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 - Poll - 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

Share

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

Related Content

Navigating the gut–metabolite–immune axis: enhancing efficacy and mitigating toxicity of immune checkpoint inhibitors

Metabolism of myeloid cells in brain tumors

Multimodal imaging diagnosis of multiple myeloma with renal involvement: a case report