ReviewClinical and translational medicine2024
Ecological and evolutionary dynamics to design and improve ovarian cancer treatment.
Review in Clinical and translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Heterogeneity in cancer: molecular mechanisms and therapeutic strategies.Signal transduction and targeted therapy · 2026Review
- An organoid-guided platform for ovarian cancer: enabling prediction of patients' chemotherapy response.Journal of ovarian research · 2026Article
- Natural Compounds as Epimodulators in Epithelial Ovarian Cancer.Epigenomes · 2026Review
- Drug-tolerant persister cells in cancer: a scoping review of definitions, models, and molecular mechanisms.Frontiers in oncology · 2026Review
- Targeting tumor transition windows.Exploration of targeted anti-tumor therapy · 2026Review
- Genetic and Molecular Determinants of Immunotherapy Response in Recurrent Ovarian Cancer.Anti-cancer agents in medicinal chemistry · 2026Review
- Unveiling critical genes and molecular subtypes in ovarian cancer: insights into tumor immunity and carbohydrate-lipid metabolism.Translational cancer research · 2025Article
- Metabolic plasticity drives mechanisms of PARP inhibitor persistence in ovarian cancer.bioRxiv : the preprint server for biology · 2025Article
- ctDNA as an Objective Marker for Postoperative Residual Disease in Primary Advanced High-Grade Serous Ovarian Cancer.Cancers · 2025Article
- A quinoline-2-thione derivative as a novel chemotherapy drug candidate displays anti-tumor activity in vitro and in vivo.BMC cancer · 2024Article
- Ecological and evolutionary dynamics to design and improve ovarian cancer treatment.Clinical and translational medicine · 2024Review
- A novel diagnostic model for early-stage high-grade serous ovarian cancer based on serum tRNA-derived fragments.Cancer biomarkers : section A of Disease markersArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Ovarian cancer ecosystems are exceedingly complex, consisting of a high heterogeneity of cancer cells. Development of drugs such as poly ADP-ribose polymerase (PARP) inhibitors, targeted therapies and immunotherapies offer more options for sequential or combined treatments. Nevertheless, mortality in metastatic ovarian cancer patients remains high because cancer cells consistently develop resistance to single and combination therapies, urging a need for treatment designs that target the evolvability of cancer cells. The evolutionary dynamics that lead to resistance emerge from the complex tumour microenvironment, the heterogeneous populations, and the individual cancer cell's plasticity. We propose that successful management of ovarian cancer requires consideration of the ecological and evolutionary dynamics of the disease. Here, we review current options and challenges in ovarian cancer treatment and discuss principles of tumour evolution. We conclude by proposing evolutionarily designed strategies for ovarian cancer, with the goal of integrating such principles with longitudinal, quantitative data to improve the treatment design and management of drug resistance. KEY POINTS/HIGHLIGHTS: Tumours are ecosystems in which cancer and non-cancer cells interact and evolve in complex and dynamic ways. Conventional therapies for ovarian cancer inevitably lead to the development of resistance because they fail to consider tumours' heterogeneity and cellular plasticity. Eco-evolutionarily designed therapies should consider cancer cell plasticity and patient-specific characteristics to improve clinical outcome and prevent relapse.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.