Evidence map›Paper›PMID 38627685›Full record

ArticleCancer cell international2024

A novel immunogenic cell death-related classification indicates the immune landscape and predicts clinical outcome and treatment response in acute myeloid leukemia.

Fangmin Zhong, Shuyang He, Ni Guo, Luyi Shi, Linlin Zhang, Hua Jin, Guangyao Kong

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 3 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

7 authors at 2 institutions in 1 country.

Fangmin ZhongDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Shuyang HeQueen Mary School of Nanchang University, Nanchang, Jiangxi, People's Republic of China.
Ni GuoPrecision Medical Institute, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Luyi ShiPrecision Medical Institute, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Linlin ZhangPrecision Medical Institute, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Hua JinPrecision Medical Institute, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China.
Guangyao KongDepartment of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, People's Republic of China. konggy@xjtu.edu.cn.
Second Affiliated Hospital of Xi'an Jiaotong University · CNNanchang University · CN

Funding

National Key Research and Development Program of China 2019YFA0801804National Natural Science Foundation of China 82170140, 82370146, and 82100150Natural Science Foundation of Jiangxi Province 20232BAB216037Natural Science Foundation of Shanxi Province 2022JQ-776, 2022JQ-946, and 2020JQ-558
6 · The paper itself

Abstract

backgroundImmunogenic cell death (ICD) is closely related to anti-tumor therapy and regulates the tumor microenvironment (TME). This study aims to explore the molecular characteristics of ICD in acute myeloid leukemia (AML) and to analyze the value of ICD-related biomarkers in TME indication, prognosis prediction, and treatment response evaluation in AML.

methodsSingle-sample gene set enrichment analysis was used to calculate the ICD score. LASSO regression was used to construct a prognostic risk score model. We also analyzed differences in clinical characteristics, immune landscape, immunotherapy response, and chemotherapy sensitivity between high-risk and low-risk patients.

resultsThis study identified two ICD-related subtypes and found significant heterogeneity in clinical prognosis, TME, and immune landscape between different ICD subtypes. Subsequently, a novel ICD-related prognostic risk score model was developed, which accurately predicted the prognosis of AML patients and was validated in nine AML cohorts. Moreover, there were significant correlations between risk scores and clinicopathological factors, somatic mutations, TME characteristics, immune cell infiltration, immunotherapy response, and chemosensitivity. We further validated the model gene expression in a clinically real-world cohort.

conclusionsThe novel ICD-related signatures identified and validated by us can serve as promising biomarkers for predicting clinical outcomes, chemotherapy sensitivity, and immunotherapy response in AML patients, guiding the establishment of personalized and accurate treatment strategies for AML.

Identifiers

PMID38627685
PMCPMC11022379
OpenAlexW4394856695

What Socratic holds

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LicenceCC BY
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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 Socratic graph.