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21 Publications visible to you, out of a total of 21

Abstract (Expand)

Mutations in the BRCA1 and BRCA2 genes are known risk factors and drivers of breast and ovarian cancers. So far, few studies have been focused on understanding the differences in transcriptome andd functional landscapes associated with the disease (breast vs. ovarian cancers), gene (BRCA1 vs. BRCA2), and mutation type (germline vs. somatic). In this study, we were aimed at systemic evaluation of the association of BRCA1 and BRCA2 germline and somatic mutations with gene expression, disease clinical features, outcome, and treatment. We performed BRCA1/2 mutation centered RNA-seq data analysis of breast and ovarian cancers from the TCGA repository using transcriptome and phenotype “portrayal” with multi-layer self-organizing maps and functional annotation. The results revealed considerable differences in BRCA1- and BRCA2-dependent transcriptome landscapes in the studied cancers. Furthermore, our data indicated that somatic and germline mutations for both genes are characterized by deregulation of different biological functions and differential associations with phenotype characteristics and poly(ADP-ribose) polymerase (PARP)-inhibitor gene signatures. Overall, this study demonstrates considerable variation in transcriptomic landscapes of breast and ovarian cancers associated with the affected gene (BRCA1 vs. BRCA2), as well as the mutation type (somatic vs. germline). These results warrant further investigations with larger groups of mutation carriers aimed at refining the understanding of molecular mechanisms of breast and ovarian cancers.

Authors: Arsen Arakelyan, Ani Melkonyan, Siras Hakobyan, Uljana Boyarskih, Arman Simonyan, Lilit Nersisyan, Maria Nikoghosyan, Maxim Filipenko, Hans Binder

Date Published: 28th Jan 2021

Publication Type: Journal

Abstract (Expand)

Background: The blood transcriptome is expected to provide a detailed picture of an organism's physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research. We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration. Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features. Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes. Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications. Keywords: age; gene expression; immune response; lifestyle and obesity; omics and phenotype integration; self-organizing maps; subtypes. Copyright © 2020 Schmidt, Hopp, Arakelyan, Kirsten, Engel, Wirkner, Krohn, Burkhardt, Thiery, Loeffler, Loeffler-Wirth and Binder.

Authors: Maria Schmidt, Lydia Hopp, Arsen Arakelyan, Holger Kirsten, Christoph Engel, Kerstin Wirkner, Knut Krohn, Ralph Burkhardt, Joachim Thiery, Markus Loeffler, Henry Loeffler-Wirth, Hans Binder

Date Published: 30th Oct 2020

Publication Type: Journal

Abstract (Expand)

Objective: Mutations in TP53 lead to loss of function (LOF) or gain of function (GOF) of the corresponding protein p53 and produce a different effect on the tumor. Our goal was to determine the spectrum of somatic TP53 variants in BRCA1/2 associated high-grade serous ovarian cancer (HGSOC). Methods: The population under study comprised of HGSOCs with pathogenic variants in BRCA1 (n = 78) or BRCA2 (n = 21). Only chemo-naive and platinum-sensitive patients were included in this study. The case group of the IARC database (n = 1249) with HGSOC not stratified by BRCA status was used as a reference. A custom NGS panel was used for sequencing TP53 and mutational hot-spots of other genes, and p53 expression was evaluated by immunohistochemistry for 68 cases of HGSOCs. Results: Somatic TP53 variants (95) or inhibition of wild-type p53 expression (3) were observed in 98 cases. The sample with normal p53 had CDKNA1 variants. The frequency of truncating variants was significantly higher than in the reference cohort (30.3 vs. 21.0%, p = 0.01). Most of the samples (41/68) demonstrated low (or absent) expression of p53, and 17 samples overexpressed p53. LOH was typical for TP53 nonsense variants (14/15). In total, 68/95 samples were LOH positive and showed LOH in all tumorous cells, thus indicating the driver effect of TP53 mutations. Three specimens had KRAS, BAX, APC, and CTNNB1 subclones variants. Conclusion: High frequency of TP53 truncating variants, the low expression of mutant p53, and low incidence of oncogene mutations show potential GOF properties of p53 to be poorly represented in BRCA1/2 associated HGSOC. Keywords: BRCA1/2 carriers; TP53 somatic mutations; gain of function; loss of function; ovarian cancer; p53 expression.

Authors: Ulyana A. Boyarskikh, L. F. Gulyaeva, A. M. Avdalyan, A. A. Kechin, E. A. Khrapov, D. G. Lazareva, N. E. Kushlinskii, A. Melkonyan, A. Arakelyan, Maxim Leonidovich Filipenko

Date Published: 16th Jul 2020

Publication Type: Journal

Abstract (Expand)

Telomere length (TL) regulation is an important factor in ageing, reproduction and cancer development. Genetic, hereditary and environmental factors regulating TL are currently widely investigated, however, their relative contribution to TL variability is still understudied. We have used whole genome sequencing data of 250 family trios from the Genome of the Netherlands project to perform computational measurement of TL and a series of regression and genome-wide association analyses to reveal TL inheritance patterns and associated genetic factors. Our results confirm that TL is a largely heritable trait, primarily with mother's, and, to a lesser extent, with father's TL having the strongest influence on the offspring. In this cohort, mother's, but not father's age at conception was positively linked to offspring TL. Age-related TL attrition of 40 bp/year had relatively small influence on TL variability. Finally, we have identified TL-associated variations in ribonuclease reductase catalytic subunit M1 (RRM1 gene), which is known to regulate telomere maintenance in yeast. We also highlight the importance of multivariate approach and the limitations of existing tools for the analysis of TL as a polygenic heritable quantitative trait.

Authors: Lilit Nersisyan, Maria Nikoghosyan, Laurent C. Francioli, Androniki Menelaou, Sara L. Pulit, Clara C. Elbers, Wigard P. Kloosterman, Jessica van Setten, Isaäc J. Nijman, Ivo Renkens, Paul I. W. de Bakker, Freerk van Dijk, Pieter B. T. Neerincx, Patrick Deelen, Alexandros Kanterakis, Martijn Dijkstra, Heorhiy Byelas, K. Joeri van der Velde, Mathieu Platteel, Morris A. Swertz, Cisca Wijmenga, Pier Francesco Palamara, Itsik Pe’er, Kai Ye, Eric-Wubbo Lameijer, Matthijs H. Moed, Marian Beekman, Anton J. M. de Craen, H. Eka D. Suchiman, P. Eline Slagboom, Victor Guryev, Abdel Abdellaoui, Jouke Jan Hottenga, Mathijs Kattenberg, Gonneke Willemsen, Dorret I. Boomsma, Elisabeth M. van Leeuwen, Lennart C. Karssen, Najaf Amin, Fernando Rivadeneira, Aaron Isaacs, Albert Hofman, André G. Uitterlinden, Cornelia M. van Duijn, Mannis van Oven, Manfred Kayser, Martijn Vermaat, Jeroen F. J. Laros, Johan T. den Dunnen, David van Enckevort, Hailiang Mei, Mingkun Li, Mark Stoneking, Barbera D. C. van Schaik, Jan Bot, Tobias Marschall, Alexander Schönhuth, Jayne Y. Hehir-Kwa, Robert E. Handsaker, Paz Polak, Mashaal Sohail, Dana Vuzman, Karol Estrada, Steven A. McCarroll, Shamil R. Sunyaev, Fereydoun Hormozdiari, Vyacheslav Koval, Carolina Medina-Gomez, Ben Oostra, Jan H. Veldink, Leonard H. van den Berg, Steven J. Pitts, Shobha Potluri, Purnima Sundar, David R. Cox, Peter de Knijff, Qibin Li, Yingrui Li, Yuanping Du, Ruoyan Chen, Hongzhi Cao, Jun Wang, Ning Li, Sujie Cao, Jasper A. Bovenberg, Gert-Jan B. van Ommen, Arsen Arakelyan

Date Published: 10th Dec 2019

Publication Type: Journal

Abstract (Expand)

Background: Activation of telomere maintenance mechanisms (TMMs) is a hallmark of most cancers, and is required to prevent genome instability and to establish cellular immortality through reconstitution of capping of chromosome ends. TMM depends on the cancer type. Comparative studies linking tumor biology and TMM have potential impact for evaluating cancer onset and development. Methods: We have studied alterations of telomere length, their sequence composition and transcriptional regulation in mismatch repair deficient colorectal cancers arising in Lynch syndrome (LS-CRC) and microsatellite instable (MSI) sporadic CRC (MSI s-CRC), and for comparison, in microsatellite stable (MSS) s-CRC and in benign colon mucosa. Our study applied bioinformatics analysis of whole genome DNA and RNA sequencing data and a pathway model to study telomere length alterations and the potential effect of the "classical" telomerase (TEL-) and alternative (ALT-) TMM using transcriptomic signatures. Results: We have found progressive decrease of mean telomere length in all cancer subtypes compared with reference systems. Our results support the view that telomere attrition is an early event in tumorigenesis. TMM gets activated in all tumors studied due to concerted overexpression of a large fraction of genes with direct relation to telomere function, where only a very small fraction of them showed recurrent mutations. TEL-related transcriptional state was dominating in all CRC subtypes, showing, however, subtype-specific activation patterns; while contribution of the ALT-TMM was slightly more prominent in the hypermutated MSI s-CRC and LS-CRC. TEL-TMM is mainly activated by over-expression of DKC1 and/or TERT genes and their interaction partners, where DKC1 is more prominent in MSS than in MSI s-CRC and can serve as a transcriptomic marker of TMM activity. Conclusions: Our results suggest that transcriptional patterns are indicative for TMM pathway activation with subtle differences between TEL and ALT mechanisms in a CRC subtype-specific fashion. Sequencing data potentially provide a suited measure to study alterations of telomere length and of underlying transcriptional regulation. Further studies are needed to improve this method. Keywords: DNAseq and RNAseq data analysis; colorectal cancer; mismatch repair; pathway models; telomerase and alternative telomere maintenance; telomere attrition; telomere length; telomere repeat variants.

Authors: Lilit Nersisyan, Lydia Hopp, Henry Loeffler-Wirth, Jörg Galle, Markus Loeffler, Arsen Arakelyan, Hans Binder

Date Published: 5th Nov 2019

Publication Type: Journal

Abstract (Expand)

Background: Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt's lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma. Methods: We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics. Results: We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt's lymphoma and particularly on 'double-hit' MYC and BCL2 transformed lymphomas. Conclusions: The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities. Keywords: B cell malignancies; Gene regulation; Machine learning; Molecular subtypes; Tumor heterogeneity.

Authors: Henry Loeffler-Wirth, Markus Kreuz, Lydia Hopp, Arsen Arakelyan, Andrea Haake, Sergio B. Cogliatti, Alfred C. Feller, Martin-Leo Hansmann, Dido Lenze, Peter Möller, Hans Konrad Müller-Hermelink, Erik Fortenbacher, Edith Willscher, German Ott, Andreas Rosenwald, Christiane Pott, Carsten Schwaenen, Heiko Trautmann, Swen Wessendorf, Harald Stein, Monika Szczepanowski, Lorenz Trümper, Michael Hummel, Wolfram Klapper, Reiner Siebert, Markus Loeffler, Hans Binder

Date Published: 30th Apr 2019

Publication Type: Journal

Abstract (Expand)

Background. Breast cancer is one of the most common cancers in women worldwide. The germline mutations of the BRCA1 and BRCA2 genes are the most significant and well characterized genetic risk factors for hereditary breast cancer. Intensive research in the last decades has demonstrated that the incidence of mutations varies widely among different populations. In this study we attempted to perform a pilot study for identification and characterization of mutations in BRCA1 and BRCA2 genes among Armenian patients with family history of breast cancer and their healthy relatives. Methods. We performed targeted exome sequencing for BRCA1 and BRCA2 genes in 6 patients and their healthy relatives. After alignment of short reads to the reference genome, germline single nucleotide variation and indel discovery was performed using GATK software. Functional implications of identified variants were assessed using ENSEMBL Variant Effect Predictor tool. Results. In total, 39 single nucleotide variations and 4 indels were identified, from which 15 SNPs and 3 indels were novel. No known pathogenic mutations were identified, but 2 SNPs causing missense amino acid mutations had significantly increased frequencies in the study group compared to the 1000 Genome populations. Conclusions. Our results demonstrate the importance of screening of BRCA1 and BRCA2 gene variants in the Armenian population in order to identity specifics of mutation spectrum and frequencies and enable accurate risk assessment of hereditary breast cancers. Keywords: BRCA1; BRCA2; breast cancer; mutation screening; targeted exome sequencing.

Authors: Sofi Atshemyan, Andranik Chavushyan, Nerses Berberian, Arthur Sahakyan, Roksana Zakharyan, Arsen Arakelyan

Date Published: 10th Jan 2017

Publication Type: Journal

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