Multi-omics unveils BCAA metabolism markers L-leucine and HMGCS1 as prognostic marker for immunotherapy efficacy in non-small cell lung cancer - Liyuan Dai; Xinzheng Wang; Ning Lou; Lin Li; Liling Huang; Le Tang; Jiarui Yao; Yuankai Shi; Xiaohong Han (Respiratory Research)
Abstract Background This study aims to identify branched-chain amino acid (BCAA) plasma metabolites and gene signatures that enhance prognostic assessments in non-small cell lung cancer (NSCLC) patients receiving immunotherapy. Methods Plasma metabolites were measured using untargeted UPLC-MS/MS (n = 94 and 40), with lymphocyte subset tests on 72 patients. BCAA-related subtypes were identified in NSCLC datasets (n = 274, 176, and 196). A prognostic risk model was developed and validated in NSCLC (n = 16, 27, 24, and 339), melanoma (n = 25), and pan-cancer ICIs cohorts (n = 330 and 81). Immune cell infiltration and prognostic signatures were validated using mIF (n = 21 in CHCAMS), scRNA-seq (n = 8 and 21), and spatial transcriptomics (n = 2 and 6). Cell and animal experiments involving HMGCS1 were conducted in a lung cancer model. Additionally, based on our previous findings that B cells with higher malignancy exhibited enhanced cholesterol homeostasis pathways in diffuse large B-cell lymphoma (DLBCL), we further analyzed the prognostic value of HMGCS1 using our spatial transcriptomics (n = 10) and immunohistochemistry (IHC, n = 39) in DLBCL. Results Our plasma metabolite analysis showed higher L-leucine levels were associated with better prognosis and had higher T cell counts and CD4+ T cell counts (P < 0.05). In GEO datasets, four NSCLC subtypes were identified, showing distinct prognostic outcomes and tumor microenvironment. Five BCAA-related genes (ACAT2, ALDH2, HMGCS1, MLYCD, and PPM1 K) formed a prognostic risk model for NSCLC, validated through Kaplan–Meier and ROC curve analyses in ICI cohorts (P < 0.05). HMGCS1 was an independent prognostic value in ICI cohorts and was negatively correlated with CD8+ T cell infiltration, while positively correlating with tumor severity, cholesterol homeostasis, and BCAA degradation across multiple platforms, including GEO datasets, our mIF cohort, public scRNA-seq, and spatial transcriptomics (P < 0.05). And our cell and animal function experiments found HMGCS1 overexpression promotes metabolic pathways and accelerates tumor growth, whereas HMGCS1 knockdown suppresses tumor progression in a mouse model treated with PD-1 monoclonal antibody (P < 0.05). In DLBCL, high HMGCS1 expression was associated with shorter overall survival, enriched in B cells and relapsed patients, correlated with cholesterol homeostasis and amino acid degradation pathways, and its prognostic value was further validated at the protein level by our IHC cohort (P < 0.05). Conclusions This study identifies a BCAA-related plasma metabolites and gene signature as effective prognostic markers for NSCLC patients receiving immunotherapy, with HMGCS1 as a key prognostic factor influencing tumor progression and immune response.