Evidence map›Paper›PMID 41441926›Full record

ArticleDiscover oncology2025

Single cell transcriptomic profiling uncovers shared inflammatory pathways and immune dysregulation underlying the asthma to lung cancer transition.

He Huang, Gang Teng, Jing Zhou, Ling Liu, Mei Dong, Wei Chen, Nianzhi Zhang

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 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

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

2 citing papers in PubMed.

  1. Article
  2. 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.

He HuangDepartment of Respiratory Medicine, The First Affiliated Hospital of Anhui University of Chinese Medicine, No.117 Meishan Road, Hefei, 230031, China.
Gang TengDepartment of Respiratory Medicine, The First Affiliated Hospital of Anhui University of Chinese Medicine, No.117 Meishan Road, Hefei, 230031, China.
Jing ZhouDepartment of Respiratory Medicine, The First Affiliated Hospital of Anhui University of Chinese Medicine, No.117 Meishan Road, Hefei, 230031, China.
Ling LiuDepartment of Respiratory Medicine, The First Affiliated Hospital of Anhui University of Chinese Medicine, No.117 Meishan Road, Hefei, 230031, China.
Mei DongDepartment of Respiratory Medicine, The First Affiliated Hospital of Anhui University of Chinese Medicine, No.117 Meishan Road, Hefei, 230031, China.
Wei ChenDepartment of Respiratory Medicine, The First Affiliated Hospital of Anhui University of Chinese Medicine, No.117 Meishan Road, Hefei, 230031, China.
Nianzhi ZhangDepartment of Respiratory Medicine, The First Affiliated Hospital of Anhui University of Chinese Medicine, No.117 Meishan Road, Hefei, 230031, China. zhangnianzhiazy@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWorldwide, lung cancer stands as the predominant contributor to cancer mortality, characterized by substantial heterogeneity alongside intricate tumor microenvironment interactions. Gaining insight into how immune cells behave across space and time, coupled with profiling key gene expression, offers pathways toward comprehending disease advancement and uncovering therapeutic innovations.

methodsCharacterization of the lung cancer immune cell landscape was achieved through single-cell RNA sequencing technology. Advanced dimensionality reduction techniques, encompassing UMAP and t-SNE methodologies, enabled multimodal examination of how cells are composed and distributed spatially. Gene Ontology (GO) enrichment alongside pathway analyses were executed to pinpoint biological processes and signaling networks operating within the immune microenvironment. To validate the transcriptomic findings, quantitative real-time PCR (qRT-PCR) was conducted in lung cancer cell lines to assess the relative expression of CXCL12, CXCR4, and PD-L1 using GAPDH as an internal control.

resultsOur investigation uncovered an intricate immune cell subpopulation architecture displaying distinctive spatial arrangement patterns. Among various cell types, key genes exhibited particular expression signatures, with tumor-associated macrophages and cytotoxic T cells showing elevated expression levels. Functioning as a principal coordinator of immune cell interactions, the CXCL12-CXCR4 signaling axis stood out prominently. Through pseudotime trajectory examination, we documented evolving patterns in cellular proportions and representative gene expression, reflecting how immune responses transform throughout tumor development. qRT-PCR analysis further confirmed that CXCL12, CXCR4, and PD-L1 were significantly upregulated in lung cancer cell lines, consistent with the single-cell sequencing results.

conclusionThrough investigating immune cell spatiotemporal behaviors and key gene activities, our research illuminates the intricate immune architecture within lung cancer microenvironments. Personalized immunotherapy development will be guided by these insights, which clarify how specific immune cells function while exposing prospective therapeutic intervention points. Additionally, qRT-PCR validation in lung cancer cell lines confirmed the differential expression of CXCL12, CXCR4, and PD-L1, reinforcing the robustness and translational relevance of our single-cell findings.

Indexed as

CXCL12-CXCR4 axisImmunotherapyLung cancerSingle-cell RNA sequencingTumor microenvironment

Identifiers

PMID41441926
PMCPMC12770138

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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.