Insights From Nonsense-Mediated mRNA Decay for Prognosis in Homologous Recombination-Deficient Ovarian Cancer.

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Tác giả: Yanan Cheng, Li Dong, Lei Han, Jialing Liu, Juntian Liu, Ke Wang, Lijuan Wei, Jinpu Yu, Runjiao Zhang

Ngôn ngữ: eng

Ký hiệu phân loại:

Thông tin xuất bản: England : Cancer science , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 734888

 Not all ovarian cancer patients with homologous recombination deficiency, especially those with germline BRCA mutations, can benefit from platinum-based and targeted therapy. Our study aimed to determine the value of nonsense-mediated mRNA decay, which targeted these mutations. The retrospective analysis of 797 ovarian cancer patients was performed using two public cohorts and one in-house cohort. We developed a prediction algorithm for nonsense-mediated mRNA decay to discriminate between trigger and escape status, finding that escape status indicated a better prognosis. Subsequently, we analyzed differential gene expression and functional pathways between the two statuses and filtered 8 genes associated with the cell cycle. Then the optimized key gene model was built using integrated machine learning algorithms (mean AUC >
  0.89), which had a higher independent prognostic value for ovarian cancer with germline BRCA variants or homologous recombination deficiency than the nonsense-mediated mRNA decay algorithm. Furthermore, we classified patients into high- and low-risk groups by the machine learning model and found that the low-risk group had a better prognosis with higher drug response and immune levels of activated dendritic cells than the high-risk controls. Our findings provide a perspective based on nonsense-mediated mRNA decay and cell cycle pathways to distinguish subtypes of germline BRCA or homologous recombination deficiency.
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