Metabolism-associated marker gene-based predictive model for prognosis, targeted therapy, and immune landscape in ovarian cancer: an integrative analysis of single-cell and bulk RNA sequencing with spatial transcriptomics

Metabolism-associated marker gene-based predictive model for prognosis, targeted therapy, and immune landscape in ovarian cancer: an integrative analysis of single-cell and bulk RNA sequencing with spatial transcriptomics

Abstract Background Ovarian cancer (OC) is a formidable gynecological tumor marked with the highest mortality rate. The lack of effective biomarkers and treatment drugs places a substantial proportion of patients with OC at significant risk of mortality, primarily due to metastasis. Glycolysis metab...

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Bibliographic Details
Main Authors: Lele Ling, Bingrong Li, Boliang Ke, Yinjie Hu, Kaiyong Zhang, Siwen Li, Te Liu, Peng Liu, Bimeng Zhang
Format: Article
Language:English
Published: BMC 2025-05-01
Series:BMC Women's Health
Subjects:
Metabolism
Ovarian cancer
Biomarkers
Single-cell sequencing
Bulk RNA sequencing
Online Access:https://doi.org/10.1186/s12905-025-03750-y
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https://doi.org/10.1186/s12905-025-03750-y

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