Identification and validation of NETs-related biomarkers in hepatocellular carcinoma through bioinformatics analysis and machine learning algorithms

This study identified NET-related key biomarkers (ECM1, DNASE1L3, JUN) as reliable diagnostic tools for HCC, highlighting their diagnostic and therapeutic potential, and providing insights for HCC diagnostic tools and immunotherapy strategies.

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Publication Details

Journal
Discover Oncology
Published
2026-02-02
DOI
https://doi.org/10.1007/s12672-026-04388-4
Primary Topic
Hepatocellular Carcinoma Treatment and Prognosis
Type
article
Field-Weighted Citation Impact
0.00
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article

Identification and validation of NETs-related biomarkers in hepatocellular carcinoma through bioinformatics analysis and machine learning algorithms

Lele NIE, Qunguang Jiang, Junhua Ai, Zhiyong Hu et al.
Discover Oncology
Hepatocellular Carcinoma Treatment and Prognosis
article

Identification and validation of NETs-related biomarkers in hepatocellular carcinoma through bioinformatics analysis and machine learning algorithms

Lele NIE, Qunguang Jiang, Junhua Ai, Zhiyong Hu, Bo Tang
article en

Abstract

This study identified NET-related key biomarkers (ECM1, DNASE1L3, JUN) as reliable diagnostic tools for HCC, highlighting their diagnostic and therapeutic potential, and providing insights for HCC diagnostic tools and immunotherapy strategies.

Discover OncologyVol. 17(1)
Nanchang University (CN), First Affiliated Hospital of Jiangxi Medical College (CN), Fuzhou General Hospital of Nanjing Military Command (CN), First Affiliated Hospital of Nanchang University (CN)
Good health and well-being
Openalex Percentile: Top 68%
Hepatocellular Carcinoma Treatment and Prognosis
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