Multi-group Biomarker Exploration And Prediction Model Establishment Of Lung Cancer Immunotherapy-related Adverse Reactions

Background and objectives:Immune checkpoint inhibitors(ICIs)are revolutionizing the landscape of cancer treatment.They have been widely applicated in the treatment of advanced lung cancers.When boosting effector function and reversing T cell exhaustion to eliminate tumor cells,immune checkpoint inhibitors(ICIs)unselectively break the immune balance,and lead to a unique spectrum of immune-related adverse events(irAEs).Previous studies have reported an association between irAEs occurrence and ICIs efficacy,but a definite conclusion has not been drawn based on the findings from each single study.Meanwhile,exploring potential irAEs biomarkers is of great clinical significance to the early recognition and proper management of the adverse events.Current known biomarkers have the disadvantages of single index,low prediction efficiency and lack of effective integration.This study intends to explore and integrate predictors of irAEs from multiple dimensions including tumor,peripheral blood,and patient genetic information,and further establish a prediction model of irAEs.Additionally,based on the preliminary findings of our cohort,this study performed a meta-analysis to integrate published literature to evaluate the correlation between irAEs and the efficacy of immunotherapy.Methods s Cohort analysis:Patients with advanced lung cancer who received anti-PD-1/PD-L1 immunotherapy were enrolled in the study.Baseline clinical characteristics,survival data and irAEs information were documented.Baseline serum and lymphocytes samples were collected.We performed high-throughput sequencing of ctDNA based on a 1021 panel.The TCR of PD-1+CD4+/CD8+T lymphocytes was also sequenced using high-throughput immune sequencing technology,73 cytokines were measured by electrochemiluminescence method.For statistical analysis,we analyzed the association of individual biomarkers and irAEs.We applied Lasso regression method and Logistic regression to screen variables and establish the prediction model.Meta analysis:Under the guidance of a predefined protocol and Preferred Reporting Items for Systematic Reviews and Meta-analyses statement,this meta-analysis included cohort studies investigating the association of irAEs and efficacy of ICIs in patients with cancer.The primary outcome was overall survival(OS),and the secondary outcome was progression-free survival(PFS).Specific analyses of the type and grade of irAEs were also performed.Results:Cohort analysis:①The study included 55 locally advanced/advanced lung cancer patients who received immunotherapy.The PFS and OS of the irAEs group were significantly longer than those of the non-irAEs group(PFS:4.5m vs 2.0m,p=0.005,OS:Not reached vs 4.6 m,p<0.0001).②There were significant differences in the baseline NLR,PLR and PNI levels between the irAEs group and the non-irAE group(NLR:p=0.014,PLR:p=0.044,PNI:p=0.003).The diversity of the baseline PD-1-1+CD8+T cell and PD-1+CD4+T cell immune repertoire of patients in the irAEs group was significantly higher than that of the patients in the non-irAEs group(PD-1+CD8+TCR:p=0.016,PD-1+CD4+TCR:p=0.042).HLA distribution and bTMB levels were not significantly different between the two groups.③Among 73 types of cytokines,IL-2 and IL-17C levels are correlated with irAEs(IL-2:p=0.006,IL-17C:p=0.040)·④In the irAEs model constructed by multiple factors,the area under the curve of the prediction model is 0.934(95%CI:0.844-1.000),the best prediction sensitivity is 89.5%,and the specificity is 91.7%.Meta analysis:This meta-analysis included 30 studies of 4971 individuals.Patients with cancer who developed irAEs experienced both an OS benefit and a PFS benefit from ICI therapy compared to patients who did not develop irAEs(OS:hazard ratio(HR)=0.54,95%confidence interval(CI),0.45-0.65;p<0.001;PFS:HR=0.52,95%CI,0.44-0.61,p<0.001).Specific analyses of endocrine irAEs(OS:HR=0.52,95%CI,0.44-0.62,p<0.001),dermatological irAEs(OS:HR=0.45,95%CI,0.35-0.59,p<0.001)and low-grade irAEs(OS:HR=0.57,95%CI,0.43-0.75;p<0.001)yielded similar results.Conclusion:In summary,this study constructed an irAEs cohort of lung cancer patients receiving immunotherapy.Peripheral inflammation biomarkers,T cell immune repertoire and cytokine levels are related to the occurrence of irAEs.On this basis,the multi-dimensional indicators were further integrated,and we establish an irAEs prediction model.Furthermore,based on retrospective cohort data and meta-analysis,this study found that irAEs are significantly correlated with favorable patients’ overall survival and progression-free survival.