ArticleInternational journal of molecular sciences2016
PPIC, EMP3 and CHI3L1 Are Novel Prognostic Markers for High Grade Glioma.
Article in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- mRNA markers for survival prediction in glioblastoma multiforme patients: a systematic review with bioinformatic analyses.BMC cancer · 2024Pooled it
- Metabolic reprogramming of glioma-associated macrophages identifies detoxification and energetic macrophages as drivers of immunosuppression and therapeutic vulnerability.Frontiers in immunology · 2026Article
- Disulfidptosis as a key regulator of glioblastoma progression and immune cell impairment.Frontiers in immunology · 2025Article
- PPIC-labeled CAFs: Key players in neoadjuvant chemotherapy resistance for gastric cancer.Translational oncology · 2024Article
- Combining single-cell and bulk RNA sequencing, NK cell marker genes reveal a prognostic and immune status in pancreatic ductal adenocarcinoma.Scientific reports · 2024Article
- Article
- Hypoxia-related THBDJournal of cellular and molecular medicine · 2024Article
- Review
- EMP3: A promising biomarker for tumor prognosis and targeted cancer therapy.Cancer biomarkers : section A of Disease markers · 2024Review
- Shikonin Induces Glioma Necroptosis, Stemness Decline, and Impedes (Immuno)Proteasome Activity.Stem cells international · 2024Article
- EMP3 sustains oncogenic EGFR/CDK2 signaling by restricting receptor degradation in glioblastoma.Acta neuropathologica communications · 2023Article
- Epithelial Membrane Protein-3 and Chitinase-3-like Protein-1 as New Prognostic Predictors of Glioma, a Two-Gene Study.Current oncology (Toronto, Ont.) · 2023Article
- Article
- An integrative bioinformatics investigation and experimental validation of critically involved genes in high-grade gliomas.Diagnostic pathology · 2022Article
- Identification and Characterization of Extrachromosomal Circular DNA in Plasma of Lung Adenocarcinoma Patients.International journal of general medicine · 2022Article
- A Novel Multi-Omics Analysis Model for Diagnosis and Survival Prediction of Lower-Grade Glioma Patients.Frontiers in oncology · 2022Article
- Peptidylprolyl isomerase C (Ppic) regulates invariant Natural Killer T cell (iNKT) differentiation in mice.European journal of immunology · 2021Article
- The Long-Term Prognostic Significance of Circulating Tumor Cells in Ovarian Cancer-A Study of the OVCAD Consortium.Cancers · 2021Article
- EMP3 mediates glioblastoma-associated macrophage infiltration to drive T cell exclusion.Journal of experimental & clinical cancer research : CR · 2021Article
- Identification of a mesenchymal-related signature associated with clinical prognosis in glioma.Aging · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current treatment methods for patients diagnosed with gliomas have shown limited success. This is partly due to the lack of prognostic genes available to accurately predict disease outcomes. The aim of this study was to investigate novel prognostic genes based on the molecular profile of tumor samples and their correlation with clinical parameters. In the current study, microarray data (GSE4412 and GSE7696) downloaded from Gene Expression Omnibus were used to identify differentially expressed prognostic genes (DEPGs) by significant analysis of microarray (SAM) between long-term survivors (>2 years) and short-term survivors (≤2 years). DEPGs generated from these two datasets were intersected to obtain a list of common DEPGs. The expression of a subset of common DEPGs was then independently validated by real-time reverse transcription quantitative PCR (qPCR). Survival value of the common DEPGs was validated using known survival data from the GSE4412 and TCGA dataset. After intersecting DEPGs generated from the above two datasets, three genes were identified which may potentially be used to determine glioma patient prognosis. Independent validation with glioma patients tissue (
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