased the GTP-loaded, activated state of RIT1 in vitro, but they could be classified into two groups with different intrinsic GTPase properties. The S35T, A57G, and Y89H mutants exhibited more rapid nucleotide exchange, whereas F82V and T83P impaired GTP hydrolysis. A RAS-binding domain pulldown assay indicated that RIT1 A57G and Y89H were highly activated in HEK293T cells, whereas T83P and F82V exhibited more modest activation. All five mutations are associated with NS, whereas two (A57G and F82V) have also been identified in urinary tract cancers and myeloid malignancies. Characterization of the effects on the GTPase cycle of RIT1 disease-associated mutations should enable better understanding of their role in disease processes.

COSMIC: exploring the world's knowledge of somatic mutations in human cancer.

COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk) is the world's largest and most comprehensive resource for exploring the impact of somatic mutations in human cancer. Our latest release (v70; Aug 2014) describes 2 002 811 coding point mutations in over one million tumor samples and across most human genes. To emphasize depth of knowledge on known cancer genes, mutation information is curated manually from the scientific literature, allowing very precise definitions of disease types and patient details. Combination of almost 20 000 published studies gives substantial resolution of how mutations and phenotypes relate in human cancer, providing insights into the stratification of mutations and biomarkers across cancer patient populations. Conversely, our curation of cancer genomes (over 12 000) emphasizes knowledge breadth, driving discovery of unrecognized cancer-driving hotspots and molecular targets. Our high-resolution curation approach is globally unique, giving substantial insight into molecular biomarkers in human oncology. In addition, COSMIC also details more than six million noncoding mutations, 10 534 gene fusions, 61 299 genome rearrangements, 695 504 abnormal copy number segments and 60 119 787 abnormal expression variants. All these types of somatic mutation are annotated to both the human genome and each affected coding gene, then correlated across disease and mutation types.

Abstract 5326: COSMIC: Enhancing the world's knowledge of somatic mutations in human cancer

Abstract COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk) is the world's largest and most comprehensive online resource for exploring the impact of somatic mutations in human cancer. Now running for over 10 years, the 67th release (Oct 2013) describes 1592109 mutations in 947213 tumour samples across 25606 genes. This information is curated manually from the scientific literature, and automatically from genome resequencing consortium data portals. Full curation of the scientific literature provides in-depth understanding of the impact that each gene has in human cancer, and this has been achieved for 127 point-mutated cancer genes, and 185 fusion gene pairs. Curated genes are selected from the Cancer Gene Census (http://cancer.sanger.ac.uk/census), a listing of all genes with substantial evidence implicating them in cancer promotion, currently numbering 513 and updated frequently. The mutations discovered in the re-sequencing of over 8000 tumour genomes are now present in COSMIC (viewable in isolation from the genic curations, http://cancer.sanger.ac.uk/wgs). In addition, the Sanger has now fully exome sequenced 1015 common cancer cell lines, identifying 1146874 coding mutations annotated for functional significance, and this is available exclusively in COSMIC at (http://cancer.sanger.ac.uk/cell_lines). While COSMIC has focused on point mutations and gene fusions, many other mutation mechanisms cause oncogenesis and these are now being integrated. The 67th COSMIC release includes copy number mutations integrated into the database and major web page views. To allow easy graphical examination of this data, copy number information was reduced to ‘gain’ and ‘loss’ annotations for inclusion in histograms and tables, with much more precise detail available with a further click. Copy number data is available in detail for every gene in COSMIC, and also for every tissue. Exploring cancer via COSMIC’s Cancer Browser (http://cancer.sanger.ac.uk/cosmic/browse/tissue), results not just in a plot of the most mutated genes, but now also a circular genome plot summarizing the copy number gains and losses across all the samples from that tumour type, all explorable in more detail via clicks on the pictures. As the genomic data increases in COSMIC, it is becoming more important to qualitatively annotate the information, indicating which is more important or significant to oncogenesis. We are now building systems to better highlight known or putative functional mutations, improving the signal-to-noise ratio of cancer genome resequencing. Citation Format: C Boutselakis, S A. Forbes, P Gunasekaran, M Jia, D Beare, N Bindal, C Y. Kok, K Leung, D Minjie, R Shepherd, S Bamford, S Ward, C Cole, J W. Teague, M Stratton, P Campbell, U McDermott. COSMIC: Enhancing the world's knowledge of somatic mutations in human cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5326. doi:10.1158/1538-7445.AM2014-5326

Abstract 5142: COSMIC: Exploring the world's knowledge of somatic mutations in cancer.

Abstract COSMIC, the Catalogue Of Somatic Mutations in Cancer (http://cancer.sanger.ac.uk/), is the world's largest database of curated somatic mutations. The current version (v62, Nov 2012) has over a million mutations across 800000 samples from 15327 peer-reviewd publications, online data portals such as TCGA, ICGC, the IARC p53 database and the Cancer Genome Project (CGP) at the Sanger Institute, UK. The project aims to build a comprehensive catalogue of somatic mutations prioritized by the Cancer Gene Census (http://cancer.sanger.ac.uk/cancergenome/projects/census/), allowing users to explore correlations between cancer phenotypes and mutant genotypes. At present, a full distribution of somatic mutations have been curated across 116 known cancer genes and 169 gene fusion pairs. A focus on cancer genomes has recently emerged from the rapid expansion of whole genome/exome resequencing, as shown by our "COSMIC Genomes" website (http://cancer.sanger.ac.uk/cancergenome/projects/studies/), already comprising over 4500 tumours across a variety of cancer types. There are a number of ways to examine the data within COSMIC. A newly released website provides an intuitive interface for users to scrutinize the data through numerous filters, including mutation types, histology and tissue types. This is supplimented with statistical summaries presented in many graphs and charts. The website includes a COSMIC genome browser for views across combined cancer genomes, including all mutation types in one graphical window. Many other resources are designed for bioinformatic access including a Biomart, and FTP downloads in a variety of formats (ftp://ftp.sanger.ac.uk/pub/CGP/cosmic/). We actively seek to integrate with the wider bioinformatics community and are integrated within the UCSC and Ensembl genome browsers. COSMIC both documents mutation trends in known cancer genes, and combines distributed information to allow substantial mining of these data for discovery of novel correlations. COSMIC can aid discovery of novel recurrence patterns between variants, genes and tissues in different mutant genotypes and cancer phenotypes. The most frequently mutated gene in COSMIC (v62, Nov 2012), is JAK2 with the p.V617F mutation observed in 36% of all blood cancers examined. This is followed by TP53 with a variety of truncating mutations observed at a total frequency of 29.7%, and KRAS, found mutated in 21% of cancers, most frequently p.G12D in pancreatic tumours. Focusing particularly on the 4571 whole genomes, the most mutated gene is unsurprisingly TP53 at 27.57% (followed by TTN, MUC16, PIK3CA, CSMD3). Many techniques may identify putative novel cancer genes outside the cancer gene census. For instance, in Lung cancer the most mutated genes (correcting for CDS length) are TPTE, FAM5C, CDH10 and KEAP1. The rapid combination of increasingly large datasets in COSMIC ensure its future relevance in discovery of new trends in cancer genetics. Citation Format: Kenric Leung, Chai Yin Kok, Rebecca Shepherd, John Gamble, Mingming Jia, Sally Bamford, Sari Ward, Charlotte Cole, David Beare, Nidhi Bindal, Prasad Gunasekaran, Jon Teague, Simon A. Forbes, Michael R. Stratton, Peter Campbell. COSMIC: Exploring the world's knowledge of somatic mutations in cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5142. doi:10.1158/1538-7445.AM2013-5142

PIK3CA, HRAS and KRAS Gene Mutations in Human Penile Cancer

The knowledge of somatic mutations that arise in penile cancer is limited. We examined the dysregulation of components in the phosphatidylinositol 3-kinase and Ras pathways. Using single stranded conformational analysis and direct sequencing we performed mutational analysis of the PIK3CA, PTEN, HRAS, KRAS, NRAS and BRAF genes in 28 penile tumors. We identified somatic missense mutations in 11 of the 28 penile cancer samples (39%). In the PIK3CA gene 8 mutations (29%) were identified that were E542K or E545K. In the HRAS gene a G12S and a Q61L mutation were found (7%). The KRAS gene contained 1 mutation (3%), that is a G12S change. PIK3CA mutations were found in all grades and stages, whereas HRAS and KRAS mutations were found in larger and more advanced tumors. The mutations were mutually exclusive, suggesting that dysregulation of either pathway is sufficient for the development and progression of penile carcinoma. The high frequency of mutations in the PIK3CA, HRAS and KRAS genes leads us to believe that dysregulation of the phosphatidylinositol 3-kinase or Ras pathway is significant for the development and progression of penile carcinoma.