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Sozzi S, Manni I, Ercolani C, Diodoro MG, Bartolazzi A, Spallotta F, Piaggio G, Monteonofrio L, Soddu S, Rinaldo C, Valente D. Inactivation of HIPK2 attenuates KRAS G12D activity and prevents pancreatic tumorigenesis. J Exp Clin Cancer Res 2024; 43:265. [PMID: 39342278 PMCID: PMC11437985 DOI: 10.1186/s13046-024-03189-3] [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: 05/31/2024] [Accepted: 09/11/2024] [Indexed: 10/01/2024] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) features KRAS mutations in approximately 90% of human cases and excessive stromal response, termed desmoplastic reaction. Oncogenic KRAS drives pancreatic carcinogenesis by acting on both epithelial cells and tumor microenvironment (TME). We have previously shown that Homeodomain-Interacting Protein Kinase 2 (HIPK2) cooperates with KRAS in sustaining ERK1/2 phosphorylation in human colorectal cancers. Here, we investigated whether HIPK2 contributes to oncogenic KRAS-driven tumorigenesis in vivo, in the onset of pancreatic cancer. METHODS We employed an extensively characterized model of KRASG12D-dependent preinvasive PDAC, the Pdx1-Cre;LSL-KRasG12D/+ (KC) mice. In these mice, HIPK2 was inhibited by genetic knockout in the pancreatic epithelial cells (KCH-/-) or by pharmacologic inactivation with the small molecule 5-IodoTubercidin (5-ITu). The development of preneoplastic acinar-to-ductal metaplasia (ADM), intraepithelial neoplasia (PanIN), and their associated desmoplastic reaction were analyzed. RESULTS In Hipk2-KO mice (KCH-/-), ERK phosphorylation was lowered, the appearance of ADM was slowed down, and both the number and pathologic grade of PanIN were reduced compared to Hipk2-WT KC mice. The pancreatic lesion phenotype in KCH-/- mice was characterized by abundant collagen fibers and reduced number of αSMA+ and pSTAT3+ desmoplastic cells. These features were reminiscent of the recently described human "deserted" sub-TME, poor in cells, rich in matrix, and associated with tumor differentiation. In contrast, the desmoplastic reaction of KC mice resembled the "reactive" sub-TME, rich in stromal cells and associated with tumor progression. These observations were confirmed by the pharmacologic inhibition of HIPK2 in KC mice. CONCLUSION This study demonstrates that HIPK2 inhibition weakens oncogenic KRAS activity and pancreatic tumorigenesis providing a rationale for testing HIPK2 inhibitors to mitigate the incidence of PDAC development in high-risk individuals.
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Affiliation(s)
- Silvia Sozzi
- Unit of Cellular Networks and Molecular Therapeutic Targets, IRCCS Regina Elena National Cancer Institute, Rome, Italy
- Department of Science, Roma Tre University, Rome, Italy
| | - Isabella Manni
- SAFU Unit, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Cristiana Ercolani
- Department of Pathology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Maria Grazia Diodoro
- Department of Pathology, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Armando Bartolazzi
- Pathology Research Laboratories, Sant'Andrea University Hospital, Rome, Italy
| | - Francesco Spallotta
- Department of Biology and Biotechnologies "Charles Darwin", Sapienza University, Rome, Italy
| | - Giulia Piaggio
- SAFU Unit, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Laura Monteonofrio
- Unit of Cellular Networks and Molecular Therapeutic Targets, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Silvia Soddu
- Unit of Cellular Networks and Molecular Therapeutic Targets, IRCCS Regina Elena National Cancer Institute, Rome, Italy
| | - Cinzia Rinaldo
- Unit of Cellular Networks and Molecular Therapeutic Targets, IRCCS Regina Elena National Cancer Institute, Rome, Italy.
- Institute of Molecular Biology and Pathology (IBPM), National Research Council (CNR), c/o Sapienza University, Rome, Italy.
| | - Davide Valente
- Unit of Cellular Networks and Molecular Therapeutic Targets, IRCCS Regina Elena National Cancer Institute, Rome, Italy.
- Institute of Molecular Biology and Pathology (IBPM), National Research Council (CNR), c/o Sapienza University, Rome, Italy.
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Oketch DJA, Giulietti M, Piva F. Copy Number Variations in Pancreatic Cancer: From Biological Significance to Clinical Utility. Int J Mol Sci 2023; 25:391. [PMID: 38203561 PMCID: PMC10779192 DOI: 10.3390/ijms25010391] [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: 11/24/2023] [Revised: 12/20/2023] [Accepted: 12/24/2023] [Indexed: 01/12/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer, characterized by high tumor heterogeneity and a poor prognosis. Inter- and intra-tumoral heterogeneity in PDAC is a major obstacle to effective PDAC treatment; therefore, it is highly desirable to explore the tumor heterogeneity and underlying mechanisms for the improvement of PDAC prognosis. Gene copy number variations (CNVs) are increasingly recognized as a common and heritable source of inter-individual variation in genomic sequence. In this review, we outline the origin, main characteristics, and pathological aspects of CNVs. We then describe the occurrence of CNVs in PDAC, including those that have been clearly shown to have a pathogenic role, and further highlight some key examples of their involvement in tumor development and progression. The ability to efficiently identify and analyze CNVs in tumor samples is important to support translational research and foster precision oncology, as copy number variants can be utilized to guide clinical decisions. We provide insights into understanding the CNV landscapes and the role of both somatic and germline CNVs in PDAC, which could lead to significant advances in diagnosis, prognosis, and treatment. Although there has been significant progress in this field, understanding the full contribution of CNVs to the genetic basis of PDAC will require further research, with more accurate CNV assays such as single-cell techniques and larger cohorts than have been performed to date.
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Affiliation(s)
| | - Matteo Giulietti
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
| | - Francesco Piva
- Department of Specialistic Clinical and Odontostomatological Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
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3
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DeVries AA, Dennis J, Tyrer JP, Peng PC, Coetzee SG, Reyes AL, Plummer JT, Davis BD, Chen SS, Dezem FS, Aben KKH, Anton-Culver H, Antonenkova NN, Beckmann MW, Beeghly-Fadiel A, Berchuck A, Bogdanova NV, Bogdanova-Markov N, Brenton JD, Butzow R, Campbell I, Chang-Claude J, Chenevix-Trench G, Cook LS, DeFazio A, Doherty JA, Dörk T, Eccles DM, Eliassen AH, Fasching PA, Fortner RT, Giles GG, Goode EL, Goodman MT, Gronwald J, Håkansson N, Hildebrandt MAT, Huff C, Huntsman DG, Jensen A, Kar S, Karlan BY, Khusnutdinova EK, Kiemeney LA, Kjaer SK, Kupryjanczyk J, Labrie M, Lambrechts D, Le ND, Lubiński J, May T, Menon U, Milne RL, Modugno F, Monteiro AN, Moysich KB, Odunsi K, Olsson H, Pearce CL, Pejovic T, Ramus SJ, Riboli E, Riggan MJ, Romieu I, Sandler DP, Schildkraut JM, Setiawan VW, Sieh W, Song H, Sutphen R, Terry KL, Thompson PJ, Titus L, Tworoger SS, Van Nieuwenhuysen E, Edwards DV, Webb PM, Wentzensen N, Whittemore AS, Wolk A, Wu AH, Ziogas A, Freedman ML, Lawrenson K, Pharoah PDP, Easton DF, Gayther SA, Jones MR. Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci. J Natl Cancer Inst 2022; 114:1533-1544. [PMID: 36210504 PMCID: PMC9949586 DOI: 10.1093/jnci/djac160] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/13/2022] [Accepted: 08/18/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort. METHODS Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types. RESULTS We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types. CONCLUSIONS CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.
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Grants
- P01 CA017054 NCI NIH HHS
- N01 CN025403 NCI NIH HHS
- UM1 CA176726 NCI NIH HHS
- R01 CA058860 NCI NIH HHS
- P50 CA105009 NCI NIH HHS
- R01-CA122443 NIH HHS
- 076113 Wellcome Trust
- G0401527 Medical Research Council
- U19-CA148112 NCI NIH HHS
- P50 CA136393 NCI NIH HHS
- C490/A10119 C490/A10124 Cancer Research UK
- 1000143 Medical Research Council
- R01-CA54419 NIH HHS
- C8221/A19170 Cancer Research UK
- R01 CA049449 NCI NIH HHS
- P50 CA159981 NCI NIH HHS
- T32 GM118288 NIGMS NIH HHS
- CA1X01HG007491-01 NIH HHS
- Z01-ES044005 NIEHS NIH HHS
- R01 CA106414 NCI NIH HHS
- R01 CA095023 NCI NIH HHS
- N01 PC067010 NCI NIH HHS
- P30 CA047904 NCI NIH HHS
- R01 CA058598 NCI NIH HHS
- U01 CA176726 NCI NIH HHS
- S10 RR025141 NCRR NIH HHS
- M01 RR000056 NCRR NIH HHS
- Department of Health
- 5T32GM118288-03 NIH HHS
- MR/N003284/1 Medical Research Council
- P30 CA014089 NCI NIH HHS
- K07-CA080668 NCI NIH HHS
- 14136 Cancer Research UK
- Worldwide Cancer Research
- MR_UU_12023 Medical Research Council
- R01 CA067262 NCI NIH HHS
- UM1 CA186107 NCI NIH HHS
- P30 CA015083 NCI NIH HHS
- G1000143 Medical Research Council
- R01 CA076016 NCI NIH HHS
- NHGRI NIH HHS
- P01 CA087969 NCI NIH HHS
- R01- CA61107 NCI NIH HHS
- R01-CA58598 NIH HHS
- U19 CA148112 NCI NIH HHS
- ULTR000445 NCATS NIH HHS
- R03 CA115195 NCI NIH HHS
- Wellcome Trust
- Breast Cancer Now
- R01 CA160669 NCI NIH HHS
- R01-CA058860 NIH HHS
- MC_UU_00004/01 Medical Research Council
- C570/A16491 Cancer Research UK
- R01-CA76016 NIH HHS
- R01-CA106414-A2 NIH HHS
- 001 World Health Organization
- Z01 ES049033 Intramural NIH HHS
- R01 CA126841 NCI NIH HHS
- MR/M012190/1 Medical Research Council
- 209057 Wellcome Trust
- R03 CA113148 NCI NIH HHS
- R01 CA149429 NCI NIH HHS
- National Institute of General Medical Sciences
- National Institutes of Health
- CSMC Precision Health Initiative
- Tell Every Amazing Lady About Ovarian Cancer Louisa M. McGregor Ovarian Cancer Foundation
- Ovarian Cancer Research Fund thanks
- National Cancer Institute
- National Human Genome Research Institute
- Canadian Institutes of Health Research
- Ovarian Cancer Research Fund
- European Commission’s Seventh Framework Programme
- Army Medical Research and Materiel Command
- National Health & Medical Research Council of Australia
- Cancer Councils of New South Wales, Victoria, Queensland, South Australia and Tasmania and Cancer Foundation of Western Australia
- Ovarian Cancer Australia
- Peter MacCallum Foundation
- University of Erlangen-Nuremberg
- National Kankerplan
- Breast Cancer Now, Institute of Cancer Research
- National Center for Advancing Translational Sciences
- European Commission
- International Agency for Research on Cancer
- Danish Cancer Society
- Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale
- Institut National de la Santé et de la Recherche Médicale
- German Cancer Aid; German Cancer Research Center
- Federal Ministry of Education and Research
- Hellenic Health Foundation
- Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy
- National Research Council
- Dutch Ministry of Public Health, Welfare and Sports
- Netherlands Cancer Registry
- LK Research Funds
- Dutch Prevention Funds
- World Cancer Research Fund
- Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health
- Health Research Fund
- Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra
- Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten
- German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research
- German Cancer Research Center
- Rudolf-Bartling Foundation
- Helsinki University Hospital Research Fund
- University of Pittsburgh School of Medicine Dean’s Faculty Advancement Award
- Department of Defense
- NCI
- Swedish Cancer Society, Swedish Research Council, Beta Kamprad Foundation
- Danish Cancer Society, Copenhagen
- Mayo Foundation
- Minnesota Ovarian Cancer Alliance
- Fred C. and Katherine B. Andersen Foundation
- VicHealth and Cancer Council Victoria, Cancer Council Victoria
- National Health and Medical Research Council of Australia
- NHMRC
- DOD Ovarian Cancer Research Program
- Moffitt Cancer Center
- Merck Pharmaceuticals
- Radboud University Medical Centre
- UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge
- National Institute of Environmental Health Sciences
- The Swedish Cancer Foundation
- the Swedish Research Council
- American Cancer Society
- Celma Mastry Ovarian Cancer Foundation
- Lon V Smith Foundation
- The Eve Appeal
- National Institute for Health Research University College London Hospitals Biomedical Research Centre
- California Cancer Research Program
- National Science Centre
- NIH
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Affiliation(s)
- Amber A DeVries
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jonathan P Tyrer
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Pei-Chen Peng
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Simon G Coetzee
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Alberto L Reyes
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jasmine T Plummer
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Applied Genomics, Computation and Translational Core, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Brian D Davis
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Applied Genomics, Computation and Translational Core, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Stephanie S Chen
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Applied Genomics, Computation and Translational Core, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Felipe Segato Dezem
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Katja K H Aben
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
- Netherlands Comprehensive Cancer Organisation, Utrecht, The Netherlands
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Natalia N Antonenkova
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
| | - Matthias W Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-European Metropolitan Region of Nuremberg, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
| | - Alicia Beeghly-Fadiel
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Andrew Berchuck
- Department of Gynecologic Oncology, Duke University Hospital, Durham, NC, USA
| | - Natalia V Bogdanova
- N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | | | - James D Brenton
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Ralf Butzow
- Department of Pathology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Ian Campbell
- Cancer Genetics Laboratory, Research Division, Peter MacCallum Cancer Center, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Georgia Chenevix-Trench
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Linda S Cook
- Epidemiology, School of Public Health, University of Colorado, Aurora, CO, USA
- Community Health Sciences, University of Calgary, Calgary, AB, Canada
| | - Anna DeFazio
- Centre for Cancer Research, The Westmead Institute for Medical Research, Sydney, New South Wales, Australia
- Department of Gynaecological Oncology, Westmead Hospital, Sydney, New South Wales, Australia
- The Daffodil Centre, a joint venture with Cancer Council NSW, The University of Sydney, Sydney, New South Wales, Australia
| | - Jennifer A Doherty
- Huntsman Cancer Institute, Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Diana M Eccles
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - A Heather Eliassen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Peter A Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-European Metropolitan Region of Nuremberg, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany
- David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA
| | - Renée T Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Ellen L Goode
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA
| | - Marc T Goodman
- Samuel Oschin Comprehensive Cancer Institute, Cancer Prevention and Genetics Program, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Jacek Gronwald
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Niclas Håkansson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Chad Huff
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - David G Huntsman
- Department of Obstetrics and Gynecology, University of British Columbia, Vancouver, BC, Canada
- Department of Molecular Oncology, BC Cancer Research Centre, Vancouver, BC, Canada
| | - Allan Jensen
- Department of Lifestyle, Reproduction and Cancer, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Siddhartha Kar
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Section of Translational Epidemiology, Division of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Beth Y Karlan
- David Geffen School of Medicine, Department of Obstetrics and Gynecology, University of California at Los Angeles, Los Angeles, CA, USA
| | - Elza K Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia
- Saint Petersburg State University, Saint Petersburg, Russia
| | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Susanne K Kjaer
- Department of Lifestyle, Reproduction and Cancer, Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Gynaecology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Jolanta Kupryjanczyk
- Department of Pathology and Laboratory Diagnostics, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Marilyne Labrie
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - Diether Lambrechts
- VIB Center for Cancer Biology, VIB, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Nhu D Le
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | - Jan Lubiński
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Taymaa May
- Division of Gynecologic Oncology, University Health Network, Princess Margaret Hospital, Toronto, Ontario, Canada
| | - Usha Menon
- MRC Clinical Trials Unit, Institute of Clinical Trials & Methodology, University College London, London, UK
| | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Francesmary Modugno
- Women's Cancer Research Center, Magee-Womens Research Institute and Hillman Cancer Center, Pittsburgh, PA, USA
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Alvaro N Monteiro
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Kirsten B Moysich
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Kunle Odunsi
- Department of Oncology, University of Chicago Medicine Comprehensive Cancer Center, Chicago, IL, USA
- Department of Obstetrics and Gynecology, University of Chicago Medicine Comprehensive Cancer Center, Chicago, IL, USA
| | - Håkan Olsson
- Oncology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Celeste L Pearce
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Tanja Pejovic
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
- Department of Obstetrics and Gynecology, Oregon Health & Science University, Portland, OR, USA
| | - Susan J Ramus
- School of Women's and Children's Health, Faculty of Medicine and Health, University of NSW Sydney, Sydney, New South Wales, Australia
- Adult Cancer Program, Lowy Cancer Research Centre, University of NSW Sydney, Sydney, New South Wales, Australia
| | | | - Marjorie J Riggan
- Department of Gynecologic Oncology, Duke University Hospital, Durham, NC, USA
| | - Isabelle Romieu
- Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Joellen M Schildkraut
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - V Wendy Setiawan
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Weiva Sieh
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Honglin Song
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Rebecca Sutphen
- Epidemiology Center, College of Medicine, University of South Florida, Tampa, FL, USA
| | - Kathryn L Terry
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Pamela J Thompson
- Samuel Oschin Comprehensive Cancer Institute, Cancer Prevention and Genetics Program, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Linda Titus
- Muskie School of Public Policy, Public Health, Portland, ME, USA
| | - Shelley S Tworoger
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Els Van Nieuwenhuysen
- Division of Gynecologic Oncology, Department of Gynecology and Obstetrics, Leuven Cancer Institute, Leuven, Belgium
| | - Digna Velez Edwards
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Department of Biomedical Sciences, Women's Health Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Penelope M Webb
- Population Health Department, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Nicolas Wentzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Alice S Whittemore
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Argyrios Ziogas
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA
| | - Matthew L Freedman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kate Lawrenson
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Women's Cancer Program at the Samuel Oschin Cancer Institute Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Simon A Gayther
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Michelle R Jones
- Center for Bioinformatics and Functional Genomics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
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Rupp B, Owen S, Ball H, Smith KJ, Gunchick V, Keller ET, Sahai V, Nagrath S. Integrated Workflow for the Label-Free Isolation and Genomic Analysis of Single Circulating Tumor Cells in Pancreatic Cancer. Int J Mol Sci 2022; 23:7852. [PMID: 35887203 PMCID: PMC9316651 DOI: 10.3390/ijms23147852] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/12/2022] [Accepted: 07/13/2022] [Indexed: 02/04/2023] Open
Abstract
As pancreatic cancer is the third deadliest cancer in the U.S., the ability to study genetic alterations is necessary to provide further insight into potentially targetable regions for cancer treatment. Circulating tumor cells (CTCs) represent an especially aggressive subset of cancer cells, capable of causing metastasis and progressing the disease. Here, we present the Labyrinth-DEPArray pipeline for the isolation and analysis of single CTCs. Established cell lines, patient-derived CTC cell lines and freshly isolated CTCs were recovered and sequenced to reveal single-cell copy number variations (CNVs). The resulting CNV profiles of established cell lines showed concordance with previously reported data and highlight several gains and losses of cancer-related genes such as FGFR3 and GNAS. The novel sequencing of patient-derived CTC cell lines showed gains in chromosome 8q, 10q and 17q across both CTC cell lines. The pipeline was used to process and isolate single cells from a metastatic pancreatic cancer patient revealing a gain of chromosome 1q and a loss of chromosome 5q. Overall, the Labyrinth-DEPArray pipeline offers a validated workflow combining the benefits of antigen-free CTC isolation with single cell genomic analysis.
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Affiliation(s)
- Brittany Rupp
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; (B.R.); (S.O.); (H.B.); (K.J.S.)
- BioInterface Institute, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Sarah Owen
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; (B.R.); (S.O.); (H.B.); (K.J.S.)
- BioInterface Institute, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Harrison Ball
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; (B.R.); (S.O.); (H.B.); (K.J.S.)
- BioInterface Institute, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Kaylee Judith Smith
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; (B.R.); (S.O.); (H.B.); (K.J.S.)
- BioInterface Institute, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Valerie Gunchick
- Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA; (V.G.); (V.S.)
| | - Evan T. Keller
- BioInterface Institute, University of Michigan, Ann Arbor, MI 48109, USA;
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Urology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Vaibhav Sahai
- Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA; (V.G.); (V.S.)
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sunitha Nagrath
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; (B.R.); (S.O.); (H.B.); (K.J.S.)
- BioInterface Institute, University of Michigan, Ann Arbor, MI 48109, USA;
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI 48109, USA
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5
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Tan M, Brusgaard K, Gerdes AM, Larsen MJ, Mortensen MB, Detlefsen S, de Muckadell OBS, Joergensen MT. Whole genome sequencing identifies rare genetic variants in familial pancreatic cancer patients. Ann Hum Genet 2022; 86:195-206. [PMID: 35312039 PMCID: PMC9313800 DOI: 10.1111/ahg.12464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/25/2022] [Accepted: 03/03/2022] [Indexed: 11/27/2022]
Affiliation(s)
- Ming Tan
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Department of Medical Gastroenterology, Odense University Hospital, Odense, Denmark.,Odense Pancreas Center (OPAC), Odense University Hospital, Odense, Denmark
| | - Klaus Brusgaard
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Anne-Marie Gerdes
- Department of Clinical Genetics, Rigshospitalet, Copenhagen, Denmark
| | - Martin Jakob Larsen
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Department of Clinical Genetics, Odense University Hospital, Odense, Denmark
| | - Michael Bau Mortensen
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Odense Pancreas Center (OPAC), Odense University Hospital, Odense, Denmark.,Department of Surgery, Odense University Hospital, Odense, Denmark
| | - Sönke Detlefsen
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Odense Pancreas Center (OPAC), Odense University Hospital, Odense, Denmark.,Department of Pathology, Odense University Hospital, Odense, Denmark
| | - Ove B Schaffalitzky de Muckadell
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Department of Medical Gastroenterology, Odense University Hospital, Odense, Denmark.,Odense Pancreas Center (OPAC), Odense University Hospital, Odense, Denmark
| | - Maiken Thyregod Joergensen
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark.,Department of Medical Gastroenterology, Odense University Hospital, Odense, Denmark.,Odense Pancreas Center (OPAC), Odense University Hospital, Odense, Denmark
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6
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Agaoglu NB, Unal B, Akgun Dogan O, Zolfagharian P, Sharifli P, Karakurt A, Can Senay B, Kizilboga T, Yildiz J, Dinler Doganay G, Doganay L. Determining the accuracy of next generation sequencing based copy number variation analysis in Hereditary Breast and Ovarian Cancer. Expert Rev Mol Diagn 2022; 22:239-246. [PMID: 35240897 DOI: 10.1080/14737159.2022.2048373] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 02/24/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND Copy number variations (CNVs) are commonly associated with malignancies, including hereditary breast and ovarian cancers. Next generation sequencing (NGS) provides solutions for CNV detection in a single run. This study aimed to compare the accuracy of CNV detection by NGS analyzing tool against Multiplex Ligation Dependent Probe Amplification (MLPA). RESEARCH DESIGN AND METHODS In total, 1276 cases were studied by targeted NGS panels and 691 cases (61 calls in 58 NGS-CNV positive and 633 NGS-CNV negative cases) were validated by MLPA. RESULTS Twenty-eight (46%) NGS-CNV positive calls were consistent, whereas 33 (54%) calls showed discordance with MLPA. Two cases were detected as SNV by the NGS and CNV by the MLPA analysis. In total, 2% of the cases showed an MLPA confirmed CNV region in BRCA1/2. The results of this study showed that despite the high false positive call rate of the NGS-CNV algorithm, there were no false negative calls. The cases that were determined to be negative by the NGS and positive by the MLPA were actually carrying SNVs that were located on the MLPA probe binding sites. CONCLUSION The diagnostic performance of NGS-CNV analysis is promising; however, the need for confirmation by different methods remains.
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Affiliation(s)
- Nihat Bugra Agaoglu
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
- Department of Medical Genetics, Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Busra Unal
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Ozlem Akgun Dogan
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
- Department of Pediatric Genetics, Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Payam Zolfagharian
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Pari Sharifli
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Aylin Karakurt
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Burak Can Senay
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Tugba Kizilboga
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
- Department of Molecular Biology and Genetics, Istanbul Technical University, Istanbul, Turkey
| | - Jale Yildiz
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
- Department of Molecular Biology and Genetics, Istanbul Technical University, Istanbul, Turkey
| | - Gizem Dinler Doganay
- Department of Molecular Biology and Genetics, Istanbul Technical University, Istanbul, Turkey
| | - Levent Doganay
- Genomic Laboratory (GLAB), Umraniye Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
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7
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Qin F, Luo X, Cai G, Xiao F. Shall genomic correlation structure be considered in copy number variants detection? Brief Bioinform 2021; 22:6295811. [PMID: 34114005 DOI: 10.1093/bib/bbab215] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 04/16/2021] [Accepted: 05/17/2021] [Indexed: 11/14/2022] Open
Abstract
Copy number variation has been identified as a major source of genomic variation associated with disease susceptibility. With the advent of whole-exome sequencing (WES) technology, massive WES data have been generated, allowing for the identification of copy number variants (CNVs) in the protein-coding regions with direct functional interpretation. We have previously shown evidence of the genomic correlation structure in array data and developed a novel chromosomal breakpoint detection algorithm, LDcnv, which showed significantly improved detection power through integrating the correlation structure in a systematic modeling manner. However, it remains unexplored whether the genomic correlation exists in WES data and how such correlation structure integration can improve the CNV detection accuracy. In this study, we first explored the correlation structure of the WES data using the 1000 Genomes Project data. Both real raw read depth and median-normalized data showed strong evidence of the correlation structure. Motivated by this fact, we proposed a correlation-based method, CORRseq, as a novel release of the LDcnv algorithm in profiling WES data. The performance of CORRseq was evaluated in extensive simulation studies and real data analysis from the 1000 Genomes Project. CORRseq outperformed the existing methods in detecting medium and large CNVs. In conclusion, it would be more advantageous to model genomic correlation structure in detecting relatively long CNVs. This study provides great insights for methodology development of CNV detection with NGS data.
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Affiliation(s)
- Fei Qin
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina (USC), Discovery 449, 915 Greene St, Columbia, SC 29208, USA
| | - Xizhi Luo
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, USC, Discovery 449, 915 Greene St, Columbia, SC 29208, USA
| | - Guoshuai Cai
- Department of Environmental Health Science, Arnold School of Public Health, USC, Discovery 449, 915 Greene St, Columbia, SC 29208, USA
| | - Feifei Xiao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, USC, Discovery 449, 915 Greene St, Columbia, SC 29208, USA
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8
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Luo X, Qin F, Cai G, Xiao F. Integrating genomic correlation structure improves copy number variations detection. Bioinformatics 2021; 37:312-317. [PMID: 32805016 DOI: 10.1093/bioinformatics/btaa737] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/23/2020] [Accepted: 08/12/2020] [Indexed: 12/16/2022] Open
Abstract
MOTIVATION Copy number variation plays important roles in human complex diseases. The detection of copy number variants (CNVs) is identifying mean shift in genetic intensities to locate chromosomal breakpoints, the step of which is referred to as chromosomal segmentation. Many segmentation algorithms have been developed with a strong assumption of independent observations in the genetic loci, and they assume each locus has an equal chance to be a breakpoint (i.e. boundary of CNVs). However, this assumption is violated in the genetics perspective due to the existence of correlation among genomic positions, such as linkage disequilibrium (LD). Our study showed that the LD structure is related to the location distribution of CNVs, which indeed presents a non-random pattern on the genome. To generate more accurate CNVs, we proposed a novel algorithm, LDcnv, that models the CNV data with its biological characteristics relating to genetic dependence structure (i.e. LD). RESULTS We theoretically demonstrated the correlation structure of CNV data in SNP array, which further supports the necessity of integrating biological structure in statistical methods for CNV detection. Therefore, we developed the LDcnv that integrated the genomic correlation structure with a local search strategy into statistical modeling of the CNV intensities. To evaluate the performance of LDcnv, we conducted extensive simulations and analyzed large-scale HapMap datasets. We showed that LDcnv presented high accuracy, stability and robustness in CNV detection and higher precision in detecting short CNVs compared to existing methods. This new segmentation algorithm has a wide scope of potential application with data from various high-throughput technology platforms. AVAILABILITY AND IMPLEMENTATION https://github.com/FeifeiXiaoUSC/LDcnv. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Xizhi Luo
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Fei Qin
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Guoshuai Cai
- Department of Environmental Health Science, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
| | - Feifei Xiao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
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9
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Xiao F, Luo X, Hao N, Niu YS, Xiao X, Cai G, Amos CI, Zhang H. An accurate and powerful method for copy number variation detection. Bioinformatics 2020; 35:2891-2898. [PMID: 30649252 DOI: 10.1093/bioinformatics/bty1041] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 11/28/2018] [Accepted: 01/09/2019] [Indexed: 12/12/2022] Open
Abstract
MOTIVATION Integration of multiple genetic sources for copy number variation detection (CNV) is a powerful approach to improve the identification of variants associated with complex traits. Although it has been shown that the widely used change point based methods can increase statistical power to identify variants, it remains challenging to effectively detect CNVs with weak signals due to the noisy nature of genotyping intensity data. We previously developed modSaRa, a normal mean-based model on a screening and ranking algorithm for copy number variation identification which presented desirable sensitivity with high computational efficiency. To boost statistical power for the identification of variants, here we present a novel improvement that integrates the relative allelic intensity with external information from empirical statistics with modeling, which we called modSaRa2. RESULTS Simulation studies illustrated that modSaRa2 markedly improved both sensitivity and specificity over existing methods for analyzing array-based data. The improvement in weak CNV signal detection is the most substantial, while it also simultaneously improves stability when CNV size varies. The application of the new method to a whole genome melanoma dataset identified novel candidate melanoma risk associated deletions on chromosome bands 1p22.2 and duplications on 6p22, 6q25 and 19p13 regions, which may facilitate the understanding of the possible roles of germline copy number variants in the etiology of melanoma. AVAILABILITY AND IMPLEMENTATION http://c2s2.yale.edu/software/modSaRa2 or https://github.com/FeifeiXiaoUSC/modSaRa2. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Feifei Xiao
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA
| | - Xizhi Luo
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA
| | - Ning Hao
- Department of Mathematics, University of Arizona, Tucson, AZ, USA
| | - Yue S Niu
- Department of Mathematics, University of Arizona, Tucson, AZ, USA
| | - Xiangjun Xiao
- Department of Quantitative Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Guoshuai Cai
- Department of Environmental Health Science, University of South Carolina, Columbia, SC, USA
| | - Christopher I Amos
- Department of Quantitative Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Heping Zhang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
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10
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Principe DR, Rana A. Updated risk factors to inform early pancreatic cancer screening and identify high risk patients. Cancer Lett 2020; 485:56-65. [PMID: 32389710 DOI: 10.1016/j.canlet.2020.04.022] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 04/06/2020] [Accepted: 04/23/2020] [Indexed: 02/07/2023]
Abstract
Pancreatic adenocarcinoma (PDAC) is associated with poor clinical outcomes and incomplete responses to conventional therapy. Therefore, there is an unmet clinical need to better understand the predisposing factors for pancreatic cancer in hopes of providing early screening to high-risk patients. While select risk factors such as age, race, and family history, or predisposing syndromes are unavoidable, there are several new and established risk factors that allow for intervention, namely by counseling patients to make the appropriate lifestyle modifications. Here, we discuss the best-studied risk factors for PDAC such as tobacco use and chronic pancreatitis, as well as newly emerging risk factors including select nutritional deficits, bacterial infections, and psychosocial factors. As several of these risk factors appear to be additive or synergistic, by understanding their relationships and offering coordinated, multidisciplinary care to high-risk patients, it may be possible to reduce pancreatic cancer incidence and improve clinical outcomes through early detection.
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Affiliation(s)
- Daniel R Principe
- Medical Scientist Training Program, University of Illinois College of Medicine, Chicago, IL, USA; Department of Surgery, Division of Surgical Oncology, University of Illinois at Chicago, Chicago, IL, USA.
| | - Ajay Rana
- Department of Surgery, Division of Surgical Oncology, University of Illinois at Chicago, Chicago, IL, USA; Jesse Brown VA Medical Center, Chicago, IL, USA.
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11
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Augereau C, Collet L, Vargiu P, Guerra C, Ortega S, Lemaigre FP, Jacquemin P. Chronic pancreatitis and lipomatosis are associated with defective function of ciliary genes in pancreatic ductal cells. Hum Mol Genet 2018; 25:5017-5026. [PMID: 28159992 DOI: 10.1093/hmg/ddw332] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2016] [Revised: 09/23/2016] [Accepted: 09/25/2016] [Indexed: 12/18/2022] Open
Abstract
Genetic diseases associated with defects in primary cilia are classified as ciliopathies. Pancreatic lesions and ductal cysts are found in patients with ciliopathic polycystic kidney diseases suggesting a close connection between pancreatic defects and primary cilia. Here we investigate the role of two genes whose deletion is known to cause primary cilium defects, namely Hnf6 and Lkb1, in pancreatic ductal homeostasis. We find that mice with postnatal duct-specific deletion of Hnf6 or Lkb1 show duct dilations. Cells lining dilated ducts present shorter cilia with swollen tips, suggesting defective intraciliary transport. This is associated with signs of chronic pancreatitis, namely acinar-to-ductal metaplasia, acinar proliferation and apoptosis, presence of inflammatory infiltrates, fibrosis and lipomatosis. Our data reveal a tight association between ductal ciliary defects and pancreatitis with perturbed acinar homeostasis and differentiation. Such injuries can account for the increased risk to develop pancreatic cancer in Peutz-Jeghers patients who carry LKB1 loss-of-function mutations.
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Affiliation(s)
- Cécile Augereau
- Université catholique de Louvain, de Duve Institute, Brussels, Belgium
| | - Louis Collet
- Université catholique de Louvain, de Duve Institute, Brussels, Belgium
| | - Pierfrancesco Vargiu
- Transgenic Mice Core Unit, Spanish National Cancer Research Center (CNIO), Madrid, Spain
| | - Carmen Guerra
- Molecular Oncology, Centro Nacional de Investigaciones Oncológicas, Madrid, Spain
| | - Sagrario Ortega
- Transgenic Mice Core Unit, Spanish National Cancer Research Center (CNIO), Madrid, Spain
| | | | - Patrick Jacquemin
- Université catholique de Louvain, de Duve Institute, Brussels, Belgium
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12
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Kumaran M, Cass CE, Graham K, Mackey JR, Hubaux R, Lam W, Yasui Y, Damaraju S. Germline copy number variations are associated with breast cancer risk and prognosis. Sci Rep 2017; 7:14621. [PMID: 29116104 PMCID: PMC5677082 DOI: 10.1038/s41598-017-14799-7] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 10/16/2017] [Indexed: 12/14/2022] Open
Abstract
Breast cancer is one of the most common cancers among women, and susceptibility is explained by genetic, lifestyle and environmental components. Copy Number Variants (CNVs) are structural DNA variations that contribute to diverse phenotypes via gene-dosage effects or cis-regulation. In this study, we aimed to identify germline CNVs associated with breast cancer susceptibility and their relevance to prognosis. We performed whole genome CNV genotyping in 422 cases and 348 controls using Human Affymetrix SNP 6 array. Principal component analysis for population stratification revealed 84 outliers leaving 366 cases and 320 controls of Caucasian ancestry for association analysis; CNVs with frequency > 10% and overlapping with protein coding genes were considered for breast cancer risk and prognostic relevance. Coding genes within the CNVs identified were interrogated for gene- dosage effects by correlating copy number status with gene expression profiles in breast tumor tissue. We identified 200 CNVs associated with breast cancer (q-value < 0.05). Of these, 21 CNV regions (overlapping with 22 genes) also showed association with prognosis. We validated representative CNVs overlapping with APOBEC3B and GSTM1 genes using the TaqMan assay. Germline CNVs conferred dosage effects on gene expression in breast tissue. The candidate CNVs identified in this study warrant independent replication.
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Affiliation(s)
- Mahalakshmi Kumaran
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada
| | - Carol E Cass
- Department of Oncology, University of Alberta, Edmonton, Alberta, Canada
| | - Kathryn Graham
- Department of Oncology, University of Alberta, Edmonton, Alberta, Canada
| | - John R Mackey
- Department of Oncology, University of Alberta, Edmonton, Alberta, Canada
| | - Roland Hubaux
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Wan Lam
- Department of Integrative Oncology, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Yutaka Yasui
- School of Public Health, University of Alberta, Edmonton, Alberta, Canada
| | - Sambasivarao Damaraju
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada. .,Cross Cancer Institute, Alberta Health Services, Edmonton, AB, Canada.
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13
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Shi J, Zhou W, Zhu B, Hyland PL, Bennett H, Xiao Y, Zhang X, Burke LS, Song L, Hsu CH, Yan C, Chen Q, Meerzaman D, Dagnall CL, Burdette L, Hicks B, Freedman ND, Chanock SJ, Yeager M, Tucker MA, Goldstein AM, Yang XR. Rare Germline Copy Number Variations and Disease Susceptibility in Familial Melanoma. J Invest Dermatol 2016; 136:2436-2443. [PMID: 27476724 PMCID: PMC5123914 DOI: 10.1016/j.jid.2016.07.023] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Revised: 06/02/2016] [Accepted: 07/05/2016] [Indexed: 01/12/2023]
Abstract
Mounting evidence suggests that copy number variations (CNVs) can contribute to cancer susceptibility. The main goal of this study was to evaluate the role of germline CNVs in melanoma predisposition in high-risk melanoma families. We used genome-wide tiling comparative genomic hybridization and single nucleotide polymorphism arrays to characterize CNVs in 335 individuals (240 melanoma cases) from American melanoma-prone families (22 with germline CDKN2A or CDK4 mutations). We found that the global burden of overall CNVs (or deletions or duplications separately) was not significantly associated with case-control or CDKN2A/CDK4 mutation status after accounting for the familial dependence. However, we identified several rare CNVs that either involved known melanoma genes (e.g., PARP1, CDKN2A) or cosegregated with melanoma (duplication on 10q23.23, 3p12.2 and deletions on 8q424.3, 2q22.1) in families without mutations in known melanoma high-risk genes. Some of these CNVs were correlated with expression changes in disrupted genes based on RNASeq data from a subset of melanoma cases included in the CNV study. These results suggest that rare cosegregating CNVs may influence melanoma susceptibility in some melanoma-prone families and genes found in our study warrant further evaluation in future genetic analyses of melanoma.
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Affiliation(s)
- Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Weiyin Zhou
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Bin Zhu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Paula L Hyland
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Hunter Bennett
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Yanzi Xiao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Xijun Zhang
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Laura S Burke
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA; Statistics Collaborative, Inc., Washington, DC, USA
| | - Lei Song
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Chih Hao Hsu
- Computational Genomics Research Group, Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, Maryland, USA
| | - Chunhua Yan
- Computational Genomics Research Group, Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, Maryland, USA
| | - Qingrong Chen
- Computational Genomics Research Group, Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, Maryland, USA
| | - Daoud Meerzaman
- Computational Genomics Research Group, Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, Maryland, USA
| | - Casey L Dagnall
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Laurie Burdette
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Belynda Hicks
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Meredith Yeager
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Margaret A Tucker
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Alisa M Goldstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA
| | - Xiaohong R Yang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, DHHS, Bethesda, Maryland, USA.
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Verma M. Genome-wide association studies and epigenome-wide association studies go together in cancer control. Future Oncol 2016; 12:1645-64. [PMID: 27079684 PMCID: PMC5551540 DOI: 10.2217/fon-2015-0035] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2015] [Accepted: 03/22/2016] [Indexed: 02/07/2023] Open
Abstract
Completion of the human genome a decade ago laid the foundation for: using genetic information in assessing risk to identify individuals and populations that are likely to develop cancer, and designing treatments based on a person's genetic profiling (precision medicine). Genome-wide association studies (GWAS) completed during the past few years have identified risk-associated single nucleotide polymorphisms that can be used as screening tools in epidemiologic studies of a variety of tumor types. This led to the conduct of epigenome-wide association studies (EWAS). This article discusses the current status, challenges and research opportunities in GWAS and EWAS. Information gained from GWAS and EWAS has potential applications in cancer control and treatment.
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Affiliation(s)
- Mukesh Verma
- Methods & Technologies Branch, Epidemiology & Genomics Research Program, Division of Cancer Control & Population Sciences, National Cancer Institute (NCI), NIH, 9609 Medical Center Drive, Suite 4E102, Rockville, MD 20850, USA
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15
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Atkinson EJ, Eckel-Passow JE, Wang A, Greenberg AJ, Scott CG, Pankratz VS, Purrington KN, Sellers TA, Rider DN, Heit JA, de Andrade M, Cunningham JM, Couch FJ, Vachon CM. The association of copy number variation and percent mammographic density. BMC Res Notes 2015; 8:297. [PMID: 26152678 PMCID: PMC4494822 DOI: 10.1186/s13104-015-1212-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Accepted: 05/22/2015] [Indexed: 11/10/2022] Open
Abstract
Background Percent mammographic density (PD) estimates the proportion of stromal, fat, and epithelial breast tissues on the mammogram image. Adjusted for age and body mass index (BMI), PD is one of the strongest risk factors for breast cancer [1]. Inherited factors are hypothesized to explain between 30 and 60% of the variance in this trait [2–5]. However, previously identified common genetic variants account for less than 6% of the variance in PD, leaving much of the genetic contribution to this trait unexplained. We performed the first study to examine whether germline copy number variation (CNV) are associated with PD. Two genome-wide association studies (GWAS) of percent density conducted on the Illumina 660W-Quad were used to identify and replicate the association between candidate CNVs and PD: the Minnesota Breast Cancer Family Study (MBCFS) and controls from the Mayo Venous Thromboembolism (Mayo VTE) Case–Control Study, with 585 and 328 women, respectively. Linear models were utilized to examine the association of each probe with PD, adjusted for age, menopausal status and BMI. Segmentation was subsequently performed on the probe-level test statistics to identify candidate CNV regions that were associated with PD. Results Sixty-one probes from five chromosomal regions [3q26.1 (2 regions), 8q24.22, 11p15.3, and 17q22] were significantly associated with PD in MBCFS (p-values <0.0001). A CNV at 3q26.1 showed the greatest evidence for association with PD; a region without any known SNPs. Conversely, the CNV at 17q22 was largely due to the association between SNPs and PD in the region. SNPs in the 8q24.22 region have been shown to be associated with risk of many cancers; however, SNPs in this region were not responsible for the observed CNV association. While we were unable to replicate the associations with PD, two of the five CNVs (3q26.1 and 11p15.3) were also observed in the Mayo VTE controls. Conclusions CNVs may help to explain some of the variability in PD that is currently unexplained by SNPs. While we were able to replicate the existence of two CNVs across the two GWAS studies, we were unable to replicate the associations with PD. Even so, the proximity of the identified CNV regions to loci known to be associated with breast cancer risk suggests further investigation and potentially shared genetic mechanisms underlying the PD and breast cancer association. Electronic supplementary material The online version of this article (doi:10.1186/s13104-015-1212-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elizabeth J Atkinson
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Jeanette E Eckel-Passow
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Alice Wang
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Alexandra J Greenberg
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Christopher G Scott
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - V Shane Pankratz
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Kristen N Purrington
- Wayne State University School of Medicine and Karmanos Cancer Institute, Detroit, MI, USA.
| | - Thomas A Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA.
| | - David N Rider
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - John A Heit
- Division of Cardiovascular Disease, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
| | - Mariza de Andrade
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Julie M Cunningham
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA.
| | - Fergus J Couch
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA.
| | - Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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16
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Moir-Meyer GL, Pearson JF, Lose F, Scott RJ, McEvoy M, Attia J, Holliday EG, Pharoah PD, Dunning AM, Thompson DJ, Easton DF, Spurdle AB, Walker LC. Rare germline copy number deletions of likely functional importance are implicated in endometrial cancer predisposition. Hum Genet 2015; 134:269-78. [PMID: 25381466 DOI: 10.1007/s00439-014-1507-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2014] [Accepted: 10/29/2014] [Indexed: 01/15/2023]
Abstract
Endometrial cancer is the most common invasive gynaecological cancer in women, and relatively little is known about inherited risk factors for this disease. This is the first genome-wide study to explore the role of common and rare germline copy number variants (CNVs) in predisposition to endometrial cancer. CNVs were called from germline DNA of 1,209 endometrioid endometrial cancer cases and 528 cancer-unaffected female controls. Overall CNV load of deletions or DNA gains did not differ significantly between cases and controls (P > 0.05), but cases presented with an excess of rare germline deletions overlapping likely functional genomic regions including genes (P = 8 × 10(-10)), CpG islands (P = 1 × 10(-7)) and sno/miRNAs regions (P = 3 × 10(-9)). On average, at least one additional gene and two additional CpG islands were disrupted by rare deletions in cases compared to controls. The most pronounced difference was that over 30 sno/miRNAs were disrupted by rare deletions in cases for every single disruption event in controls. A total of 13 DNA repair genes were disrupted by rare deletions in 19/1,209 cases (1.6%) compared to one gene in 1/528 controls (0.2%; P = 0.007), and this increased DNA repair gene loss in cases persisted after excluding five individuals carrying CNVs disrupting mismatch repair genes MLH1, MSH2 and MSH6 (P = 0.03). There were 34 miRNA regions deleted in at least one case but not in controls, the most frequent of which encompassed hsa-mir-661 and hsa-mir-203. Our study implicates rare germline deletions of functional and regulatory regions as possible mechanisms conferring endometrial cancer risk, and has identified specific regulatory elements as candidates for further investigation.
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Affiliation(s)
- Gemma L Moir-Meyer
- Mackenzie Cancer Research Group, Department of Pathology, University of Otago, Christchurch, New Zealand,
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17
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Sapkota Y. Germline DNA variations in breast cancer predisposition and prognosis: a systematic review of the literature. Cytogenet Genome Res 2014; 144:77-91. [PMID: 25401968 DOI: 10.1159/000369045] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2014] [Indexed: 11/19/2022] Open
Abstract
Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The disease is caused by a combination of genetic, environmental, lifestyle, and reproductive risk factors. Linkage and family-based studies have identified many pathological germline mutations, which account for around 20% of the genetic risk of familial breast cancer. In recent years, single nucleotide polymorphism-based genetic association studies, especially genome-wide association studies (GWASs), have been very successful in uncovering low-penetrance common variants associated with breast cancer risk. These common variants alone may explain up to an additional 30% of the familial risk of breast cancer. With the advent of available genetic resources and growing collaborations among researchers across the globe, the much needed large sample size to capture variants with small effect sizes and low population frequencies is being addressed, and hence many more common variants are expected to be discovered in the coming days. Here, major GWASs conducted for breast cancer predisposition and prognosis until 2013 are summarized. Few studies investigating other forms of genetic variations contributing to breast cancer predisposition and disease outcomes are also discussed. Finally, the potential utility of the GWAS-identified variants in disease risk models and some future perspectives are presented.
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Affiliation(s)
- Yadav Sapkota
- The Neurogenetics Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Qld., Australia
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18
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Association of melanoma with intraepithelial neoplasia of the pancreas in three patients. Exp Mol Pathol 2014; 97:144-7. [DOI: 10.1016/j.yexmp.2014.06.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Accepted: 06/27/2014] [Indexed: 12/20/2022]
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19
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Ding X, Tsang SY, Ng SK, Xue H. Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk. GENOMICS INSIGHTS 2014. [PMID: 26203258 PMCID: PMC4504076 DOI: 10.4137/gei.s15002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
In the present study, recurrent copy number variations (CNVs) from non-tumor blood cell DNAs of Caucasian non-cancer subjects and glioma, myeloma, and colorectal cancer-patients, and Korean non-cancer subjects and hepatocellular carcinoma, gastric cancer, and colorectal cancer patients, were found to reveal for each of the two ethnic cohorts highly significant differences between cancer patients and controls with respect to the number of CN-losses and size-distribution of CN-gains, suggesting the existence of recurrent constitutional CNV-features useful for prediction of predisposition to cancer. Upon identification by machine learning, such CNV-features could extensively discriminate between cancer-patient and control DNAs. When the CNV-features selected from a learning-group of Caucasian or Korean mixed DNAs consisting of both cancer-patient and control DNAs were employed to make predictions on the cancer predisposition of an unseen test group of mixed DNAs, the average prediction accuracy was 93.6% for the Caucasian cohort and 86.5% for the Korean cohort.
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Affiliation(s)
- Xiaofan Ding
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Shui-Ying Tsang
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Siu-Kin Ng
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Hong Xue
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
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20
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Familial Pancreatic Cancer: Challenging Diagnostic Approach and Therapeutic Management. J Gastrointest Cancer 2014; 45:256-61. [DOI: 10.1007/s12029-014-9609-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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21
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Willis JA, Mukherjee S, Orlow I, Viale A, Offit K, Kurtz RC, Olson SH, Klein RJ. Genome-wide analysis of the role of copy-number variation in pancreatic cancer risk. Front Genet 2014; 5:29. [PMID: 24592275 PMCID: PMC3923159 DOI: 10.3389/fgene.2014.00029] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2013] [Accepted: 01/26/2014] [Indexed: 12/20/2022] Open
Abstract
Although family history is a risk factor for pancreatic adenocarcinoma, much of the genetic etiology of this disease remains unknown. While genome-wide association studies have identified some common single nucleotide polymorphisms (SNPs) associated with pancreatic cancer risk, these SNPs do not explain all the heritability of this disease. We hypothesized that copy number variation (CNVs) in the genome may play a role in genetic predisposition to pancreatic adenocarcinoma. Here, we report a genome-wide analysis of CNVs in a small hospital-based, European ancestry cohort of pancreatic cancer cases and controls. Germline CNV discovery was performed using the Illumina Human CNV370 platform in 223 pancreatic cancer cases (both sporadic and familial) and 169 controls. Following stringent quality control, we asked if global CNV burden was a risk factor for pancreatic cancer. Finally, we performed in silico CNV genotyping and association testing to discover novel CNV risk loci. When we examined the global CNV burden, we found no strong evidence that CNV burden plays a role in pancreatic cancer risk either overall or specifically in individuals with a family history of the disease. Similarly, we saw no significant evidence that any particular CNV is associated with pancreatic cancer risk. Taken together, these data suggest that CNVs do not contribute substantially to the genetic etiology of pancreatic cancer, though the results are tempered by small sample size and large experimental variability inherent in array-based CNV studies.
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Affiliation(s)
- Jason A Willis
- Department of Medicine, Memorial Sloan-Kettering Cancer Center New York, NY, USA ; Program in Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center New York, NY, USA
| | - Semanti Mukherjee
- Program in Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center New York, NY, USA
| | - Irene Orlow
- Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center New York, NY, USA
| | - Agnes Viale
- Genomics Core Laboratory, Memorial Sloan-Kettering Cancer Center New York, NY, USA
| | - Kenneth Offit
- Department of Medicine, Memorial Sloan-Kettering Cancer Center New York, NY, USA ; Program in Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center New York, NY, USA
| | - Robert C Kurtz
- Department of Medicine, Memorial Sloan-Kettering Cancer Center New York, NY, USA
| | - Sara H Olson
- Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center New York, NY, USA
| | - Robert J Klein
- Department of Medicine, Memorial Sloan-Kettering Cancer Center New York, NY, USA ; Program in Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center New York, NY, USA
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22
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Abstract
Beset by poor prognosis, pancreatic ductal adenocarcinoma is classified as familial or sporadic. This review elaborates on the known genetic syndromes that underlie familial pancreatic cancer, where there are opportunities for genetic counseling and testing as well as clinical monitoring of at-risk patients. Such subsets of familial pancreatic cancer involve germline cationic trypsinogen or PRSS1 mutations (hereditary pancreatitis), BRCA2 mutations (usually in association with hereditary breast-ovarian cancer syndrome), CDKN2 mutations (familial atypical mole and multiple melanoma), or DNA repair gene mutations (e.g., ATM and PALB2, apart from those in BRCA2). However, the vast majority of familial pancreatic cancer cases have yet to have their genetic underpinnings elucidated, waiting in part for the results of deep sequencing efforts.
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Affiliation(s)
- Anil K. Rustgi
- Division of Gastroenterology, Department of Medicine and Genetics, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
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23
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Fang Y, Yao Q, Chen Z, Xiang J, William FE, Gibbs RA, Chen C. Genetic and molecular alterations in pancreatic cancer: implications for personalized medicine. Med Sci Monit 2013; 19:916-26. [PMID: 24172537 PMCID: PMC3818103 DOI: 10.12659/msm.889636] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Recent advances in human genomics and biotechnologies have profound impacts on medical research and clinical practice. Individual genomic information, including DNA sequences and gene expression profiles, can be used for prediction, prevention, diagnosis, and treatment for many complex diseases. Personalized medicine attempts to tailor medical care to individual patients by incorporating their genomic information. In a case of pancreatic cancer, the fourth leading cause of cancer death in the United States, alteration in many genes as well as molecular profiles in blood, pancreas tissue, and pancreas juice has recently been discovered to be closely associated with tumorigenesis or prognosis of the cancer. This review aims to summarize recent advances of important genes, proteins, and microRNAs that play a critical role in the pathogenesis of pancreatic cancer, and to provide implications for personalized medicine in pancreatic cancer.
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Affiliation(s)
- Yantian Fang
- Molecular Surgeon Research Center, Division of Surgical Research, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, U.S.A. and Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, P.R. China
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24
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Husain K, Centeno BA, Chen DT, Fulp WJ, Perez M, Zhang Lee G, Luetteke N, Hingorani SR, Sebti SM, Malafa MP. Prolonged survival and delayed progression of pancreatic intraepithelial neoplasia in LSL-KrasG12D/+;Pdx-1-Cre mice by vitamin E δ-tocotrienol. Carcinogenesis 2013; 34:858-63. [PMID: 23302291 DOI: 10.1093/carcin/bgt002] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The highly lethal nature of pancreatic cancer and the increasing recognition of high-risk individuals have made research into chemoprevention a high priority. Here, we tested the chemopreventive activity of δ-tocotrienol, a bioactive vitamin E derivative extracted from palm fruit, in the LSL-Kras(G12D/+);Pdx-1-Cre pancreatic cancer mouse model. At 10 weeks of age, mice (n = 92) were randomly allocated to three groups: (i) no treatment; (ii) vehicle and (iii) δ-tocotrienol (200mg/kg × 2/day, PO). Treatment was continued for 12 months. Mice treated with δ-tocotrienol showed increased median survival from the onset of treatment (11.1 months) compared with vehicle-treated mice (9.7 months) and non-treated mice (8.5 months; P < 0.025). Importantly, none of the mice treated with δ-tocotrienol harbored invasive cancer compared with 10% and 8% in vehicle-treated and non-treated mice, respectively. Furthermore, δ-tocotrienol treatment also resulted in significant suppression of mouse pancreatic intraepithelial neoplasm (mPanIN) progression compared with vehicle-treated and non-treated mice: mPanIN-1: 47-50% (P < 0.09), mPanIN-2: 6-11% (P < 0.001), mPanIN-3: 3-15% (P < 0.001) and invasive cancer: 0-10% (P < 0.001). δ-Tocotrienol treatment inhibited mutant Kras-driven pathways such as MEK/ERK, PI3K/AKT and NF-kB/p65, as well as Bcl-xL and induced p27. δ-Tocotrienol also induced biomarkers of apoptosis such as Bax and activated caspase 3 along with an increase in plasma levels of CK18. In summary, δ-tocotrienol's ability to interfere with oncogenic Kras pathways coupled with the observed increase in median survival and significant delay in PanIN progression highlights the chemopreventative potential of δ-tocotrienol and warrants further investigation of this micronutrient in individuals at high risk for pancreatic cancer.
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Affiliation(s)
- Kazim Husain
- Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA
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