Abstract

Therapeutic options for small cell lung cancer (SCLC), a particularly lethal malignancy, remain limited. Members of the B7-CD28 family are compelling targets for immune checkpoint blockade strategies, which involve activating, inhibiting, and fine-tuning the T cell immune response. However, their clinical features and significance have not been explored comprehensively. We enrolled 228 patients with an initial diagnosis of SCLC, including 77 cases from Cbioportal and a validation cohort of 151 cases with qPCR data. Kaplan-Meier analysis and LASSO Cox model were used to identify a signature based on the B7-CD28 family, which was applied for accurate prediction of chemotherapy benefit and prognosis for SCLC patients. In addition, we applied bioinformatics analysis to explore potential signature-related molecular mechanisms and the immune landscape. The mutation profiles of healthy tissues and SCLC tissues were distinct. A signature consisting of seven genes (CD86, ICOSLG, CD276, CD28, CTLA-4, PDCD1, and TMIGD2) was identified and applied to group patients based on risk level (high-risk and low-risk), producing two groups for which survival outcomes differed significantly (HR=3.81, 95% CI: 2.16-6.74, P<0.001). The immune checkpoint-based signature accurately predicted patient outcomes for the selected training and validation sets. Notably, low-risk patients were more likely to benefit from chemotherapy and showed greater immune activation. Additionally, time-dependent ROC curves and C-index analysis confirmed that the immune checkpoint-based signature has excellent predictive power for prognosis and chemotherapy benefit compared to clinically recognized parameters. Finally, multivariate analysis confirmed the identified signature as an independent risk factor for prognosis and chemotherapeutic response. We systematically obtained a comprehensive molecular profile for B7-CD28 family members in SCLC patients, from which we produced a reliable and robust prognostic immune checkpoint-based signature with the potential to improve prognostic stratification and therapy strategies for SCLC patients.

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