Integrated multi-omics unraveled a basal cell-dependent signature predictor of outcome and immunotherapy response in LUSC

Lung squamous carcinoma (LUSC) is a major lung cancer killer with no biomarkers and limited therapeutic options. Although still unclear, transformation of the pseudostratified and basal epithelium is linked with its origin. With integrated transcriptomics, proteomics, genomics, epigenetics, and single-cell RNA sequencing (scRNA-seq), we explore basal cell-dependent signatures as therapy response predictors in LUSC.Unsupervised clustering of the TCGA-LUSC cohort classified patients into “Hot” and “Cold” using immune and basal cell-associated hub genes. The “hot” cluster had higher immune scores, immune cell infiltration (ICI), and better immunotherapy response (IR). The “cold” cluster had a higher proliferative basal cell score and expression of KRT5/6 and TP63.Both clusters had a unique and distinctive mutational landscape (shared driver mutations: TP53, KRTAP-5-5; hot: NOTCH1, ZFR; cold: ARID1A, RECQL5). Copy number variants results showed that both clusters had shared amplifications and deletions, but also individual ones [amplification – hot: WHSC1L1, KAT6A; cold: EGFR, AKT1); deletion – hot: ROBO1; cold: STK11)]. 15 key prognostic genes were identified, for the first time, CTTNBP2 and COL22A1 predicted survival in 4 different LUSC cohorts. Intercellular communication analysis of scRNA-seq showed a novel communication dependency between basal and immune cells that might influence IR. For the first time, our multi-omic integrative approach identified “Hot” and “Cold” clusters that differ substantially in their genetic landscape, a 15 key prognostic gene signature that reflect survival, and a basal cell-dependent communication that predicts IR in LUSC.