ArticleCancers2020
Ex-Vivo Treatment of Tumor Tissue Slices as a Predictive Preclinical Method to Evaluate Targeted Therapies for Patients with Renal Carcinoma.
Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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
38 citing papers in PubMed, 59 citations in OpenAlex.
- Physiologically Relevant Organotypic Tissue Slice Model for Evaluating Cell Responses to Ionizing Radiation.International journal of molecular sciences · 2026Review
- Methods and applications of patient-derived organoid models for immune microenvironment and immunotherapy research in multiple cancer types.Experimental hematology & oncology · 2026Review
- A live tumor fragment platform to assess immunotherapy response in core needle biopsies while addressing challenges of tumor heterogeneity.Journal of translational medicine · 2026Observational
- Precision-cut tumor slices: a biomimetic tool for accelerating oncological development from basic research to clinical translation.Frontiers in physiology · 2026Review
- Functional Assays to Guide Personalized Oncological Treatment of Patients with Soft-Tissue Sarcomas.Cancers · 2025Review
- From lab to life: technological innovations in transforming cancer metastasis detection and therapy.Discover oncology · 2025Review
- Establishment of patient-derived 3D in vitro models of sarcomas: literature review and guidelines on behalf of the FORTRESS working group.Neoplasia (New York, N.Y.) · 2025Review
- Advances and challenges in human 3D solid tumor models.Advanced functional materials · 2025Article
- Role of Data in Development and Application of Quantitative Systems Pharmacology Models.Handbook of experimental pharmacology · 2025Review
- Innovative Therapies Targeting Drug-Resistant Biomarkers in Metastatic Clear Cell Renal Cell Carcinoma (ccRCC).International journal of molecular sciences · 2024Review
- Cancer selective cell death induction by a bivalent CK2 inhibitor targeting the ATP site and the allosteric αD pocket.iScience · 2024Article
- Breast Cancer Tissue Explants: An Approach to Develop Personalized Therapy in Public Health Services.Journal of personalized medicine · 2023Article
- A new scaffold-free tumoroid model provides a robust preclinical tool to investigate invasion and drug response in Renal Cell Carcinoma.Cell death & disease · 2023Article
- Article
- COL7A1 Expression Improves Prognosis Prediction for Patients with Clear Cell Renal Cell Carcinoma Atop of Stage.Cancers · 2023Article
- Organotypic Models for Functional Drug Testing of Human Cancers.BME frontiers · 2023Review
- Review
- Optimal microRNA Sequencing Depth to Predict Cancer Patient Survival with Random Forest and Cox Models.Genes · 2022Article
- A hitchhiker's guide to cancer models.Trends in biotechnology · 2022Review
- How to build a tumor: An industry perspective.Drug discovery today · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 2 institutions in 1 country.
Funding
Abstract
Clear cell renal cell carcinoma (ccRCC) is the third type of urologic cancer. At time of diagnosis, 30% of cases are metastatic with no effect of chemotherapy or radiotherapy. Current targeted therapies lead to a high rate of relapse and resistance after a short-term response. Thus, a major hurdle in the development and use of new treatments for ccRCC is the lack of good pre-clinical models that can accurately predict the efficacy of new drugs and allow the stratification of patients into the correct treatment regime. Here, we describe different 3D cultures models of ccRCC, emphasizing the feasibility and the advantage of ex-vivo treatment of fresh, surgically resected human tumor slice cultures of ccRCC as a robust preclinical model for identifying patient response to specific therapeutics. Moreover, this model based on precision-cut tissue slices enables histopathology measurements as tumor architecture is retained, including the spatial relationship between the tumor and tumor-infiltrating lymphocytes and the stromal components. Our data suggest that acute treatment of tumor tissue slices could represent a benchmark of further exploration as a companion diagnostic tool in ccRCC treatment and a model to develop new therapeutic drugs.
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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.