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Updated: Feb 4, 2026
Mining Spatial Transcriptomics Datasets using DeepSpaceDB
Published on: September 5, 2025
Multi-Omics Evidence Based on Spatial Transcriptomics Data Reveals the Therapeutic Value of Copper Death Genes in
Zhaoliang Xue1, Zhengfei Song1, Lianjie Mo1
1Department of Neurosurgery, SIR Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China, zju.edu.cn.
Background:
Cuprotosis is an emerging form of copper-dependent programmed cell death, while low-grade gliomas (LGGs) represent a common subtype of primary brain tumors.
Methods:
Datasets from The Cancer Genome Atlas and TargetScan were utilized to identify cuprotosis-related microRNAs (CRMs). Univariate Cox and Lasso regression analyses identified CRMs linked to prognostic outcomes. Prognostic profiles for patients with LGG were constructed using multivariate Cox regression and validated for risk stratification in the CGGA external validation cohort. The study examined clinical features, mutational status, immune cell infiltration, signaling pathways, and immune checkpoint expression across different risk groups. Functional experiments assessed the biological significance of key model genes.
Results:
Seven CRMs significantly associated with LGG prognosis were identified. The correlation between the CRM signature and poor prognosis in high-risk LGG cases was validated through Kaplan-Meier survival analysis, yielding a one-year area under the curve (AUC) of 0.849, indicating strong predictive accuracy. Risk scores were linked to 1p/19q co-deletion, IDH mutation, and tumor grade, with the model outperforming traditional clinicopathological criteria. Molecular enrichment analyses, including Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), revealed significant associations between high-risk subgroups and pathways related to tumorigenesis and immune dysregulation. Increased tumor mutational burden and elevated IC expression were noted in high-risk cohorts. Furthermore, miR-93-5p was validated as a critical gene, with its disruption leading to significant reductions in GBM cell proliferation, migration, and invasion.
Conclusion:
The novel CRM signature enhances the prognostic landscape for patients with LGG, offering a new framework for evaluating immunotherapeutic efficacy.
Insights
A new signature of cuprotosis-related microRNAs (CRMs) accurately predicts outcomes in low-grade gliomas (LGGs). This discovery aids in understanding tumor progression and guides potential immunotherapeutic strategies for LGG patients.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Cuprotosis, a novel form of cell death, is linked to copper metabolism.
- Low-grade gliomas (LGGs) are common primary brain tumors with variable prognoses.
Purpose of the Study:
- To identify cuprotosis-related microRNAs (CRMs) associated with LGG prognosis.
- To develop a prognostic model for LGG patients based on CRMs.
- To explore the molecular and immune landscape of different risk groups within LGGs.
Main Methods:
- Utilized The Cancer Genome Atlas and TargetScan datasets to identify CRMs.
- Employed univariate Cox, Lasso, and multivariate Cox regression for prognostic model construction.
- Validated the model in an external cohort and analyzed clinical features, mutational status, and immune profiles.
- Performed functional experiments on key genes like miR-93-5p.
Main Results:
- Identified seven CRMs significantly associated with LGG prognosis.
- Developed a CRM signature that accurately stratified LGG patients into high- and low-risk groups (AUC=0.849).
- Linked CRM signature to 1p/19q co-deletion, IDH mutation, tumor grade, and immune dysregulation pathways. MiR-93-5p was validated as a critical gene impacting GBM cell behavior.
Conclusions:
- The novel CRM signature improves prognostic accuracy for LGG.
- This signature provides a new framework for assessing immunotherapy efficacy in LGG.
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