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Colon cancer subtypes: concordance, effect on survival and selection of the most representative preclinical models.

ABSTRACT: Multiple gene-expression-based subtypes have been proposed for the molecular subdivision of colon cancer in the last decade. We aimed to cross-validate these classifiers to explore their concordance and their power to predict survival. A gene-chip-based database comprising 2,166 samples from 12 independent datasets was set up. A total of 22 different molecular subtypes were re-trained including the CCHS, CIN25, CMS, ColoGuideEx, ColoGuidePro, CRCassigner, MDA114, Meta163, ODXcolon, Oncodefender, TCA19, and V7RHS classifiers as well as subtypes established by Budinska, Chang, DeSousa, Marisa, Merlos, Popovici, Schetter, Yuen, and Watanabe (first authors). Correlation with survival was assessed by Cox proportional hazards regression for each classifier using relapse-free survival data. The highest efficacy at predicting survival in stage 2-3 patients was achieved by Yuen (p?=?3.9e-05, HR?=?2.9), Marisa (p?=?2.6e-05, HR?=?2.6) and Chang (p?=?9e-09, HR?=?2.35). Finally, 61 colon cancer cell lines from four independent studies were assigned to the closest molecular subtype.

SUBMITTER: Sztupinszki Z

PROVIDER: S-EPMC5111107 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Colon cancer subtypes: concordance, effect on survival and selection of the most representative preclinical models.

Sztupinszki Zsófia Z Győrffy Balázs B

Scientific reports 20161116

Multiple gene-expression-based subtypes have been proposed for the molecular subdivision of colon cancer in the last decade. We aimed to cross-validate these classifiers to explore their concordance and their power to predict survival. A gene-chip-based database comprising 2,166 samples from 12 independent datasets was set up. A total of 22 different molecular subtypes were re-trained including the CCHS, CIN25, CMS, ColoGuideEx, ColoGuidePro, CRCassigner, MDA114, Meta163, ODXcolon, Oncodefender, ...[more]

PMID: 27849044

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Project description:Human colorectal cancer (CRC) cell lines are a used widely-used to model system for investigation investigate of tumour biology, experimental therapytherapeutic and biomarkers discovery. However, to what extent these established CRC cell lines represent and maintain the genetic diversity of primary cancers is uncertain. In this study, we analyzed 70 CRC cell lines were analysed for mutations using whole exome sequencing and DNA copy-number using by whole-exome sequencing and SNP microarray profilings, respectively. Presence of gGene expression was defined using RNA-Seq. Data from cellCell line datas were was compared to those that published from for primary CRCs published by in The the Cancer Genome Atlas Network. Notably, we found that The spectrum of exome mutations and DNA copy-number aberrations spectra in 70 CRC cell lines closely resembled those seen inat of primary colorectal tumours. Similarities included the presence of at least two hypermutation phenotypes, as defined by signatures of for defective DNA mismatch repair and DNA polymerase ? (POLE) proof-reading deficiency, and along with concordant mutation profiles in the broadly altered WNT, MAPK, PI3K, TGF? and p53 pathways. In additionFurther, we documented mutations were enriched in genes involved in chromatin remodelling (ARID1A, CHD6, SRCAP) and histone methylation or acetylation (ASH1L, EP300, EP400, MLL2, MLL3, PRDM2, TRRAP). Chromosomal instability was prevalent in non-hypermutated cases, with similar patterns of whole, partial and focal chromosomal aberrations and overlapping significant minimal regions ofchromosomal gains and losses. While paired cell lines derived from the same tumour were found to exhibited considerable mutation and DNA copy-number differences, in silico simulations suggest that these differenceslargely mainly reflected a pre-existing heterogeneity in the tumour cells heterogeneity. In conclusion, our results establish that human CRC lines are representative of the main subtypes of primary tumours at the genomic level, further validating underscoring their utility as tools for to investigating investigate CRC biology and drug responses. 69 colorectal cancer cell lines were analysed for DNA copy number profiles.

Project description:Human colorectal cancer (CRC) cell lines are a used widely-used to model system for investigation investigate of tumour biology, experimental therapytherapeutic and biomarkers discovery. However, to what extent these established CRC cell lines represent and maintain the genetic diversity of primary cancers is uncertain. In this study, we analyzed 70 CRC cell lines were analysed for mutations using whole exome sequencing and DNA copy-number using by whole-exome sequencing and SNP microarray profilings, respectively. Presence of gGene expression was defined using RNA-Seq. Data from cellCell line datas were was compared to those that published from for primary CRCs published by in The the Cancer Genome Atlas Network. Notably, we found that The spectrum of exome mutations and DNA copy-number aberrations spectra in 70 CRC cell lines closely resembled those seen inat of primary colorectal tumours. Similarities included the presence of at least two hypermutation phenotypes, as defined by signatures of for defective DNA mismatch repair and DNA polymerase ε (POLE) proof-reading deficiency, and along with concordant mutation profiles in the broadly altered WNT, MAPK, PI3K, TGFβ and p53 pathways. In additionFurther, we documented mutations were enriched in genes involved in chromatin remodelling (ARID1A, CHD6, SRCAP) and histone methylation or acetylation (ASH1L, EP300, EP400, MLL2, MLL3, PRDM2, TRRAP). Chromosomal instability was prevalent in non-hypermutated cases, with similar patterns of whole, partial and focal chromosomal aberrations and overlapping significant minimal regions ofchromosomal gains and losses. While paired cell lines derived from the same tumour were found to exhibited considerable mutation and DNA copy-number differences, in silico simulations suggest that these differenceslargely mainly reflected a pre-existing heterogeneity in the tumour cells heterogeneity. In conclusion, our results establish that human CRC lines are representative of the main subtypes of primary tumours at the genomic level, further validating underscoring their utility as tools for to investigating investigate CRC biology and drug responses.

Project description:BackgroundTranscriptome analysis of breast cancer discovered distinct disease subtypes of clinical significance. However, it remains a challenge to define disease biology solely based on gene expression because tumor biology is often the result of protein function. Here, we measured global proteome and transcriptome expression in human breast tumors and adjacent non-cancerous tissue and performed an integrated proteotranscriptomic analysis.MethodsWe applied a quantitative liquid chromatography/mass spectrometry-based proteome analysis using an untargeted approach and analyzed protein extracts from 65 breast tumors and 53 adjacent non-cancerous tissues. Additional gene expression data from Affymetrix Gene Chip Human Gene ST Arrays were available for 59 tumors and 38 non-cancerous tissues in our study. We then applied an integrated analysis of the proteomic and transcriptomic data to examine relationships between them, disease characteristics, and patient survival. Findings were validated in a second dataset using proteome and transcriptome data from "The Cancer Genome Atlas" and the Clinical Proteomic Tumor Analysis Consortium.ResultsWe found that the proteome describes differences between cancerous and non-cancerous tissues that are not revealed by the transcriptome. The proteome, but not the transcriptome, revealed an activation of infection-related signal pathways in basal-like and triple-negative tumors. We also observed that proteins rather than mRNAs are increased in tumors and show that this observation could be related to shortening of the 3' untranslated region of mRNAs in tumors. The integrated analysis of the two technologies further revealed a global increase in protein-mRNA concordance in tumors. Highly correlated protein-gene pairs were enriched in protein processing and disease metabolic pathways. The increased concordance between transcript and protein levels was additionally associated with aggressive disease, including basal-like/triple-negative tumors, and decreased patient survival. We also uncovered a strong positive association between protein-mRNA concordance and proliferation of tumors. Finally, we observed that protein expression profiles co-segregate with a Myc activation signature and separate breast tumors into two subgroups with different survival outcomes.ConclusionsOur study provides new insights into the relationship between protein and mRNA expression in breast cancer and shows that an integrated analysis of the proteome and transcriptome has the potential of uncovering novel disease characteristics.

Dataset Information

Colon cancer subtypes: concordance, effect on survival and selection of the most representative preclinical models.

Publications

Colon cancer subtypes: concordance, effect on survival and selection of the most representative preclinical models.

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