Immune infiltration patterns and identification of new diagnostic biomarkers GDF10, NCKAP5, and RTKN2 in non-small cell lung cancer

作者：Kaiqin Chen, Chun Ye, Zihan Gao, Jue Hu, Chunjing Chen, Rong Xiao, Fangguo Lu, Ke Wei · 发表于：Translational Oncology · 年份：2023 · DOI：10.1016/j.tranon.2023.101618 · 被引用次数：19 · 研究领域：Ferroptosis and cancer prognosis、RNA modifications and cancer、Cancer-related molecular mechanisms research

This study aimed to identify potential biomarkers for non-small cell lung cancer (NSCLC) and analyze the role of immune cell infiltration in NSCLC. R software was used to screen differentially expressed genes (DEGs) from NSCLC datasets obtained from the Gene Expression Omnibus (GEO) database, and functional correlation analysis was performed. The machine learning algorithms were used to screen the potential biomarkers of NSCLC. The diagnostic values were assessed through receiver operating characteristic (ROC) curves. The protein and mRNA expression levels of potential biomarkers were verified based on the Human Protein Atlas (HPA) database and qRT-PCR. CIBERSORT was used to evaluate the infiltration of immune cells in NSCLC tissues, and the correlation between potential biomarkers and infiltrated immune cell was analyzed. Finally, specific siRNAs were utilized to reduce the GDF10, NCKAP5, and RTKN2 expression in A549 and H1975 cells. The proliferation ability of A549 and H1975 cells was detected by MTT assay. A total of 848 upregulated DEGs and 1308 downregulated DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that the DEGs were mainly related to cell division. Disease ontology (DO) enrichment analysis showed that the diseases with these DEGs were mainly lung diseases, including NSCLC. In addition,three potential biomarkers were identified: GDF10, NCKAP5, and RTKN2. Immune cell infiltration analysis showe...