ArticleCancer medicine2026
Network and Gene Set Enrichment Analysis of Adipokine Drivers of Prostate Cancer; Unravelling the Mechanistic Link Between Excess Adiposity and Prostate Cancer Risk.
Article in Cancer medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdiposity-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.
methodsA 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.
results14 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).
conclusionTop 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.
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