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 (, , , , , and ) 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 and 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.