Evidence mapPaperPMID 42190049Full record

ArticleThe Prostate2026

Microbial Differences in Prostate Lesions Between Black and White American Men.

Shiv Verma, Karishma Gupta, Xi Qiao, Daniel L Shen, Gregory T MacLennan, Mangesh Suryavanshi, Liangliang Zhang, Aaron W Miller, Sanjay Gupta

Abstract readComparative Study
In one paragraph

Article in The Prostate, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Shiv VermaDepartment of Urology, Case Western Reserve University, Cleveland, Ohio, USA.
Karishma GuptaDepartment of Urology, Case Western Reserve University, Cleveland, Ohio, USA.
Xi QiaoDepartment of Population and Quantitative Health Sciences, Cleveland, Ohio, USA.
Daniel L ShenDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio, USA.
Gregory T MacLennanDepartment of Pathology, Case Western Reserve University, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0001-6171-2042
Mangesh SuryavanshiGlickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Liangliang ZhangDepartment of Population and Quantitative Health Sciences, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0001-5986-2260
Aaron W MillerGlickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Sanjay GuptaDepartment of Urology, Case Western Reserve University, Cleveland, Ohio, USA.ORCID https://orcid.org/0000-0002-9492-3249

Funding

U.S. Department of Defense W81XWH-18-1-0618U.S. Department of Defense W81XWH-19-1-0720
6 · The paper itself

Abstract

backgroundEthnicity and pathological factors contribute to differences in prostate neoplasm, and this landscape could be influenced by the local microbiome.

methodsTo investigate whether prostate tissue harbors race-specific microbiota, we performed 16S rRNA gene sequencing of various hypervariable regions of cancer, inflammation, and non-cancer (benign) tissue from Black and White American men with prostate cancer followed by qRT-PCR for validation. All reported p-values were adjusted for false discovery rate to account for multiple comparisons.

resultsComparative analysis revealed marked differences in microbial composition between the two groups. Several species showed significant differential abundance, including Alphaproteobacteria (p < 0.001), Bacteroides fragilis (p < 0.001), Candidatus Kerfeldbacteria (p < 0.001), Flavobacterium frigoris (p < 0.0001), Fusobacterium nucleatum (p < 0.003), Rhizobiales bacterium (p < 0.0001), Sphingomonas glacialis (p < 0.0001), and Staphylococcus epidermidis (p < 0.05). Lesion-specific analysis further identified Pseudomonadota, Actinomycetota, and Bacilliota as the most abundant phyla in inflammatory lesions of both racial groups. However, Tenericutes were uniquely present in Black American samples, whereas Bacteroidota and Deinococcota were more abundant in the inflammatory lesions of White American men. At the genus level, analysis identified several key bacterial taxa associated with prostate cancer. Streptococcus, Abiotrophia, and Acinetobacter were significantly enriched in the Black American prostate tissues, while Staphylococcus and Corynebacterium were more abundant in tissue from White American men.

conclusionsThis is the first study to demonstrate significant microbial diversity and distinct microbial signatures in Black and White American men, suggesting that intra-prostatic bacteria may play a role in disease disparities and pathogenesis.

Indexed as

Black or African AmericanMicrobiotaProstateProstatic NeoplasmsWhiteAgedHumansMaleMiddle AgedRNA, Ribosomal, 16SRNA, Ribosomal, 16Sdisparitydysbiosisinflammationmicrobiomeprostate lesions

Identifiers

PMID42190049
PMCPMC13327710

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.