Department of Thoracic Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Obstetrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Comb Chem High Throughput Screen. 2023;26(2):313-329. doi: 10.2174/1386207325666220318094440.
The mutated genes in lung squamous cell carcinoma were investigated for their possible association with tumor mutation burden, microsatellite instability, and cancer prognosis.
Our study aims to evaluate the value of the candidate genes as a potential biomarker of lung squamous cell carcinoma and pan-cancer analysis.
The landscape of the tumor microenvironment and infiltrating lymphocytes in lung squamous cell carcinoma was calculated using ESTIMATE and CIBERSORT algorithm. Weighed gene co-expression network analysis was used to screen key modules related to immune cell infiltration. Somatic mutations were found by data analysis from the TCGA and ICGC databases. Mann-Whitney U test was used to evaluate the tumor mutation burden difference between patients with mutant and wild-type SVEP1 genes. The Kaplan-Meier method was used to examine the prognosis of the patients with mutations. The effects of SVEP1 expression on tumor mutation burden and immunity in different cancers were determined by pan-cancer analysis.
SVEP1 mutation was found to be associated with a higher tumor mutation burden and prognosis. SVEP1 mutation might be involved in the possible biological process of the anti-tumor immune response. SVEP1 is related to different degrees of immune infiltration in cancer. Moreover, the miRNA-SVEP1 targeting network was used to illuminate the possible mechanisms.
SVEP1 mutation and its mRNA expression are related to tumor mutation burden and cancer immunity in lung squamous cell carcinoma. Our findings reveal the underlying mechanisms, indicating that SVEP1 may be a prognostic marker of lung squamous cell carcinoma.
研究肺鳞癌的突变基因，探讨其与肿瘤突变负担、微卫星不稳定性和癌症预后的关系。
本研究旨在评估候选基因作为肺鳞癌潜在生物标志物的价值和泛癌分析。
采用 ESTIMATE 和 CIBERSORT 算法计算肺鳞癌肿瘤微环境和浸润淋巴细胞的景观。通过加权基因共表达网络分析筛选与免疫细胞浸润相关的关键模块。从 TCGA 和 ICGC 数据库的数据分析中发现体细胞突变。采用 Mann-Whitney U 检验评估 SVEP1 基因突变为野生型患者的肿瘤突变负担差异。采用 Kaplan-Meier 法检验突变患者的预后。通过泛癌分析，确定 SVEP1 表达对不同癌症肿瘤突变负担和免疫的影响。
SVEP1 突变与较高的肿瘤突变负担和预后相关。SVEP1 突变可能参与抗肿瘤免疫反应的可能生物学过程。SVEP1 与癌症中不同程度的免疫浸润有关。此外，还使用 miRNA-SVEP1 靶向网络阐明了可能的机制。
SVEP1 突变及其 mRNA 表达与肺鳞癌的肿瘤突变负担和癌症免疫有关。本研究结果揭示了潜在的机制，表明 SVEP1 可能是肺鳞癌的预后标志物。
