ArticleCell reports2020
Mouse Ovarian Cancer Models Recapitulate the Human Tumor Microenvironment and Patient Response to Treatment.
Article in Cell reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
75 citing papers in PubMed, 1 synthesis or guideline pooled it.
- High-dimensional analysis of the adenosine pathway in high-grade serous ovarian cancer.Journal for immunotherapy of cancer · 2021Pooled it
- VISTA+ Neutrophils Contribute to Platinum Resistance by Suppressing CD8+ T Cells in High-Grade Serous Ovarian Cancer.Cancer immunology research · 2026Article
- Inhibiting CXCR2 Remodels the Tumor Microenvironment and Blunts Tumor Progression and Dissemination of High-Grade Serous Carcinoma.Cancer research communications · 2026Article
- Reconstruction of septin higher-order nano-size structures in ovarian cancer cells uncover susceptibility to the septin-targeting small molecule UR214-9.bioRxiv : the preprint server for biology · 2026Article
- Rethinking ovarian cancer III: the past decade and future directions.Nature reviews. Cancer · 2026Review
- IL1β/IL1R1/IRAK4 Drives Inflammatory Ovarian Cancer Seeding at the inflamed sites and Is Reversed by an IRAK4 inhibitor UR241-2.bioRxiv : the preprint server for biology · 2026Article
- HE4 drives PD-L1 expression in myeloid cells via IFN-γR-JAK-STAT3 signaling to promote tumor immune evasion.Cell reports. Medicine · 2026Article
- NKG2A inhibition promotes NK cell-CD8Nature communications · 2026Article
- FAK inhibition in ovarian cancer releases omega-3 fatty acids to program CXCL13-producing anti-tumor resident peritoneal macrophages.Cell reports · 2026Article
- Matrix structure and microenvironment dynamics correlate with chemotherapy response in ovarian cancer.iScience · 2026Article
- Identification of ADAR1i-124: The first effective A-to-I RNA editing inhibitor with promising cancer therapeutic potential.iScience · 2026Article
- Inflammatory milieu and role of epigenetic modifications in high-grade serous ovarian cancer.Clinical epigenetics · 2026Review
- High-Grade Serous Ovarian Carcinoma in the Genomics Era: Current Applications, Challenges and Future Directions.International journal of molecular sciences · 2026Review
- Ovarian Cancer Susceptibility and Chemosensitivity to KRAS Modulation.International journal of molecular sciences · 2026Article
- Models of high-grade serous carcinoma of tubo-ovarian origin.Oncology reviews · 2026Review
- Organoids and AI-integrated models in ovarian cancer research: the future of personalized therapy.Frontiers in oncology · 2026Review
- Development and Application of MiMouse, a Comprehensive Genomic Profiling Panel for Credentialing Mouse Tumor Models.Cancer research communications · 2025Article
- Targeting RAD52 overcomes PARP inhibitor resistance in preclinicalbioRxiv : the preprint server for biology · 2025Article
- Loss ofOncotarget · 2025Article
- Ovarian Tumor FAK Inhibition Releases Omega-3 Fatty Acids Stimulating GATA6 Peritoneal Macrophage CXCL13 Production Enhancing Immunotherapy.bioRxiv : the preprint server for biology · 2025Article
15 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Although there are many prospective targets in the tumor microenvironment (TME) of high-grade serous ovarian cancer (HGSOC), pre-clinical testing is challenging, especially as there is limited information on the murine TME. Here, we characterize the TME of six orthotopic, transplantable syngeneic murine HGSOC lines established from genetic models and compare these to patient biopsies. We identify significant correlations between the transcriptome, host cell infiltrates, matrisome, vasculature, and tissue modulus of mouse and human TMEs, with several stromal and malignant targets in common. However, each model shows distinct differences and potential vulnerabilities that enabled us to test predictions about response to chemotherapy and an anti-IL-6 antibody. Using machine learning, the transcriptional profiles of the mouse tumors that differed in chemotherapy response are able to classify chemotherapy-sensitive and -refractory patient tumors. These models provide useful pre-clinical tools and may help identify subgroups of HGSOC patients who are most likely to respond to specific therapies.
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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.