Bacterial extracellular vesicles and microbial-derived small RNAs as circulating cancer biomarkers

Abstract

Emerging evidence suggests that bacterial extracellular vesicles (BEVs) and microbial-derived small RNAs (msRNAs) in human plasma represent a new class of circulating cancer biomarkers. Multi-cohort analyses of more than 1100 patients revealed 2.8- to 3.5-fold higher BEV levels in cancer cases versus controls, with microbial RNA cargo comprising up to 1.6% of total plasma RNA. Specific BEV-msRNA panels achieved area under the curve values of 0.87–0.94 for early-stage cancer detection, outperforming conventional CEA and CA19-9 markers. Functionally, BEV-associated msRNAs modulate tumor-related signaling by activating NF-κB and STAT3 pathways and suppressing TP53/PTEN expression, promoting cytokine release and oncogenic inflammation. BEVs also exhibit superior stability remaining detectable for more than 72 hours in circulation supporting their feasibility for clinical liquid biopsy. Collectively, circulating BEVs and msRNAs offer promising, mechanism-linked biomarkers for non-invasive cancer detection and precision monitoring.

Dear Editor,

The development of noninvasive and reliable biomarkers remains one of the central challenges in cancer diagnostics. Growing evidence highlights bacterial extracellular vesicles (BEVs) and microbial-derived small RNAs (msRNAs) as novel circulating indicators that mirror tumor-associated microbial dysbiosis and oncogenic signaling.

BEVs, membrane-bound vesicles ranging 30–250 nm in diameter, are shed by commensal and pathogenic bacteria into circulation, carrying microbial DNA, RNA, proteins, and lipids. Recent multi-cohort analyses encompassing over 1100 patients reported that circulating BEV levels were 2.8- to 3.5-fold higher in cancer patients compared with healthy controls, with unique RNA cargo patterns reflecting cancer type and stage^[1]. Quantitative RNA sequencing demonstrated that BEV-associated microbial transcripts comprised up to 1.6% of total plasma RNA reads in cancer, versus <0.3% in controls, underscoring their stability and abundance^[2].

The msRNAs, including bacterial tRNA fragments and rRNA-derived small RNAs, mediate cross-kingdom gene regulation. In gastric and colorectal cancers, specific BEV-msRNA panels achieved area under the curve (AUC) values between 0.87 and 0.94 for distinguishing early-stage disease from controls, surpassing traditional markers such as CEA (AUC: 0.71) and CA19-9 (AUC: 0.68)^[3]. In a 2025 multicenter study of 468 patients, elevated BEV-msRNAs such as tsRNA-23U-Ala and tsRNA-19G-Glu were associated with a 3.9-fold increased metastasis risk and a twofold shorter disease-free survival (P < 0.01)^[4].

Bacterial vesicles and their RNA cargo influence tumor progression by altering host immunity and transcriptional control. BEV-derived msRNAs can downregulate tumor suppressor genes (TP53, PTEN) and activate NF-κB and STAT3, fostering cytokine release, angiogenesis, and immune evasion^[5]. BEVs isolated from colorectal cancer plasma increased IL-6 and TNF-α secretion by 2.7-fold in cultured epithelial cells, demonstrating their proinflammatory potential^[6].

Clinically, circulating BEVs exhibit superior stability compared to tumor exosomes, remaining detectable for >72 hours at room temperature and showing reproducible RNA profiles across repeated sampling. This supports their feasibility as liquid biopsy biomarkers for early detection, disease monitoring, and therapy response evaluation.

In summary, accumulating quantitative evidence establishes bacterial extracellular vesicles and microbial small RNAs as promising, mechanistically linked biomarkers in oncology. Their diagnostic accuracy, molecular stability, and ability to reflect tumor microbe interaction make them strong candidates for inclusion in next-generation precision screening platforms. This study followed the transparency in the reporting of artificial intelligence (TITAN) guidelines 2025^[7].

Ethical approval

Not applicable.

Consent

Consent for publication is not applicable as this study involves publicly available data.

Sources of funding

The authors received no funding.

Author contributions

M.S.M.: conceptualization, methodology, software, data curation, writing original draft preparation, reviewing and editing; N.D.: writing – original draft preparation, reviewing and editing.

Conflicts of interest disclosure

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Research registration unique identifying number (UIN)

Not applicable.

Provenance and peer review

Not commissioned, externally peer-reviewed.

Use of generative AI and AI-assisted technologies

No AI or AI-assisted technologies were used in the preparation of this manuscript.