ReviewJournal of immunology research2020
Activating the Antitumor Immune Response in Non-Hodgkin Lymphoma Using Immune Checkpoint Inhibitors.
Review in Journal of immunology research, 2020. 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, 16 citations in OpenAlex.
- Review
- Review
- Development of a recombinant human IgG1 monoclonal antibody against the TRBV5-1 segment of the T cell receptor for the treatment of mature T cell neoplasms.Frontiers in immunology · 2024Article
- Tumor microenvironment contribution to checkpoint blockade therapy: lessons learned from Hodgkin lymphoma.Blood · 2023Article
- Dysfunctions of innate and adaptive immune tumor microenvironment in Waldenström macroglobulinemia.International journal of cancer · 2023Article
- Review
- Unravelling soluble immune checkpoints in chronic lymphocytic leukemia: Physiological immunomodulators or immune dysfunction.Frontiers in immunology · 2022Article
- Engaging the Innate and Adaptive Antitumor Immune Response in Lymphoma.International journal of molecular sciences · 2021Review
- CD4-Targeted T Cells Rapidly Induce Remissions in Mice with T Cell Lymphoma.BioMed research international · 2021Article
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
Non-Hodgkin lymphomas comprise a heterogenous group of disorders which differ in biology. Although response rates are high in some groups, relapsed disease can be difficult to treat, and newer approaches are needed for this patient population. It is increasingly apparent that the immune system plays a significant role in the propagation and survival of malignant cells. Immune checkpoint blocking agents augment cytotoxic activity of the adaptive and innate immune systems and enhance tumor cell killing. Anti-PD-1 and anti-CTLA-4 antibodies have been tested as both single agents and combination therapy. Although success rates with anti-PD-1 antibodies are high in patients with Hodgkin lymphoma, the results are yet to be replicated in those with non-Hodgkin lymphomas. Some lymphoma histologies, such as primary mediastinal B cell lymphoma (PMBL), central nervous system, and testicular lymphomas and gray zone lymphoma, respond favorably to PD-1 blockade, but the response rates in most lymphoma subtypes are low. Other agents including those targeting the adaptive immune system such as TIM-3, TIGIT, and BTLA and innate immune system such as CD47 and KIR are therefore in trials to test alternative ways to activate the immune system. Patient selection based on tumor biology is likely to be a determining factor in treatment response in patients, and further research exploring optimal patient populations, newer targets, and combination therapy as well as identifying biomarkers is needed.
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.