CRIS, a superior predictive and prognostic classification system of colorectal cancer based on high-resolution analysis of cancer cell-autonomous traits II
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE76402 | GEO | 2017/06/19
SECONDARY ACCESSION(S): PRJNA307186
REPOSITORIES: GEO
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Project description:Sadanandam et al. (2013) recently published a study based on the use of microarray data to classify colorectal cancer (CRC) samples. The classification claimed to have strong clinical implications, as reflected in the paper title: “A colorectal cancer classification system that associates cellular phenotype and responses to therapy”. They defined five subtypes: (i) inflammatory; (ii) goblet-like; (iii) enterocyte; (iv) transit-amplifying; and (v) stem-like. Based on drug sensitivity data from 21 patients, they also reported that the so-called stem-like subtype show differential sensitivity to FOLFIRI. This is the key result in their publication, since it implies a direct relation between the subtype and the choice of CRC therapy (i.e. FOLFIRI response). However, our analyses using the same drug sensitivity data and results from additional patients showed that the CRC classification reported by Sadanandam et al. is not predictive of FOLFIRI response. We used the classification algorithm to obtain CRC subtypes from our samples. Then we tested the subtype-drug response association performing a retrospective study.
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Project description:High-throughput genomic studies have identified thousands of genetic alterations in colorectal cancer (CRC). Distinguishing driver from passenger mutations is critical for developing rational therapeutic strategies. Because only a few transcriptional subtypes exist in previously studied tumor types, we hypothesize that highly heterogeneous genomic alterations may converge to a limited number of distinct mechanisms that drive unique gene expression patterns in different transcriptional subtypes. In this study, we defined transcriptional subtypes for CRC and identified driver networks/pathways for each subtype, respectively. Applying consensus clustering to a patient cohort with 1173 samples identified three transcriptional subtypes, which were validated in an independent cohort with 485 samples. The three subtypes were characterized by different transcriptional programs related to normal adult colon, early colon embryonic development, and epithelial mesenchymal transition, respectively. They also showed statistically different clinical outcomes. For each subtype, we mapped somatic mutation and copy number variation data onto an integrated signaling network and identified subtype-specific driver networks using a random walk-based strategy. We found that genomic alterations in the Wnt signaling pathway were common among all three subtypes; however, unique combinations of pathway alterations including Wnt, VEGF, Notch and TGF-beta drove distinct molecular and clinical phenotypes in different CRC subtypes. Our results provide a coherent and integrated picture of human CRC that links genomic alterations to molecular and clinical consequences, and which provides insights for the development of personalized therapeutic strategies for different CRC subtypes.
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Project description:Background: Multi-omics analyses are profitable for discovering novel biomarkers and drug targets, but such integrated examinations on mitochondria of colorectal cancer (CRC) patients are lacking. Methods: We investigated global structural variants, DNA methylation, chromatin accessibility, proteome, and phosphoproteome on human CRC (n = 6-8). The alterations of mitochondria on these levels and potential upstream regulatory genes were described. Furthermore, combining with the mRNA datasets of 538 CRC and 91 colitis patients from the public databases, we identified independent prognostic factors (IPFs). Findings: Revealed by the proteogenomic analyses in our study, mitochondria altered the most among all organelles in CRC, which were also associated with patient prognosis the most. We found that the mRNA of one nuclear-coding mitochondrial gene (NCMG), HIGD1A, decreased in colitis, two subtypes of adenoma, and six subtypes of CRC, subsequently was identified as a favorable IPF for CRC. Besides, the comprehensive analyses of mitochondria by multi-omics uncovered unique proteogenomic alterations on six survival-related NCMGs. Key transcriptional factors potentially regulating the mitochondria were also unveiled, such as GLIS1, JUN, CREB1, and YAP1. Finally, p38 was highlighted as one possible central kinase involving in the modulation of mitochondrial activity in CRC patients. Interpretation: Our study presents a multilayer and molecular picture of mitochondria of CRC patients, recognizes HIGD1A as a potential prognostic biomarker, and provides new candidate genes as therapeutic targets.
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