Screening disrupted molecular functions and pathways associated with clear cell renal cell carcinoma using Gibbs sampling. (October 2017)

• Record Type: Journal Article
• Authors: Nan, Ning; Chen, Qi; Wang, Yu; Zhai, Xu; Yang, Chuan-Ce; Cao, Bin; Chong, Tie
• Is Part Of: Computational biology and chemistry. Volume 70(2017)
• Page Start: 15
• Page End: 20
• Publication Date: 2017-10
• Subjects: Clear cell renal cell carcinoma -- Molecular functions -- Gibbs sampling -- Markov chain -- Oxidoreductase activity -- Oxidative phosphorylation; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2017.07.002
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Gibbs sampling was employed to identify disrupted molecular functions. We identified 13 differentially expressed molecular functions and 79 pivotal genes in ccRCC. Cases with alterations in pivotal genes showed poor prognosis. Oxidoreductase activity showed the highest posterior value. Oxidative phosphorylation was identified as pivotal pathway in ccRCC. Abstract: Objective: To explore the disturbed molecular functions and pathways in clear cell renal cell carcinoma (ccRCC) using Gibbs sampling. Methods: Gene expression data of ccRCC samples and adjacent non-tumor renal tissues were recruited from public available database. Then, molecular functions of expression changed genes in ccRCC were classed to Gene Ontology (GO) project, and these molecular functions were converted into Markov chains. Markov chain Monte Carlo (MCMC) algorithm was implemented to perform posterior inference and identify probability distributions of molecular functions in Gibbs sampling. Differentially expressed molecular functions were selected under posterior value more than 0.95, and genes with the appeared times in differentially expressed molecular functions ≥5 were defined as pivotal genes. Functional analysis was employed to explore the pathways of pivotal genes and their strongly co-regulated genes. Results: In this work, we obtained 396 molecular functions, and 13 of them were differentially expressed. Oxidoreductase activity showed the highest posterior value. Gene composition analysis identified 79 pivotal genes, and survival analysis indicated that these pivotal genes could be used as a strong independent predictor of poor prognosis in patients with ccRCC. Pathway analysis identified one pivotal pathway − oxidative phosphorylation. Conclusions: We identified the differentially expressed molecular functions and pivotal pathway in ccRCC using Gibbs sampling. The results could be considered as potential signatures for early detection and therapy of ccRCC.