ReviewBlood advances2025
Predictive markers for the efficacy of CAR T-cell therapy: the interplay between CAR T-cell fitness and systemic immunity.
Review in Blood advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Impaired hematopoiesis affects apheresis and CAR T-cell product composition and treatment response.Transfusion · 2026Article
- Advances in targeted and cellular therapies for relapsed/refractory mantle cell lymphoma: immunotherapeutic strategies and challenges.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- A versatile and GMP-compliant bead-based IFN-γ potency assay for standardized quality control and release testing of CAR-T cell drug products.International journal of pharmaceutics: X · 2026Article
- Cell-free RNA Signatures Derived from the Tumor Microenvironment Predict Outcomes of CAR-T Therapy in Large B Cell Lymphoma.medRxiv : the preprint server for health sciences · 2026Article
- Multi-Omics-Enabled Precision Strategies for Overcoming CAR-T Therapy Limitations in Gastrointestinal Malignancies.BioFactors (Oxford, England)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
abstractChimeric antigen receptor (CAR) T-cell therapy has revolutionized the therapeutic landscape for relapsed or refractory lymphoid malignancies, achieving remarkable rates of durable remission. Despite this success, significant variability among patients in clinical responses and treatment-related toxicities remains a critical challenge, highlighting an urgent need for robust predictive biomarkers. Key intrinsic CAR T-cell attributes predictive of therapeutic efficacy and safety include the composition of memory T-cell subsets, particularly central memory and stem cell memory T-cell populations, CAR density and transduction efficiency, cytokine production profiles with emphasis on polyfunctionality, and metabolic fitness. Additionally, the systemic immune contexture significantly modulates outcomes, including baseline systemic inflammatory cytokines, presence of regulatory immune cell populations, and the pretreatment immunosuppressive tumor microenvironment. Recent advances in single-cell transcriptomics, comprehensive proteomic profiling, and cytokine polyfunctionality assays have provided greater resolution for identifying predictive biomarkers and optimizing therapeutic strategies. High-dimensional immunophenotyping combined with advanced machine learning methods enables automated CAR T-cell manufacturing quality control and precise immunological synapse quantification. Furthermore, tumor antigen (epitope) spreading after CAR T-cell therapy has risen as a provisional biomarker indicating broadened antitumor immunity and potentially sustained remission. Integrating these emerging biomarkers and advanced multiomic approaches into clinical practice can refine patient stratification, enhance CAR T-cell manufacturing processes, and improve therapeutic outcomes in patients with lymphoid malignancies.
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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.