Evidence map›Paper›PMID 40993741›Full record

ArticleJournal of translational medicine2025

Integrative single-cell and machine learning approach to characterize immunogenic cell death and tumor microenvironment in LUAD.

Han Zhang, Qiuqiao Mu, Yuhang Jiang, Xiaojiang Zhao, Xiaoteng Jia, Kai Wang, Xin Li, Daqiang Sun

Abstract read
In one paragraph

Article in Journal of translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Han Zhang *Tianjin Chest Hospital, Tianjin University, Tianjin, China.
Qiuqiao Mu *Tianjin Chest Hospital, Tianjin University, Tianjin, China.
Yuhang Jiang *Tianjin Chest Hospital, Tianjin University, Tianjin, China.
Xiaojiang ZhaoTianjin Chest Hospital, Tianjin University, Tianjin, China.
Xiaoteng JiaTianjin Chest Hospital, Tianjin University, Tianjin, China.
Kai WangTianjin Chest Hospital, Tianjin University, Tianjin, China.
Xin LiTianjin Chest Hospital, Tianjin University, Tianjin, China.
Daqiang SunTianjin Chest Hospital, Tianjin University, Tianjin, China. sdqmd@tju.edu.cn.ORCID 0009-0000-6602-357X

Funding

Tianjin Health Research Project(TJWJ2024QN063) TJWJ2024QN063Tianjin Key Medical Discipline (Specialty) Construction Project TJYXZDXK-018A
6 · The paper itself

Abstract

backgroundImmunogenic cell death (ICD) triggers antitumor immune responses and plays a critical role in shaping the tumor microenvironment (TME). However, its specific contribution to lung adenocarcinoma (LUAD) progression and immunotherapy response remains insufficiently explored.

methodWe integrated single-cell RNA sequencing with machine learning to characterize ICD-related transcriptional features in LUAD. ICD activity was quantified across cell types using five scoring algorithms. To develop a robust prognostic model, we evaluated over 100 machine learning algorithm combinations and selected the CoxBoost + SuperPC approach based on the highest concordance index (C-index). The resulting ICD-related gene signature (ICDRS) was validated in six external cohorts. Downstream analyses included immune infiltration, mutation profiling, drug sensitivity, and immunotherapy response. SLC2A1 was selected for functional validation using qRT-PCR, CCK-8, Transwell, colony formation, and xenograft assays.

resultsSingle-cell analysis revealed that macrophages exhibited the highest ICD activity and contributed significantly to intercellular communication. Based on ICD-associated genes, the ICDRS model consisting of 11 core genes was constructed and showed superior prognostic performance over 112 published LUAD signatures across multiple cohorts. The ICDRS stratified patients into distinct risk groups with significant differences in overall survival, immune infiltration patterns, and immunotherapy benefit. Low-risk patients exhibited higher levels of CD8⁺ T cells, dendritic cells, and immune function scores, along with greater sensitivity to standard chemotherapeutics and immune checkpoint inhibitors. Functional experiments confirmed that SLC2A1 was upregulated in LUAD tissues and cell lines. Silencing SLC2A1 suppressed proliferation and invasion in vitro and inhibited tumor growth in xenograft models, supporting its oncogenic role.

conclusionThis study highlights the crucial role of ICD in LUAD immune regulation and prognosis. The ICDRS serves as a robust biomarker for risk stratification and immunotherapy guidance, while SLC2A1 emerges as a potential therapeutic target to augment immunotherapeutic efficacy.

Indexed as

Adenocarcinoma of LungImmunogenic Cell DeathLung NeoplasmsMachine LearningSingle-Cell AnalysisTumor MicroenvironmentAnimalsCell Line, TumorGene Expression Regulation, NeoplasticHumansMicePrognosisReproducibility of ResultsICD3Immunotherapy5LUAD1Machine Learning4scRNA-seq2SLC2A16

Identifiers

PMID40993741
PMCPMC12462218

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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.