Zeynep H. Gümüş

Integrative annotation of variants from 1092 humans: application to cancer genomics.

Introduction Plummeting sequencing costs have led to a great increase in the number of personal genomes. Interpreting the large number of variants in them, particularly in noncoding regions, is a current challenge. This is especially the case for somatic variants in cancer genomes, a large proportion of which are noncoding. Prioritization of candidate noncoding cancer drivers based on patterns of selection. (Step 1) Filter somatic variants to exclude 1000 Genomes polymorphisms; (2) retain variants in noncoding annotations; (3) retain those in “sensitive” regions; (4) prioritize those disrupting a transcription-factor binding motif and (5) residing near the center of a biological network; (6) prioritize ones in annotation blocks mutated in multiple cancer samples. Methods We investigated patterns of selection in DNA elements from the ENCODE project using the full spectrum of variants from 1092 individuals in the 1000 Genomes Project (Phase 1), including single-nucleotide variants (SNVs), short insertions and deletions (indels), and structural variants (SVs). Although we analyzed broad functional annotations, such as all transcription-factor binding sites, we focused more on highly specific categories such as distal binding sites of factor ZNF274. The greater statistical power of the Phase 1 data set compared with earlier ones allowed us to differentiate the selective constraints on these categories. We also used connectivity information between elements from protein-protein-interaction and regulatory networks. We integrated all the information on selection to develop a workflow (FunSeq) to prioritize personal-genome variants on the basis of their deleterious impact. As a proof of principle, we experimentally validated and characterized a few candidate variants. Results We identified a specific subgroup of noncoding categories with almost as much selective constraint as coding genes: “ultrasensitive” regions. We also uncovered a number of clear patterns of selection. Elements more consistently active across tissues and both maternal and paternal alleles (in terms of allele-specific activity) are under stronger selection. Variants disruptive because of mechanistic effects on transcription-factor binding (i.e. “motif-breakers”) are selected against. Higher network connectivity (i.e. for hubs) is associated with higher constraint. Additionally, many hub promoters and regulatory elements show evidence of recent positive selection. Overall, indels and SVs follow the same pattern as SNVs; however, there are notable exceptions. For instance, enhancers are enriched for SVs formed by nonallelic homologous recombination. We integrated these patterns of selection into the FunSeq prioritization workflow and applied it to cancer variants, because they present a strong contrast to inherited polymorphisms. In particular, application to ~90 cancer genomes (breast, prostate and medulloblastoma) reveals nearly a hundred candidate noncoding drivers. Discussion Our approach can be readily used to prioritize variants in cancer and is immediately applicable in a precision-medicine context. It can be further improved by incorporation of larger-scale population sequencing, better annotations, and expression data from large cohorts. Identifying Important Identifiers Each of us has millions of sequence variations in our genomes. Signatures of purifying or negative selection should help identify which of those variations is functionally important. Khurana et al. (1235587) used sequence polymorphisms from 1092 humans across 14 populations to identify patterns of selection, especially in noncoding regulatory regions. Noncoding regions under very strong negative selection included binding sites of some chromatin and general transcription factors (TFs) and core motifs of some important TF families. Positive selection in TF binding sites tended to occur in network hub promoters. Many recurrent somatic cancer variants occurred in noncoding regulatory regions and thus might indicate mutations that drive cancer. Regions under strong selection in the human genome identify noncoding regulatory elements with possible roles in disease. Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations (“ultrasensitive”) and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, “motif-breakers”). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.

Gene expression elucidates functional impact of polygenic risk for schizophrenia.

Over 100 genetic loci harbor schizophrenia-associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of people with schizophrenia (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ∼20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3 or SNAP91. Altering expression of FURIN, TSNARE1 or CNTN4 changed neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yielded abnormal migration. Of 693 genes showing significant case-versus-control differential expression, their fold changes were ≤ 1.33, and an independent cohort yielded similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show that schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.

Effects of Cigarette Smoke on the Human Oral Mucosal Transcriptome

Use of tobacco is responsible for ∼30% of all cancer-related deaths in the United States, including cancers of the upper aerodigestive tract. In the current study, 40 current and 40 age- and gender-matched never smokers underwent buccal biopsies to evaluate the effects of smoking on the transcriptome. Microarray analyses were carried out using Affymetrix HGU133 Plus 2 arrays. Smoking altered the expression of numerous genes: 32 genes showed increased expression and 9 genes showed reduced expression in the oral mucosa of smokers versus never smokers. Increases were found in genes involved in xenobiotic metabolism, oxidant stress, eicosanoid synthesis, nicotine signaling, and cell adhesion. Increased numbers of Langerhans cells were found in the oral mucosa of smokers. Interestingly, smoking caused greater induction of aldo-keto reductases, enzymes linked to polycyclic aromatic hydrocarbon–induced genotoxicity, in the oral mucosa of women than men. Striking similarities in expression changes were found in oral compared with the bronchial mucosa. The observed changes in gene expression were compared with known chemical signatures using the Connectivity Map database and suggested that geldanamycin, a heat shock protein 90 inhibitor, might be an antimimetic of tobacco smoke. Consistent with this prediction, geldanamycin caused dose-dependent suppression of tobacco smoke extract–mediated induction of CYP1A1 and CYP1B1 in vitro. Collectively, these results provide new insights into the carcinogenic effects of tobacco smoke, support the potential use of oral epithelium as a surrogate tissue in future lung cancer chemoprevention trials, and illustrate the potential of computational biology to identify chemopreventive agents. Cancer Prev Res; 3(3); 266–78

Global Optimization of Nonlinear Bilevel Programming Problems

A novel technique that addresses the solution of the general nonlinear bilevel programming problem to global optimality is presented. Global optimality is guaranteed for problems that involve twice differentiable nonlinear functions as long as the linear independence constraint qualification condition holds for the inner problem constraints. The approach is based on the relaxation of the feasible region by convex underestimation, embedded in a branch and bound framework utilizing the basic principles of the deterministic global optimization algorithm, αBB [2, 4, 5, 11]. Epsilon global optimality in a finite number of iterations is theoretically guaranteed. Computational studies on several literature problems are reported.

GLOBAL OPTIMIZATION OF MIXED-INTEGER BILEVEL PROGRAMMING PROBLEMS

Abstract.Two approaches that solve the mixed-integer nonlinear bilevel programming problem to global optimality are introduced. The first addresses problems mixed-integer nonlinear in outer variables and C2-nonlinear in inner variables. The second adresses problems with general mixed-integer nonlinear functions in outer level. Inner level functions may be mixed-integer nonlinear in outer variables, linear, polynomial, or multilinear in inner integer variables, and linear in inner continuous variables. This second approach is based on reformulating the mixed-integer inner problem as continuous via its vertex polyheral convex hull representation and solving the resulting nonlinear bilevel optimization problem by a novel deterministic global optimization framework. Computational studies illustrate proposed approaches.

miR-23a Promotes the Transition from Indolent to Invasive Colorectal Cancer

Colorectal cancer is a classic example of a tumor that progresses through multiple distinct stages in its evolution. To understand the mechanisms regulating the transition from indolent to invasive disease, we profiled somatic copy number alterations in noninvasive adenomas and invasive adenocarcinomas from Apc and DNA mismatch repair (MMR) mutant mouse models. We identified a recurrent amplicon on mouse chromosome 8 that encodes microRNA (miRNA) 23a and -27a (miR). miR-23a and -27a levels are upregulated in mouse intestinal adenocarcinomas, primary tumors from patients with stage I/II colorectal cancers, as well as in human colorectal cancer cell lines and cancer stem cells. Functionally, miR-23a promotes the migration and invasion of colorectal cancer cells and stem cells, whereas miR-27a primarily promotes proliferation. We computationally and experimentally validated that metastasis suppressor 1 (MTSS1) is a direct miR-23a target and similarly validated that the ubiquitin ligase FBXW7 is a direct miR-27a target. Analyses of computationally predicted target genes in microarray data sets of patients with colorectal cancers are consistent with a role for miR-23a, but not miR-27a, specifically in invasive colorectal cancers.

Effects of Tobacco Smoke on Gene Expression and Cellular Pathways in a Cellular Model of Oral Leukoplakia

Abstract In addition to being causally linked to the formation of multiple tumor types, tobacco use has been associated with decreased efficacy of anticancer treatment and reduced survival time. A detailed understanding of the cellular mechanisms that are affected by tobacco smoke (TS) should facilitate the development of improved preventive and therapeutic strategies. We have investigated the effects of a TS extract on the transcriptome of MSK-Leuk1 cells, a cellular model of oral leukoplakia. Using Affymetrix HGU133 Plus 2 arrays, 411 differentially expressed probe sets were identified. The observed transcriptome changes were grouped according to functional information and translated into molecular interaction network maps and signaling pathways. Pathways related to cellular proliferation, inflammation, apoptosis, and tissue injury seemed to be perturbed. Analysis of networks connecting the affected genes identified specific modulated molecular interactions, hubs, and key transcription regulators. Thus, TS was found to induce several epidermal growth factor receptor (EGFR) ligands forming an EGFR-centered molecular interaction network, as well as several aryl hydrocarbon receptor–dependent genes, including the xenobiotic metabolizing enzymes CYP1A1 and CYP1B1. Notably, the latter findings in vitro are consistent with our parallel finding that CYP1A1 and CYP1B1 levels were increased in oral mucosa of smokers. Collectively, these results offer insights into the mechanisms underlying the procarcinogenic effects of TS and raise the possibility that inhibitors of EGFR or aryl hydrocarbon receptor signaling will prevent or delay the development of TS-related tumors. Moreover, the inductive effects of TS on xenobiotic metabolizing enzymes may help explain the reduced efficacy of chemotherapy, and suggest targets for chemopreventive agents in smokers.

Chemokine 25-induced signaling suppresses colon cancer invasion and metastasis.

Chemotactic cytokines (chemokines) can help regulate tumor cell invasion and metastasis. Here, we show that chemokine 25 (CCL25) and its cognate receptor chemokine receptor 9 (CCR9) inhibit colorectal cancer (CRC) invasion and metastasis. We found that CCR9 protein expression levels were highest in colon adenomas and progressively decreased in invasive and metastatic CRCs. CCR9 was expressed in both primary tumor cell cultures and colon-cancer-initiating cell (CCIC) lines derived from early-stage CRCs but not from metastatic CRC. CCL25 stimulated cell proliferation by activating AKT signaling. In vivo, systemically injected CCR9+ early-stage CCICs led to the formation of orthotopic gastrointestinal xenograft tumors. Blocking CCR9 signaling inhibited CRC tumor formation in the native gastrointestinal CCL25+ microenvironment, while increasing extraintestinal tumor incidence. NOTCH signaling, which promotes CRC metastasis, increased extraintestinal tumor frequency by stimulating CCR9 proteasomal degradation. Overall, these data indicate that CCL25 and CCR9 regulate CRC progression and invasion and further demonstrate an appropriate in vivo experimental system to study CRC progression in the native colon microenvironment.

miR-1269 promotes metastasis and forms a positive feedback loop with TGF-β

As patient survival drops precipitously from early-stage cancers to late-stage and metastatic cancers, microRNAs that promote relapse and metastasis can serve as prognostic and predictive markers as well as therapeutic targets for chemoprevention. Here we show that miR-1269a promotes colorectal cancer (CRC) metastasis and forms a positive feedback loop with TGF-β signaling. miR-1269a is upregulated in late-stage CRCs, and long-term monitoring of 100 stage II CRC patients revealed that miR-1269a expression in their surgically removed primary tumors is strongly associated with risk of CRC relapse and metastasis. Consistent with clinical observations, miR-1269a significantly increases the ability of CRC cells to invade and metastasize in vivo. TGF-β activates miR-1269 via Sox4, while miR-1269a enhances TGF-β signaling by targeting Smad7 and HOXD10, hence forming a positive feedback loop. Our findings suggest that miR-1269a is a potential marker to inform adjuvant chemotherapy decisions for CRC patients and a potential therapeutic target to deter metastasis.

Reactive distillation column design with vapor/liquid/liquid equilibria

This paper explores the design of reactive distillation columns with vapor/liquid/liquid equilibria. The number of phases and the phase equilibria on each tray are determined by minimizing the Gibbs free energy, allowing for a variable number of phases on each tray. The minimization problems are embedded within a larger problem that minimizes the annualized cost of the column, creating a bilevel optimization problem. A novel sequential approximation approach that can identify global solutions of the inner optimization problems is also introduced. The sequential approximation approach is employed to design reactive distillation and reactive flash processes.