Identification of Key Genes via Integrated Multi-Omics and Machine Learning Uncovers Tumor Biological Features and Prognostic Biomarkers in Uterine Leiomyosarcoma

InteGenes reflect ULMS pathogenesis; the GBM model and Mgenes are promising diagnostic tools. Mgenes modulate ULMS's TIME, offering immunotherapeutic targets. This study advances ULMS molecular/immune understanding for translational research.

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Publication Details

Journal
International Journal of Medical Sciences
Published
2026-02-04
DOI
https://doi.org/10.7150/ijms.126491
Primary Topic
Endometrial and Cervical Cancer Treatments
Type
article
Field-Weighted Citation Impact
0.00
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article

Identification of Key Genes via Integrated Multi-Omics and Machine Learning Uncovers Tumor Biological Features and Prognostic Biomarkers in Uterine Leiomyosarcoma

Susu Jiang, Rujun Chen, Yi Guo, Qiran Sun et al.
International Journal of Medical Sciences
Endometrial and Cervical Cancer Treatments
article

Identification of Key Genes via Integrated Multi-Omics and Machine Learning Uncovers Tumor Biological Features and Prognostic Biomarkers in Uterine Leiomyosarcoma

Susu Jiang, Rujun Chen, Yi Guo, Qiran Sun, LiWen Zhang, Ying Yang, Xiaoqin Wang, Wei Lu
article en

Abstract

InteGenes reflect ULMS pathogenesis; the GBM model and Mgenes are promising diagnostic tools. Mgenes modulate ULMS's TIME, offering immunotherapeutic targets. This study advances ULMS molecular/immune understanding for translational research.

International Journal of Medical SciencesVol. 23(3)
Fudan University (CN), Shanghai East Hospital (CN)
Good health and well-being
Openalex Percentile: Top 59%
Endometrial and Cervical Cancer Treatments
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