ReviewImmunological reviews2014
Rapamycin-resistant effector T-cell therapy.
Review in Immunological reviews, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 19 citations in OpenAlex.
- Investigating the prognostic value of mTORC1 signaling in bladder cancer via bioinformatics evaluation.Scientific reports · 2023Article
- Article
- Tumor cell metabolic reprogramming and hypoxic immunosuppression: driving carcinogenesis to metastatic colonization.Frontiers in immunology · 2023Review
- Peripheral immune characteristics of hepatitis B virus-related hepatocellular carcinoma.Frontiers in immunology · 2023Article
- Pleiotropic effects of antibiotics on T cell metabolism and T cell-mediated immunity.Frontiers in microbiology · 2022Review
- Elevated Neddylation Pathway Promotes Th2 Cells Infiltration by Transactivating STAT5A in Hepatocellular Carcinoma.Frontiers in oncology · 2021Article
- T cell engineering as therapy for cancer and HIV: our synthetic future.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015Review
- Engineering T cells for cancer: our synthetic future.Immunological reviews · 2014Article
- A Comparison of Automated Perfusion- and Manual Diffusion-Based Human Regulatory T Cell Expansion and Functionality Using a Soluble Activator Complex.Cell transplantationArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Pharmacologic inhibition of the mechanistic target of rapamycin (mTOR) represents a stress test for tumor cells and T cells. Mechanisms exist that allow cells to survive this stress, including suboptimal target block, alternative signaling pathways, and autophagy. Rapamycin-resistant effector T (T-Rapa) cells have an altered phenotype that associates with increased function. Ex vivo rapamycin, when used in combination with polarizing cytokines and antigen-presenting-cell free costimulation, is a flexible therapeutic approach as polarization to T-helper 1 (Th1)- or Th2-type effectors is possible. Murine T-Rapa cells skewed toward a Th2-type prevented graft rejection and graft-versus-host disease (GVHD) more potently than control Th2 cells and effectively balanced GVHD and graft-versus-tumor (GVT) effects. A phase II clinical trial using low-intensity allogeneic hematopoietic cell transplantation demonstrated that interleukin-4 polarized human T-Rapa cells had a mixed Th2/Th1 phenotype; T-Rapa cell recipients had a balanced Th2/Th1 cytokine profile, conversion of mixed chimerism toward full donor chimerism, and a potentially favorable balance between GVHD and GVT effects. In addition, a phase I clinical trial evaluating autologous T-Rapa cells skewed toward a Th1- and Tc1-type is underway. Use of ex vivo rapamycin to modulate effector T-cell function represents a promising new approach to transplantation therapy.
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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.