Discover oncology · 2026
Integrative multi-omics identifies a glycosylation-based prognostic framework and nominates ALG3 for targeted therapy in bladder cancer.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Feng Wubing, He Weiyang
Аннотация
BACKGROUND: Bladder urothelial carcinoma (BLCA) exhibits heterogeneous outcomes, creating an urgent need for reliable prognostic biomarkers. Glycosylation modifications are crucial in cancer but understudied for BLCA stratification.
METHODS: Using clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) and glycosylation-related genes from the Gene Set Enrichment Analysis (GSEA) database, we constructed a prognostic signature via LASSO regression. It was validated using receiver operating characteristic (ROC) curve and stratified survival analyses. The key gene, alpha-1,3-mannosyltransferase (ALG3), was experimentally validated.
RESULTS: A novel 9-glycosylation-mRNA signature effectively stratified BLCA patients into distinct risk groups with significant overall survival differences. The model showed robust predictive accuracy (AUC) and remained independent of common clinicopathological factors. We identified ALG3 as central to the signature, confirming its elevated tumor expression and critical role in promoting cancer cell proliferation.
CONCLUSION: We established a potent, glycosylation-based prognostic model for BLCA. Functional validation of ALG3 underscores glycosylation's biological importance in tumor progression and highlights its therapeutic potential.
METHODS: Using clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) and glycosylation-related genes from the Gene Set Enrichment Analysis (GSEA) database, we constructed a prognostic signature via LASSO regression. It was validated using receiver operating characteristic (ROC) curve and stratified survival analyses. The key gene, alpha-1,3-mannosyltransferase (ALG3), was experimentally validated.
RESULTS: A novel 9-glycosylation-mRNA signature effectively stratified BLCA patients into distinct risk groups with significant overall survival differences. The model showed robust predictive accuracy (AUC) and remained independent of common clinicopathological factors. We identified ALG3 as central to the signature, confirming its elevated tumor expression and critical role in promoting cancer cell proliferation.
CONCLUSION: We established a potent, glycosylation-based prognostic model for BLCA. Functional validation of ALG3 underscores glycosylation's biological importance in tumor progression and highlights its therapeutic potential.