Ed Curry

Whole–genome characterization of chemoresistant ovarian cancer

Patients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1.

Poised epigenetic states and acquired drug resistance in cancer.

Epigenetic events, which are somatically inherited through cell division, are potential drivers of acquired drug resistance in cancer. The high rate of epigenetic change in tumours generates diversity in gene expression patterns that can rapidly evolve through drug selection during treatment, leading to the development of acquired resistance. This will potentially confound stratified chemotherapy decisions that are solely based on mutation biomarkers. Poised epigenetic states in tumour cells may drive multistep epigenetic fixation of gene expression during the acquisition of drug resistance, which has implications for clinical strategies to prevent the emergence of drug resistance.

Chromatin H3K27me3/H3K4me3 histone marks define gene sets in high-grade serous ovarian cancer that distinguish malignant, tumour-sustaining and chemo-resistant ovarian tumour cells

In embryonic stem (ES) cells, bivalent chromatin domains containing H3K4me3 and H3K27me3 marks silence developmental genes, while keeping them poised for activation following differentiation. We have identified gene sets associated with H3K27me3 and H3K4me3 marks at transcription start sites in a high-grade ovarian serous tumour and examined their association with epigenetic silencing and malignant progression. This revealed novel silenced bivalent marked genes, not described previously for ES cells, which are significantly enriched for the PI3K (P<10−7) and TGF-β signalling pathways (P<10−5). We matched histone marked gene sets to gene expression sets of eight normal fallopian tubes and 499 high-grade serous malignant ovarian samples. This revealed a significant decrease in gene expression for the H3K27me3 and bivalent gene sets in malignant tissue. We then correlated H3K27me3 and bivalent gene sets to gene expression data of ovarian tumour ‘stem cell-like’ sustaining cells versus non-sustaining cells. This showed a significantly lower expression for the H3K27me3 and bivalent gene sets in the tumour-sustaining cells. Similarly, comparison of matched chemo-sensitive and chemo-resistant ovarian cell lines showed a significantly lower expression of H3K27me3/bivalent marked genes in the chemo-resistant compared with the chemo-sensitive cell line. Our analysis supports the hypothesis that bivalent marks are associated with epigenetic silencing in ovarian cancer. However it also suggests that additional tumour specific bivalent marks, to those known in ES cells, are present in tumours and may potentially influence the subsequent development of drug resistance and tumour progression.

LARP1 post-transcriptionally regulates mTOR and contributes to cancer progression

RNA-binding proteins (RBPs) bind to and post-transcriptionally regulate the stability of mRNAs. La-related protein 1 (LARP1) is a conserved RBP that interacts with poly-A-binding protein and is known to regulate 5′-terminal oligopyrimidine tract (TOP) mRNA translation. Here, we show that LARP1 is complexed to 3000 mRNAs enriched for cancer pathways. A prominent member of the LARP1 interactome is mTOR whose mRNA transcript is stabilized by LARP1. At a functional level, we show that LARP1 promotes cell migration, invasion, anchorage-independent growth and in vivo tumorigenesis. Furthermore, we show that LARP1 expression is elevated in epithelial cancers such as cervical and non-small cell lung cancers, where its expression correlates with disease progression and adverse prognosis, respectively. We therefore conclude that, through the post-transcriptional regulation of genes such as mTOR within cancer pathways, LARP1 contributes to cancer progression.

RIP140 Represses the “Brown-in-White” Adipocyte Program Including a Futile Cycle of Triacyclglycerol Breakdown and Synthesis

Receptor-interacting protein 140 (RIP140) is a corepressor of nuclear receptors that is highly expressed in adipose tissues. We investigated the role of RIP140 in conditionally immortal preadipocyte cell lines prepared from white or brown fat depots. In white adipocytes, a large set of brown fat-associated genes was up-regulated in the absence of RIP140. In contrast, a relatively minor role can be ascribed to RIP140 in the control of basal gene expression in differentiated brown adipocytes because significant changes were observed only in Ptgds and Fabp3. The minor role of RIP140 in brown adipocytes correlates with the similar histology and uncoupling protein 1 and CIDEA staining in knockout compared with wild-type brown adipose tissue (BAT). In contrast, RIP140 knockout sc white adipose tissue (WAT) shows increased numbers of multilocular adipocytes with elevated staining for uncoupling protein 1 and CIDEA. Furthermore in a white adipocyte cell line, the markers of BRITE adipocytes, Tbx1, CD137, Tmem26, Cited1, and Epsti1 were repressed in the presence of RIP140 as was Prdm16. Microarray analysis of wild-type and RIP140-knockout white fat revealed elevated expression of genes associated with cold-induced expression or high expression in BAT. A set of genes associated with a futile cycle of triacylglycerol breakdown and resynthesis and functional assays revealed that glycerol kinase and glycerol-3-phosphate dehydrogenase activity as well as [3H]glycerol incorporation were elevated in the absence of RIP140. Thus, RIP140 blocks the BRITE program in WAT, preventing the expression of brown fat genes and inhibiting a triacylglycerol futile cycle, with important implications for energy homeostasis.

Differential expression of IL-8 and IL-8 receptors in benign, borderline and malignant ovarian epithelial tumours

INTRODUCTION Ovarian Cancer is the leading cause of death from gynecological malignancy. The poor prognosis is mainly due to presentation at a late stage and poor response to therapy. Much research is needed to identify diagnostic and prognostic biomarkers as well as therapeutic targets for ovarian cancer. Interleukin-8 is expressed by many tumour types and is known to have mitogenic, motogenic and angiogenic effects on tumour cells. AIMS The aim of this study was to investigate the expression of IL-8 and IL-8 receptors (IL-8RA and IL-8RB) in different histological subtypes of ovarian tumours, as potential prognostic biomarkers in ovarian tumours. MATERIALS AND METHODS Immunohitochemistry was used to study the expression of IL-8 and IL-8 receptors in 115 ovarian tumours including 21 benign tumours, 25 borderline tumours and 69 carcinomas of serous, clear cell, endometrioid and mucinous types. The correlation of expression profile, tumour type, stage, and progression free survival and overall survival was statistically analysed. RESULTS IL-8 and IL-8 receptors were expressed in all types of tumours with variable intensity and subcellular distribution. There was a statistically significant correlation between levels of expression and tumour stage and tumour type, being mostly significant in serous tumours. No correlation with patient progression free survival or overall survival was found. CONCLUSION This is the first study investigating the expression of IL-8 and IL-8 receptors using immunohistochemistry in different types of ovarian tumours, including benign and borderline tumours. IL-8 and IL-8RA are potential prognostic biomarkers and therapeutic targets in ovarian cancer, particularly in ovarian serous carcinoma.

Dual EZH2 and EHMT2 histone methyltransferase inhibition increases biological efficacy in breast cancer cells

BackgroundMany cancers show aberrant silencing of gene expression and overexpression of histone methyltransferases. The histone methyltransferases (HKMT) EZH2 and EHMT2 maintain the repressive chromatin histone methylation marks H3K27me and H3K9me, respectively, which are associated with transcriptional silencing. Although selective HKMT inhibitors reduce levels of individual repressive marks, removal of H3K27me3 by specific EZH2 inhibitors, for instance, may not be sufficient for inducing the expression of genes with multiple repressive marks.ResultsWe report that gene expression and inhibition of triple negative breast cancer cell growth (MDA-MB-231) are markedly increased when targeting both EZH2 and EHMT2, either by siRNA knockdown or pharmacological inhibition, rather than either enzyme independently. Indeed, expression of certain genes is only induced upon dual inhibition. We sought to identify compounds which showed evidence of dual EZH2 and EHMT2 inhibition. Using a cell-based assay, based on the substrate competitive EHMT2 inhibitor BIX01294, we have identified proof-of-concept compounds that induce re-expression of a subset of genes consistent with dual HKMT inhibition. Chromatin immunoprecipitation verified a decrease in silencing marks and an increase in permissive marks at the promoter and transcription start site of re-expressed genes, while Western analysis showed reduction in global levels of H3K27me3 and H3K9me3. The compounds inhibit growth in a panel of breast cancer and lymphoma cell lines with low to sub-micromolar IC50s. Biochemically, the compounds are substrate competitive inhibitors against both EZH2 and EHMT1/2.ConclusionsWe have demonstrated that dual inhibition of EZH2 and EHMT2 is more effective at eliciting biological responses of gene transcription and cancer cell growth inhibition compared to inhibition of single HKMTs, and we report the first dual EZH2-EHMT1/2 substrate competitive inhibitors that are functional in cells.

Molecular subtypes of serous borderline ovarian tumor show distinct expression patterns of benign tumor and malignant tumor-associated signatures

Borderline ovarian tumors show heterogeneity in clinical behavior. Most have excellent prognosis, although a small percentage show recurrence or progressive disease, usually to low-grade serous carcinoma. The aim of this study was to understand the molecular relationship between these entities and identify potential markers of tumor progression and therapeutic targets. We studied gene expression using Affymetrix HGU133plus2 GeneChip microarrays in 3 low-grade serous carcinomas, 13 serous borderline tumors and 8 serous cystadenomas. An independent data set of 18 serous borderline tumors and 3 low-grade serous carcinomas was used for validation. Unsupervised clustering revealed clear separation of benign and malignant tumors, whereas borderline tumors showed two distinct groups, one clustering with benign and the other with malignant tumors. The segregation into benign- and malignant-like borderline molecular subtypes was reproducible on applying the same analysis to an independent publicly available data set. We identified 50 genes that separate borderline tumors into their subgroups. Functional enrichment analysis of genes that separate borderline tumors to the two subgroups highlights a cell adhesion signature for the malignant-like subset, with Claudins particularly prominent. This is the first report of molecular subtypes of borderline tumors based on gene expression profiling. Our results provide the basis for identification of biomarkers for the malignant potential of borderline ovarian tumor and potential therapeutic targets for low-grade serous carcinoma.

A distance-based test of association between paired heterogeneous genomic data

MOTIVATION Due to rapid technological advances, a wide range of different measurements can be obtained from a given biological sample including single nucleotide polymorphisms, copy number variation, gene expression levels, DNA methylation and proteomic profiles. Each of these distinct measurements provides the means to characterize a certain aspect of biological diversity, and a fundamental problem of broad interest concerns the discovery of shared patterns of variation across different data types. Such data types are heterogeneous in the sense that they represent measurements taken at different scales or represented by different data structures. RESULTS We propose a distance-based statistical test, the generalized RV (GRV) test, to assess whether there is a common and non-random pattern of variability between paired biological measurements obtained from the same random sample. The measurements enter the test through the use of two distance measures, which can be chosen to capture a particular aspect of the data. An approximate null distribution is proposed to compute P-values in closed-form and without the need to perform costly Monte Carlo permutation procedures. Compared with the classical Mantel test for association between distance matrices, the GRV test has been found to be more powerful in a number of simulation settings. We also demonstrate how the GRV test can be used to detect biological pathways in which genetic variability is associated to variation in gene expression levels in an ovarian cancer sample, and present results obtained from two independent cohorts. AVAILABILITY R code to compute the GRV test is freely available from http://www2.imperial.ac.uk/∼gmontana

Network-guided regression for detecting associations between DNA methylation and gene expression.

MOTIVATION High-throughput profiling in biological research has resulted in the availability of a wealth of data cataloguing the genetic, epigenetic and transcriptional states of cells. These data could yield discoveries that may lead to breakthroughs in the diagnosis and treatment of human disease, but require statistical methods designed to find the most relevant patterns from millions of potential interactions. Aberrant DNA methylation is often a feature of cancer, and has been proposed as a therapeutic target. However, the relationship between DNA methylation and gene expression remains poorly understood. RESULTS We propose Network-sparse Reduced-Rank Regression (NsRRR), a multivariate regression framework capable of using prior biological knowledge expressed as gene interaction networks to guide the search for associations between gene expression and DNA methylation signatures. We use simulations to show the advantage of our proposed model in terms of variable selection accuracy over alternative models that do not use prior network information. We discuss an application of NsRRR to The Cancer Genome Atlas datasets on primary ovarian tumours. AVAILABILITY AND IMPLEMENTATION R code implementing the NsRRR model is available at http://www2.imperial.ac.uk/∼gmontana CONTACT giovanni.montana@kcl.ac.uk SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.