Development of a novel disulfidptosis-correlated m6A/m1A/m5C/m7G gene signature to predict prognosis and therapeutic response for lung adenocarcinoma patients by integrated machine-learning

Abstract Background Lung adenocarcinoma (LUAD) represents a significant global health burden, necessitating advanced prognostic tools for improved patient management. RNA modifications (m6A, m1A, m5C, m7G), and disulfidptosis, a novel cell death mechanism, have emerged as promising biomarkers and th...

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Hlavní autoři:	Bilin Xu, Liangyu Zhang, Lijie Lin, Yanfeng Lin, Fancai Lai
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Springer 2024-11-01
Edice:	Discover Oncology
Témata:	Disulfidptosis m6A/m1A/m5C/m7G Machine-learning Lung adenocarcinoma Prognosis
On-line přístup:	https://doi.org/10.1007/s12672-024-01530-y
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