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Integrative Analysis of Exogenous, Endogenous, Tumour and Immune
Gut Online First, published on February 6, 2018 as 10.1136/gutjnl-2017-315537 Recent advances in basic science Integrative analysis of exogenous, endogenous, Gut: first published as 10.1136/gutjnl-2017-315537 on 6 February 2018. Downloaded from tumour and immune factors for precision medicine Shuji Ogino,1,2,3,4 Jonathan A Nowak,1 Tsuyoshi Hamada,2 Amanda I Phipps,5,6 Ulrike Peters,5,6 Danny A Milner Jr,7 Edward L Giovannucci,3,8,9 Reiko Nishihara,1,3,4,8,10 Marios Giannakis,4,11,12 Wendy S Garrett,4,11,13 Mingyang Song8,14,15 For numbered affiliations see ABSTRACT including inflammatory and immune cells. A fraction end of article. Immunotherapy strategies targeting immune checkpoints of somatic mutations may result in the generation of such as the CTLA4 and CD274 (programmed cell death new antigens (neoantigens) that can be recognised as Correspondence to 1 ligand 1, PD-L1)/PDCD1 (programmed cell death 1, non-self by the immune system. During an individu- Dr Shuji Ogino, Program in MPE Molecular Pathological PD-1) T-cell coreceptor pathways are revolutionising al's life-course, cells may acquire somatic molecular Epidemiology, Brigham and oncology. The approval of pembrolizumab use for alterations, and some of these cells undergo clonal Women’s Hospital, Boston, MA solid tumours with high-level microsatellite instability expansion, displaying hallmarks of early neoplasia. 02215, USA; shuji_ ogino@ dfci. or mismatch repair deficiency by the US Food and Many of these cells are likely kept in check or killed harvard. edu Drug Administration highlights promise of precision by the host immune system before they can develop Received 24 October 2017 immuno-oncology. -
The Future of Precision Medicine : Potential Impacts for Health Technology Assessment
This is a repository copy of The Future of Precision Medicine : Potential Impacts for Health Technology Assessment. White Rose Research Online URL for this paper: https://eprints.whiterose.ac.uk/133069/ Version: Accepted Version Article: Love-Koh, James orcid.org/0000-0001-9009-5346, Peel, Alison, Rejon-Parilla, Juan Carlos et al. (6 more authors) (2018) The Future of Precision Medicine : Potential Impacts for Health Technology Assessment. Pharmacoeconomics. pp. 1439-1451. ISSN 1179-2027 https://doi.org/10.1007/s40273-018-0686-6 Reuse This article is distributed under the terms of the Creative Commons Attribution-NonCommercial (CC BY-NC) licence. This licence allows you to remix, tweak, and build upon this work non-commercially, and any new works must also acknowledge the authors and be non-commercial. You don’t have to license any derivative works on the same terms. 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/ The Future of Precision Medicine: Potential Impacts for Health Technology Assessment Title: The Future of Precision Medicine: Potential Impacts for Health Technology Assessment Authors: James Love-Koh1,2, Alison Peel1, Juan Carlos Rejon-Parilla3, Kate Ennis1,4, Rosemary Lovett3, Andrea Manca2,5, Anastasia Chalkidou6, Hannah Wood1, Matthew Taylor1 1 YorK Health Economics Consortium 2 Centre for Health Economics, University of YorK 3 National Institute for Health and Care Excellence 4 Institute of Infection and Global Health, University of Liverpool 5 Luxembourg Institute of Health 6 Kings Technology Evaluation Centre Corresponding Author Details: Name: James Love-Koh Address: Centre for Health Economics, Alcuin A Block, University of York, Heslington, York, YO10 5DD, UK. -
Genomic Epidemiology and Recent Update on Nucleic Acid–Based Diagnostics for COVID-19
Current Tropical Medicine Reports https://doi.org/10.1007/s40475-020-00212-3 COVID-19 IN THE TROPICS: IMPACT AND SOLUTIONS (AJ RODRIGUEZ-MORALES, SECTION EDITOR)) Genomic Epidemiology and Recent Update on Nucleic Acid–Based Diagnostics for COVID-19 Ali A. Rabaan1 & Shamsah H. Al-Ahmed2 & Ranjit Sah3 & Jaffar A. Al-Tawfiq4,5,6 & Shafiul Haque7 & Harapan Harapan8,9,10 & Kovy Arteaga-Livias11,12 & D. Katterine Bonilla Aldana13,14 & Pawan Kumar 15 & Kuldeep Dhama16 & Alfonso J. Rodriguez-Morales12,13,14,17 Accepted: 10 September 2020 # Springer Nature Switzerland AG 2020 Abstract Purpose of the Review The SARS-CoV-2 genome has been sequenced and the data is made available in the public domain. Molecular epidemiological investigators have utilized this information to elucidate the origin, mode of transmission, and contact tracing of SARS-CoV-2. The present review aims to highlight the recent advancements in the molecular epidemiological studies along with updating recent advancements in the molecular (nucleic acid based) diagnostics for COVID-19, the disease caused by SARS-CoV-2. Recent Findings Epidemiological studies with the integration of molecular genetics principles and tools are now mainly focused on the elucidation of molecular pathology of COVID-19. Molecular epidemiological studies have discovered the mutability of SARS-CoV-2 which is of utmost importance for the development of therapeutics and vaccines for COVID-19. The whole world is now participating in the race for development of better and rapid diagnostics and therapeutics for COVID-19. Several molecular diagnostic techniques have been developed for accurate and precise diagnosis of COVID-19. Summary Novel genomic techniques have helped in the understanding of the disease pathology, origin, and spread of COVID- 19. -
Role and Limitations of Epidemiology in Establishing a Causal Association Eduardo L
Seminars in Cancer Biology 14 (2004) 413–426 Role and limitations of epidemiology in establishing a causal association Eduardo L. Franco a,∗, Pelayo Correa b, Regina M. Santella c, Xifeng Wu d, Steven N. Goodman e, Gloria M. Petersen f a Departments of Epidemiology and Oncology, McGill University, 546 Pine Avenue West, Montreal, QC, Canada H2W1S6 b Department of Pathology, Louisiana State University Health Sciences Center, New Orleans, LA, USA c Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA d Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA e Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA f Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA Abstract Cancer risk assessment is one of the most visible and controversial endeavors of epidemiology. Epidemiologic approaches are among the most influential of all disciplines that inform policy decisions to reduce cancer risk. The adoption of epidemiologic reasoning to define causal criteria beyond the realm of mechanistic concepts of cause-effect relationships in disease etiology has placed greater reliance on controlled observations of cancer risk as a function of putative exposures in populations. The advent of molecular epidemiology further expanded the field to allow more accurate exposure assessment, improved understanding of intermediate endpoints, and enhanced risk prediction by incorporating the knowledge on genetic susceptibility. We examine herein the role and limitations of epidemiology as a discipline concerned with the identification of carcinogens in the physical, chemical, and biological environment. We reviewed two examples of the application of epidemiologic approaches to aid in the discovery of the causative factors of two very important malignant diseases worldwide, stomach and cervical cancers. -
Molecular Epidemiology and Whole-Genome Analysis of Bovine Foamy Virus in Japan
viruses Article Molecular Epidemiology and Whole-Genome Analysis of Bovine Foamy Virus in Japan Hirohisa Mekata 1,* , Tomohiro Okagawa 2, Satoru Konnai 2,3 and Takayuki Miyazawa 4 1 Center for Animal Disease Control, University of Miyazaki, Miyazaki 889-2192, Japan 2 Department of Advanced Pharmaceutics, Faculty of Veterinary Medicine, Hokkaido University, Sapporo 060-0818, Japan; [email protected] (T.O.); [email protected] (S.K.) 3 Department of Disease Control, Faculty of Veterinary Medicine, Hokkaido University, Sapporo 060-0818, Japan 4 Laboratory of Virus-Host Coevolution, Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto 606-8507, Japan; [email protected] * Correspondence: [email protected]; Tel./Fax: +81-985-58-7881 Abstract: Bovine foamy virus (BFV) is a member of the foamy virus family in cattle. Information on the epidemiology, transmission routes, and whole-genome sequences of BFV is still limited. To understand the characteristics of BFV, this study included a molecular survey in Japan and the determination of the whole-genome sequences of 30 BFV isolates. A total of 30 (3.4%, 30/884) cattle were infected with BFV according to PCR analysis. Cattle less than 48 months old were scarcely infected with this virus, and older animals had a significantly higher rate of infection. To reveal the possibility of vertical transmission, we additionally surveyed 77 pairs of dams and 3-month-old calves in a farm already confirmed to have BFV. We confirmed that one of the calves born from a dam with BFV was infected. -
What Are Precision Medicine and Personalized Medicine?
What Are Precision Medicine and Personalized Medicine? Precision medicine, also known as personalized medicine, is a new frontier for healthcare combining genomics, big data analytics, and population health. Source: Thinkstock Since the beginning of recorded history, healthcare practitioners have striven to make their actions more effective for their patients by experimenting with different treatments, observing and sharing their results, and improving upon the efforts of previous generations. Becoming more accurate, precise, proactive, and impactful for each individual that comes under their care has always been the goal of all clinicians, no matter how basic the tools at their disposal. But now, modern physicians and scientists are now able to take this mission far, far beyond the reach of their ancestors with the help of electronic health records, genetic testing, big data analytics, and supercomputing – all the ingredients required to engage in what is quickly becoming truly precise and personalized medicine. Precision medicine, also commonly referred to as personalized medicine, is one of the most promising approaches to tackling diseases that have thus far eluded effective treatments or cures. Cancer, neurodegenerative diseases, and rare genetic conditions take an enormous toll on individuals, families and societies as a whole. Approximately 1.7 million new cancer cases were diagnosed in the United States in 2017. Around 600,000 deaths were expected during that year, according to the American Cancer Society. The Agency for Healthcare Research and Quality adds that the direct economic impact of cancer is around $80 billion per year – loss of productivity, wages, and caregiver needs sap billions more from the economy. -
Advancing Standards for Precision Medicine
Advancing Standards for Precision Medicine FINAL REPORT Prepared by: Audacious Inquiry on behalf of the Office of the National Coordinator for Health Information Technology under Contract No. HHSM-500-2017-000101 Task Order No. HHSP23320100013U January 2021 ONC Advancing Standards for Precision Medicine Table of Contents Executive Summary ...................................................................................................................................... 5 Standards Development and Demonstration Projects ............................................................................ 5 Mobile Health, Sensors, and Wearables ........................................................................................... 5 Social Determinants of Health (SDOH) ............................................................................................. 5 Findings and Lessons Learned .......................................................................................................... 6 Recommendations ........................................................................................................................................ 6 Introduction ................................................................................................................................................... 7 Background ................................................................................................................................................... 7 Project Purpose, Goals, and Objectives .................................................................................................. -
Molecular Pathological Epidemiology Gives Clues to Paradoxical Findings
Molecular Pathological Epidemiology Gives Clues to Paradoxical Findings The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Nishihara, Reiko, Tyler J. VanderWeele, Kenji Shibuya, Murray A. Mittleman, Molin Wang, Alison E. Field, Edward Giovannucci, Paul Lochhead, and Shuji Ogino. 2015. “Molecular Pathological Epidemiology Gives Clues to Paradoxical Findings.” European Journal of Epidemiology 30 (10): 1129–35. https://doi.org/10.1007/ s10654-015-0088-4. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:41392032 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#OAP HHS Public Access Author manuscript Author Manuscript Author ManuscriptEur J Epidemiol Author Manuscript. Author Author Manuscript manuscript; available in PMC 2016 October 07. Published in final edited form as: Eur J Epidemiol. 2015 October ; 30(10): 1129–1135. doi:10.1007/s10654-015-0088-4. Molecular Pathological Epidemiology Gives Clues to Paradoxical Findings Reiko Nishiharaa,b,c, Tyler J. VanderWeeled,e, Kenji Shibuyac, Murray A. Mittlemand,f, Molin Wangd,e,g, Alison E. Fieldd,g,h,i, Edward Giovannuccia,d,g, Paul Lochheadi,j, and Shuji Oginob,d,k aDepartment of Nutrition, Harvard T.H. Chan School of Public Health, 655 Huntington Ave., Boston, Massachusetts 02115 USA bDepartment of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, 450 Brookline Ave., Boston, Massachusetts 02215 USA cDepartment of Global Health Policy, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan dDepartment of Epidemiology, Harvard T.H. -
Molecular Epidemiology and Precision Medicine
Pharmacogenetics: Past, Present, and Future Brooke L. Fridley, PhD Associate Professor of Biostatistics University of Kansas Medical Center Site Director, K-INBRE Bioinformatics Core Director, Biostatistics and Informatics Shared Resource, University of Kansas Cancer Center What is Pharmacogenomics? Pharmacogenomics & Precision Medicine Aims to deliver the correct drug or treatment: • At the right time • To the right patient • At the right dose Can only be achieved when we have accurate clinical tests (BIOMARKER) and companion drugs at our disposal What is a Biomarker? • Biomarker: “A characteristic that is objectively measured and evaluated as an indicator of – normal biological processes, – pathogenic processes, or – pharmacologic responses to a therapeutic intervention.” Biomarkers Definitions Working Group. Biomarkers and surrogate end points: preferred definitions and conceptual framework. Clin Pharmacol Ther 2001;69:89–95 Candidate Gene Era 1950 – 1990 – Structure of 1980 – 1985 – HGP DNA TPMT PCR begins 1997 – 1977 – 1983 – First 1987 – NHGRI Sanger human P450 formed Sequencing disease supergene gene family mapped Candidate • Genotyping Variant & • RT-PCR Gene • Re-sequencing genes (exons) with Sanger Studies Sequencing PK and PD and * Alleles (haplotypes) PGx Effect = Gene*Drug Interaction Drug 1 Drug 2 Genome-wide Array Era 2003 – FDA 2002 – issues draft 1998 -Illumina HapMap guidelines for founded begins PGx 2001 – 1st 2003 – 2004 – 1st NGS version of Completion of platform human HGP genome completed Genome- • SNP arrays (~mid 2000s) wide • mRNA arrays (~mid 1990s) Association Studies • Methylation arrays (~2008-2010) Study of Genetic Association with Drug Response Phenotypes Cases: Non-responders Cases: Responders Genetic association studies look at the frequency of genetic changes to try to determine whether specific changes are associated with a phenotype. -
The Personalized Medicine Report
THE PERSONALIZED MEDICINE REPORT 2017 · Opportunity, Challenges, and the Future The Personalized Medicine Coalition gratefully acknowledges graduate students at Manchester University in North Manchester, Indiana, and at the University of Florida, who updated the appendix of this report under the guidance of David Kisor, Pharm.D., Director, Pharmacogenomics Education, Manchester University, and Stephan Schmidt, Ph.D., Associate Director, Pharmaceutics, University of Florida. The Coalition also acknowledges the contributions of its many members who offered insights and suggestions for the content in the report. CONTENTS INTRODUCTION 5 THE OPPORTUNITY 7 Benefits 9 Scientific Advancement 17 THE CHALLENGES 27 Regulatory Policy 29 Coverage and Payment Policy 35 Clinical Adoption 39 Health Information Technology 45 THE FUTURE 49 Conclusion 51 REFERENCES 53 APPENDIX 57 Selected Personalized Medicine Drugs and Relevant Biomarkers 57 HISTORICAL PRECEDENT For more than two millennia, medicine has maintained its aspiration of being personalized. In ancient times, Hippocrates combined an assessment of the four humors — blood, phlegm, yellow bile, and black bile — to determine the best course of treatment for each patient. Today, the sequence of the four chemical building blocks that comprise DNA, coupled with telltale proteins in the blood, enable more accurate medical predictions. The Personalized Medicine Report 5 INTRODUCTION When it comes to medicine, one size does not fit all. Treatments that help some patients are ineffective for others (Figure 1),1 and the same medicine may cause side effects in only certain patients. Yet, bound by the constructs of traditional disease, and, at the same time, increase the care delivery models, many of today’s doctors still efficiency of the health care system by improving prescribe therapies based on population averages. -
Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data
Twin Research and Human Genetics (2020), 23, 145–155 doi:10.1017/thg.2020.53 Article Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data René Pool1,2* , Fiona A. Hagenbeek1,2* , Anne M. Hendriks1,2 , Jenny van Dongen1,2 , Gonneke Willemsen1 , Eco de Geus1,2 BBMRI Metabolomics Consortium3, Ko Willems van Dijk4,5,6 , Aswin Verhoeven7 , H. Eka Suchiman8 , Marian Beekman8 , P. Eline Slagboom8 , Amy C. Harms9,10 , Thomas Hankemeier9,10 and Dorret I. Boomsma1,2 1Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands, 2Amsterdam Public Health Research Institute, Amsterdam, the Netherlands, 3Members of the BBMRI Metabolomics Consortium are listed after the abstract, 4Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands, 5Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands, 6Department of Internal Medicine Division Endocrinology, Leiden University Medical Center, Leiden, the Netherlands, 7Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, the Netherlands, 8Department of Biomedical Data Sciences, Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands, 9Division of Analytical Biosciences, Leiden Academic Center for Drug Research, Leiden University, Leiden, the Netherlands and 10The Netherlands Metabolomics Centre, Leiden, the Netherlands Abstract Metabolites are small molecules involved in cellular metabolism where -
A Bioinformatics Approach for Precision Medicine Off-Label Drug
View metadata, citation and similar papers at core.ac.uk brought to you by CORE Cheng L, et al. J Am Med Inform Assoc 2016;23:741–749. doi:10.1093/jamia/ocw004, Research and Applications provided by IUPUIScholarWorks RECEIVED 5 September 2015 A bioinformatics approach for precision REVISED 10 December 2015 ACCEPTED 10 January 2016 medicine off-label drug selection among PUBLISHED ONLINE FIRST 23 April 2016 triple negative breast cancer patients Lijun Cheng,1,2 Bryan P Schneider,3,4 and Lang Li1,2,4 ABSTRACT .................................................................................................................................................... Background Cancer has been extensively characterized on the basis of genomics. The integration of genetic information about cancers with data on how the cancers respond to target based therapy to help to optimum cancer treatment. Objective The increasing usage of sequencing technology in cancer research and clinical practice has enormously advanced our understanding of cancer RESEARCH AND APPLICATIONS mechanisms. The cancer precision medicine is becoming a reality. Although off-label drug usage is a common practice in treating cancer, it suffers from the lack of knowledge base for proper cancer drug selections. This eminent need has become even more apparent considering the upcoming genomics data. Methods In this paper, a personalized medicine knowledge base is constructed by integrating various cancer drugs, drug-target database, and knowl- edge sources for the proper cancer drugs and their target selections. Based on the knowledge base, a bioinformatics approach for cancer drugs selec- tion in precision medicine is developed. It integrates personal molecular profile data, including copy number variation, mutation, and gene expression. Results By analyzing the 85 triple negative breast cancer (TNBC) patient data in the Cancer Genome Altar, we have shown that 71.7% of the TNBC patients have FDA approved drug targets, and 51.7% of the patients have more than one drug target.