Purpose:

Radiotherapy is important in managing pelvic cancers. However, radiation enteropathy may occur and can be dose limiting. The gut microbiota may contribute to the pathogenesis of radiation enteropathy. We hypothesized that the microbiome differs between patients with and without radiation enteropathy.

Experimental Design: Three cohorts of patients (n = 134) were recruited. The early cohort (n = 32) was followed sequentially up to 12 months post-radiotherapy to assess early radiation enteropathy. Linear mixed models were used to assess microbiota dynamics. The late cohort (n = 87) was assessed cross-sectionally to assess late radiation enteropathy. The colonoscopy cohort compared the intestinal mucosa microenvironment in patients with radiation enteropathy (cases, n = 9) with healthy controls (controls, n = 6). Fecal samples were obtained from all cohorts. In the colonoscopy cohort, intestinal mucosa samples were taken. Metataxonomics (16S rRNA gene) and imputed metataxonomics (Piphillin) were used to characterize the microbiome. Clinician- and patient-reported outcomes were used for clinical characterization.

Results:

In the acute cohort, we observed a trend for higher preradiotherapy diversity in patients with no self-reported symptoms (P = 0.09). Dynamically, diversity decreased less over time in patients with rising radiation enteropathy (P = 0.05). A consistent association between low bacterial diversity and late radiation enteropathy was also observed, albeit nonsignificantly. Higher counts of Clostridium IV, Roseburia, and Phascolarctobacterium significantly associated with radiation enteropathy. Homeostatic intestinal mucosa cytokines related to microbiota regulation and intestinal wall maintenance were significantly reduced in radiation enteropathy [IL7 (P = 0.05), IL12/IL23p40 (P = 0.03), IL15 (P = 0.05), and IL16 (P = 0.009)]. IL15 inversely correlated with counts of Roseburia and Propionibacterium.

Conclusions:

The microbiota presents opportunities to predict, prevent, or treat radiation enteropathy. We report the largest clinical study to date into associations of the microbiota with acute and late radiation enteropathy. An altered microbiota associates with early and late radiation enteropathy, with clinical implications for risk assessment, prevention, and treatment of radiation-induced side-effects.

See related commentary by Lam et al., p. 6280

Translational Relevance

Clinical evidence shows that gut microbiota changes during radiotherapy and suggests associations with radiation enteropathy, but this evidence is limited. Clinical studies often include patients receiving concurrent cytotoxic systemic therapies. Experiments in animal models indicate that gut microbiota is necessary for radiation enteropathy to occur and that an irradiated microbiota promotes enteropathy. However, animal models have different radioresistance and microbiota compared with humans, and usually receive high-dose single-fraction radiation, limiting clinical translation. Moreover, all evidence focuses on acute radiation enteropathy and does not address dose-limiting late radiation enteropathy. We report the largest clinical study to date into associations of the microbiota with acute and late radiation enteropathy. It is the only study where patients received homogeneous treatment and where no patients received cytotoxic systemic therapies. Our novel methodology allowed assessment of acute and late radiation enteropathy. We demonstrate that some bacteria producing short-chain fatty acids are associated with radiation-induced side-effects and that this relates to an altered intestinal microenvironment. We demonstrate that an altered microbiota associates with early and late radiation enteropathy, with clinical implications for risk assessment, prevention, and treatment of radiation-induced side-effects.

Pelvic radiotherapy is an important curative treatment option for patients with pelvic cancers. However, acute (≤90 days of starting radiotherapy) and chronic (thereafter) gastrointestinal side-effects, collectively summarized by the term “radiation enteropathy”, may develop. Indeed, risk of gastrointestinal toxicity limits the radiation dose that can be delivered (1). Radiation enteropathy can be defined as a progressive, ischemic, and profibrotic process occurring after abdominal or pelvic irradiation, driven by pathophysiologic processes which are incompletely defined (1, 2). Mechanisms involving the microbiota may contribute to the spectrum of radiation enteropathy (1). However, published research concentrates on acute radiation enteropathy, whereas it is late radiation enteropathy that is usually dose limiting, and often uses animal models, which have limitations (3–6).

To better understand the role of the microbiota in radiation enteropathy, we prospectively collected fecal samples from three complementary cohorts of patients, collectively assessing the whole spectrum of radiation enteropathy. We hypothesized that the microbiome differs between patients with and without radiation enteropathy after pelvic radiotherapy.

### The MARS study

The MARS study was an observational, noninterventional study. Three cohorts were recruited in parallel (Supplementary Fig. S1). All patients attending relevant clinics were invited to participate during a 2-year period (see Section 1C in Supplementary Data for sample size justification).

The first (termed “early cohort”) assessed the development of early radiation enteropathy in a group of patients recruited before undergoing high-dose intensity-modulated radiotherapy to the prostate and pelvic lymph nodes (PLN-IMRT) and followed longitudinally up to a year thereafter. Patients undergoing PLN-IMRT were chosen because they are at increased risk of radiation enteropathy when compared with prostate-only radiotherapy (7). Clinical assessment and sampling was performed at baseline (preradiotherapy), at 2/3 weeks, 4/5 weeks, 12 weeks, 6 months, and 12 months post-radiotherapy initiation (Supplementary Fig. S2).

The second (termed “late cohort”) explored late radiation enteropathy and included patients with ≥2 years of follow-up after PLN-IMRT who were evaluated cross-sectionally. Patients in this cohort were recruited from the population of a previously reported dose-escalation trial of PLN-IMRT (7). Their radiotherapy followed an identical protocol to the longitudinal cohort.

The third (termed “colonoscopy cohort”) assessed the intestinal mucosa immune environment in radiation enteropathy and its relationships with the microbiome. It included patients with ≥1 year of follow-up after radiotherapy for prostate cancer and attending a specialist clinical service for managing radiation-induced gastrointestinal symptoms who were undergoing colonoscopy for symptom investigation (termed “cases”), as well as nonirradiated control subjects (“controls”), undergoing colonoscopy for colon cancer screening and confirmed free of gastrointestinal diseases. We sampled anterior rectum (cases/controls) and distal sigmoid (cases only). The anterior rectum is the gastrointestinal location receiving maximal irradiation in radiotherapy for prostate cancer, while the distal sigmoid is less irradiated and was thus used as a self-control in cases.

All subjects provided written informed consent prior to entry into the study. The study was approved by the Committee for Clinical Research at the Royal Marsden (no.: 4010) and by the London-Bromley Research Ethics Committee (no.: 13/LO/1527), and registered by the NHS Health Research Authority (ID: 130287). All study procedures were conducted in accordance to the Declaration of Helsinki.

### Assessments

Clinician-reported outcomes (CRO) included items of the Radiation Therapy Oncology Group (RTOG) and Late Effects of Normal Tissues (LENT-SOM) scales with an impact on quality of life [bowel problem/distress measured with the University of California, Los Angeles Prostate Cancer Index (UCLA-PCI) scale; refs. 8–10]. The criteria used were RTOG diarrhea and proctitis, and LENT-SOM sphincter control (subjective); tenesmus (subjective), bleeding (objective), pain (objective), and bleeding (management). Two summary figures (RTOG maximum and LENT/SOM maximum) were created from maximum toxicity scores. Both scales are graded 1–5, with increasing scores representing worse symptoms. Patient-reported outcomes (PRO) were analyzed with the bowel subset of a gastrointestinal symptom score validated for radiation enteropathy and graded 1–7 for 10 items (Supplementary Table S1), with scores ranging from 10 (very symptomatic) to 70 (no symptoms; ref. 11).

In the late cohort, peak cumulative late toxicity scores (from 6 month after radiotherapy onwards) were available as per the IMRT for Prostate Cancer study protocol. CRO included RTOG diarrhea and RTOG proctitis. PRO included UCLA-PCI bowel problem and distress. For convenience, we have termed prevalence data at the time of sampling “actual toxicity”, and peak cumulative data “historic toxicity”.

Patient comorbidity and diet, were also assessed (Supplementary Materials and Methods; Supplementary Table S2). Intestinal mucosa histology (colonoscopy cohort), was evaluated with a semiquantitative histopathology score (Supplementary Table S3; ref. 12).

### Definition of symptom groups

Patients in the early cohort were divided in three groups, which were (i) no symptoms (no symptoms at either 4/5 weeks or 6 months); (ii) nonpersistent symptoms (symptoms at either 4/5 weeks or 6 months); and (iii) persistent symptoms (symptoms at 4/5 weeks and 6 months). To not lose data, the CRO-based symptom classification was substituted for 13 patients (41%) where PRO data were missing at either of these timepoints, which were chosen as representative of maximal acute enteropathy (4/5 weeks) and early late enteropathy (6 months; ref. 7). This strategy enables identification of patients experiencing nonhealing acute toxicity, which may be related to a consequential reaction and determines a higher risk of long-term radiation enteropathy (13).

In the late cohort, CRO groups were defined by symptom grade. PRO-based groupings were based on the data, by dividing patients in quartiles defining increasing symptoms. For convenience, these categories were identified as no, mild, moderate, and severe symptoms (Supplementary Table S4).

In the colonoscopy cohort, cases were compared with controls.

### Sampling procedures and processing

#### Sampling of stool.

Sampling of stool was performed according to published guidance (14). Details are given in Supplementary Materials and Methods.

#### Sampling of intestinal mucosa (colonoscopy cohort only).

Three biopsies were taken per site (Supplementary Fig. S3) for metataxonomics, cytokine analysis, and pathology assessment. In cases and controls, samples were obtained from the anterior rectum, which is the part of the gastrointestinal tract which receives the greatest radiation dose during radiotherapy for prostate cancer (15). In cases only, another three biopsies were obtained from a macroscopically unaffected region as close to affected areas as possible, which was in all the distal sigmoid, to be used as a self-control. Further details are given in Supplementary Materials and Methods.

#### Data acquisition.

##### DNA extraction procedure, data acquisition, and processing

Genomic DNA was extracted from fecal (250 mg) and gut biopsy (whole biopsy) samples using the Qiagen Stool Kit (Qiagen) according to the manufacturer's instructions with an additional bead beating step for homogenization of sample and lysis of bacterial cells. Library preparation and Illumina (MiSeq) sequencing of the V1–2 regions of the 16S rRNA gene were performed at RTL Genomics. Details are given in Supplementary Materials and Methods.

##### Cytokine detection

Total protein was extracted from mucosal samples and cytokine detection was carried out with the MSD V-PLEX Human Cytokine 30-Plex kit according to the manufacturer's instructions. The manufacturer states that all cytokine isoforms are detected. Details are given in Supplementary Materials and Methods.

### Statistical considerations

#### Bioinformatic processing of 16S rRNA gene data.

Sequences generated from Illumina (MiSeq) sequencing were analyzed with MOTHUR (version 1.36.0) for identification of operational taxonomic units (OTU), taxonomic assignment, community comparison, and data cleaning by adapting its standard operational procedure (16). Details are given in Supplementary Materials and Methods.

Inferred metagenomes were obtained by using the Piphillin web tool by Second Genome, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) May 2017 database, and a 97% identity cutoff.

#### Significance testing.

The significance of taxonomic differences was assessed with one-way ANOVA (≥3 group comparisons), or White nonparametric two-sided t test (two-group comparisons). The Benjamini–Hochberg method was used for FDR correction. However, a pragmatic approach was taken, with uncorrected P values taken into account given the exploratory context of this work (17). Uncorrected P values are termed “p*”, while P values after correction are termed “p”. Statistically significant results explained by large peaks in <10% of a group were considered nonbiologically relevant.

The Kruskal–Wallis H test was used to assess differences observed when comparing α-diversity indices, diet, and histology scores (colonoscopy cohort).

Longitudinal dynamics in the early cohort were evaluated with linear mixed models. Linear mixed models use fixed and random effects in the same analysis. Unlike univariate or multivariate linear regression, one can assess individual variation by subject per timepoint by analyzing the longitudinal change of a variable of interest over time by symptom group (18). Also, mixed mods allow for missing observations, as other data endpoints can be still be used as long as the missing data meets the missing-at-random definition (18). This analysis was performed in R using the “nlme” package and the following formulation:

Where |{\beta _0}$| is the population estimate of the intercept for the control group (no symptoms), |{\beta _1}$| is the population estimate of the linear slope of the control group, |{\beta _2}$| and |{\beta _3}$| capture the estimates of the mean difference in intercept and slope between symptom groups, |{b_{0i}}$| and |{b_{1i}}$| are random effects that allow the intercepts and slopes to vary across individuals, and |{\varepsilon _{ti}}$| is a time-specific residual that expresses the difference between and individual's fitter linear trajectory and the observed data. Thus, |{\beta _3}$| represents the “symptom group by timepoint” interaction (19). To assess significance, t tests using Satterthwaite method were implemented.

Variable transformations were used according to the data and are discussed with results. The Akaike Information Criterion was used to assess whether models with transformed variables improved goodness of fit. Full results (including all effect estimates and significance) are provided in Supplementary Materials and Methods.

Multivariate analysis was performed with robust linear models in R using the “MASS” and “sfsmisc” packages with the following formulation:

Where |{\beta _0}$| is the mean intercept, and |{\beta _1}$| and |{\beta _2}$| are the coefficients for variables |{x_1}$| and |{x_2}\$|⁠, respectively. Significance of coefficients was assessed with a robust F test (Wald test) using the f.robftest() function.

#### Comparison of cytokine levels and correlations with microbiome.

The significance of differences between cytokine levels was assessed with the Kruskal–Wallis H test. A significance of P < 0.1 (uncorrected for multiple comparisons) was defined for post hoc (Mann–Whitney) testing. We report results of post hoc tests. Correlations of cytokines with the microbiome were explored in bacterial genera where OTU counts were >0 in ≥20% of subjects with Spearman rank correlation coefficient.

### Data availability

All data generated or analyzed during this study are included in the published article and its Supplementary Information Files.

### Demographics and symptoms

A total of 134 men were enrolled between March 18, 2014 and February 01, 2016 (Table 1): 32 in the early cohort, 87 in the late cohort, and 15 in the colonoscopy cohort (9 cases/6 controls). All patients in the early and late cohorts underwent prostate and pelvic radiotherapy following a previously published protocol (7). In the colonoscopy cohort, 6 cases had undergone radiotherapy to the prostate and seminal vesicles, 1 had undergone radiotherapy to the prostate, seminal vesicles, and pelvic lymph nodes, and 2 had undergone postprostatectomy radiotherapy to the prostate bed and pelvic lymph nodes. Control subjects had not been treated with any radiotherapy.

Table 1.

Demographics

Colonoscopy cohort
ItemEarly cohortLate cohortCasesControls
Median age at date of enrollment in years (IQR) 66 (63–72) 74 (68–79) 75 (71–76) 68 (57–69)
Median time in years between radiotherapy commencement and sampling NA 6.05 (4.57–7.28) 4.2 (1.9–10.4) NA
Radiotherapy details
Patients treated with conventionally fractionated radiotherapya: 70–74 Gy to prostate and seminal vesicles (35–37 fractions) or 64 Gy to prostate bed (32 fractions); 50–60 Gy to pelvic lymph nodes (35–37 fractions)–n (%) 31 (97%) 48 (55%) 3 (33%) NA
Patients treated with hypofractionated radiotherapya: 60 Gy to prostate and seminal vesicles or 55 Gy to prostate bed (20 fractions); 47 Gy to pelvic lymph nodes)–n (%) 1 (3%) 39 (45%) 0 (0%) NA
Patients treated with conventionally fractionated radiotherapy to prostate and seminal vesicles only: 70–74 Gy in 35–37 fractions NA NA 6 (67%) NA
Prostate cancer details
Median presenting PSA (IQR) in ng/mL 26.2 (13.4–47) 18.1 (11.05–34.50) 7.05 (5.43–13.40) NA
Median PSA at time of sampling (IQR) in ng/mL NA NA 8.4 (5.7–14.6) NA
Gleason 6–n (%) 1 (3%) 3 (3%) 2 (22%) NA
Gleason 7–n (%) 12 (37%) 33 (38%) 6 (67%) NA
Gleason 8–n (%) 3 (9%) 14 (16%) 0 (0%) NA
Gleason 9–n (%) 16 (50%) 37 (43%) 1 (1%) NA
N0–n (%) 16 (50%) 62 (71%) 7 (78%) NA
N1–n (%) 16 (50%) 24 (28%) 2 (22%) NA
NX–n (%) 0 (0%) 1 (1%) 0 (0%) NA
T1–n (%) 1 (3%) 1 (1%) 0 (0%) NA
T2–n (%) 7 (22%) 18 (21%) 2 (22%) NA
T3–n (%) 24 (75%) 65 (75%) 7 (78%) NA
T4–n (%) 0 (0%) 2 (2%) 0 (0%) NA
TX–n (%) 0 (0%) 1 (1%) 0 (0%) NA
Subjects on short-course antiandrogen and long-term LHRH analogues 22 (69%) NA 1 (1%) NA
Subjects on bicalutamide monotherapy 1 (3%) NA 0 (0%) NA
Subjects on maximum androgen blockade 9 (28%) NA 0 (0%) NA
Subjects with recurrent tumors at time of sampling–n (%)b NA 11 (13%) 1 (1%) NA
Subjects on ADT at time of sampling–n (%)b 32 (100%)c 10 (11%) 1 (1%) NA
Subjects with recovered testosterone levels (≥6 nmol/L)–n (%)b NAc 47 (54%) 5 (56%) NA
Other comorbiditiesb
Subjects with history of abdominal or pelvic surgery–n (%) 19 (59%) 40 (46%) 6 (67%) 3 (50%)
Median body mass index (IQR) 27 (25–32) 26.5 (24.7–29.8) 26 (25–27) 24 (24–25)
Subjects with dyslipidemia and on statins–n (%) 10 (31%) 45 (52%) 4 (44%) 2 (33%)
Subjects with history of diabetes–n (%) 7 (22%) 15 (17%) 0 (0%) 0 (0%)
Subjects with history of hypertension and on medical treatment–n (%) 13 (41%) 49 (56%) 7 (78%) 1 (16%)
Subjects with history of IBS–n (%) 0 (0%) 3 (3.4%) 2 (22%) 2 (33%)
Subjects with history of diverticular disease–n (%) 1 (3%) 10 (11%) 2 (22%) 0 (0%)
Nonsmokers/ex-smokers/smokers–n (%) 19 (59%)/11 (34%)/2 (6%) 37 (42%)/38 (44%)/12 (14%) 4 (44%)/4 (44%)/1 (1%) 1 (17%)/5 (83%)/0 (0%)
Colonoscopy cohort
ItemEarly cohortLate cohortCasesControls
Median age at date of enrollment in years (IQR) 66 (63–72) 74 (68–79) 75 (71–76) 68 (57–69)
Median time in years between radiotherapy commencement and sampling NA 6.05 (4.57–7.28) 4.2 (1.9–10.4) NA
Radiotherapy details
Patients treated with conventionally fractionated radiotherapya: 70–74 Gy to prostate and seminal vesicles (35–37 fractions) or 64 Gy to prostate bed (32 fractions); 50–60 Gy to pelvic lymph nodes (35–37 fractions)–n (%) 31 (97%) 48 (55%) 3 (33%) NA
Patients treated with hypofractionated radiotherapya: 60 Gy to prostate and seminal vesicles or 55 Gy to prostate bed (20 fractions); 47 Gy to pelvic lymph nodes)–n (%) 1 (3%) 39 (45%) 0 (0%) NA
Patients treated with conventionally fractionated radiotherapy to prostate and seminal vesicles only: 70–74 Gy in 35–37 fractions NA NA 6 (67%) NA
Prostate cancer details
Median presenting PSA (IQR) in ng/mL 26.2 (13.4–47) 18.1 (11.05–34.50) 7.05 (5.43–13.40) NA
Median PSA at time of sampling (IQR) in ng/mL NA NA 8.4 (5.7–14.6) NA
Gleason 6–n (%) 1 (3%) 3 (3%) 2 (22%) NA
Gleason 7–n (%) 12 (37%) 33 (38%) 6 (67%) NA
Gleason 8–n (%) 3 (9%) 14 (16%) 0 (0%) NA
Gleason 9–n (%) 16 (50%) 37 (43%) 1 (1%) NA
N0–n (%) 16 (50%) 62 (71%) 7 (78%) NA
N1–n (%) 16 (50%) 24 (28%) 2 (22%) NA
NX–n (%) 0 (0%) 1 (1%) 0 (0%) NA
T1–n (%) 1 (3%) 1 (1%) 0 (0%) NA
T2–n (%) 7 (22%) 18 (21%) 2 (22%) NA
T3–n (%) 24 (75%) 65 (75%) 7 (78%) NA
T4–n (%) 0 (0%) 2 (2%) 0 (0%) NA
TX–n (%) 0 (0%) 1 (1%) 0 (0%) NA
Subjects on short-course antiandrogen and long-term LHRH analogues 22 (69%) NA 1 (1%) NA
Subjects on bicalutamide monotherapy 1 (3%) NA 0 (0%) NA
Subjects on maximum androgen blockade 9 (28%) NA 0 (0%) NA
Subjects with recurrent tumors at time of sampling–n (%)b NA 11 (13%) 1 (1%) NA
Subjects on ADT at time of sampling–n (%)b 32 (100%)c 10 (11%) 1 (1%) NA
Subjects with recovered testosterone levels (≥6 nmol/L)–n (%)b NAc 47 (54%) 5 (56%) NA
Other comorbiditiesb
Subjects with history of abdominal or pelvic surgery–n (%) 19 (59%) 40 (46%) 6 (67%) 3 (50%)
Median body mass index (IQR) 27 (25–32) 26.5 (24.7–29.8) 26 (25–27) 24 (24–25)
Subjects with dyslipidemia and on statins–n (%) 10 (31%) 45 (52%) 4 (44%) 2 (33%)
Subjects with history of diabetes–n (%) 7 (22%) 15 (17%) 0 (0%) 0 (0%)
Subjects with history of hypertension and on medical treatment–n (%) 13 (41%) 49 (56%) 7 (78%) 1 (16%)
Subjects with history of IBS–n (%) 0 (0%) 3 (3.4%) 2 (22%) 2 (33%)
Subjects with history of diverticular disease–n (%) 1 (3%) 10 (11%) 2 (22%) 0 (0%)
Nonsmokers/ex-smokers/smokers–n (%) 19 (59%)/11 (34%)/2 (6%) 37 (42%)/38 (44%)/12 (14%) 4 (44%)/4 (44%)/1 (1%) 1 (17%)/5 (83%)/0 (0%)

NOTE: The reader is reminded that cohorts were not directly compared, but independently assessed to investigate the microbiota of patients with early and late side-effects.

Abbreviations: IQR, inter quartile range; NA = not applicable.

aConventional and hypofractionated radiotherapy schedules used to treat patients were shown to produce comparable rates of tumor recurrence, as well as early and late toxicities in a phase II trial (see ref. 7).

bA detailed comparison of comorbidities between toxicity groups in each cohort is reported in the main text and in Supplementary Tables S6–S8 in Supplementary Materials and Methods.

cAll subjects in the early cohort were under neo-adjuvant ADT from the time of recruitment, as per the protocol for treating high-risk prostate cancer (including ADT starting before radiotherapy and extending for 2–3 years in total) and their testosterone levels were therefore undetectable. Some patients in the late cohort (≥2 years after RT) were under long-term ADT for the same reason. ADT was not found to significantly impact the microbiome in this study (see Supplementary Data).

In the early cohort, patients with nonpersistent symptoms mostly experienced symptoms at 4/5 weeks (84%/PRO, 92%/CRO). Classification was concordant (i.e., patients classified in the same group with both PRO and CRO) in 21 patients (66%; Supplementary Table S5).

Symptoms and diet are described detail in Supplementary Data. We did not detect biologically relevant dietary differences between groups.

As per our study design, cohorts were not compared with one another, but used to assess different aspects of radiation enteropathy. Therefore, we analyzed whether comorbidities [including body mass index, smoking status/history, metabolic diseases, androgen deprivation therapy (ADT), and other comedications] were different between symptom groups to be analyzed in each cohort. Overall, comorbidities were well balanced between groups (Supplementary Tables S6–S8). No significant differences were found in the early cohort. In the late cohort, actual CRO-stratified groups showed significantly higher proportions of irritable bowel syndrome (P = 0.0004) in patients with rising symptoms. In the colonoscopy cohort, proportions of controls under hypertensive medication were higher than in cases (P = 0.02). The overall low proportions of patients with irritable bowel syndrome (IBS) in all cohorts may be attributed to eligibility criteria for pelvic radiotherapy, which is relatively contraindicated for patients with gastrointestinal conditions.

### Comparison of stool and mucosal microbiome in the colonoscopy cohort

We did not find significant differences when comparing stool and intestinal mucosa microbiomes in the colonoscopy cohort, although there was a trend for higher α-diversity, measured with the Chao index, in stools compared with intestinal mucosal microbiome in cases [median (IQR): 77 (59.3–117.1) vs. 54.1 (51.3–65.2)]. However, no significant differences in β-diversity or in individual phyla or genera were found. Results are described in detail in Supplementary Data.

### Low bacterial diversity associates with radiation enteropathy

Low bacterial diversity has been consistently associated with acute radiation enteropathy (6, 20–23). Relationships with late enteropathy have never been explored. We therefore assessed bacterial diversity between irradiated patients with and without gastrointestinal side-effects.

In the early cohort, we first explored associations between baseline diversity and radiation enteropathy in the acute cohort. We found a trend for higher diversity at baseline in patients with no self-reported symptoms [P = 0.09; median (IQR) Chao richness for no radiation enteropathy: 89.1 (78.9–114.0); nonpersistent radiation enteropathy: 55.2 (42.6–72.5); and persistent radiation enteropathy: 68.6 (41.8–75.1)]. This observation was recapitulated with CRO, albeit nonsignificantly [P = 0.61; 76.3 (65–86.1); nonpersistent radiation enteropathy: 55.2 (48.0–84.5); and persistent radiation enteropathy: 65.3 (39.1–75.1)]. We next examined dynamics of α-diversity over time with linear mixed models. The variable of interest was Chao abundance of bacterial species, with predictors of dynamics specified as timepoint and symptom group (Supplementary Fig. S1A and S1B; Supplementary Table S9). When not stratified by symptom group, diversity appeared to decrease in the whole cohort over time, albeit nonsignificantly (effect of timepoint: −0.02; P = 0.35; Supplementary Fig. S5). With PRO stratification, diversity generally decreased over time (P = 0.03). A positive effect of timepoint by symptom group indicates differential dynamics of diversity over time (P = 0.05; Fig. 1A). This pattern was similar when an identical model based on CRO was used, although it did not reach statistical significance. We next examined differences in bacterial diversity between patients with and without late enteropathy in the late cohort (Fig. 1C–J). No significant differences were found with PRO or CRO in the late (Fig. 1C–J; Supplementary Fig S4) or colonoscopy (Fig. 1K–L) cohorts. However, a nonsignificant pattern of higher diversity in symptomatic patients was observed in both cohorts.

Figure 1.

Bacterial diversity in the early (A and B), late (C–J), and colonoscopy (K and L) cohorts of the MARS study. Dynamics of Chao diversity over time in PRO (A) and CRO (B) stratified groups, where the effect of timepoint (P = 0.03) and timepoint by symptom group (P = 0.05) were significant in PRO-stratified groups. Groups: 0, no symptoms; 1, nonpersistent symptoms; and 2, persistent symptoms. Timepoints: 1, baseline; 2, 2/3 weeks; 3, 4/5 weeks; 4, 12 weeks; 5, 6 months; and 6, 12 months after radiotherapy initiation. A log transformation was used because of a positive skew of the data, which was confirmed to provide superior goodness of fit when compared with square-root transformations. Chao diversity in the late cohort in groups stratified by CRO actual/historical diarrhea (C and F), proctitis (D and G), and maximum toxicity (E and H); and by PRO actual (I) and late (J) toxicity. P > 0.05 in all comparisons. The reader is reminded that scales for PRO stratification differed between actual and historical toxicity (see Materials and Methods). Chao diversity in the colonoscopy cohort with stool (K) and intestinal mucosa (L) samples (P > 0.05 in both comparisons).

Figure 1.

Bacterial diversity in the early (A and B), late (C–J), and colonoscopy (K and L) cohorts of the MARS study. Dynamics of Chao diversity over time in PRO (A) and CRO (B) stratified groups, where the effect of timepoint (P = 0.03) and timepoint by symptom group (P = 0.05) were significant in PRO-stratified groups. Groups: 0, no symptoms; 1, nonpersistent symptoms; and 2, persistent symptoms. Timepoints: 1, baseline; 2, 2/3 weeks; 3, 4/5 weeks; 4, 12 weeks; 5, 6 months; and 6, 12 months after radiotherapy initiation. A log transformation was used because of a positive skew of the data, which was confirmed to provide superior goodness of fit when compared with square-root transformations. Chao diversity in the late cohort in groups stratified by CRO actual/historical diarrhea (C and F), proctitis (D and G), and maximum toxicity (E and H); and by PRO actual (I) and late (J) toxicity. P > 0.05 in all comparisons. The reader is reminded that scales for PRO stratification differed between actual and historical toxicity (see Materials and Methods). Chao diversity in the colonoscopy cohort with stool (K) and intestinal mucosa (L) samples (P > 0.05 in both comparisons).

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### Patients with radiation enteropathy have higher counts of Roseburia, Clostridium IV, and Faecalibacterium

Enrichment in specific microbial taxa has been described in patients with primary inflammatory bowel disease (IBD; ref. 24). Similarly, associations between specific bacterial taxa and acute radiation enteropathy have been reported (6, 21, 23, 25). We therefore investigated whether specific bacterial taxa were associated with radiation enteropathy. We first compared proportions of phyla and genera between patients with and without radiation enteropathy at each timepoint in the early cohort. No microbial features showed statistically significant relationships. However, because of the limited power of this cohort for detecting differences based on direct comparisons per timepoint, we defined biologically plausible relationships as progressive changes in proportions of microbial features (i.e., either increasing or decreasing) with rising symptoms, irrespective of statistical significance. Results are summarized in Supplementary Table S10. We used linear mixed models to evaluate longitudinal dynamics of specific microbial taxa taking into account the results above. Bacterial taxa with biologically plausible relationships where uncorrected P values (p*) < 0.05 were retained. They were Clostridium IV, Roseburia, and Phascolarctobacterium, which are short chain fatty acid (SCFA) producers. Sutterella dynamics were also analyzed in light of a biologically plausible relationship and a published evidence suggesting that a microbiome enriched in this taxon associates with acute radiation proctitis in an animal model (23). Results are summarized in Fig. 2 and Supplementary Table S11. Clostridium IV proportions increased significantly with PRO (effect = 0.4; P = 0.007), with a trend toward a progressively more negative slope of proportions over time with increasing symptoms group (estimate = −0.04; P = 0.11). This behavior was reflected with CRO. A trend was also observed for increased Roseburia counts in direct proportion with patient-reported symptoms (effect = 0.37; P = 0.08), which were reflected with CRO. Plotting the models shows a comparatively steep decrease in Roseburia proportions in patients with persistent symptoms. A trend of higher proportions of Phascolarctobacterium in direct proportion to CRO was observed (effect = 0.26; P = 0.09) and reflected with PRO. Proportions of Sutterella appeared to increase with symptoms with minimal change over time, albeit nonsignificantly.

Figure 2.

Dynamics of proportions of Clostridium IV (A and B), Roseburia (C and D), Phascolarctobacterium (E and F), and Sutterella (G and H) over time in PRO (left) and CRO (right) stratified groups. The effect of PRO symptom group was significant for Clostridium IV (P = 0.007). There was a trend for significance for the effect of PRO and CRO symptom group for Roseburia (P = 0.08) and Phascolarctobacterium, respectively. Groups: 0, no symptoms; 1, nonpersistent symptoms; and 2, persistent symptoms. Timepoints: 1, baseline; 2, 2/3 weeks; 3, 4/5 weeks; 4, 12 weeks; 5, 6 months; and 6, 12 months after radiotherapy initiation. A square-root transformation was used because of a positive skew of the data, which was confirmed to provide superior goodness of fit when compared with a log transformation in all models.

Figure 2.

Dynamics of proportions of Clostridium IV (A and B), Roseburia (C and D), Phascolarctobacterium (E and F), and Sutterella (G and H) over time in PRO (left) and CRO (right) stratified groups. The effect of PRO symptom group was significant for Clostridium IV (P = 0.007). There was a trend for significance for the effect of PRO and CRO symptom group for Roseburia (P = 0.08) and Phascolarctobacterium, respectively. Groups: 0, no symptoms; 1, nonpersistent symptoms; and 2, persistent symptoms. Timepoints: 1, baseline; 2, 2/3 weeks; 3, 4/5 weeks; 4, 12 weeks; 5, 6 months; and 6, 12 months after radiotherapy initiation. A square-root transformation was used because of a positive skew of the data, which was confirmed to provide superior goodness of fit when compared with a log transformation in all models.

Close modal

We next examined microbial taxa in the late cohort. It is noted that this analysis was completely independent of the early cohort, so all microbial taxa (and not only SCFA producers) were included, with ensuing FDR correction. No significant differences were found at either phylum or genus levels when stratifying patients according to either actual or historical PROs. However, when stratifying patients according to CROs, Roseburia significantly associated with toxicity (Fig. 3; Supplementary Table S12). Proportions of Roseburia rose with maximum actual (p* < 0.000001; p < 0.00001) and historical (p* = 0.001; p = 0.06) CRO symptom grade. No relevant differences at either phylum or genus level were detected for proctopathy. Roseburia significantly rose with both actual (P < 0.000001) and historical (P < 0.00001) clinician-reported diarrhea grade. To test whether significance was due to very high peaks in patients with grade 3 diarrhea, all patients with grade 3 toxicity were removed and differences retested including only patients with grade 0–2 diarrhea. Results with actual (P = 0.056) and historical (P = 0.04) diarrhea remained significant. Proportions of Roseburia also rose with historical PRO-stratified symptoms, albeit nonsignificantly (Supplementary Table S12). As higher proportions of IBS were found in patients with CRO-stratified actual symptoms, we used robust linear regression to adjust for these parameters in two independent multivariate models. The model predicted actual CRO grade with IBS (P = 0.002) and Roseburia (P = 0.02) as significant variables. To further assess whether a relationship between Roseburia and IBS was present, we also examined correlation between the two variables, which was not present (Spearman Rho = 0.09; P = 0.43). Moreover, no significant differences in genus-level taxa were found between patients with and without IBS in the late cohort, including Roseburia (p* = 0.60; p > 0.1) and Clostridium IV (p* = 0.59, p > 0.1). Because ADT has been associated with a modified microbiota in a previous report, we also examined in the microbiota of the late cohort stratified by active ADT or testosterone recovery status (26). No significant differences were found in α-diversity or in taxa (see Supplementary Data). We note that we did not carry out such analyses in the early cohort due to all patients being on active ADT since before baseline sampling and consequently having undetectable testosterone levels.

Figure 3.

Proportions of Roseburia in actual (AC) and historical (DF) CRO-stratified groups of the late cohort by CRO grade. A and D, Maximum toxicity. B and E, Diarrhea. C and F, Proctitis. Higher grades reflect more serious symptoms. *, P = 0.06; **, P ≤ 0.01; ****, P ≤ 0.001. All P values shown are corrected for FDR. The x-axis shows CRO grade.

Figure 3.

Proportions of Roseburia in actual (AC) and historical (DF) CRO-stratified groups of the late cohort by CRO grade. A and D, Maximum toxicity. B and E, Diarrhea. C and F, Proctitis. Higher grades reflect more serious symptoms. *, P = 0.06; **, P ≤ 0.01; ****, P ≤ 0.001. All P values shown are corrected for FDR. The x-axis shows CRO grade.

Close modal

In the colonoscopy cohort, no significant differences were found when comparing cases and controls. However, the size of this cohort limited statistical power (see Supplementary Data).

We then hypothesized that metagenomic abundance of microbial SCFA metabolism pathways differed between patients with and without symptoms of radiation enteropathy where significant associations were detected. We combined community composition with annotated genomes from the KEGG catalog and selected pathways related to microbial SCFA metabolism for analysis (27). We again used linear mixed models to evaluate dynamics in the early cohort (Supplementary Fig. S6; Supplementary Table S13). Abundances of SCFA-related microbial metabolic pathways increased consistently with symptoms, most noticeably with PRO, although this effect only trended for significance for propionate metabolism (P = 0.07). Propionate and other SCFA fuel colonocytes and upregulate colonic regulatory T lymphocytes, thereby promoting gut homeostasis (28). Its benefits to gut health have been reviewed elsewhere (29). The consistently negative effect of timepoint by symptom group suggests that microbial SCFA pathways may decrease more over time with rising symptoms. In the late cohort, only the abundance of fatty acid metabolism pathways decreased consistently with rising CRO diarrhea grade (P < 0.0001; Supplementary Fig. S7; Supplementary Table S14).

### Patients with radiation enteropathy have depletion of rectal mucosa cytokines regulating gut microbiota and homeostasis, correlating with higher counts of Roseburia and Propionibacterium

Cytokines are small molecules involved in cell signaling and have immunomodulatory, paracrine, and autocrine functions with pathophysiologic implications. However, gastrointestinal mucosal cytokine changes have never been studied in late radiation enteropathy. We therefore investigated differences in the concentrations of 29 cytokines, divided in three panels, between cases and controls in the colonoscopy cohort. A distinct general pattern of highest concentration in controls and lowest concentrations in the anterior rectum of cases was observed, except for proinflammatory cytokines, where no differences were found. When analyzing differences between sample types by cytokine, IL7 (P = 0.05), IL12/IL23p40 (P = 0.03), IL15 (P = 0.05), and IL16 (P = 0.009) were significantly higher in control than in case rectal biopsies, while eotaxin (P = 0.03) followed an inverse pattern (Fig. 4A–C). We did not find significant differences in pathology (including fibrosis) or in proinflammatory cytokines between cases and controls, which argues against the hypothesis of difficulty in tissue permeation in cases or subclinical inflammation in controls (Supplementary Table S15). Interestingly, cytokines observed to be lower in cases have intestinal homeostatic properties by regulating the microbiota and the intestinal barrier (Supplementary Table S16).

Figure 4.

Mean absolute cytokine concentrations by sample group. Blue, controls (rectum); green, cases (sigmoid); and red, cases (rectum). A, Chemokine panel. B, Cytokine panel. C, Proinflammatory panel. For scaling purposes, all concentrations are pg/mL except TARC, IL7, IL12/IL23p40, and IL17α (× 10 pg/mL; A); IL16 (× 10 ng/mL); and IL8, VEGFα, IFNγ, IL1β, and IL2 (× 0.1 ng/mL; B); and IL8 and IL13 (× 0.01 pg/mL; C; *, P ≤ 0.05).

Figure 4.

Mean absolute cytokine concentrations by sample group. Blue, controls (rectum); green, cases (sigmoid); and red, cases (rectum). A, Chemokine panel. B, Cytokine panel. C, Proinflammatory panel. For scaling purposes, all concentrations are pg/mL except TARC, IL7, IL12/IL23p40, and IL17α (× 10 pg/mL; A); IL16 (× 10 ng/mL); and IL8, VEGFα, IFNγ, IL1β, and IL2 (× 0.1 ng/mL; B); and IL8 and IL13 (× 0.01 pg/mL; C; *, P ≤ 0.05).

Close modal

We then examined correlations between the microbiome of the anterior rectal mucosa and cytokine concentrations. Rectal Roseburia and Propionibacterium, which are SCFA producers, and Streptococcus, an acetate producer, were inversely correlated with IL15 (decreased in patients with radiation enteropathy) in our dataset (rho = −0.54 and −0.52; P = 0.04 and 0.05, respectively; Fig. 5; ref. 30). Flavonifractor, a butyrate-producing genus, correlated positively with eotaxin (increased in patients with radiation enteropathy; ref. 31). These observations suggests an association between mucosal SCFA producers and radiation enteropathy in the anterior rectal mucosa, which is the gastrointestinal location receiving the highest levels of radiation in prostate radiotherapy. We observed similar correlations, albeit not so evidently, with sigmoid and stool microbiota.

Figure 5.

Correlation matrices of microbiome of stools (A), rectal mucosa (B), and sigmoid mucosa (C) and concentrations of cytokines. The size of circles represents significance and the color code represents Spearman correlation coefficient (rho). Only significant results (P ≤ 0.05) are shown. Stools and rectal mucosa microbiomes were correlated with rectal cytokine levels, whereas sigmoid microbiome was correlated with sigmoid cytokine levels. Class is defined as either cases (coded 0) or controls (coded 1) and therefore a positive correlation denotes higher concentration/proportion in controls and vice versa.

Figure 5.

Correlation matrices of microbiome of stools (A), rectal mucosa (B), and sigmoid mucosa (C) and concentrations of cytokines. The size of circles represents significance and the color code represents Spearman correlation coefficient (rho). Only significant results (P ≤ 0.05) are shown. Stools and rectal mucosa microbiomes were correlated with rectal cytokine levels, whereas sigmoid microbiome was correlated with sigmoid cytokine levels. Class is defined as either cases (coded 0) or controls (coded 1) and therefore a positive correlation denotes higher concentration/proportion in controls and vice versa.

Close modal

In this study, we have shown that a modified microbiota is associated with radiation enteropathy and that key homeostatic intestinal mucosa cytokines related to microbiota regulation and intestinal wall maintenance are also significantly reduced in patients with radiation enteropathy. Our study confirms previous observations in small cohorts of patients where acute radiation injury was associated with an altered microbiota (6, 20, 21, 23, 25). However, our data are not compromised by the delivery of concurrent cytotoxic systemic treatments, which made the findings from these smaller studies difficult to interpret. In addition, we have shown for the first time that a modified microbiota is associated with late radiation enteropathy.

We previously reviewed the potential of the microbiota in the prediction and treatment of radiation enteropathy (1). Although the importance of the gastrointestinal microbiota in radiation-induced intestinal toxicity is highlighted by the recognition of causes of enteropathy such as small intestinal bacterial overgrowth, the studies evaluating the microbiome in patients with radiation-induced gastrointestinal symptoms are limited by low patient numbers. Also, all previous authors focused only on acute radiation enteropathy. Although bacteriotherapy has been studied by administering probiotics or prebiotics, interventions were marred by insufficient knowledge of the microbiota in radiation enteropathy, which is reflected in modest and often conflicting results. Also, although preclinical studies provide useful information, they do not reflect the clinical reality of radiation enteropathy in the modern era of precision radiotherapy. We thus intended to provide a comprehensive characterization of the microbiota in radiation enteropathy, which provides a foundation for further studies in this field.

We acknowledge the limitations of our study. Radiation enteropathy has multiple causes, which are likely to have differential contributions from the microbiota (2). As yet, no objective markers of radiation enteropathy have been defined and there is no option but to rely on abnormal symptoms. However, symptom scales have limitations for detecting radiation enteropathy, hence our approach of using both CRO and PRO for better characterization of patients. Also, although our patients had comorbidities, as expected in the aged population of patients with prostate cancer, they were globally well distributed between symptom groups. We nevertheless adjusted for their effect where significant differences in comorbidities could have an impact, and our results were robust to these analyses. The relatively younger age of patients in the early compared with the late cohort reflects that patients undergoing treatment are younger than patients on long-term follow-up. However, this is unlikely to significantly affect the microbiota, given its overall stability with time (1). Moreover, we did not directly compare these cohorts, which were used to analyze different phases of radiation enteropathy as per our study design (32). We also acknowledge that, although we detected consistent results across all cohorts, high intersubject variability of the microbiota is known to affect cohort studies and is the main conundrum bedeviling all microbiota research in humans (33). Unfortunately, studies in animals are limited by administration of extreme (often lethal) radiation doses and very different radioresistance and microbiota when compared with humans. Although findings may appear more clear-cut, such models poorly represent clinical radiotherapy (5, 23). Furthermore, we acknowledge the limitation of not measuring diet longitudinally in the acute cohort, which was due to ethical concerns of study procedure–related patient exhaustion. We did not find, however, biologically relevant dietary differences between any of the cohorts. Also, although radiation-induced gastrointestinal side-effects remain the main dose-limiting factor in modern prostate cancer radiotherapy, their severity has been much reduced by successful improvements in treatment delivery. Limitations of metataxonomics are also acknowledged, such as PCR bias and artificial over-representation of some species carrying multiple copies of 16S rRNA genes (34).

We observed associations of microbiota endpoints with acute (mostly with PRO) and late (mostly with CRO) toxicity. Using both types of instruments is known to provide a full representation of toxicity and is the reason why radiotherapy trialists now report both separately (35). We hypothesize that this discrepancy is due to three factors: (i) differences in perception of side-effects from the point of view of patients and clinicians; (ii) limitations of both PRO and CRO instruments; and (iii) the overall low grade of toxicity produced by modern radiotherapy. In the acute setting, where patients are naïve to radiotherapy, their perception of symptoms may be higher and therefore PROs may be more sensitive. In the late setting, both successful ongoing treatment of toxicity and increased patient tolerance to side-effects may make CROs more sensitive. For example, a patient successfully using loperamide for diarrhea may not report symptoms, but clinicians would classify such a patient as having diarrhea. Furthermore, we acknowledge limitations in using PRO instruments. PROs in the acute cohort were analyzed as difference to baseline, and will thus reflect better each patient's longitudinal evolution in terms of symptoms (36). However, patients were assigned to groups of increasing late patient–reported toxicity (late and cohort) based on dividing them in four quartiles, as there are is no “normal threshold” in our validated PRO score. Given the small range in PRO scores in the late cohort (described in Supplementary Materials and Methods), patients with different toxicity phenotypes may have been grouped together therefore making results more difficult to interpret. Despite these limitations and in the absence of a reliable biomarker of radiation enteropathy, our approach provides the most comprehensive clinical characterization of radiation enteropathy ever carried out in a study in this field.

Decreased bacterial diversity was consistently associated with radiation enteropathy in all three cohorts, and we conclude that this observation is not random, although results in two of our cohorts were nonsignificant. A less diverse microbiota associates with other forms of colitis, including IBD, IBS, and infective colitis, as well as with diseases such as obesity and autoimmune diseases (37, 38). Associations between acute radiation enteropathy and reduced diversity have also been reported by other authors (6, 20–23). In animal models, a less diverse irradiated microbiota (which is enriched in Sutterella among other bacteria) is sufficient for the induction of higher susceptibility to intestinal inflammation, suggesting that reduced bacterial diversity may cause patients to be at risk of enteropathy in the short and long terms (23). It is noteworthy that Sutterella was higher in patients with radiation enteropathy in the early cohort, albeit nonsignificantly (23). Our results suggest that strategies for increasing bacterial diversity in patients at risk could be trialed to see whether they modify the course of radiation enteropathy.

We found significant associations between some organisms producing SCFA and radiation enteropathy in all cohorts, again suggesting that this association is nonrandom. Imbalances in the microbiota, often termed dysbiosis, associate with many gastrointestinal diseases, including IBD, IBS, and viral colitis. Generally, such imbalances are characterized by an increase in bacteria, which are recognized to be pathogens, such as Escherichia coli, or the Shigella and Klebsiella genera (1). However, SCFA producers promote intestinal homeostasis and their depletion has been associated with IBD, so increased proportions in patients with symptoms are surprising (39). Mechanistic exploration is beyond the scope of our study, but some hypotheses can be suggested. These bacteria are part of intestinal mucosa–associated communities and it is possible that, in patients at risk of symptoms, increased competition by potentially pathogenic bacteria leads to increased shedding in the stools. This shedding would be consistent with differential dynamics observed between groups. An alternative hypothesis would be that chronic, subclinical preradiotherapy intestinal dysfunction may lead to a dependence on microbiota-derived nutrients for epithelial health (2). Radiotherapy led to decreased SCFA production capacity, associating with symptom onset. The high counts of Roseburia associating with CRO-stratified but not PRO-stratified late symptoms support that higher proportions of these bacteria relate to decreased symptom perception by patients in the presence of clinician-perceived disease. This hypothesis is consistent with the limited clinical effectiveness of oral or topical butyrate when treating radiation enteropathy (40). Although we acknowledge the low comparative proportions of these bacteria when compared with other SCFA producers such as Faecalibacterium, the trend of patients with radiation enteropathy having higher, but dynamically decreasing, SCFA production capacity (early cohort) and significantly decreased levels of homeostatic rectal mucosa cytokines involved in mucosal barrier maintenance and microbiota regulation (colonoscopy cohort) would support this assumption. These hypotheses need to be further explored.

Our study provides evidence of structural and functional shifts in the microbiota in patients with radiation enteropathy. However, whether these changes are a cause or consequence of intestinal symptoms is a matter of considerable debate even in well researched fields of noninfectious colitis such as IBD (41). Also, unlike IBD, radiation enteropathy is characterized by noninflammatory mechanisms, which is well illustrated by evidence of a recent placebo-controlled randomized trial where sulfasalazine, an anti-inflammatory drug often used to treat IBD, actually had a detrimental effect in terms of diarrhea for patients undergoing radiation enteropathy (42). We also did not find evidence of increased inflammatory cytokines in patients with late radiation enteropathy. Other authors have provided complementary mechanistic evidence, which suggests a causative role for the microbiota in radiation enteropathy (23). We provide a framework for further downstream studies assessing a causative role for the microbiota, which could provide further scope for microbial interventions such as fecal transplantation, which has recently been suggested as a successful treatment of immunotherapy-induced colitis (43). Other bacteriotherapy interventions, such as the administration of probiotics (live organisms that, when consumed in an adequate amount, confer a health effect on the host) or prebiotics (nondigestible foods that promote the growth or activity of specific microorganisms, promoting a health effect), have also been trialed in patients undergoing pelvic radiotherapy (1). The mixed results observed may stem from the fact that many of these therapies modulate bacteria, which do not have an impact in radiation enteropathy. However, Garcia-Peris and colleagues showed in a randomized trial that the delivery of a fiber mixture containing inulin, which promotes the growth of SCFA producers such as Roseburia, improves diarrhea in patients undergoing pelvic radiotherapy, supporting our observations (44, 45).

We conclude that radiotherapy may upset the balance of microbiota which supports intestinal health, by decreasing the influence of key microorganisms, probably more susceptible to radiation effects. The microbiota may be used to predict, prevent, or treat clinical radiation enteropathy and our study provides an evidence base for developing preclinical and clinical studies.

D.P. Dearnaley is listed as a co-inventor on a patent application regarding a plastic rectal obturator to improve accuracy and reduce the side effects of prostate radiotherapy that will be owned by The Institute of Cancer Research and Sussex Development; is a consultant/advisory board member for Takeda, Amgen, Astellas, Sandoz, Janssen, EMA, MsC Lecture Fees, EMUC Presentation Prize, Norway Oncology Society Meeting Honorarium, and Queens University Belfast; and reports receiving other remuneration from the Institute of Cancer Research. No potential conflicts of interest were disclosed by the other authors.

This article is independent research funded by the National Institute for Health Research (NIHR) Biomedical Research Centre, and the views expressed in this article are those of the authors and not necessarily those of the NHS, NIHR, or the Department of Health.

Conception and design: M. Reis Ferreira, H.J.N. Andreyev, J. Li, J. Marchesi, D.P. Dearnaley

Development of methodology: M. Reis Ferreira, H.J.N. Andreyev, S.M. Gowan, J. Marchesi, D.P. Dearnaley

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): M. Reis Ferreira, H.J.N. Andreyev, L. Truelove, S.M. Gowan, J. Marchesi, D.P. Dearnaley

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): M. Reis Ferreira, H.J.N. Andreyev, K. Mohammed, S.M. Gowan, J. Li, S.L. Gulliford, J. Marchesi, D.P. Dearnaley

Writing, review, and/or revision of the manuscript: M. Reis Ferreira, H.J.N. Andreyev, K. Mohammed, L. Truelove, S.M. Gowan, J. Li, S.L. Gulliford, J. Marchesi, D.P. Dearnaley

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M. Reis Ferreira, K. Mohammed, L. Truelove

Study supervision: H.J.N. Andreyev, D.P. Dearnaley

Other (sample collection, day-to-day management, design of figures and tables): M. Reis Ferreira

We thank the patients and the trials unit staff at the Bob Champion Unit and RMH Trial Unit who contributed to the coordination of the study. We acknowledge support of Cancer Research UK awarded to D. Dearnaley (C8262/A7253, C1491/A9895, C1491/A15955, and SP2312/021), funding from the NIHR Cancer Research Network through the NIHR BRC at the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London awarded to D. Dearnaley and M. Reis Ferreira (A53/CCR4010), the Department of Health, the National Institute for Health Research (NIHR) Cancer Research Network, and NHS funding to the NIHR Biomedical Research Centre (BRC) at the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London. The Division of Integrative Systems Medicine and Digestive Disease at Imperial College London (to J. Marchesi) received financial support from the NIHR Imperial BRC based at Imperial College Healthcare NHS Trust and Imperial College London. M. Reis Ferreira acknowledges support from the Calouste Gulbenkian Foundation, the Fundação para a Ciência e a Tecnologia, and the Champalimaud Foundation (SFRH/BDINTD/51547/2011). J. Li acknowledges Medical Research Council and European Research Commission starting grants for salary support.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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