Habib Hamidi

Prognostic and Therapeutic Relevance of Molecular Subtypes in High-Grade Serous Ovarian Cancer

Molecular classification of high-grade serous ovarian cancer (HGSOC) using transcriptional profiling has proven to be complex and difficult to validate across studies. We determined gene expression profiles of 174 well-annotated HGSOCs and demonstrate prognostic significance of the prespecified TCGA Network gene signatures. Furthermore, we confirm the presence of four HGSOC transcriptional subtypes using a de novo classification. Survival differed statistically significantly between de novo subtypes (log rank, P = .006) and was the best for the immunoreactive-like subtype, but statistically significantly worse for the proliferative- or mesenchymal-like subtypes (adjusted hazard ratio = 1.89, 95% confidence interval = 1.18 to 3.02, P = .008, and adjusted hazard ratio = 2.45, 95% confidence interval = 1.43 to 4.18, P = .001, respectively). More prognostic information was provided by the de novo than the TCGA classification (Likelihood Ratio tests, P = .003 and P = .04, respectively). All statistical tests were two-sided. These findings were replicated in an external data set of 185 HGSOCs and confirm the presence of four prognostically relevant molecular subtypes that have the potential to guide therapy decisions.

Clinical Characteristics of Ovarian Cancer Classified by BRCA1, BRCA2, and RAD51C Status

We evaluated homologous recombination deficient (HRD) phenotypes in epithelial ovarian cancer (EOC) considering BRCA1, BRCA2, and RAD51C in a large well-annotated patient set. We evaluated EOC patients for germline deleterious mutations (n = 899), somatic mutations (n = 279) and epigenetic alterations (n = 482) in these genes using NGS and genome-wide methylation arrays. Deleterious germline mutations were identified in 32 (3.6%) patients for BRCA1, in 28 (3.1%) for BRCA2 and in 26 (2.9%) for RAD51C. Ten somatically sequenced patients had deleterious alterations, six (2.1%) in BRCA1 and four (1.4%) in BRCA2. Fifty two patients (10.8%) had methylated BRCA1 or RAD51C. HRD patients with germline or somatic alterations in any gene were more likely to be high grade serous, have an earlier diagnosis age and have ovarian and/or breast cancer family history. The HRD phenotype was most common in high grade serous EOC. Identification of EOC patients with an HRD phenotype may help tailor specific therapies.

The HSP90 inhibitor NVP-AUY922 potently inhibits non-small cell lung cancer growth

Heat shock protein 90 (HSP90) is involved in protein folding and functions as a chaperone for numerous client proteins, many of which are important in non–small cell lung cancer (NSCLC) pathogenesis. We sought to define preclinical effects of the HSP90 inhibitor NVP-AUY922 and identify predictors of response. We assessed in vitro effects of NVP-AUY922 on proliferation and protein expression in NSCLC cell lines. We evaluated gene expression changes induced by NVP-AUY922 exposure. Xenograft models were evaluated for tumor control and biological effects. NVP-AUY922 potently inhibited in vitro growth in all 41 NSCLC cell lines evaluated with IC50 < 100 nmol/L. IC100 (complete inhibition of proliferation) < 40 nmol/L was seen in 36 of 41 lines. Consistent gene expression changes after NVP-AUY922 exposure involved a wide range of cellular functions, including consistently decreased dihydrofolate reductase after exposure. NVP-AUY922 slowed growth of A549 (KRAS-mutant) xenografts and achieved tumor stability and decreased EGF receptor (EGFR) protein expression in H1975 xenografts, a model harboring a sensitizing and a resistance mutation for EGFR-tyrosine kinase inhibitors in the EGFR gene. These data will help inform the evaluation of correlative data from a recently completed phase II NSCLC trial and a planned phase IB trial of NVP-AUY922 in combination with pemetrexed in NSCLCs. Mol Cancer Ther; 12(6); 890–900. ©2013 AACR.

Epigenome-wide ovarian cancer analysis identifies a methylation profile differentiating clear-cell histology with epigenetic silencing of the HERG K+ channel

Ovarian cancer remains the leading cause of death in women with gynecologic malignancies, despite surgical advances and the development of more effective chemotherapeutics. As increasing evidence indicates that clear-cell ovarian cancer may have unique pathogenesis, further understanding of molecular features may enable us to begin to understand the underlying biology and histology-specific information for improved outcomes. To study epigenetics in clear-cell ovarian cancer, fresh frozen tumor DNA (n = 485) was assayed on Illumina Infinium HumanMethylation450 BeadChips. We identified a clear-cell ovarian cancer tumor methylation profile (n = 163) which we validated in two independent replication sets (set 1, n = 163; set 2, n = 159), highlighting 22 CpG loci associated with nine genes (VWA1, FOXP1, FGFRL1, LINC00340, KCNH2, ANK1, ATXN2, NDRG21 and SLC16A11). Nearly all of the differentially methylated CpGs showed a propensity toward hypermethylation among clear-cell cases. Several loci methylation inversely correlated with tumor gene expression, most notably KCNH2 (HERG, a potassium channel) (P = 9.5 × 10(-7)), indicating epigenetic silencing. In addition, a predicted methylation class mainly represented by the clear-cell cases (20 clear cell out of 23 cases) had improved survival time. Although these analyses included only 30 clear-cell carcinomas, results suggest that loss of expression of KCNH2 (HERG) by methylation could be a good prognostic marker, given that overexpression of the potassium (K(+)) channel Eag family members promotes increased proliferation and results in poor prognosis. Validation in a bigger cohort of clear-cell tumors of the ovary is warranted.

Identification of novel targets of CSL-dependent Notch signaling in hematopoiesis.

Somatic activating mutations in the Notch1 receptor result in the overexpression of activated Notch1, which can be tumorigenic. The goal of this study is to understand the molecular mechanisms underlying the phenotypic changes caused by the overexpression of ligand independent Notch 1 by using a tetracycline inducible promoter in an in vitro embryonic stem (ES) cells/OP9 stromal cells coculture system, recapitulating normal hematopoiesis. First, an in silico analysis of the promoters of Notch regulated genes (previously determined by microarray analysis) revealed that the motifs recognized by regulatory proteins known to mediate hematopoiesis were overrepresented. Notch 1 does not bind DNA but instead binds the CSL transcription factor to regulate gene expression. The in silico analysis also showed that there were putative CSL binding sites observed in the promoters of 28 out of 148 genes. A custom ChIP-chip array was used to assess the occupancy of CSL in the promoter regions of the Notch1 regulated genes in vivo and showed that 61 genes were bound by activated Notch responsive CSL. Then, comprehensive mapping of the CSL binding sites genome-wide using ChIP-seq analysis revealed that over 10,000 genes were bound within 10 kb of the TSS (transcription start site). The majority of the targets discovered by ChIP-seq belong to pathways that have been shown by others to crosstalk with Notch signaling. Finally, 83 miRNAs were significantly differentially expressed by greater than 1.5-fold during the course of in vitro hematopoiesis. Thirty one miRNA were up-regulated and fifty two were down-regulated. Overexpression of Notch1 altered this pattern of expression of microRNA: six miRNAs were up-regulated and four were down regulated as a result of activated Notch1 overexpression during the course of hematopoiesis. Time course analysis of hematopoietic development revealed that cells with Notch 1 overexpression mimic miRNA expression of cells in a less mature stage, which is consistent with our previous biological characterization.

Estrogen receptor (ER)α-regulated lipocalin 2 expression in adipose tissue links obesity with breast cancer progression.

Background: Mechanisms underlying obesity-associated breast cancer incidence are incompletely understood. Results: Adipose tissue estrogen receptor (ER)α expression is inversely associated with adiposity and the expression and release of Lcn2, an adipokine promoting breast cancer cell proliferation and migration. Conclusion: ERα is critical for restraining adiposity and Lcn2 production. Significance: Modulation of adipose tissue ERα action is a potential approach to prevent obesity and reduce breast cancer risk. Obesity is associated with increased breast cancer (BrCA) incidence. Considering that inactivation of estrogen receptor (ER)α promotes obesity and metabolic dysfunction in women and female mice, understanding the mechanisms and tissue-specific sites of ERα action to combat metabolic-related disease, including BrCA, is of clinical importance. To study the role of ERα in adipose tissue we generated fat-specific ERα knock-out (FERKO) mice. Herein we show that ERα deletion increased adipocyte size, fat pad weight, and tissue expression and circulating levels of the secreted glycoprotein, lipocalin 2 (Lcn2), an adipokine previously associated with BrCA development. Chromatin immunoprecipitation and luciferase reporter studies showed that ERα binds the Lcn2 promoter to repress its expression. Because adipocytes constitute an important cell type of the breast microenvironment, we examined the impact of adipocyte ERα deletion on cancer cell behavior. Conditioned medium from ERα-null adipocytes and medium containing pure Lcn2 increased proliferation and migration of a subset of BrCA cells in culture. The proliferative and promigratory effects of ERα-deficient adipocyte-conditioned medium on BrCA cells was reversed by Lcn2 deletion. BrCA cell responsiveness to exogenous Lcn2 was heightened in cell types where endogenous Lcn2 expression was minimal, but components of the Lcn2 signaling pathway were enriched, i.e. SLC22A17 and 3-hydroxybutyrate dehydrogenase (BDH2). In breast tumor biopsies from women diagnosed with BrCA we found that BDH2 expression was positively associated with adiposity and circulating Lcn2 levels. Collectively these data suggest that reduction of ERα expression in adipose tissue promotes adiposity and is linked with the progression and severity of BrCA via increased adipocyte-specific Lcn2 production and enhanced tumor cell Lcn2 sensitivity.

KRAS mutational subtype and copy number predict in vitro response of human pancreatic cancer cell lines to MEK inhibition

Background:To study the molecular mechanism regulating sensitivity to MEK inhibition in pancreatic cancer cell lines.Methods:A growth inhibition assay determined sensitivity to MEK162 in a panel of 29 pancreatic cancer cell lines. For the same panel, KRAS mutational status and copy-number variation (CNV) was determine using PCR, array CGH and FISH. Two sensitive and two resistant cell lines were further interrogated for difference in baseline and MEK162-induced gene expression, as well as signal transduction using microarray and western blotting. Cell cycle and apoptosis analysis was measured by flow cytometry.Results:We report a strong correlation between both specific KRAS mutational subtype and CNV, and sensitivity to MEK inhibition. Cell lines with a KRAS (V12) mutation and KRAS gains or loss (n=7) are ∼10 times more resistant than those having neither a KRAS (V12) mutation nor KRAS CNV (n=14). Significant differences in baseline and MEK162-induced gene expression exist between the sensitive and resistant lines, especially in genes involved in RAS, EGF receptor and PI3K pathways. This was further supported by difference in signal transduction. MEK 162 blocked ERK1/2, as well as inhibited PI3K and S6 and increased p27KIP1 levels in the sensitive lines.Conclusions:Given the potency of MEK162, it may be a promising new therapy for patients with pancreatic cancer and KRAS mutational subtypes, and CNV may serve as important biomarkers for selecting patients that benefit from MEK-targeting based on these preclinical data.

Dacomitinib, an irreversible Pan-ErbB inhibitor significantly abrogates growth in head and neck cancer models that exhibit low response to cetuximab.

Aberrant epidermal growth factor (EGF) signaling is associated with tumor growth in squamous cell carcinoma of the head and neck in humans (HNSCC), and is a major focus of targeted therapy. Cetuximab, a monoclonal antibody against EGFR, has been successful at prolonging survival but has only a 10% tumor shrinkage response rate in a clinical setting. The goal of this study was to compare dacomitinib (PF-00299804), a next generation small molecule tyrosine kinase inhibitor that irreversibly blocks multiple HER family receptors (HER-1 (EGFR), HER-2 and HER-4 tyrosine kinases), to cetuximab, the current FDA approved anti-EGFR medication for HNSCC and erlotinib, an EGFR specific small molecule tyrosine kinase inhibitor. Dacomitinib, erlotinib and cetuximab were tested in a panel of 27 HNSCC cell lines. Treatment with 100 ug/ml of cetuximab or 1 uM of erlotinib inhibited growth by at least 50% in 7/27 cell lines, while treatment with 1 uM of dacomitinib had similar growth inhibition in 17/27 lines. Cell lines representing three levels of sensitivity to dacomitinib were further examined using Western blots, cell cycle and apoptosis analysis. Treatment with 100 nM of dacomitinib reduced EGFR activity and downstream AKT and ERK pathways more effectively than treatment with 100 ug/ml of cetuximab in all ten tested lines. Although both compounds induced apoptosis at similar levels, dacomitinib caused greater G0/G1 arrest. Sensitivity to EGFR blockade was associated with levels of EGFR and ERK and was not associated with common oncogenic mutations and copy number variations. Phosphorylated and total EGFR and ERK levels correlate with sensitivity to both cetuximab and dacomitinib. Three of the four lines in the exquisitely sensitive group had the highest levels of phosphorylated and total EGFR and ERK among the ten lines selected, while the three resistant lines collectively had the lowest levels. Neither pAKT nor tAKT was associated with sensitivity.

Molecular classification of high grade endometrioid and clear cell ovarian cancer using TCGA gene expression signatures

BACKGROUND It is unclear whether the transcriptional subtypes of high grade serous ovarian cancer (HGSOC) apply to high grade clear cell (HGCCOC) or high grade endometrioid ovarian cancer (HGEOC). We aim to delineate transcriptional profiles of HGCCOCs and HGEOCs. METHODS We used Agilent microarrays to determine gene expression profiles of 276 well annotated ovarian cancers (OCs) including 37 HGCCOCs and 66 HGEOCs. We excluded low grade OCs as these are known to be distinct molecular entities. We applied the prespecified TCGA and CLOVAR gene signatures using consensus non-negative matrix factorization (NMF). RESULTS We confirm the presence of four TCGA transcriptional subtypes and their significant prognostic relevance (p<0.001) across all three histological subtypes (HGSOC, HGCCOC and HGEOCs). However, we also demonstrate that 22/37 (59%) HGCCOCs and 30/67 (45%) HGEOCs form 2 additional separate clusters with distinct gene signatures. Importantly, of the HGCCOC and HGEOCs that clustered separately 62% and 65% were early stage (FIGO I/II), respectively. These finding were confirmed using the reduced CLOVAR gene set for classification where most early stage HGCCOCs and HGEOCs formed a distinct cluster of their own. When restricting the analysis to the four TCGA signatures (ssGSEA or NMF with CLOVAR genes) most early stage HGCCOCs and HGEOC were assigned to the differentiated subtype. CONCLUSIONS Using transcriptional profiling the current study suggests that HGCCOCs and HGEOCs of advanced stage group together with HGSOCs. However, HGCCOCs and HGEOCs of early disease stages may have distinct transcriptional signatures similar to those seen in their low grade counterparts.

Comprehensive Cross-Population Analysis of High-Grade Serous Ovarian Cancer Supports No More Than Three Subtypes

Four gene expression subtypes of high-grade serous ovarian cancer (HGSC) have been previously described. In these early studies, a fraction of samples that did not fit well into the four subtype classifications were excluded. Therefore, we sought to systematically determine the concordance of transcriptomic HGSC subtypes across populations without removing any samples. We created a bioinformatics pipeline to independently cluster the five largest mRNA expression datasets using k-means and nonnegative matrix factorization (NMF). We summarized differential expression patterns to compare clusters across studies. While previous studies reported four subtypes, our cross-population comparison does not support four. Because these results contrast with previous reports, we attempted to reproduce analyses performed in those studies. Our results suggest that early results favoring four subtypes may have been driven by the inclusion of serous borderline tumors. In summary, our analysis suggests that either two or three, but not four, gene expression subtypes are most consistent across datasets.