Loss of DOK2 induces carboplatin resistance in ovarian cancer via suppression of apoptosis

Objective. Ovarian cancers are highly heterogeneous and while chemotherapy is the preferred treatment many patients are intrinsically resistant or quickly develop resistance. Furthermore, all tumors that recur ultimately become resistant. Recent evidence suggests that epigenetic deregulation may be a key factor in the onset and maintenance of chemoresistance. We set out to identify epigenetically silenced genes that affect chemoresistance. Methods. The epigenomes of a total of 45 ovarian samples were analyzed to identify epigenetically altered genes that segregate with platinum response, and further filtered with expression data to identify genes that were suppressed. A tissue culture carboplatin resistance screen was utilized to functionally validate this set of candidate platinum resistance genes. Results. Our screen correctly identified 19 genes that when suppressed altered the chemoresistance of the cells in culture. Of the genes identified in the screen we further characterized one gene, docking protein 2 (DOK2), an adapter protein downstream of tyrosine kinase, to determine if we could elucidate the mechanism by which it increased resistance. The loss of DOK2 decreased the level of apoptosis in response to carboplatin. Furthermore, in cells with reduced DOK2, the level of anoikis was decreased. Conclusions. We have developed a screening methodology that analyzes the epigenome and informatically identifies candidate genes followed by in vitro culture screening of the candidate genes. To validate our screening methodology we further characterized one candidate gene, DOK2, and showed that loss of DOK2 induces chemotherapy resistance by decreasing the level of apoptosis in response to treatment. (C) 2013 The Authors. Published by Elsevier Inc. All rights reserved

Single nucleus genome sequencing reveals high similarity among nuclei of an endomycorrhizal fungus

Nuclei of arbuscular endomycorrhizal fungi have been described as highly diverse due to their asexual nature and absence of a single cell stage with only one nucleus. This has raised fundamental questions concerning speciation, selection and transmission of the genetic make-up to next generations. Although this concept has become textbook knowledge, it is only based on studying a few loci, including 45S rDNA. To provide a more comprehensive insight into the genetic makeup of arbuscular endomycorrhizal fungi, we applied de novo genome sequencing of individual nuclei of Rhizophagus irregularis. This revealed a surprisingly low level of polymorphism between nuclei. In contrast, within a nucleus, the 45S rDNA repeat unit turned out to be highly diverged. This finding demystifies a long-lasting hypothesis on the complex genetic makeup of arbuscular endomycorrhizal fungi. Subsequent genome assembly resulted in the first draft reference genome sequence of an arbuscular endomycorrhizal fungus. Its length is 141 Mbps, representing over 27,000 protein-coding gene models. We used the genomic sequence to reinvestigate the phylogenetic relationships of Rhizophagus irregularis with other fungal phyla. This unambiguously demonstrated that Glomeromycota are more closely related to Mucoromycotina than to its postulated sister Dikarya

Identification of Tumor Suppressors and Oncogenes from Genomic and Epigenetic Features in Ovarian Cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates

Integrative prediction of gene function and platinum-free survival from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to discover genes critical to the development, progression, and therapeutic resistance of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatics analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We identify changes in DNA methylation and expression specifically for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic gene function from integrative analysis of three modalities: copy number variation, DNA methylation, and gene expression. Our method (1) calculates the extent of genomic and epigenetic alterations of defined tumor suppressor and oncogenic features for the functional prediction of significant ovarian cancer gene candidates and (2) identifies the functional activity or inactivity of known tumor suppressors and oncogenes in ovarian cancer. We applied our protocol on 42 primary serous ovarian cancer samples using MOMA-ROMA representational array assays. Additionally, we provide the basis for incorporating epigenetic profiles of ovarian tumors for the purposes of platinum-free survival prediction in the context of TCGA data

A quantitative proteomics-based signature of platinum sensitivity in ovarian cancer cell lines

Although DNA encodes the molecular instructions that underlie the control of cell function, it is the proteins that are primarily responsible for implementing those instructions. Therefore quantitative analyses of the proteome would be expected to yield insights into important candidates for the detection and treatment of disease. We present an iTRAQ (isobaric tag for relative and absolute quantification)-based proteomic analysis of ten ovarian cancer cell lines and two normal ovarian surface epithelial cell lines. We profiled the abundance of 2659 cellular proteins of which 1273 were common to all 12 cell lines. Of the 1273, 75 proteins exhibited elevated expression and 164 proteins had diminished expression in the cancerous cells compared with the normal cell lines. The iTRAQ expression profiles allowed us to segregate cell lines based upon sensitivity and resistance to carboplatin. Importantly, we observed no substantial correlation between protein abundance and RNA expression or epigenetic DNA methylation data. Furthermore, we could not discriminate between sensitivity and resistance to carboplatin on the basis of RNA expression and DNA methylation data alone. The present study illustrates the importance of proteomics-based discovery for defining the basis for the carboplatin response in ovarian cancer and highlights candidate proteins, particularly involved in cellular redox regulation, homologous recombination and DNA damage repair, which otherwise could not have been predicted from whole genome and expression data sources alone

Proteomic identification of carboplatin resistance in ovarian cancer cells

The analysis of quantitative protein expression is necessary for the determination of actual biochemical protein concentrations that can lead to a more accurate description of cellular function. A knowledgebase of cancer function based on cellular protein levels can more directly implicate potential gene candidates for the detection and treatment of disease. Therefore, we analyzed iTRAQ (isobaric tag for relative and absolute quantification) data from 11 serous ovarian cancer cell lines and 2 normal ovarian surface epithelial cell lines. We profiled cellular protein abundance in over 3000 proteins with 749 proteins common to all 13 cell lines. Of the 749, 52 proteins exhibited elevated expression and 46 proteins had diminished expression in the cancerous cells when compared to the normal cell lines. We identified the 300 most variable iTRAQ expressed proteins based on median absolute deviation within 8 carboplatin sensitive and resistant cell lines. Using iTRAQ protein expression profiles from these 300 we successfully segregated the cell lines based on carboplatin sensitivity and resistance measurements. We further examined correlations among iTRAQ protein expression, individual gene RNA expression and DNA methylation data. There was no substantial correlation between protein abundance and RNA expression or epigenetic data. Furthermore RNA expression and DNA methylation data alone did not show any significant discrimination for chemosensitivity or resistance. We therefore present the potential of proteomics based discovery for carboplatin response in ovarian cancer and also identify putative gene candidates that may be functionally responsible for chemotherapy response which otherwise would not have been predicted using other singular whole genome data sources

Rna sequencing of primary cutaneous and breast-implant associated anaplastic large cell lymphomas reveals infrequent fusion transcripts and upregulation of PI3K/AKT signaling via neurotrophin pathway genes

Cutaneous and breast implant-associated anaplastic large-cell lymphomas (cALCLs and BI-ALCLs) are two localized forms of peripheral T-cell lymphomas (PTCLs) that are recognized as distinct entities within the family of ALCL. JAK-STAT signaling is a common feature of all ALCL subtypes, whereas DUSP22/IRF4, TP63 and TYK gene rearrangements have been reported in a proportion of ALK-negative sALCLs and cALCLs. Both cALCLs and BI-ALCLs differ in their gene expression profiles compared to PTCLs; however, a direct comparison of the genomic alterations and transcriptomes of these two entities is lacking. By performing RNA sequencing of 1385 genes (TruSight RNA Pan-Cancer, Illumina) in 12 cALCLs, 10 BI-ALCLs and two anaplastic lymphoma kinase (ALK)-positive sALCLs, we identified the previously reported TYK2-NPM1 fusion in 1 cALCL (1/12, 8%), and four new intrachromosomal gene fusions in 2 BI-ALCLs (2/10, 20%) involving genes on chromosome 1 (EPS15-GNG12 and ARNT-GOLPH3L) and on chromosome 17 (MYO18A-GIT1 and NF1-GOSR1). One of the two BI-ALCL samples showed a complex karyotype, raising the possibility that genomic instability may be responsible for intra-chromosomal fusions in BI-ALCL. Moreover, transcriptional analysis revealed similar upregulation of the PI3K/Akt pathway, associated with enrichment in the expression of neurotrophin signaling genes, which was more conspicuous in BI-ALCL, as well as differences, i.e., over-expression of genes involved in the RNA polymerase II transcription program in BI-ALCL and of the RNA splicing/processing program in cALCL

Functional Mutation of SMAC/DIABLO, Encoding a Mitochondrial Proapoptotic Protein, Causes Human Progressive Hearing Loss DFNA64

SMAC/DIABLO is a mitochondrial proapoptotic protein that is released from mitochondria during apoptosis and counters the inhibitory activities of inhibitor of apoptosis proteins, IAPs. By linkage analysis and candidate screening, we identified a heterozygous SMAC/DIABLO mutation, c.377C>T (p.Ser126Leu, refers to p.Ser71Leu in the mature protein) in a six-generation Chinese kindred characterized by dominant progressive nonsyndromic hearing loss, designated as DFNA64. SMAC/DIABLO is highly expressed in human embryonic ears and is enriched in the developing mouse inner-ear hair cells, suggesting it has a role in the development and homeostasis of hair cells. We used a functional study to demonstrate that the SMAC/DIABLOS71L mutant, while retaining the proapoptotic function, triggers significant degradation of both wild-type and mutant SMAC/DIABLO and renders host mitochondria susceptible to calcium-induced loss of the membrane potential. Our work identifies DFNA64 as the human genetic disorder associated with SMAC/DIABLO malfunction and suggests that mutant SMAC/DIABLOS71L might cause mitochondrial dysfunction