Evidence map›Paper›PMID 39893253›Full record

ArticleCommunications biology2025

Selective inhibition of TGF-β-induced epithelial-mesenchymal transition overcomes chemotherapy resistance in high-risk lung squamous cell carcinoma.

Liangdong Sun, Jue Wang, Huansha Yu, Xinsheng Zhu, Jing Zhang, Junjie Hu, Yilv Yan, Xun Zhang, Yuming Zhu, Gening Jiang and 3 more

Abstract read
In one paragraph

Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  3. Review
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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

13 authors.

Liangdong Sun *Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Jue Wang *Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Huansha YuDepartment of Animal Experimental Center, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Xinsheng ZhuDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Jing ZhangDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Junjie HuDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Yilv YanDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Xun ZhangDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Yuming ZhuDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Gening JiangDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Ming DingSchool of Life Science and Technology, China Pharmaceutical University, Nanjing, Jiangsu, China. mingding@cpu.edu.cn.ORCID http://orcid.org/0000-0002-9135-9275
Peng ZhangDepartment of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China. zhangpeng1121@tongji.edu.cn.ORCID http://orcid.org/0000-0003-1771-7545
Lele ZhangCentral Laboratory, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China. zhanglele@tongji.edu.cn.ORCID http://orcid.org/0000-0002-5595-3103

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82201948
6 · The paper itself

Abstract

Lung squamous cell carcinoma (LUSC) represents a major subtype of lung cancer, and it demonstrates limited treatment options and worse survival. Identifications of a prognostic model and chemoresistance mechanism can be helpful for improving stratification and guiding therapy decisions. The integrative development of machine learning-based models reveals a random survival forest (RSF) prognostic model for LUSC. The 12-gene RSF model exhibits high prognostic power in more than 1,000 LUSC patients. High-risk LUSC patients are associated with worse survival and the activation of the epithelial-mesenchymal transition pathway. Additionally, high-risk LUSC patients are resistant to docetaxel or vinorelbine treatment. In vitro and in vivo drug sensitivity experiments indicates that high-risk HCC15/H226 tumour cells and cell line-derived xenograft models are more resistant to vinorelbine treatment. Furthermore, the combination of chemotherapy with transforming growth factor-β inhibition augments antitumour responses in LUSC tumours. Our study provides valuable insights into prognosis stratification and the development of therapeutic strategies for LUSC.

Indexed as

Carcinoma, Squamous CellDrug Resistance, NeoplasmEpithelial-Mesenchymal TransitionLung NeoplasmsTransforming Growth Factor betaAnimalsCell Line, TumorFemaleHumansMaleMicePrognosisVinorelbineXenograft Model Antitumor AssaysTransforming Growth Factor betaVinorelbine

Identifiers

PMID39893253
PMCPMC11787392

What OpenQuestion holds

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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.