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Integrative single-cell and machine learning framework reveals prognostic fibroblast subtypes and constructs a fibroblast-related risk signature in lung adenocarcinoma

Crossref DOI link: https://doi.org/10.1038/s41598-026-35830-w

Published Online: 2026-02-09

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Cheng, Shizhao

Zhang, Han

Mu, Qiuqiao

Zhang, Hao

Tan, Lin

Sun, Daqiang
Funding

Funding for this research was provided by:

Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-018A)
License Information

Text and Data Mining valid from 2026-02-09

Accepted Manuscript valid from 2026-02-09
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Article History

Received: 5 June 2025

Accepted: 8 January 2026

First Online: 9 February 2026

Declarations

:

: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The authors declare no competing interests.

: All participants in this study signed informed consent forms. The study was conducted in accordance with the Declaration of Helsinki and received approval from the Ethics Committee of Tianjin Chest Hospital. Participants were prospectively recruited between May 2024 and March 2025.

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