Interpretable machine learning-driven multi-omics risk stratification and drug repurposing nominates Treg/Th17 with gluconeogenesis/lactylation integration as a prognostic and druggable biomarker for glioblastoma patients - Top-Institutions - MDSpire

Interpretable machine learning-driven multi-omics risk stratification and drug repurposing nominates Treg/Th17 with gluconeogenesis/lactylation integration as a prognostic and druggable biomarker for glioblastoma patients

  • By

  • Siqi Xie

  • Weiming Chen

  • Bing Zhang

  • Shangeng Weng

  • July 14, 2026

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Top Institutions in Oncology

Brief introduction explaining scope and methodology.

  • #1

    The Cancer Genome Atlas
    The Cancer Genome Atlas

    Washington, DC

    Key Differentiators

    • Oncology

  • #2

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Oncology

  • #3

    University Medical Center Hamburg-Eppendorf
    University Medical Center Hamburg-Eppendorf

    Hamburg, Germany

    Key Differentiators

    • Oncology

Original Source(s)

Interpretable machine learning-driven multi-omics risk stratification and drug repurposing nominates Treg/Th17 with gluconeogenesis/lactylation integration as a prognostic and druggable biomarker for glioblastoma patients

  • by Siqi Xie, Weiming Chen, Bing Zhang, Shangeng Weng

  • July 14, 2026

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