ReviewCancers2023
Engineered Adoptive T-Cell Therapies for Breast Cancer: Current Progress, Challenges, and Potential.
Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.
- Global research trends and focus on immunotherapy for endometrial cancer: a comprehensive bibliometric insight and visualization analysis (2012-2024).Frontiers in immunology · 2025Pooled it
- Breast cancer immunotherapy: mechanisms of immune evasion, biomarkers, and emerging therapeutic strategies.Molecular cancer · 2026Review
- Bispecific Antibodies in Breast Cancer Immunotherapy: Mechanisms, Advances, and Translational Challenges.Targeted oncology · 2026Review
- Immune system, inflammatory response, and regulated cell death in breast cancer research (Review).Oncology reports · 2026Review
- Tumor-specific CD8 T cell characterization in HRCell reports. Medicine · 2025Article
- Proteogenomic characterization of invasive breast tumors in young women.NPJ breast cancer · 2025Article
- Cytokine Networks in Triple-Negative Breast Cancer: Mechanisms, Therapeutic Targets, and Emerging Strategies.Biomedicines · 2025Review
- ZP4: A novel target for CAR-T cell therapy in triple negative breast cancer.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Article
- Harnessing the tumor microenvironment: targeted cancer therapies through modulation of epithelial-mesenchymal transition.Journal of hematology & oncology · 2025Review
- Regulatory effects of traditional Chinese medicine on the breast-cancer immune microenvironment.Frontiers in immunology · 2025Review
- Targeting cancer with precision: strategical insights into TCR-engineered T cell therapies.Theranostics · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Breast cancer remains a significant health challenge, and novel treatment approaches are critically needed. This review presents an in-depth analysis of engineered adoptive T-cell therapies (E-ACTs), an innovative frontier in cancer immunotherapy, focusing on their application in breast cancer. We explore the evolving landscape of chimeric antigen receptor (CAR) and T-cell receptor (TCR) T-cell therapies, highlighting their potential and challenges in targeting breast cancer. The review addresses key obstacles such as target antigen selection, the complex breast cancer tumor microenvironment, and the persistence of engineered T-cells. We discuss the advances in overcoming these barriers, including strategies to enhance T-cell efficacy. Finally, our comprehensive analysis of the current clinical trials in this area provides insights into the future possibilities and directions of E-ACTs in breast cancer treatment.
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.