Immune checkpoint blockade (ICB) therapy has achieved breakthroughs in the treatment of advanced non-small cell lung cancer (NSCLC). Nevertheless, the low response due to immuno-cold tumor microenvironment (TME) largely limits the application of ICB therapy. Based on the glycolytic/cholesterol synthesis axis, a stratification framework for EGFR wild-type NSCLC was developed to summarize the metabolic features of immuno-cold and immuno-hot tumors. The cholesterol subgroup displays the worst prognosis in immuno-cold NSCLC with significant enrichment of the cholesterol gene signature, indicating targeting cholesterol synthesis is essential for the therapy for immuno-cold NSCLC. Statin, the inhibitor for cholesterol synthesis, can suppress the aggressiveness of NSCLC in vitro and in vivo and also drastically reverse immuno-cold to an inflamed phenotype in vivo which exhibited a higher response to ICB therapy. Moreover, both our in-house data and meta-analysis further support that statin can significantly enhance ICB efficacy. In terms of preliminary mechanisms, statin could transcriptionally inhibit PD-L1 expression and induce ferroptosis in NSCLC cells. Overall, we reveal the significance of cholesterol synthesis in NSCLC and demonstrate the improved therapeutic efficacy of ICB in combination with statin.These findings could provide a innovative clinical insight to treat NSCLC patients with immuno-cold tumors.

Background Immune checkpoint blockade (ICB) only works well for a certain subset of patients with non-small cell lung cancer (NSCLC). Therefore, biomarkers for patient stratification are desired, which can suggest the most beneficial treatment. Methods In this study, three datasets (GSE126044, GSE135222, and GSE136961) of immunotherapy from the Gene Expression Omnibus (GEO) database were analyzed, and seven intersected candidates were extracted as potential biomarkers for ICB followed by validation with The Cancer Genome Atlas (TCGA) dataset and the in-house cohort data. Results Among these candidates, we found that human leukocyte antigen-DR alpha (HLA-DRA) was downregulated in NSCLC tissues and both tumor and immune cells expressed HLA-DRA. In addition, HLA-DRA was associated with an inflamed tumor microenvironment (TME) and could predict the response to ICB in NSCLC. Moreover, we validated the predictive value of HLA-DRA in immunotherapy using an in-house cohort. Furthermore, HLA-DRA was related to the features of inflamed TME in not only NSCLC but also in most cancer types. Conclusion Overall, HLA-DRA could be a promising biomarker for guiding ICB in NSCLC.

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Non-small cell lung cancer (NSCLC) is a heterogeneous disease, and its demarcation contributes to various therapeutic outcomes. However, a small subset of tumors shows different molecular features that are in contradiction with pathological classification. Unsupervised clustering was performed to subtype NSCLC using the transcriptome data from the TCGA database. Next, immune microenvironment features of lung adenocarcinoma (LUAD), lung squamous carcinoma (LUSC), and lung adenoid squamous carcinoma (LASC) were characterized. In addition, diagnostic biomarkers to demarcate LASC among LUSC were screened using weighted gene co-expression network analysis (WGCNA) and validated by the in-house cohort. LASC was identified as a novel subtype with adenoid transcriptomic features in LUSC, which exhibited the most immuno-escaped phenotype among all NSCLC subtypes. In addition, FOLR1 was identified as a biomarker for LASC discrimination using the WGCNA analysis, and its diagnostic value was validated by the in-house cohort. Moreover, FOLR1 was related to immuno-escaped tumors in LUSC but not in LUAD. Overall, we proposed a novel typing strategy in NSCLC and identified FOLR1 as a biomarker for LASC discrimination.