FACS-based Isolation of Neural and Glioma Stem Cell Populations from Fresh Human Tissues Utilizing EGF Ligand

Direct isolation of human neural and glioma stem cells from fresh tissues permits their biological study without prior culture and may capture novel aspects of their molecular phenotype in their native state. Recently, we demonstrated the ability to prospectively isolate stem cell populations from fresh human germinal matrix and glioblastoma samples, exploiting the ability of cells to bind the Epidermal Growth Factor (EGF) ligand in fluorescence-activated cell sorting (FACS). We demonstrated that FACS-isolated EGF-bound neural and glioblastoma populations encompass the sphere-forming colonies; in vitro; , and are capable of both self-renewal and multilineage differentiation. Here we describe in detail the purification methodology of EGF-bound (; i.e; ., EGFR+) human neural and glioma cells with stem cell properties from fresh postmortem and surgical tissues. The ability to prospectively isolate stem cell populations using native ligand-binding ability opens new doors for understanding both normal and tumor cell biology in uncultured conditions, and is applicable for various downstream molecular sequencing studies at both population and single-cell resolution

EGFR promoter exhibits dynamic histone modifications and binding of ASH2L and P300 in human germinal matrix and gliomas

Several signaling pathways important for the proliferation and growth of brain cells are pathologically dysregulated in gliomas, including the epidermal growth factor receptor (EGFR). Expression of EGFR is high in neural progenitors during development and in gliomas but decreases significantly in most adult brain regions. Here we show that EGFR expression is maintained in the astrocyte ribbon of the adult human subventricular zone. The transcriptional regulation of EGFR expression is poorly understood. To investigate the role of epigenetics on EGFR regulation in the contexts of neural development and gliomagenesis, we measured levels of DNA methylation and histone H3 modifications at the EGFR promoter in human brain tissues, glioma specimens, and EGFR-expressing neural cells, acutely isolated from their native niche. While DNA was constitutively hypomethylated in non-neoplastic and glioma samples, regardless of their EGFR-expression status, the activating histone modifications H3K27ac and H3K4me3 were enriched only when EGFR is highly expressed (developing germinal matrix and gliomas). Conversely, repressive H3K27me3 marks predominated in adult white matter where EGFR is repressed. Furthermore, the histone methyltransferase core enzyme ASH2L was bound at EGFR in the germinal matrix and in gliomas where levels of H3K4me3 are high, and the histone acetyltransferase P300 was bound in samples with H3K27ac enrichment. Our studies use human cells and tissues undisturbed by cell-culture artifact, and point to an important, locus-specific role for chromatin remodeling in EGFR expression in human neural development that may be dysregulated during gliomagenesis, unraveling potential novel targets for future drug therapy

Practical Bioinformatic DNA-Sequencing Pipeline for Detecting Oncogene Amplification and EGFRvIII Mutational Status in Clinical Glioblastoma Samples

Glioblastoma is a malignant brain tumor with dismal prognosis. Oncogenic mutations in glioblastoma frequently affect receptor tyrosine kinase pathway components that are challenging to quantify because of heterogeneous expression. EGFRvIII, a common oncogenic receptor tyrosine kinase mutant protein in glioblastoma, potentiates tumor malignancy and is an emerging tumor-specific immunotarget, underlining the need for its more accessible and quantitative detection. We used normalized next-generation sequencing data from 117 brain and 371 reference clinical tumor samples to detect focal gene amplifications across the commercial Ion AmpliSeq Cancer Hotspot Panel version 2 and infer EGFRvIII status based on relative coverage dropout of the gene\u27s truncated region within EGFR. In glioblastomas (n = 45), amplification of EGFR [18 (40%)], PDGFRA [3 (7%)], KIT [2 (4%)], MET [1 (2%)], and AKT1 [1 (2%)] was detected. With respect to EGFR and PDGFRA amplification, there was near-complete agreement between next-generation sequencing and in situ hybridization. Consistent with previous reports, this method detected EGFRvIII exclusively in EGFR-amplified glioblastomas [8 (44%)], which was confirmed using long-range PCR. Our study offers a practical method for detecting oncogene amplifications and large intragenic mutations in a clinically implemented hotspot panel that can be quantified using z scores. The validated detection of EGFRvIII using DNA sequencing eliminates problems with transcript degradation, and the provided script facilitates efficient incorporation into a laboratory\u27s bioinformatic pipeline

P16 immunohistochemistry is a sensitive and specific surrogate marker for CDKN2A homozygous deletion in gliomas

Abstract Molecular characterization of gliomas has uncovered genomic signatures with significant impact on tumor diagnosis and prognostication. CDKN2A is a tumor suppressor gene involved in cell cycle control. Homozygous deletion of the CDKN2A/B locus has been implicated in both gliomagenesis and tumor progression through dysregulated cell proliferation. In histologically lower grade gliomas, CDKN2A homozygous deletion is associated with more aggressive clinical course and is a molecular marker of grade 4 status in the 2021 WHO diagnostic system. Despite its prognostic utility, molecular analysis for CDKN2A deletion remains time consuming, expensive, and is not widely available. This study assessed whether semi-quantitative immunohistochemistry for expression of p16, the protein product of CDKN2A, can serve as a sensitive and a specific marker for CDKN2A homozygous deletion in gliomas. P16 expression was quantified by immunohistochemistry in 100 gliomas, representing both IDH-wildtype and IDH-mutant tumors of all grades, using two independent pathologists’ scores and QuPath digital pathology analysis. Molecular CDKN2A status was determined using next-generation DNA sequencing, with homozygous CDKN2A deletion detected in 48% of the tumor cohort. Classifying CDKN2A status based on p16 tumor cell expression (0–100%) demonstrated robust performance over a wide range of thresholds, with receiver operating characteristic curve area of 0.993 and 0.997 (blinded and unblinded pathologist p16 scores, respectively) and 0.969 (QuPath p16 score). Importantly, in tumors with pathologist-scored p16 equal to or less than 5%, the specificity for predicting CDKN2A homozygous deletion was 100%; and in tumors with p16 greater than 20%, specificity for excluding CDKN2A homozygous deletion was also 100%. Conversely, tumors with p16 scores of 6–20% represented gray zone with imperfect correlation to CDKN2A status. The findings indicate that p16 immunohistochemistry is a reliable surrogate marker of CDKN2A homozygous deletion in gliomas, with recommended p16 cutoff scores of ≤ 5% for confirming and > 20% for excluding biallelic CDKN2A loss

<i>EGFR</i> promoter exhibits dynamic histone modifications and binding of ASH2L and P300 in human germinal matrix and gliomas

<div><p>Several signaling pathways important for the proliferation and growth of brain cells are pathologically dysregulated in gliomas, including the epidermal growth factor receptor (EGFR). Expression of EGFR is high in neural progenitors during development and in gliomas but decreases significantly in most adult brain regions. Here we show that EGFR expression is maintained in the astrocyte ribbon of the adult human subventricular zone. The transcriptional regulation of <i>EGFR</i> expression is poorly understood. To investigate the role of epigenetics on <i>EGFR</i> regulation in the contexts of neural development and gliomagenesis, we measured levels of DNA methylation and histone H3 modifications at the <i>EGFR</i> promoter in human brain tissues, glioma specimens, and EGFR-expressing neural cells, acutely isolated from their native niche. While DNA was constitutively hypomethylated in non-neoplastic and glioma samples, regardless of their EGFR-expression status, the activating histone modifications H3K27ac and H3K4me3 were enriched only when <i>EGFR</i> is highly expressed (developing germinal matrix and gliomas). Conversely, repressive H3K27me3 marks predominated in adult white matter where <i>EGFR</i> is repressed. Furthermore, the histone methyltransferase core enzyme ASH2L was bound at <i>EGFR</i> in the germinal matrix and in gliomas where levels of H3K4me3 are high, and the histone acetyltransferase P300 was bound in samples with H3K27ac enrichment. Our studies use human cells and tissues undisturbed by cell-culture artifact, and point to an important, locus-specific role for chromatin remodeling in <i>EGFR</i> expression in human neural development that may be dysregulated during gliomagenesis, unraveling potential novel targets for future drug therapy.</p></div

An improved ScoreCard to assess the differentiation potential of human pluripotent stem cells

Research on human pluripotent stem cells has been hampered by the lack of a standardized, quantitative, scalable assay of pluripotency. We have previously described an assay called ScoreCard that used gene expression signatures to quantify differentiation efficiency. Here we report an improved version of the assay based on qPCR that enables faster, more quantitative assessment of functional pluripotency. We provide an in-depth characterization of the revised signature panel through embryoid body and directed differentiation experiments as well as a detailed comparison to the teratoma assay. We also show that the improved ScoreCard enables applications such as screening of small molecules, genetic perturbations and assessment of culture conditions. Beyond stem cell applications, this approach can in principle be extended to other cell types and lineages

Multiparametric MRI texture analysis in prediction of glioma biomarker status: added value of MR diffusion.

BackgroundEarly identification of glioma molecular phenotypes can lead to understanding of patient prognosis and treatment guidance. We aimed to develop a multiparametric MRI texture analysis model using a combination of conventional and diffusion MRI to predict a wide range of biomarkers in patients with glioma.MethodsIn this retrospective study, patients were included if they (1) had diagnosis of gliomas with known IDH1, EGFR, MGMT, ATRX, TP53, and PTEN status from surgical pathology and (2) had preoperative MRI including FLAIR, T1c+ and diffusion for radiomic texture analysis. Statistical analysis included logistic regression and receiver-operating characteristic (ROC) curve analysis to determine the optimal model for predicting glioma biomarkers. A comparative analysis between ROCs (conventional only vs conventional + diffusion) was performed.ResultsFrom a total of 111 patients included, 91 (82%) were categorized to training and 20 (18%) to test datasets. Constructed cross-validated model using a combination of texture features from conventional and diffusion MRI resulted in overall AUC/accuracy of 1/79% for IDH1, 0.99/80% for ATRX, 0.79/67% for MGMT, and 0.77/66% for EGFR. The addition of diffusion data to conventional MRI features significantly (P &lt; .05) increased predictive performance for IDH1, MGMT, and ATRX. The overall accuracy of the final model in predicting biomarkers in the test group was 80% (IDH1), 70% (ATRX), 70% (MGMT), and 75% (EGFR).ConclusionAddition of MR diffusion to conventional MRI features provides added diagnostic value in preoperative determination of IDH1, MGMT, and ATRX in patients with glioma

Multiparametric MRI texture analysis in prediction of glioma biomarker status: added value of MR diffusion.

BackgroundEarly identification of glioma molecular phenotypes can lead to understanding of patient prognosis and treatment guidance. We aimed to develop a multiparametric MRI texture analysis model using a combination of conventional and diffusion MRI to predict a wide range of biomarkers in patients with glioma.MethodsIn this retrospective study, patients were included if they (1) had diagnosis of gliomas with known IDH1, EGFR, MGMT, ATRX, TP53, and PTEN status from surgical pathology and (2) had preoperative MRI including FLAIR, T1c+ and diffusion for radiomic texture analysis. Statistical analysis included logistic regression and receiver-operating characteristic (ROC) curve analysis to determine the optimal model for predicting glioma biomarkers. A comparative analysis between ROCs (conventional only vs conventional + diffusion) was performed.ResultsFrom a total of 111 patients included, 91 (82%) were categorized to training and 20 (18%) to test datasets. Constructed cross-validated model using a combination of texture features from conventional and diffusion MRI resulted in overall AUC/accuracy of 1/79% for IDH1, 0.99/80% for ATRX, 0.79/67% for MGMT, and 0.77/66% for EGFR. The addition of diffusion data to conventional MRI features significantly (P &lt; .05) increased predictive performance for IDH1, MGMT, and ATRX. The overall accuracy of the final model in predicting biomarkers in the test group was 80% (IDH1), 70% (ATRX), 70% (MGMT), and 75% (EGFR).ConclusionAddition of MR diffusion to conventional MRI features provides added diagnostic value in preoperative determination of IDH1, MGMT, and ATRX in patients with glioma