Holly Stevenson

MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis

Metabolic profiling of cancer cells has recently been established as a promising tool for the development of therapies and identification of cancer biomarkers. Here we characterized the metabolomic profile of human breast tumors and uncovered intrinsic metabolite signatures in these tumors using an untargeted discovery approach and validation of key metabolites. The oncometabolite 2-hydroxyglutarate (2HG) accumulated at high levels in a subset of tumors and human breast cancer cell lines. We discovered an association between increased 2HG levels and MYC pathway activation in breast cancer, and further corroborated this relationship using MYC overexpression and knockdown in human mammary epithelial and breast cancer cells. Further analyses revealed globally increased DNA methylation in 2HG-high tumors and identified a tumor subtype with high tissue 2HG and a distinct DNA methylation pattern that was associated with poor prognosis and occurred with higher frequency in African-American patients. Tumors of this subtype had a stem cell-like transcriptional signature and tended to overexpress glutaminase, suggestive of a functional relationship between glutamine and 2HG metabolism in breast cancer. Accordingly, 13C-labeled glutamine was incorporated into 2HG in cells with aberrant 2HG accumulation, whereas pharmacologic and siRNA-mediated glutaminase inhibition reduced 2HG levels. Our findings implicate 2HG as a candidate breast cancer oncometabolite associated with MYC activation and poor prognosis.

Recurrent epimutation of SDHC in gastrointestinal stromal tumors

Methylation of the SDH gene explains the loss of SDH gene expression in SDH wild-type gastrointestinal stromal tumors. All Roads Lead to Loss of Expression Gastrointestinal stromal tumors are the most common mesenchymal tumors in the gastrointestinal tract, and they can occur in isolation or as part of a constellation of cancers known as Carney triad. A subtype of this cancer, characterized by lack of expression in a gene called SDH, is not well understood and lacks a specific treatment, and this is the type that most commonly occurs in children. Now, Killian et al. have identified methylation of the SDH gene in patients with SDH-deficient gastrointestinal stromal tumors who lack mutations in the SDH gene. This finding provides a common link explaining the pathogenesis of these SDH-deficient tumors, including many of the ones associated with Carney triad. Succinate dehydrogenase (SDH) is a conserved effector of cellular metabolism and energy production, and loss of SDH function is a driver mechanism in several cancers. SDH-deficient gastrointestinal stromal tumors (dSDH GISTs) collectively manifest similar phenotypes, including hypermethylated epigenomic signatures, tendency to occur in pediatric patients, and lack of KIT/PDGFRA mutations. dSDH GISTs often harbor deleterious mutations in SDH subunit genes (SDHA, SDHB, SDHC, and SDHD, termed SDHx), but some are SDHx wild type (WT). To further elucidate mechanisms of SDH deactivation in SDHx-WT GIST, we performed targeted exome sequencing on 59 dSDH GISTs to identify 43 SDHx-mutant and 16 SDHx-WT cases. Genome-wide DNA methylation and expression profiling exposed SDHC promoter–specific CpG island hypermethylation and gene silencing in SDHx-WT dSDH GISTs [15 of 16 cases (94%)]. Six of 15 SDHC-epimutant GISTs occurred in the setting of the multitumor syndrome Carney triad. We observed neither SDHB promoter hypermethylation nor large deletions on chromosome 1q in any SDHx-WT cases. Deep genome sequencing of a 130-kbp (kilo–base pair) window around SDHC revealed no recognizable sequence anomalies in SDHC-epimutant tumors. More than 2000 benign and tumor reference tissues, including stem cells and malignancies with a hypermethylator epigenotype, exhibit solely a non-epimutant SDHC promoter. Mosaic constitutional SDHC promoter hypermethylation in blood and saliva from patients with SDHC-epimutant GIST implicates a postzygotic mechanism in the establishment and maintenance of SDHC epimutation. The discovery of SDHC epimutation provides a unifying explanation for the pathogenesis of dSDH GIST, whereby loss of SDH function stems from either SDHx mutation or SDHC epimutation.

DNA methylation profiling identifies global methylation differences and markers of adrenocortical tumors.

CONTEXT It is not known whether there are any DNA methylation alterations in adrenocortical tumors. OBJECTIVE The objective of the study was to determine the methylation profile of normal adrenal cortex and benign and malignant adrenocortical tumors. METHODS Genome-wide methylation status of CpG regions were determined in normal (n = 19), benign (n = 48), primary malignant (n = 8), and metastatic malignant (n = 12) adrenocortical tissue samples. An integrated analysis of genome-wide methylation and mRNA expression in benign vs. malignant adrenocortical tissue samples was also performed. RESULTS Methylation profiling revealed the following: 1) that methylation patterns were distinctly different and could distinguish normal, benign, primary malignant, and metastatic tissue samples; 2) that malignant samples have global hypomethylation; and 3) that the methylation of CpG regions are different in benign adrenocortical tumors by functional status. Normal compared with benign samples had the least amount of methylation differences, whereas normal compared with primary and metastatic adrenocortical carcinoma samples had the greatest variability in methylation (adjusted P ≤ 0.01). Of 215 down-regulated genes (≥2-fold, adjusted P ≤ 0.05) in malignant primary adrenocortical tumor samples, 52 of these genes were also hypermethylated. CONCLUSIONS Malignant adrenocortical tumors are globally hypomethylated as compared with normal and benign tumors. Methylation profile differences may accurately distinguish between primary benign and malignant adrenocortical tumors. Several differentially methylated sites are associated with genes known to be dysregulated in malignant adrenocortical tumors.

Histone Demethylase Jumonji D3 (JMJD3) as a Tumor Suppressor by Regulating p53 Protein Nuclear Stabilization

Histone methylation regulates normal stem cell fate decisions through a coordinated interplay between histone methyltransferases and demethylases at lineage specific genes. Malignant transformation is associated with aberrant accumulation of repressive histone modifications, such as polycomb mediated histone 3 lysine 27 (H3K27me3) resulting in a histone methylation mediated block to differentiation. The relevance, however, of histone demethylases in cancer remains less clear. We report that JMJD3, a H3K27me3 demethylase, is induced during differentiation of glioblastoma stem cells (GSCs), where it promotes a differentiation-like phenotype via chromatin dependent (INK4A/ARF locus activation) and chromatin independent (nuclear p53 protein stabilization) mechanisms. Our findings indicate that deregulation of JMJD3 may contribute to gliomagenesis via inhibition of the p53 pathway resulting in a block to terminal differentiation.

An Integrated Prognostic Classifier for Stage I Lung Adenocarcinoma Based on mRNA, microRNA, and DNA Methylation Biomarkers.

Introduction: Up to 30% stage I lung cancer patients suffer recurrence within 5 years of curative surgery. We sought to improve existing protein-coding gene and microRNA expression prognostic classifiers by incorporating epigenetic biomarkers. Methods: Genome-wide screening of DNA methylation and pyrosequencing analysis of HOXA9 promoter methylation were performed in two independently collected cohorts of stage I lung adenocarcinoma. The prognostic value of HOXA9 promoter methylation alone and in combination with mRNA and miRNA biomarkers was assessed by Cox regression and Kaplan–Meier survival analysis in both cohorts. Results: Promoters of genes marked by polycomb in embryonic stem cells were methylated de novo in tumors and identified patients with poor prognosis. The HOXA9 locus was methylated de novo in stage I tumors (p < 0.0005). High HOXA9 promoter methylation was associated with worse cancer-specific survival (hazard ratio [HR], 2.6; p = 0.02) and recurrence-free survival (HR, 3.0; p = 0.01), and identified high-risk patients in stratified analysis of stages IA and IB. Four protein-coding gene (XPO1, BRCA1, HIF1&agr;, and DLC1), miR-21 expression, and HOXA9 promoter methylation were each independently associated with outcome (HR, 2.8; p = 0.002; HR, 2.3; p = 0.01; and HR, 2.4; p = 0.005, respectively), and when combined, identified high-risk, therapy naive, stage I patients (HR, 10.2; p = 3 × 10−5). All associations were confirmed in two independently collected cohorts. Conclusion: A prognostic classifier comprising three types of genomic and epigenomic data may help guide the postoperative management of stage I lung cancer patients at high risk of recurrence.

Genome-Wide Methylation Patterns in Papillary Thyroid Cancer Are Distinct Based on Histological Subtype and Tumor Genotype

CONTEXT Aberrant DNA methylation is known to be a major factor in oncogenesis and cancer progression, but effects of methylation in papillary thyroid cancer (PTC) are not well defined. OBJECTIVE The objective of the study was to identify altered methylation patterns, which may be associated with PTC disease behavior. DESIGN This study was a genome-wide methylation analysis of PTC. SETTING The study was conducted at the National Institutes of Health Clinical Center. PATIENTS PTC tissue from 51 patients were analyzed and compared with normal thyroid tissue from seven patients. INTERVENTIONS CpG methylation status was assessed using advanced genome-wide methylation bead chips. OUTCOME MEASURES Altered methylation patterns in PTC were analyzed by stage, recurrence, histological subtype of tumor, and tumor genotype. RESULTS PTC is globally hypomethylated compared with normal thyroid with 2837 differentially methylated CpG sites. The follicular variant of PTC demonstrated less differential methylation with only 569 differentially methylated CpG sites. Tumors with mutations in BRAF, RET/PTC, and RAS demonstrated a 3.6-fold increase in the number of differentially methylated sites compared with wild-type tumors. The differentially methylated genes were associated with oncological pathways including cellular movement, growth, and proliferation. CONCLUSION PTC is epigenetically distinct from the follicular variant of PTC and by gene mutation status (BRAF, RET/PTC, and RAS).

BP1 transcriptionally activates bcl-2 and inhibits TNFα-induced cell death in MCF7 breast cancer cells

IntroductionWe have previously shown that the Beta Protein 1 (BP1) homeodomain protein is expressed in 81% of invasive ductal breast carcinomas, and that increased BP1 expression correlates with tumor progression. The purpose of our current investigation was to determine whether elevated levels of BP1 in breast cancer cells are associated with increased cell survival.MethodsEffects on cell viability and apoptosis of MCF7 cells stably overexpressing BP1 were determined using MTT and Annexin V assays, and through examination of caspase activation. TNFα was used to induce apoptosis. The potential regulation of apoptosis-associated genes by BP1 was studied using real-time PCR and western blot analyses. Electrophoretic mobility shift assays, site-directed mutagenesis, and transient assays were performed to specifically characterize the interaction of BP1 with the promoter of the bcl-2 gene.ResultsStable overexpression of BP1 led to inhibition of apoptosis in MCF7 breast cancer cells challenged with TNFα. Increased BP1 resulted in reduced processing and activation of caspase-7, caspase-8, and caspase-9, and inactivation of the caspase substrate Poly(ADP-Ribose) Polymerase (PARP). Increased levels of full-length PARP and a decrease in procaspase-8 were also associated with BP1 overexpression. The bcl-2 gene is a direct target of BP1 since: (i) BP1 protein bound to a consensus binding sequence upstream of the bcl-2 P1 promoter in vitro. (ii) MCF7 cells overexpressing BP1 showed increased levels of bcl-2 mRNA and protein. (iii) Transient assays indicated that increased bcl-2 promoter activity is due to direct binding and modulation by BP1 protein. BP1 expression also prevented TNFα-mediated downregulation of bcl-2 mRNA and protein.ConclusionThese findings suggest mechanisms by which increased BP1 may impart a survival advantage to breast cancer cells, which could lead to increased resistance to therapeutic agents in patients.

G-CIMP Status Prediction of Glioblastoma Samples Using mRNA Expression Data

Glioblastoma Multiforme (GBM) is a tumor with high mortality and no known cure. The dramatic molecular and clinical heterogeneity seen in this tumor has led to attempts to define genetically similar subgroups of GBM with the hope of developing tumor specific therapies targeted to the unique biology within each of these subgroups. Recently, a subset of relatively favorable prognosis GBMs has been identified. These glioma CpG island methylator phenotype, or G-CIMP tumors, have distinct genomic copy number aberrations, DNA methylation patterns, and (mRNA) expression profiles compared to other GBMs. While the standard method for identifying G-CIMP tumors is based on genome-wide DNA methylation data, such data is often not available compared to the more widely available gene expression data. In this study, we have developed and evaluated a method to predict the G-CIMP status of GBM samples based solely on gene expression data.

Micro-Environment Causes Reversible Changes in DNA Methylation and mRNA Expression Profiles in Patient-Derived Glioma Stem Cells

In vitro and in vivo models are widely used in cancer research. Characterizing the similarities and differences between a patients tumor and corresponding in vitro and in vivo models is important for understanding the potential clinical relevance of experimental data generated with these models. Towards this aim, we analyzed the genomic aberrations, DNA methylation and transcriptome profiles of five parental tumors and their matched in vitro isolated glioma stem cell (GSC) lines and xenografts generated from these same GSCs using high-resolution platforms. We observed that the methylation and transcriptome profiles of in vitro GSCs were significantly different from their corresponding xenografts, which were actually more similar to their original parental tumors. This points to the potentially critical role of the brain microenvironment in influencing methylation and transcriptional patterns of GSCs. Consistent with this possibility, ex vivo cultured GSCs isolated from xenografts showed a tendency to return to their initial in vitro states even after a short time in culture, supporting a rapid dynamic adaptation to the in vitro microenvironment. These results show that methylation and transcriptome profiles are highly dependent on the microenvironment and growth in orthotopic sites partially reverse the changes caused by in vitro culturing.

The NCI-60 Methylome and Its Integration into CellMiner

A unique resource for systems pharmacology and genomic studies is the NCI-60 cancer cell line panel, which provides data for the largest publicly available library of compounds with cytotoxic activity (∼21,000 compounds), including 108 FDA-approved and 70 clinical trial drugs as well as genomic data, including whole-exome sequencing, gene and miRNA transcripts, DNA copy number, and protein levels. Here, we provide the first readily usable genome-wide DNA methylation database for the NCI-60, including 485,577 probes from the Infinium HumanMethylation450k BeadChip array, which yielded DNA methylation signatures for 17,559 genes integrated into our open access CellMiner version 2.0 (https://discover.nci.nih.gov/cellminer). Among new insights, transcript versus DNA methylation correlations revealed the epithelial/mesenchymal gene functional category as being influenced most heavily by methylation. DNA methylation and copy number integration with transcript levels yielded an assessment of their relative influence for 15,798 genes, including tumor suppressor, mitochondrial, and mismatch repair genes. Four forms of molecular data were combined, providing rationale for microsatellite instability for 8 of the 9 cell lines in which it occurred. Individual cell line analyses showed global methylome patterns with overall methylation levels ranging from 17% to 84%. A six-gene model, including PARP1, EP300, KDM5C, SMARCB1, and UHRF1 matched this pattern. In addition, promoter methylation of two translationally relevant genes, Schlafen 11 (SLFN11) and methylguanine methyltransferase (MGMT), served as indicators of therapeutic resistance or susceptibility, respectively. Overall, our database provides a resource of pharmacologic data that can reinforce known therapeutic strategies and identify novel drugs and drug targets across multiple cancer types. Cancer Res; 77(3); 601-12. ©2016 AACR.