Liao Zhicheng, Jia Pengcheng, Li Yifan, Zheng Zhihui, Zhang Jizhou
Department of Medical Oncology, Wenzhou TCM Hospital of Zhejiang Chinese Medical University, Wenzhou, China.
Front Immunol. 2025 Jan 13;15:1464259. doi: 10.3389/fimmu.2024.1464259. eCollection 2024.
The main objective of this study was to explore and identify new genetic targets in small-cell lung cancer (SCLC) through transcriptomics analysis and Mendelian randomization (MR) analysis, which will help in the subsequent development of new therapeutic interventions.
In this study, we extracted the SCLC dataset from the Gene Expression Omnibus (GEO) database, processed the data, and screened out differentially expressed genes (DEGs) using R software. Based on expression quantitative trait loci data and the genome-wide association study data of SCLC, MR analysis was used to screen the genes closely related to SCLC disease, which intersect with DEGs to obtain co-expressed genes (CEGs), and the biological functions and pathways of CEGs were further explored by enrichment analysis. In addition, the CIBERSORT algorithm was applied to assess the level of immune cell infiltration in SCLC and to analyze the correlation between CEGs and immune cells. Meanwhile, we performed a survival analysis on these five CEGs using an independent cohort of SCLC patients. Finally, the results for the target genes were validated.
In this study, 857 DEGs were identified, including 443 up-regulated and 414 down-regulated genes, and 5 CEGs () that were significantly associated with SCLC were identified through further intersecting. The results of enrichment analyses indicated that CEGs play important roles in several key functions and pathways. Immune-cell-related analysis revealed the unique distribution of immune cell infiltration in SCLC and the mechanism of immune cell regulation by CEGs. Survival analysis results indicated that was significantly correlated with the overall survival of SCLC, and the survival rate of the high-expression group was markedly lower than that of the low-expression group. Finally, the consistency of the results between the validation group analyses and MR analysis confirmed that the results of this study is reliable.
The CEGs and their associated functions and pathways screened in this study may be potential targets of therapeutic intervention in SCLC by targeting specific molecular pathways.
本研究的主要目的是通过转录组学分析和孟德尔随机化(MR)分析来探索和鉴定小细胞肺癌(SCLC)中的新基因靶点,这将有助于后续新型治疗干预措施的开发。
在本研究中,我们从基因表达综合数据库(GEO)中提取了SCLC数据集,对数据进行处理,并使用R软件筛选出差异表达基因(DEGs)。基于SCLC的表达数量性状位点数据和全基因组关联研究数据,采用MR分析筛选与SCLC疾病密切相关的基因,将其与DEGs进行交叉以获得共表达基因(CEGs),并通过富集分析进一步探索CEGs的生物学功能和途径。此外,应用CIBERSORT算法评估SCLC中免疫细胞浸润水平,并分析CEGs与免疫细胞之间的相关性。同时,我们使用SCLC患者的独立队列对这五个CEGs进行生存分析。最后,对靶基因的结果进行验证。
在本研究中,共鉴定出857个DEGs,其中包括443个上调基因和414个下调基因,通过进一步交叉鉴定出5个与SCLC显著相关的CEGs。富集分析结果表明,CEGs在几个关键功能和途径中发挥重要作用。免疫细胞相关分析揭示了SCLC中免疫细胞浸润的独特分布以及CEGs对免疫细胞的调节机制。生存分析结果表明,[基因名称]与SCLC的总生存期显著相关,高表达组的生存率明显低于低表达组。最后,验证组分析与MR分析结果的一致性证实了本研究结果的可靠性。
本研究筛选出的CEGs及其相关功能和途径可能是通过靶向特定分子途径对SCLC进行治疗干预的潜在靶点。