ReviewJournal of oncology2019
The Therapeutic Strategies of Regulatory T Cells in Malignancies and Stem Cell Transplantations.
Review in Journal of oncology, 2019. 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, 10 citations in OpenAlex.
- Targeting regulatory T cells in glioblastoma: from mechanistic insights to novel immunotherapeutic strategies.Frontiers in immunology · 2026Review
- Review
- Optimizing Blood Stem Cell Transplants Through Cellular Engineering.Blood cell therapy · 2022Review
- β2-Adrenergic receptor activation on donor cells ameliorates acute GvHD.JCI insight · 2020Article
- The Role of TLRs in Anti-cancer Immunity and Tumor Rejection.Frontiers in immunology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Regulatory T cells (Treg cells) are considered one of the main dynamic cell types within the immune system. Because Treg cells suppress immune responses, they have potential roles in immunological self-tolerance and may help to maintain immune homeostasis. Promoting Treg cell function and increasing their numbers might be useful in treating autoimmune disorders, as well as preventing allograft rejection. However, studies of mice and humans demonstrate that Treg cells promote cancer progression and suppress antitumor immunity. Therefore, suppressing Treg cell function or reducing their numbers could support the immune system's response to pathogenic microorganisms and tumors. As a result, there is great interest in investigating the Treg cells role in the treatment of hematological and nonhematological malignancies. Consequently, Treg cells could be a fundamentally important target for pathologies of the immune system. Targeting effector Treg cells could help to distinguish and selectively decrease these cells while preserving other Treg cells needed to suppress autoimmunity. Currently, a promising way to treat malignancies and other autoimmune disorders is stem cell transplantation. Stem cell transplants (SCT) can help to manage the production of Treg cells and also may produce more efficient Treg cells, thereby suppressing clinical disease progression. Specifically, mature T cells within the engrafted stem cells mediate this SCT beneficial effect. During SCT, the recipient's immune system is replaced with a donor, which allows for improved immune system function. In addition, SCT can protect from disease relapse, as graft-versus-host disease (GvHD) in transplant patients can be protective against cancer recurrence. The current review will define the role of regulatory T cells in treatment of malignancy. Additionally, it will summarize current promising research regarding the utility of regulatory T cells in stem cell transplantation.
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.