Network and Gene Set Enrichment Analysis of Adipokine Drivers of Prostate Cancer; Unravelling the Mechanistic Link Between Excess Adiposity and Prostate Cancer Risk.
[BACKGROUND] Adiposity-Based Chronic Disease (ABCD), a novel model housing obesity, insulin resistance, and adipokine-related inflammation, increases the risk of aggressive prostate cancer (PCa), post
APA
Dovey Z, Bort ET, Mechanick JI (2026). Network and Gene Set Enrichment Analysis of Adipokine Drivers of Prostate Cancer; Unravelling the Mechanistic Link Between Excess Adiposity and Prostate Cancer Risk.. Cancer medicine, 15(1), e71468. https://doi.org/10.1002/cam4.71468
MLA
Dovey Z, et al.. "Network and Gene Set Enrichment Analysis of Adipokine Drivers of Prostate Cancer; Unravelling the Mechanistic Link Between Excess Adiposity and Prostate Cancer Risk.." Cancer medicine, vol. 15, no. 1, 2026, pp. e71468.
PMID
41450167
Abstract
[BACKGROUND] Adiposity-Based Chronic Disease (ABCD), a novel model housing obesity, insulin resistance, and adipokine-related inflammation, increases the risk of aggressive prostate cancer (PCa), posttreatment PCa recurrence, and PCa mortality. This paper provides a new network analysis of relevant metabolic drivers to provide insight into the ABCD-PCa relationship.
[METHODS] A literature search was performed using the terms "prostate cancer" AND "obesity" AND "inflammation", with 629 references found, from which 17 reviews were chosen. Biomarkers identified from these reviews were characterized by cellular origin, signaling pathway, and oncogenic effect. The Webgestalt gene analysis toolkit was then used to generate modular-based network analyses and gene ontology (GO) categories of these biomarkers for interpretation.
[RESULTS] 14 prominent biomarkers were identified influencing PCa risk through cellular proliferation, resisting cell death, metabolic reprogramming, tumor-promoting inflammation, avoiding immune destruction, angiogenesis, and activating invasion. Network analyses of biomarker interactions highlighted prominent roles of monocyte chemoattractant protein-1, interleukin-1β, and C-X-C motif chemokine ligand 1. Top GO categories for the wider ABCD-PCa network found key roles of ABCD-gut microbiome dysbiosis and exposure of periprostatic white adipose tissue to the prostate microbiome (involving bacterial and lipopolysaccharide-induced inflammation).
[CONCLUSION] Top hypotheses to guide molecular targeted therapies and lifestyle biomarker panels for PCa in ABCD relate to MCP-1, IL-1β, and CXCL1 signaling, as well as gut microbiome dysbiosis and the exposure of the periprostatic adipose tissue to the prostate microbiome. Further research and possible clinical trials allowing histological examination of pre- and post-lifestyle intervention PCa tissue may provide further insights.
[METHODS] A literature search was performed using the terms "prostate cancer" AND "obesity" AND "inflammation", with 629 references found, from which 17 reviews were chosen. Biomarkers identified from these reviews were characterized by cellular origin, signaling pathway, and oncogenic effect. The Webgestalt gene analysis toolkit was then used to generate modular-based network analyses and gene ontology (GO) categories of these biomarkers for interpretation.
[RESULTS] 14 prominent biomarkers were identified influencing PCa risk through cellular proliferation, resisting cell death, metabolic reprogramming, tumor-promoting inflammation, avoiding immune destruction, angiogenesis, and activating invasion. Network analyses of biomarker interactions highlighted prominent roles of monocyte chemoattractant protein-1, interleukin-1β, and C-X-C motif chemokine ligand 1. Top GO categories for the wider ABCD-PCa network found key roles of ABCD-gut microbiome dysbiosis and exposure of periprostatic white adipose tissue to the prostate microbiome (involving bacterial and lipopolysaccharide-induced inflammation).
[CONCLUSION] Top hypotheses to guide molecular targeted therapies and lifestyle biomarker panels for PCa in ABCD relate to MCP-1, IL-1β, and CXCL1 signaling, as well as gut microbiome dysbiosis and the exposure of the periprostatic adipose tissue to the prostate microbiome. Further research and possible clinical trials allowing histological examination of pre- and post-lifestyle intervention PCa tissue may provide further insights.
MeSH Terms
Male; Humans; Prostatic Neoplasms; Adipokines; Adiposity; Obesity; Biomarkers, Tumor; Gene Regulatory Networks; Inflammation; Risk Factors