Negative Breast Cancer Patients Without Germline BRCA1/2 Mutation
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Integrative Genomic and Epigenomic Analyses Identified IRAK1 As a Novel Target for Chronic Inflammation-Driven Prostate Tumorigenesis
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.16.447920; this version posted June 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Integrative genomic and epigenomic analyses identified IRAK1 as a novel target for chronic inflammation-driven prostate tumorigenesis Saheed Oluwasina Oseni1,*, Olayinka Adebayo2, Adeyinka Adebayo3, Alexander Kwakye4, Mirjana Pavlovic5, Waseem Asghar5, James Hartmann1, Gregg B. Fields6, and James Kumi-Diaka1 Affiliations 1 Department of Biological Sciences, Florida Atlantic University, Florida, USA 2 Morehouse School of Medicine, Atlanta, Georgia, USA 3 Georgia Institute of Technology, Atlanta, Georgia, USA 4 College of Medicine, Florida Atlantic University, Florida, USA 5 Department of Computer and Electrical Engineering, Florida Atlantic University, Florida, USA 6 Department of Chemistry & Biochemistry and I-HEALTH, Florida Atlantic University, Florida, USA Corresponding Author: [email protected] (S.O.O) Running Title: Chronic inflammation signaling in prostate tumorigenesis bioRxiv preprint doi: https://doi.org/10.1101/2021.06.16.447920; this version posted June 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract The impacts of many inflammatory genes in prostate tumorigenesis remain understudied despite the increasing evidence that associates chronic inflammation with prostate cancer (PCa) initiation, progression, and therapy resistance. -
Targeting Non-Oncogene Addiction for Cancer Therapy
biomolecules Review Targeting Non-Oncogene Addiction for Cancer Therapy Hae Ryung Chang 1,*,†, Eunyoung Jung 1,†, Soobin Cho 1, Young-Jun Jeon 2 and Yonghwan Kim 1,* 1 Department of Biological Sciences and Research Institute of Women’s Health, Sookmyung Women’s University, Seoul 04310, Korea; [email protected] (E.J.); [email protected] (S.C.) 2 Department of Integrative Biotechnology, Sungkyunkwan University, Suwon 16419, Korea; [email protected] * Correspondence: [email protected] (H.R.C.); [email protected] (Y.K.); Tel.: +82-2-710-9552 (H.R.C.); +82-2-710-9552 (Y.K.) † These authors contributed equally. Abstract: While Next-Generation Sequencing (NGS) and technological advances have been useful in identifying genetic profiles of tumorigenesis, novel target proteins and various clinical biomarkers, cancer continues to be a major global health threat. DNA replication, DNA damage response (DDR) and repair, and cell cycle regulation continue to be essential systems in targeted cancer therapies. Although many genes involved in DDR are known to be tumor suppressor genes, cancer cells are often dependent and addicted to these genes, making them excellent therapeutic targets. In this review, genes implicated in DNA replication, DDR, DNA repair, cell cycle regulation are discussed with reference to peptide or small molecule inhibitors which may prove therapeutic in cancer patients. Additionally, the potential of utilizing novel synthetic lethal genes in these pathways is examined, providing possible new targets for future therapeutics. Specifically, we evaluate the potential of TONSL as a novel gene for targeted therapy. Although it is a scaffold protein with no known enzymatic activity, the strategy used for developing PCNA inhibitors can also be utilized to target TONSL. -
Plenary and Platform Abstracts
American Society of Human Genetics 68th Annual Meeting PLENARY AND PLATFORM ABSTRACTS Abstract #'s Tuesday, October 16, 5:30-6:50 pm: 4. Featured Plenary Abstract Session I Hall C #1-#4 Wednesday, October 17, 9:00-10:00 am, Concurrent Platform Session A: 6. Variant Insights from Large Population Datasets Ballroom 20A #5-#8 7. GWAS in Combined Cancer Phenotypes Ballroom 20BC #9-#12 8. Genome-wide Epigenomics and Non-coding Variants Ballroom 20D #13-#16 9. Clonal Mosaicism in Cancer, Alzheimer's Disease, and Healthy Room 6A #17-#20 Tissue 10. Genetics of Behavioral Traits and Diseases Room 6B #21-#24 11. New Frontiers in Computational Genomics Room 6C #25-#28 12. Bone and Muscle: Identifying Causal Genes Room 6D #29-#32 13. Precision Medicine Initiatives: Outcomes and Lessons Learned Room 6E #33-#36 14. Environmental Exposures in Human Traits Room 6F #37-#40 Wednesday, October 17, 4:15-5:45 pm, Concurrent Platform Session B: 24. Variant Interpretation Practices and Resources Ballroom 20A #41-#46 25. Integrated Variant Analysis in Cancer Genomics Ballroom 20BC #47-#52 26. Gene Discovery and Functional Models of Neurological Disorders Ballroom 20D #53-#58 27. Whole Exome and Whole Genome Associations Room 6A #59-#64 28. Sequencing-based Diagnostics for Newborns and Infants Room 6B #65-#70 29. Omics Studies in Alzheimer's Disease Room 6C #71-#76 30. Cardiac, Valvular, and Vascular Disorders Room 6D #77-#82 31. Natural Selection and Human Phenotypes Room 6E #83-#88 32. Genetics of Cardiometabolic Traits Room 6F #89-#94 Wednesday, October 17, 6:00-7:00 pm, Concurrent Platform Session C: 33. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Systematic Screening Reveals a Role for BRCA1 in the Response to Transcription-Associated DNA Damage
Downloaded from genesdev.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press RESOURCE/METHODOLOGY Systematic screening reveals a role for BRCA1 in the response to transcription-associated DNA damage Sarah J. Hill,1,2 Thomas Rolland,1,2,3 Guillaume Adelmant,1,4,5 Xianfang Xia,1,2,3 Matthew S. Owen,1,2,3 Amelie Dricot,1,2,3 Travis I. Zack,1,6 Nidhi Sahni,1,2,3 Yves Jacob,1,2,3,7,8,9 Tong Hao,1,2,3 Kristine M. McKinney,1,2 Allison P. Clark,1,2 Deepak Reyon,10,11,12 Shengdar Q. Tsai,10,11,12 J. Keith Joung,10,11,12 Rameen Beroukhim,1,6,13 Jarrod A. Marto,1,4,5 Marc Vidal,1,2,3 Suzanne Gaudet,1,2,3 David E. Hill,1,2,3,14 and David M. Livingston1,2,14 1Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; 2Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA; 3Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; 4Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA; 5Blais Proteomics Center, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; 6The Broad Institute, Cambridge, Massachusetts 02142, USA; 7Departement de Virologie, Unite de Gen etique Moleculaire des Virus a ARN, Institut Pasteur, F-75015 Paris, France; 8UMR3569, Centre National de la Recherche Scientifique, F-75015 Paris, France; 9UnitedeG en etique Moleculaire des Virus a ARN, Universite Paris Diderot, F-75015 Paris, France; 10Molecular Pathology Unit, Center for Computational and Integrative Biology, 11Center for Cancer Research, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA; 12Department of Pathology, Harvard Medical School, Boston, Massachusetts 02115, USA; 13Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA BRCA1 is a breast and ovarian tumor suppressor. -
Lncrna TONSL-AS1 Regulates Mir-490-3P/CDK1 to Affect Ovarian
Liu et al. Journal of Ovarian Research (2020) 13:60 https://doi.org/10.1186/s13048-020-00657-0 RESEARCH Open Access LncRNA TONSL-AS1 regulates miR-490-3p/ CDK1 to affect ovarian epithelial carcinoma cell proliferation Yan Liu1†, Ling Li1†, Xiangyang Wang2, Ping Wang1 and Zhongxian Wang1* Abstract Background: LncRNA TONSL-AS1 has been characterized as a critical player in gastric cancer. By analyze the TCGA dataset, we observed the upregulation of TONSL-AS1 in ovarian epithelial carcinoma (EOC). We therefore investigated the involvement of TONSL-AS1 in EOC. Methods: The differential expression of TONSL-AS1 in EOC was first explored by analyzing the TCGA dataset. The effects of overexpression of TONSL-AS1 and miR-490-3p on the expression of CDK1 mRNA and protein in OVCAR3 cells were evaluated by qPCR and western blot, respectively. CCK-8 assay was performed to investigate the effects of overexpression of TONSL-AS1, miR-490-3p and CDK1 on proliferation of OVCAR3 cells. Results: We observed that TONSL-AS1 was upregulated in EOC tumor tissues from EOC patients, and its high expression level was correlated with poor survival. Dual luciferase assay and RNA interaction prediction showed the direct interaction between TONSL-AS1 and miR-490-3p. However, overexpression of miR-490-3p did not affect the expression of TONSL- AS1. Instead, overexpression of TONSL-AS1 resulted in the upregulation of CDK1, a target of miR-490-3p, in EOC cells. Overexpression of TONSL-AS1 and CDK1 resulted in increased proliferation rate of EOC cells. Overexpression of miR-490- 3p played an opposite role and reduced the effects of overexpression of TONSL -AS1 and CDK1. -
Mining Novel Candidate Imprinted Genes Using Genome-Wide Methylation Screening and Literature Review
epigenomes Article Mining Novel Candidate Imprinted Genes Using Genome-Wide Methylation Screening and Literature Review Adriano Bonaldi 1, André Kashiwabara 2, Érica S. de Araújo 3, Lygia V. Pereira 1, Alexandre R. Paschoal 2 ID , Mayra B. Andozia 1, Darine Villela 1, Maria P. Rivas 1 ID , Claudia K. Suemoto 4,5, Carlos A. Pasqualucci 5,6, Lea T. Grinberg 5,7, Helena Brentani 8 ID , Silvya S. Maria-Engler 9, Dirce M. Carraro 3, Angela M. Vianna-Morgante 1, Carla Rosenberg 1, Luciana R. Vasques 1,† and Ana Krepischi 1,*,† ID 1 Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, Rua do Matão 277, 05508-090 São Paulo, SP, Brazil; [email protected] (A.B.); [email protected] (L.V.P.); [email protected] (M.B.A.); [email protected] (D.V.); [email protected] (M.P.R.); [email protected] (A.M.V.-M.); [email protected] (C.R.); [email protected] (L.R.V.) 2 Department of Computation, Federal University of Technology-Paraná, Avenida Alberto Carazzai, 1640, 86300-000 Cornélio Procópio, PR, Brazil; [email protected] (A.K.); [email protected] (A.R.P.) 3 International Center for Research, A. C. Camargo Cancer Center, Rua Taguá, 440, 01508-010 São Paulo, SP, Brazil; [email protected] (É.S.d.A.); [email protected] (D.M.C.) 4 Division of Geriatrics, University of São Paulo Medical School, Av. Dr. Arnaldo, 455, 01246-903 São Paulo, SP, Brazil; [email protected] 5 Brazilian Aging Brain Study Group-LIM22, Department of Pathology, University of São Paulo Medical School, Av. -
Bi-Allelic Variants in TONSL Cause SPONASTRIME Dysplasia and a Spectrum of Skeletal Dysplasia Phenotypes
This is a repository copy of Bi-allelic variants in TONSL cause SPONASTRIME dysplasia and a spectrum of skeletal dysplasia phenotypes. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/142839/ Version: Accepted Version Article: Burrage, L.C., Reynolds, J.J., Baratang, N.V. et al. (57 more authors) (2019) Bi-allelic variants in TONSL cause SPONASTRIME dysplasia and a spectrum of skeletal dysplasia phenotypes. American Journal of Human Genetics. ISSN 0002-9297 https://doi.org/10.1016/j.ajhg.2019.01.007 Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). Reuse This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can’t change the article in any way or use it commercially. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ Biallelic Variants in TONSL Cause SPONASTRIME Dysplasia and a Spectrum of Skeletal Dysplasia Phenotypes Lindsay C. Burrage,1,2, 38 John J. Reynolds,3,38 Nissan Vida Baratang,4 Jennifer B. Phillips,5 Jeremy Wegner,5 Ashley McFarquhar,4 Martin R. -
Shinydepmap, a Tool to Identify Targetable Cancer Genes and Their Functional Connections from Cancer Dependency Map Data
TOOLS AND RESOURCES shinyDepMap, a tool to identify targetable cancer genes and their functional connections from Cancer Dependency Map data Kenichi Shimada*, John A Bachman, Jeremy L Muhlich, Timothy J Mitchison Laboratory of Systems Pharmacology and Department of Systems Biology, Harvard Medical School, Boston, United States Abstract Individual cancers rely on distinct essential genes for their survival. The Cancer Dependency Map (DepMap) is an ongoing project to uncover these gene dependencies in hundreds of cancer cell lines. To make this drug discovery resource more accessible to the scientific community, we built an easy-to-use browser, shinyDepMap (https://labsyspharm.shinyapps.io/ depmap). shinyDepMap combines CRISPR and shRNA data to determine, for each gene, the growth reduction caused by knockout/knockdown and the selectivity of this effect across cell lines. The tool also clusters genes with similar dependencies, revealing functional relationships. shinyDepMap can be used to (1) predict the efficacy and selectivity of drugs targeting particular genes; (2) identify maximally sensitive cell lines for testing a drug; (3) target hop, that is, navigate from an undruggable protein with the desired selectivity profile, such as an activated oncogene, to more druggable targets with a similar profile; and (4) identify novel pathways driving cancer cell growth and survival. *For correspondence: [email protected]. Introduction edu Cancer is a disease of the genome. Hundreds, if not thousands, of driver mutations cause cancer in different patients (MC3 Working Group et al., 2018), and extensive collaborative efforts such as Competing interest: See the Cancer Genome Atlas Program (TCGA) have helped discover them (The Cancer Genome Atlas page 17 Research Network, 2019). -
A Sparse and Low-Rank Regression Model for Identifying The
G C A T T A C G G C A T genes Article A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis Yishu Wang 1,*, Lingyun Xu 2 and Dongmei Ai 1,3,* 1 School of Mathematics and Physics, University of Science & Technology Beijing, Beijing 100083, China 2 School of Mathematics and Statistics, Qingdao University, Qingdao 266003, China; [email protected] 3 Basic Experimental Center of Natural Science, University of Science and Technology Beijing, Beijing 100083, China * Correspondence: [email protected] (Y.W.); [email protected] (D.A.); Tel.: 010-62332349 (Y.W.) Abstract: DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low- rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a Citation: Wang, Y.; Xu, L.; Ai, D. -
Downloaded Expression Data and Experimental Design Meta Data from GEO
META-ANALYSIS OF GENE EXPRESSION IN MOUSE MODELS OF NEURODEGENERATIVE DISORDERS by Cuili Zhuang B.Sc. Biology, The University of British Columbia, 2009 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Bioinformatics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2017 © Cuili Zhuang, 2017 Abstract There is intense interest in understanding the molecular mechanisms that contribute to neurodegenerative disorders (NDs), which involve complex interplays of genetic and environmental factors. To catch early events involved in disease initiation requires investigation on pre-symptomatic brain samples. It is difficult to capture early molecular events using post- mortem human brain samples since these samples represent the late phase of the disorder with progressive brain damage and neurodegeneration. Disease mouse models are developed to study disease progression and pathophysiology. Here, I focus on two of the most studied NDs: Alzheimer’s disease (AD) and Huntington’s disease (HD). Mouse models developed for the disease (AD or HD) often share similar phenotypes mimicking human disease symptoms, which suggest potential common underlying mechanisms of disease initiation and progression across mouse models of the same disease. Investigation of gene expression profiles of pre-symptomatic animals from different mouse models may shed light on the mechanisms occurred in the early disease phase. Gene expression profiling analyses have been performed on mouse models and some of the studies investigate the molecular changes in pre-symptomatic phase of AD and HD respectively. However, their findings have not reached a clear consensus. To identify shared molecular changes across mouse models, I conducted a systematic meta-analysis of gene expression in mouse models of AD and HD, consisted of 369 gene expression profiles from 23 independent studies. -
Identi Cation of Potential Pathogenic Genes Causing Occipitalization Of
Identication of potential pathogenic genes causing occipitalization of the atlas Shanhang Jia Xuan Wu Hospital of the Capital Medical University Wanru Duan Xuan Wu Hospital of the Capital Medical University Zong Xin Xuan Wu Hospital of the Capital Medical University Boyan Zhang Xuan Wu Hospital of the Capital Medical University Qiang Jian Xuan Wu Hospital of the Capital Medical University Chen Wei Beihang University Zan Chen ( [email protected] ) Xuan Wu Hospital of the Capital Medical University Research Article Keywords: Occipilatization of the atlas, Whole-exome sequencing, Pathogenic gene, GO-BP, KEGG, Fanconi anemia Posted Date: February 26th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-244773/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/12 Abstract Background Occipitalization of the atlas (AO) is among the most common congenital or environmental malformations of the craniovertebral region, the rate of incidence of which ranges from 0.08%-2.76% in the general population. The fundamental pathogenic mechanisms and molecular etiology remain largely unknown.. Results Rare variants were detected in two genes (MEOX1 and MYO18B) with reported association with vertebral malformations, especially in AO. Through the use of a functional prediction tool, Meta-SVM, and genotype-phenotype analysis of 101 candidate genes related to vertebral segmentation abnormalities, TNS1 was identied as having the greatest probability of being associated with AO, followed by FGFR2, AGAP1, TBX2, LRP5, and TONSL. GO-BP and KEGG analyses were then performed on the candidate genes, the results indicating that Fanconi anemia-related genes may drive vertebral malformation in AO patients.