Landscape of Cell States and Multicellular Ecotypes in Non-Small Cell Lung Cancer.

Honghao Li, Yan Jiang, Zhengchun Huo, Shaokang Li, Xu Luo, Yumeng Xie, Qilemuge Xi, Shiyuan Wang, Lei Yang

Abstract read

In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Honghao LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Yan JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Zhengchun HuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Shaokang LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Xu LuoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Yumeng XieCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Qilemuge XiThe State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, College of Life Sciences, Inner Mongolia University, Hohhot 010070, China.

Shiyuan WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Lei YangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.ORCID 0000-0002-1133-9099

Funding

National Natural Science Foundation of China No. 62173117; No. 62461046

6 · The paper itself

Abstract

Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer and remains a major global health burden. Comprehensive characterization of tumor microenvironment (TME) heterogeneity is critical for understanding tumor progression and clinical outcomes in NSCLC. In this study, we identified 34 transcriptionally defined cell states and 6 multicellular ecotypes using the EcoTyper framework, thereby systematically delineating the TME landscape of NSCLC. These cell states and ecotypes were further validated across 11 independent bulk transcriptomic cohorts, one single-cell RNA sequencing cohort, and one spatial transcriptomics cohort, demonstrating strong reproducibility and robustness. Prognostic analyses revealed that several cell states and ecotypes were significantly associated with patient survival outcomes in NSCLC. Transcriptional regulatory analysis further identified

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsTumor MicroenvironmentEcotypeGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisTranscriptomecell statesclinical prognosisnon-small cell lung cancertranscriptional regulatortumor microenvironment

Identifiers

PMID42589378

DOI10.3390/ijms27156718

PMCPMC13467122

What Socratic holds

Textmetadata

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 Socratic graph.