Dataset Information

Landscape of transcriptome variations uncovering known and novel driver events in colorectal carcinoma.

ABSTRACT: We focused on an integrated view of genomic changes in Colorectal cancer (CRC) and distant normal colon tissue (NTC) to test the effectiveness of expression profiling on identification of molecular targets. We performed transcriptome on 16 primary coupled CRC and NTC tissues. We identified pathways and networks related to pathophysiology of CRC and selected potential therapeutic targets. CRC cells have multiple ways to reprogram its transcriptome: a functional enrichment analysis in 285 genes, 25% mutated, showed that they control the major cellular processes known to promote tumorigenesis. Among the genes showing alternative splicing, cell cycle related genes were upregulated (CCND1, CDC25B, MCM2, MCM3), while genes involved in fatty acid metabolism (ACAAA2, ACADS, ACAT1, ACOX, CPT1A, HMGCS2) were downregulated. Overall 148 genes showed differential splicing identifying 17 new isoforms. Most of them are involved in the pathogenesis of CRC, although the functions of these variants remain unknown. We identified 2 in-frame fusion events, KRT19-KRT18 and EEF1A1-HSP90AB1, encoding for chemical proteins in two CRC patients. We draw a functional interactome map involving integrated multiple genomic features in CRC. Finally, we underline that two functional cell programs are prevalently deregulated and absolutely crucial to determinate and sustain CRC phenotype.

SUBMITTER: Pira G

PROVIDER: S-EPMC6965099 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Landscape of transcriptome variations uncovering known and novel driver events in colorectal carcinoma.

Pira Giovanna G Uva Paolo P Scanu Antonio Mario AM Rocca Paolo Cossu PC Murgia Luciano L Uleri Elena E Piu Claudia C Porcu Alberto A Carru Ciriaco C Manca Alessandra A Persico Ivana I Muroni Maria Rosaria MR Sanges Francesca F Serra Caterina C Dolei Antonia A Angius Andrea A De Miglio Maria Rosaria MR

Scientific reports 20200116 1

We focused on an integrated view of genomic changes in Colorectal cancer (CRC) and distant normal colon tissue (NTC) to test the effectiveness of expression profiling on identification of molecular targets. We performed transcriptome on 16 primary coupled CRC and NTC tissues. We identified pathways and networks related to pathophysiology of CRC and selected potential therapeutic targets. CRC cells have multiple ways to reprogram its transcriptome: a functional enrichment analysis in 285 genes, 2 ...[more]

PMID: 31949199

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Project description:Bladder cancer (BC) is the ninth most common malignancy worldwide. Bladder urothelial carcinoma (BLCA) constitutes more than 90% of bladder cancer (BC). The five-year survival rate is 5-70%, and patients with BLCA have a poor clinical outcome. The identification of novel clinical molecular markers in BLCA is still urgent to allow for predicting clinical outcomes. This study aimed to identify a novel signature integrating the three-dimension transcriptome of protein coding genes, long non-coding RNAs, microRNAs that is related to the overall survival of patients with BLCA, contributing to earlier prediction and effective treatment selection, as well as to the verification of the established model in the subtypes identified. Gene expression profiling and the clinical information of 400 patients diagnosed with BLCA were retrieved from The Cancer Genome Atlas (TCGA) database. A univariate Cox regression analysis, robust likelihood-based survival modelling analysis and random forests for survival regression and classification algorithms were used to identify the critical biomarkers. A multivariate Cox regression analysis was utilized to construct a risk score formula with a maximum area under the curve (AUC = 0.7669 in the training set). The significant signature could classify patients into high-risk and low-risk groups with significant differences in overall survival time. Similar results were confirmed in the test set (AUC = 0.645) and in the entire set (AUC = 0.710). The multivariate Cox regression analysis indicated that the five-RNA signature was an independent predictive factor for patients with BLCA. Non-negative matrix factorization and a similarity network fusion algorithm were applied for identifying three molecular subtypes. The signature could separate patients in every subtype into high- and low- groups with a distinct difference. Gene set variation analysis of protein-coding genes associated with the five prognostic RNAs demonstrated that the co-expressed protein-coding genes were involved in the pathways and biological process of tumourigenesis. The five-RNA signature could serve as to some degree a reliable independent signature for predicting outcome in patients with BLCA.

Dataset Information

Landscape of transcriptome variations uncovering known and novel driver events in colorectal carcinoma.

Publications

Landscape of transcriptome variations uncovering known and novel driver events in colorectal carcinoma.

Similar Datasets

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