AIMC Topic: Ovarian Neoplasms
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HRProfiler Detects Homologous Recombination Deficiency in Breast and Ovarian Cancers Using Whole-Genome and Whole-Exome Sequencing Data.
Cancer research
Jul 2, 2025
UNLABELLED: Breast and ovarian cancers harboring homologous recombination deficiency (HRD) are sensitive to PARP inhibitors and platinum chemotherapy. Conventionally, detecting HRD involves screening for defects in BRCA1, BRCA2, and other relevant ge...
Computer-aided drug discovery of a dual-target inhibitor for ovarian cancer: therapeutic intervention targeting CDK1/TTK signaling pathway and structural insights in the NCI-60.
Computers in biology and medicine
Jul 1, 2025
Ovarian cancer remains the third most prevalent and deadliest gynecologic malignancy worldwide, with most patients eventually developing resistance to platinum-based chemotherapy. This highlights a critical unmet need for innovative multitargeted the...
Integrating bulk RNA-seq and scRNA-seq analyses with machine learning to predict platinum response and prognosis in ovarian cancer.
Scientific reports
May 31, 2025
Platinum-based therapy is an integral part of the standard treatment for ovarian cancer. However, despite extensive research spanning several decades, the identification of dependable predictive biomarkers for platinum response in clinical practice h...
[WW domain-containing ubiquitin E3 ligase 1 regulates immune infiltration in tumor microenvironment of ovarian cancer].
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
May 20, 2025
OBJECTIVES: To explore the association of the expression of WW domain-containing ubiquitin E3 ligase 1 (WWP1) with immune infiltration in tumor microenvironment (TME) of ovarian cancer.
A Deep-Learning Framework for Ovarian Cancer Subtype Classification Using Whole Slide Images.
Studies in health technology and informatics
May 15, 2025
Ovarian cancer, a leading cause of cancer-related deaths among women, comprises distinct subtypes each requiring different treatment approaches. This paper presents a deep-learning framework for classifying ovarian cancer subtypes using Whole Slide I...
Deep learning based on ultrasound images to predict platinum resistance in patients with epithelial ovarian cancer.
Biomedical engineering online
May 13, 2025
BACKGROUND: The study aimed at developing and validating a deep learning (DL) model based on the ultrasound imaging for predicting the platinum resistance of patients with epithelial ovarian cancer (EOC).
Unraveling the molecular mechanisms of paclitaxel in high-grade serous ovarian cancer through network pharmacology.
Scientific reports
May 12, 2025
High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of epithelial ovarian cancer, often diagnosed at advanced stages with a poor prognosis. Paclitaxel (PTX), a standard chemotherapeutic agent for HGSOC, exerts cytotoxic...
Kaplan-Meier Estimate
Cystadenocarcinoma, Serous
Network Pharmacology
Gene Expression Regulation, Neoplastic
Antineoplastic Agents, Phytogenic
Ovarian Neoplasms
Paclitaxel
Protein Interaction Maps
Gene Regulatory Networks
Female
Computational Biology
Tumor Microenvironment
Biomarkers, Tumor
Humans
Molecular Docking Simulation
Prognosis
Random forest-based model for the recurrence prediction of borderline ovarian tumor: clinical development and validation.
Journal of cancer research and clinical oncology
May 11, 2025
PURPOSE: This study aims to develop an effective machine learning (ML)-based predictive model for the recurrence of borderline ovarian tumor (BOT), and provide the guidelines of accurate clinical diagnosis and precise treatment for patients.
Multi-dimensional characterization of cellular states reveals clinically relevant immunological subtypes and therapeutic vulnerabilities in ovarian cancer.
Journal of translational medicine
May 8, 2025
BACKGROUND: Diverse cell types and cellular states in the tumor microenvironment (TME) are drivers of biological and therapeutic heterogeneity in ovarian cancer (OV). Characterization of the diverse malignant and immunology cellular states that make ...
Mitigation of outcome conflation in predicting patient outcomes using electronic health records.
Journal of the American Medical Informatics Association : JAMIA
May 1, 2025
OBJECTIVES: Artificial intelligence (AI) models utilizing electronic health record data for disease prediction can enhance risk stratification but may lack specificity, which is crucial for reducing the economic and psychological burdens associated w...
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