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Item IDH-mutant glioma specific association of rs55705857 located at 8q24.21 involves MYC deregulation(NATURE PUBLISHING GROUP, 2016-01-01) Oktay, Yavuz; Ulgen, Ege; Can, Ozge; Akyerli, Cemaliye B.; Yuksel, Sirin; Erdemgil, Yigit; Durasi, I. Melis; Henegariu, Octavian Ioan; Nanni, E. Paolo; Selevsek, Nathalie; Grossmann, Jonas; Erson-Omay, E. Zeynep; Bai, Hanwen; Gupta, Manu; Lee, William; Turcan, Sevin; Ozpinar, Aysel; Huse, Jason T.; Sav, M. Aydin; Flanagan, Adrienne; Gunel, Murat; Sezerman, O. Ugur; Yakicier, M. Cengiz; Pamir, M. Necmettin; Ozduman, KorayThe single nucleotide polymorphism rs55705857, located in a non-coding but evolutionarily conserved region at 8q24.21, is strongly associated with IDH-mutant glioma development and was suggested to be a causal variant. However, the molecular mechanism underlying this association has remained unknown. With a case control study in 285 gliomas, 316 healthy controls, 380 systemic cancers, 31 other CNS-tumors, and 120 IDH-mutant cartilaginous tumors, we identified that the association was specific to IDH-mutant gliomas. Odds-ratios were 9.25 (5.17-16.52Item Comparison of endometrial prostanoid profiles in three infertile subgroups: the missing part of receptivity?(ELSEVIER SCIENCE INC, 2020-01-01) Keles, Irem Demiral; Ulgen, Ege; Erkan, Melike Belkiz; Celik, Saliha Esin; Aydin, Yasemin; Onem, Ayse Nur; Kandemir, Hulya; Arslanoglu, Tugce; Apak, Mustafa Resat; Sezerman, Ugur; Yeh, John; Buyru, Faruk; Bastu, ErcanObjective: To study the prostanoid profile of the endometria of patients with recurrent implantation failure (RIF), unexplained infertility (UIF), and recurrent miscarriages (RM), and to compare them with the endometria of healthy fertile controls. Design: Prospective cohort study. Setting: University hospital. Patient(s): Fifteen patients with RIF, 18 patients with UIF, 16 patients with RM, and 23 fertile controls were recruited. Intervention(s): Endometrial samples were taken during the window of implantation. After tissue homogenization and extraction, analysis with ultra-performance liquid chromatography diode array detector electrospray ionisation tandemmass spectrometrywas performed. Main Outcome Measures: Concentrations of prostaglandin (PG) D1, PGE1, PGF1 alpha, 6-ketoPGF1 alpha GD2, PGE2, PGF2 alpha, 15-deoxy-Delta 12,14-PGJ2, PGD3, PGE3, PGF3 alpha, thromboxane B2, 13,14-dihydro-PGE1, 13,14-dihydro-PGF1 alpha, 13,14-dihydro-PGF2 alpha, 13,14dihydro-15-keto-PGE1, 13,14-dihydro-15-keto-PGE2, and 13,14-dihydro-15-keto-PGF2 alpha were assessed. Result(s): Comparison of the endometria of patients with UIF and the controls showed no statistically significant differences. When the endometria of patients with RIF were compared with the controls, thromboxane B2 (TXB2) was found significantly higher (843.1 pg/mg vs. 133.5 pg/mg). When the endometria of patients with RM were compared with controls, 13,14-dihydro-15-keto PGF2 alpha and TXB2 were found significantly higher (3907.30 pg/mg vs. 17.80 pg/mg and 858.7 pg/mg vs. 133.5 pg/mg respectively). Conclusion(s): We identified increased endometrial presence of TXB2 in patients with RM and RIF, and 13,14-dihydro-15-keto PGF2 alpha in patients with RM. Although common ground is observed for RM and RIF, prostanoids, on the other hand, might make their own contribution to endometrial receptivity as important as genes and proteins. Attempts to normalize the prostaglandin profile of the endometrium via enzymatic activity can open new therapeutic options. (C) 2019 by American Society for Reproductive Medicine.Item Mutations and Copy Number Alterations in IDH Wild-Type Glioblastomas Are Shaped by Different Oncogenic Mechanisms(MDPI, 2020-01-01) Ulgen, Ege; Karacan, Sila; Gerlevik, Umut; Can, Ozge; Bilguvar, Kaya; Oktay, Yavuz; B. Akyerli, Cemaliye; K. Yuksel, Sirin; E. Danyeli, Ayca; Tihan, Tarik; Sezerman, O. Ugur; Yakicier, M. Cengiz; Pamir, M. Necmettin; Ozduman, KorayLittle is known about the mutational processes that shape the genetic landscape of gliomas. Numerous mutational processes leave marks on the genome in the form of mutations, copy number alterations, rearrangements or their combinations. To explore gliomagenesis, we hypothesized that gliomas with different underlying oncogenic mechanisms would have differences in the burden of various forms of these genomic alterations. This was an analysis on adult diffuse gliomas, but IDH-mutant gliomas as well as diffuse midline gliomas H3-K27M were excluded to search for the possible presence of new entities among the very heterogenous group of IDH-WT glioblastomas. The cohort was divided into two molecular subsets: (1) Molecularly-defined GBM (mGBM) as those that carried molecular features of glioblastomas (including TERT promoter mutations, 7/10 pattern, or EGFR-amplification), and (2) those who did not (others). Whole exome sequencing was performed for 37 primary tumors and matched blood samples as well as 8 recurrences. Single nucleotide variations (SNV), short insertion or deletions (indels) and copy number alterations (CNA) were quantified using 5 quantitative metrics (SNV burden, indel burden, copy number alteration frequency-wGII, chromosomal arm event ratio-CAER, copy number amplitude) as well as 4 parameters that explored underlying oncogenic mechanisms (chromothripsis, double minutes, microsatellite instability and mutational signatures). Findings were validated in the TCGA pan-glioma cohort. mGBM and ``Others{''} differed significantly in their SNV (only in the TCGA cohort) and CNA metrics but not indel burden. SNV burden increased with increasing age at diagnosis and at recurrences and was driven by mismatch repair deficiency. On the contrary, indel and CNA metrics remained stable over increasing age at diagnosis and with recurrences. Copy number alteration frequency (wGII) correlated significantly with chromothripsis while CAER and CN amplitude correlated significantly with the presence of double minutes, suggesting separate underlying mechanisms for different forms of CNA.Item Investigation of multiple sclerosis-related pathways through the integration of genomic and proteomic data(PEERJ INC, 2021-01-01) Everest, Elif; Ulgen, Ege; Uygunoglu, Ugur; Tutuncu, Melih; Saip, Sabahattin; Sezerman, Osman Ugur; Siva, Aksel; Turanli, Eda TahirBackground. Multiple sclerosis (MS) has a complex pathophysiology, variable clinical presentation, and unpredictable prognosisItem Sequential filtering for clinically relevant variants as a method for clinical interpretation of whole exome sequencing findings in glioma(BMC, 2021-01-01) Ulgen, Ege; Can, Ozge; Bilguvar, Kaya; Boylu, Cemaliye Akyerli; Yuksel, Sirin Kilicturgay; Danyeli, Ayca Ersen; Sezerman, O. Ugur; Yakicier, M. Cengiz; Pamir, M. Necmettin; Ozduman, KorayBackground In the clinical setting, workflows for analyzing individual genomics data should be both comprehensive and convenient for clinical interpretation. In an effort for comprehensiveness and practicality, we attempted to create a clinical individual whole exome sequencing (WES) analysis workflow, allowing identification of genomic alterations and presentation of neurooncologically-relevant findings. Methods The analysis workflow detects germline and somatic variants and presents: (1) germline variants, (2) somatic short variants, (3) tumor mutational burden (TMB), (4) microsatellite instability (MSI), (5) somatic copy number alterations (SCNA), (6) SCNA burden, (7) loss of heterozygosity, (8) genes with double-hit, (9) mutational signatures, and (10) pathway enrichment analyses. Using the workflow, 58 WES analyses from matched blood and tumor samples of 52 patients were analyzed: 47 primary and 11 recurrent diffuse gliomas. Results The median mean read depths were 199.88 for tumor and 110.955 for normal samples. For germline variants, a median of 22 (14-33) variants per patient was reported. There was a median of 6 (0-590) reported somatic short variants per tumor. A median of 19 (0-94) broad SCNAs and a median of 6 (0-12) gene-level SCNAs were reported per tumor. The gene with the most frequent somatic short variants was TP53 (41.38\%). The most frequent chromosome-/arm-level SCNA events were chr7 amplification, chr22q loss, and chr10 loss. TMB in primary gliomas were significantly lower than in recurrent tumors (p = 0.002). MSI incidence was low (6.9\%). Conclusions We demonstrate that WES can be practically and efficiently utilized for clinical analysis of individual brain tumors. The results display that NOTATES produces clinically relevant results in a concise but exhaustive manner.Item pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks(FRONTIERS MEDIA SA, 2019-01-01) Ulgen, Ege; Ozisik, Ozan; Sezerman, Osman UgurPathway analysis is often the first choice for studying the mechanisms underlying a phenotype. However, conventional methods for pathway analysis do not take into account complex protein-protein interaction information, resulting in incomplete conclusions. Previously, numerous approaches that utilize protein-protein interaction information to enhance pathway analysis yielded superior results compared to conventional methods. Hereby, we present pathfindR, another approach exploiting protein-protein interaction information and the first R package for active-subnetwork-oriented pathway enrichment analyses for class comparison omics experiments. Using the list of genes obtained from an omics experiment comparing two groups of samples, pathfindR identifies active subnetworks in a protein-protein interaction network. It then performs pathway enrichment analyses on these identified subnetworks. To further reduce the complexity, it provides functionality for clustering the resulting pathways. Moreover, through a scoring function, the overall activity of each pathway in each sample can be estimated. We illustrate the capabilities of our pathway analysis method on three gene expression datasets and compare our results with those obtained from three popular pathway analysis tools. The results demonstrate that literature-supported disease-related pathways ranked higher in our approach compared to the others. Moreover, pathfindR identified additional pathways relevant to the conditions that were not identified by other tools, including pathways named after the conditions.Item CogNet: classification of gene expression data based on ranked active-subnetwork- oriented KEGG pathway enrichment analysis(PEERJ INC, 2021-01-01) Yousef, Malik; Ulgen, Ege; Sezerman, Osman UgurMost of the traditional gene selection approaches are borrowed from other fields such as statistics and computer science, However, they do not prioritize biologically relevant genes since the ultimate goal is to determine features that optimize model performance metrics not to build a biologically meaningful model. Therefore, there is an imminent need for new computational tools that integrate the biological knowledge about the data in the process of gene selection and machine learning. Integrative gene selection enables incorporation of biological domain knowledge from external biological resources. In this study, we propose a new computational approach named CogNet that is an integrative gene selection tool that exploits biological knowledge for grouping the genes for the computational modeling tasks of ranking and classification. In CogNet, the pathfindR serves as the biological grouping tool to allow the main algorithm to rank active-subnetwork-oriented KEGG pathway enrichment analysis results to build a biologically relevant model. CogNet provides a list of significant KEGG pathways that can classify the data with a very high accuracy. The list also provides the genes belonging to these pathways that are differentially expressed that are used as features in the classification problem. The list facilitates deep analysis and better interpretability of the role of KEGG pathways in classification of the data thus better establishing the biological relevance of these differentially expressed genes. Even though the main aim of our study is not to improve the accuracy of any existing tool, the performance of the CogNet outperforms a similar approach called maTE while obtaining similar performance compared to other similar tools including SVM-RCE. CogNet was tested on 13 gene expression datasets concerning a variety of diseases.Item Correlation of anatomical involvement patterns of insular gliomas with subnetworks of the limbic system(AMER ASSOC NEUROLOGICAL SURGEONS, 2022-01-01) Ulgen, Ege; Aras, Fuat Kaan; Cosgun, Erdal; Ersen-Danyeli, Ayca; Dincer, Alp; Usseli, M. Imre; Ozduman, Koray; Pamir, M. NecmettinOBJECTIVE Gliomas frequently involve the insula both primarily and secondarily by invasion. Despite the high connectivity of the human insula, gliomas do not spread randomly to or from the insula but follow stereotypical anatomical involvement patterns. In the majority of cases, these patterns correspond to the intrinsic connectivity of the limbic system, except for tumors with aggressive biology. On the basis of these observations, the authors hypothesized that these different involvement patterns may be correlated with distinct outcomes and analyzed these correlations in an institutional cohort. METHODS Fifty-nine patients who had undergone surgery for insular diffuse gliomas and had complete demographic, pre- and postoperative imaging, pathology, molecular genetics, and clinical follow-up data were included in the analysis (median age 37 years, range 21-71 years, M/F ratio 1.68). Patients with gliomatosis and those with only minor involvement of the insula were excluded. The presence of T2-hyperintense tumor infiltration was evaluated in 12 anatomical structures. Hierarchical biclustering was used to identify co-involved structures, and the findings were correlated with established functional anatomy knowledge. Overall survival was evaluated using Kaplan-Meier and Cox proportional hazards regression analysis (17 parameters). RESULTS The tumors involved the anterior insula (98.3\%), posterior insula (67.8\%), temporal operculum (47.5\%), amygdala (42.4\%), frontal operculum (40.7\%), temporal pole (39\%), parolfactory area (35.6\%), hypothalamus (23.7\%), hippocampus (16.9\%), thalamus (6.8\%), striatum (5.1\%), and cingulate gyrus (3.4\%). A mean 4.2 +/- 2.6 structures were involved. On the basis of hierarchical biclustering, 7 involvement patterns were identified and correlated with cortical functional anatomy (pure insular {[}11.9\%], olfactocentric {[}15.3\%], olfactoopercular {[}33.9\%], operculoinsular {[}15.3\%], striatoinsular {[}3.4\%], translimbic {[}11.9\%], and multifocal {[}8.5\%] patterns). Cox regression identified hippocampal involvement (p = 0.006) and postoperative tumor volume (p = 0.027) as significant negative independent prognosticators of overall survival and extent of resection (p = 0.015) as a significant positive independent prognosticator. CONCLUSIONS The study findings indicate that insular gliomas primarily involve the olfactocentric limbic girdle and that involvement in the hippocampocentric limbic girdle is associated with a worse prognosis.Item driveR: a novel method for prioritizing cancer driver genes using somatic genomics data(BMC, 2021-01-01) Ulgen, Ege; Sezerman, O. UgurBackground: Cancer develops due to ``driver{''} alterations. Numerous approaches exist for predicting cancer drivers from cohort-scale genomics data. However, methods for personalized analysis of driver genes are underdeveloped. In this study, we developed a novel personalized/batch analysis approach for driver gene prioritization utilizing somatic genomics data, called driveR. Results: Combining genomics information and prior biological knowledge, driveR accurately prioritizes cancer driver genes via a multi-task learning model. Testing on 28 different datasets, this study demonstrates that driveR performs adequately, achieving a median AUC of 0.684 (range 0.651-0.861) on the 28 batch analysis test datasets, and a median AUC of 0.773 (range 0-1) on the 5157 personalized analysis test samples. Moreover, it outperforms existing approaches, achieving a significantly higher median AUC than all of MutSigCV (Wilcoxon rank-sum test p < 0.001), DriverNet (p < 0.001), OncodriveFML (p < 0.001) and MutPanning (p < 0.001) on batch analysis test datasets, and a significantly higher median AUC than DawnRank (p < 0.001) and PRODIGY (p < 0.001) on personalized analysis datasets. Conclusions: This study demonstrates that the proposed method is an accurate and easy-to-utilize approach for prioritizing driver genes in cancer genomes in personalized or batch analyses. driveR is available on CRAN: https://cran.r-project.org/package=driveR.