Evidence map›Paper›PMID 37561221›Full record

ArticleClinical and experimental medicine2023

Identifying prognostic biomarker related to immune infiltration in acute myeloid leukemia.

Weixiang Lu, Guopan Yu, Yanlin Li, Changxin Yin, Jiaxin Long, Xiaofan Chen, Yanxiao Chen, Zhongxin Zheng, Yujie Lai, Xinyu Zhou and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Clinical and experimental medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

11 authors at 3 institutions in 1 country.

Weixiang Lu *Department of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Guopan Yu *Department of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Yanlin LiDepartment of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Changxin YinDepartment of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Jiaxin LongDepartment of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Xiaofan ChenDepartment of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Yanxiao ChenDepartment of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Zhongxin ZhengDepartment of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China.
Yujie LaiThe First Clinical Medical College, Guangdong Medical University, Zhanjiang, 524000, China.
Xinyu ZhouThe First Clinical Medical College, Guangdong Medical University, Zhanjiang, 524000, China.
Dan XuDepartment of Hematology, Nanfang Hospital, Southern Medical University, No.1838 Guangzhou Avenue North, Guangzhou, 510515, China. xudanxiang@163.com.
Nanfang Hospital · CNSouthern Medical University · CNGuangdong Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The immune cells of tumor microenvironment (TME) constitute a vital element of the tumor tissue. There is increasing evidence for their clinical significance in predicting prognosis and therapeutic outcomes. However, the TME immune cell infiltrating pattern of the bone marrow in acute myeloid leukemia (AML) patients remains unclear. Here, RNA-sequencing results of AML patients from TCGA database were used to quantify the abundance of 28 types of immune cells in the TME using the single-sample gene set enrichment analysis algorithm. We comprehensively evaluated the immune infiltration status in the TCGA-LAML cohort and defined two immunophenotypes: the immune hot and immune cold subtypes. Additionally, we constructed a TME score reflecting the immune infiltrating pattern of the patients using Cox regression algorithm. Subtypes with high TME score were characterized by over-activation of immune inflammation-related pathways, release of inflammatory factors, T-cell dysfunction, and poor prognosis. Subtypes with a low TME score were characterized by relatively low immune infiltration and immune exclusion. Our analysis indicated that patients in the low TME score group were more sensitive to chemotherapeutic drugs, and those in high TME score were more likely to respond to immunotherapy. Our study provides a new direction to evaluate anti-tumor therapy from immune infiltration of the TME, and the individualized scoring system in this study has important clinical significance in identifying patients who respond to immunotherapy.

Indexed as

Leukemia, Myeloid, AcuteBiomarkersHumansImmunophenotypingImmunotherapyPrognosisTumor MicroenvironmentBiomarkersAcute myeloid leukemiaImmune infiltrationImmunophenotypeTumor microenvironment

Identifiers

PMID37561221
OpenAlexW4385715404

What OpenQuestion holds

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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.