Dataset Information

DZIP3 is a key factor to stratify IDH1 wild-type lower-grade gliomas.

ABSTRACT:

Background

Malignant glioma is the most common form of primary malignant brain cancer. Heterogeneity is the hallmark of glioma. DAZ-interacting zinc finger 3 (DZIP3), acts as an RNA-binding RING-type ubiquitin ligase; however, its function in glioma is yet unclear.

Results

The DZIP3 expression was related to the World Health Organization (WHO) grade and isocitrate dehydrogenase 1(IDH1) status, as well as the clinical outcome. Malignant cases exhibit lower DZIP3 expression. DZIP3 was an independent predictive factor of good prognosis in all grade and lower grade gliomas (p < 0.0001). Gene enrichment analysis and immunohistochemistry indicated that DZIP3 affected the biological behavior of glioma through the angiogenesis pathway. Moreover, based on DZIP3 expression, IDH1 wild-type lower-grade gliomas could be divided into two groups with different survival time.

Conclusion

In conclusion, the loss of DZIP3 may be involved in the mechanism of angiogenesis in the invasive biological process of glioma. These findings laid an understanding of DZIP3-specific clinical features in glioma.

Methods

A total of 325 glioma patients from the Chinese Glioma Genome Atlas (CGGA) RNA-seq cohort comprised the training cohort, while 265 patients from the GSE 16011 array cohort formed the validation cohort. The mRNA expression of DZIP3 and clinical characteristics was assessed. DZIP3 protein expression and microvessel density (MVD) were evaluated by immunohistochemistry (IHC).

SUBMITTER: Liang T

PROVIDER: S-EPMC7803555 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Publications

DZIP3 is a key factor to stratify IDH1 wild-type lower-grade gliomas.

Liang Tingyu T Zhou Xingang X Li Peiliang P You Gan G Wang Fang F Wang Peng P Feng Enshan E

Aging 20201121 24

<h4>Background</h4>Malignant glioma is the most common form of primary malignant brain cancer. Heterogeneity is the hallmark of glioma. DAZ-interacting zinc finger 3 (DZIP3), acts as an RNA-binding RING-type ubiquitin ligase; however, its function in glioma is yet unclear.<h4>Results</h4>The <i>DZIP3</i> expression was related to the World Health Organization (WHO) grade and isocitrate dehydrogenase 1(<i>IDH1</i>) status, as well as the clinical outcome. Malignant cases exhibit lower <i>DZIP3</i ...[more]

PMID: 33229627

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Project description:Background and purposeIsocitrate dehydrogenase (IDH) wild-type lower-grade gliomas (histologic grades II and III) with epidermal growth factor receptor (EGFR) amplification or telomerase reverse transcriptase (TERT) promoter mutation are reported to behave similar to glioblastoma. We aimed to evaluate whether MR imaging features could identify a subset of IDH wild-type lower-grade gliomas that carry molecular features of glioblastoma.Materials and methodsIn this multi-institutional retrospective study, pathologically confirmed IDH wild-type lower-grade gliomas from 2 tertiary institutions and The Cancer Genome Atlas constituted the training set (institution 1 and The Cancer Genome Atlas, 64 patients) and the independent test set (institution 2, 57 patients). Preoperative MRIs were analyzed using the Visually AcceSAble Rembrandt Images and radiomics. The molecular glioblastoma status was determined on the basis of the presence of EGFR amplification and TERT promoter mutation. Molecular glioblastoma was present in 73.4% and 56.1% in the training and test sets, respectively. Models using clinical, Visually AcceSAble Rembrandt Images, and radiomic features were built to predict the molecular glioblastoma status in the training set; then they were validated in the test set.ResultsIn the test set, a model using both Visually AcceSAble Rembrandt Images and radiomic features showed superior predictive performance (area under the curve = 0.854) than that with only clinical features or Visually AcceSAble Rembrandt Images (areas under the curve = 0.514 and 0.648, respectively; P < . 001, both). When both Visually AcceSAble Rembrandt Images and radiomics were added to clinical features, the predictive performance significantly increased (areas under the curve = 0.514 versus 0.863, P < .001).ConclusionsMR imaging features integrated with machine learning classifiers may predict a subset of IDH wild-type lower-grade gliomas that carry molecular features of glioblastoma.

Project description:Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations.

Dataset Information

DZIP3 is a key factor to stratify IDH1 wild-type lower-grade gliomas.

Background

Results

Conclusion

Methods

Publications

DZIP3 is a key factor to stratify IDH1 wild-type lower-grade gliomas.

Similar Datasets

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