Lung adenocarcinoma (LUAD) is one of the most common forms of lung cancer, with a very high mortality rate. Although the treatments available for LUAD have become more effective in recent years, significant improvement is still needed. Advances in sequencing technologies and bioinformatics analysis have enabled new approaches to be developed for identifying drug targets. In this work we utilized data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify hub genes related to LUAD through Weighted Gene Correlation Network Analysis (WGCNA) and other bioinformatics methods, with the goal of identifying new drug targets for cancer treatment.

中文翻译：

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综合生物信息学方法鉴定与分析肺腺癌相关基因

肺腺癌 (LUAD) 是最常见的肺癌形式之一，死亡率非常高。尽管近年来可用于 LUAD 的治疗方法变得更加有效，但仍需要显着改进。测序技术和生物信息学分析的进步使得开发新的药物靶标方法成为可能。在这项工作中，我们利用来自癌症基因组图谱 (TCGA) 和基因表达综合 (GEO) 数据库的数据，通过加权基因相关网络分析 (WGCNA) 和其他生物信息学方法识别与 LUAD 相关的枢纽基因，目的是识别新药癌症治疗的靶点。