基于整合生物信息学分析鉴定与肺鳞状细胞癌相关的新型生物标志物。

Identification of Novel Biomarkers Related to Lung Squamous Cell Carcinoma Using Integrated Bioinformatics Analysis.

机构信息

Department of Ultrasonography Center, Tai'an City Central Hospital, Tai'an, China.

Department of Thoracic Surgery, Shenzhen Bao'an People's Hospital (Group), Shenzhen, China.

出版信息

Comput Math Methods Med. 2021 Oct 8;2021:9059116. doi: 10.1155/2021/9059116. eCollection 2021.

DOI:10.1155/2021/9059116

PMID:34659450

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8519687/

Abstract

BACKGROUND

Lung squamous cell carcinoma (LUSC) is one of the most common types of lung carcinoma and has specific clinicopathologic characteristics. In this study, we screened novel molecular biomarkers relevant to the prognosis of LUSC to explore new diagnostic and treatment approaches for this disease.

METHODS

We downloaded GSE73402 from the Gene Expression Omnibus (GEO) database. GSE73402 contains 62 samples, which could be classified as four subtypes according to their pathology and stages. Via weighted gene coexpression network analysis (WGCNA), the main module was identified and was further analyzed using differentially expressed genes (DEGs) analysis. Then, by protein-protein interaction (PPI) network and Gene Expression Profiling Interactive Analysis (GEPIA), hub genes were screened for potential biomarkers of LUSC.

RESULTS

Via WGCNA, the yellow module containing 349 genes was identified, and it is strongly related to the subtype of CIS (carcinoma in situ). DEGs analysis detected 180 genes that expressed differentially between the subtype of CIS and subtype of early-stage carcinoma (Stage I and Stage II). A PPI network of DEGs was constructed, and the top 20 genes with the highest correlations were selected for GEPIA database to explore their effect on LUSC survival prognosis. Finally, ITGA5, TUBB3, SCNN1B, and SERPINE1 were screened as hub genes in LUSC.

CONCLUSIONS

ITGA5, TUBB3, SCNN1B, and SERPINE1 may have great diagnostic and prognostic significance for LUSC and have great potential to be new treatment targets for LUSC.

摘要

背景

肺鳞状细胞癌（LUSC）是最常见的肺癌类型之一，具有特定的临床病理特征。在本研究中，我们筛选了与 LUSC 预后相关的新型分子生物标志物，以探索该疾病的新诊断和治疗方法。

方法

我们从基因表达综合（GEO）数据库中下载了 GSE73402。GSE73402 包含 62 个样本，根据其病理和分期可分为四个亚型。通过加权基因共表达网络分析（WGCNA），确定了主要模块，并进一步通过差异表达基因（DEGs）分析进行了分析。然后，通过蛋白质-蛋白质相互作用（PPI）网络和基因表达谱交互式分析（GEPIA），筛选出 LUSC 的潜在生物标志物的核心基因。

结果

通过 WGCNA，鉴定出包含 349 个基因的黄色模块，与原位癌（CIS）亚型密切相关。DEGs 分析检测到 CIS 亚型和早期癌（I 期和 II 期）亚型之间表达差异的 180 个基因。构建了 DEGs 的 PPI 网络，选择前 20 个相关性最高的基因在 GEPIA 数据库中进行探索，以研究它们对 LUSC 生存预后的影响。最后，筛选出 ITGA5、TUBB3、SCNN1B 和 SERPINE1 作为 LUSC 的核心基因。