Colorectal cancer (CRC) with microsatellite instability (MSI) is often treated with immune checkpoint inhibitors (ICIs), such as anti-PD-1 antibodies. However, a substantial fraction of MSI CRCs do not respond to ICIs. Recent studies have identified the DNA helicase WRN as a synthetic lethal target in MSI cancer cells, leading to the development of several small-molecule WRN inhibitors that are currently in clinical trials. In this study, we found that targeting WRN in MSI CRC cells triggered a robust antitumor immune response. Cell death induced by WRN inhibition was selective in MSI CRC cells and led to the release of extrachromosomal circular DNA (eccDNA), which directly stimulated immune cell activation and cytokine production. The deletion of nuclear ligase LIG3, a key mediator of eccDNA biogenesis, abolished the antitumor and immunogenic effects of WRN inhibition in MSI CRC cells and tumors. Furthermore, WRN inhibition potentiated anti-PD-1 therapy in MSI CRC models, including syngeneic mouse tumors and patient-derived tumor organoids. Together, these results reveal eccDNA-mediated immunogenic effects of WRN inhibition in MSI CRC, further strengthening the rationale for combining WRN inhibitors with ICIs.

BACKGROUND & AIMS:Colorectal cancers (CRCs) with deficient DNA mismatch repair (dMMR) and microsatellite instability (MSI) are believed to be intrinsically immunogenic and respond more favorably to immune checkpoint inhibitor (ICI) therapy. However, a significant fraction of dMMR/MSI CRCs do not respond or eventually develop resistance to ICIs. The mechanisms underlying dMMR/MSI-associated immunogenicity is unclear. The aim of this study was to investigate the role and mechanism of MSI-induced antitumor immunity in CRCs. METHODS:We used transplant syngeneic tumor models, immune cell co-culture assays, and air-liquid interface (ALI) culture of tumor-derived organoids to investigate the mechanism by which dMMR elicits an antitumor immune response. We also analyzed the gene expression databases of CRC cancer patients receiving ICI treatment. RESULTS:We found that inactivating Mlh1 causes endoplasmic reticulum (ER) stress and death receptor 5 (Dr5)-mediated apoptosis in syngeneic colorectal tumors. Sustained immune response against Mlh1-deficient tumors requires nuclear Ligase 3 (Lig3)-mediated release of extrachromosomal circular DNAs (eccDNAs) from apoptotic cells. A feedback Dr5/Lig3 amplification loop perpetuates apoptosis and immune cell activation in Mlh1-deficient syngeneic tumors. This feedback mechanism is critical for the response to ICI therapy in mice, which is supported by a significant association between DR5 or LIG3 expression and the efficacy of ICI therapy in cancer patients. CONCLUSIONS:Our results reveal a functional link between dMMR and antitumor immunity, which may be useful for improving ICI therapy in tumors with different MMR statuses.

Somatic mutations in KRAS are a common driver of colorectal cancer (CRC) and present at different frequencies by race, sex, tumor site, ethnicity, and genetic similarity. Inherited germline variants may influence tumor somatic mutation frequency by altering mutation or DNA repair processes or altering cellular, immunological and/or microenvironmental responses after a mutation. We hypothesized that the germline genetic background modifies somatic KRAS mutation frequency in CRC. To test this, we performed a genome-wide association study (GWAS) in 7071 individuals with CRC, using KRAS mutation status as the phenotype. Single-nucleotide variants were chosen for validation analyses based on P values from the discovery GWAS, predicted in silico functional effects, and proximity to genes with potential cancer relevance. A validation analysis of 101 SNVs of interest was performed in 2482 individuals. No SNVs were significantly associated with KRAS-mutant CRC (P value < 0.0005). One variant rs73067863-T showed a non-significant exploratory association with fewer KRAS-mutant tumors in the combined sample (P value = 9.7 × 10-7, OR = 0.75). Follow-up studies are needed to determine if these or other germline variants impact population differences in KRAS mutations in CRC.

Physical activity is an established protective factor for colorectal cancer (CRC), but it is unclear if genetic variants modify this effect. To investigate this possibility, we conducted a genome-wide gene–physical activity interaction analysis. Using logistic regression (1-d.f), two-step screening and testing method (EDGE), and joint tests (3-d.f), we analyzed interactions between common genetic variants across the genome and physical activity in relation to CRC risk. Self-reported physical activity levels were categorized as active (≥ 8.75 MET-h/wk) vs. inactive (< 8.75 MET-h/wk; 39,992 participants) and as study- and sex-specific quartiles of activity (42,602 participants). Physical activity was inversely associated with CRC risk overall (OR [active vs. inactive] = 0.85; 95

Summary What is this summary about? This summary describes the α-CORRECT study and its key results. The study evaluated a new blood test that looks for tiny traces of cancer in patients with stage III colorectal cancer after treatment. What is the purpose of this plain language summary? The purpose of this plain language summary is to help readers understand the main findings of the α-CORRECT study. Why was this study done? Colorectal cancer is a leading cause of cancer death. Many patients with stage III colorectal cancer are treated with surgery to remove the tumor, followed by chemotherapy to kill any remaining cancer cells. However, some cancer cells may stay in the body after surgery and chemotherapy, and potentially grow, causing cancer recurrence – when cancer returns with tumors and/or symptoms, even years later. Patients with traces of cancer remaining in the body after standard treatment have what is called molecular residual disease (MRD). Because only a few cancer cells remain, the signs of disease (such as symptoms or abnormal physical exam findings) are typically absent, and even imaging methods like computed tomography (CT) or Positron Emission Tomography (PET) may not detect the cancer. However, the presence of these cancer cells can sometimes be detected by a new type of MRD test that looks for fragments of tumor genetic material – circulating tumor DNA (ctDNA) – that cancer cells release into the blood. The α-CORRECT study was designed to find out whether a new MRD test that looks for ctDNA in the blood could detect the presence of cancer cells in the body after treatment, and how well detection of ctDNA predicted cancer return. What did the study show? The study showed that the new MRD test can accurately predict the likelihood of cancer return after treatment. The chances of cancer returning were about 10 times higher for a person with MRD detected after surgery and about 50 times higher for a person with MRD detected during the follow-up (surveillance) period than for a person with no MRD detected. During the follow-up period, the MRD test detected ctDNA about 10 months before cancer was found by symptoms or by imaging methods. In other words, the new blood test warned doctors about cancer returning many months earlier than usual tests. Why is this study important? Finding evidence of MRD can help predict the likelihood of cancer return and may help doctors decide who needs more treatment and who may safely avoid additional chemotherapy: Patients with ctDNA detected (meaning MRD is present and the risk of cancer recurrence is high) may be candidates to receive additional treatment, which may improve their survival. Patients with no ctDNA detected (meaning MRD is likely absent, and the risk of cancer recurrence is low) may not require chemotherapy, helping them to avoid side effects and costs from treatment that may not provide benefit. The α-CORRECT study was not meant to set exact MRD levels for changing treatment. Other ongoing clinical studies are looking at how MRD test results should be used to make better treatment decisions.

Endpoint titers of plasma antibodies at week 12 amongst vaccine responders

Supplementary Table S4 lists the 140 colorectal-cancer-associated loci and associations with colorectal cancer in European-ancestry population.

Supplementary Figure S6 shows the calibration on relative risk of PRS stratified by PRS with 7 bins in groups of different ancestry in the GERA cohort.

This table includes the overall sample description stratified by colorectal cancer (CRC) status and smoking status.

Supplementary Table S1 describes baseline characteristics of participants

This file includes the expression imputation statistics and included SNPs from the elastin net models.

Supplementary Figure from Beyond GWAS of Colorectal Cancer: Evidence of Interaction with Alcohol Consumption and Putative Causal Variant for the 10q24.2 Region

This file details the two-step interaction tests, and the gene-based aggregate test.

BACKGROUND:Recent advances in vaccine technology raise hopes for effective cancer preventative vaccines. The first clinical trials (single-arm NCT007773097; double-blind, placebo controlled randomized trial NCT02134925) of a non-viral cancer preventative vaccine were conducted in individuals with previous advanced colonic adenoma to test the safety and immunogenicity of the MUC1 tumor antigen vaccine. The vaccine was safe and strongly immunogenic in 43 %-25 % of participants. The lack of response in a significant number of participants suggested that the pre-malignant immune system may have already been exposed to some level of suppression, something previously reported only in cancer. METHODS:Single-cell RNA-sequencing (scRNA-seq) data were collected from banked pre-vaccination peripheral blood mononuclear cells (PBMCs) (16 immune responders and 16 non-responders) and analyzed using standard bioinformatic and novel machine learning methods. RESULTS:We identified specific cell types, genes, and pathways characteristic of vaccine response. A significantly higher percentage of CD4 + naïve T cells and lower percentage of CD8 + T effector memory (TEM) cells and CD16 + monocytes were present in responders. Differential gene expression (DGE) and transcription factor inference analysis showed a higher level of expression of T cell activation genes (like Fos, Jun) in CD4 + naïve T cells. Pathway analysis showed enriched signaling activity in responders. Furthermore, Bayesian graph analysis suggested that these genes were mechanistically related to response. CONCLUSIONS:Our analyses identified several immune mechanisms and candidate biomarkers which can be further validated as predictors of immune responses to a preventative cancer vaccine. These could facilitate selection of individuals likely to benefit from a vaccine or be used in further research to improve vaccine responses.

Recent studies have demonstrated that for various diseases, incorporating polygenic risk scores (PRSs) for other traits and diseases into the PRS-based risk prediction model may improve predictive performance – known as Multiple Polygenic Score (MPS) approach. We aimed to examine whether the MPS approach improves colorectal cancer (CRC) risk prediction. We included 2,187 non-CRC PRSs from the polygenic Score (PGS) Catalog and used machine learning (ML) models to select the most predictive non-CRC PRSs, utilizing individual-level data from 31,257 CRC cases and 33,408 controls. An independent dataset from the Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort (4,852 cases and 67,939 controls) was randomly split into subsets for model estimation and validation. The model combined MPS with two existing CRC-PRSs based on known loci and genome-wide genotyping. We then assessed model performance by calculating the area under the receiver operating curve (AUC) in the validation set and performed 1,000 bootstrapped iterations to evaluate AUC improvements. The ML model selected 337 non-CRC PRSs predictive of CRC risk. Adding MPS to the CRC-PRSs significantly improved AUC by 0.017 (95% CI: 0.011–0.022, p < 0.0001) when combined with known-loci CRC-PRS, 0.005 (95% CI: 0.002–0.007, p = 0.0005) with genome-wide CRC-PRS, and 0.004 (95% CI: 0.002–0.006, p = 0.0005) with both the known loci and genome-wide CRC-PRSs. These findings demonstrate MPS’s potential to refine CRC risk prediction models and highlight opportunities for further advancements in risk prediction.

Supplemental Figure 3: EVL methylation levels of normal colon for patients with no history of adenoma or cancer after initial colonoscopy (left group) and for levels patients with an adenoma or colorectal cancer detected after initial (middle group). Patients with no follow-up colonoscopies (right group) were not included in the analyses for Comparison Set 2. %mEVL=percentage of DNA that is methylated at the EVL locus assayed.