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Spectrum of somatic mitochondrial mutations in five cancers.

ABSTRACT: 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.

SUBMITTER: Larman TC

PROVIDER: S-EPMC3435197 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Spectrum of somatic mitochondrial mutations in five cancers.

Larman Tatianna C TC DePalma Steven R SR Hadjipanayis Angela G AG Protopopov Alexei A Zhang Jianhua J Gabriel Stacey B SB Chin Lynda L Seidman Christine E CE Kucherlapati Raju R Seidman J G JG

Proceedings of the National Academy of Sciences of the United States of America 20120813 35

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 tumo ...[more]

PMID: 22891333

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Project description:BackgroundWith the advent of whole-genome analysis for profiling tumor tissue, a pressing need has emerged for principled methods of organizing the large amounts of resulting genomic information. We propose the concept of multiplicity measures on cancer and gene networks to organize the information in a clinically meaningful manner. Multiplicity applied in this context extends Fearon and Vogelstein's multi-hit genetic model of colorectal carcinoma across multiple cancers.MethodsUsing the Catalogue of Somatic Mutations in Cancer (COSMIC), we construct networks of interacting cancers and genes. Multiplicity is calculated by evaluating the number of cancers and genes linked by the measurement of a somatic mutation. The Kamada-Kawai algorithm is used to find a two-dimensional minimum energy solution with multiplicity as an input similarity measure. Cancers and genes are positioned in two dimensions according to this similarity. A third dimension is added to the network by assigning a maximal multiplicity to each cancer or gene. Hierarchical clustering within this three-dimensional network is used to identify similar clusters in somatic mutation patterns across cancer types.ResultsThe clustering of genes in a three-dimensional network reveals a similarity in acquired mutations across different cancer types. Surprisingly, the clusters separate known causal mutations. The multiplicity clustering technique identifies a set of causal genes with an area under the ROC curve of 0.84 versus 0.57 when clustering on gene mutation rate alone. The cluster multiplicity value and number of causal genes are positively correlated via Spearman's Rank Order correlation (rs(8) = 0.894, Spearman's t = 17.48, p < 0.05). A clustering analysis of cancer types segregates different types of cancer. All blood tumors cluster together, and the cluster multiplicity values differ significantly (Kruskal-Wallis, H = 16.98, df = 2, p < 0.05).ConclusionWe demonstrate the principle of multiplicity for organizing somatic mutations and cancers in clinically relevant clusters. These clusters of cancers and mutations provide representations that identify segregations of cancer and genes driving cancer progression.

Project description:PURPOSE:The therascreen PIK3CA mutation assay and the alpha-specific PI3K inhibitor alpelisib are FDA-approved for identifying and treating patients with advanced PIK3CA-mutated (PIK3CAmut) breast cancer (BC). However, it is currently unknown to what extend this assay detects most PIK3CA mutations in BC. This information is critical as patients and clinicians are using this and other genomic assays to indicate alpelisib. METHODS:Data from 6338 patients with BC was explored across 10 publicly available studies. The primary objective was to evaluate the proportion and distribution of PIK3CA mutations in BC. Secondary objectives were (1) to evaluate in silico the spectrum of PIK3CA mutations in BC that would be captured by the therascreen panel; (2) to evaluate the proportion and distribution of PIK3CA mutations in hormone receptor-positive/HER2-negative (HR+/HER2-), HER2+, and triple-negative BC (TNBC); and (3) to explore the identification of PIK3CA mutations in a cohort of 48 HR+/HER2- advanced BC patients by the Guardant B360 circulating tumor DNA (ctDNA) assay. RESULTS:Patients with PIK3CAmut tumors represented 35.7% (2261/6338). Five PIK3CA mutations comprised 73% of all PIK3CA mutations: H1047R (35%), E545K (17%), E542K (11%), N345K (6%), and H1047L (4%). Therascreen gene list would capture 72% of all PIK3CA mutations and 80% of patients with a known PIK3CAmut BC. Among patients with double PIK3CAmut tumors (12% of all PIK3CAmut), the therascreen panel would capture 78% as harboring 1 single PIK3CA mutation, 17% as PIK3CAmut undetected, and 5% as PIK3CA double-mut. PIK3CA mutation rates were lower in TNBC (16%) compared to HR+/HER2 (42%) and HER2+ (31%) BC; however, the distribution of the 4 main PIK3CA mutations across subtypes was similar. Finally, 28% of PIK3CA mutations identified in ctDNA in 48 patients with advanced HR+/HER2- BC were not part of the therascreen panel. CONCLUSION:PIK3CA mutations in BC are heterogenous and ~?20% of patients with a known PIK3CA mutation, and 95% with a known double PIK3CAmut tumor, would not be captured by the therascreen panel. Finally, the clinical utility of PIK3CA mutations not present in the therascreen companion diagnostic assay or identified by other sequencing-based assays needs further investigation.

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Spectrum of somatic mitochondrial mutations in five cancers.

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Spectrum of somatic mitochondrial mutations in five cancers.

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