Evidence map›Paper›PMID 40029500›Full record

ArticleDiscover oncology2025

Single cell transcriptomic analysis reveals tumor immune infiltration by macrophage cells gene signature in lung adenocarcinoma.

Xiaotong Guo, Youjun Deng, Wenjun Jiang, Heng Li, Yisheng Luo, Huachuan Zhang, Hao Wu

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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.

Xiaotong Guo *Department of Thoracic Surgery, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center Shenzhen Cancer Hospital, Shenzhen, China.
Youjun Deng *Department of Thoracic Surgery, Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center Shenzhen Cancer Hospital, Shenzhen, China.
Wenjun JiangRadiation Oncology Key Laboratory of Sichuan Province, Sichuan Cancer Hospital, Chengdu, China.
Heng LiDepartment of Thoracic Surgery, Yunnan Hospital of Oncology, Kunming, China.
Yisheng LuoDepartment of Thoracic Surgery, Shenzhen Second People's Hospital, Shenzhen, China.
Huachuan ZhangDepartment of Thoracic Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China. Zhanghuachuanq@163.com.
Hao WuDepartment of Thoracic Surgery, Shenzhen Second People's Hospital, Shenzhen, China. haowudr@outlook.com.

Funding

Sanming Project of Medicine in Shenzen Municipality SZSM201612097
6 · The paper itself

Abstract

backgroundTumor-associated macrophages (TAMs) play pivotal roles in innate immunity and contribute to the advancement of lung cancer. We aimed to identify novel TAM-related biomarkers and significance of macrophage infiltration in lung adenocarcinoma (LUAD) through an integrative analysis of single-cell RNA-sequencing (scRNA-seq) data. To describe the cell atlas and construct a novel prognostic signature in LUAD.

methodsThe gene signature linked to TAMs was identified utilizing Scanpy from the scRNA-seq dataset GSE131907. Subsequent analysis involved evaluating the expression levels of these genes, their potential molecular mechanisms, and prognostic significance in LUAD using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We also constructed a risk score models through LASSO Cox regression for these genes. The underlying mechanism was further elucidated through the application of GSEA, ESTIMATE, TIDE, and other bioinformatic algorithms.

resultsSingle-cell atlas was described by analyze 29 scRNA-seq samples from 19 LUAD patients. The TAMs-related gene signature (TGS) was identified as an independent prognostic factor by LASSO Cox regression analysis using differential expression genes (DEGs) derived from pro- and anti-inflammatory macrophage cells. Risk score model including nine TAMs-related genes (FOSL1, ZNF697, ADM, UBE2S, TICAM1, S100P, BIRC3, TLE1, and DEFB1) were obtained for prognosis construction. Moreover, the risk model underwent additional validation in four external GEO cohorts: GSE31210, GSE72094, GSE26939, and GSE30219. Interestingly, TGS-high tumors revealed enrichments in TGF-β signaling and hypoxia pathways, which shown low immune infiltration and immunosuppression by ESTIMATE and TIDE algorithm. The TGS-high risk group exhibited lower richness and diversity in the T-cell receptor (TCR) repertoire.

conclusionThis study introduces a novel TGS score developed through LASSO Cox regression analysis, utilizing DEGs in pro- and anti-inflammatory macrophage cells. High TGS tumors exhibited enrichment in TGF-β signaling and hypoxia pathways, suggesting their potential utility in predicting prognosis and immune responses in patients with LUAD. These results offer promising implications for the development of therapeutic strategies for LUAD.

Indexed as

Immune infiltrationLung adenocarcinoma (LUAD)PrognosisSingle-cell RNA-sequencingTGF-β signalingTumor-associated macrophages (TAMs)

Identifiers

PMID40029500
PMCPMC11876514

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.