SynthesisBMC cancer2015
Prediction of resistance to chemotherapy in ovarian cancer: a systematic review.
Synthesis in BMC cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
41 citing papers in PubMed.
- Worldwide Research Trends on the Immunotherapy-Based Treatment of Ovarian Cancers: A Bibliometric and Visual Analysis.Journal of multidisciplinary healthcare · 2025Article
- Article
- TMEM158, as plasma cfRNA marker, promotes proliferation and doxorubicin resistance in ovarian cancer.The pharmacogenomics journal · 2024Article
- Identification of genes predicting chemoresistance and short survival in ovarian cancer.Translational cancer research · 2024Article
- Comprehensive analysis of hub genes associated with cisplatin-resistance in ovarian cancer and screening of therapeutic drugs through bioinformatics and experimental validation.Journal of ovarian research · 2024Article
- E26 transformation-specific transcription variant 5 in development and cancer: modification, regulation and function.Journal of biomedical science · 2023Review
- Predicting chemoresponsiveness in epithelial ovarian cancer patients using circulating small extracellular vesicle-derived plasma gelsolin.Journal of ovarian research · 2023Article
- A chemotherapy response prediction model derived from tumor-promoting B and Tregs and proinflammatory macrophages in HGSOC.Frontiers in oncology · 2023Article
- CRAC and SK Channels: Their Molecular Mechanisms Associated with Cancer Cell Development.Cancers · 2022Review
- A Pair of Prognostic Biomarkers in Triple-Negative Breast Cancer: KLK10 and KLK11 mRNA Expression.Life (Basel, Switzerland) · 2022Article
- Variational Bayes for high-dimensional proportional hazards models with applications within gene expression.Bioinformatics (Oxford, England) · 2022Article
- The impact of neoadjuvant chemotherapy on the tumor microenvironment in advanced high-grade serous carcinoma.Oncogenesis · 2022Article
- Can Schlafen 11 Help to Stratify Ovarian Cancer Patients Treated with DNA-Damaging Agents?Cancers · 2022Review
- Novel MicroRNA-Regulated Transcript Networks Are Associated with Chemotherapy Response in Ovarian Cancer.International journal of molecular sciences · 2022Article
- Gene co-expression network analysis revealed novel biomarkers for ovarian cancer.Frontiers in genetics · 2022Article
- Transcriptional epigenetic regulation of Fkbp1/Pax9 genes is associated with impaired sensitivity to platinum treatment in ovarian cancer.Clinical epigenetics · 2021Article
- Article
- Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer.BMC cancer · 2021Article
- Emerging Roles for Ion Channels in Ovarian Cancer: Pathomechanisms and Pharmacological Treatment.Cancers · 2021Review
- Targeting mTOR and eIF4E: a feasible scenario in ovarian cancer therapy.Cancer drug resistance (Alhambra, Calif.) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundPatient response to chemotherapy for ovarian cancer is extremely heterogeneous and there are currently no tools to aid the prediction of sensitivity or resistance to chemotherapy and allow treatment stratification. Such a tool could greatly improve patient survival by identifying the most appropriate treatment on a patient-specific basis.
methodsPubMed was searched for studies predicting response or resistance to chemotherapy using gene expression measurements of human tissue in ovarian cancer.
results42 studies were identified and both the data collection and modelling methods were compared. The majority of studies utilised fresh-frozen or formalin-fixed paraffin-embedded tissue. Modelling techniques varied, the most popular being Cox proportional hazards regression and hierarchical clustering which were used by 17 and 11 studies respectively. The gene signatures identified by the various studies were not consistent, with very few genes being identified by more than two studies. Patient cohorts were often noted to be heterogeneous with respect to chemotherapy treatment undergone by patients.
conclusionsA clinically applicable gene signature capable of predicting patient response to chemotherapy has not yet been identified. Research into a predictive, as opposed to prognostic, model could be highly beneficial and aid the identification of the most suitable treatment for patients.
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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.