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Abstract <p>This study was aimed to identify prognostic genes in the tumor microenvironment (TME) of lung squamous cell carcinoma (LUSC). The LUSC transcriptome data were downloaded from the TCGA and GEO databases. The immune and stromal scores as well as tumor purity of LUSC samples were analyzed. The differentially expressed genes (DEGs) in high vs. low stromal score and high vs. low immune score were respectively screened. The important TME-related genes were screened using univariate/multivariate cox regression, and LASSO regression analyses. The correlation of important TME-related genes and immune microenvironment was analyzed. Finally, the important TME-related genes were validated through GEO dataset and clinical samples. The LUSC samples with low estimate, immune and stromal scores, and high purity score had better prognosis. 1241 and 798 DEGs were respective lyscreened in two groups, with 642&#xa0;intersection DEGs. Pathway analysis identified cytokine-cytokine receptor interaction as the most significantly correlated pathway. From these intersection genes, <i>STARD6</i>, <i>FGA</i>, <i>TRIM58</i> and <i>HPR</i> were considered prognosis-correlated important TME-related genes. High expression of <i>STARD6</i> had a better prognosis, while low expression of <i>FGA</i>, <i>TRIM58</i> and <i>HPR</i> had a better prognosis. <i>STARD6</i> was upregulated in tumors, while <i>FGA</i>, <i>TRIM58</i> and <i>HPR</i> were downregulated in tumors. TME may be related with cancer progression and prognosis of patients in LUSC. Immune and stromal scores-based genes may serve as treatment biomarkers for LUSC.</p>

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Identification of Prognostic Genes in the Tumor Microenvironment of Lung Squamous Cell Carcinoma

  • 期刊论文

  • 发表日期：

    2025年1月1日

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  • J. Ding,
  • Sh. Wang,
  • J. Ning,
  • N. Sun

摘要

Abstract

This study was aimed to identify prognostic genes in the tumor microenvironment (TME) of lung squamous cell carcinoma (LUSC). The LUSC transcriptome data were downloaded from the TCGA and GEO databases. The immune and stromal scores as well as tumor purity of LUSC samples were analyzed. The differentially expressed genes (DEGs) in high vs. low stromal score and high vs. low immune score were respectively screened. The important TME-related genes were screened using univariate/multivariate cox regression, and LASSO regression analyses. The correlation of important TME-related genes and immune microenvironment was analyzed. Finally, the important TME-related genes were validated through GEO dataset and clinical samples. The LUSC samples with low estimate, immune and stromal scores, and high purity score had better prognosis. 1241 and 798 DEGs were respective lyscreened in two groups, with 642 intersection DEGs. Pathway analysis identified cytokine-cytokine receptor interaction as the most significantly correlated pathway. From these intersection genes, STARD6, FGA, TRIM58 and HPR were considered prognosis-correlated important TME-related genes. High expression of STARD6 had a better prognosis, while low expression of FGA, TRIM58 and HPR had a better prognosis. STARD6 was upregulated in tumors, while FGA, TRIM58 and HPR were downregulated in tumors. TME may be related with cancer progression and prognosis of patients in LUSC. Immune and stromal scores-based genes may serve as treatment biomarkers for LUSC.