Evidence map›Paper›PMID 35355427›Full record

ArticleCancer medicine2022

Immune-related gene signature predicts clinical outcomes and immunotherapy response in acute myeloid leukemia.

Qiang Xu, Dedong Cao, Bin Fang, Siqi Yan, Yu Hu, Tao Guo

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

7 citing papers in PubMed, 7 citations in OpenAlex.

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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 2 institutions in 1 country.

Qiang XuInstitute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Dedong CaoDepartment of Oncology, Renmin Hospital of Wuhan University, Wuhan, China.ORCID 0000-0002-5777-4176
Bin FangDepartment of Nephrology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Siqi YanInstitute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yu HuInstitute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tao GuoInstitute of Hematology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0001-7714-9020
Union Hospital · CNWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe immune response in the bone marrow microenvironment has implications for progression and prognosis in acute myeloid leukemia (AML). However, few immune-related biomarkers for AML prognosis and immunotherapy response have been identified. We aimed to establish a predictive gene signature and to explore the determinants of prognosis in AML.

methodsImmune-related genes with clinical significance were screened by a weighted gene co-expression network analysis. Seven immune-related genes were used to establish a gene signature by a multivariate Cox regression analysis. Based on the signature, low- and high-risk groups were compared with respect to the immune microenvironment, immune checkpoints, pathway activities, and mutation frequencies. The tumor immune dysfunction and exclusion (TIDE) method was used to predict the response to immune checkpoint blockade (ICB) therapy. The Connectivity Map database was used to explore small-molecule drugs expected to treat high-risk populations.

resultsA seven-gene prognostic signature was used to classify patients into high- and low-risk groups. Prognosis was poorer for patients in the former than in the latter. The high-risk group displayed higher levels of immune checkpoint molecules (LAG3, PD-1, CTLA4, PD-L2, and PD-L1), immune cell infiltration (dendritic cells, T helper 1, and gamma delta T), and somatic mutations (NPM1 and RUNX1). Moreover, hematopoietic stem cell/leukemia stem cell pathways were enriched in the high-risk phenotype. Compared with that in the low-risk group, the lower TIDE score for the high-risk group implied that this group is more likely to benefit from ICB therapy. Finally, some drugs (FLT3 inhibitors and BCL inhibitors) targeting the expression profiles associated with the high-risk group were generated using Connectivity Map.

conclusionThe newly developed immune-related gene signature is an effective biomarker for predicting prognosis in AML and provides a basis, from an immunological perspective, for the development of comprehensive therapeutic strategies.

Indexed as

Leukemia, Myeloid, AcuteBiomarkers, TumorBone MarrowHumansImmunologic FactorsImmunotherapyPhenotypePrognosisTumor MicroenvironmentBiomarkers, TumorImmunologic Factorsacute myeloid leukemiabiomarkerimmune microenvironmentimmunotherapyprognosis

Identifiers

PMID35355427
PMCPMC9468431
OpenAlexW4221112809

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LicenceCC BY
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Registered trials

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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.