Evidence map›Paper›PMID 28679300›Full record

ReviewLeukemia & lymphoma2018

The emerging role of immune checkpoint based approaches in AML and MDS.

Prajwal Boddu, Hagop Kantarjian, Guillermo Garcia-Manero, James Allison, Padmanee Sharma, Naval Daver

Abstract readReview
In one paragraph

Review in Leukemia & lymphoma, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed
8.8field-weighted citation impact, top 2% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 111 citations in OpenAlex.

  1. Trial
  2. The Journal of international medical research · 2020
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  18. Immunologic Predictors for Clinical Responses during Immune Checkpoint Blockade in Patients with Myelodysplastic Syndromes.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023
    Article
  19. Can Immune Therapy Cure Acute Myeloid Leukemia?Current treatment options in oncology · 2023
    Review
  20. Review

3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Prajwal Boddua Department of Leukemia , The University of Texas M. D. Anderson Cancer Center , Houston , TX , USA.ORCID 0000-0001-9408-5882
Hagop Kantarjiana Department of Leukemia , The University of Texas M. D. Anderson Cancer Center , Houston , TX , USA.
Guillermo Garcia-Maneroa Department of Leukemia , The University of Texas M. D. Anderson Cancer Center , Houston , TX , USA.
James Allisona Department of Leukemia , The University of Texas M. D. Anderson Cancer Center , Houston , TX , USA.
Padmanee Sharmab Immunotherapy Platform , The University of Texas M. D. Anderson Cancer Center , Houston , TX , USA.
Naval Davera Department of Leukemia , The University of Texas M. D. Anderson Cancer Center , Houston , TX , USA.
The University of Texas MD Anderson Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
University of Texas M.D. Anderson Cancer SPORE-LeukemiaP50CA100632 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KONOPLEVA, MARINA Y · 2003 to 2023
$43.7M
NCI NIH HHS P30 CA016672NCI NIH HHS P50 CA100632
6 · The paper itself

Abstract

The development of immune checkpoint inhibitors represents a major breakthrough in the field of cancer therapeutics. Pursuant to their success in melanoma and numerous solid tumor malignancies, these agents are being investigated in hematological malignancies including acute myelogenous leukemia (AML) and myelodysplastic syndromes (MDS). Although AML/MDS have traditionally been considered to be less immunogenic than solid tumor malignancies, recent pre-clinical models suggest a therapeutic role for immune checkpoint inhibition in these diseases. CTLA-4 inhibition may be especially effective in treating late post-allogeneic stem cell transplant relapse of AML in patients with limited or no graft versus host disease. Immune checkpoint inhibition, specifically PD-1 inhibition, demonstrated limited single agent efficacy in patients with relapsed AML and with MDS post-hypomethylating therapy. Rationally designed combinations of PD-1 inhibitors with standard anti-leukemic therapy are needed. Hypomethylating agents such as azacitidine, up-regulate PD-1, PD-L1, and PD-L2 in patients with AML/MDS and up-regulation of these genes was associated with the emergence of resistance. The combination of azacitidine and PD-1/PD-L1 inhibition may be a potential mechanism to prevent or overcome resistance to 5-azacitidine. A number of such combinations are being evaluated in clinical trials with early encouraging results. Immune checkpoint inhibition is also an attractive option to improve relapse-free survival or eliminate minimal residual disease post induction and consolidation by enhancing T-cell surveillance in patients with high-risk AML. The ongoing clinical trials with checkpoint inhibitors in AML/MDS will improve our understanding of the immunobiology of these diseases and guide us to the most appropriate application of these agents in the therapy of AML/MDS.

Indexed as

Antineoplastic Agents, ImmunologicalAntineoplastic Combined Chemotherapy ProtocolsClinical Trials as TopicCostimulatory and Inhibitory T-Cell ReceptorsDNA MethylationDrug Resistance, NeoplasmHumansLeukemia, Myeloid, AcuteMyelodysplastic SyndromesT-LymphocytesTreatment OutcomeUp-RegulationAntineoplastic Agents, ImmunologicalCostimulatory and Inhibitory T-Cell Receptorsacute myeloid leukemiaCheckpoint inhibitorsimmunotherapymyelodysplastic syndrome

Identifiers

PMID28679300
PMCPMC5872841
OpenAlexW2733520933

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.