Complex-based analysis of dysregulated cellular processes in cancer
Sriganesh Srihari, Piyush B. Madhamshettiwar, Sarah Song, Chao Liu,, Peter T. Simpson, Kum Kum Khanna, Mark A. Ragan

TL;DR
This paper presents a systematic analysis of protein complexes and their transcriptional regulation in cancer, revealing key complexes and TFs involved in tumor mechanisms through integrated data analysis and a novel log-linear model.
Contribution
It introduces a new integrative approach combining PPI and gene expression data with a log-linear model to identify cancer-related complexes and their regulation by TFs.
Findings
Complexes involved in genome stability and cell proliferation show significant expression changes.
Tumors exhibit both decreases and increases in complex expression, indicating compensatory mechanisms.
TFs regulate these complexes cooperatively and counteractively, influencing cancer progression.
Abstract
Background: Differential expression analysis of (individual) genes is often used to study their roles in diseases. However, diseases such as cancer are a result of the combined effect of multiple genes. Gene products such as proteins seldom act in isolation, but instead constitute stable multi-protein complexes performing dedicated functions. Therefore, complexes aggregate the effect of individual genes (proteins) and can be used to gain a better understanding of cancer mechanisms. Here, we observe that complexes show considerable changes in their expression, in turn directed by the concerted action of transcription factors (TFs), across cancer conditions. We seek to gain novel insights into cancer mechanisms through a systematic analysis of complexes and their transcriptional regulation. Results: We integrated large-scale protein-interaction (PPI) and gene-expression datasets to…
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Taxonomy
TopicsBioinformatics and Genomic Networks · Gene expression and cancer classification · Genomics and Chromatin Dynamics
