A novel mouse model recapitulating the MMR-defective SCLC subtype uncovers an actionable sensitivity to immune checkpoint blockade

Purpose Small cell lung cancer (SCLC) has an extremely poor prognosis. Despite high initial response rates to chemotherapy and modest survival improvements with the addition of immune checkpoint inhibitors (ICI), almost all patients experience relapse and fatal outcomes. Recent genomic insights uncovered extensive molecular heterogeneity in addition to the almost uniform loss of RB1 and TRP53 . Additionally, defective DNA mismatch repair (MMR) has recently been described in some SCLC cases. Here, we generated a novel SCLC mouse model capturing MMR deficiency and assessed immunotherapy responses. Methods We developed an MMR-deficient genetically engineered mouse model (GEMM) of SCLC by introducing a conditional Msh2 gene, crucial for maintaining MMR integrity, into the standard Rb1 fl/fl ; Trp53 fl/fl (RP) model. Genomic characteristics and preclinical therapy responses were evaluated by focusing on overall survival and whole exome sequencing (WES) analyses. Results MMR-defective SCLC tumors ( Rb1 fl/fl ; Trp53 fl/fl ; Msh2 fl/fl (RPM)) developed later than tumors in MMR-proficient mice. However, the time from tumor manifestation to death of the affected animals was substantially shortened (median survival 55 days in RP vs. 46.5 days in RPM), indicating increased aggressiveness of MMR-defective tumors. RPM tumors exhibited MMR deficiency, high tumor mutational burden (TMB), and an elevated load of candidate neoantigens, compared to RP lesions ( p = 0.0106), suggesting increased immunogenicity. Importantly, the overall survival of RPM animals was significantly improved when exposed to ICI. Conclusion We propose a novel RPM mouse model as a suitable system to mimic MMR-defective SCLC and tumors with high TMB. We provide in vivo evidence that Msh2 deficiency enhances ICI sensitivity. These findings could contribute to stratifying SCLC patients to immunotherapy, thereby improving treatment outcomes.