Dataset Information

Somatic mutation profiles in primary colorectal cancers and matching ovarian metastases: Identification of driver and passenger mutations.

ABSTRACT: The mutational profiles of primary colorectal cancers (CRCs) and corresponding ovarian metastases were compared. Using a custom-made next generation sequencing panel, 115 cancer-driving genes were analyzed in a cohort of 26 primary CRCs and 30 matching ovarian metastases (four with bilateral metastases). To obtain a complete overview of the mutational profile, low thresholds were used in bioinformatics analysis to prevent low frequency passenger mutations from being filtered out. A subset of variants was validated using Sanger and/or hydrolysis probe assays. The mutational landscape of CRC that metastasized to the ovary was not strikingly different from CRC in consecutive series. When comparing primary CRCs and their matching ovarian metastases, there was considerable overlap in the mutations of early affected genes. A subset of mutations demonstrated less overlap, presumably being passenger mutations. In particular, primary CRCs showed a substantially high number of passenger mutations. We also compared the primary CRCs and matching metastases for stratifying variants of six genes (KRAS, NRAS, BRAF, FBXW7, PTEN and PIK3CA) that select for established (EGFR directed) or future targeted therapies. In a total of 31 variants 12 were not found in either of the two locations. Tumours thus differed in the number of discordant variants between the primary tumours and matching metastases. Half of these discordant variants were definitive class 4/5 pathogenic variants. However, in terms of temporal heterogeneity, no clear relationship was observed between the number of discordant variants and the time interval between primary CRCs and the detection of ovarian metastases. This suggests that dormant metastases may be present from the early days of the primary tumours.

SUBMITTER: Crobach S

PROVIDER: S-EPMC4958737 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Somatic mutation profiles in primary colorectal cancers and matching ovarian metastases: Identification of driver and passenger mutations.

Crobach Stijn S Ruano Dina D van Eijk Ronald R Schrumpf Melanie M Fleuren Gertjan G van Wezel Tom T Morreau Hans H

The journal of pathology. Clinical research 20160415 3

The mutational profiles of primary colorectal cancers (CRCs) and corresponding ovarian metastases were compared. Using a custom-made next generation sequencing panel, 115 cancer-driving genes were analyzed in a cohort of 26 primary CRCs and 30 matching ovarian metastases (four with bilateral metastases). To obtain a complete overview of the mutational profile, low thresholds were used in bioinformatics analysis to prevent low frequency passenger mutations from being filtered out. A subset of var ...[more]

PMID: 27499925

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Project description:MotivationNext-generation sequencing technologies have accelerated the discovery of single nucleotide variants in the human genome, stimulating the development of predictors for classifying which of these variants are likely functional in disease, and which neutral. Recently, we proposed CScape, a method for discriminating between cancer driver mutations and presumed benign variants. For the neutral class, this method relied on benign germline variants found in the 1000 Genomes Project database. Discrimination could, therefore, be influenced by the distinction of germline versus somatic, rather than neutral versus disease driver. This motivates this article in which we consider predictive discrimination between recurrent and rare somatic single point mutations based solely on using cancer data, and the distinction between these two somatic classes and germline single point mutations.ResultsFor somatic point mutations in coding and non-coding regions of the genome, we propose CScape-somatic, an integrative classifier for predictively discriminating between recurrent and rare variants in the human cancer genome. In this study, we use purely cancer genome data and investigate the distinction between minimal occurrence and significantly recurrent somatic single point mutations in the human cancer genome. We show that this type of predictive distinction can give novel insight, and may deliver more meaningful prediction in both coding and non-coding regions of the cancer genome. Tested on somatic mutations, CScape-somatic outperforms alternative methods, reaching 74% balanced accuracy in coding regions and 69% in non-coding regions, whereas even higher accuracy may be achieved using thresholds to isolate high-confidence predictions.Availability and implementationPredictions and software are available at http://CScape-somatic.biocompute.org.uk/.Contactmark.f.rogers.phd@gmail.com or C.Campbell@bristol.ac.uk.Supplementary informationSupplementary data are available at Bioinformatics online.

Project description:IntroductionBesides genetic and epigenetic alterations that lead to carcinogenesis and development of colorectal cancer (CRC), intestinal microbiomes are recently recognized to play a critical role in CRC progression. The abundant species associated with human CRC have been proposed for their roles in promoting tumorigenesis. However, a recent "driver-passenger" model suggests that these CRC-associated species with high relative abundances may be passenger bacteria that take advantage of the tumor environment instead of initiating CRC, whereas the driver species that initiate CRC have been replaced by passenger bacteria due to the alteration of the intestinal niche.MethodsHere, to reveal potential driver and passenger bacteria during CRC progression, we compare the gut mucosal microbiomes of 75 triplet-paired CRC samples collected from on-tumor site, adjacent-tumor site, and off-tumor site, and 26 healthy controls.ResultsOur analyses revealed potential driver bacteria in four genera and two families, and potential passenger bacteria in 14 genera or families. Bacillus, Bradyrhizobium, Methylobacterium, Streptomyces, Intrasporangiaceae and Sinobacteraceae were predicted to be potential driver bacteria. Moreover, 14 potential passenger bacteria were identified and divided into five groups. Group I passenger bacteria contain Fusobacterium, Campylobacter, Streptococcus, Schwartzia, and Parvimonas. Group II passenger bacteria contain Dethiosulfatibacter, Selenomonas, Peptostreptococus, Leptotrichia. Group III passenger bacteria contain Granulicatella. Group IV passenger bacteria contain Shewanella, Mogibacterium, and Eikenella. Group V passenger bacteria contain Anaerococus. Co-occurrence network analysis reveals a low correlation relationship between driver and passenger bacteria in CRC patients compared with healthy controls.DiscussionThese driver and passenger species may serve as bio-marker species for screening cohorts with high risk to initiate CRC or patients with CRC, respectively. Further functional studies will help understand the roles of driver and passenger bacteria in CRC initiation and development.

Dataset Information

Somatic mutation profiles in primary colorectal cancers and matching ovarian metastases: Identification of driver and passenger mutations.

Publications

Somatic mutation profiles in primary colorectal cancers and matching ovarian metastases: Identification of driver and passenger mutations.

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