Chimeric Antigen Receptor-T Cells in Colorectal Cancer: Pioneering New Avenues in Solid Tumor Immunotherapy
Bibliographic record
Abstract
Colorectal cancer (CRC) remains a major global health burden, being one of the most prevalent cancers with high mortality rates. Despite advances in conventional treatment modalities, patients with metastatic CRC often face limited options and poor outcomes. Chimeric antigen receptor-T (CAR-T) cell therapy, initially successful in hematologic malignancies, presents a promising avenue for treating solid tumors, including CRC. This review explores the potential of CAR-T cell therapy in CRC by analyzing clinical trials and highlighting prominent CRC-specific targets. We discuss the challenges such as immunosuppressive microenvironment, tumor heterogeneity, and physical barriers that limit CAR-T efficacy. Emerging strategies, such as logic-gated and dual-targeting CAR-T cells, offer practical solutions to overcome these hurdles. Furthermore, we explore the combination of CAR-T cell therapy with immune checkpoint inhibitors to enhance T-cell persistence and tumor infiltration. As the field continues to evolve, CAR-T cell therapies hold significant potential for revolutionizing the treatment landscape of CRC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".