An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

Journal: Journal of cancer research and clinical oncology

PMID: 32968877

Abstract

PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient prognosis based on immune-related genes (IRGs).

Authors

En-Hui Ren

Department of Orthopaedics, Xining First People's Hospital, Xining, Qinghai, 810000, People's Republic of China.
Ya-Jun Deng

Lanzhou University, Lanzhou, Gansu, 730000, People's Republic of China.
Wen-Hua Yuan

Lanzhou University, Lanzhou, Gansu, 730000, People's Republic of China.
Zuo-Long Wu

Lanzhou University, Lanzhou, Gansu, 730000, People's Republic of China.
Guang-Zhi Zhang

Lanzhou University, Lanzhou, Gansu, 730000, People's Republic of China.
Qi-Qi Xie

Lanzhou University, Lanzhou, Gansu, 730000, People's Republic of China. jieqq16@lzu.edu.cn.

Keywords

Adolescent Biomarkers, Tumor Bone Neoplasms Female Follow-Up Studies Gene Expression Profiling Gene Expression Regulation, Neoplastic Humans Lymphocytes, Tumor-Infiltrating Machine Learning Male Prognosis Sarcoma, Ewing Survival Rate Tumor Microenvironment

External Resources

View on PubMed Access via DOI PubMed (32968877)

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

Abstract

Authors

Keywords

External Resources

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