Pan-cancer analysis reveals signal transducer and activator of transcription (STAT) gene family as biomarkers for prognostic prediction and therapeutic guidance

Background: The signal transducer and activator of transcription (STAT) gene family have been widely found to regulate cell proliferation, differentiation, apoptosis, and angiogenesis through complex signaling pathways, and thus impacting tumor formation and development in different types of tumor. However, the roles of STATs on prognostic prediction and therapeutic guidance in pan-cancer remain unexplored. Materials and Methods: The dataset of 33 types of TCGA tumor, para-carcinoma and normal tissues, was obtained from the UCSC Xena database, including the gene expression profiles in the formats of FPKM value, demographic characteristics, clinical information, and survival data of STATs. Differential expression and co-expression analyses, WGCNA, clinical relevance analysis, immune subtype analysis, tumor stemness analysis, tumor purity analysis, immune infiltration analysis, immunotherapy related analysis, tumor mutation related analysis, and drug sensitivity analysis were performed by R software. Results: Differential expression of STAT1 was found between normal and BRCA tissues (p < 0.001, log2FC = 0.895). Additionally, the strongest correlation among STATs lied between STAT1 and STAT2 (correlation coefficient = 0.6). Moreover, high expression levels of STAT1 (p = 0.031) were revealed to be notably correlated with poor prognosis in KIRP. In addition, STAT1 expressed the highest value in immune subtypes C1, C2, C3, and C6 in LUAD. What’s more, strong negative correlations were demonstrated between expression of STAT6 and mDNAss and mRNAss of TGCT. Additionally, STAT4 expression was characterized to be significantly negatively correlated with tumor purity of the majority of cancer types. Moreover, STAT1 and STAT3 were shown to be generally high-expressed in pan-cancer myeloid cells, and STATs all had positive correlation with the infiltration of the majority of immune cells. In addition, STATs were revealed to be closely linked with immunotherapy response. What’s more, STAT4 expression was identified to have a strong negative correlation with TMB value in DLBC. Last but not least, positive correlations were accessed between STAT5 and sensitivity of Nelarabine (cor = 0.600, p < 0.001). Conclusion: In the present study, we identified STATs as biomarkers for prognostic prediction and therapeutic guidance in pan-cancer. Hopefully our findings could provide a valuable reference for future STATs research and clinical applications.