ArticleTechnology in cancer research & treatment
Identification of Prognostic Biomarkers for Glioblastoma Based on Transcriptome and Proteome Association Analysis.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Review
- Analysis of transcription profiles for the identification of master regulators as the key players in glioblastoma.Computational and structural biotechnology journal · 2024Article
- Bioinformatics Examination of Glioblastoma Identifies a Potential Panel of Therapeutic Biomarkers.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Cost Matrix of Molecular Pathology in Glioma-Towards AI-Driven Rational Molecular Testing and Precision Care for the Future.Biomedicines · 2022Review
- Laminin-5, Fibronectin, and Type IV Collagen as Potential Biomarkers of Brain Glioma Malignancy.Biomedicines · 2022Article
- The complex interactions between the cellular and non-cellular components of the brain tumor microenvironmental landscape and their therapeutic implications.Frontiers in oncology · 2022Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveGlioblastoma multiforme (GBM) is the most malignant primary brain tumor in adults. This study aimed to identify significant prognostic biomarkers related to GBM.
methodsWe collected 3 GBM and 3 healthy human brain samples for transcriptome and proteomic sequencing analysis. Differentially expressed genes (DEGs) between GBM and control samples were identified using the edge R package in R. Functional enrichment analyses, prediction of long noncoding RNA target genes, and protein-protein interaction network analyses were performed. Subsequently, transcriptomic and proteomic association analyses, validation using The Cancer Genome Atlas (TCGA) database, and survival and prognostic analyses were conducted. Then the hub genes directly related to GBM were screened. Finally, the expression of key genes was verified by quantitative polymerase chain reaction (qPCR).
resultsTotally, 1140 transcripts and 503 proteins were significantly up- or down-regulated. A total of 25 genes were upregulated and 62 were downregulated at both the transcriptome and proteome levels. Results from TCGA database showed that 84 of these 87 genes matched with transcriptome sequencing results. A Cox regression analysis suggested that Fibronectin 1(
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.