Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma

Abstract

Background: Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunotherapysignificantly. As such, dendritic cells are important in killing tumors and influencing tumor microenvironment,whereas their roles in lung adenocarcinoma (LUAD) are largely unknown. Methods: In this study, 1658 LUAD patients from different cohorts were included. In addition, 724 cancer patientswho received immunotherapy were also included. To identify DC marker genes in LUAD, we used single-cell RNAsequencingdata for analysis and determined 83 genes as DC marker genes. Following that, integrative machinelearning procedure was developed to construct a signature for DC marker genes. Results: Using TCGA bulk-RNA sequencing data as the training set, we developed a signature consisting of sevengenes and classified patients by their risk status. Another six independent cohorts demonstrated the signature’ sprognostic power, and multivariate analysis demonstrated it was an independent prognostic factor. LUAD patientsin the high-risk group displayed more advanced features, discriminatory immune-cell infiltrations andimmunosuppressive states. Cell–cell communication analysis indicates that tumor cells with lower risk scorescommunicate more actively with the tumor microenvironment. Eight independent immunotherapy cohorts revealedthat patients with low-risk had better immunotherapy responses. Drug sensitivity analysis indicated that targetedtherapy agents exhibited greater sensitivity to low-risk patients, while chemotherapy agents displayed greatersensitivity to high-risk patients. In vitro experiments confirmed that CTSH is a novel protective factor for LUAD. Conclusions: An unique signature based on DC marker genes that is highly predictive of LUAD patients’ prognosisand response to immunotherapy. CTSH is a new biomarker for LUAD.