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Clinical Trial
. 2020 May 1;107(1):163-171.
doi: 10.1016/j.ijrobp.2019.12.040. Epub 2020 Jan 25.

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

Aparna Mitra  1 , Greyson Willis Grossman Biegert  1 , Andrea Y Delgado  1 , Tatiana V Karpinets  2 , Travis N Solley  1 , Melissa P Mezzari  3 , Kyoko Yoshida-Court  1 , Joe F Petrosino  3 , Megan D Mikkelson  1 , Lilie Lin  1 , Patricia Eifel  1 , Jianhua Zhang  2 , Lois M Ramondetta  1 , Anuja Jhingran  1 , Travis T Sims  1 , Kathleen Schmeler  4 , Pablo Okhuysen  5 , Lauren E Colbert  6 , Ann H Klopp  1
Affiliations
Clinical Trial

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

Aparna Mitra et al. Int J Radiat Oncol Biol Phys. .

Abstract

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.

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Conflict of interest statement

Conflict of interest: None

Figures

Figure 1.
Figure 1.
Expanded Prostate Cancer Index Composite (EPIC) assessment of patient reported gastrointestinal toxicity during radiation therapy. The total score (1A) and bother score (1B) declined over the course of treatment, representing an increase in the symptom burden during treatment. Comparisons between each time point were made and p-values for significant differences are shown.
Figure 1.
Figure 1.
Expanded Prostate Cancer Index Composite (EPIC) assessment of patient reported gastrointestinal toxicity during radiation therapy. The total score (1A) and bother score (1B) declined over the course of treatment, representing an increase in the symptom burden during treatment. Comparisons between each time point were made and p-values for significant differences are shown.
Figure 2.
Figure 2.
Changes in alpha diversity and taxa abundance during radiation therapy. Alpha diversity for patients that received radiation therapy at baseline, week 1, week 3 and week 5 of radiation therapy (2A). A significant decline in alpha diversity was seen in between baseline and week 5 of radiation (paired t-test). Principle coordinate analysis of Jaccard distances of fecal microbiota from 16S gene sequence analysis in all patients receiving radiation therapy for a period of 5 weeks. Axis levels indicate percent of variance represented by principle coordinate axis (2B). The relative abundance of microbes over the 5 week course of radiation therapy using 16S sequencing data analysis done using ATIMA (R package of APE and VEGAN). (C). Microbes belonging to the order Clostridia decline significantly over time (2C).
Figure 2.
Figure 2.
Changes in alpha diversity and taxa abundance during radiation therapy. Alpha diversity for patients that received radiation therapy at baseline, week 1, week 3 and week 5 of radiation therapy (2A). A significant decline in alpha diversity was seen in between baseline and week 5 of radiation (paired t-test). Principle coordinate analysis of Jaccard distances of fecal microbiota from 16S gene sequence analysis in all patients receiving radiation therapy for a period of 5 weeks. Axis levels indicate percent of variance represented by principle coordinate axis (2B). The relative abundance of microbes over the 5 week course of radiation therapy using 16S sequencing data analysis done using ATIMA (R package of APE and VEGAN). (C). Microbes belonging to the order Clostridia decline significantly over time (2C).
Figure 2.
Figure 2.
Changes in alpha diversity and taxa abundance during radiation therapy. Alpha diversity for patients that received radiation therapy at baseline, week 1, week 3 and week 5 of radiation therapy (2A). A significant decline in alpha diversity was seen in between baseline and week 5 of radiation (paired t-test). Principle coordinate analysis of Jaccard distances of fecal microbiota from 16S gene sequence analysis in all patients receiving radiation therapy for a period of 5 weeks. Axis levels indicate percent of variance represented by principle coordinate axis (2B). The relative abundance of microbes over the 5 week course of radiation therapy using 16S sequencing data analysis done using ATIMA (R package of APE and VEGAN). (C). Microbes belonging to the order Clostridia decline significantly over time (2C).
Figure 3.
Figure 3.
Correlation between alpha diversity and patient reported toxicity. Alpha diversity (Simpson Diversity) was correlated with EPIC scores for all patients at all-time points (3A). Alpha diversity in patients who developed high or low toxicity was not significantly different at each time point (3B). (3C)Association networks (Anets) of baseline samples (A) and week 5 samples (B). Nodes represent samples and edge indicate similar profiles of shared species richness. (3D)
Figure 3.
Figure 3.
Correlation between alpha diversity and patient reported toxicity. Alpha diversity (Simpson Diversity) was correlated with EPIC scores for all patients at all-time points (3A). Alpha diversity in patients who developed high or low toxicity was not significantly different at each time point (3B). (3C)Association networks (Anets) of baseline samples (A) and week 5 samples (B). Nodes represent samples and edge indicate similar profiles of shared species richness. (3D)
Figure 3.
Figure 3.
Correlation between alpha diversity and patient reported toxicity. Alpha diversity (Simpson Diversity) was correlated with EPIC scores for all patients at all-time points (3A). Alpha diversity in patients who developed high or low toxicity was not significantly different at each time point (3B). (3C)Association networks (Anets) of baseline samples (A) and week 5 samples (B). Nodes represent samples and edge indicate similar profiles of shared species richness. (3D)
Figure 3.
Figure 3.
Correlation between alpha diversity and patient reported toxicity. Alpha diversity (Simpson Diversity) was correlated with EPIC scores for all patients at all-time points (3A). Alpha diversity in patients who developed high or low toxicity was not significantly different at each time point (3B). (3C)Association networks (Anets) of baseline samples (A) and week 5 samples (B). Nodes represent samples and edge indicate similar profiles of shared species richness. (3D)
Figure4:
Figure4:
Heat map Specific OTUs associated with high/low toxicity according to the Fisher test (not adjusted for multiple testing) at the end of therapy (A) and their abundances at baseline (B).
Figure 5:
Figure 5:
Identification of taxa discriminating patients developing longitudinal toxicity or experiencing high toxicity at any time. Differential abundance of taxa in patients who experienced high toxicity over the course of treatment as compared to patients with low toxicity over the course of treatment using Linear Discriminant Analysis Effect Size (LefSe) at baseline (5A) and at week 5 (5B).
Figure 5:
Figure 5:
Identification of taxa discriminating patients developing longitudinal toxicity or experiencing high toxicity at any time. Differential abundance of taxa in patients who experienced high toxicity over the course of treatment as compared to patients with low toxicity over the course of treatment using Linear Discriminant Analysis Effect Size (LefSe) at baseline (5A) and at week 5 (5B).
Figure 5:
Figure 5:
Identification of taxa discriminating patients developing longitudinal toxicity or experiencing high toxicity at any time. Differential abundance of taxa in patients who experienced high toxicity over the course of treatment as compared to patients with low toxicity over the course of treatment using Linear Discriminant Analysis Effect Size (LefSe) at baseline (5A) and at week 5 (5B).
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