Baseline oral and gut microbiome profiles were associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer, and integrating microbiome and clinical features yielded an observed AUC of 0.917 in an internal test subset, though the model remains exploratory and requires validation in larger, independent cohorts.
Key Findings
Results
Response-associated differences were observed in bacterial and nonbacterial taxonomic profiles in both oral and gut microbiota of LARC patients before treatment.
Saliva and fecal samples were collected from patients with locally advanced rectal cancer (LARC) before neoadjuvant chemoradiotherapy (nCRT).
Shotgun metagenomic sequencing was used to profile bacterial, archaeal, eukaryotic, and viral taxonomic groups.
Differences were observed between responders and non-responders to nCRT across multiple microbial kingdoms, not just bacteria.
Both oral and gut microbial compartments showed response-associated taxonomic differences.
Results
Response-associated differences were also detected in oral and gut microbial functional profiles between nCRT responders and non-responders.
Shotgun metagenomic sequencing enabled examination of microbial functional profiles in addition to taxonomic composition.
Functional differences were identified in both the oral (saliva) and gut (fecal) microbiome compartments.
Statistical analyses compared diversity and response-associated microbial features between responders and non-responders.
The study extended beyond bacterial taxonomy to include archaeal, eukaryotic, and viral functional contributions.
Results
An artificial intelligence-based prediction model integrating oral and gut microbiome data with clinical information achieved an observed AUC of 0.917 in the internal test subset.
The model was developed by integrating oral and gut microbiome data with clinical information.
In the internal test subset, the integrated analysis yielded an observed AUC of 0.917.
The authors explicitly note that 'given the small cohort and the exploratory comparison of candidate classifiers, this estimate requires confirmation in larger, independent cohorts.'
The model is described as 'exploratory' and not yet suitable for clinical application without further validation.
Multiple classifier candidates were compared, which contributes to the need for external validation.
Results
Baseline oral and gut microbiome profiles were associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Samples were collected before treatment initiation, establishing baseline microbiome profiles as the exposure of interest.
Both saliva (oral) and fecal (gut) samples were analyzed, representing two distinct microbial compartments.
The study included patients with locally advanced rectal cancer (LARC) undergoing nCRT.
The study was retrospectively registered on 01/08/2026 under NCT07346729, indicating a relatively small and exploratory cohort design.
Background
Prior research on gut bacteria in colorectal cancer has insufficiently explored the influence of oral microbiota and nonbacterial gut microbiota (archaea, eukaryotes, viruses) on treatment efficacy.
The study was motivated by a gap in the literature regarding non-gut and non-bacterial microbiota in colorectal cancer treatment response.
The authors specifically aimed to investigate archaeal, eukaryotic, and viral taxonomic groups in addition to bacteria.
Shotgun metagenomic sequencing was chosen specifically to enable profiling of all these taxonomic groups simultaneously.
Both oral and nonbacterial microbiota were identified as understudied in the context of nCRT efficacy.
What This Means
This research suggests that the community of microorganisms living in the mouth and gut of rectal cancer patients — including not just bacteria but also archaea, fungi, and viruses — may be linked to how well patients respond to a standard pre-surgical treatment called neoadjuvant chemoradiotherapy (nCRT). The researchers collected saliva and stool samples from patients with locally advanced rectal cancer before they started treatment, then used advanced DNA sequencing to map all the microbial life present. They found meaningful differences in the types and functions of microorganisms between patients who responded well to treatment and those who did not.
Using these microbiome profiles combined with patients' clinical information, the researchers built an artificial intelligence model to try to predict treatment response before therapy begins. In their internal testing, the model performed well, with an AUC (a measure of predictive accuracy, where 1.0 is perfect) of 0.917. However, the study involved a small number of patients, and the authors themselves emphasize that this result is preliminary and exploratory — it needs to be confirmed in much larger, independent groups of patients before it could ever be used in a clinical setting.
This research matters because predicting which rectal cancer patients will respond to chemoradiotherapy before treatment starts could one day help doctors personalize treatment plans and avoid ineffective therapies. The finding that oral microbiota and non-bacterial microorganisms (not just gut bacteria) are also associated with treatment response opens up new directions for research. However, given the small cohort size and exploratory nature of the study, these findings should be viewed as hypothesis-generating rather than practice-changing.
Wen Y, Luo Z, Li Z, Li K, Li J, Yin S, et al.. (2026). Oral and gut microbiota profiles in patients with locally advanced rectal cancer with varying responses to neoadjuvant chemoradiotherapy.. Functional & integrative genomics. https://doi.org/10.1007/s10142-026-02025-5