Evidence map›Paper›PMID 40140461›Full record

ArticleScientific reports2025

Single-cell RNA sequencing reveals potential therapeutic targets in the tumor microenvironment of lung squamous cell carcinoma.

Junda Fan, Yu Chen, Yue Gong, Hongmei Sun, Rui Hou, Xiaoya Dou, Yanping Zhang, Cheng Huo

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

8 authors.

Junda Fan *Department of Oncology, 242 Hospital Affiliated to Shenyang Medical College, Shenyang, 110034, China.
Yu Chen *Jiamusi Central Hospital, Jiamusi, 154000, China.
Yue GongGeneis Beijing Co., Ltd, Beijing, 100102, China.
Hongmei SunDepartment of Medical Oncology, The Cancer Hospital of Jia Mu Si, Jiamusi, 154000, China.
Rui HouGeneis Beijing Co., Ltd, Beijing, 100102, China.
Xiaoya DouGeneis Beijing Co., Ltd, Beijing, 100102, China.
Yanping ZhangSchool of Mathematics and Physics Science and Engineering, Hebei University of Engineering, Handan, 056038, China.
Cheng HuoDepartmen of Pathology, Sinopharm Tongmei General Hospital, Datong, 037003, China. huocheng_tmzy@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung squamous cell carcinoma (LUSC), accounting for 30% of lung cancer cases, lacks adequate research due to limited understanding of its molecular abnormalities. Our study analyzed public LUSC datasets to explore the tumor microenvironment (TME) composition using scRNA-seq from two cohorts. Applying non-negative matrix factorization, we identified unique malignant cell phenotypes, or meta-programs (MPs), based on gene expression patterns. Survival analysis revealed the clinical relevance of these MPs. Findings illuminated a TME landscape enriched with immune cells-CD8 + T, exhausted T, CD4 + T, and naive T cells-and suggested roles for myeloid cells, like cDC1 and pDCs, in LUSC progression. Different MPs highlighted the heterogeneity of malignant cells and their clinical implications. Targeting MP-specific genes may enable personalized therapy, especially for early-stage LUSC. This study offers insights into immune cell function in tumor dynamics, identifies MPs, and paves the way for novel LUSC strategies, enhancing early intervention, personalized treatment, and prognosis, ultimately improving patient outcomes.

Indexed as

Carcinoma, Squamous CellLung NeoplasmsSingle-Cell AnalysisTumor MicroenvironmentBiomarkers, TumorGene Expression Regulation, NeoplasticHumansPrognosisSequence Analysis, RNABiomarkers, TumorBioinformaticsLung cancerNon-negative matrix factorizationSingle-cell RNA sequencingTumor microenvironment

Identifiers

PMID40140461
PMCPMC11947091

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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.