ReviewCancer research2010
The COXEN principle: translating signatures of in vitro chemosensitivity into tools for clinical outcome prediction and drug discovery in cancer.
Review in Cancer research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
54 citing papers in PubMed.
- Association of Molecular Subtypes with Pathologic Response, PFS, and OS in a Phase II Study of COXEN with Neoadjuvant Chemotherapy for Muscle-invasive Bladder Cancer.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Trial
- Long-term Outcomes from a Phase 2 Study of Neoadjuvant Chemotherapy for Muscle-invasive Bladder Cancer (SWOG S1314; NCT02177695).European urology · 2023Trial
- A Randomized Phase II Study of Coexpression Extrapolation (COXEN) with Neoadjuvant Chemotherapy for Bladder Cancer (SWOG S1314; NCT02177695).Clinical cancer research : an official journal of the American Association for Cancer Research · 2021Trial
- Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment.Nature reviews. Urology · 2024Review
- Biomarker challenges in the pursuit of personalized neoadjuvant chemotherapy for muscle-invasive bladder cancer: conclusions from SWOG S1314.Translational andrology and urology · 2024Article
- Precision Medicine in Bladder Cancer: Present Challenges and Future Directions.Journal of personalized medicine · 2023Review
- Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images.Frontiers in medicine · 2023Article
- Predictive Biomarkers of Response to Neoadjuvant Therapy in Muscle Invasive Bladder Cancer.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Predictive molecular biomarkers for determining neoadjuvant chemosensitivity in muscle invasive bladder cancer.Oncotarget · 2022Article
- Using Cell Lines To Guide Neoadjuvant Therapy in Bladder Cancer: COXEN and SWOG S1314.European urology focus · 2022Article
- Review
- Prospective clinical trial testing COXEN-based gene expression models of chemosensitivity in dogs with spontaneous osteosarcoma.Cancer chemotherapy and pharmacology · 2021Article
- Ensemble transfer learning for the prediction of anti-cancer drug response.Scientific reports · 2020Article
- Article
- Review of SWOG S1314: Lessons from a Randomized Phase II Study of Co-Expression Extrapolation (COXEN) with Neoadjuvant Chemotherapy for Localized, Muscle-Invasive Bladder Cancer.Bladder cancer (Amsterdam, Netherlands) · 2020Review
- Organotypic Modeling of the Tumor Landscape.Frontiers in cell and developmental biology · 2020Review
- Article
- AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing.Frontiers in oncology · 2019Review
- Predicting tumor cell line response to drug pairs with deep learning.BMC bioinformatics · 2018Article
- Novel therapies in urothelial carcinoma: a biomarker-driven approach.Annals of oncology : official journal of the European Society for Medical Oncology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Substantial effort has been devoted to in vitro testing of candidate chemotherapeutic agents. In particular, the United States National Cancer Institute Developmental Therapeutics Program (NCI-DTP) Human Tumor Cell Line Screen has screened hundreds of thousands of compounds and extracts, for which data on more than 40,000 compounds tested on a panel of 60 cancer cell lines (NCI-60) are publically available. In tandem, gene expression profiling has brought about a sea change in our understanding of cancer biology, allowing discovery of biomarkers or signatures able to characterize, classify, and prognosticate clinical behavior of human tumors. Recent studies have used tumor profiling matched to clinical trial outcome data to derive gene expression models predicting therapeutic outcomes, though such efforts are costly, time-consuming, tumor type-specific, and not amenable to rare diseases. Furthermore, addition of new or established drugs to multidrug combinations in which such models are already available requires the entire model to be re-derived. Can the aforementioned in vitro testing platform, coupled to the universal language of genomics, be used to develop, a priori, gene expression models predictive of clinical outcomes? Recent advances, including the CO-eXpression ExtrapolatioN (COXEN) algorithm, suggest that development of these models may be possible and raise important implications for future trial design and drug discovery.
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What OpenQuestion holds
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.