Evidence map›Paper›PMID 40673074›Full record

ArticleTranslational lung cancer research2025

Identification of prognostic-related tumor microenvironment genes in lung adenocarcinoma and establishment of a prognostic prediction model.

Xisheng Fang, Shaopeng Zheng, Zekui Fang, Xiping Wu, Erin L Schenk, Lorenzo Belluomini, Huizhen Fan

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Article in Translational lung cancer research, 2025. 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
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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

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xisheng Fang *Department of Oncology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, China.
Shaopeng Zheng *Department of Thoracic Surgery, Cancer Hospital of Shantou University Medical College, Shantou, China.
Zekui FangDepartment of Pulmonary and Critical Care Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Xiping WuDepartment of Pulmonary and Critical Care Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Erin L SchenkDivision of Medical Oncology, Department of Medicine, University of Colorado - Anschutz Medical Campus, Aurora, CO, USA.
Lorenzo BelluominiSection of Innovation Biomedicine - Oncology Area, Department of Engineering for Innovation Medicine (DIMI), University of Verona School of Medicine and Verona University Hospital Trust, Verona, Italy.
Huizhen FanDepartment of Pulmonary and Critical Care Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: With the swift advancements in immunotherapy for solid tumors, exploring immune characteristics of tumors has become increasingly important. The tumor microenvironment (TME) is closely related to the prognosis and treatment of tumor patients. This study aims to explore the expression characteristics and model construction of TME-related genes in lung adenocarcinoma (LUAD) patients, and provide help for clinical diagnosis and treatment. Methods: Through the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm, we analyzed the transcriptomic data of 559 samples from The Cancer Genome Atlas (TCGA) data set to estimate the stromal cells and immune cells, and screened the immune-related differentially expressed genes (DEGs), namely, the TME-DEGs. Essential TME genes were then selected from the TME-DEGs by multivariate Cox and least absolute shrinkage and selection operator (LASSO) regression, and a prediction model of prognostic risk score (RS) was established. Results: We identified 5 crucial TME genes: Conclusions: Five crucial TME genes,

Indexed as

differentially expressed genes (DEGs)lung adenocarcinoma (LUAD)prediction modelTumor microenvironment (TME)

Identifiers

PMID40673074
PMCPMC12261383

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