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Gene Expression Studies to Identify Significant Genes in AR, MTOR, MAPK Pathways and their Overlapping Regulatory Role in Prostate Cancer

Authors: Asati Nimisha; Mishra Abhinav; Shukla Ankita; Singh Tiratha Raj;

Gene Expression Studies to Identify Significant Genes in AR, MTOR, MAPK Pathways and their Overlapping Regulatory Role in Prostate Cancer

Abstract

Abstract Gene expression studies revealed a large degree of variability in gene expression patterns particularly in tissues even in genetically identical individuals. It helps to reveal the components majorly fluctuating during the disease condition. With the advent of gene expression studies many microarray studies have been conducted in prostate cancer, but the results have varied across different studies. To better understand the genetic and biological regulatory mechanisms of prostate cancer, we conducted a meta-analysis of three major pathways i.e. androgen receptor (AR), mechanistic target of rapamycin (mTOR) and Mitogen-Activated Protein Kinase (MAPK) on prostate cancer. Meta-analysis has been performed for the gene expression data for the human species that are exposed to prostate cancer. Twelve datasets comprising AR, mTOR, and MAPK pathways were taken for analysis, out of which thirteen potential biomarkers were identified through meta-analysis. These findings were compiled based upon the quantitative data analysis by using different tools. Also, various interconnections were found amongst the pathways in study. Our study suggests that the microarray analysis of the gene expression data and their pathway level connections allows detection of the potential predictors that can prove to be putative therapeutic targets with biological and functional significance in progression of prostate cancer.

Keywords

Male, MAP Kinase Signaling System, TOR Serine-Threonine Kinases, pathways, Prostatic Neoplasms, prostate cancer, Neoplasm Proteins, meta-analysis, Gene Expression Regulation, Neoplastic, Receptors, Androgen, mtor, Humans, Databases, Nucleic Acid, microarray, mapk, TP248.13-248.65, Research Articles, ar, Biotechnology

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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