ReviewFrontiers in oncology2022
CAR-T Cells in the Treatment of Urologic Neoplasms: Present and Future.
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 11 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
11 citing papers in PubMed, 13 citations in OpenAlex.
- Cardiovascular Complications Associated with Uro-Oncology Treatments-A Primer for the Clinician.Diagnostics (Basel, Switzerland) · 2026Review
- Recent advances in immunotherapy for bladder cancer: mechanisms, clinical applications, and future perspectives.Frontiers in oncology · 2026Review
- Advancing CAR T-Cell Therapy in Solid Tumors: Current Landscape and Future Directions.Cancers · 2025Review
- The role of immunotherapy in targeting tumor microenvironment in genitourinary cancers.Frontiers in immunology · 2025Review
- Advances in the immunological microenvironment and immunotherapy of bladder cancer.Frontiers in immunology · 2025Review
- High-throughput screening for optimizing adoptive T cell therapies.Experimental hematology & oncology · 2024Review
- Advances in tumor microenvironment and underlying molecular mechanisms of bladder cancer: a systematic review.Discover oncology · 2024Review
- Emerging molecular therapies in the treatment of bladder cancer.Exploration of targeted anti-tumor therapy · 2024Review
- Review of T cell proliferation regulatory factors in treatment and prognostic prediction for solid tumors.Heliyon · 2023Review
- Review
- A new immune-related gene signature predicts the prognosis and immune escape of bladder cancer.Cancer biomarkers : section A of Disease markers · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, with the breakthrough of CAR-T cells in the treatment of hematological tumors, they are increasingly being used to treat solid tumors, including urologic neoplasms. There are many relatively specific targets for urologic neoplasms, especially prostate cancer. Besides, urologic neoplasms tend to progress more slowly than tumors in other organs of the body, providing ample time for CAR-T cell application. Therefore, CAR-T cells technology has inherent advantages in urologic neoplasms. CAR-T cells in the treatment of urologic neoplasms have been extensively studied and preliminary achievements have been made. However, no breakthrough has been made due to the problems of targeting extra-tumor cytotoxicity and poor anti-tumor activity. we systematacially summarized the research actuality of CAR-T cells in urologic neoplasms, discussed the potential value and difficulties of the research. The application of CAR-T cells in the treatment of urologic neoplasms requires improvement of function through screening for better targets, modification of CAR structures, or in combination with other antitumor approaches.
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.