ReviewCells2023
Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation.
Review in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Conditionally Reprogrammed Cells Preserve Cellular Diversity and Permit Genetic Manipulation: Implications for Cancer Heterogeneity and Tissue Regeneration.Serican journal of medicine · 2026Article
- Review
- Urine PD-L1 as a non-invasive biomarker for immune checkpoint inhibitor (ICI) therapy in bladder cancer.Advances in biomarker sciences and technology · 2025Article
- Modeling respiratory tract diseases for clinical translation employing conditionally reprogrammed cells.Cell insight · 2024Review
- Review
- Unlocking Translational Potential: Conditionally Reprogrammed Cells in Advancing Breast Cancer Research.Cells · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The use of advanced preclinical models has become increasingly important in drug development. This is particularly relevant in bladder cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (chemotherapy, radiotherapy, immunotherapy, and/or surgery) are largely absent. Patient-derived and clinically relevant models including patient-derived xenografts (PDX), organoids, and conditional reprogramming (CR) of cell cultures efficiently generate numerous models and are being used in both basic and translational cancer biology. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have utilized CR technology to conduct bladder cancer research.
Indexed as
Identifiers
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.