Therapeutic efficacy of RAS inhibitor trametinib using a juvenile myelomonocytic leukemia patient-derived xenograft model.

Juvenile myelomonocytic leukemia (JMML) is an aggressive pediatric leukemia with few effective treatments and poor outcomes even after stem cell transplantation, the only current curative treatment. We developed a JMML patient-derived xenograft (PDX) mouse model and demonstrated the in vivo therapeutic efficacy and confirmed the target of trametinib, a RAS-RAF-MEK-ERK pathway inhibitor, in this model. A PDX model was created through transplantation of patient JMML cells into mice, up to the second generation, and successful engraftment was confirmed using flow cytometry. JMML PDX mice were treated with trametinib versus vehicle control, with a median survival of 194 days in the treatment group versus 124 days in the control group (p = 0.02). Trametinib's target as a RAS pathway inhibitor was verified by showing inhibition of ERK phosphorylation using immunoblot assays. In conclusion, trametinib monotherapy significantly prolongs survival in our JMML PDX model by inhibiting the RAS pathway. Our model can be effectively used for assessment of novel targeted treatments, including potential combination therapies, to improve JMML outcomes.

Targeting RAS-ERK pathway alterations with MEK inhibitors to improve chemosensitivity in high grade serous ovarian cancers.

OBJECTIVE: Assess if MEK inhibitor blockade of RAS-ERK pathway adaptive response in high grade serous ovarian cancers (HGSOC) improves platinum sensitivity. METHODS: Three HGSOC cell lines and three patient derived organoid (PDOs) samples from ascites of platinum resistant HGSOC patients were collected. Cell lines and PDOs were exposed to carboplatin and MEK inhibitors cobimetinib or trametinib. Cytotoxic effects of MEK inhibitors alone or combined with carboplatin were established. Western blots demonstrated RAS-ERK pathway blockage after MEK inhibitor treatment. RNA sequencing assessed gene expression after MEK inhibitor treatment. Cell line NF1 gene knockdown was performed with corresponding chemosensitivity levels. RESULTS: High carboplatin IC50 levels indicated platinum resistance in cell lines and PDOs. Cobimetinib induced cytotoxicity in cell lines and PDOs, while trametinib was less effective. Western blot confirmed MEK-ERK pathway blockage at minimal concentrations of MEK inhibitors in cell lines and PDOs. Phosphorylated-ERK levels of untreated cells indicated higher levels of RAS-ERK pathway activation in OVSAHO and OVCAR7 compared to OVCAR3. OVSAHO harbors a NF1 mutation and had highest levels of RAS-ERK activation. Cotreatment with carboplatin and MEK inhibitors showed varying synergistic cytotoxic effects at different combinations. Synergistic effect was most prominent in the OVSAHO carboplatin and cobimetinib combination. RNA sequencing identified downregulation of c-MYC and FOXM1 gene expression after MEK inhibitor treatment. NF1 gene knockdown showed an acquired increased IC50 compared to parental cells. CONCLUSION: MEK inhibitors block RAS-ERK pathways in platinum resistant HGSOC cells and PDOs. MEK inhibitors with carboplatin have select synergistic effects which may indicate a strategy to improve platinum sensitivity.

In vivo modeling of metastatic human high-grade serous ovarian cancer in mice.

Metastasis is responsible for 90% of human cancer mortality, yet it remains a challenge to model human cancer metastasis in vivo. Here we describe mouse models of high-grade serous ovarian cancer, also known as high-grade serous carcinoma (HGSC), the most common and deadliest human ovarian cancer type. Mice genetically engineered to harbor Dicer1 and Pten inactivation and mutant p53 robustly replicate the peritoneal metastases of human HGSC with complete penetrance. Arising from the fallopian tube, tumors spread to the ovary and metastasize throughout the pelvic and peritoneal cavities, invariably inducing hemorrhagic ascites. Widespread and abundant peritoneal metastases ultimately cause mouse deaths (100%). Besides the phenotypic and histopathological similarities, mouse HGSCs also display marked chromosomal instability, impaired DNA repair, and chemosensitivity. Faithfully recapitulating the clinical metastases as well as molecular and genomic features of human HGSC, this murine model will be valuable for elucidating the mechanisms underlying the development and progression of metastatic ovarian cancer and also for evaluating potential therapies.

MutEx: a multifaceted gateway for exploring integrative pan-cancer genomic data.

Somatic mutation and gene expression dysregulation are considered two major tumorigenesis factors. While independent investigations of either factor pervade, studies of associations between somatic mutations and gene expression changes have been sporadic and nonsystematic. Utilizing genomic data collected from 11 315 subjects of 33 distinct cancer types, we constructed MutEx, a pan-cancer integrative genomic database. This database records the relationships among gene expression, somatic mutation and survival data for cancer patients. MutEx can be used to swiftly explore the relationship between these genomic/clinic features within and across cancer types and, more importantly, search for corroborating evidence for hypothesis inception. Our database also incorporated Gene Ontology and several pathway databases to enhance functional annotation, and elastic net and a gene expression composite score to aid in survival analysis. To demonstrate the usability of MutEx, we provide several application examples, including top somatic mutations associated with the most extensive expression dysregulation in breast cancer, differential mutational burden downstream of DNA mismatch repair gene mutations and composite gene expression score-based survival difference in breast cancer. MutEx can be accessed at http://www.innovebioinfo.com/Databases/Mutationdb_About.php.

Serine Protease HTRA1 as a Novel Target Antigen in Primary Membranous Nephropathy.

BACKGROUND: Identification of target antigens PLA2R, THSD7A, NELL1, or Semaphorin-3B can explain the majority of cases of primary membranous nephropathy (MN). However, target antigens remain unidentified in 15%-20% of patients. METHODS: A multipronged approach, using traditional and modern technologies, converged on a novel target antigen, and capitalized on the temporal variation in autoantibody titer for biomarker discovery. Immunoblotting of human glomerular proteins followed by differential immunoprecipitation and mass spectrometric analysis was complemented by laser-capture microdissection followed by mass spectrometry, elution of immune complexes from renal biopsy specimen tissue, and autoimmune profiling on a protein fragment microarray. RESULTS: These approaches identified serine protease HTRA1 as a novel podocyte antigen in a subset of patients with primary MN. Sera from two patients reacted by immunoblotting with a 51-kD protein within glomerular extract and with recombinant human HTRA1, under reducing and nonreducing conditions. Longitudinal serum samples from these patients seemed to correlate with clinical disease activity. As in PLA2R- and THSD7A- associated MN, anti-HTRA1 antibodies were predominantly IgG4, suggesting a primary etiology. Analysis of sera collected during active disease versus remission on protein fragment microarrays detected significantly higher titers of anti-HTRA1 antibody in active disease. HTRA1 was specifically detected within immune deposits of HTRA1-associated MN in 14 patients identified among three cohorts. Screening of 118 "quadruple-negative" (PLA2R-, THSD7A-, NELL1-, EXT2-negative) patients in a large repository of MN biopsy specimens revealed a prevalence of 4.2%. CONCLUSIONS: Conventional and more modern techniques converged to identify serine protease HTRA1 as a target antigen in MN.

Rydberg States of H3 and HeH as Potential Coolants for Primordial Star Formation.

Current theory and measurements establish the age of the universe as ca. 13.8 billion years. For the first several hundred million years of its existence, it was a dark, opaque void. After that, the hydrogen atoms comprising most of the "ordinary" matter began to condense and ionize, eventually forming the first stars that would illuminate the sky. Details of how these "primordial" stars formed have been widely debated, but remain elusive. A central issue in this process is the mechanism by which the primordial gas (mainly hydrogen and helium atoms) collected via the action of dark matter cooled and further accreted to fusion densities. Current models invoke collisional excitation of H2 molecular rotations and subsequent radiative rotational transitions allowed by the weak molecular quadrupole moment. In this work, we review the salient considerations and present some new ideas, based on recent spectroscopic observations of neutral H3 Rydberg electronic state emission in the mid-infrared region.

A large-scale comparative study of isoform expressions measured on four platforms.

BACKGROUND: Most eukaryotic genes produce different transcripts of multiple isoforms by inclusion or exclusion of particular exons. The isoforms of a gene often play diverse functional roles, and thus it is necessary to accurately measure isoform expressions as well as gene expressions. While previous studies have demonstrated the strong agreement between mRNA sequencing (RNA-seq) and array-based gene and/or isoform quantification platforms (Microarray gene expression and Exon-array), the more recently developed NanoString platform has not been systematically evaluated and compared, especially in large-scale studies across different cancer domains. RESULTS: In this paper, we present a large-scale comparative study among RNA-seq, NanoString, array-based, and RT-qPCR platforms using 46 cancer cell lines across different cancer types. The goal is to understand and evaluate the calibers of the platforms for measuring gene and isoform expressions in cancer studies. We first performed NanoString experiments on 59 cancer cell lines with 404 custom-designed probes for measuring the expressions of 478 isoforms in 155 genes, and additional RT-qPCR experiments for a subset of the measured isoforms in 13 cell lines. We then combined the data with the matched RNA-seq, Exon-array, and Microarray data of 46 of the 59 cell lines for the comparative analysis. CONCLUSION: In the comparisons of the platforms for measuring the expressions at both isoform and gene levels, we found that (1) the agreement on isoform expressions is lower than the agreement on gene expressions across the four platforms; (2) NanoString and Exon-array are not consistent on isoform quantification even though both techniques are based on hybridization reactions; (3) RT-qPCR experiments are more consistent with RNA-seq and Exon-array than NanoString in isoform quantification; (4) different RNA-seq isoform quantification methods show varying estimation results, and among the methods, Net-RSTQ and eXpress are more consistent across the platforms; and (5) RNA-seq has the best overall consistency with the other platforms on gene expression quantification.

Short-term organoid culture for drug sensitivity testing of high-grade serous carcinoma.

OBJECTIVE: Cancer patient-derived organoids (PDOs) grow as three dimensional (3D) structures in the presence of extracellular matrix and have been found to represent the original tumor's genetic complexity. In addition, PDOs can be grown and subjected to drug sensitivity testing in a shorter time course and with lesser expense than patient-derived xenograft models. Many patients with recurrent ovarian cancer develop malignant effusions that become refractory to chemotherapy. Since these same patients often present for palliative aspiration of ascites or pleural effusions, there is a potential opportunity to obtain tumor specimens in the form of multicellular spheroids (MCS) present in malignant effusion fluids. Our objective was to develop a short duration culture of MCS from ovarian cancer malignant effusions in conditions selected to support organoid growth and use them as a platform for empirical drug sensitivity testing. METHODS: In this study, malignant effusion specimens were collected from patients with high-grade serous ovarian carcinoma (HGSOC). MCS were recovered and subjected to culture conditions designed to support organoid growth. In a subset of specimens, RNA-sequencing was performed at two time points during the short-term culture to determine changes in transcriptome in response to culture conditions. Organoid induction was also characterized in these specimens using Ki67 staining and histologic analysis. Drug sensitivity testing was performed on all specimens. RESULTS: Our model describes organoids formed within days of primary culture, which can recapitulate the histological features of malignant ascites fluid and can be expanded for at least 6 days. RNA-seq analysis of four patient specimens showed that within 6 days of culture, there was significant up-regulation of genes related to cellular proliferation, epithelial-mesenchymal transition, and KRAS signaling pathways. Drug sensitivity testing identified several agents with therapeutic potential. CONCLUSIONS: Short duration organoid culture of MCS from HGSOC malignant effusions can be used as a platform for empiric drug sensitivity testing. These ex vivo models may be helpful in screening new or existing therapeutic agents prior to individualized treatment options.

The P72R Polymorphism in R248Q/W p53 Mutants Modifies the Mutant Effect on Epithelial to Mesenchymal Transition Phenotype and Cell Invasion via CXCL1 Expression.

High-grade serous carcinoma (HGSC), the most lethal subtype of epithelial ovarian cancer (EOC), is characterized by widespread TP53 mutations (>90%), most of which are missense mutations (>70%). The objective of this study was to investigate differential transcriptional targets affected by a common germline P72R SNP (rs1042522) in two p53 hotspot mutants, R248Q and R248W, and identify the mechanism through which the P72R SNP affects the neomorphic properties of these mutants. Using isogenic cell line models, transcriptomic analysis, xenografts, and patient data, we found that the P72R SNP modifies the effect of p53 hotspot mutants on cellular morphology and invasion properties. Most importantly, RNA sequencing studies identified CXCL1 a critical factor that is differentially affected by P72R SNP in R248Q and R248W mutants and is responsible for differences in cellular morphology and functional properties observed in these p53 mutants. We show that the mutants with the P72 SNP promote a reversion of the EMT phenotype to epithelial characteristics, whereas its R72 counterpart promotes a mesenchymal transition via the chemokine CXCL1. These studies reveal a new role of the P72R SNP in modulating the neomorphic properties of p53 mutants via CXCL1, which has significant implications for tumor invasion and metastasis.

digit-a tool for detection and identification of genomic interchromosomal translocations.

Structural variations (SVs) in genomic DNA can have profound effects on the evolution of living organisms, on phenotypic variations and on disease processes. A critical step in discovering the full extent of structural variations is the development of tools to characterize these variations accurately in next generation sequencing data. Toward this goal, we developed a software pipeline named digit that implements a novel measure of mapping ambiguity to discover interchromosomal SVs from mate-pair and pair-end sequencing data. The workflow robustly handles the high numbers of artifacts present in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity. In the simulated data set, our workflow recovered 96% of simulated SVs. It generates a self-updating library of common translocations and allows for the investigation of patient- or group-specific events, making it suitable for discovering and cataloging chromosomal translocations associated with specific groups, traits, diseases or population structures.

Changes in O-Linked N-Acetylglucosamine (O-GlcNAc) Homeostasis Activate the p53 Pathway in Ovarian Cancer Cells.

O-GlcNAcylation is a dynamic post-translational modification consisting of the addition of a single N-acetylglucosamine sugar to serine and threonine residues in proteins by the enzyme O-linked ß-N-acetylglucosamine transferase (OGT), whereas the enzyme O-GlcNAcase (OGA) removes the modification. In cancer, tumor samples present with altered O-GlcNAcylation; however, changes in O-GlcNAcylation are not consistent between tumor types. Interestingly, the tumor suppressor p53 is modified by O-GlcNAc, and most solid tumors contain mutations in p53 leading to the loss of p53 function. Because ovarian cancer has a high frequency of p53 mutation rates, we decided to investigate the relationship between O-GlcNAcylation and p53 function in ovarian cancer. We measured a significant decrease in O-GlcNAcylation of tumor tissue in an ovarian tumor microarray. Furthermore, O-GlcNAcylation was increased, and OGA protein and mRNA levels were decreased in ovarian tumor cell lines not expressing the protein p53. Treatment with the OGA inhibitor Thiamet-G (TMG), silencing of OGA, or overexpression of OGA and OGT led to p53 stabilization, increased nuclear localization, and increased protein and mRNA levels of p53 target genes. These data suggest that changes in O-GlcNAc homeostasis activate the p53 pathway. Combination treatment of the chemotherapeutic cisplatin with TMG decreased tumor cell growth and enhanced cell cycle arrest without impairing cytotoxicity. The effects of TMG on tumor cell growth were partially dependent on wild type p53 activation. In conclusion, changes in O-GlcNAc homeostasis activate the wild type p53 pathway in ovarian cancer cells, and OGA inhibition has the potential as an adjuvant treatment for ovarian carcinoma.

Meeting Report From the 2016 11th Biennial Ovarian Cancer Research Symposium: Mechanisms of Initiation and Progression of Ovarian Cancers.

OBJECTIVE: The aim of this study was to review the latest research advances on the mechanisms of initiation and progression of ovarian cancer. METHODS: At the 11th Biennial Ovarian Cancer Research Symposium, which was held in Seattle, Washington in September 2016, leaders in ovarian cancer research convened to present and discuss current advances and future directions in ovarian cancer research. RESULTS: One session was dedicated to Mechanisms of Initiation and Progression of Ovarian Cancer, and included a keynote presentation from Dr Ronny Drapkin, MD (University of Pennsylvania), and an invited oral presentation from Laising Yen, PhD (Baylor College of Medicine). Nine additional oral presentations were selected from abstract submissions. Thirty-three abstracts were presented in poster format and were grouped into the categories of mechanisms of the genesis of genomic instability, tumor initiation, metastases of ovarian cancers, innate and acquired chemotherapy resistance, tumor progression, tumor-initiating cell and chemotherapy resistance, and immunomodulation. CONCLUSIONS: Eradication of ovarian cancers requires clear understanding of molecular mechanisms of ovarian cancer initiation and progression. These mechanisms will not only drive the precision of early detection, but also discovery of new therapies to target precursor lesions and more advanced stage disease.

Ovarian Cancer Prevention, Screening, and Early Detection: Report From the 11th Biennial Ovarian Cancer Research Symposium.

OBJECTIVE: The aim of this study is to provide a summary report on recent research advances in ovarian cancer prevention, screening, and early detection that were presented at the 11th Biennial Ovarian Cancer Research Symposium in Seattle, Wash. METHODS: At the symposium, researchers from around the world participated in the poster, invited oral presentation and keynote presentation, and discussed the latest advances in the areas of cancer prevention, screening, and early detection. RESULTS: In the Scientific Session for Prevention, Screening, and Early Detection, Usha Menon, PhD (University of College London), presented exploratory studies from the ongoing UK Collaborative Trial of Ovarian Cancer Screening trial. Karen Lu, MD, presented her studies on BRCA testing and salpingectomies as prevention strategies. Eight speakers were selected from the abstracts for short oral presentations, and the topic ranges from Ovarian Cancer Early Detection Program by Saul Rivkin, MD, to the ultra-deep sequencing of somatic mutations in TP53 in normal and cancer patients by Rosana Risques, PhD. Fourteen additional poster presentations, ranging from the potential role of cancer stem cells in recurrence to retrotransposons in ovarian cancer development, round up the session. CONCLUSIONS: Although progress is being made in the areas of prevention, screening, and early detection, these advances have not yet translated into tangible clinical benefits for patients with ovarian cancer. A wide array of research topics presented in the session provides a glimmer of hope that better understanding of genetic risk factors, refining screening strategies, and developing new methods for early detection will eventually lead to improved outcome for patients with ovarian cancer.

TP53 mutations, tetraploidy and homologous recombination repair defects in early stage high-grade serous ovarian cancer.

To determine early somatic changes in high-grade serous ovarian cancer (HGSOC), we performed whole genome sequencing on a rare collection of 16 low stage HGSOCs. The majority showed extensive structural alterations (one had an ultramutated profile), exhibited high levels of p53 immunoreactivity, and harboured a TP53 mutation, deletion or inactivation. BRCA1 and BRCA2 mutations were observed in two tumors, with nine showing evidence of a homologous recombination (HR) defect. Combined Analysis with The Cancer Genome Atlas (TCGA) indicated that low and late stage HGSOCs have similar mutation and copy number profiles. We also found evidence that deleterious TP53 mutations are the earliest events, followed by deletions or loss of heterozygosity (LOH) of chromosomes carrying TP53, BRCA1 or BRCA2. Inactivation of HR appears to be an early event, as 62.5% of tumours showed a LOH pattern suggestive of HR defects. Three tumours with the highest ploidy had little genome-wide LOH, yet one of these had a homozygous somatic frame-shift BRCA2 mutation, suggesting that some carcinomas begin as tetraploid then descend into diploidy accompanied by genome-wide LOH. Lastly, we found evidence that structural variants (SV) cluster in HGSOC, but are absent in one ultramutated tumor, providing insights into the pathogenesis of low stage HGSOC.

Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis.

High-throughput mRNA sequencing (RNA-Seq) is widely used for transcript quantification of gene isoforms. Since RNA-Seq data alone is often not sufficient to accurately identify the read origins from the isoforms for quantification, we propose to explore protein domain-domain interactions as prior knowledge for integrative analysis with RNA-Seq data. We introduce a Network-based method for RNA-Seq-based Transcript Quantification (Net-RSTQ) to integrate protein domain-domain interaction network with short read alignments for transcript abundance estimation. Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene. The transcript abundances of all the genes are then jointly estimated with alternating optimization of multiple EM problems. In simulation Net-RSTQ effectively improved isoform transcript quantifications when isoform co-expressions correlate with their interactions. qRT-PCR results on 25 multi-isoform genes in a stem cell line, an ovarian cancer cell line, and a breast cancer cell line also showed that Net-RSTQ estimated more consistent isoform proportions with RNA-Seq data. In the experiments on the RNA-Seq data in The Cancer Genome Atlas (TCGA), the transcript abundances estimated by Net-RSTQ are more informative for patient sample classification of ovarian cancer, breast cancer and lung cancer. All experimental results collectively support that Net-RSTQ is a promising approach for isoform quantification. Net-RSTQ toolbox is available at http://compbio.cs.umn.edu/Net-RSTQ/.

Expression profiling of in vivo ductal carcinoma in situ progression models identified B cell lymphoma-9 as a molecular driver of breast cancer invasion.

INTRODUCTION: There are an estimated 60,000 new cases of ductal carcinoma in situ (DCIS) each year. A lack of understanding in DCIS pathobiology has led to overtreatment of more than half of patients. We profiled the temporal molecular changes during DCIS transition to invasive ductal carcinoma (IDC) using in vivo DCIS progression models. These studies identified B cell lymphoma-9 (BCL9) as a potential molecular driver of early invasion. BCL9 is a newly found co-activator of Wnt-stimulated ß-catenin-mediated transcription. BCL9 has been shown to promote progression of multiple myeloma and colon carcinoma. However BCL9 role in breast cancer had not been previously recognized. METHODS: Microarray and RNA sequencing were utilized to characterize the sequential changes in mRNA expression during DCIS invasive transition. BCL9-shRNA knockdown was performed to assess the role of BCL9 in in vivo invasion, epithelial-mesenchymal transition (EMT) and canonical Wnt-signaling. Immunofluorescence of 28 patient samples was used to assess a correlation between the expression of BCL9 and biomarkers of high risk DCIS. The cancer genome atlas data were analyzed to assess the status of BCL9 gene alterations in breast cancers. RESULTS: Analysis of BCL9, by RNA and protein showed BCL9 up-regulation to be associated with DCIS transition to IDC. Analysis of patient DCIS revealed a significant correlation between high nuclear BCL9 and pathologic characteristics associated with DCIS recurrence: Estrogen receptor (ER) and progesterone receptor (PR) negative, high nuclear grade, and high human epidermal growth factor receptor2 (HER2). In vivo silencing of BCL9 resulted in the inhibition of DCIS invasion and reversal of EMT. Analysis of the TCGA data showed BCL9 to be altered in 26 % of breast cancers. This is a significant alteration when compared to HER2 (ERBB2) gene (19 %) and estrogen receptor (ESR1) gene (8 %). A significantly higher proportion of basal like invasive breast cancers compared to luminal breast cancers showed BCL9 amplification. CONCLUSION: BCL9 is a molecular driver of DCIS invasive progression and may predispose to the development of basal like invasive breast cancers. As such, BCL9 has the potential to serve as a biomarker of high risk DCIS and as a therapeutic target for prevention of IDC.

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.

Somatic loss of function mutations in neurofibromin 1 and MYC associated factor X genes identified by exome-wide sequencing in a wild-type GIST case.

BACKGROUND: Approximately 10-15 % of gastrointestinal stromal tumors (GISTs) lack gain of function mutations in the KIT and platelet-derived growth factor receptor alpha (PDGFRA) genes. An alternate mechanism of oncogenesis through loss of function of the succinate-dehydrogenase (SDH) enzyme complex has been identified for a subset of these "wild type" GISTs. METHODS: Paired tumor and normal DNA from an SDH-intact wild-type GIST case was subjected to whole exome sequencing to identify the pathogenic mechanism(s) in this tumor. Selected findings were further investigated in panels of GIST tumors through Sanger DNA sequencing, quantitative real-time PCR, and immunohistochemical approaches. RESULTS: A hemizygous frameshift mutation (p.His2261Leufs*4), in the neurofibromin 1 (NF1) gene was identified in the patient's GIST; however, no germline NF1 mutation was found. A somatic frameshift mutation (p.Lys54Argfs*31) in the MYC associated factor X (MAX) gene was also identified. Immunohistochemical analysis for MAX on a large panel of GISTs identified loss of MAX expression in the MAX-mutated GIST and in a subset of mainly KIT-mutated tumors. CONCLUSION: This study suggests that inactivating NF1 mutations outside the context of neurofibromatosis may be the oncogenic mechanism for a subset of sporadic GIST. In addition, loss of function mutation of the MAX gene was identified for the first time in GIST, and a broader role for MAX in GIST progression was suggested.

Network-based survival analysis reveals subnetwork signatures for predicting outcomes of ovarian cancer treatment.

Cox regression is commonly used to predict the outcome by the time to an event of interest and in addition, identify relevant features for survival analysis in cancer genomics. Due to the high-dimensionality of high-throughput genomic data, existing Cox models trained on any particular dataset usually generalize poorly to other independent datasets. In this paper, we propose a network-based Cox regression model called Net-Cox and applied Net-Cox for a large-scale survival analysis across multiple ovarian cancer datasets. Net-Cox integrates gene network information into the Cox's proportional hazard model to explore the co-expression or functional relation among high-dimensional gene expression features in the gene network. Net-Cox was applied to analyze three independent gene expression datasets including the TCGA ovarian cancer dataset and two other public ovarian cancer datasets. Net-Cox with the network information from gene co-expression or functional relations identified highly consistent signature genes across the three datasets, and because of the better generalization across the datasets, Net-Cox also consistently improved the accuracy of survival prediction over the Cox models regularized by L(2) or L(1). This study focused on analyzing the death and recurrence outcomes in the treatment of ovarian carcinoma to identify signature genes that can more reliably predict the events. The signature genes comprise dense protein-protein interaction subnetworks, enriched by extracellular matrix receptors and modulators or by nuclear signaling components downstream of extracellular signal-regulated kinases. In the laboratory validation of the signature genes, a tumor array experiment by protein staining on an independent patient cohort from Mayo Clinic showed that the protein expression of the signature gene FBN1 is a biomarker significantly associated with the early recurrence after 12 months of the treatment in the ovarian cancer patients who are initially sensitive to chemotherapy. Net-Cox toolbox is available at http://compbio.cs.umn.edu/Net-Cox/.

Metformin intake is associated with better survival in ovarian cancer: a case-control study.

BACKGROUND: The objective of this case-control study was to identify any association of metformin intake with the survival of patients with ovarian cancer. METHODS: In this retrospective case-control study, women with ovarian cancer who received metformin (cases) were compared with women with ovarian cancer who did not receive metformin (controls). A 2-layered analysis was conducted. In preliminary analysis, all cases (the OC cohort) were compared with controls at a 1:2 ratio. Subsequently, in definitive analysis, only patients who had epithelial ovarian cancer (the EOC cohort) were compared with controls at a 1:3 ratio. In the EOC cohort, cases were matched with controls for age (±5 years), International Federation of Gynecology and Obstetrics stage, and residual disease. Prognostic variables and disease specific survival were compared using chi-square tests, the Kaplan-Meier (log-rank) method, and Cox proportional hazards analysis. RESULTS: In a preliminary analysis of the OC cohort (72 cases and 143 controls), cases had better survival (5-year disease-specific survival for cases vs controls, 73% vs 44%; P = .0002). In the definitive analysis of the EOC cohort (61 cases and 178 controls), the distribution of age, disease stage, optimal cytoreduction, serous histology, and platinum chemotherapy remained similar between cases and controls (P > .05). Despite these similarities, cases had significantly better survival (5-year disease-specific survival for cases vs controls, 67% vs 47%; P = .007). On multivariate analysis, metformin remained an independent predictor of survival (hazard ratio, 2.2; 95% confidence interval, 1.2-3.8; P = .007) after controlling for disease stage, grade, histology, chemotherapy, body mass index, and surgical cytoreduction. CONCLUSIONS: The results of this study indicated an association of metformin intake with survival in patients with ovarian cancer. The receipt of metformin was associated with better survival, and the authors concluded that metformin is worthy of clinical trials in ovarian cancer.