Evidence map›Paper›PMID 39773365›Full record

ArticleBMC cancer2025

Highly proliferating cancer cells function as novel prognostic biomarkers for lung adenocarcinoma with particular usefulness for stage IA risk stratification.

Yanlu Xiong, Yongfu Ma, Jie Lei, Jianfei Zhu, Nianlin Xie, Feng Tian, Qiang Lu, Miaomiao Wen, Qian Zheng, Yong Han and 2 more

Abstract read
In one paragraph

Article in BMC cancer, 2025. 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
–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

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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.

  1. Article
  2. Computational and structural biotechnology journal · 2025
    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

12 authors.

Yanlu Xiong *Department of Thoracic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Yongfu Ma *Department of Thoracic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Jie Lei *Department of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Jianfei ZhuDepartment of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Nianlin XieDepartment of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Feng TianDepartment of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Qiang LuDepartment of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Miaomiao WenDepartment of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Qian ZhengDepartment of Thoracic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Yong HanDepartment of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Tao JiangDepartment of Thoracic Surgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China. jiangtaochest@163.com.ORCID http://orcid.org/0000-0002-5848-1922
Yang LiuDepartment of Thoracic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China. sunny301x@sina.com.

Funding

National Natural Science Foundation of China 82002421
6 · The paper itself

Abstract

backgroundThe refinement of risk stratification in lung adenocarcinoma (LUAD) plays a pivotal role in advancing precision medicine; however, the current staging classification falls short of comprehensiveness, particularly in the case of stage IA patients. We aimed to molecularly stratify LUAD patients especially for stage IA.

methodsWe analysed tumour heterogeneity and identified highly proliferating cancer cells (HPCs) in LUAD by performing single-cell RNA sequencing (scRNA-seq) analysis, immunohistochemical (IHC) staining using a tissue microarray, flow cytometry and biological experiments. Then, we quantified the content of HPCs in nine LUAD datasets by single-sample gene set enrichment analysis and evaluated the relationship between the percentage of HPCs and overall survival (OS). Next, we analysed the OS predictive effect of HPCs at different LUAD stages, especially for stage I risk stratification. Furthermore, we established a prognostic prediction model based on HPC-associated genes for clinical application. The above findings were validated in another five LUAD datasets. Finally, we explored the relationship between HPCs and the progressive pathological evolution of early-stage LUAD and the driving mutations by scRNA-seq, bulk RNA-seq and IHC staining.

resultsLUAD tissues carry a small proportion of HPCs, which show potential for malignant proliferation and intense interactions with the microenvironment. A high HPC content is an independent risk factor for OS in LUAD patients, even in stage IA patients. HPCs can be used to establish a cut-off point for the prognosis of stage IA disease, with patients with a higher risk showing a prognosis similar to that of patients with stage IB disease. We built an R package (HSurADs) based on HPC-associated genes, which exhibited good efficacy for the prognostic prediction of LUAD. HPCs gradually increase with the pathological evolution of early-stage LUAD, which may be affected by TP53 mutations.

conclusionThe HPC content can be used as a novel prognostic factor for LUAD, especially for stage IA risk stratification.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorCell ProliferationLung NeoplasmsNeoplasm StagingAgedFemaleHumansMaleMiddle AgedMutationPrognosisRisk AssessmentSingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorHighly proliferating cancer cellsLung adenocarcinomaPrognosisStage IA

Identifiers

PMID39773365
PMCPMC11707901

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LicenceCC BY-NC-ND
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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.