Comprehensive pan-cancer analysis of STAT3 as a prognostic and immunological biomarker

Abstract

Numerous studies have indicated that STAT3 plays a key role in promoting oncogenesis and it is considered a potential therapeutic target for cancer treatment; however, there are no reports on STAT3 using pan-cancer analysis. Therefore, it is important to investigate the role of STAT3 in different types of tumors using pan-cancer analysis. In the present study, we used multiple databases to comprehensively analyze the relationship between STAT3 expression and prognosis, different stages of patients with cancer, investigate the clinical value of STAT3 in predicting prognosis, and the relationship between STAT3 genetic alteration and prognosis, drug sensitivity, and STAT3 expression, to determine whether STAT3 participates in tumor immunity, to provide a rationale for STAT3 as a treatment target for a broad-spectrum malignancies. Our results indicate that STAT3 can serve as a prognostic, sensitivity prediction biomarker and a target for immunotherapy, which has been of great value for pan-cancer treatment. Overall, we found that STAT3 significantly predicted cancer prognosis, drug resistance, and immunotherapy, providing a rationale for further experimental studies.

Case Report: Identification of a novel STAT3 mutation in EBV-positive inflammatory follicular dendritic cell sarcoma

“…These genes serve as transcription factors that regulate the activation or inhibition of target genes by binding to their regulatory regions. STAT3 specifically plays a significant role in cell proliferation, migration, and apoptosis, and it interacts with Janus kinases (JAKs), epidermal growth factor receptor (EGFR), and interleukin 6 (IL6) ( 21 ).…”

Investigating Torsin‐1A‐interacting protein 1 as a predictive and immunological biomarker in cancer

“…In the "multiple proteins" box, TOR1AIP1 was used as the input query and "Homo sapiens" was selected as the species. To further refine the analysis, other parameters were changed which included (a) meaning of network edges: "evidence", (b) active interaction sources: "Experiments", (c) minimum required interaction score: "low confidence 0.15" and (d) max number of interactors to show "no more than 50 interactors" [24,25]. The cBioPortal database (https://www.cbioportal.org/) was used to study the gene alterations in TOR1AIP1.…”

“…The "Mutations" module presented detailed information on the specific sites that were mutated. While the "Cancer Types Summary" displayed the alteration frequency in different types of cancer [24,26,27].…”

“…The GEPIA database, accessible at http://gepia.cancerpku.cn/index.html, was utilized for the analysis of overall survival and disease-free survival in cancer patients [23,24]. The TOR1AIP1 gene was added as an input with the Cutoff-High (%) and Cutoff-Low (%) parameters set to 50, with 95% confidence interval for the analysis.…”

“…The TOR1AIP1 gene was added as an input with the Cutoff-High (%) and Cutoff-Low (%) parameters set to 50, with 95% confidence interval for the analysis. This approach allowed for the investigation of the potential association between TOR1AIP1 expression levels and patient survival outcomes in various types of cancer [23,24].…”