Publication details

ColPortal, an integrative multiomic platform for analysing epigenetic interactions in colorectal cancer

Authors

ESTEBAN-GIL Angel PEREZ-SANZ Fernando GARCIA-SOLANO Jose ALBURQUERQUE-GONZALEZ Begona PARRENO-GONZALEZ Maria LEGAZ-GARCIA Maria del Carmen FERNANDEZ-BREIS Jesualdo Tomas RODRIGUEZ-BRAUN Edith PIMENTEL Paola TUOMISTO Anne MAKINEN Markus SLABÝ Ondřej CONESA-ZAMORA Pablo

Year of publication 2019
Type Article in Periodical
Magazine / Source SCIENTIFIC DATA
MU Faculty or unit

Central European Institute of Technology

Citation
Web https://www.nature.com/articles/s41597-019-0198-z.pdf
Doi http://dx.doi.org/10.1038/s41597-019-0198-z
Keywords MICROSATELLITE INSTABILITY; PROMOTER HYPERMETHYLATION; SERRATED POLYPS; COLON-CANCER; PHENOTYPE; CARCINOGENESIS; ADENOCARCINOMA; BIOMARKERS; PATHWAYS; GENES
Description Colorectal cancer (CRC) is the third leading cause of cancer mortality worldwide. Different pathological pathways and molecular drivers have been described and some of the associated markers are used to select effective anti-neoplastic therapy. More recent evidence points to a causal role of microbiota and altered microRNA expression in CRC carcinogenesis, but their relationship with pathological drivers or molecular phenotypes is not clearly established. Joint analysis of clinical and omics data can help clarify such relations. We present ColPortal, a platform that integrates transcriptomic, microtranscriptomic, methylomic and microbiota data of patients with colorectal cancer. ColPortal also includes detailed information of histological features and digital histological slides from the study cases, since histology is a morphological manifestation of a complex molecular change. The current cohort consists of Caucasian patients from Europe. For each patient, demographic information, location, histology, tumor staging, tissue prognostic factors, molecular biomarker status and clinical outcomes are integrated with omics data. ColPortal allows one to perform multiomics analyses for groups of patients selected by their clinical data.

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