A Riskscore Model for Predicting Survival, Tumor Microenvironment, Immunotherapy and Drug Sensitivity of Lung Squamous Cell Carcinoma Based on PI3K/AKT/MTOR Pathway-Related Genes

Targeting PI3K/AKT/MTOR (PAM) signaling pathway may be a strategy at the fore for treating lung squamous cell carcinoma (LUSC). However, relationships of PAM pathway-related genes (PAGs) with LUSC prognosis are unknown. Therefore, identifying the prognostic significance of PAGs for LUSC is innovative and feasible. Transcriptomic data, clinical features, and PAGs of LUSC were obtained from public databases (TCGA, GEO). A PAGs-based prognostic model was built using regression analysis in TCGA-LUSC. Gene levels were assessed via qRT-PCR. Predictive performance was verified through multiple datasets. Differences in immune infiltration and anti-tumor immunity between risk groups were assessed by R packages. Sensitivity to common anti-cancer agents was tested using oncoPredict package. We identified a Riskscore model containing 11 PAGs. Patients were assigned into groups of high risk (HR) and low risk (LR) per median Riskscore. CAB39L, CDKN1A, and ITPR2 were significantly underexpressed in LUSC cells. TRAF2 and TRIB3 were significantly enhanced in LUSC cells. The LR group had a longer survival time. Prognostic values of one-, three-, and five-year ROC curves were good. Results were verified in GEO. Patients in LR group had higher immune infiltration levels of B cells and Tfh cells, and higher ssGSEA scores for APC_co_inhibition and T_cell_ co_stimulation. LR group had lower TIDE scores and lower IC50 values (Alpelisib, Ibrutinib, Sapitinib, and Savolitinib). We successfully built a reliable 11-gene Riskscore prognostic model. Patients in LR group had potential advantages in survival, immune response, and drug sensitivity. In summary, the results offered new insights into prognosis prediction, immunotherapy, and personalized treatment of LUSC.