ReviewFrontiers in oncology2022
Patient-derived cancer models: Valuable platforms for anticancer drug testing.
Review in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 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
25 citing papers in PubMed, 33 citations in OpenAlex.
- Human lung explants as a predictive platform for evaluating the on-target, off-tumor toxicity of T cell bispecifics.iScience · 2026Article
- Article
- Human iPSC-derived and conventional cancer models in precision oncology: advancing patient-specific therapies from bench to bedside.Journal of experimental & clinical cancer research : CR · 2026Review
- Stem Cell-Derived Organoids for Cancer Therapy: Precision Medicine and Drug Selection.International journal of molecular sciences · 2026Review
- Regorafenib-Induced Stress Response Alters the Bioenergetic Profile of Osteosarcoma Cells and Modulates Gene Expression Associated with Metabolic regulation-a Potential Mechanism of Osteosarcoma Treatment-Related Adaptation.Cancer management and research · 2026Article
- Nanoformulated Phytochemicals Against Pancreatic Cancer: Emerging Advances in Therapeutic Strategies.International journal of nanomedicine · 2026Review
- Advances and Challenges in Drug Screening for Cancer Therapy: A Comprehensive Review.Bioengineering (Basel, Switzerland) · 2025Review
- Targeting Cell-Matrix Induced Chemoresistance With Regorafenib in a 3D Model of Osteosarcoma.Journal of biomedical materials research. Part A · 2025Article
- Patient-derived xenograft models: Current status, challenges, and innovations in cancer research.Genes & diseases · 2025Review
- Antitumor Efficacy of Paclitaxel Injection Concentrate for Nanodispersion in Patient-Derived Breast, Head and Neck, and Non-Small Cell Lung Cancer Mouse Xenografts.AAPS PharmSciTech · 2025Article
- Prediction of Patient Drug Response via 3D Bioprinted Gastric Cancer Model Utilized Patient-Derived Tissue Laden Tissue-Specific Bioink.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Harnessing Organoid Platforms for Nanoparticle Drug Development.Drug design, development and therapy · 2025Review
- Approaches to modeling cancer metastasis: from bench to bedside.Frontiers in oncology · 2025Review
- A novel approach to engineering three-dimensional bladder tumor models for drug testing.Scientific reports · 2024Article
- Antibody-Drug Conjugates to Promote Immune Surveillance: Lessons Learned from Breast Cancer.Biomedicines · 2024Review
- TOWARDS Study: Patient-Derived Xenograft Engraftment Predicts Poor Survival in Patients With Newly Diagnosed Triple-Negative Breast Cancer.JCO precision oncology · 2024Article
- Alginate-Chitosan Biodegradable and Biocompatible Based Hydrogel for Breast Cancer Immunotherapy and Diagnosis: A Comprehensive Review.ACS applied bio materials · 2024Review
- Advancement in Cancer Vasculogenesis Modeling through 3D Bioprinting Technology.Biomimetics (Basel, Switzerland) · 2024Review
- Extracellular Vesicles in Breast Cancer: From Intercellular Communication to Therapeutic Opportunities.Pharmaceutics · 2024Review
- Promising preclinical models for lung cancer research-lung cancer organoids: a narrative review.Translational lung cancer research · 2024Review
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecularly targeted treatments and immunotherapy are cornerstones in oncology, with demonstrated efficacy across different tumor types. Nevertheless, the overwhelming majority metastatic disease is incurable due to the onset of drug resistance. Preclinical models including genetically engineered mouse models, patient-derived xenografts and two- and three-dimensional cell cultures have emerged as a useful resource to study mechanisms of cancer progression and predict efficacy of anticancer drugs. However, variables including tumor heterogeneity and the complexities of the microenvironment can impair the faithfulness of these platforms. Here, we will discuss advantages and limitations of these preclinical models, their applicability for drug testing and in co-clinical trials and potential strategies to increase their reliability in predicting responsiveness to anticancer medications.
Indexed as
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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.