Comprehensive multi-omics analysis identifies chromatin regulator-related signatures and TFF1 as a therapeutic target in lung adenocarcinoma through a 429-combination machine learning approach.

Journal: Frontiers in immunology

PMID: 39539551

Abstract

INTRODUCTION: Lung cancer is a leading cause of cancer-related deaths, with its incidence continuing to rise. Chromatin remodeling, a crucial process in gene expression regulation, plays a significant role in the development and progression of malignant tumors. However, the role of chromatin regulators (CRs) in lung adenocarcinoma (LUAD) remains underexplored.

Authors

Jun Fan

Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
BoGuang Chen

Oncology Department I, Huai'an 82 Hospital, Huai'an, Jiangsu, China.
Hao Wu

Zhejiang Institute of Tianjin University (Shaoxing), Shaoxing, China.
Xiaoqing Liang

Department of Oncology, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
Wen Shen
Xiaye Miao

Department of Laboratory Medicine, Northern Jiangsu People's Hospital, Yangzhou, China.

Keywords

Adenocarcinoma of Lung Animals Apoptosis Biomarkers, Tumor Cell Line, Tumor Cell Proliferation Chromatin Female Gene Expression Regulation, Neoplastic Humans Lung Neoplasms Machine Learning Mice Multiomics Prognosis Trefoil Factor-1 Tumor Microenvironment Xenograft Model Antitumor Assays

External Resources

View on PubMed Access via DOI PubMed (39539551)

Comprehensive multi-omics analysis identifies chromatin regulator-related signatures and TFF1 as a therapeutic target in lung adenocarcinoma through a 429-combination machine learning approach.

Abstract

Authors

Keywords

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