The proportion of patients with stage Ⅰ lung adenocarcinoma (LUAD) has dramatically increased with the prevalence of low-dose computed tomography use for screening. Up to 30% of patients with stage Ⅰ LUAD experience recurrence within 5 years after curative surgery. A robust risk stratification tool is urgently needed to identify patients who might benefit from adjuvant treatment.

In this first investigation of the relationship between metabolic reprogramming and recurrence in stage Ⅰ LUAD, we developed a recurrence-associated metabolic signature (RAMS). This RAMS was based on metabolism-associated genes to predict cancer relapse and overall prognoses of patients with stage Ⅰ LUAD. The clinical significance and immune landscapes of the signature were comprehensively analyzed.

Based on a gene expression profile from the GSE31210 database, functional enrichment analysis revealed a significant difference in metabolic reprogramming that distinguished patients with stage Ⅰ LUAD with relapse from those without relapse. We then identified a metabolic signature (i.e., RAMS) represented by 2 genes (ACADM and RPS8) significantly related to recurrence-free survival and overall survival times of patients with stage Ⅰ LUAD using transcriptome data analysis of a training set. The training set was well validated in a test set. The discriminatory power of the 2 gene metabolic signature was further validated using protein values in an additional independent cohort. The results indicated a clear association between a high risk score and a very poor patient prognosis. Stratification analysis and multivariate Cox regression analysis showed that the RAMS was an independent prognostic factor. We also found that the risk score was positively correlated with inflammatory response, the antigen-presenting process, and the expression levels of many immunosuppressive checkpoint molecules (e.g., PD-L1, PD-L2, B7-H3, galectin-9, and FGL-1). These results suggested that high risk patients had immune response suppression. Further analysis revealed that anti-PD-1/PD-L1 immunotherapy did not have significant benefits for high risk patients. However, the patients could respond better to chemotherapy.

This study is the first to highlight the relationship between metabolic reprogramming and recurrence in stage Ⅰ LUAD, and is the first to also develop a clinically feasible signature. This signature may be a powerful prognostic tool and help further optimize the cancer therapy paradigm.

The aim of this study was to investigate how the tumor immune microenvironment differs regarding tumor genomics, as well as its impact on prognoses and responses to immunotherapy in East Asian patients with non-small cell lung cancer (NSCLC).

We performed an integrated analysis using publicly available data to identify associations between anti-programmed death 1 (PD-1)/ programmed death-ligand 1 (PD-L1) immunotherapy efficacy and classic driver oncogene mutations in East Asian NSCLC patients. Four pooled and clinical cohort analyses were used to correlate driver oncogene mutation status and tumor microenvironment based on PD-L1 and CD8⁺ tumor-infiltrating lymphocytes (TILs). Immune infiltrating patterns were also established for genomic NSCLC subgroups using the CIBERSORT algorithm.

Based on East Asian NSCLC patients, TIDE analyses revealed that for anti-PD-1/PD-L1 immunotherapy, epidermal growth factor receptor (EGFR)-mutant and anaplastic lymphoma kinase (ALK)-rearranged tumors yielded inferior responses; however, although Kirsten rat sarcoma viral oncogene homolog (KRAS)-mutant tumors responded better, the difference was not statistically significant (EGFR: P = 0.037; ALK: P < 0.001; KRAS: P = 0.701). Pooled and clinical cohort analyses demonstrated tumor immune microenvironment heterogeneities correlated with oncogenic patterns. The results showed remarkably higher PD-L1- and TIL-positive KRAS-mutant tumors, suggesting KRAS mutations may drive an inflammatory phenotype with adaptive immune resistance. However, the EGFR-mutant or ALK-rearranged groups showed a remarkably higher proportion of PD-L1-/TIL-tumors, suggesting an uninflamed phenotype with immunological ignorance. Notably, similar to triple wild-type NSCLC tumors, EGFR L858R-mutant tumors positively correlated with an inflammatory phenotype, suggesting responsiveness to anti-PD-1/PD-L1 immunotherapy (P < 0.05). Furthermore, the CIBERSORT algorithm results revealed that EGFR-mutant and ALK-rearranged tumors were characterized by an enriched resting memory CD4⁺ T cell population (P < 0.001), as well as a lack of CD8⁺ T cells (P < 0.01), and activated memory CD4⁺ T cells (P = 0.001).

Our study highlighted the complex relationships between immune heterogeneity and immunotherapeutic responses in East Asian NSCLC patients regarding oncogenic dependence.