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Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network
by
Qin, Guimin
, Du, Longting
, Yin, Yu
, Ma, Yuying
, Wang, Liming
in
Bioinformatics
/ Biomarkers
/ Biomarkers, Tumor - analysis
/ Biomarkers, Tumor - genetics
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain cancer
/ Brain tumors
/ Cancer
/ Cell type
/ Development and progression
/ Gene Expression
/ Gene Regulatory Networks
/ Genetic aspects
/ Genetic markers
/ Glioma
/ Glioma - metabolism
/ Glioma cells
/ Gliomas
/ Human Genetics
/ Humans
/ Ligands
/ Medical prognosis
/ Medical research
/ Methods
/ Microarrays
/ Molecular modelling
/ Mutation
/ NADH
/ Oncology, Experimental
/ Patients
/ Prognosis
/ Proteins
/ Risk factors
/ RNA sequencing
/ Single-Cell Analysis - methods
/ Single-cell gene expression profile
/ Survival analysis
/ Technical Advance
/ Transcription
/ Tumor gene biomarkers
/ Tumors
/ Ubiquinone oxidoreductase
/ Whole Exome Sequencing
2021
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Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network
by
Qin, Guimin
, Du, Longting
, Yin, Yu
, Ma, Yuying
, Wang, Liming
in
Bioinformatics
/ Biomarkers
/ Biomarkers, Tumor - analysis
/ Biomarkers, Tumor - genetics
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain cancer
/ Brain tumors
/ Cancer
/ Cell type
/ Development and progression
/ Gene Expression
/ Gene Regulatory Networks
/ Genetic aspects
/ Genetic markers
/ Glioma
/ Glioma - metabolism
/ Glioma cells
/ Gliomas
/ Human Genetics
/ Humans
/ Ligands
/ Medical prognosis
/ Medical research
/ Methods
/ Microarrays
/ Molecular modelling
/ Mutation
/ NADH
/ Oncology, Experimental
/ Patients
/ Prognosis
/ Proteins
/ Risk factors
/ RNA sequencing
/ Single-Cell Analysis - methods
/ Single-cell gene expression profile
/ Survival analysis
/ Technical Advance
/ Transcription
/ Tumor gene biomarkers
/ Tumors
/ Ubiquinone oxidoreductase
/ Whole Exome Sequencing
2021
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Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network
by
Qin, Guimin
, Du, Longting
, Yin, Yu
, Ma, Yuying
, Wang, Liming
in
Bioinformatics
/ Biomarkers
/ Biomarkers, Tumor - analysis
/ Biomarkers, Tumor - genetics
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain cancer
/ Brain tumors
/ Cancer
/ Cell type
/ Development and progression
/ Gene Expression
/ Gene Regulatory Networks
/ Genetic aspects
/ Genetic markers
/ Glioma
/ Glioma - metabolism
/ Glioma cells
/ Gliomas
/ Human Genetics
/ Humans
/ Ligands
/ Medical prognosis
/ Medical research
/ Methods
/ Microarrays
/ Molecular modelling
/ Mutation
/ NADH
/ Oncology, Experimental
/ Patients
/ Prognosis
/ Proteins
/ Risk factors
/ RNA sequencing
/ Single-Cell Analysis - methods
/ Single-cell gene expression profile
/ Survival analysis
/ Technical Advance
/ Transcription
/ Tumor gene biomarkers
/ Tumors
/ Ubiquinone oxidoreductase
/ Whole Exome Sequencing
2021
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Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network
Journal Article
Gene biomarker prediction in glioma by integrating scRNA-seq data and gene regulatory network
2021
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Overview
Background
Although great efforts have been made to study the occurrence and development of glioma, the molecular mechanisms of glioma are still unclear. Single-cell sequencing technology provides a new perspective for researchers to explore the pathogens of tumors to further help make treatment and prognosis decisions for patients with tumors.
Methods
In this study, we proposed an algorithm framework to explore the molecular mechanisms of glioma by integrating single-cell gene expression profiles and gene regulatory relations. First, since there were great differences among malignant cells from different glioma samples, we analyzed the expression status of malignant cells for each sample, and then tumor consensus genes were identified by constructing and analyzing cell-specific networks. Second, to comprehensively analyze the characteristics of glioma, we integrated transcriptional regulatory relationships and consensus genes to construct a tumor-specific regulatory network. Third, we performed a hybrid clustering analysis to identify glioma cell types. Finally, candidate tumor gene biomarkers were identified based on cell types and known glioma-related genes.
Results
We got six identified cell types using the method we proposed and for these cell types, we performed functional and biological pathway enrichment analyses. The candidate tumor gene biomarkers were analyzed through survival analysis and verified using literature from PubMed.
Conclusions
The results showed that these candidate tumor gene biomarkers were closely related to glioma and could provide clues for the diagnosis and prognosis of patients with glioma. In addition, we found that four of the candidate tumor gene biomarkers (
NDUFS5
,
NDUFA1
,
NDUFA13
, and
NDUFB8
) belong to the NADH ubiquinone oxidoreductase subunit gene family, so we inferred that this gene family may be strongly related to glioma.
Publisher
BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
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