biostudies-literatureCao XScience and Technology Program of DeYang City2024 Sichuan Provincial Science and Technology Achievement Transfer and Transformation Guidance Program2025 Sichuan Provincial Key Research and Development Program1744https://www.ebi.ac.uk/biostudies/studies/S-EPMC12480193biostudies-literatureUnknown16(1)<h4>Background</h4>The intrinsic heterogeneity and invasiveness of diffuse gliomas complicate accurate prognosis. Existing approaches are largely constrained by subtype specificity or limited analytical dimensions. To address this gap, a multi- dimension-based prognostic framework encompassing the full glioma spectrum was developed, accompanied by an analysis of the associated immune microenvironment.<h4>Methods</h4>A total of 3,323 glioma samples from the SEER (n = 2181), CGGA (n = 807), and TCGA (n = 335) datasets were integrated. Differentially expressed genes were screened using the limma package, and a Lasso-Cox-based prognostic signature (Glioma-GDPM) was established. Clinical variables such as age, grade, and IDH mutation status were harmonized through propensity score matching to cDiscover oncologyMultilayered insights into the full spectrum of diffuse gliomas: a novel prognostic evaluation model.PMC12480193No.2023SZZ093No.2024ZHCG0018No. 25QYCX0359Cao XLiu MZhang JHuang JZou DLi KfalseMultilayered insights into the full spectrum of diffuse gliomas: a novel prognostic evaluation model.<h4>Background</h4>The intrinsic heterogeneity and invasiveness of diffuse gliomas complicate accurate prognosis. Existing approaches are largely constrained by subtype specificity or limited analytical dimensions. To address this gap, a multi- dimension-based prognostic framework encompassing the full glioma spectrum was developed, accompanied by an analysis of the associated immune microenvironment.<h4>Methods</h4>A total of 3,323 glioma samples from the SEER (n = 2181), CGGA (n = 807), and TCGA (n = 335) datasets were integrated. Differentially expressed genes were screened using the limma package, and a Lasso-Cox-based prognostic signature (Glioma-GDPM) was established. Clinical variables such as age, grade, and IDH mutation status were harmonized through propensity score matching to c2025-01-01T00:00:00Z2025 Sep2026-05-03T03:13:33.757Z2026-05-03T03:10:18.892ZS-EPMC124801934102092010.1007/s12672-025-03551-7