Objective  To screen genes associated with laryngeal cancer using tumor stemness index (mRNAsi), in order to provide new ideas for laryngeal cancer research.

Methods  Laryngeal cancer mRNA expression profile was downloaded from The Cancer Genome Atlas (TCGA) database, weighted gene co-expression network analysis (WGCNA) was used to construct gene co-expression network module, and the differential genes of the most significant dry module were obtained. Cox regression and least absolute shrinkage and selection operator (LASSO) algorithms were used to establish risk curves, single sample gene set enrichment analysis (ssGSEA) was then used to explore the immune infiltration pattern of intersected genes based on Tumor Immune Dysfunction and Exclusion (TIDE) database, and CellMiner database was used to analyze gene drug sensitivity. Gene set enrichment analysis (GSEA) was used to enrich the functions and signaling pathways of key genes involved in laryngeal cancer.

Results  A total of 30 laryngeal cancer co-expression gene modules were constructed by WGCNA, and the light yellow and purple co-expression modules were selected for Cox regression analysis. LASSO algorithm constructed a model to screen MTHFD2 and TBX2 genes, and constructed a risk curve, which were associated with plasmacytoid dendritic cell precursors (pDCs) and T helper 2 cell (Th2) immune cells. TIDE in low-risk group was significantly higher than that in high-risk group, and dasatinib was associated with increased gene resistance. Functional enrichment showed that key genes may be related to keratinocytes.

Conclusion  MTHFD2 and TBX2 genes can be used as biomarkers of laryngeal cancer mRNAsi.

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