Microbial Diversity and Composition Is Associated with Patient-Reported Toxicity during Chemoradiation Therapy for Cervical Cancer.

PURPOSE

Patients receiving pelvic radiation for cervical cancer experience high rates of acute gastrointestinal (GI) toxicity. The association of changes in the gut microbiome with bowel toxicity from radiation is not well characterized.

METHODS AND MATERIALS

Thirty-five patients undergoing definitive chemoradiation therapy (CRT) underwent longitudinal sampling (baseline and weeks 1, 3, and 5) of the gut microbiome and prospective assessment of patient-reported GI toxicity. DNA was isolated from stool obtained at rectal examination and analyzed with 16S rRNA sequencing. GI toxicity was assessed with the Expanded Prostate Cancer Index Composite instrument to evaluate frequency, urgency, and discomfort associated with bowel function. Shannon diversity index was used to characterize alpha (within sample) diversity. Weighted UniFrac principle coordinates analysis was used to compare beta (between sample) diversity between samples using permutational multivariate analysis of variance. Linear discriminant analysis effect size highlighted microbial features that best distinguish categorized patient samples.

RESULTS

Gut microbiome diversity continuously decreased over the course of CRT, with the largest decrease at week 5. Expanded Prostate Cancer Index Composite bowel function scores also declined over the course of treatment, reflecting increased symptom burden. At all individual time points, higher diversity of the gut microbiome was linearly correlated with better patient-reported GI function, but baseline diversity was not predictive of eventual outcome. Patients with high toxicity demonstrated different compositional changes during CRT in addition to compositional differences in Clostridia species.

CONCLUSIONS

Over time, increased radiation toxicity is associated with decreased gut microbiome diversity. Baseline diversity is not predictive of end-of-treatment bowel toxicity, but composition may identify patients at risk for developing high toxicity.