Pan-cancer landscape of the RUNX protein family reveals their potential as carcinogenic biomarkers and the mechanisms underlying their action

Abstract

Abstract Background The RUNX family of transcription factors plays an important regulatory role in tumor development. Although the importance of RUNX in certain cancer types is well known, the pan-cancer landscape remains unclear. Materials and Methods Data from The Cancer Genome Atlas (TCGA) provides a pan-cancer overview of the RUNX genes. Hence, herein, we performed a pan-cancer analysis of abnormal RUNX expression and deciphered the potential regulatory mechanism. Specifically, we used TCGA multi-omics data combined with multiple online tools to analyze transcripts, genetic alterations, DNA methylation, clinical prognoses, miRNA networks, and potential target genes. Results RUNX genes are consistently overexpressed in esophageal, gastric, pancreatic, and pan-renal cancers. The total protein expression of RUNX1 in lung adenocarcinoma, kidney renal clear cell carcinoma (KIRC), and uterine corpus endometrial carcinoma (UCEC) is consistent with the mRNA expression results. Moreover, increased phosphorylation on the T14 and T18 residues of RUNX1 may represent potential pathogenic factors. The RUNX genes are significantly associated with survival in pan-renal cancer, brain lower-grade glioma, and uveal melanoma. Meanwhile, various mutations and posttranscriptional changes, including the RUNX1 D96 mutation in invasive breast carcinoma, the co-occurrence of RUNX gene mutations in UCEC, and methylation changes in the RUNX2 promoter in KIRC, may be associated with cancer development. Finally, analysis of epigenetic regulator co-expression, miRNA networks, and target genes revealed the carcinogenicity, abnormal expression, and direct regulation of RUNX genes. Conclusions We successfully analyzed the pan-cancer abnormal expression and prognostic value of RUNX genes, thereby providing potential biomarkers for various cancers. Further, mutations revealed via genetic alteration analysis may serve as a basis for personalized patient therapies.