Machine learning-based selection of immune cell markers in osteosarcoma: prognostic determination and validation of CLK1 in disease progression.

Journal: Frontiers in immunology

PMID: 39742274

Abstract

INTRODUCTION: Osteosarcoma (OS) is a malignancy of the bone that mainly afflicts younger individuals. Despite existing treatment approaches, patients with metastatic or recurrent disease generally face poor prognoses. A greater understanding of the tumor microenvironment (TME) is critical for enhancing outcomes in OS patients.

Authors

Nan Zhang

Department of Pulmonary and Critical Care Medicine II, Emergency General Hospital, Beijing, China.
Zhou Haizhen

Department of Orthopedics, Honghui Hospital, Xi'an Jiaotong University College of Medicine, Xi'an, Shaanxi, China.
Runqi Zhang

Pathology Teaching and Research Office, Xi'an Medicine College, Xi'an, Shaanxi, China.
Xiaoju Li

Department of Pathology, Honghui Hospital, Xi'an Jiaotong University College of Medicine, Xi'an, Shaanxi, China.

Keywords

Biomarkers, Tumor Bone Neoplasms Cell Line, Tumor Cell Proliferation Disease Progression DNA Copy Number Variations Female Gene Expression Regulation, Neoplastic Humans Lymphocytes, Tumor-Infiltrating Machine Learning Male Osteosarcoma Prognosis Protein Serine-Threonine Kinases Protein-Tyrosine Kinases Tumor Microenvironment

External Resources

View on PubMed Access via DOI PubMed (39742274)

Machine learning-based selection of immune cell markers in osteosarcoma: prognostic determination and validation of CLK1 in disease progression.

Abstract

Authors

Keywords

External Resources

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