10.3390/polym8030084

Vollständiger Abstract

Worum geht es in dieser Arbeit?

<h4>Background</h4>Cellular senescence exerts a complex influence on BRCA progression and TME remodeling. However, the specific roles of ASIGs in regulating the TME and determining patient outcomes remain unclear.<h4>Methods</h4>Using TCGA (training), METABRIC (validation), and single-cell RNA-seq datasets, we systematically characterized ASIGs in BRCA. Prognostic ASIGs were identified to define molecular subtypes and construct a 17-gene LASSO-Cox risk model, which was integrated with clinical factors to develop a prognostic nomogram. Microenvironmental features and cell-cell communication networks were deconstructed using computational deconvolution and single-cell algorithms (SCISSOR and CellChat).<h4>Results</h4>We established a robust 17-gene ASIG-based prognostic signature that effectively stratified BRCA patients into high- and low-risk groups and served as an independent prognostic predictor (HR = 3.94, <i>p</i> < 0.001). The nomogram accurately predicted 1-, 3-, and 5-year overall survival. Notably, the two risk groups exhibited strikingly distinct TME landscapes. The low-risk group was characterized by a coordinated, B cell-centric immune network, whereas the high-risk group displayed T cell exhaustion and immunosuppressive myeloid infiltration.<h4>Conclusions</h4>The ASIG-based prognostic risk model is independent of traditional clinicopathological factors, providing a robust tool for patient risk stratification and offering biological insights into senescence-driven microenvironmental remodeling.

Abstract: PubMed · Datensatz