Dataset Information

Cancer driver-passenger distinction via sporadic human and dog cancer comparison: a proof-of-principle study with colorectal cancer.

ABSTRACT: Herein we report a proof-of-principle study illustrating a novel dog-human comparison strategy that addresses a central aim of cancer research, namely cancer driver-passenger distinction. We previously demonstrated that sporadic canine colorectal cancers (CRCs) share similar molecular pathogenesis mechanisms as their human counterparts. In this study, we compared the genome-wide copy number abnormalities between 29 human and 10 canine sporadic CRCs. This led to the identification of 73 driver candidate genes (DCGs), altered in both species, and with 27 from the whole genome and 46 from dog-human genomic rearrangement breakpoint (GRB) regions, as well as 38 passenger candidate genes (PCGs), altered in humans only and located in GRB regions. We noted that DCGs significantly differ from PCGs in every analysis conducted to assess their cancer relevance and biological functions. Importantly, although PCGs are not enriched in any specific functions, DCGs possess significantly enhanced functionality closely associated with cell proliferation and death regulation, as well as with epithelial cell apicobasal polarity establishment/maintenance. These observations support the notion that, in sporadic CRCs of both species, cell polarity genes not only contribute in preventing cancer cell invasion and spreading, but also likely serve as tumor suppressors by modulating cell growth. This pilot study validates our novel strategy and has uncovered four new potential cell polarity and colorectal tumor suppressor genes (RASA3, NUPL1, DENND5A and AVL9). Expansion of this study would make more driver-passenger distinctions for cancers with large genomic amplifications or deletions, and address key questions regarding the relationship between cancer pathogenesis and epithelial cell polarity control in mammals.

SUBMITTER: Tang J

PROVIDER: S-EPMC3932186 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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Cancer driver-passenger distinction via sporadic human and dog cancer comparison: a proof-of-principle study with colorectal cancer.

Tang J J Li Y Y Lyon K K Camps J J Dalton S S Ried T T Zhao S S

Oncogene 20130218 7

Herein we report a proof-of-principle study illustrating a novel dog-human comparison strategy that addresses a central aim of cancer research, namely cancer driver-passenger distinction. We previously demonstrated that sporadic canine colorectal cancers (CRCs) share similar molecular pathogenesis mechanisms as their human counterparts. In this study, we compared the genome-wide copy number abnormalities between 29 human and 10 canine sporadic CRCs. This led to the identification of 73 driver ca ...[more]

PMID: 23416983

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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.

Project description:BACKGROUND: We are developing a cross-species comparison strategy to distinguish between cancer driver- and passenger gene alteration candidates, by utilizing the difference in genomic location of orthologous genes between the human and other mammals. As an initial test of this strategy, we conducted a pilot study with human colorectal cancer (CRC) and its mouse model C57BL/6J ApcMin/+, focusing on human 5q22.2 and 18q21.1-q21.2. METHODS: We first performed bioinformatics analysis on the evolution of 5q22.2 and 18q21.1-q21.2 regions. Then, we performed exon-targeted sequencing, real time quantitative polymerase chain reaction (qPCR), and real time quantitative reverse transcriptase PCR (qRT-PCR) analyses on a number of genes of both regions with both human and mouse colon tumors. RESULTS: These two regions (5q22.2 and 18q21.1-q21.2) are frequently deleted in human CRCs and encode genuine colorectal tumor suppressors APC and SMAD4. They also encode genes such as MCC (mutated in colorectal cancer) with their role in CRC etiology unknown. We have discovered that both regions are evolutionarily unstable, resulting in genes that are clustered in each human region being found scattered at several distinct loci in the genome of many other species. For instance, APC and MCC are within 200 kb apart in human 5q22.2 but are 10 Mb apart in the mouse genome. Importantly, our analyses revealed that, while known CRC driver genes APC and SMAD4 were disrupted in both human colorectal tumors and tumors from ApcMin/+ mice, the questionable MCC gene was disrupted in human tumors but appeared to be intact in mouse tumors. CONCLUSIONS: These results indicate that MCC may not actually play any causative role in early colorectal tumorigenesis. We also hypothesize that its disruption in human CRCs is likely a mere result of its close proximity to APC in the human genome. Expanding this pilot study to the entire genome may identify more questionable genes like MCC, facilitating the discovery of new CRC driver gene candidates.

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.

Dataset Information

Cancer driver-passenger distinction via sporadic human and dog cancer comparison: a proof-of-principle study with colorectal cancer.

Publications

Cancer driver-passenger distinction via sporadic human and dog cancer comparison: a proof-of-principle study with colorectal cancer.

Similar Datasets

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