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Harnessing machine learning-driven multiomics integration: deciphering programmed cell death networks for prognostication and immunotherapy prediction in lung adenocarcinoma

Crossref DOI link: https://doi.org/10.1007/s10565-025-10125-4

Published Online: 2026-01-07

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

Authors

Chang, Wuguang

Luo, Bin

Wen, Zhesheng

Chen, Youfang
Funding

Funding for this research was provided by:

Guangdong Basic and Applied Basic Research Foundation (2024A1515013219)

Fostering Program for NSFC Young Applicants (Tulip Talent Training Program) of Sun Yat-sen University Cancer Center (2024yfd11)
License Information

Text and Data Mining valid from 2026-01-07

Version of Record valid from 2026-01-21
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Article History

Received: 7 August 2025

Accepted: 22 November 2025

First Online: 7 January 2026

Declarations

:

: All samples were collected with the written informed consent of the patients and their families, and the collection process strictly adhered to the principles outlined in the Declaration of Helsinki. This study has been approved by the Ethics Committee of the Cancer Center, Sun Yat-sen University (B2024-064–01).

: The authors declare no competing interests.

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