Dataset Information

Nuclear mitochondria-related genes-based molecular classification and prognostic signature reveal immune landscape, somatic mutation, and prognosis for glioma.

ABSTRACT:

Background

Glioma is the most frequent malignant primary brain tumor, and mitochondria may influence the progression of glioma. The aim of this study was to analyze the role of nuclear mitochondria related genes (MTRGs) in glioma, identify subtypes and construct a prognostic model based on nuclear MTRGs and machine learning algorithms.

Methods

Samples containing both gene expression profiles and clinical information were retrieved from the TCGA database, CGGA database, and GEO database. We selected 16 nuclear MTRGs and identified two clusters of glioma. Prognostic features, microenvironment, mutation landscape, and drug sensitivity were compared between the clusters. A prognostic model based on multiple machine learning algorithms was then constructed and validated by multiple datasets.

Results

We observed significant discrepancies between the two clusters. Cluster One had higher nuclear MTRG expression, a lower survival rate, and higher immune infiltration than Cluster Two. For the two clusters, we found distinct predictive drug sensitivities and responses to immune therapy, and the infiltration of immune cells was significantly different. Among the 22 combinations of machine learning algorithms we tested, LASSO was the most effective in constructing the prognostic model. The model's accuracy was further verified in three independent glioma datasets. We identified MGME1 as a vital gene associated with infiltrating immune cells in multiple types of tumors.

Conclusion

In short, our research identified two clusters of glioma and developed a dependable prognostic model based on machine learning methods. MGME1 was identified as a potential biomarker for multiple tumors. Our results will contribute to precise medicine and glioma management.

SUBMITTER: Liu C

PROVIDER: S-EPMC10559255 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Nuclear mitochondria-related genes-based molecular classification and prognostic signature reveal immune landscape, somatic mutation, and prognosis for glioma.

Liu Chang C Zhang Ning N Xu Zhihao Z Wang Xiaofeng X Yang Yang Y Bu Junming J Cao Huake H Xiao Jin J Xie Yinyin Y

Heliyon 20230905 9

<h4>Background</h4>Glioma is the most frequent malignant primary brain tumor, and mitochondria may influence the progression of glioma. The aim of this study was to analyze the role of nuclear mitochondria related genes (MTRGs) in glioma, identify subtypes and construct a prognostic model based on nuclear MTRGs and machine learning algorithms.<h4>Methods</h4>Samples containing both gene expression profiles and clinical information were retrieved from the TCGA database, CGGA database, and GEO dat ...[more]

PMID: 37809472

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Dataset Information

Nuclear mitochondria-related genes-based molecular classification and prognostic signature reveal immune landscape, somatic mutation, and prognosis for glioma.

Background

Methods

Results

Conclusion

Publications

Nuclear mitochondria-related genes-based molecular classification and prognostic signature reveal immune landscape, somatic mutation, and prognosis for glioma.

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