Development and Validation of a Centrosome Amplification-Related Prognostic Model in Pancreatic Cancer: Multi-Omics Guided Risk Stratification and Tumor Microenvironment

胰腺癌中心体扩增相关预后模型的开发与验证:多组学指导的风险分层和肿瘤微环境

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Abstract

Background: Centrosome amplification, a hallmark of cell cycle dysregulation, drives carcinogenesis through aneuploidy induction and invasive phenotype acquisition. In pancreatic adenocarcinoma-a malignancy characterized by profound genomic instability-the molecular circuitry of centrosome amplification remains enigmatic. Critical gaps persist in understanding its spatiotemporal dynamics in tumor microenvironment remodeling and therapy resistance. Methods: This study integrated centrosome amplification-related genes from TCGA and Genecards, established a prognostic risk model through univariate Cox regression-LASSO penalized Cox regression-multivariate Cox regression analyses, and validated it using GEO datasets. Single-cell sequencing analyses dissected transcriptional heterogeneity and intercellular communication networks, while spatially resolved transcriptomics unveiled spatiotemporal expression patterns and molecular regulatory mechanisms of core genes. With further experimental validation via PCR analysis of patient-derived tissue samples confirming key gene expression patterns. Results: This study identified 23 centrosome amplification-related prognostic genes in pancreatic adenocarcinoma, establishing IFI27, KIF20A, KLK10, SPINK7, and TOP2A as highly specific diagnostic and prognostic biomarkers. The constructed signature was established as an independent prognostic indicator correlating with aggressive clinicopathological characteristics and chemoresistance. Mechanistically linked to enhanced DNA repair capacity and accelerated cell cycle progression, also synergizes with KRAS mutational profiles. Tumor microenvironment analysis revealed significant associations with immunosuppressive. Single-cell resolution demonstrated cellular specificity of IFI27/KLK10 in ductal epithelial cells and fibroblasts, with intercellular communication networks exhibiting multidimensional regulatory features. Spatially resolved transcriptomics delineated tumor-region-specific expression patterns of core genes. While PCR validation on matched tumor/normal tissues confirmed significant differential expression of IFI27, KIF20A, KLK10, and TOP2A. Conclusions: This study deciphers the multidimensional clinic-molecular network orchestrated by centrosome amplification in PDAC, revealing its dual-pathogenic mechanism in fueling tumor aggressiveness through coordinated induction of genomic instability and immunosuppressive microenvironment reprogramming. These findings establish a translational framework for developing centrosome dynamics-based prognostic stratification and molecularly targeted therapeutic strategies.

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