Immunogenicity of somatic mutations in human gastrointestinal cancers.
Ontology highlight
ABSTRACT:
SUBMITTER: Tran E
PROVIDER: S-EPMC7445892 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Immunotherapies can mediate regression of human tumors with high mutation rates, but responses are rarely observed in patients with common epithelial cancers. This raises the question of whether patients with these common cancers harbor T lymphocytes that recognize mutant proteins expressed by autologous tumors that may represent ideal targets for immunotherapy. Using high-throughput immunologic screening of mutant gene products identified via whole-exome sequencing, we identified neoantigen-reactive tumor-infiltrating lymphocytes (TIL) from 62 of 75 (83%) patients with common gastrointestinal cancers. In total, 124 neoantigen-reactive TIL populations were identified, and all but one of the neoantigenic determinants were unique. The results of in vitro T-cell recognition assays demonstrated that 1.6% of the gene products encoded by somatic nonsynonymous mutations were immunogenic. These findings demonstrate that the majority of common epithelial cancers elicit immune recognition and open possibilities for cell-based immunotherapies for patients bearing these cancers. SIGNIFICANCE: TILs cultured from 62 of 75 (83%) patients with gastrointestinal cancers recognized neoantigens encoded by 1.6% of somatic mutations expressed by autologous tumor cells, and 99% of the neoantigenic determinants appeared to be unique and not shared between patients.This article is highlighted in the In This Issue feature, p. 983.
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Project description:Whole-exome and whole-genome sequencing have revealed millions of somatic mutations associated with different human cancers, and the vast majority of them are located outside of coding sequences, making it challenging to directly interpret their functional effects. With the rapid advances in high-throughput sequencing technologies, genome-scale long-range chromatin interactions were detected, and distal target genes of regulatory elements were determined using three-dimensional (3D) chromatin looping. Herein, we present OncoBase (http://www.oncobase.biols.ac.cn/), an integrated database for annotating 81 385 242 somatic mutations in 68 cancer types from more than 120 cancer projects by exploring their roles in distal interactions between target genes and regulatory elements. OncoBase integrates local chromatin signatures, 3D chromatin interactions in different cell types and reconstruction of enhancer-target networks using state-of-the-art algorithms. It employs informative visualization tools to display the integrated local and 3D chromatin signatures and effects of somatic mutations on regulatory elements. Enhancer-promoter interactions estimated from chromatin interactions are integrated into a network diffusion system that quantitatively prioritizes somatic mutations and target genes from a large pool. Thus, OncoBase is a useful resource for the functional annotation of regulatory noncoding regions and systematically benchmarking the regulatory effects of embedded noncoding somatic mutations in human carcinogenesis.
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Project description:Large-scale cancer sequencing studies of patient cohorts have statistically implicated many genes driving cancer growth and progression, and their identification has yielded substantial translational impact. However, a remaining challenge is to increase the resolution of driver prediction from the level of genes to mutations because mutation-level predictions are more closely aligned with the goal of precision cancer medicine. Here, we present CHASMplus, a computational method that is uniquely capable of identifying driver missense mutations, including those specific to a cancer type, as evidenced by significantly superior performance on diverse benchmarks. Applied to 8,657 tumor samples across 32 cancer types in The Cancer Genome Atlas (TCGA), CHASMplus identifies over 4,000 unique driver missense mutations in 240 genes, supporting a prominent role for rare driver mutations. We show which TCGA cancer types are likely to yield discovery of new driver missense mutations by additional sequencing, which has important implications for public policy.
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Project description:Cancer is characterized by uncontrolled cell growth, and the cause of different cancers is generally attributed to checkpoint dysregulation of cell proliferation and apoptosis. Recent studies have shown that non-optimal codons were preferentially adopted by genes to generate cell cycle-dependent oscillations in protein levels. This raises the intriguing question of how dynamic changes of codon usage modulate the cancer genome to cope with a non-controlled proliferative cell cycle. In this study, we comprehensively analyzed the somatic mutations of codons in human cancers, and found that non-optimal codons tended to be accumulated through both synonymous and non-synonymous mutations compared with other types of genomic substitution. We further demonstrated that non-optimal codons were prevalently accumulated across different types of cancers, amino acids, and chromosomes, and genes with accumulation of non-optimal codons tended to be involved in protein interaction/signaling networks and encoded important enzymes in metabolic networks that played roles in cancer-related pathways. This study provides insights into the dynamics of codons in the cancer genome and demonstrates that accumulation of non-optimal codons may be an adaptive strategy for cancerous cells to win the competition with normal cells. This deeper interpretation of the patterns and the functional characterization of somatic mutations of codons will help to broaden the current understanding of the molecular basis of cancers.
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Project description:Somatic mutations in the nuclear genome are required for tumor formation, but the functional consequences of somatic mitochondrial DNA (mtDNA) mutations are less understood. Here we identify somatic mtDNA mutations across 527 tumors and 14 cancer types, using an approach that takes advantage of evidence from both genomic and transcriptomic sequencing. We find that there is selective pressure against deleterious coding mutations, supporting that functional mitochondria are required in tumor cells, and also observe a strong mutational strand bias, compatible with endogenous replication-coupled errors as the major source of mutations. Interestingly, while allelic ratios in general were consistent in RNA compared to DNA, some mutations in tRNAs displayed strong allelic imbalances caused by accumulation of unprocessed tRNA precursors. The effect was explained by altered secondary structure, demonstrating that correct tRNA folding is a major determinant for processing of polycistronic mitochondrial transcripts. Additionally, the data suggest that tRNA clusters are preferably processed in the 3' to 5' direction. Our study gives insights into mtDNA function in cancer and answers questions regarding mitochondrial tRNA biogenesis that are difficult to address in controlled experimental systems.
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Project description:BackgroundMalignant transformation requires the interaction of cancer cells with their microenvironment, including infiltrating leukocytes. However, somatic mutational studies have focused on alterations in cancer cells, assuming that the microenvironment is genetically normal. Because we hypothesized that this might not be a valid assumption, we performed exome sequencing and targeted sequencing to investigate for the presence of pathogenic mutations in tumor-associated leukocytes in breast cancers.MethodsWe used targeted sequencing and exome sequencing to evaluate the presence of mutations in sorted tumor-infiltrating CD45-positive cells from primary untreated breast cancers. We used high-depth sequencing to determine the presence/absence of the mutations we identified in breast cancer-infiltrating leukocytes in purified tumor cells and in circulating blood cells.ResultsCapture-based sequencing of 15 paired tumor-infiltrating leukocytes and matched germline DNA identified variants in known cancer genes in all 15 primary breast cancer patients in our cohort. We validated the presence of mutations identified by targeted sequencing in infiltrating leukocytes through orthogonal exome sequencing. Ten patients harbored alterations previously reported as somatically acquired variants, including in known leukemia genes (DNTM3A, TET2, and BCOR). One of the mutations observed in the tumor-infiltrating leukocytes was also detected in the circulating leukocytes of the same patients at a lower allele frequency than observed in the tumor-infiltrating cells.ConclusionsHere we show that somatic mutations, including mutations in known cancer genes, are present in the leukocytes infiltrating a subset of primary breast cancers. This observation allows for the possibility that the cancer cells interact with mutant infiltrating leukocytes, which has many potential clinical implications.
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Project description:Somatic mtDNA mutations have been reported in some human tumors, but their spectrum in different malignancies and their role in cancer development remain incompletely understood. Here, we describe the breadth of somatic and inherited mutations across the mitochondrial genome by sequence analyses of paired tumor and normal tissue samples from 226 individuals with five types of cancer using whole-genome data generated by The Cancer Genome Atlas Research Network. The frequencies of deleterious tumor-specific somatic mutations found in mtDNA varied across tumor types, ranging from 13% of glioblastomas to 63% of rectal adenocarcinomas. Compared with inherited mtDNA variants, somatic mtDNA mutations were enriched for nonsynonymous vs. synonymous changes (93 vs. 15; P < 2.2E-16) and were predicted to functionally impact the encoded protein. Somatic missense mutations in tumors were distributed uniformly among the mitochondrial protein genes, but 65% of somatic truncating mutations occurred in NADH dehydrogenase 5. Analysis of staging data in colon and rectal cancers revealed that the frequency of damaging mitochondrial mutations is the same in stages I and IV tumors. In summary, these data suggest that damaging somatic mtDNA mutations occur frequently (13-63%) in these five tumor types and likely confer a selective advantage in oncogenesis.
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Project description:TP53 is the most frequently altered gene in human cancers. Numerous retrospective studies have related its mutation and abnormal p53 protein expression to poor patient survival. Nonetheless, the clinical significance of TP53 (p53) status has been a controversial issue. In this work, we aimed to characterize TP53 somatic mutations in tumor cells across multiple cancer types, primarily focusing on several less investigated features of the mutation spectra, and determine their prognostic implications. We performed an integrative study on the clinically annotated genomic data released by The Cancer Genome Atlas. Standard statistical methods, such as the Cox proportional hazards model and logistic regression, were used. This study resulted in several novel findings. They include the following: (1) similar to previously reported cases in breast cancer, the mutations in exons 1 to 4 of TP53 were more lethal than those in exons 5 to 9 for the patients with lung adenocarcinomas; (2) TP53 mutants tended to be negatively selected in mammalian evolution, but the evolutionary conservation had various clinical implications for different cancers; (3) conserved correlation patterns (ie, consistent co-occurrence or consistent mutual exclusivity) between TP53 mutations and the alterations in several other cancer genes (ie, PIK3CA, PTEN, KRAS, APC, CDKN2A, and ATM) were present in several cancers in which prognosis was associated with TP53 status and/or the mutational characteristics; (4) among TP53-mutated tumors, the total mutation burden in other driver genes was a predictive signature (P <.05, false discovery rate <0.11) for better patient survival outcome in several cancer types, including glioblastoma multiforme. Among these findings, the fourth is of special significance as it suggested the potential existence of epistatic interaction effects among the mutations in different cancer driver genes on clinical outcomes.
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Project description:The histone demethylase KDM6A has recently elicited significant attention because its mutations are associated with a rare congenital disorder (Kabuki syndrome) and various types of human cancers. However, distinguishing KDM6A mutations that are deleterious to the enzyme and their underlying mechanisms of dysfunction remain to be fully understood. Here, we report the results from a multi-tiered approach evaluating the impact of 197 KDM6A somatic mutations using information derived from combining conventional genomics data with computational biophysics. This comprehensive approach incorporates multiple scores derived from alterations in protein sequence, structure, and molecular dynamics. Using this method, we classify the KDM6A mutations into 136 damaging variants (69.0%), 32 tolerated variants (16.2%), and 29 variants of uncertain significance (VUS, 14.7%), which is a significant improvement from the previous classification based on the conventional tools (over 40% VUS). We further classify the damaging variants into 15 structural variants (SV), 88 dynamic variants (DV), and 33 structural and dynamic variants (SDV). Comparison with variant scoring methods used in current clinical diagnosis guidelines demonstrates that our approach provides a more comprehensive evaluation of damaging potential and reveals mechanisms of dysfunction. Thus, these results should be taken into consideration for clinical assessment of the damaging potential of each mutation, as they provide hypotheses for experimental validation and critical information for the development of mutant-specific drugs to fight diseases caused by KDM6A dysfunctions.
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