ABSTRACT
In most cancers, forkhead box N3 (FOXN3) acts as a transcriptional inhibitor to suppress tumor proliferation, but in pancreatic cancer, the opposite effect is observed. To confirm and investigate this phenomenon, FOXN3 expression in various carcinomas was determined using GEPIA2 and was found to be highly expressed in pancreatic cancer. Kaplan-Meier plotter was then used for survival analysis, revealing that high FOXN3 expression in pancreatic cancer might be associated with a poor prognosis. Similarly, clinical samples collected for immunohistochemical staining and survival analysis showed consistent results. The RNA-seq data of pancreatic cancer patients from the TCGA were then downloaded, and the differential expression gene set was obtained using R for gene set enrichment analysis (GSEA). The intersection of the above gene sets and FOXN3-related genes was defined as related differentially expressed gene sets (DEGs), and enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, we analyzed the relationship between FOXN3 and immune infiltration in pancreatic cancer. Collectively, our findings reveal that FOXN3 is involved in the occurrence and progression of pancreatic cancer and may be useful as a prognostic tool in pancreatic cancer immunotherapy.
ABSTRACT
Background: The TGF-ß signaling pathway is clinically predictive of pan-cancer. Nevertheless, its clinical prognosis and regulation of immune microenvironment (TME) characteristics as well as the prediction of immunotherapy efficacy need to be further elucidated in head and neck squamous cell carcinoma. Method: At first, we summarized TGF-ß related genes from previous published articles, used ssGSEA to establish the TGF-ß risk score. Considering the complexity of its clinical application, we improved it with the LASSO-COX algorithm to construct the model. In addition, we explored the predictive efficacy of TGF-ß risk score in the observation of TME phenotype and immunotherapy effect. Finally, the potency of TGF-ß risk score in adjusting precise treatment of HNSC was evaluated. Results: We systematically established TGF-ß risk score with multi-level predictive ability. TGF-ß risk score was employed to predict the tumor microenvironment status, which was negatively associated with NK cells but positively related to macrophages and fibroblasts. It reveals that patients with high TGF-ß risk score predict "cold" TME status. In addition, higher risk scores indicate higher sensitivity to immunotherapy. Conclusion: We first construct and validate TGF-ß characteristics that can predict immune microenvironment phenotypes and immunotherapeutic effect in multiple datasets. Noteworthy, TGF-ß risk score is helpful for individualized precise treatment of patients with the head and neck squamous cell carcinoma.
