Intratumoral Microbiota in Cancer: Spatial Evidence, Biological Mechanisms, and Translational Prospects.

Authors

Vatsal Bhargava, Sonal Gupta, Chanchal Yadav, Ishika Panchal, Nyonika Mathur, Roshan Kumar, Cherita Devi Khangembam, Pushp Lata

Published in

Progress in biophysics and molecular biology. Aug 01, 2026. Epub Aug 01, 2026.

Abstract

Finding microbial matter in tumors is one thing and deciding whether it matters is another. We frame the problem through biophysical niche constraints, evidence-tier grading, and the translational distance between biological plausibility and clinical readiness. The bar for moving from detection to biological claim varies by cancer type. In oral, colorectal, and pancreatic cancers, selected spatial and functional studies have moved beyond taxonomic cataloguing toward spatially localized host-microbe evidence within the tumor microenvironment, although the depth of validation varies substantially across studies and tumor types (Galeano Niño et al., 2022; Aykut et al., 2019; Nejman et al., 2020). For many other tumor types, low-biomass sequencing continues to outpace direct validation, and the signal-to-noise problem remains a central interpretive challenge (Dohlman et al., 2026; Vella and Rescigno, 2025). DNA damage, host signaling, immune remodeling, and metabolite exchange serve as the strongest mechanistic links involved, with the most developed examples concentrated in gastrointestinal and mucosa-adjacent tumors. Yet translational claims frequently treat sequencing-based observations as carrying comparable weight to localized intratumoral proof, conflating evidentiary categories that require different standards of support. Throughout this review, we evaluate spatial localization, contamination risk, and the distance between biological plausibility and clinical readiness as central interpretive criteria, and we argue that well-supported ecological signals presently inform more reliably than long catalogs assembled from uneven evidentiary classes.

PMID:
42542213
Bibliographic data and abstract were imported from PubMed on 02 Aug 2026.

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