Exercise Training Reduces the Inflammatory Response and Promotes Intestinal Mucosa-Associated Immunity in Lynch Syndrome

This article is featured in Selected Articles from This Issue, p. 4315

Lynch syndrome (LS) is the most common hereditary cancer syndrome, potentially affecting 1.1 million individuals in the United States (1). LS carriers have up to 60% lifetime risk of colorectal cancer (2). Exercise is one potential non-pharmacologic strategy to mitigate excessive colorectal cancer risk in patients with LS. In fact, exercise is associated with reduction in colorectal cancer among the general population (3) with evidence to suggest a robust risk reduction, increased functional capacity and quality of life among individuals who sustain moderate to high levels of activity over time compared with those remaining inactive (4, 5). A similar beneficial association between exercise and colorectal cancer risk has been suggested in patients with LS in retrospective studies showing that physical activity of ≥35 MET-h/week decreased the risk of colorectal cancer (6, 7). However, despite the biological plausibility between exercise and reduction in colorectal cancer risk being robust, the mechanism underlying this association remains unclear with studies showing modulatory effects on the gut microbiome (8, 9), insulin growth factor signaling, and other essential pathways in colorectal cancer development to promote antitumorigenic activity (10, 11).

Overall, exercise alters inflammatory, immune, and insulin growth factor pathways implicated in colorectal cancer development (12–15). In particular, exercise removes excess energy substrate availability, which drives down the formation of reactive oxygen species and subsequent signaling pathways that affect cell-cycle control and survival (16–18). Exercise is also hypothesized to impact prostaglandin (PG)-mediated inflammation, an essential pathway in the development of colorectal cancer (19). We and others have shown that cancer interception strategies such as aspirin and naproxen can successfully inhibit PG synthesis via blockage of cyclooxygenase (COX) enzymes to prevent colon tumorigenesis in LS (20, 21). To date, however, exercise studies on PG synthesis have rendered mixed results at the tissue level. One previous study demonstrated an inverse correlation between self-reported exercise and prostaglandin E2 (PGE2) levels in rectal tissue in patients with a history of polyps (19). In contrast, a randomized clinical trial of healthy adults failed to show an association between exercise training with a change in colonic PGE2 levels (22). Therefore, it remains unclear whether exercise modulates PG levels via COX enzymes and/or other potential pathways implicated in colorectal cancer development through induction of transcriptomic and metabolomic changes. More specifically, the role of exercise to biologically modulate mismatch repair (MMR)-deficient carcinogenesis in the intestinal epithelium to prevent colorectal cancer in LS carriers is unknown.

As such, we sought to (1) directly test the hypothesis that exercise using a sustained aerobic cycling intervention alters gene expression patterns and circulating factors in the colorectal mucosa and circulating PG levels over a 12-month period, and (2) to assess the feasibility of such an intervention in LS carriers as measured by recruitment, retention, and adherence rates. Here, we report the results of ‘the CYCLE-P study’ that enrolled LS participants, who were in an active cancer surveillance program at The University of Texas MD Anderson Cancer Center (MDACC) into a 12-month aerobic exercise intervention or usual care.

CYCLE-P was a prospective, non-randomized, sequential assignation to intervention, single-site controlled trial that enrolled 21 participants diagnosed with LS in a 12-month aerobic exercise intervention involving cycling classes in a local community (n = 11) followed by enrollment to usual care (n = 10, control group) between April 2018 to January 2019 (Supplementary Fig. S1). Eligible participants were approached prior to their scheduled colonoscopy and all of them provided written informed consent before enrollment. The conduct of the trial complied with the Declaration of Helsinki. Participants were told their allocation when approached for the study and each group signed a different informed consent. The trial protocol and all amendments were approved by the MDACC institutional review board. We followed the Transparent Reporting of Evaluations with Nonrandomized Designs reporting guidelines (23). All authors had access to the study data and reviewed and approved the final manuscript.

Participants were adults between 18 and 50 years of age with LS defined as carriers or obligate carriers by the pedigree of a pathogenic mutation in one of the four DNA MMR genes (i.e., MLH1, MSH2/EPCAM, MSH6, or PMS2) or as participants with a personal history of a non-sporadic MMR-deficient neoplasia defined by IHC or microsatellite instability testing or both. Participants did not have evidence of active or recurrent malignant disease or cancer-directed treatment in the previous 6 months. Only participants willing to undergo yearly screening colonoscopy were eligible. Participants were required to retain a portion of the distal colon or rectosigmoid intact to enable collection of normal mucosa biopsies. Exclusion criteria included previous total proctocolectomy, history of cardiovascular disease, or uncontrolled medical conditions. A lower age cut-off of 18 years was prespecified given standard of care surveillance endoscopy is not performed routinely in patients with LS under 18 years of age. An upper age limit of 50 years was prespecified to recruit healthy patients with LS without co-morbidities who were more likely to achieve the prescribed exercise volume and intensity [≥70% peak heart rate (PHR)] over 52 weeks.

Figure 1 shows the flow and timeline of clinical assessments, interventions, and follow-up testing. Both the intervention group and the usual care group underwent standard of care lower gastrointestinal (GI) endoscopy with biopsies and blood collection at visit 1. Cardiopulmonary exercise testing (CPET) was performed at visit 2 within 30 days of endoscopy. Visit 3 was performed at the 1-year endoscopy for both the intervention and usual care groups, followed by a CPET at visit 4 within 30 days of the 1-year endoscopy. A baseline health questionnaire was used to assess the regular use of aspirin (defined as ≥ 3 times per week) with no participants taking aspirin. Intermittent use of NSAIDs was not recorded throughout the trial.

Participants were asked to enroll in subsidized cycling classes for 45 minutes 3 times weekly for 12 months through stand-alone businesses, structured gyms (i.e., YMCA), and one participant through a Peloton bike (Supplementary Fig. S1–S2). There was no ramp-up period for physical activity during the initial weeks. However, a 2-week run-in period was allowed to identify and schedule cycling classes, and during this time participants were contacted by an exercise physiologist to discuss barriers or difficulties finding exercise classes. Afterwards, participants were contacted every two weeks to track and encourage compliance throughout the study. Exercise data including exercise minutes, sleep time, and training heart rate was tracked on an electronic wearable device (Fitbit) by retrieving the data from FITABASE over the study period, and intensity was determined by taking a percentage of an individual's PHR determined during the visit 2 CPET. We have not specifically monitored if any group has been involved in other physical activity outside the study intervention. Exercise minutes ≥70% of an individual's PHR continuously for ≥10 minutes were considered valid and counted. In addition, we tracked the average weekly wear of the Fitbit, and assessed total minutes of exercise at 70% to 85% heart peak rate, and at >85% heart peak rate. A bimonthly response to an exercise questionnaire on class attendance and weekly surveillance of valid exercise minutes and electronic wearable device compliance was overseen by an exercise physiologist.

Participants in the usual care group did not enroll in cycling classes but were counseled on current exercise guideline recommendations by an exercise physiologist at study visit 2. This group was monitored for exercise via electronic wearable devices under the same principles as the intervention group. Incentives were provided to both groups. Participants in the cycling intervention attending cycling classes received $50 at the end of each month for a total of 12 months to cover the cost of the classes. Both groups were given a $100 payment for completing visit 2 and $300 for completing visit 4.

Peak oxygen consumption (VO_2peak) was assessed by a symptom-limited CPET on a bicycle with a 12-lead electrocardiogram using the Cosmed Quark metabolic testing system with a standardized protocol for an exercise laboratory, as previously described (24). Feasibility was evaluated by recruitment in terms of eligibility and consent, adherence, and retention rates. The recruitment rate was defined as the proportion of eligible patients who consented out of the total number of patients contacted by the study team. A participant was deemed adherent in a given week if they performed all 3 cycle sessions that week. Adherence was assessed through self-reported email questionnaires. The adherence rate was then calculated as the percent of weeks (of 52) that a participant was adherent. Retention was calculated as the percent of participants in each group who completed CPET at visit 4. This study was considered feasible per protocol if the recruitment rate was at least 20%, along with at least 75% rates for both adherence and retention.

Standard of care lower GI endoscopy (flexible sigmoidoscopy or colonoscopy depending on the length of the participants’ colon) was performed in all participants. Biopsies were taken from grossly normal rectosigmoid mucosa using jumbo biopsy forceps. Tissue specimens were then processed immediately in formaldehyde for histology, RNAlater for nucleic acid extraction, and flash-frozen in liquid nitrogen for proteomic analysis and storage.

Detailed information on mRNA sequencing (mRNA-seq) and bioinformatics analysis, measurement of PGs, metabolomic studies, GeoMx Digital Spatial Profiling (DSP) and IHC are provided in Supplementary Methods.

Descriptive statistics were used to summarize demographics, health history, and study assessments. Categorical variables were summarized with counts and percentages, and Fisher exact test was used to test for associations between these characteristics and the study group. Continuous variables were summarized with median and interquartile range (IQR) and compared between groups using the Wilcoxon rank-sum test. A one-sample paired t test determined significance of the mean percent change in relative VO_2peak from baseline to 12 months being different from 0 with a 95% confidence interval (CI) for each study group. Statistical significance was determined using a significance level of 0.05. All statistical analyses were performed using SAS 9.4 for Windows (SAS Institute Inc., Cary, NC) and RStudio 1.1.463 (© 2009–2018 RStudio, Inc., Boston, MA). Statistical parameters for the metabolomic and mRNA-seq studies and the mixed-effect model are included in the Supplementary Methods.

The data generated in this study can be accessed at GSE183150 for mRNA data and at GSE210011 for DSP data. To uphold patient privacy and consent, individual participant data will not be shared.

Sixty potential participants were approached and invited to enroll in the study during their regular cancer screening visits at MDACC. Twenty-one participants signed informed consent, enrolled in the study, and were allocated to the exercise group (n = 11) or usual care group (n = 10; Fig. 1A). Participant's ages differed between the exercise group (46 years, IQR 40- 48) and a usual care group (35.5 years, IQR 34–38). Otherwise, baseline characteristics and CPET results between groups were similar in terms of sex, body mass index (BMI), and baseline VO_2peak (Table 1). No participants had a history of diabetes, hypertension, or were taking NSAIDs such as aspirin or steroids. One patient in the usual care group was receiving treatment with a statin.

The overall recruitment rate to CYCLE-P was 35% (21/60). Adherence to the exercise intervention was self-reported through questionnaires administered via email. The mean adherence rate in the exercise group was 51.3% (range, 11.5%–73.1%). Nine of 10 participants in the exercise group completed CPET at Visit 4, yielding a retention rate of 81.2% (9/11), while 7 participants in the usual care group completed CPET at Visit 4, yielding a retention rate of 70.0% (7/10).

The number of participants with adverse events (AE) of any grade was 5/11 in the exercise group and 2/10 in the usual care group. AEs were graded according to the NCI Common Terminology Criteria for Adverse Events v.4.0. This difference was not statistically significant (P = 0.36). In the Exercise group, there were one grade 2 AE and four grade 1 AEs. In the usual care group, there were three grade 2 AEs. Thus, a total of eight AEs were reported. Grade 2 was the highest grade among all AEs observed. There was no difference in the AE rate by grade between the exercise and usual care groups (P = 0.43; Supplementary Tables S1–S3).

The median total weekly exercise minutes at a heart rate ≥70% over a 52-week period was 164 minutes (IQR, 88–265) in the exercise group and 14 minutes (IQR, 1–57) in the usual care group (Fig. 1B), respectively. There was no statistically significant difference between the exercise and the usual care group in terms of the number of days that participants used the Fitbit and their baseline HR. However, exercise participants had a significantly higher number of minutes with a heart rate of ≥70% of their PHR (Supplementary Fig. S3A–S3C). Compared with baseline, there was a 21.6% increase in mean relative VO_2peak (+ 5.7 mL · kg⁻¹ · min⁻¹, P = 0.0056) in the exercise group as opposed to a 2.0% decrease (−0.47 mL · kg⁻¹ · min⁻¹, P = 0.44) in the usual care group, which rendered a significant difference when the exercise group was compared with the usual care group (21.6% increase vs. 2.0% decrease, P = 0.008 in t test; Fig. 1C; and P = 0.0029 in the mixed effect model as described in Supplementary Methods). In parallel, the exercise group had significantly decreased PGE2 levels in the colonic tissue relative to baseline when compared with the usual care group (P < 0.05 in t test; Fig. 1D; P = 0.03 in the mixed effect model). However, no significant differences between the exercise and usual care groups were observed in the levels of intermediate PG metabolites, including tetranor PGE1, 15-keto PGE2, and 13–14-Dihydro-15-Keto-PGE2, in colonic tissue (Supplementary Figures S4A and S4C).

Untargeted metabolomic analyses were performed to assess the effect of the cycling intervention on the serum metabolome. A total of 740 uniquely annotated metabolites were quantified. Differential analyses identified 29 metabolites that were statistically significantly altered following intervention in the exercise group but not in the usual care group (P < 0.05 in t test and in the mixed effect model): 7 were increased following exercise, whereas 22 were decreased (Supplementary Table S4). Among the 22 metabolites decreased after exercise were PGE2 and 12-Hydroxyheptadecatrienoic acid [12(s)-HHTrE], a primary metabolite of arachidonic acid metabolism via thromboxane synthase (Fig. 2A–C). Moreover, there was a reduction in several circulating triacylglycerols (TG; n = 12), particularly those containing highly unsaturated long-chain fatty acids on the acyl groups that are key regulators in the production of COX2-mediated PGE2 (Fig. 2D).

Transcriptomic analysis by mRNA-seq showed statistically significant changes in gene expression in colorectal normal mucosa between the exercise and usual care groups. Among differentially expressed genes (DEG) in the exercise group, 13 genes were upregulated, and 33 genes were downregulated (up to 10-fold) when compared with the usual care group (Fig. 3A and B; Supplementary Table S5). The top DEGs were C5orf17 (LINC02899), ABCG8 (ATP Binding Cassette Subfamily G Member 8), B4GALNT2 (Beta-1,4-N-Acetyl-Galactosaminyltransferase 2), and KCNV1 (Potassium Voltage-Gated Channel Modifier Subfamily V Member 1), while the downregulated genes were TMPRSS6 (Transmembrane Serine Protease 6), PRAC1/2 (Small nuclear protein PRAC1/2), and HOXB13 (Homeobox B13), and those genes are indicated as bold (Fig. 3A). Further, pathway enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and gene ontology biological process databases revealed that the top activated pathways in the exercise group were related to the immune system (Th17, Th1-Th2 cell differentiation, and Toll-like signaling) and others related to growth, survival, proliferation, and differentiation signals such as Rap1 (Ras-related protein 1), VEGF, and EGFR, as well as key cellular processes of DNA replication and cell-cycle control (Fig. 3C; Supplementary Table S6). The top suppressed pathways were related to the ribosome, cardiac muscle contraction, oxidative phosphorylation, and synaptic vesicle cycle. In addition, gene set enrichment analysis (GSEA) showed engagement of the IL6 pathway in the exercise group (P = 0.055; Supplementary Fig. S5A) using two independent transcriptome data sets generated in vitro for IL6 stimulation (25) and deprivation (26) showing positive enrichment scores (P = 2.9×10⁻⁵ and P = 8.9×10⁻⁸; respectively; Supplementary Fig. S5B and S5C).

Overall, metabolic and transcriptomic analysis consistently showed a reduction of PGE2 levels and activation of immune-related pathways in the exercise group. Therefore, we performed in silico deconvolution of immune cell types in the colorectal mucosa using CIBERSORT. Overall, the CIBERSORT analysis using stringent criteria showed no significant changes in proportions of different immune cell types present in the colorectal mucosa between the exercise and usual care groups [Benjamini–Hochberg (BH)-Adjusted P < 0.05]; however, it was notable for the enrichment of CD8⁺ T cells with a non-statistically significant trend (Supplementary Fig. S6; Supplementary Table S7). Because VO_2peak represents overall exercise capacity and was higher in the exercise group (Fig. 1C), we also analyzed the correlation between the change in VO_2peak after 12 months and the change in other clinical outcomes and immune cell subtypes using scatter plot (Fig. 3D and E) and the Pearson correlation coefficient matrix (BH-Adjusted P < 0.1; Supplementary Fig. S7). These analyses revealed that changes of relative VO_2peak had a positive statistically significant correlation with levels of activated natural killer (NK) cells (R = 0.58; BH-Adjusted P = 0.039; Fig. 3D). NK cells play essential roles in innate immunity towards cancer, with the ability to kill circulating cancer cells (27). In parallel, consistent with the known role of PGE2 as a regulator of an adaptive immune response, we observed that changes in PGE2 (reduction in levels) were negatively correlated with changes of CD8⁺ T cells (R = −0.66; BH-Adjusted P = 0.01; Fig. 3E), thus suggesting that cycling exercise promoted the activation and recruitment of cytotoxic T cells in colorectal mucosa, which is one of the most critical components of adaptive anticancer immunity (28, 29).

To confirm the change of the immune response pathways in trial participants, we performed spatial transcriptomics using the NanoString GeoMx Digital Spatial Profiler (DSP). A total of 16 formalin-fixed, paraffin-embedded (FFPE) samples of normal mucosa from 8 participants were available for this analysis (3 participants in the usual care and 5 in the exercise group; Fig. 4A). We focused the analysis in areas enriched by colonic crypts and assessed differences between the usual care and exercise group observing downregulation of metallothionein genes (MT1A, MT1E, MT1F, MT1G, MT1M, MT1X, and MT2A), and several small and large subunit ribosomal proteins in the exercise group compared with the usual care group (Fig. 4B; Supplementary Fig. S8A). Expression levels of cancer stem cell markers CD24 and TSPAN8, and oncogenes EIF3E, BTF3, ST14, and HMGCS also decreased in the exercise group. GSEA from DSP data revealed in the exercise group suppression of fat and carbohydrate metabolism, androgen and estrogen response, along with several oncogenic pathways including MYC, MTORC1, and TGFβ and activation of KRAS signaling downregulation, IFNγ, and inflammatory responses (Supplementary Fig. S8B). Immune cell deconvolution from DSP expression data confirmed that the exercise group had significantly increased numbers of activated NK cells compared with the usual care group (P = 0.036) and increase of CD8⁺ T cells (Fig. 4C). Then, we performed analysis of the frequency of CD8⁺ T and CD57+ NK cells in residual FFPE tissue sections of colonic mucosa of 4 participants in the exercise and 4 in the usual care group using IHC. We confirmed a significant increase of the total number of CD8⁺ T cells in the exercise group (Supplementary Fig. S8C, left) due to the stromal CD8⁺ T-cell population (Fig. 4D, left) with an increasing trend in the epithelial CD8⁺ T cells (Supplementary Fig. S8C, right). A marginal increase in total number of CD57⁺ NK cells, mainly due to the stromal population, was observed in the exercise group (Fig. 4D, right and Supplementary Fig. S8D). These findings suggest that levels of CTLs are promoted in colonic mucosa by aerobic exercise with concomitant suppression of oncogenic pathways particularly TGFβ signaling which plays a negative regulator of immune cells. In summary, our working model derived from the CYCLE-P study demonstrates that LS participants undergoing exercise through cycling for one year increase cardiorespiratory fitness (VO_2peak) and decrease pro-inflammatory and metabolic regulators, most notably, circulating PGE2 and TGs and end-organ colonic PGE2. These molecules converge promoting activation of the immune system in the large intestine by increasing cytotoxic CD8⁺ T and CD57⁺ NK cells. Increased VO_2peak upon aerobic exercise has been linked to the production of different myokines and cytokines serving as immune modulators (Fig. 4E). Taken together, these pathways triggered by exercise may elicit adaptive antitumor immunity in LS carriers, thus eliciting cancer prevention.

The results of this proof-of-concept and small trial showed that 12 months of sustained aerobic exercise increased absolute VO_2peak in LS carriers. Additionally, biomarker studies performed in the normal mucosa and plasma of patients with LS showed that exercise modulates inflammation via the reduction of PGE2 and it has a role in the modulation of the activity of the immune system with increased activation of NK and CD8⁺ T cells. Overall, our data highlight the role and potential of aerobic exercise as a non-pharmacologic preventive intervention in LS population.

In the study, we achieved a recruitment rate of 35%, which exceeded our prespecified target and was within the range of other exercise clinical trials. The retention rates of 81.2% (9/11) and 70% (7/10) for the exercise and usual groups, respectively, over the 12-month study, were also in line with our expectations of 75%. On the basis of the wearable device information, the intervention group achieved, on average, a PHR of ≥70% during exercise for a significantly greater amount of time (164 min/wk) than the usual care group (14 min/wk) over the 52-week study period. Thus, we conclude that it is feasible to recruit and retain LS participants to a cycling intervention. However, adjustments to measure and promote adherence throughout the study period are warranted for future studies.

Two prior studies have assessed the relationship between exercise and PGE2 levels in colorectal tissue. Martinez and colleagues assessed the PGE2 levels in the rectal mucosa of 63 participants with a prior history of polyps and found an inverse association between self-reported exercise (MET-hr-wk) and PGE2 levels (−0.28, P < 0.05) and 28% lower PGE2 levels among those with a reported 22 MET-hr-wk difference in activity (19). Limitations included self-reporting of exercise and the cross-sectional nature of the study design. In a second study, Campbell and colleagues performed a 12-month exercise intervention (combination of supervised and home-based aerobic exercise) in 187 men and women 40 to 75 years of age, reporting a mean 370 minutes a week of exercise in men and 295 minutes a week in women over the study period based on study logs (30). VO_2max increased by 2.5 mL · kg⁻¹ · min⁻¹ (10%) in women and 3.3 mL · kg⁻¹ · min⁻¹ (11%) in men in the exercise group and decreased in the usual care group. Of the 187 participants, 89 had follow-up biopsies and subsequent measurement of colonic PGE2 levels, demonstrating no differences in either men (P = 0.74) or women (P = 0.99; ref. 22). Differences in PGE2 levels by VO_2peak change were not reported. A combination of factors may explain the discordant findings from these studies and our results. First, the technological advances in PGE2 measurement and the ascertainment of two colonic biopsies for each participant in our CYCLE-P study might likely improve sensitivity for PGE2 detection. Second, it is possible that a more robust change in VO_2peak (4.6 mL · kg⁻¹ · min⁻¹) over 12 months in our trial allowed for a greater intervention effect to detect a difference in PGE2. Of note, we tracked minutes of exercise based on participants meeting a threshold heart rate greater than 70% of PHR (not below this threshold), while Campbell and colleagues asked participants to reach 60% to 80% of PHR but reported only overall minutes, not intensity. Therefore, an absolute “exercise dose” difference between the trials cannot be established. Third, we studied a high-risk genetic cohort of LS participants, and Martinez and colleagues recruited participants with a history of polyps, while Campbell and colleagues enrolled participants with no known high-risk features. This poses the question of whether individuals “at-risk” for colorectal cancer are more susceptible to the effects of exercise on colonic tissue. This question will require additional experimental studies applying similar methods across different risk cohorts.

Our findings are biologically plausible, showing an effect of exercise on the COX pathway, consistent with modulation of serum levels of TGs with sustained aerobic exercise. Endogenous TGs are the largest energy source of the body. Fatty acid oxidation is the preferred substrate utilized during sustained bouts of exercise to delay the onset of skeletal muscle glycogen depletion. Our results, supported by prior work (31), showed a decrease in TGs in the resting state among the exercise participants, not observed in the usual care group. Furthermore, we found that long-chain highly unsaturated TGs such as arachidonate along with downstream metabolites, PGE2 and 12 (s) – HHTrE, were lower in the exercise group than in the usual care group. To date, there have been few studies assessing change in the circulating metabolome following chronic exercise utilizing current day metabolomics platforms. Brennen and colleagues found no change in 147 metabolites profiled by liquid chromatography/tandem mass spectrometry among 216 middle-aged abdominally obese men and women following a 24-week exercise intervention (32). In a second study by Koay and colleagues, 52 healthy, normal weight soldiers underwent an 80-day intervention incorporating ∼ 8 MET-hrs per day of exercise, resulting in a 5.34 mL · kg⁻¹ · min⁻¹ in VO_2peak following the training period. Metabolomics analysis demonstrated a 1.39-fold decrease in arachidonate (P = 6.6×10⁻⁸; ref. 33). Both our study and Koay and colleagues performed a within-group analysis to reduce the interindividual variability of group comparisons, demonstrated a robust effect size change in VO_2peak and performed an unbiased assessment of a full range of circulating metabolites. Differences include that our study had a control group (demonstrating no change in arachidonate), and that we delivered an aerobic intervention at a lower exercise dose over a longer time period than Koay and colleagues.

Our transcriptomic data further support the above findings that altered expression of PRAC1/2, ABCG8, B4GALNT2, and HOXB13 affect the modulation of inflammation, immune cell types resident in the mucosa, and cholesterol levels in the LS colorectal environment with sustained aerobic exercise. ABCG8 acts as a regulator of sterols removal (34, 35), B4GALNT2 reduces inflammation in skeletal muscle and regulates the gut microbiome (36, 37), PRAC1/2 genes are expressed in the epithelium of inflamed colon in ulcerative colitis (38), and HOXB13 expression has been reported to correlate with hepatic inflammation and fibrosis (39). In addition, we observed activation of IL6 signaling in the exercise group. IL6 is an important regulator with diverse roles in exercise, PG metabolism, and antitumor immunity through activation of NK, CD8a T cells and other effector T cells (40–43). In fact, PGE2 upregulates the secretion of muscle-derived IL6 into circulation during exercise (44–47). These antitumor functions mainly happen outside the tumor microenvironment. In fact, although the activation of the IL6 pathway was strong, we did not observe overexpression of IL6 mRNA transcripts in the mucosa, thus suggesting that the mechanism of activation may be derived from endocrine secretion by cells outside any tumor microenvironment, such as muscle cells stimulated by exercise rather than colorectal epithelial cells. The main finding among participants in the exercise group was the activation and increased levels of CD8⁺ T and CD57⁺ NK cells in the colonic mucosa, though observed nonsignificant increase initially in the immune cell type deconvolution results of total RNA transcriptomic data, but verified independently using a reliable and sensitive approach of NanoString DSP and then by IHC analysis. Furthermore, spatial transcriptomic profiling of the colonic crypts revealed the downregulation of KRAS signaling and activation of immune cell regulatory pathways including inflammatory and IFNγ responses. KRAS signaling is commonly dysfunctional in colon cancer (48). Taken together, we postulate that exercise might be considered as a potential KRAS-targeting cancer treatment and an immune modulator for increased adaptive immune response and a potential KRAS targeting cancer intervention. The added value is that our exercise intervention was very reasonable and so were the cardiorespiratory measurements achieved to the point that it can be considered an exercise prescription for patients with LS seeking to boost immunity and obtain specific pathway-centered anticancer effects.

Limitations to our study include the small sample size without race heterogeneity, and the non-randomized nature of the design. In addition, our validation studies using DSP and IHC may not allow to generalize our results due to interindividual differences among the participants of the exercise group with a relative small sample size. Participants knew their allocation before signing informed consent, which might have impacted their willingness to participate in the trial. In addition, differences in timing of collection of the specimens and storage in the freezer could have driven differences in metabolite levels. Importantly, the study groups were remarkably similar other than age. The exercise group had older participants, which would result in a bias towards a type II error or a false negative result, the opposite of what we have observed. It is important to note that our inclusion criteria were intentionally geared to recruit healthy patients with LS, who could attain high levels of exercise, and to exclude individuals with hypertension, diabetes, cardiovascular disease, or inflammatory disorders. As such, we removed potential confounders to enhance the signal of the exercise intervention. Further, the role of gut microbiome, diet, and supplements taken by participants remain unexplored in this study. This could be critical as several studies have shown that levels of physical activity have differential effects on the intestinal microbiome that may involve in reduction of colorectal cancer risk (8, 49).

In conclusion, our study demonstrates for the first time that aerobic exercise is capable of modulating levels of inflammatory PGs in the colonic tissue and serum in a high-risk genetic cohort for cancer due to mismatch repair deficiency. The significant decrease in mucosal PGE2 levels correlated significantly with an increased activation or recruitment of specific immune cell populations of NK and CD8⁺ T cells to the colonic mucosa. This may be related to increased immune surveillance in the colon and, therefore, linked to a benefit in colorectal cancer prevention through clearance of dysplastic cell populations that develop in a background of MMR deficiency. Future randomized clinical trials will be needed to confirm the preventive efficacy of aerobic exercise training in LS carriers and to further elucidate the possible immune-related pathways underlying any reductions in colorectal cancer risk.

Written informed consent was obtained from all study participants, and The University of Texas MD Anderson Cancer Center Institutional Review Board (IRB) approved this study (IRB #2017–1035).

M.F. Munsell reports grants from NIH during the conduct of the study. E.T. Hawk reports grants from NCI and Exact Sciences and other support from The University of Texas Boone Pickens Distinguished Chair for Early Prevention of Cancer during the conduct of the study; other support from AACR and grants from Cancer Prevention & Research Institute of Texas outside the submitted work. Y. Li reports other support from Angenus Inc. and Mink Therapeutics Inc. outside the submitted work. J.A. Wargo reports personal fees from Imedex, Dava Oncology, Omniprex, Illumina, Gilead, PeerView, Physician Education Resource, MedImmune, Exelixis, and Bristol-Myers Squibb outside the submitted work; has a patent for PCT/US17/53.717 pending; has served as a consultant/advisory board member for Roche/Genentech, Novartis, AstraZeneca, GlaxoSmithKline, Bristol-Myers Squibb, Micronoma, OSE therapeutics, Merck, and Everimmune; in addition, receives stock options from Micronoma and OSE therapeutics. P. Sharma reports other support from Achelois, Adaptive Biotechnologies, Affini-T, Apricity, Asher Bio, BioAtla LLC, BioNTech, Candel Therapeutics, Catalio, Carisma, Codiak Biosciences Inc., C-Reveal Therapeutics, Dragonfly Therapeutics, Earli Inc, Enable Medicine, Glympse, Henlius/Hengenix, Hummingbird, ImaginAB, Infinity Pharma, Intervenn Biosciences, JSL Health, LAVA Therapeutics, Lytix Biopharma, Marker Therapeutics, Oncolytics, PBM Capital, Phenomic AI, Polaris Pharma, Sporos, Time Bioventures, Trained Therapeutix Discovery, and Two Bear Capital; and other support from Xilis Inc. outside the submitted work. E. Vilar reports grants and personal fees from Janssen Research and Development and personal fees from Recursion Pharma, Guardant Health, and Rising Tide Foundation outside the submitted work. No disclosures were reported by the other authors.

N. Deng: Data curation, formal analysis, writing–original draft. L. Reyes-Uribe: Data curation, formal analysis, writing–original draft. J.F. Fahrmann: Formal analysis, investigation, writing–original draft. W.S. Thoman: Conceptualization, supervision, investigation. M.F. Munsell: Formal analysis, validation. J.B. Dennison: Formal analysis, writing–review and editing. E. Murage: Formal analysis, writing–review and editing. R. Wu: Formal analysis, writing–review and editing. E.T. Hawk: Writing–review and editing. S. Thirumurthi: Investigation, writing–review and editing. P.M. Lynch: Investigation, writing–review and editing. C.M. Dieli-Conwright: Conceptualization. A.J. Lazar: Formal analysis, writing–review and editing. S. Jindal: Formal analysis, validation, writing–review and editing. K. Chu: Formal analysis, validation, writing–review and editing. M. Chelvanambi: Validation, writing–review and editing. K. Basen-Engquist: Writing–review and editing. Y. Li: Formal analysis. J.A. Wargo: Writing–review and editing. F. McAllister: Writing–review and editing. J.P. Allison: Writing–review and editing. P. Sharma: Formal analysis, writing–review and editing. K.M. Sinha: Formal analysis, writing–review and editing. S. Hanash: Writing–review and editing. S.C. Gilchrist: Formal analysis, supervision, investigation, writing–original draft, writing–review and editing. E. Vilar: Conceptualization, supervision, funding acquisition, investigation, methodology, writing–review and editing.

We thank the patients and their families for their participation. We thank the MDACC Clinical Cancer Prevention Research Core for their assistance in the conduction of this study. We thank the staff of the Advanced Technology Genomics Core for the assistance with RNA sequencing and the Immunotherapy Platform for the assistance with the IHC, both at MDACC. The authors are grateful to Karen Colbert Maresso for critically reading the manuscript.

This work was supported by a gift from the Feinberg Family Foundation to E. Vilar; a grant and a faculty fellowship from The University of Texas MD Anderson Cancer Center Duncan Family Institute for Cancer Prevention and Risk Assessment and the T. Boone Pickens Endowment to S.C. Gilchrist and E.T. Hawk; CA016672 (NIH/NCI) to The University of Texas MD Anderson Cancer Center Core Support Grant, P50 CA221707 (NIH/NCI) to The University of Texas MD Anderson Cancer Center GI SPORE Grant, and the generous philanthropic contributions to The University of Texas MD Anderson Cancer Center Moon Shots Program.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.