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

The PCD signature confers significant potential to predict prognosis of LUAD in patients, and NAPSA is promising as a new marker for predicting the efficacy of immunotherapy.

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Publication Details

Journal
Cell Biology and Toxicology
Published
2026-01-07
DOI
https://doi.org/10.1007/s10565-025-10125-4
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Bin Luo, youfang chen, Wuguang Chang, Zhesheng Wen
Cell Biology and Toxicology
Cancer Immunotherapy and Biomarkers
article

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

Bin Luo, youfang chen, Wuguang Chang, Zhesheng Wen
article en

Abstract

The PCD signature confers significant potential to predict prognosis of LUAD in patients, and NAPSA is promising as a new marker for predicting the efficacy of immunotherapy.

Cell Biology and ToxicologyVol. 42(1)
Sun Yat-sen University (CN), Fifth Affiliated Hospital of Sun Yat-sen University (CN), Sun Yat-sen University Cancer Center (CN)
Good health and well-being
Openalex Percentile: Top 96%
Cancer Immunotherapy and Biomarkers
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Harnessing machine learning-driven multiomics integration: deciphering programmed cell death networks for prognostication and immunotherapy prediction in lung adenocarcinoma — Bin Luo, youfang chen, et al. · Cell Biology and Toxicology (2026) | TGRS Research Map | TGRS