Network and Gene Set Enrichment Analysis of Adipokine Drivers of Prostate Cancer; Unravelling the Mechanistic Link Between Excess Adiposity and Prostate Cancer Risk

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

• Level A · Stronger Clinical Evidence
• Level B · Emerging clinical evidence with positive signals
• Level C · Early human research exploring benefits
• Level D · Scientific groundwork from lab and animal studies
• Emerging · Emerging topic under active research

Abstract (original English)

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

Evidence level

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

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