Exploring effective biomarkers and potential immune related gene in small cell lung cancer.

Small cell lung cancer (SCLC) is well known as a highly malignant neuroendocrine tumor. Immunotherapy combined with chemotherapy has become a standard treatment for extensive SCLC. However, since most patients quickly develop resistance and relapse, finding new therapeutic targets for SCLC is important. We obtained four microarray datasets from the Gene Expression Omnibus database and screened differentially expressed genes by two methods: batch correction and "RobustRankAggregation". After the establishment of a protein-protein interaction network through Cytoscape, seven hub genes (AURKB, BIRC5, TOP2A, TYMS, PCNA, UBE2C, and AURKA) with high expression in SCLC samples were obtained by eight CytoHubba algorithms. The Least Absolute Shrinkage and Selection Operator regression and the Wilcoxon test were used to analyze the differences in the immune cells' infiltration between normal and SCLC samples. The contents of seven kinds of immune cells were considered to differ significantly between SCLC samples and normal samples. A negative association was found between BIRC5 and monocytes in the correlation analysis between immune cells and the seven hub genes. The subsequent in vitro validation of experimental results showed that downregulating the expression of BIRC5 by siRNA can promote apoptotic activity of SCLC cells and inhibit their vitality, migration, and invasion. The use of BIRC5 inhibitor inhibited the vitality of SCLC cells and increased their apoptotic activity. BIRC5 may be a novel therapeutic target option for SCLC.

Integrative Analysis of Ferroptosis-Related Genes in Small Cell Lung Cancer for the Identification of Biomarkers and Therapeutic Targets.

BACKGROUND: Ferroptosis is an iron-dependent programmed cell death mode induced by the toxic buildup of phospholipid peroxidation. Although it is known to affect the initiation and growth of tumors, the association between ferroptosis-related genes (FRGs) and small cell lung cancer (SCLC) has yet to be established. METHODS: We used the gene expression omnibus (GEO) and ferroptosis database (FerrDb) to acquire information on SCLC and its associated FRGs. Marker genes were subsequently identified using Least Absolute Shrinkage and Selection Operator (LASSO) and support vector machine recursive feature eilmination (SVM-RFE) algorithms and analyzed for single-gene function and pathway enrichment. Using the drug-gene interaction database (DGIdb), we identified forty drugs targeting six marker genes. The competing endogenous RNA (ceRNA) network revealed the regulation pattern for long non-coding RNA (LncRNA)-microRNA (miRNA)-messenger RNA (mRNA) based on marker genes. RESULTS: Six differentially expressed FRGs (ATG3, MUC1, RRM2, IDH2, PARP1, and EZH2) were identified as marker genes with accurate diagnostic capabilities. According to single-gene function and pathway enrichment analyses, these marker genes may be involved in immunomodulation and the cell cycle, as well as numerous pathways connected to tumorigenesis, including the JAK-STAT and PPAR signal pathways. In addition, CIBERSORT analysis showed that MUC1 and PARP1 expression may affect the immune microenvironment in SCLC. CONCLUSIONS: We confirmed the accuracy of marker genes for the diagnosis of SCLC using a logistic regression model, thus providing further opportunities to study SCLC-related mechanisms. The accuracy of these results for the diagnosis of SCLC must now be confirmed by further research prior to clinical application.