{"title":"单细胞分辨率下肺腺癌转移代谢驱动基因的鉴定和靶向药物筛选。","authors":"Liang Wu, Wenjuan Zhao, Xin Guo, Zuquan Hu, Sen Chen, Wenzhu Huang","doi":"10.21037/tcr-2025-484","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Lung adenocarcinoma (LUAD) is the predominant type of lung cancer, and metastasis is a major cause of poor prognosis and death. Metabolic activation is a crucial factor driving tumor metastasis; however, the metabolic heterogeneity at the single-cell level presents significant challenges in targeting metabolism-related genes for treatment. This study aimed to decode the metabolic drivers in tumor metastasis progression to optimize LUAD prognosis prediction and screen specific targeted drugs.</p><p><strong>Methods: </strong>In this study, we determined that the metabolic activation of tumor and immune cells in the microenvironment is significantly altered during LUAD metastasis. Simultaneously, we identify pivotal metabolic driver genes (MDGs) based on single-cell RNA-sequencing (scRNA-seq) data, which could serve as targets for targeted therapy. We then constructed a novel prognostic risk model based on MDGs and validated its excellent predictive performance in independent datasets. Using the non-negative matrix factorization (NMF) algorithm, we classify LUAD molecular subtypes into three clusters according to MDGs and evaluate their association with prognosis and clinical characteristics.</p><p><strong>Results: </strong>We screened a panel of 307 drugs targeting MDGs and confirmed the efficacy of cholic acid, as a representative compound from the screened panel, in inhibiting the migration of LUAD cells.</p><p><strong>Conclusions: </strong>Our research provides potential targets and candidate drug for targeting metabolic-related genes in metastatic LUAD treatment.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"14 8","pages":"4774-4790"},"PeriodicalIF":1.7000,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432774/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification of metabolic driver genes and targeted drug screening for lung adenocarcinoma metastasis at the single-cell resolution.\",\"authors\":\"Liang Wu, Wenjuan Zhao, Xin Guo, Zuquan Hu, Sen Chen, Wenzhu Huang\",\"doi\":\"10.21037/tcr-2025-484\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Lung adenocarcinoma (LUAD) is the predominant type of lung cancer, and metastasis is a major cause of poor prognosis and death. Metabolic activation is a crucial factor driving tumor metastasis; however, the metabolic heterogeneity at the single-cell level presents significant challenges in targeting metabolism-related genes for treatment. This study aimed to decode the metabolic drivers in tumor metastasis progression to optimize LUAD prognosis prediction and screen specific targeted drugs.</p><p><strong>Methods: </strong>In this study, we determined that the metabolic activation of tumor and immune cells in the microenvironment is significantly altered during LUAD metastasis. Simultaneously, we identify pivotal metabolic driver genes (MDGs) based on single-cell RNA-sequencing (scRNA-seq) data, which could serve as targets for targeted therapy. We then constructed a novel prognostic risk model based on MDGs and validated its excellent predictive performance in independent datasets. Using the non-negative matrix factorization (NMF) algorithm, we classify LUAD molecular subtypes into three clusters according to MDGs and evaluate their association with prognosis and clinical characteristics.</p><p><strong>Results: </strong>We screened a panel of 307 drugs targeting MDGs and confirmed the efficacy of cholic acid, as a representative compound from the screened panel, in inhibiting the migration of LUAD cells.</p><p><strong>Conclusions: </strong>Our research provides potential targets and candidate drug for targeting metabolic-related genes in metastatic LUAD treatment.</p>\",\"PeriodicalId\":23216,\"journal\":{\"name\":\"Translational cancer research\",\"volume\":\"14 8\",\"pages\":\"4774-4790\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12432774/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational cancer research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.21037/tcr-2025-484\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/8/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational cancer research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.21037/tcr-2025-484","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/28 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"ONCOLOGY","Score":null,"Total":0}
Identification of metabolic driver genes and targeted drug screening for lung adenocarcinoma metastasis at the single-cell resolution.
Background: Lung adenocarcinoma (LUAD) is the predominant type of lung cancer, and metastasis is a major cause of poor prognosis and death. Metabolic activation is a crucial factor driving tumor metastasis; however, the metabolic heterogeneity at the single-cell level presents significant challenges in targeting metabolism-related genes for treatment. This study aimed to decode the metabolic drivers in tumor metastasis progression to optimize LUAD prognosis prediction and screen specific targeted drugs.
Methods: In this study, we determined that the metabolic activation of tumor and immune cells in the microenvironment is significantly altered during LUAD metastasis. Simultaneously, we identify pivotal metabolic driver genes (MDGs) based on single-cell RNA-sequencing (scRNA-seq) data, which could serve as targets for targeted therapy. We then constructed a novel prognostic risk model based on MDGs and validated its excellent predictive performance in independent datasets. Using the non-negative matrix factorization (NMF) algorithm, we classify LUAD molecular subtypes into three clusters according to MDGs and evaluate their association with prognosis and clinical characteristics.
Results: We screened a panel of 307 drugs targeting MDGs and confirmed the efficacy of cholic acid, as a representative compound from the screened panel, in inhibiting the migration of LUAD cells.
Conclusions: Our research provides potential targets and candidate drug for targeting metabolic-related genes in metastatic LUAD treatment.
期刊介绍:
Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.