Currently, breast cancer (BRCA) has become the most common cancer in the world, whose pathological mechanism is complex. Among its subtypes, triple-negative breast cancer (TNBC) has the worst prognosis. With the increasing number of diagnosed TNBC patients, the urgent need of novel biomarkers is also rising. Cyclin-dependent kinase inhibitor 2A (CDKN2A) has recently emerged as a key regulator associated with ferroptosis and cuproptosis (FAC) and has exhibited a significant effect on BRCA, but its detailed mechanism remains elusive. Herein, we conducted the first converge comprehensive landscape analysis of FAC-related gene CDKN2A in BRCA and disclosed its prognostic value in BRCA. Then, an unsupervised cluster analysis based on CDKN2A-correlated genes unveiled three subtypes, namely cold-immune subtype, IFN-γ activated subtype and FTL-dominant subtype. Subsequent analyses depicting hallmarks of tumor microenvironment (TME) among three subtypes suggested strong association between TNBC and CDKN2A. Given the fact that the most clinically heterogeneous TNBC always displayed the most severe outcomes and lacked relevant drug targets, we further explored the potential of immunotherapy for TNBC by interfering CDKN2A and constructed the CDKN2A-derived prognostic model for TNBC patients by Lasso-Cox. The 21-gene–based prognostic model showed high accuracy and was verified in external independent validation cohort. Moreover, we proposed three drugs for TNBC patients based on our model via targeting epidermal growth factor receptor. In summary, our study indicated the potential of CDKN2A as a pioneering prognostic predictor for TNBC and provided a rationale of immunotherapy for TNBC, and offered fresh perspectives and orientations for cancer treatment via inducing ferroptosis and cuproptosis to develop novel anti-cancer treatment strategies.
Intratumoral heterogeneity is a characteristic of glioblastomas that contain an intermixture of cell populations displaying different glioblastoma subtype gene expression signatures. Proportions of these populations change during tumor evolution, but the occurrence and regulation of glioblastoma subtype transition is not well described. To identify regulators of glioblastoma subtypes we utilized a combination of in vitro experiments and in silico analyses, using experimentally generated as well as publicly available data. Through this combined approach SOX2 was identified to confer a proneural glioblastoma subtype gene expression signature. SFRP2 was subsequently identified as a SOX2-antagonist, able to induce a mesenchymal glioblastoma subtype signature. A subset of patient glioblastoma samples with high SFRP2 and low SOX2 expression was particularly enriched with mesenchymal subtype samples. Phenotypically, SFRP2 decreased tumor sphere formation, stemness as assessed by limiting dilution assay, and overall cell proliferation but increased cell motility, whereas SOX2 induced the opposite effects. Furthermore, an SFRP2/non-canonical-WNT/KLF4/PDGFR/phospho-AKT/SOX2 signaling axis was found to be involved in the mesenchymal transition. Analysis of human tumor tissue spatial gene expression patterns showed distinct expression of SFRP2- and SOX2-correlated genes in vascular and cellular areas, respectively. Finally, conditioned media from SFRP2 overexpressing cells increased CD206 on macrophages. Together, these findings present SFRP2 as a SOX2-antagonist with the capacity to induce a mesenchymal subtype transition in glioma cells located in vascular tumor areas, highlighting its role in glioblastoma tumor evolution and intratumoral heterogeneity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.