1
|
Ochs-Balcom HM, Preus L, Du Z, Elston RC, Teerlink CC, Jia G, Guo X, Cai Q, Long J, Ping J, Li B, Stram DO, Shu XO, Sanderson M, Gao G, Ahearn T, Lunetta KL, Zirpoli G, Troester MA, Ruiz-Narváez EA, Haddad SA, Figueroa J, John EM, Bernstein L, Hu JJ, Ziegler RG, Nyante S, Bandera EV, Ingles SA, Mancuso N, Press MF, Deming SL, Rodriguez-Gil JL, Yao S, Ogundiran TO, Ojengbede O, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Sandler DP, Taylor JA, Wang Q, O’Brien KM, Weinberg CR, Kitahara CM, Blot W, Nathanson KL, Hennis A, Nemesure B, Ambs S, Sucheston-Campbell LE, Bensen JT, Chanock SJ, Olshan AF, Ambrosone CB, Olopade OI, the Ghana Breast Health Study Team, Conti DV, Palmer J, García-Closas M, Huo D, Zheng W, Haiman C. Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia. Hum Mol Genet 2024; 33:687-697. [PMID: 38263910 PMCID: PMC11000665 DOI: 10.1093/hmg/ddae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.
Collapse
Affiliation(s)
- Heather M Ochs-Balcom
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, Buffalo, NY 14214, United States
| | - Leah Preus
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, Buffalo, NY 14214, United States
| | - Zhaohui Du
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
- Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave, N. Seattle, WA 98109, United States
| | - Robert C Elston
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, United States
| | - Craig C Teerlink
- Department of Internal Medicine, University of Utah School of Medicine, 30 North Mario Capecchi Dr, 3rd Floor North, Salt Lake City, UT 84112, United States
| | - Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University, 707 Light Hall 2215 Garland Avenue, Nashville, TN 37232, United States
| | - Daniel O Stram
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, 1005 Dr. DB Todd Jr, Blvd. Nashville, TN 37208, United States
| | - Guimin Gao
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, United States
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University, 715 Albany St, Boston, MA 02118, United States
| | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Melissa A Troester
- Department of Epidemiology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC 27599, United States
| | - Edward A Ruiz-Narváez
- Department of Nutritional Sciences, University of Michigan School of Public Health, 1860 SPH I, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Stephen A Haddad
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
- Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, 9 Little France Road, Edinburgh, EH16 4UX, United Kingdom
- Cancer Research UK Edinburgh Centre, Crewe Rd S, Edinburgh, EH4 2XR, United Kingdom
| | - Esther M John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, 3145 Porter Dr, Suite E223, MC 5393, Palo Alto, CA 94304, United States
- Department of Medicine (Oncology), Stanford University School of Medicine, 291 Campus Drive Li Ka Shing Building, Stanford, CA 94305, United States
| | - Leslie Bernstein
- Division of Biomarkers of Early Detection and Prevention Department of Population Sciences, Beckman Research Institute of the City of Hope, City of Hope Comprehensive Cancer Center, 1500 East Duarte Road, Duarte, CA 91010, United States
| | - Jennifer J Hu
- Sylvester Comprehensive Cancer Center and Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14th St, CRB 1511, Miami, FL 33136, United States
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Sarah Nyante
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, 130 Mason Farm Rd., Chapel Hill, NC 27599, United States
| | - Elisa V Bandera
- Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, 120 Albany Street, Tower 2, 8th Floor, New Brunswick, NJ 08903, United States
| | - Sue A Ingles
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Nicholas Mancuso
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Michael F Press
- Department of Pathology, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1441 Eastlake Ave., Los Angeles, CA 90033, United States
| | - Sandra L Deming
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jorge L Rodriguez-Gil
- Genomics, Development and Disease Section, Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 31 Center Dr, Bethesda, MD 20894, United States
- Medical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison, 750 Highland Ave., Madison, WI 53705, United States
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, United States
| | - Temidayo O Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Queen Elizabeth II Road, Ibadan, 200285, Nigeria
| | - Oladosu Ojengbede
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, UCH, Queen Elizabeth II Road, Ibadan, 200285, Nigeria
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Iroon Avenue 6, 2371 Ayius Dometios, Nicosia, Cyprus
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Katie M O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Cari M Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
- International Epidemiology Institute, 1455 Research Boulevard, Rockville, MD 20850, United States
| | - Katherine L Nathanson
- Department of Medicine, Abramson Cancer Center, The Perelman School of Medicine at the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19140, United States
| | - Anselm Hennis
- Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Jemmotts Lane, Avalon, Bridgetown, Barbados
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, 100 Nicolls Road, Stony Brook, NY 11794, United States
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, 37 Convent Drive, Bethesda, MD 20892, United States
| | - Lara E Sucheston-Campbell
- College of Pharmacy, The Ohio State University, 217 Lloyd M. Parks Hall, 500 West 12th Ave., Columbus, OH 43210, United States
- College of Veterinary Medicine, The Ohio State University, 1900 Coffey Road, Columbus, OH 43210, United States
| | - Jeannette T Bensen
- Department of Epidemiology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC 27599, United States
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 170 Rosenau Hall, CB #7400, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, United States
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, University of Chicago, 5841 S Maryland Avenue, Chicago, IL 60637, United States
| | | | - David V Conti
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Julie Palmer
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, United States
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Christopher Haiman
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| |
Collapse
|
2
|
Kang E, Jung JJ, Lim C, Kim HK, Lee HB, Han W, Moon HG. Increased risk of contralateral breast cancer for BRCA1/2 wild-type, high-risk Korean breast cancer patients: a retrospective cohort study. Breast Cancer Res 2024; 26:14. [PMID: 38254240 PMCID: PMC10801954 DOI: 10.1186/s13058-024-01769-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 01/09/2024] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND This study aimed to investigate the contralateral breast cancer (CBC) recurrence rate in Korean breast cancer patients according to their BRCA1/2 germline mutation status, focusing particularly on the CBC recurrence risk in BRCA1/2 negative (BRCAx) patients. METHODS We conducted a retrospective study on 13,107 primary breast cancer patients. The patients were divided into high-risk and low-risk groups for hereditary breast cancer based on the Korean National Health Insurance Service's eligibility criteria for BRCA1/2 germline mutation testing. The high-risk group was further categorized into the BRCA mutation group, the BRCAx group, and the not tested group. We evaluated the overall survival and cumulative risk of developing CBC in these patients. RESULTS Among 4494 high-risk patients, 973 (21.7%) underwent genetic testing for BRCA1/2 germline mutation, revealing mutations in 158 patients (16.2%). We observed significant overall survival differences across all four groups, with the high-risk, not-tested group demonstrating notably worse overall survival (p < 0.001). However, when adjusted for other prognostic factors, there was no significant differences in hazard ratio of death between the four groups. The cumulative risk of CBC also varied among the groups. Patients with BRCA1/2 mutations showed a 7.3-fold increased risk of CBC compared to the low-risk group (95% CI 4.11-13.0, p < 0.001). Interestingly, BRCAx patients also demonstrated a significantly higher risk of CBC (HR 2.77, 95% CI 1.76-4.35, p < 0.001). The prognostic importance of the BRCAx for CBC recurrence persisted after adjusting for the age and subtype, but became insignificant when the family history of breast cancer was adjusted. CONCLUSION Breast cancer patients who are at high risk of hereditary breast cancer but with wild-type BRCA 1/2 genes (BRCAx) have increased risk of developing contralateral breast cancer when compared to the low-risk patients. More careful surveillance and follow-up can be offered to these patients especially when they have family history of breast cancer.
Collapse
Affiliation(s)
- Eunhye Kang
- Department of Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Ji-Jung Jung
- Department of Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Changjin Lim
- Department of Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Korea
| | - Hong-Kyu Kim
- Department of Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Genomic Medicine Institute, Seoul National University Medical Research Center, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Han-Byoel Lee
- Department of Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Genomic Medicine Institute, Seoul National University Medical Research Center, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Wonshik Han
- Department of Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Genomic Medicine Institute, Seoul National University Medical Research Center, Seoul, Korea
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea
| | - Hyeong-Gon Moon
- Department of Surgery, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
- Genomic Medicine Institute, Seoul National University Medical Research Center, Seoul, Korea.
- Cancer Research Institute, Seoul National University, Seoul, Republic of Korea.
| |
Collapse
|
3
|
Haycock PC, Borges MC, Burrows K, Lemaitre RN, Harrison S, Burgess S, Chang X, Westra J, Khankari NK, Tsilidis KK, Gaunt T, Hemani G, Zheng J, Truong T, O’Mara TA, Spurdle AB, Law MH, Slager SL, Birmann BM, Saberi Hosnijeh F, Mariosa D, Amos CI, Hung RJ, Zheng W, Gunter MJ, Davey Smith G, Relton C, Martin RM. Design and quality control of large-scale two-sample Mendelian randomization studies. Int J Epidemiol 2023; 52:1498-1521. [PMID: 38587501 PMCID: PMC10555669 DOI: 10.1093/ije/dyad018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 02/10/2023] [Indexed: 03/27/2024] Open
Abstract
Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).
Collapse
Affiliation(s)
- Philip C Haycock
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kimberley Burrows
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Sean Harrison
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Xuling Chang
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat—National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Jason Westra
- Department of Mathematics, Statistics, and Computer Science, Dordt College, Sioux Center, IA, USA
| | - Nikhil K Khankari
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kostas K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Tom Gaunt
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Therese Truong
- Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Team “Exposome, Heredity, Cancer and Health”, CESP, Villejuif, France
| | - Tracy A O’Mara
- Genetics and Computational Biology Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Medicine, Faculty of Health Sciences, University of Queensland, Brisbane, Australia
| | - Amanda B Spurdle
- Genetics and Computational Biology Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Medicine, Faculty of Health Sciences, University of Queensland, Brisbane, Australia
| | - Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Susan L Slager
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Brenda M Birmann
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Daniela Mariosa
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Christopher I Amos
- Dan L Duncan Comprehensive Cancer Center Baylor College of Medicine, Houston, USA
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health and University of Toronto, Toronto, Canada
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC), Lyon, France
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
| |
Collapse
|
4
|
Sanchez A, Lhuillier J, Grosjean G, Ayadi L, Maenner S. The Long Non-Coding RNA ANRIL in Cancers. Cancers (Basel) 2023; 15:4160. [PMID: 37627188 PMCID: PMC10453084 DOI: 10.3390/cancers15164160] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 08/27/2023] Open
Abstract
ANRIL (Antisense Noncoding RNA in the INK4 Locus), a long non-coding RNA encoded in the human chromosome 9p21 region, is a critical factor for regulating gene expression by interacting with multiple proteins and miRNAs. It has been found to play important roles in various cellular processes, including cell cycle control and proliferation. Dysregulation of ANRIL has been associated with several diseases like cancers and cardiovascular diseases, for instance. Understanding the oncogenic role of ANRIL and its potential as a diagnostic and prognostic biomarker in cancer is crucial. This review provides insights into the regulatory mechanisms and oncogenic significance of the 9p21 locus and ANRIL in cancer.
Collapse
Affiliation(s)
| | | | | | - Lilia Ayadi
- CNRS, Université de Lorraine, IMoPA, F-54000 Nancy, France
| | | |
Collapse
|
5
|
Zorn A, Baillie G. Phosphodiesterase 7 as a therapeutic target - Where are we now? Cell Signal 2023; 108:110689. [PMID: 37120115 DOI: 10.1016/j.cellsig.2023.110689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/14/2023] [Accepted: 04/24/2023] [Indexed: 05/01/2023]
Abstract
Cyclic nucleotide phosphodiesterases (PDEs) are a superfamily of enzymes that hydrolyse the intracellular second messengers cAMP and cGMP to their inactive forms 5'AMP and 5'GMP. Some members of the PDE family display specificity towards a single cyclic nucleotide messenger, and PDE4, PDE7, and PDE8 specifically hydrolyse cAMP. While the role of PDE4 and its use as a therapeutic target have been well studied, less is known about PDE7 and PDE8. This review aims to collate the present knowledge on human PDE7 and outline its potential use as a therapeutic target. Human PDE7 exists as two isoforms PDE7A and PDE7B that display different expression patterns but are predominantly found in the central nervous system, immune cells, and lymphoid tissue. As a result, PDE7 is thought to play a role in T cell activation and proliferation, inflammation, and regulate several physiological processes in the central nervous system, such as neurogenesis, synaptogenesis, and long-term memory formation. Increased expression and activity of PDE7 has been detected in several disease states, including neurodegenerative diseases such as Parkinson's, Alzheimer's and Huntington's disease, autoimmune diseases such as multiple sclerosis and COPD, and several types of cancer. Early studies have shown that administration of PDE7 inhibitors may ameliorate the clinical state of these diseases. Targeting PDE7 may therefore provide a novel therapeutic strategy for targeting a broad range of disease and possibly provide a complementary alternative to inhibitors of other cAMP-selective PDEs, such as PDE4, which are severely limited by their side-effects.
Collapse
Affiliation(s)
- Alina Zorn
- University of Glasgow, 535 Wolfson Link Building, G12 8QQ Glasgow, United Kingdom.
| | - George Baillie
- University of Glasgow, 535 Wolfson Link Building, G12 8QQ Glasgow, United Kingdom.
| |
Collapse
|
6
|
Zhang H, Chen B, Waliullah ASM, Aramaki S, Ping Y, Takanashi Y, Zhang C, Zhai Q, Yan J, Oyama S, Kahyo T, Setou M. A New Potential Therapeutic Target for Cancer in Ubiquitin-Like Proteins-UBL3. Int J Mol Sci 2023; 24:ijms24021231. [PMID: 36674743 PMCID: PMC9863382 DOI: 10.3390/ijms24021231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/31/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Ubiquitin-like proteins (Ubls) are involved in a variety of biological processes through the modification of proteins. Dysregulation of Ubl modifications is associated with various diseases, especially cancer. Ubiquitin-like protein 3 (UBL3), a type of Ubl, was revealed to be a key factor in the process of small extracellular vesicle (sEV) protein sorting and major histocompatibility complex class II ubiquitination. A variety of sEV proteins that affects cancer properties has been found to interact with UBL3. An increasing number of studies has implied that UBL3 expression affects cancer cell growth and cancer prognosis. In this review, we provide an overview of the relationship between various Ubls and cancers. We mainly introduce UBL3 and its functions and summarize the current findings of UBL3 and examine its potential as a therapeutic target in cancers.
Collapse
Affiliation(s)
- Hengsen Zhang
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Bin Chen
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - A. S. M. Waliullah
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Shuhei Aramaki
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
- Department of Radiation Oncology, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Yashuang Ping
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Yusuke Takanashi
- First Department of Surgery, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Chi Zhang
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
- Department of Systems Molecular Anatomy, Institute for Medical Photonics Research, Preeminent Medical Photonics, Education & Research Center, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Qing Zhai
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Jing Yan
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Soho Oyama
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Tomoaki Kahyo
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
- International Mass Imaging Center, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
| | - Mitsutoshi Setou
- Department of Cellular and Molecular Anatomy, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
- Department of Systems Molecular Anatomy, Institute for Medical Photonics Research, Preeminent Medical Photonics, Education & Research Center, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
- International Mass Imaging Center, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka 431-3192, Japan
- Correspondence: ; Tel.: +81-053-435-2086; Fax: +81-053-435-2468
| |
Collapse
|
7
|
BREAst screening Tailored for HEr (BREATHE)-A study protocol on personalised risk-based breast cancer screening programme. PLoS One 2022; 17:e0265965. [PMID: 35358246 PMCID: PMC8970365 DOI: 10.1371/journal.pone.0265965] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/22/2022] [Indexed: 12/29/2022] Open
Abstract
Routine mammography screening is currently the standard tool for finding cancers at an early stage, when treatment is most successful. Current breast screening programmes are one-size-fits-all which all women above a certain age threshold are encouraged to participate. However, breast cancer risk varies by individual. The BREAst screening Tailored for HEr (BREATHE) study aims to assess acceptability of a comprehensive risk-based personalised breast screening in Singapore. Advancing beyond the current age-based screening paradigm, BREATHE integrates both genetic and non-genetic breast cancer risk prediction tools to personalise screening recommendations. BREATHE is a cohort study targeting to recruit ~3,500 women. The first recruitment visit will include questionnaires and a buccal cheek swab. After receiving a tailored breast cancer risk report, participants will attend an in-person risk review, followed by a final session assessing the acceptability of our risk stratification programme. Risk prediction is based on: a) Gail model (non-genetic), b) mammographic density and recall, c) BOADICEA predictions (breast cancer predisposition genes), and d) breast cancer polygenic risk score. For national implementation of personalised risk-based breast screening, exploration of the acceptability within the target populace is critical, in addition to validated predication tools. To our knowledge, this is the first study to implement a comprehensive risk-based mammography screening programme in Asia. The BREATHE study will provide essential data for policy implementation which will transform the health system to deliver a better health and healthcare outcomes.
Collapse
|
8
|
Ubiquitin-like protein 3 (UBL3) is required for MARCH ubiquitination of major histocompatibility complex class II and CD86. Nat Commun 2022; 13:1934. [PMID: 35411049 PMCID: PMC9001657 DOI: 10.1038/s41467-022-29524-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/07/2022] [Indexed: 12/14/2022] Open
Abstract
The MARCH E3 ubiquitin (Ub) ligase MARCH1 regulates trafficking of major histocompatibility complex class II (MHC II) and CD86, molecules of critical importance to immunity. Here we show, using a genome-wide CRISPR knockout screen, that ubiquitin-like protein 3 (UBL3) is a necessary component of ubiquitination-mediated trafficking of these molecules in mice and in humans. Ubl3-deficient mice have elevated MHC II and CD86 expression on the surface of professional and atypical antigen presenting cells. UBL3 also regulates MHC II and CD86 in human dendritic cells (DCs) and macrophages. UBL3 impacts ubiquitination of MARCH1 substrates, a mechanism that requires UBL3 plasma membrane anchoring via prenylation. Loss of UBL3 alters adaptive immunity with impaired development of thymic regulatory T cells, loss of conventional type 1 DCs, increased number of trogocytic marginal zone B cells, and defective in vivo MHC II and MHC I antigen presentation. In summary, we identify UBL3 as a conserved, critical factor in MARCH1-mediated ubiquitination with important roles in immune responses. Regulated trafficking of major histocompatibility complex class II and CD86 is a prerequisite of antigen presenting cell functionality. Authors show here that ubiquitin-like protein 3 is critically involved in the ubiquitination process that controls trafficking, with wide-ranging immunological consequences.
Collapse
|
9
|
Shen L, Zhang S, Wang K, Wang X. Familial Breast Cancer: Disease Related Gene Mutations and Screening Strategies for Chinese Population. Front Oncol 2021; 11:740227. [PMID: 34926254 PMCID: PMC8671637 DOI: 10.3389/fonc.2021.740227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 11/12/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND About 5%-10% of the breast cancer cases have a hereditary background, and this subset is referred to as familial breast cancer (FBC). In this review, we summarize the susceptibility genes and genetic syndromes associated with FBC and discuss the FBC screening and high-risk patient consulting strategies for the Chinese population. METHODS We searched the PubMed database for articles published between January 2000 and August 2021. Finally, 380 pieces of literature addressing the genes and genetic syndromes related to FBC were included and reviewed. RESULTS We identified 16 FBC-related genes and divided them into three types (high-, medium-, and low-penetrance) of genes according to their relative risk ratios. In addition, six genetic syndromes were found to be associated with FBC. We then summarized the currently available screening strategies for FBC and discussed those available for high-risk Chinese populations. CONCLUSION Multiple gene mutations and genetic disorders are closely related to FBC. The National Comprehensive Cancer Network (NCCN) guidelines recommend corresponding screening strategies for these genetic diseases. However, such guidelines for the Chinese population are still lacking. For screening high-risk groups in the Chinese population, genetic testing is recommended after genetic counseling.
Collapse
Affiliation(s)
| | | | | | - Xiaochen Wang
- Department of Breast Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| |
Collapse
|
10
|
Zhao X, Yongchun Z, Qian H, Sanhui G, Jie L, Hong Y, Yanfei Z, Guizhen W, Yunchao H, Guangbiao Z. Identification of a potential tumor suppressor gene, UBL3, in non-small cell lung cancer. Cancer Biol Med 2021; 17:76-87. [PMID: 32296577 PMCID: PMC7142850 DOI: 10.20892/j.issn.2095-3941.2019.0279] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Accepted: 10/24/2019] [Indexed: 12/24/2022] Open
Abstract
Objective: Oncogenes have been shown to be drivers of non-small cell lung cancer (NSCLC), yet the tumor suppressing genes involved in lung carcinogenesis remain to be systematically investigated. This study aimed to identify tumor suppressing ubiquitin pathway genes (UPGs) that were critical to lung tumorigenesis. Methods: The 696 UPGs were silenced by an siRNA screening in NSCLC cells; the potential tumor suppressing UPGs were analyzed, and their clinical significance was investigated. Results: We reported that silencing of 11 UPGs resulted in enhanced proliferation of NSCLC cells, and four UPGs (UBL3, TRIM22, UBE2G2, and MARCH1) were significantly downregulated in tumor samples compared to that in normal lung tissues and their expression levels were positively associated with overall survival (OS) of NSCLC patients. Among these genes, UBL3 was the most significant one. UBL3 expression was decreased in tumor samples compared to that in paired normal lung tissues in 59/86 (68.6%) NSCLCs, was correlated with TNM stage and sex of NSCLC patients, and was significantly higher in non-smoking patients than in smoking patients. Silencing UBL3 accelerated cell proliferation and ectopic expression of UBL3 suppressed NSCLC in vitro and in vivo. Conclusions: These results showed that UBL3 represented a tumor suppressor in NSCLC and may have potential for use in therapeutics and for the prediction of clinical outcome of patients.
Collapse
Affiliation(s)
- Xinchun Zhao
- School of Life Sciences, University of Science and Technology of China, Hefei 230026, China.,State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhou Yongchun
- Department of Thoracic Surgery, the Third Affiliated Hospital of Kunming Medical University, Kunming 650106, China
| | - Hu Qian
- State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Gao Sanhui
- State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Liu Jie
- State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Yu Hong
- State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Zhang Yanfei
- State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Wang Guizhen
- State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Huang Yunchao
- Department of Thoracic Surgery, the Third Affiliated Hospital of Kunming Medical University, Kunming 650106, China
| | - Zhou Guangbiao
- State Key Laboratory of Molecular Oncology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.,State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| |
Collapse
|
11
|
Fritsche LG, Patil S, Beesley LJ, VandeHaar P, Salvatore M, Ma Y, Peng RB, Taliun D, Zhou X, Mukherjee B. Cancer PRSweb: An Online Repository with Polygenic Risk Scores for Major Cancer Traits and Their Evaluation in Two Independent Biobanks. Am J Hum Genet 2020; 107:815-836. [PMID: 32991828 PMCID: PMC7675001 DOI: 10.1016/j.ajhg.2020.08.025] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Accepted: 08/28/2020] [Indexed: 02/06/2023] Open
Abstract
To facilitate scientific collaboration on polygenic risk scores (PRSs) research, we created an extensive PRS online repository for 35 common cancer traits integrating freely available genome-wide association studies (GWASs) summary statistics from three sources: published GWASs, the NHGRI-EBI GWAS Catalog, and UK Biobank-based GWASs. Our framework condenses these summary statistics into PRSs using various approaches such as linkage disequilibrium pruning/p value thresholding (fixed or data-adaptively optimized thresholds) and penalized, genome-wide effect size weighting. We evaluated the PRSs in two biobanks: the Michigan Genomics Initiative (MGI), a longitudinal biorepository effort at Michigan Medicine, and the population-based UK Biobank (UKB). For each PRS construct, we provide measures on predictive performance and discrimination. Besides PRS evaluation, the Cancer-PRSweb platform features construct downloads and phenome-wide PRS association study results (PRS-PheWAS) for predictive PRSs. We expect this integrated platform to accelerate PRS-related cancer research.
Collapse
Affiliation(s)
- Lars G Fritsche
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA.
| | - Snehal Patil
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Lauren J Beesley
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Peter VandeHaar
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Maxwell Salvatore
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Ying Ma
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Robert B Peng
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Department of Statistics, Northwestern University, Evanston, IL 60208, USA
| | - Daniel Taliun
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA
| | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Center for Precision Health Data Science, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI 48109, USA; Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA; University of Michigan Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA.
| |
Collapse
|
12
|
Inositol 1,4,5-Trisphosphate Receptors in Human Disease: A Comprehensive Update. J Clin Med 2020; 9:jcm9041096. [PMID: 32290556 PMCID: PMC7231134 DOI: 10.3390/jcm9041096] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 03/30/2020] [Accepted: 04/10/2020] [Indexed: 12/22/2022] Open
Abstract
Inositol 1,4,5-trisphosphate receptors (ITPRs) are intracellular calcium release channels located on the endoplasmic reticulum of virtually every cell. Herein, we are reporting an updated systematic summary of the current knowledge on the functional role of ITPRs in human disorders. Specifically, we are describing the involvement of its loss-of-function and gain-of-function mutations in the pathogenesis of neurological, immunological, cardiovascular, and neoplastic human disease. Recent results from genome-wide association studies are also discussed.
Collapse
|
13
|
Yanes T, Young MA, Meiser B, James PA. Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field. Breast Cancer Res 2020; 22:21. [PMID: 32066492 PMCID: PMC7026946 DOI: 10.1186/s13058-020-01260-3] [Citation(s) in RCA: 80] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 02/07/2020] [Indexed: 01/04/2023] Open
Abstract
Polygenic factors are estimated to account for an additional 18% of the familial relative risk of breast cancer, with those at the highest level of polygenic risk distribution having a least a twofold increased risk of the disease. Polygenic testing promises to revolutionize health services by providing personalized risk assessments to women at high-risk of breast cancer and within population breast screening programs. However, implementation of polygenic testing needs to be considered in light of its current limitations, such as limited risk prediction for women of non-European ancestry. This article aims to provide a comprehensive review of the evidence for polygenic breast cancer risk, including the discovery of variants associated with breast cancer at the genome-wide level of significance and the use of polygenic risk scores to estimate breast cancer risk. We also review the different applications of this technology including testing of women from high-risk breast cancer families with uninformative genetic testing results, as a moderator of monogenic risk, and for population screening programs. Finally, a potential framework for introducing testing for polygenic risk in familial cancer clinics and the potential challenges with implementing this technology in clinical practice are discussed.
Collapse
Affiliation(s)
- Tatiane Yanes
- Psychosocial Research Group, Prince of Wales Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia. .,The University of Queensland Diamantina Institute, Dermatology Research Centre, University of Queensland, Brisbane, QLD, 4102, Australia.
| | - Mary-Anne Young
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia
| | - Bettina Meiser
- Psychosocial Research Group, Prince of Wales Clinical School, Faculty of Medicine, UNSW Sydney, Sydney, NSW, Australia
| | - Paul A James
- Parkville Integrated Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, VIC, 3000, Australia
| |
Collapse
|
14
|
da Costa E Silva Carvalho S, Cury NM, Brotto DB, de Araujo LF, Rosa RCA, Texeira LA, Plaça JR, Marques AA, Peronni KC, Ruy PDC, Molfetta GA, Moriguti JC, Carraro DM, Palmero EI, Ashton-Prolla P, de Faria Ferraz VE, Silva WA. Germline variants in DNA repair genes associated with hereditary breast and ovarian cancer syndrome: analysis of a 21 gene panel in the Brazilian population. BMC Med Genomics 2020; 13:21. [PMID: 32039725 PMCID: PMC7011249 DOI: 10.1186/s12920-019-0652-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 12/23/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The Hereditary Breast and Ovarian Cancer Syndrome (HBOC) occurs in families with a history of breast/ovarian cancer, presenting an autosomal dominant inheritance pattern. BRCA1 and BRCA2 are high penetrance genes associated with an increased risk of up to 20-fold for breast and ovarian cancer. However, only 20-30% of HBOC cases present pathogenic variants in those genes, and other DNA repair genes have emerged as increasing the risk for HBOC. In Brazil, variants in ATM, ATR, CHEK2, MLH1, MSH2, MSH6, POLQ, PTEN, and TP53 genes have been reported in up to 7.35% of the studied cases. Here we screened and characterized variants in 21 DNA repair genes in HBOC patients. METHODS We systematically analyzed 708 amplicons encompassing the coding and flanking regions of 21 genes related to DNA repair pathways (ABRAXAS1, ATM, ATR, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, MLH1, MRE11, MSH2, MSH6, NBN, PALB2, PMS2, PTEN, RAD50, RAD51, TP53 and UIMC1). A total of 95 individuals with HBOC syndrome clinical suspicion in Southeast Brazil were sequenced, and 25 samples were evaluated for insertions/deletions in BRCA1/BRCA2 genes. Identified variants were assessed in terms of population allele frequency and their functional effects were predicted through in silico algorithms. RESULTS We identified 80 variants in 19 genes. About 23.4% of the patients presented pathogenic variants in BRCA1, BRCA2 and TP53, a frequency higher than that identified among previous studies in Brazil. We identified a novel variant in ATR, which was predicted as pathogenic by in silico tools. The association analysis revealed 13 missense variants in ABRAXAS1, BARD1, BRCA2, CHEK2, CDH1, MLH1, PALB2, and PMS2 genes, as significantly associated with increased risk to HBOC, and the patients carrying those variants did not present large insertions or deletions in BRCA1/BRCA2 genes. CONCLUSIONS This study embodies the third report of a multi-gene analysis in the Brazilian population, and addresses the first report of many germline variants associated with HBOC in Brazil. Although further functional analyses are necessary to better characterize the contribution of those variants to the phenotype, these findings would improve the risk estimation and clinical follow-up of patients with HBOC clinical suspicion.
Collapse
Affiliation(s)
- Simone da Costa E Silva Carvalho
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
- Center for Medical Genomics at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Nathalia Moreno Cury
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Danielle Barbosa Brotto
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Luiza Ferreira de Araujo
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Reginaldo Cruz Alves Rosa
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
- Center for Medical Genomics at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Lorena Alves Texeira
- Division of Internal Medicine and Geriatrics, Department of Internal Medicine, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Jessica Rodrigues Plaça
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Adriana Aparecida Marques
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Kamila Chagas Peronni
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Patricia de Cássia Ruy
- Center for Medical Genomics at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Greice Andreotti Molfetta
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
- Center for Medical Genomics at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Julio Cesar Moriguti
- Division of Internal Medicine and Geriatrics, Department of Internal Medicine, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Dirce Maria Carraro
- International Research, Center/CIPE, AC Camargo Cancer Center, Sao Paulo, SP, Brazil
| | - Edenir Inêz Palmero
- Molecular Oncology Research Center, Barretos Cancer Hospital, Barretos, SP, Brazil
| | - Patricia Ashton-Prolla
- Laboratório de Medicina Genômica, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Victor Evangelista de Faria Ferraz
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil
- Center for Medical Genomics at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil
- Department of Medical Genetics, University Hospital of the Ribeirão Preto Medical School, Ribeirão Preto, Brazil
| | - Wilson Araujo Silva
- Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil.
- Center for Medical Genomics at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil.
- Regional Blood Center at University Hospital of the Ribeirão Preto Medical School of University of São Paulo, Ribeirão Preto, SP, Brazil.
| |
Collapse
|
15
|
Park CS, Park HY, Jung JH, Kim WW, Chae YS, Lee SJ, Park JY, Park JY, Lee J. Comparison of clinical features and oncologic outcomes between familial non-hereditary and hereditary breast cancer in Korean female patients. Asian J Surg 2020; 43:996-1001. [PMID: 31924417 DOI: 10.1016/j.asjsur.2019.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Revised: 11/04/2019] [Accepted: 12/02/2019] [Indexed: 10/25/2022] Open
Abstract
BACKGROUND The authors compared the clinical features between familial (non-hereditary) and hereditary breast cancer. And we also analyzed their oncologic outcomes to establish appropriate surveillance protocol for familial (non-hereditary) and hereditary breast cancer. METHODS Among 232 patients with breast cancer who were performed BRCA gene evaluation, twenty-eight patients were diagnosed as hereditary breast cancer with BRCA gene mutation and one-hundred and seventy-six patients were familial (non-hereditary) breast cancer. The clinical characteristics and oncologic outcomes were compared between two groups. RESULTS While the incidence of multifocality was higher in familial (non-hereditary) breast cancer group (p < 0.001), the bilaterality was higher in hereditary breast cancer group (p < 0.001). And the rate of pathologic complete remission was also significantly higher in hereditary breast cancer group (p = 0.030). The characteristics of tumor were different between familial (non-hereditary) breast cancer and hereditary breast cancer. The oncologic outcome was better in familial (non-hereditary) breast cancer group than hereditary breast cancer group except death. CONCLUSION The clinical characteristics of familial (non-hereditary) breast cancer were different from those of hereditary breast cancer but similar to those of sporadic breast cancer. The prognosis of the familial (non-hereditary) breast cancer was significantly better than hereditary breast cancer.
Collapse
Affiliation(s)
- Chan Sub Park
- Department of Surgery, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Ho Yong Park
- Department of Surgery, School of Medicine, Kyungpook National University, Daegu, Republic of Korea; Joint Institute for Regenerative Medicine, Kyungpook National University, Republic of Korea
| | - Jin Hyang Jung
- Department of Surgery, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Wan Wook Kim
- Department of Surgery, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Yee Soo Chae
- Department of Hemato-oncology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Soo Jung Lee
- Department of Hemato-oncology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Ji-Young Park
- Department of Pathology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jee Young Park
- Department of Pathology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea
| | - Jeeyeon Lee
- Department of Surgery, School of Medicine, Kyungpook National University, Daegu, Republic of Korea.
| |
Collapse
|
16
|
Ahmed Z, Zeeshan S, Mendhe D, Dong X. Human gene and disease associations for clinical-genomics and precision medicine research. Clin Transl Med 2020; 10:297-318. [PMID: 32508008 PMCID: PMC7240856 DOI: 10.1002/ctm2.28] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 04/02/2020] [Accepted: 04/03/2020] [Indexed: 12/15/2022] Open
Abstract
We are entering the era of personalized medicine in which an individual's genetic makeup will eventually determine how a doctor can tailor his or her therapy. Therefore, it is becoming critical to understand the genetic basis of common diseases, for example, which genes predispose and rare genetic variants contribute to diseases, and so on. Our study focuses on helping researchers, medical practitioners, and pharmacists in having a broad view of genetic variants that may be implicated in the likelihood of developing certain diseases. Our focus here is to create a comprehensive database with mobile access to all available, authentic and actionable genes, SNPs, and classified diseases and drugs collected from different clinical and genomics databases worldwide, including Ensembl, GenCode, ClinVar, GeneCards, DISEASES, HGMD, OMIM, GTR, CNVD, Novoseek, Swiss-Prot, LncRNADisease, Orphanet, GWAS Catalog, SwissVar, COSMIC, WHO, and FDA. We present a new cutting-edge gene-SNP-disease-drug mobile database with a smart phone application, integrating information about classified diseases and related genes, germline and somatic mutations, and drugs. Its database includes over 59 000 protein-coding and noncoding genes; over 67 000 germline SNPs and over a million somatic mutations reported for over 19 000 protein-coding genes located in over 1000 regions, published with over 3000 articles in over 415 journals available at the PUBMED; over 80 000 ICDs; over 123 000 NDCs; and over 100 000 classified gene-SNP-disease associations. We present an application that can provide new insights into the information about genetic basis of human complex diseases and contribute to assimilating genomic with phenotypic data for the availability of gene-based designer drugs, precise targeting of molecular fingerprints for tumor, appropriate drug therapy, predicting individual susceptibility to disease, diagnosis, and treatment of rare illnesses are all a few of the many transformations expected in the decade to come.
Collapse
Affiliation(s)
- Zeeshan Ahmed
- Institute for Health, Health Care Policy and Aging Research, RutgersThe State University of New JerseyNew BrunswickNew JerseyUSA
- Department of Medicine, Rutgers Robert Wood Johnson Medical SchoolRutgers Biomedical and Health SciencesNew BrunswickNew JerseyUSA
| | - Saman Zeeshan
- Rutgers Cancer Institute of New Jersey, RutgersThe State University of New JerseyNew BrunswickNew JerseyUSA
| | - Dinesh Mendhe
- Institute for Health, Health Care Policy and Aging Research, RutgersThe State University of New JerseyNew BrunswickNew JerseyUSA
| | - XinQi Dong
- Institute for Health, Health Care Policy and Aging Research, RutgersThe State University of New JerseyNew BrunswickNew JerseyUSA
- Department of Medicine, Rutgers Robert Wood Johnson Medical SchoolRutgers Biomedical and Health SciencesNew BrunswickNew JerseyUSA
| |
Collapse
|
17
|
Ageta H, Tsuchida K. Post-translational modification and protein sorting to small extracellular vesicles including exosomes by ubiquitin and UBLs. Cell Mol Life Sci 2019; 76:4829-4848. [PMID: 31363817 PMCID: PMC11105257 DOI: 10.1007/s00018-019-03246-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 07/06/2019] [Accepted: 07/23/2019] [Indexed: 02/06/2023]
Abstract
Exosomes, a type of small extracellular vesicles (sEVs), are secreted membrane vesicles that are derived from various cell types, including cancer cells, mesenchymal stem cells, and immune cells via multivesicular bodies (MVBs). These sEVs contain RNAs (mRNA, miRNA, lncRNA, and rRNA), lipids, DNA, proteins, and metabolites, all of which mediate cell-to-cell communication. This communication is known to be implicated in a diverse set of diseases such as cancers and their metastases and degenerative diseases. The molecular mechanisms, by which proteins are modified and sorted to sEVs, are not fully understood. Various cellular processes, including degradation, transcription, DNA repair, cell cycle, signal transduction, and autophagy, are known to be associated with ubiquitin and ubiquitin-like proteins (UBLs). Recent studies have revealed that ubiquitin and UBLs also regulate MVBs and protein sorting to sEVs. Ubiquitin-like 3 (UBL3)/membrane-anchored Ub-fold protein (MUB) acts as a post-translational modification (PTM) factor to regulate efficient protein sorting to sEVs. In this review, we focus on the mechanism of PTM by ubiquitin and UBLs and the pathway of protein sorting into sEVs and discuss the potential biological significance of these processes.
Collapse
Affiliation(s)
- Hiroshi Ageta
- Division for Therapies Against Intractable Diseases, Institute for Comprehensive Medical Science, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Kunihiro Tsuchida
- Division for Therapies Against Intractable Diseases, Institute for Comprehensive Medical Science, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| |
Collapse
|