YUSHI YANG1,#, CHUJIAO HU2,#, SHAN LEI3, XIN BAO3, ZHIRUI ZENG3,*, WENPENG CAO4,*
Oncology Research, Vol.32, No.12, pp. 1921-1934, 2024, DOI:10.32604/or.2024.046191
- 13 November 2024
Abstract Background: The heterogeneity of prognosis and treatment benefits among patients with gliomas is due to tumor microenvironment characteristics. However, biomarkers that reflect microenvironmental characteristics and predict the prognosis of gliomas are limited. Therefore, we aimed to develop a model that can effectively predict prognosis, differentiate microenvironment signatures, and optimize drug selection for patients with glioma. Materials and Methods: The CIBERSORT algorithm, bulk sequencing analysis, and single-cell RNA (scRNA) analysis were employed to identify significant cross-talk genes between M2 macrophages and cancer cells in glioma tissues. A predictive model was constructed based on cross-talk gene expression, and… More >
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