Gene · 2026
Development of a gene signature related to phospholipid metabolism for prognosis and therapeutic Prediction in Osteosarcoma: Focus on VAC14.
СтатьяНазвание и аннотация: Перевод в очереди
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.
Liang Yihui, Ba Yiwen, Zhou Qiwei, Xuan Jiangwei, Ni Wenfei, Wu Chenyu, Zhan Jingdi
Аннотация
BACKGROUND: Osteosarcoma is the malignant bone neoplasm affecting pediatric and adolescent with unsatisfactory five-year survival. Dysregulated phospholipid metabolism is crucial for membrane integrity, signaling, and energy homeostasis, contributinga range of cancers' progression. Nevertheless, itsrolein osteosarcoma persists uncertain. The investigation aims to identify phospholipid metabolism-related signature genes for osteosarcoma and evaluate their prognostic value and therapeutic potential.
METHODS: The data curated from the TARGET and GEO databases. Differential expression analysis, LASSO, and SVM-RFE screened feature genes. A Cox regression-based prognostic model was established and validated internally (survival analysis, ROC) and externally, assessing discrimination and calibration. Analyses of the tumor microenvironment composition, immunocyte infiltration, and drug sensitivity and key findings were validatedin vitro.
RESULTS: A risk model incorporating seven prognostic genes was constructed and confirmed using univariate Cox regression. High-risk patients showed markedly reduced overall survival(P < 0.001). ROC curves validated the predictive power of risk model (AUCs > 0.81 at 1, 3, and 5 years). Single-cell sequencing uncovered a linkage between genes and immunocyte infiltration. Risk scores covaried with infiltration extent and immune pathway activity. Metabolomic analysis of five phospholipid-related genes revealed tumor-associated metabolite differences. In vitro, Vorinostat strongly induced Osteosarcoma cell apoptosis and upregulated VAC14 protein expression.
CONCLUSIONS: The phospholipid metabolism-based risk model aids Osteosarcoma prognosis. The immune microenvironment and drug sensitivity lay the groundwork for future mechanistic investigations. VAC14 is a potential target for neoadjuvant therapy, highlighting phospholipid metabolism as a promising therapeutic avenue.
METHODS: The data curated from the TARGET and GEO databases. Differential expression analysis, LASSO, and SVM-RFE screened feature genes. A Cox regression-based prognostic model was established and validated internally (survival analysis, ROC) and externally, assessing discrimination and calibration. Analyses of the tumor microenvironment composition, immunocyte infiltration, and drug sensitivity and key findings were validatedin vitro.
RESULTS: A risk model incorporating seven prognostic genes was constructed and confirmed using univariate Cox regression. High-risk patients showed markedly reduced overall survival(P < 0.001). ROC curves validated the predictive power of risk model (AUCs > 0.81 at 1, 3, and 5 years). Single-cell sequencing uncovered a linkage between genes and immunocyte infiltration. Risk scores covaried with infiltration extent and immune pathway activity. Metabolomic analysis of five phospholipid-related genes revealed tumor-associated metabolite differences. In vitro, Vorinostat strongly induced Osteosarcoma cell apoptosis and upregulated VAC14 protein expression.
CONCLUSIONS: The phospholipid metabolism-based risk model aids Osteosarcoma prognosis. The immune microenvironment and drug sensitivity lay the groundwork for future mechanistic investigations. VAC14 is a potential target for neoadjuvant therapy, highlighting phospholipid metabolism as a promising therapeutic avenue.