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CRIS, a superior predictive and prognostic classification system of colorectal cancer based on high-resolution analysis of cancer cell-autonomous traits

ABSTRACT: Recent work built on published transcriptional subtypes of colorectal cancer (CRC) has shown that tumor stromal content impacts CRC classification, with both clinical and biological implications. To Tackle the issue of intrinsic epithelial gene profiles, we assembled a dataset of matched liver metastatic colorectal cancer and Patients Derived Xenografts. in which the stroma of the original tumor is substituted by murine tissue, we deployed a molecularly annotated collection of 515 PDXs from 244 patients as a resource for species (human)-specific assessment of cancer-cell intrinsic transcriptional features. We identified five ColoRectal cancer Intrinsic Subtypes (CRIS) endowed with functional and phenotypic characteristics related to specific genetic traits, most of which were not evidenced in the transcriptional subgroups reported in previous studies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE73255 | GEO | 2017/06/19

SECONDARY ACCESSION(S): PRJNA296465

REPOSITORIES: GEO

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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. To characterize the embryonic development of colon, we conducted a time course microarray study using the inbred C57BL/6 (Jackson Laboratories, Bar Harbor, ME) mice. Seven samples corresponding to the mouse colonic development from E13.5 to E18.5 and adult (eight week post-natal) were collected. RNA samples were submitted to the Vanderbilt Functional Genomics Shared Resource (FSGR, http://array.mc.vanderbilt.edu), where RNA was hybridized to the Affymetrix Mouse Genome 430 2.0 GeneChip Expression Arrays (Santa Clara, CA) according to manufacturer’s instructions. The RMA algorithm was used for data normalization. Mouse gene symbols were mapped to human gene symbols by the Human and Mouse Orthology list available from the Mouse Genome Informatics (http://www.informatics.jax.org/).

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CRIS, a superior predictive and prognostic classification system of colorectal cancer based on high-resolution analysis of cancer cell-autonomous traits

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