{"title":"Multidimensional characterization of the tumor microenvironment profiles in lung squamous cell carcinoma.","authors":"Yi Zhou, Lixun Chai, Yuyao Wang, Hongguang Zhang","doi":"10.1152/physiolgenomics.00042.2025","DOIUrl":null,"url":null,"abstract":"<p><p>Tumor microenvironment (TME) plays an important role in tumorigenesis, development, metastasis, and drug sensitivity, but little is known about it in lung squamous cell carcinoma (LUSC). Here, the RNA-sequencing data, clinical and survival data of patients with LUSC in The Cancer Genome Atlas, and six independent datasets were collected. Based on the unsupervised clustering of knowledge-based functional gene expression signatures, LUSC was classified into four subtypes. <i>Cluster 1</i> and <i>cluster 3</i> exhibited substantial tumor immune infiltration, suggesting a better response to immunotherapy. Relatively worse survival was observed in <i>cluster 4</i>, probably due to higher angiogenesis. Besides, differentially expressed genes in <i>cluster 1</i>, <i>cluster 2</i>, and <i>cluster 3</i> were prominently enriched in immune-related pathways, whereas extracellular matrix-related pathways were enriched for <i>cluster 4</i>. Genomic data analyses showed significant variations in tumor mutational burden and mutational frequency of several genes, such as tumor protein P53 (<i>TP53</i>), among the four subtypes. In addition, the four subtypes exhibited heterogeneity in the sensitivity of commonly used chemotherapy drugs for lung cancer and the intratumor microbiome profile. Finally, a prognostic model was developed, and its performance and generalization ability were independently validated in multiple datasets. Overall, our study advances the understanding of the TME in LUSC and proposes a prognostic model that facilitates clinical decision-making.<b>NEW & NOTEWORTHY</b> This study obtained four immunological subtypes exhibiting substantial difference in the tumor microenvironment (TME), immune-related pathways, tumor mutational burden, drug sensitivity, and intratumor microbiome. Furthermore, we developed a novel prognostic model consisting of 11 signature genes showing excellent performance in predicting prognosis. Our study deepens the understanding of the heterogeneity of the TME in lung squamous cell carcinoma (LUSC) and contributes to the precision therapy of patients with LUSC.</p>","PeriodicalId":20129,"journal":{"name":"Physiological genomics","volume":" ","pages":"485-497"},"PeriodicalIF":2.5000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physiological genomics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1152/physiolgenomics.00042.2025","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/6/25 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Tumor microenvironment (TME) plays an important role in tumorigenesis, development, metastasis, and drug sensitivity, but little is known about it in lung squamous cell carcinoma (LUSC). Here, the RNA-sequencing data, clinical and survival data of patients with LUSC in The Cancer Genome Atlas, and six independent datasets were collected. Based on the unsupervised clustering of knowledge-based functional gene expression signatures, LUSC was classified into four subtypes. Cluster 1 and cluster 3 exhibited substantial tumor immune infiltration, suggesting a better response to immunotherapy. Relatively worse survival was observed in cluster 4, probably due to higher angiogenesis. Besides, differentially expressed genes in cluster 1, cluster 2, and cluster 3 were prominently enriched in immune-related pathways, whereas extracellular matrix-related pathways were enriched for cluster 4. Genomic data analyses showed significant variations in tumor mutational burden and mutational frequency of several genes, such as tumor protein P53 (TP53), among the four subtypes. In addition, the four subtypes exhibited heterogeneity in the sensitivity of commonly used chemotherapy drugs for lung cancer and the intratumor microbiome profile. Finally, a prognostic model was developed, and its performance and generalization ability were independently validated in multiple datasets. Overall, our study advances the understanding of the TME in LUSC and proposes a prognostic model that facilitates clinical decision-making.NEW & NOTEWORTHY This study obtained four immunological subtypes exhibiting substantial difference in the tumor microenvironment (TME), immune-related pathways, tumor mutational burden, drug sensitivity, and intratumor microbiome. Furthermore, we developed a novel prognostic model consisting of 11 signature genes showing excellent performance in predicting prognosis. Our study deepens the understanding of the heterogeneity of the TME in lung squamous cell carcinoma (LUSC) and contributes to the precision therapy of patients with LUSC.
期刊介绍:
The Physiological Genomics publishes original papers, reviews and rapid reports in a wide area of research focused on uncovering the links between genes and physiology at all levels of biological organization. Articles on topics ranging from single genes to the whole genome and their links to the physiology of humans, any model organism, organ, tissue or cell are welcome. Areas of interest include complex polygenic traits preferably of importance to human health and gene-function relationships of disease processes. Specifically, the Journal has dedicated Sections focused on genome-wide association studies (GWAS) to function, cardiovascular, renal, metabolic and neurological systems, exercise physiology, pharmacogenomics, clinical, translational and genomics for precision medicine, comparative and statistical genomics and databases. For further details on research themes covered within these Sections, please refer to the descriptions given under each Section.