Abstract Lynch Syndrome (LS) provides the perfect context to understand DNA mismatch repair deficient carcinogenesis, which is characterized by neoplastic lesions with high rates of shared neoantigens eliciting adaptive immunity through T cell receptor (TCR) recognition. However, the TCR landscape in LS carriers remains unexplored. Here, we perform TCR sequencing of 277 blood samples from LS cancer survivors, previvors, and controls, as well as matching colorectal cancers and pre-cancers. We show that up to 41% of the most expanded TCRβs from colorectal neoplasms are detectable in the blood of LS carriers, while showing minimal expansion in controls. In addition, we develop and validate a classification model that distinguishes LS carriers from controls using circulating TCRβs signatures associated with LS independent of thecancer history and with cancer-free LS previvors. Together, our findings characterize circulating and tissue TCRβs associated with LS, thus representing a step toward identifying blood-based TCR biomarkers for immune surveillance.

The Collaborative Group of the Americas on Inherited Gastrointestinal Cancer (CGA-IGC) was created in 1995, when a small group of clinicians and researchers interested in improving the understanding of hereditary gastrointestinal (GI) cancer syndromes met in St. Louis. The organization was modeled after similar societies being formed internationally, with the goals of addressing uniquely American aspects of the healthcare of patients, providing opportunities for interested institutions and individuals to collaborate on studies, and facilitating affordable and accessible meetings. Over the subsequent 30 years, CGA-IGC has grown in size and scope. The organization was formally established in 1996 and annual academic meetings began in 1997, at which time the organization’s name was the Collaborative Group of the Americas on Inherited Colorectal Cancer (CGA-ICC). Milestones included the organization’s first strategic plan in 2010, the hiring of outside administrative management in 2014, and the creation of working committees in 2017. These decisions led to progressive growth of the organization, allowing for provision of year-round educational opportunities and increased member engagement. Given the recognition that the hereditary syndromes of interest to this group involve all parts of the gastrointestinal tract, the organization’s name was changed from Collaborative Group of the Americas on Inherited Colorectal Cancer to Collaborative Group of the Americas on Inherited Gastrointestinal Cancer in 2018. Presently, CGA-IGC enjoys record-high membership, with over 500 members. A new 3-year strategic plan was implemented in 2024 to guide CGA-IGC into its next 30 years.

Table S7. Results of in silico deconvolution of immune cell types using CIBERSORT.

Table S5. Results of differential gene expression analysis between the exercise and usual care groups using mRNAseq.

Figure S1. Flow diagram of participants in the ‘CYCLE-P’ trial. Diagram provides details on follow-up procedures and number of patients/samples available for each analysis.

Figure S8. (A) Volcano plot of statistically significant genes and fold-changes between the usual care and exercise groups in DSP assay. Top significantly differentially expressed genes are labeled; (B) The dot plot presents enriched GSEA HALLMARK pathways. The sizes of the dots represent the count of core enrichment (leading-edge) genes. The colors of the dots represent the BH-adjusted P-values. The order of HALLMARK gene sets is based on the gene ratio (number of significant genes associated with the HALLMARK gene sets / total number of significant genes; (C) Total CD8+ T cell density per mm2 (left) and epithelial (right) in colonic mucosa preand post- intervention from usual care (n=4) and exercise (n=4) participants; (D) Total CD57+ NK cell density per mm2 (left) and epithelial (right) in colonic mucosa pre- and post- intervention from usual care (n=4) and exercise (n=4) participants.

Figure S5. (A) Gene Set Enrichment Analysis (GSEA) of BIOCARTA IL-6 pathway; (B) Gene set of IL-6-stimulated cell cultures; (C) Gene set in IL-6-deprived cell cultures. GSEA was performed by 1000 permutations. The maximum and minimum sizes for gene sets were 500 and 15, respectively. The y-axis represents the enrichment score (ES) and the x-axis lists the ranked genes by fold change. Vertical black lines on the x-axis represent the genes in gene sets. The green line connects points of ES and genes. ES is the maximum deviation from zero as calculated for each gene going down the ranked list and represents the degree of over-representation of a gene set at the top or the bottom of the ranked gene list. The P-value and ES are labeled at the top of the figure. The peak towards to left of the x-axis suggests a positive enrichment of the target gene set and vice versa.

Table S4. Untargeted metabolomic analyses in the serum metabolome.

Table S3. Number of patients experiencing adverse events. Only those toxicities experienced while on the trial are presented in the table. Toxicities during the pre-study stage of the trial, for example, that were present before participants begin intervention were not included. Should a patient experience an adverse event more than once, the patient is only counted once at the highest grade for that adverse event.

Butyrate may reduce the risk of colorectal cancer and can be delivered to the colon using butyrylated high-amylose maize starch (HAMSB). This trial evaluated the effects of HAMSB on polyp burden in participants with familial adenomatous polyposis. This study was a randomized, double-blind, placebo-controlled crossover trial. In three 6-month periods, participants ingested 40 g/day of HAMSB or low-amylose starch, followed by the alternative, and then a washout. Participants underwent four video-recorded colonoscopies to assess polyp burden as the primary endpoint. At baseline, two distal bowel tattoos were placed: tattoo one where polyps were cleared at each scope and tattoo two where polyps were left in situ. Generalized linear mixed models were used to estimate the ratio of mean polyp counts in intervention compared with placebo periods. Seventy-two participants were randomized (33 female), with 49 completing the study. In the intention-to-treat analysis, HAMSB did not reduce mean global [0.9 fold change (FC); 95% confidence interval (CI), 0.77-1.06; P = 0.218] or small (<2.4 mm) polyp numbers (0.88 FC; 95% CI, 0.71-1.1; P = 0.267). There was a trend for the reduction of small polyps in tattoo one (0.72 FC; 95% CI, 0.5-1.03; P = 0.074). In the per-protocol analysis, there was a strong trend for HAMSB to reduce mean global small polyp numbers (0.79 FC; 95% CI, 0.62-1; P = 0.051). HAMSB may reduce polyp initiation in the distal bowel without causing regression or growth of existing polyps. However, 95% CIs indicate large uncertainty to the true direction of the treatment effect, and the P values provide only weak evidence against the null hypothesis of no treatment effect. Prevention Relevance: There is convincing evidence that dietary fiber reduces the risk of colorectal cancer possibly by production of butyrate during microbial fermentation of indigestible fiber. This study was designed to determine if a dietary supplement that delivers butyrate to the colon reduces polyp burden in participants with familial adenomatous polyposis.

Figure S4. Relative change in prostaglandin metabolite levels after twelve months follow-up in usual care and exercise groups (A-C, Wilcoxon signed-rank test; ns, P>0.05; *, P ≤0.05; **, P≤0.01).

Table S1. Adverse events (AEs) experience by participants with possible or probable relation to the study intervention. Summary of the adverse events by grade, relationship, and arm. Adverse events were reported by subjects, including AEs that happened between consent and initiation of exercise regimen (Pre-Study) and in the exercise and usual care group.

Figure S2. CYCLE-P trial study visits and follow-up.

Table S2. Number of Patients Experiencing Adverse Events by Maximum Grade consent and initiation of exercise regimen (Pre-Study) and in the exercise and usual care group. List with the number of patients experiencing adverse events. Should a patient experience any adverse event, the patient is counted only at the highest (maximum) grade experienced.

Supplementary Table 8. Representativeness of Study Participants

Figure S6. Deconvolution of immune cell types by CIBERSORT. Changes in deconvoluted immune cell type proportions derived from mRNAseq data are shown after twelve months of follow-up in the usual care (N=6) and exercise (N=9) groups using CIBERSORT. No significant changes in immune cell types were observed, though CD8+ T cells were non-statistically significantly higher in the exercise group (two-tail Wilcoxon signed-rank test).

Figure S7. Pearson correlation coefficient matrix analyses. Heatmap shows correlations among VO2peak, BMI, PGs, and immune cell types.

Figure S3. (A) Average time that study participants wore the Fitbit throughout the study; (B) Resting heart rate in study participants at baseline; (C) Average total minutes of exercise at heart rate 70-85% of PHR; (D) Average total minutes of exercise at heart rate >85% of PHR. (***, P ≤0.001; ****, P≤0.0001).

Table S6. Gene set enrichment analysis using the KEGG pathways and Gene Ontology Biological Processes databases. Pathways statistically significant activated or suppressed after twelve months exercise are displayed (BH-adjusted P-value<0.05).