Background Non-small cell lung cancer (NSCLC), which makes up the majority of lung cancers, remains one of the deadliest malignancies in the world. It has a poor prognosis due to its late detection and lack of response to chemoradiaiton. Therefore, it is urgent to find a new prognostic marker. Methods We evaluated biological function and immune cell infiltration in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients from TCGA and GEO databases between different clusters based on autophagy related hub genes. Autophagy scores were used to assess the degree of autophagy in each individual by using component analysis. Results Three different clusters were obtained. Gene set variation analysis, single-sample gene set enrichment analysis and survive analysis showed differences among these three clusters. We demonstrated that the autophagy score of each patient could predict tumor stage and prognosis. Patients with a high autophagy score had a better prognosis, higher immune infiltration, and were more sensitive to immunotherapy and conventional chemotherapy. Conclusion It was uncovered that autophagy played an irreplaceable role in NSCLC. Quantified autophagy scores for each NSCLC patient would help guide effective treatment strategies.

Compound kushen injection is an effective traditional Chinese medicine for the treatment of lung cancer. However, its influence on the survival and prognosis of patients with lung adenocarcinoma patients was less studied; especially its pharmacological mechanism remains to be further elucidated. In the present study, we adopted a network pharmacology (NP)-based approach to screening effective compounds, screening and predicting target genes, analyzing biological functions and pathways, constructing a regulatory network and protein interaction network, and screening the key targets. Moreover, mass survival analysis and molecular docking were conducted. In the end, 35 key compounds and four possible central target genes were screened out, which could be used for the treatment of lung adenocarcinoma and affected the survival and prognosis of patients with lung adenocarcinoma. In addition, their key compounds had good docking affinity. Enrichment analysis showed that CKI might affect the treatment and prognosis of lung adenocarcinoma patients by regulating the PI3K–Akt signaling pathway, TNF signaling pathway, non-small cell lung cancer, Hepatitis C, etc. We discussed the pharmacological mechanisms and potential therapeutic targets of CKI in the treatment of lung adenocarcinoma, which verified the effect of CKI on the prognosis and survival of patients. The present study might promote the further clinical application of CKI and provide a theoretical basis for further experimental studies.

No abstract