1
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Kim M, Huda MN, Evans LW, Que E, Gertz ER, Maeda-Smithies N, Bennett BJ. Integrative analysis of hepatic transcriptional profiles reveals genetic regulation of atherosclerosis in hyperlipidemic Diversity Outbred-F1 mice. Sci Rep 2023; 13:9475. [PMID: 37301941 PMCID: PMC10257719 DOI: 10.1038/s41598-023-35917-8] [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: 05/16/2022] [Accepted: 05/25/2023] [Indexed: 06/12/2023] Open
Abstract
Atherogenesis is an insipidus but precipitating process leading to serious consequences of many cardiovascular diseases (CVD). Numerous genetic loci contributing to atherosclerosis have been identified in human genome-wide association studies, but these studies have limitations in the ability to control environmental factors and to decipher cause/effect relationships. To assess the power of hyperlipidemic Diversity Outbred (DO) mice in facilitating quantitative trait loci (QTL) analysis of complex traits, we generated a high-resolution genetic panel of atherosclerosis susceptible (DO-F1) mouse cohort by crossing 200 DO females with C57BL/6J males carrying two human genes: encoding apolipoprotein E3-Leiden and cholesterol ester transfer protein. We examined atherosclerotic traits including plasma lipids and glucose in the 235 female and 226 male progeny before and after 16 weeks of a high-fat/cholesterol diet, and aortic plaque size at 24 weeks. We also assessed the liver transcriptome using RNA-sequencing. Our QTL mapping for atherosclerotic traits identified one previously reported female-specific QTL on Chr10 with a narrower interval of 22.73 to 30.80 Mb, and one novel male-specific QTL at 31.89 to 40.25 Mb on Chr19. Liver transcription levels of several genes within each QTL were highly correlated with the atherogenic traits. A majority of these candidates have already known atherogenic potential in humans and/or mice, but integrative QTL, eQTL, and correlation analyses further pointed Ptprk as a major candidate of the Chr10 QTL, while Pten and Cyp2c67 of the Chr19 QTL in our DO-F1 cohort. Finally, through additional analyses of RNA-seq data we identified genetic regulation of hepatic transcription factors, including Nr1h3, contributes to atherogenesis in this cohort. Thus, an integrative approach using DO-F1 mice effectively validates the influence of genetic factors on atherosclerosis in DO mice and suggests an opportunity to discover therapeutics in the setting of hyperlipidemia.
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Affiliation(s)
- Myungsuk Kim
- Department of Nutrition, University of California, Davis, CA, USA
- Korea Institute of Science and Technology (KIST), Gangneung, Gangwon-Do, Republic of Korea
- Division of Bio-Medical Science and Technology, KIST School, University of Science and Technology (UST), Seoul, 02792, Republic of Korea
| | - M Nazmul Huda
- Department of Nutrition, University of California, Davis, CA, USA
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Levi W Evans
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Excel Que
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Erik R Gertz
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA
| | - Nobuyo Maeda-Smithies
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brian J Bennett
- Department of Nutrition, University of California, Davis, CA, USA.
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA, USA.
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2
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Bosenberg M, Liu ET, Yu CI, Palucka K. Mouse models for immuno-oncology. Trends Cancer 2023:S2405-8033(23)00041-9. [PMID: 37087398 DOI: 10.1016/j.trecan.2023.03.009] [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: 02/27/2023] [Revised: 03/20/2023] [Accepted: 03/29/2023] [Indexed: 04/24/2023]
Abstract
Realizing the clinical promise of cancer immunotherapy is hindered by gaps in our knowledge of in vivo mechanisms underlying treatment response as well as treatment limiting toxicity. Preclinical in vivo model systems and technologies are required to address these knowledge gaps and to surmount the challenges faced in the clinical application of immunotherapy. Mice are commonly used for basic and translational research to support development and testing of immune interventions, including for cancer. Here, we discuss the advantages and the limitations of current models as well as future developments.
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Affiliation(s)
- Marcus Bosenberg
- Department of Dermatology, Yale School of Medicine, New Haven, CT, USA.
| | - Edison T Liu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; The Jackson Laboratory Cancer Center, Bar Harbor, ME, USA.
| | - Chun I Yu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; The Jackson Laboratory Cancer Center, Bar Harbor, ME, USA
| | - Karolina Palucka
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; The Jackson Laboratory Cancer Center, Bar Harbor, ME, USA.
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3
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Zhang X, Wang M, Zhang Y, Yang J, Duan W. Knockdown of CENPU inhibits cervical cancer cell migration and stemness through the FOXM1/Wnt/β-catenin pathway. Tissue Cell 2023; 81:102009. [PMID: 36608638 DOI: 10.1016/j.tice.2022.102009] [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: 08/12/2022] [Revised: 12/21/2022] [Accepted: 12/22/2022] [Indexed: 12/26/2022]
Abstract
Currently, the clinical outcome of cervical cancer (CC) is still undesirable, and it is urgent to explore more treatment strategies for CC. In this study, the effects of CENPU on migration and stemness of CC was studied. The CENPU expression were retrieved from The Cancer Genome Atlas (TCGA). The effects of CENPU on the viability and proliferation of cells were evaluated by CCK-8 assay and colony formation assay. Wound healing assay and invasion assay were chosen to assess migration and invasion of cells. Tumorsphere-forming assay was applied for testing the stemness. Western blot analysis was applied for assessing the level of CENPU, Nanog, Oct4, FOXM1, β-catenin, c-myc and MMP-7. The tumor sizes and volumes were also measured. The TCGA data and WB assay suggested that CENPU was upregulated in CC. CENPU knockdown would inhibit the viability of CC cells and prohibit the migration and invasion of cells. Tumorsphere-forming assay and WB results suggested that CENPU silencing decreased the sphere formation rate and the expression of Nanog and Oct4. Moreover, CENPU knockdown suppressed the expression of FOXM1, β-catenin, c-myc and MMP-7 by WB. In vivo study demonstrated that CENPU knockdown inhibited the growth of CC, indicated by reduced sizes and volumes of CC. In summary, our results suggested that knockdown of CENPU inhibited CC migration and stemness through the FOXM1/Wnt/β-catenin pathway.
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Affiliation(s)
- Xia Zhang
- Department of Pathology, Zhaoqing Medical College, Zhaoqing, Guangdong 526020, China
| | - Min Wang
- Department of Pathology, Zhaoqing Medical College, Zhaoqing, Guangdong 526020, China
| | - Yuanyi Zhang
- Department of Pathology, Zhaoqing Medical College, Zhaoqing, Guangdong 526020, China
| | - Jian Yang
- Department of Pathology, Zhaoqing Medical College, Zhaoqing, Guangdong 526020, China
| | - Wenbiao Duan
- Department of anatomy Zhaoqing Medical College, Zhaoqing, Guangdong 526020, China.
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4
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Yu Q, Liu X, Keller MP, Navarrete-Perea J, Zhang T, Fu S, Vaites LP, Shuken SR, Schmid E, Keele GR, Li J, Huttlin EL, Rashan EH, Simcox J, Churchill GA, Schweppe DK, Attie AD, Paulo JA, Gygi SP. Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression. Nat Commun 2023; 14:555. [PMID: 36732331 PMCID: PMC9894840 DOI: 10.1038/s41467-023-36269-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 01/20/2023] [Indexed: 02/04/2023] Open
Abstract
Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.
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Affiliation(s)
- Qing Yu
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Xinyue Liu
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Mark P Keller
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | | | - Tian Zhang
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Sipei Fu
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Laura P Vaites
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Steven R Shuken
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Ernst Schmid
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
| | | | - Jiaming Li
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Edward L Huttlin
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Edrees H Rashan
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Judith Simcox
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | | | - Devin K Schweppe
- Department of Genome Sciences, University of Washington, Seattle, WA, 98105, USA
| | - Alan D Attie
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA.
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5
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Welch DR, Foster C, Rigoutsos I. Roles of mitochondrial genetics in cancer metastasis. Trends Cancer 2022; 8:1002-1018. [PMID: 35915015 PMCID: PMC9884503 DOI: 10.1016/j.trecan.2022.07.004] [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: 06/02/2022] [Revised: 06/27/2022] [Accepted: 07/07/2022] [Indexed: 01/31/2023]
Abstract
The contributions of mitochondria to cancer have been recognized for decades. However, the focus on the metabolic role of mitochondria and the diminutive size of the mitochondrial genome compared to the nuclear genome have hindered discovery of the roles of mitochondrial genetics in cancer. This review summarizes recent data demonstrating the contributions of mitochondrial DNA (mtDNA) copy-number variants (CNVs), somatic mutations, and germline polymorphisms to cancer initiation, progression, and metastasis. The goal is to summarize accumulating data to establish a framework for exploring the contributions of mtDNA to neoplasia and metastasis.
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Affiliation(s)
- Danny R Welch
- Department of Cancer Biology, The Kansas University Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA; Department of Internal Medicine (Hematology/Oncology), The Kansas University Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA; Department of Molecular and Integrative Physiology, The Kansas University Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA; Department of Pathology, The Kansas University Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA; The University of Kansas Comprehensive Cancer Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA.
| | - Christian Foster
- Department of Cancer Biology, The Kansas University Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA
| | - Isidore Rigoutsos
- Computational Medicine Center, Sidney Kimmel College of Medicine, Thomas Jefferson University, 1020 Locust Street, Suite M81, Philadelphia, PA 19107, USA
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6
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Devlin R, Roberts E. Building a healthy mouse model ecosystem to interrogate cancer biology. Dis Model Mech 2022; 15:276587. [PMID: 36098988 PMCID: PMC9509886 DOI: 10.1242/dmm.049795] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
In a recent study, Sargent et al. characterise several novel Rag1-/- mouse strains and demonstrate that genetic background strongly influences xenograft development and phenotype. Here, we discuss this work within the broader context of cancer mouse modelling. We argue that new technologies will enable insights into how specific models align with human disease states and that this knowledge can be used to develop a diverse ecosystem of complementary mouse models of cancer. By utilising these diverse, well-characterised models to provide multiple perspectives on specific cancers, it should be possible to reduce the inappropriate attrition of sound hypotheses while protecting against false positives. Furthermore, careful re-introduction of biological variation, be that through outbred populations, environmental diversity or including animals of both sexes, can ensure that results are more broadly applicable and are less impacted by particular traits of homogeneous experimental populations. Thus, careful characterisation and judicious use of an array of mouse models provides an opportunity to address some of the issues surrounding both the reproducibility and translatability crises often referenced in pre-clinical cancer research.
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Affiliation(s)
- Ryan Devlin
- Beatson Institute for Cancer Research, University of Glasgow, Glasgow G61 1BD, UK
| | - Ed Roberts
- Beatson Institute for Cancer Research, University of Glasgow, Glasgow G61 1BD, UK.,Institute of Cancer Sciences, University of Glasgow, Glasgow G61 1QH, UK
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7
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Hackett J, Gibson H, Frelinger J, Buntzman A. Using the Collaborative Cross and Diversity Outbred Mice in Immunology. Curr Protoc 2022; 2:e547. [PMID: 36066328 PMCID: PMC9612550 DOI: 10.1002/cpz1.547] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
The Collaborative Cross (CC) and the Diversity Outbred (DO) stock mouse panels are the most powerful murine genetics tools available to the genetics community. Together, they combine the strength of inbred animal models with the diversity of outbred populations. Using the 63 CC strains or a panel of DO mice, each derived from the same 8 parental mouse strains, researchers can map genetic contributions to exceptionally complex immunological and infectious disease traits that would require far greater powering if performed by genome-wide association studies (GWAS) in human populations. These tools allow genes to be studied in heterozygous and homozygous states and provide a platform to study epistasis between interacting loci. Most importantly, once a quantitative phenotype is investigated and quantitative trait loci are identified, confirmatory genetic studies can be performed, which is often problematic using the GWAS approach. In addition, novel stable mouse models for immune phenotypes are often derived from studies utilizing the DO and CC mice that can serve as stronger model systems than existing ones in the field. The CC/DO systems have contributed to the fields of cancer immunology, autoimmunity, vaccinology, infectious disease, allergy, tissue rejection, and tolerance but have thus far been greatly underutilized. In this article, we present a recent review of the field and point out key areas of immunology that are ripe for further investigation and awaiting new CC/DO research projects. We also highlight some of the strong computational tools that have been developed for analyzing CC/DO genetic and phenotypic data. Additionally, we have formed a centralized community on the CyVerse infrastructure where immunogeneticists can utilize those software tools, collaborate with groups across the world, and expand the use of the CC and DO systems for investigating immunogenetic phenomena. © 2022 Wiley Periodicals LLC.
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Affiliation(s)
- Justin Hackett
- Barbara Ann Karmanos Cancer Institute, Hudson-Webber Cancer Research Center, Detroit, Michigan
| | - Heather Gibson
- Barbara Ann Karmanos Cancer Institute, Hudson-Webber Cancer Research Center, Detroit, Michigan
| | - Jeffrey Frelinger
- University of Arizona, Valley Fever Center for Excellence, Tucson, Arizona
- Department of Microbiology and Immunology, University of North Carolina System, Chapel Hill, North Carolina
| | - Adam Buntzman
- University of Arizona, BIO5 Institute, Valley Fever Center for Excellence, Tucson, Arizona
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8
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Neuner SM, Telpoukhovskaia M, Menon V, O'Connell KMS, Hohman TJ, Kaczorowski CC. Translational approaches to understanding resilience to Alzheimer's disease. Trends Neurosci 2022; 45:369-383. [PMID: 35307206 PMCID: PMC9035083 DOI: 10.1016/j.tins.2022.02.005] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 02/07/2022] [Accepted: 02/23/2022] [Indexed: 10/18/2022]
Abstract
Individuals who maintain cognitive function despite high levels of Alzheimer's disease (AD)-associated pathology are said to be 'resilient' to AD. Identifying mechanisms underlying resilience represents an exciting therapeutic opportunity. Human studies have identified a number of molecular and genetic factors associated with resilience, but the complexity of these cohorts prohibits a complete understanding of which factors are causal or simply correlated with resilience. Genetically and phenotypically diverse mouse models of AD provide new and translationally relevant opportunities to identify and prioritize new resilience mechanisms for further cross-species investigation. This review will discuss insights into resilience gained from both human and animal studies and highlight future approaches that may help translate these insights into therapeutics designed to prevent or delay AD-related dementia.
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Affiliation(s)
- Sarah M Neuner
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | | | - Vilas Menon
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Kristen M S O'Connell
- The Jackson Laboratory, Bar Harbor, ME 04609, USA; Tufts University, School of Medicine, Graduate School of Biomedical Sciences, Boston, MA 02111, USA; The University of Maine, Graduate School of Biomedical Science and Engineering, Orono, ME 04469, USA
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN 37232, USA; Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Catherine C Kaczorowski
- The Jackson Laboratory, Bar Harbor, ME 04609, USA; Tufts University, School of Medicine, Graduate School of Biomedical Sciences, Boston, MA 02111, USA; The University of Maine, Graduate School of Biomedical Science and Engineering, Orono, ME 04469, USA.
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9
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Hackett JB, Glassbrook JE, Muñiz MC, Bross M, Fielder A, Dyson G, Movahhedin N, McCasland J, McCarthy-Leo C, Gibson HM. A diversity outbred F1 mouse model identifies host-intrinsic genetic regulators of response to immune checkpoint inhibitors. Oncoimmunology 2022; 11:2064958. [PMID: 35481286 PMCID: PMC9037414 DOI: 10.1080/2162402x.2022.2064958] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Immune checkpoint inhibitors (ICI) have improved outcomes for a variety of malignancies; however, many patients fail to benefit. While tumor-intrinsic mechanisms are likely involved in therapy resistance, it is unclear to what extent host genetic background influences response. To investigate this, we utilized the Diversity Outbred (DO) and Collaborative Cross (CC) mouse models. DO mice are an outbred stock generated by crossbreeding eight inbred founder strains, and CC mice are recombinant inbred mice generated from the same eight founders. We generated 207 DOB6F1 mice representing 48 DO dams and demonstrated that these mice reliably accept the C57BL/6-syngeneic B16F0 tumor and that host genetic background influences response to ICI. Genetic linkage analysis from 142 mice identified multiple regions including one within chromosome 13 that associated with therapeutic response. We utilized 6 CC strains bearing the positive (NZO) or negative (C57BL/6) driver genotype in this locus. We found that 2/3 of predicted responder CCB6F1 crosses show reproducible ICI response. The chromosome 13 locus contains the murine prolactin family, which is a known immunomodulating cytokine associated with various autoimmune disorders. To directly test whether prolactin influences ICI response rates, we implanted inbred C57BL/6 mice with subcutaneous slow-release prolactin pellets to induce mild hyperprolactinemia. Prolactin augmented ICI response against B16F0, with increased CD8 infiltration and 5/8 mice exhibiting slowed tumor growth relative to controls. This study highlights the role of host genetics in ICI response and supports the use of F1 crosses in the DO and CC mouse populations as powerful cancer immunotherapy models.
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Affiliation(s)
- Justin B. Hackett
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - James E. Glassbrook
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
- Department of Biochemistry Microbiology Immunology, Wayne State University, Detroit, MI, USA
| | - Maria C. Muñiz
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Madeline Bross
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Abigail Fielder
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Gregory Dyson
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Nasrin Movahhedin
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Jennifer McCasland
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
| | - Claire McCarthy-Leo
- Center for Molecular Medicine and Genetics, Wayne State University, Detroit, MI, USA
| | - Heather M. Gibson
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI, USA
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10
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Iglesias-Carres L, Neilson AP. Utilizing preclinical models of genetic diversity to improve translation of phytochemical activities from rodents to humans and inform personalized nutrition. Food Funct 2021; 12:11077-11105. [PMID: 34672309 DOI: 10.1039/d1fo02782d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Mouse models are an essential tool in different areas of research, including nutrition and phytochemical research. Traditional inbred mouse models have allowed the discovery of therapeutical targets and mechanisms of action and expanded our knowledge of health and disease. However, these models lack the genetic variability typically found in human populations, which hinders the translatability of the results found in mice to humans. The development of genetically diverse mouse models, such as the collaborative cross (CC) or the diversity outbred (DO) models, has been a useful tool to overcome this obstacle in many fields, such as cancer, immunology and toxicology. However, these tools have not yet been widely adopted in the field of phytochemical research. As demonstrated in other disciplines, use of CC and DO models has the potential to provide invaluable insights for translation of phytochemicals from rodents to humans, which are desperately needed given the challenges and numerous failed clinical trials in this field. These models may prove informative for personalized use of phytochemicals in humans, including: predicting interindividual variability in phytochemical bioavailability and efficacy, identifying genetic loci or genes governing response to phytochemicals, identifying phytochemical mechanisms of action and therapeutic targets, and understanding the impact of genetic variability on individual response to phytochemicals. Such insights would prove invaluable for personalized implementation of phytochemicals in humans. This review will focus on the current work performed with genetically diverse mouse populations, and the research opportunities and advantages that these models can offer to phytochemical research.
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Affiliation(s)
- Lisard Iglesias-Carres
- Plants for Human Health Institute, Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Kannapolis, NC, USA.
| | - Andrew P Neilson
- Plants for Human Health Institute, Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Kannapolis, NC, USA.
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11
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Morra A, Escala-Garcia M, Beesley J, Keeman R, Canisius S, Ahearn TU, Andrulis IL, Anton-Culver H, Arndt V, Auer PL, Augustinsson A, Beane Freeman LE, Becher H, Beckmann MW, Behrens S, Bojesen SE, Bolla MK, Brenner H, Brüning T, Buys SS, Caan B, Campa D, Canzian F, Castelao JE, Chang-Claude J, Chanock SJ, Cheng TYD, Clarke CL, Colonna SV, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Dennis J, Dörk T, Dossus L, Dunning AM, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Eriksson M, Evans DG, Fasching PA, Flyger H, Fritschi L, Gago-Dominguez M, García-Sáenz JA, Giles GG, Grip M, Guénel P, Gündert M, Hahnen E, Haiman CA, Håkansson N, Hall P, Hamann U, Hart SN, Hartikainen JM, Hartmann A, He W, Hooning MJ, Hoppe R, Hopper JL, Howell A, Hunter DJ, Jager A, Jakubowska A, Janni W, John EM, Jung AY, Kaaks R, Keupers M, Kitahara CM, Koutros S, Kraft P, Kristensen VN, Kurian AW, Lacey JV, Lambrechts D, Le Marchand L, Lindblom A, Linet M, Luben RN, Lubiński J, Lush M, Mannermaa A, Manoochehri M, Margolin S, Martens JWM, Martinez ME, Mavroudis D, Michailidou K, Milne RL, Mulligan AM, Muranen TA, Nevanlinna H, Newman WG, Nielsen SF, Nordestgaard BG, Olshan AF, Olsson H, Orr N, Park-Simon TW, Patel AV, Peissel B, Peterlongo P, Plaseska-Karanfilska D, Prajzendanc K, Prentice R, Presneau N, Rack B, Rennert G, Rennert HS, Rhenius V, Romero A, Roylance R, Ruebner M, Saloustros E, Sawyer EJ, Schmutzler RK, Schneeweiss A, Scott C, Shah M, Smichkoska S, Southey MC, Stone J, Surowy H, Swerdlow AJ, Tamimi RM, Tapper WJ, Teras LR, Terry MB, Tollenaar RAEM, Tomlinson I, Troester MA, Truong T, Vachon CM, Wang Q, Hurson AN, Winqvist R, Wolk A, Ziogas A, Brauch H, García-Closas M, Pharoah PDP, Easton DF, Chenevix-Trench G, Schmidt MK. Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment. Breast Cancer Res 2021; 23:86. [PMID: 34407845 PMCID: PMC8371820 DOI: 10.1186/s13058-021-01450-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Accepted: 06/28/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients. METHODS We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15). RESULTS Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy. CONCLUSIONS We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.
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Affiliation(s)
- Anna Morra
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, 1066 CX The Netherlands
| | - Maria Escala-Garcia
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, 1066 CX The Netherlands
| | - Jonathan Beesley
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland Australia
| | - Renske Keeman
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, 1066 CX The Netherlands
| | - Sander Canisius
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, 1066 CX The Netherlands
- Division of Molecular Carcinogenesis, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - Thomas U. Ahearn
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Irene L. Andrulis
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Fred A. Litwin Center for Cancer Genetics, Toronto, ON Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON Canada
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA USA
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Paul L. Auer
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA USA
- Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI USA
| | - Annelie Augustinsson
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Laura E. Beane Freeman
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Heiko Becher
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthias W. Beckmann
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stig E. Bojesen
- Copenhagen University Hospital, Copenhagen General Population Study, Herlev and Gentofte Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Manjeet K. Bolla
- Department of Public Health and Primary Care, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Research Center (DKFZ), German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Thomas Brüning
- Institute of the Ruhr University Bochum (IPA), Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Bochum, Germany
| | - Saundra S. Buys
- Department of Medicine, Huntsman Cancer Institute, Salt Lake City, UT USA
| | - Bette Caan
- Division of Research, Kaiser Permanente, Oakland, CA USA
| | - Daniele Campa
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Biology, University of Pisa, Pisa, Italy
| | - Federico Canzian
- German Cancer Research Center (DKFZ), Genomic Epidemiology Group, Heidelberg, Germany
| | - Jose E. Castelao
- Instituto de Investigacion Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Oncology and Genetics Unit, Vigo, Spain
| | - 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
| | - Stephen J. Chanock
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Ting-Yuan David Cheng
- Division of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY USA
| | - Christine L. Clarke
- Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales Australia
| | - Sarah V. Colonna
- Department of Medicine, Huntsman Cancer Institute, Salt Lake City, UT USA
| | - Fergus J. Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN USA
| | - Angela Cox
- Department of Oncology and Metabolism, University of Sheffield, Sheffield Institute for Nucleic Acids (SInFoNiA), Sheffield, UK
| | - Simon S. Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Mary B. Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA USA
| | - Joe Dennis
- Department of Public Health and Primary Care, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Laure Dossus
- Nutrition and Metabolism Section, International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Alison M. Dunning
- Department of Oncology, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Miriam Dwek
- School of Life Sciences, University of Westminster, London, UK
| | - Diana M. Eccles
- Faculty of Medicine, University of Southampton, Southampton, UK
| | - Arif B. Ekici
- Institute of Human Genetics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - A. Heather Eliassen
- Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Channing Division of Network Medicine, Boston, MA USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - D. Gareth Evans
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- St Mary’s Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester, UK
| | - Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
- Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, David Geffen School of Medicine, Los Angeles, CA USA
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Lin Fritschi
- School of Public Health, Curtin University, Perth, Western Australia Australia
| | - Manuela Gago-Dominguez
- Galician Public Foundation of Genomic Medicine (FPGMX), Genomic Medicine Group, International Cancer Genetics and Epidemiology Group, Health Research Institute of Santiago (IDIS), Santiago de Compostela, Spain
- University of California San Diego, Moores Cancer Center, La Jolla, CA USA
| | - José A. García-Sáenz
- Instituto de Investigación Sanitaria San Carlos (IdISSC), Centro Investigación Biomédica en Red de Cáncer (CIBERONC), Medical Oncology Department, Hospital Clínico San Carlos, Madrid, Spain
| | - 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
| | - Mervi Grip
- Department of Surgery, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Pascal Guénel
- Team Exposome and Heredity, INSERM, University Paris-Saclay, Center for Research in Epidemiology and Population Health (CESP), Villejuif, France
| | - Melanie Gündert
- Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Molecular Biology of Breast Cancer, University Womens Clinic Heidelberg, University of Heidelberg, Heidelberg, Germany
- German Research Center for Environmental Health, Institute of Diabetes Research, Helmholtz Zentrum München, Neuherberg, Germany
| | - Eric Hahnen
- Faculty of Medicine and University Hospital Cologne, Center for Familial Breast and Ovarian Cancer, University of Cologne, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, Center for Integrated Oncology (CIO), University of Cologne, Cologne, Germany
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Niclas Håkansson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Steven N. Hart
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Jaana M. Hartikainen
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
| | - Arndt Hartmann
- Institute of Pathology, Comprehensive Cancer Center Erlangen Nuremberg, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Wei He
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Maartje J. Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Reiner Hoppe
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria Australia
| | - Anthony Howell
- Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - David J. Hunter
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - kConFab Investigators
- Research Department, Peter MacCallum Cancer Center, Melbourne, Victoria Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria Australia
| | - Agnes Jager
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
- Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland
| | - Wolfgang Janni
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Esther M. John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA USA
| | - Audrey Y. Jung
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Machteld Keupers
- Department of Radiation Oncology, University Hospitals Leuven, , University of Leuven, Leuven, Belgium
| | - Cari M. Kitahara
- Division of Cancer Epidemiology and Genetics, Radiation Epidemiology Branch, National Cancer Institute, Bethesda, MD USA
| | - Stella Koutros
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Vessela N. Kristensen
- Faculty of Medicine, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Allison W. Kurian
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA USA
- Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA USA
| | - James V. Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA USA
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA USA
| | - Diether Lambrechts
- VIB Center for Cancer Biology, Leuven, Belgium
- Laboratory for Translational Genetics, Department of Human Genetics, University of Leuven, Leuven, Belgium
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI USA
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Martha Linet
- Division of Cancer Epidemiology and Genetics, Radiation Epidemiology Branch, National Cancer Institute, Bethesda, MD USA
| | - Robert N. Luben
- Clinical Gerontology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jan Lubiński
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Michael Lush
- Department of Public Health and Primary Care, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Arto Mannermaa
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Biobank of Eastern Finland, Kuopio, Finland
| | - Mehdi Manoochehri
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sara Margolin
- Department of Oncology, Södersjukhuset, Stockholm, Sweden
- Department of Clinical Science and Education, Karolinska Institutet, Södersjukhuset, Stockholm, Sweden
| | - John W. M. Martens
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Maria Elena Martinez
- University of California San Diego, Moores Cancer Center, La Jolla, CA USA
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA USA
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece
| | - Kyriaki Michailidou
- Department of Public Health and Primary Care, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
- The Cyprus Institute of Neurology & Genetics, Cyprus School of Molecular Medicine, Nicosia, Cyprus
| | - 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
| | - Anna Marie Mulligan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON Canada
- University Health Network, Laboratory Medicine Program, Toronto, ON Canada
| | - Taru A. Muranen
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - William G. Newman
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- St Mary’s Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester, UK
| | - Sune F. Nielsen
- Copenhagen University Hospital, Copenhagen General Population Study, Herlev and Gentofte Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Børge G. Nordestgaard
- Copenhagen University Hospital, Copenhagen General Population Study, Herlev and Gentofte Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Andrew F. Olshan
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Håkan Olsson
- Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Nick Orr
- Centre for Cancer Research and Cell Biology, Queen’s University Belfast, Belfast, Northern Ireland, UK
| | | | - Alpa V. Patel
- Department of Population Science, American Cancer Society, Atlanta, GA USA
| | - Bernard Peissel
- Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM - the FIRC Institute of Molecular Oncology, Milan, Italy
| | - Dijana Plaseska-Karanfilska
- MASA, Research Centre for Genetic Engineering and Biotechnology ‘Georgi D. Efremov’, Skopje, Republic of North Macedonia
| | - Karolina Prajzendanc
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Ross Prentice
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA USA
| | - Nadege Presneau
- School of Life Sciences, University of Westminster, London, UK
| | - Brigitte Rack
- Department of Gynaecology and Obstetrics, University Hospital Ulm, Ulm, Germany
| | - Gad Rennert
- Carmel Medical Center and Technion Faculty of Medicine, Clalit National Cancer Control Center, Haifa, Israel
| | - Hedy S. Rennert
- Carmel Medical Center and Technion Faculty of Medicine, Clalit National Cancer Control Center, Haifa, Israel
| | - Valerie Rhenius
- Department of Oncology, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Atocha Romero
- Medical Oncology Department, Hospital Universitario Puerta de Hierro, Madrid, Spain
| | | | - Matthias Ruebner
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | | | - Elinor J. Sawyer
- School of Cancer & Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy’s Campus, King’s College London, London, UK
| | - Rita K. Schmutzler
- Faculty of Medicine and University Hospital Cologne, Center for Familial Breast and Ovarian Cancer, University of Cologne, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, Center for Integrated Oncology (CIO), University of Cologne, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne, University of Cologne, Center for Molecular Medicine Cologne (CMMC), Cologne, Germany
| | - Andreas Schneeweiss
- Molecular Biology of Breast Cancer, University Womens Clinic Heidelberg, University of Heidelberg, Heidelberg, Germany
- University Hospital and German Cancer Research Center, National Center for Tumor Diseases, Heidelberg, Germany
| | - Christopher Scott
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Mitul Shah
- Department of Oncology, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Snezhana Smichkoska
- Medical Faculty, University Clinic of Radiotherapy and Oncology, Ss. Cyril and Methodius University in Skopje, Skopje, Republic of North Macedonia
| | - Melissa C. Southey
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria Australia
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria Australia
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria Australia
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth, Western Australia Australia
| | - Harald Surowy
- Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Molecular Biology of Breast Cancer, University Womens Clinic Heidelberg, University of Heidelberg, Heidelberg, Germany
| | - Anthony J. Swerdlow
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
- Division of Breast Cancer Research, The Institute of Cancer Research, London, UK
| | - Rulla M. Tamimi
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY USA
| | | | - Lauren R. Teras
- Department of Population Science, American Cancer Society, Atlanta, GA USA
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY USA
| | | | - Ian Tomlinson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
- University of Oxford, Wellcome Trust Centre for Human Genetics and Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Melissa A. Troester
- Department of Epidemiology, Gillings School of Global Public Health and UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Thérèse Truong
- Team Exposome and Heredity, INSERM, University Paris-Saclay, Center for Research in Epidemiology and Population Health (CESP), Villejuif, France
| | - Celine M. Vachon
- Department of Health Science Research, Division of Epidemiology, Mayo Clinic, Rochester, MN USA
| | - Qin Wang
- Department of Public Health and Primary Care, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Amber N. Hurson
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu, Finland
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Argyrios Ziogas
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA USA
| | - Hiltrud Brauch
- Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany
- iFIT-Cluster of Excellence, University of Tübingen, Tübingen, Germany
- German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK) Partner Site Tübingen, Tübingen, Germany
| | - Montserrat García-Closas
- Department of Health and Human Services, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD USA
| | - Paul D. P. Pharoah
- Department of Public Health and Primary Care, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
- Department of Oncology, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Douglas F. Easton
- Department of Public Health and Primary Care, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
- Department of Oncology, University of Cambridge, Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Georgia Chenevix-Trench
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland Australia
| | - Marjanka K. Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, 1066 CX The Netherlands
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
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Glenny EM, Coleman MF, Giles ED, Wellberg EA, Hursting SD. Designing Relevant Preclinical Rodent Models for Studying Links Between Nutrition, Obesity, Metabolism, and Cancer. Annu Rev Nutr 2021; 41:253-282. [PMID: 34357792 DOI: 10.1146/annurev-nutr-120420-032437] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Diet and nutrition are intricately related to cancer prevention, growth, and treatment response. Preclinical rodent models are a cornerstone to biomedical research and remain instrumental in our understanding of the relationship between cancer and diet and in the development of effective therapeutics. However, the success rate of translating promising findings from the bench to the bedside is suboptimal. Well-designed rodent models will be crucial to improving the impact basic science has on clinical treatment options. This review discusses essential experimental factors to consider when designing a preclinical cancer model with an emphasis on incorporating these models into studies interrogating diet, nutrition, and metabolism. The aims of this review are to (a) provide insight into relevant considerations when designing cancer models for obesity, nutrition, and metabolism research; (b) identify common pitfalls when selecting a rodent model; and (c) discuss strengths and limitations of available preclinical models. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Elaine M Glenny
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;
| | - Michael F Coleman
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;
| | - Erin D Giles
- Department of Nutrition, Texas A&M University, College Station, Texas 77843, USA
| | - Elizabeth A Wellberg
- Department of Pathology, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma 73104, USA
| | - Stephen D Hursting
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA; .,Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA.,Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina 28081, USA
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13
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Que E, James KL, Coffey AR, Smallwood TL, Albright J, Huda MN, Pomp D, Sethupathy P, Bennett BJ. Genetic architecture modulates diet-induced hepatic mRNA and miRNA expression profiles in Diversity Outbred mice. Genetics 2021; 218:6321522. [PMID: 34849860 PMCID: PMC8757298 DOI: 10.1093/genetics/iyab068] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 07/27/2020] [Indexed: 11/30/2022] Open
Abstract
Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Finally, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility
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Affiliation(s)
- Excel Que
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA 95616, USA.,Department of Nutrition, University of California, Davis, Davis, CA 95616, USA
| | - Kristen L James
- Department of Nutrition, University of California, Davis, Davis, CA 95616, USA
| | - Alisha R Coffey
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 28081, USA
| | - Tangi L Smallwood
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 28081, USA
| | - Jody Albright
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC 28081, USA
| | - M Nazmul Huda
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA 95616, USA.,Department of Nutrition, University of California, Davis, Davis, CA 95616, USA
| | - Daniel Pomp
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Praveen Sethupathy
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Brian J Bennett
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, CA 95616, USA.,Department of Nutrition, University of California, Davis, Davis, CA 95616, USA
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14
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Kim M, Huda MN, O'Connor A, Albright J, Durbin-Johnson B, Bennett BJ. Hepatic transcriptional profile reveals the role of diet and genetic backgrounds on metabolic traits in female progenitor strains of the Collaborative Cross. Physiol Genomics 2021; 53:173-192. [PMID: 33818129 PMCID: PMC8424536 DOI: 10.1152/physiolgenomics.00140.2020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 12/28/2022] Open
Abstract
Mice have provided critical mechanistic understandings of clinical traits underlying metabolic syndrome (MetSyn) and susceptibility to MetSyn in mice is known to vary among inbred strains. We investigated the diet- and strain-dependent effects on metabolic traits in the eight Collaborative Cross (CC) founder strains (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Liver transcriptomics analysis showed that both atherogenic diet and host genetics have profound effects on the liver transcriptome, which may be related to differences in metabolic traits observed between strains. We found strain differences in circulating trimethylamine N-oxide (TMAO) concentration and liver triglyceride content, both of which are traits associated with metabolic diseases. Using a network approach, we identified a module of transcripts associated with TMAO and liver triglyceride content, which was enriched in functional pathways. Interrogation of the module related to metabolic traits identified NADPH oxidase 4 (Nox4), a gene for a key enzyme in the production of reactive oxygen species, which showed a strong association with plasma TMAO and liver triglyceride. Interestingly, Nox4 was identified as the highest expressed in the C57BL/6J and NZO/HILtJ strains and the lowest expressed in the CAST/EiJ strain. Based on these results, we suggest that there may be genetic variation in the contribution of Nox4 to the regulation of plasma TMAO and liver triglyceride content. In summary, we show that liver transcriptomic analysis identified diet- or strain-specific pathways for metabolic traits in the Collaborative Cross (CC) founder strains.
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Affiliation(s)
- Myungsuk Kim
- Department of Nutrition, University of California, Davis, California
- USDA-ARS-Western Human Nutrition Research Center, Davis, California
| | - M Nazmul Huda
- Department of Nutrition, University of California, Davis, California
- USDA-ARS-Western Human Nutrition Research Center, Davis, California
| | - Annalouise O'Connor
- Nutrition Research Institute, University of North Carolina, Kannapolis, North Carolina
| | - Jody Albright
- Nutrition Research Institute, University of North Carolina, Kannapolis, North Carolina
| | | | - Brian J Bennett
- Department of Nutrition, University of California, Davis, California
- USDA-ARS-Western Human Nutrition Research Center, Davis, California
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15
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Swanzey E, O'Connor C, Reinholdt LG. Mouse Genetic Reference Populations: Cellular Platforms for Integrative Systems Genetics. Trends Genet 2021; 37:251-265. [PMID: 33010949 PMCID: PMC7889615 DOI: 10.1016/j.tig.2020.09.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 08/28/2020] [Accepted: 09/02/2020] [Indexed: 02/07/2023]
Abstract
Interrogation of disease-relevant cellular and molecular traits exhibited by genetically diverse cell populations enables in vitro systems genetics approaches for uncovering the basic properties of cellular function and identity. Primary cells, stem cells, and organoids derived from genetically diverse mouse strains, such as Collaborative Cross and Diversity Outbred populations, offer the opportunity for parallel in vitro/in vivo screening. These panels provide genetic resolution for variant discovery and functional characterization, as well as disease modeling and in vivo validation capabilities. Here we review mouse cellular systems genetics approaches for characterizing the influence of genetic variation on signaling networks and phenotypic diversity, and we discuss approaches for data integration and cross-species validation.
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Affiliation(s)
| | - Callan O'Connor
- The Jackson Laboratory, Bar Harbor, ME, USA; Tufts Graduate School of Biomedical Sciences, Boston, MA, USA
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16
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Que E, James KL, Coffey AR, Smallwood TL, Albright J, Huda MN, Pomp D, Sethupathy P, Bennett BJ. Genetic Architecture Modulates Diet-Induced Hepatic mRNA and miRNA Expression Profiles in Diversity Outbred Mice. Genetics 2020; 216:241-259. [PMID: 32763908 PMCID: PMC7463293 DOI: 10.1534/genetics.120.303481] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 07/27/2020] [Indexed: 02/07/2023] Open
Abstract
Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Lastly, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility.
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Affiliation(s)
- Excel Que
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, California 95616
- Department of Nutrition, University of California, Davis, California
| | - Kristen L James
- Department of Nutrition, University of California, Davis, California
| | - Alisha R Coffey
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, North Carolina
| | - Tangi L Smallwood
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, North Carolina
| | - Jody Albright
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina
| | - M Nazmul Huda
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, California 95616
- Department of Nutrition, University of California, Davis, California
| | - Daniel Pomp
- Department of Genetics, University of North Carolina at Chapel Hill, North Carolina
| | - Praveen Sethupathy
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York
| | - Brian J Bennett
- Western Human Nutrition Research Center, Agricultural Research Service, US Department of Agriculture, Davis, California 95616
- Department of Nutrition, University of California, Davis, California
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17
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Wei WZ, Gibson HM, Jacob JB, Frelinger JA, Berzofsky JA, Maeng H, Dyson G, Reyes JD, Pilon-Thomas S, Ratner S, Wei KC. Diversity Outbred Mice Reveal the Quantitative Trait Locus and Regulatory Cells of HER2 Immunity. THE JOURNAL OF IMMUNOLOGY 2020; 205:1554-1563. [PMID: 32796024 DOI: 10.4049/jimmunol.2000466] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 07/11/2020] [Indexed: 01/14/2023]
Abstract
The genetic basis and mechanisms of disparate antitumor immune response was investigated in Diversity Outbred (DO) F1 mice that express human HER2. DO mouse stock samples nearly the entire genetic repertoire of the species. We crossed DO mice with syngeneic HER2 transgenic mice to study the genetics of an anti-self HER2 response in a healthy outbred population. Anti-HER2 IgG was induced by Ad/E2TM or naked pE2TM, both encoding HER2 extracellular and transmembrane domains. The response of DO F1 HER2 transgenic mice was remarkably variable. Still, immune sera inhibited HER2+ SKBR3 cell survival in a dose-dependent fashion. Using DO quantitative trait locus (QTL) analysis, we mapped the QTL that influences both total IgG and IgG2(a/b/c) Ab response to either Ad/E2TM or pE2TM. QTL from these four datasets identified a region in chromosome 17 that was responsible for regulating the response. A/J and NOD segments of genes in this region drove elevated HER2 Ig levels. This region is rich in MHC-IB genes, several of which interact with inhibitory receptors of NK cells. (B6xA/J)F1 and (B6xNOD)F1 HER2 transgenic mice received Ad/E2TM after NK cell depletion, and they produced less HER2 IgG, demonstrating positive regulatory function of NK cells. Depletion of regulatory T cells enhanced response. Using DO QTL analysis, we show that MHC-IB reactive NK cells exert positive influence on the immunity, countering negative regulation by regulatory T cells. This new, to our knowledge, DO F1 platform is a powerful tool for revealing novel immune regulatory mechanisms and for testing new interventional strategies.
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Affiliation(s)
- Wei-Zen Wei
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201;
| | - Heather M Gibson
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201
| | - Jennifer B Jacob
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201
| | - Jeffrey A Frelinger
- Valley Fever Center of Excellence, Department of Immunobiology, University of Arizona, Tucson, AZ 85724
| | - Jay A Berzofsky
- Vaccine Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892; and
| | - Hoyoung Maeng
- Vaccine Branch, Center for Cancer Research, National Cancer Institute, Bethesda, MD 20892; and
| | - Gregory Dyson
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201
| | - Joyce D Reyes
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201
| | - Shari Pilon-Thomas
- Department of Immunology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612
| | - Stuart Ratner
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201
| | - Kuang-Chung Wei
- Department of Oncology, Karmanos Cancer Institute, Wayne State University, Detroit, MI 48201
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18
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Wang Y, Wang J, Yan K, Lin J, Zheng Z, Bi J. Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases. PeerJ 2020; 8:e8786. [PMID: 32266115 PMCID: PMC7120053 DOI: 10.7717/peerj.8786] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 02/23/2020] [Indexed: 12/27/2022] Open
Abstract
Abstract The morbidity and mortality of prostate carcinoma has increased in recent years and has become the second most common ale malignant carcinoma worldwide. The interaction mechanisms between different genes and signaling pathways, however, are still unclear. Methods Variation analysis of GSE38241, GSE69223, GSE46602 and GSE104749 were realized by GEO2R in Gene Expression Omnibus database. Function enrichment was analyzed by DAVID.6.8. Furthermore, the PPI network and the significant module were analyzed by Cytoscape, STRING and MCODE.GO. Pathway analysis showed that the 20 candidate genes were closely related to mitosis, cell division, cell cycle phases and the p53 signaling pathway. A total of six independent prognostic factors were identified in GSE21032 and TCGA PRAD. Oncomine database and The Human Protein Atlas were applied to explicit that six core genes were over expression in prostate cancer compared to normal prostate tissue in the process of transcriptional and translational. Finally, gene set enrichment were performed to identified the related pathway of core genes involved in prostate cancer. Result Hierarchical clustering analysis revealed that these 20 core genes were mostly related to carcinogenesis and development. CKS2, TK1, MKI67, TOP2A, CCNB1 and RRM2 directly related to the recurrence and prognosis of prostate cancer. This result was verified by TCGA database and GSE21032. Conclusion These core genes play a crucial role in tumor carcinogenesis, development, recurrence, metastasis and progression. Identifying these genes could help us to understand the molecular mechanisms and provide potential biomarkers for the diagnosis and treatment of prostate cancer.
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Affiliation(s)
- Yutao Wang
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Jianfeng Wang
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Kexin Yan
- Department of Dermatology, The First Hospital of China Medical University, Shenyang, China
| | - Jiaxing Lin
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Zhenhua Zheng
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
| | - Jianbin Bi
- Department of Urology, The First Hospital of China Medical University, Shenyang, China
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19
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Bucsan AN, Mehra S, Khader SA, Kaushal D. The current state of animal models and genomic approaches towards identifying and validating molecular determinants of Mycobacterium tuberculosis infection and tuberculosis disease. Pathog Dis 2020; 77:5543892. [PMID: 31381766 PMCID: PMC6687098 DOI: 10.1093/femspd/ftz037] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2019] [Accepted: 07/25/2019] [Indexed: 12/31/2022] Open
Abstract
Animal models are important in understanding both the pathogenesis of and immunity to tuberculosis (TB). Unfortunately, we are beginning to understand that no animal model perfectly recapitulates the human TB syndrome, which encompasses numerous different stages. Furthermore, Mycobacterium tuberculosis infection is a very heterogeneous event at both the levels of pathogenesis and immunity. This review seeks to establish the current understanding of TB pathogenesis and immunity, as validated in the animal models of TB in active use today. We especially focus on the use of modern genomic approaches in these models to determine the mechanism and the role of specific molecular pathways. Animal models have significantly enhanced our understanding of TB. Incorporation of contemporary technologies such as single cell transcriptomics, high-parameter flow cytometric immune profiling, proteomics, proteomic flow cytometry and immunocytometry into the animal models in use will further enhance our understanding of TB and facilitate the development of treatment and vaccination strategies.
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Affiliation(s)
- Allison N Bucsan
- Tulane Center for Tuberculosis Research, Covington, LA, USA.,Tulane National Primate Research Center, Covington, LA, USA
| | - Smriti Mehra
- Tulane National Primate Research Center, Covington, LA, USA
| | | | - Deepak Kaushal
- Tulane Center for Tuberculosis Research, Covington, LA, USA.,Tulane National Primate Research Center, Covington, LA, USA.,Southwest National Primate Research Center, San Antonio, TX, USA.,Texas Biomedical Research Institute, San Antonio, TX, USA
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20
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Zhu C, Hu H, Li J, Wang J, Wang K, Sun J. Identification of key differentially expressed genes and gene mutations in breast ductal carcinoma in situ using RNA-seq analysis. World J Surg Oncol 2020; 18:52. [PMID: 32156290 PMCID: PMC7063758 DOI: 10.1186/s12957-020-01820-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 02/18/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The aim of this study was to identify the key differentially expressed genes (DEGs) and high-risk gene mutations in breast ductal carcinoma in situ (DCIS). METHODS Raw data (GSE36863) were downloaded from the database of Gene Expression Omnibus (GEO), including three DCIS samples (DCIS cell lines MCF10.DCIS, Sum102, and Sum225) and one normal control sample (normal mammary epithelial cell line MCF10A). The DEGs were analyzed using NOIseq and annotated via DAVID. Motif scanning in the promoter region of DEGs was performed via SeqPos. Additionally, single nucleotide variations (SNVs) were identified via GenomeAnalysisTK and SNV risk was assessed via VarioWatch. Mutant genes with a high frequency and risk were validated by RT-PCR analyses. RESULTS Finally, 5391, 7073, and 7944 DEGs were identified in DCIS, Sum102, and Sum22 cell lines, respectively, when compared with MCF10A. VENN analysis of the three cell lines revealed 603 upregulated and 1043 downregulated DEGs, including 16 upregulated and 36 downregulated transcription factor (TF) genes. In addition, six TFs each (e.g., E2F1 and CREB1) were found to regulate the core up- and downregulated DEGs, respectively. Furthermore, SNV detection results revealed 1104 (MCF10.DCIS), 2833 (Sum102), and 1132 (Sum22) mutation sites. Four mutant genes (RWDD4, SDHC, SEPT7, and SFN) with high frequency and risk were identified. The results of RT-PCR analysis as well as bioinformatics analysis consistently demonstrated that the expression of RWDD4, SDHC, SEPT7, and SFN was downregulated in the tumor tissues as compared with that in adjacent non-tumor tissues. CONCLUSIONS The differentially expressed TFs, TFs regulating DEGs (e.g., E2F1 and CREB1), and high-frequency mutant genes (RWDD4, SDHC, SEPT7, and SFN) might play key roles in the pathogenesis of DCIS.
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Affiliation(s)
- Congyuan Zhu
- Department of General Surgery, the Affiliated Hospital of Jiangnan University (original area of Wuxi Third People's Hospital), No. 585 North Xingyuan Road, Liangxi District, Wuxi, 214002, Jiangsu, China.
| | - Hao Hu
- Department of General Surgery, the Affiliated Hospital of Jiangnan University (original area of Wuxi Third People's Hospital), No. 585 North Xingyuan Road, Liangxi District, Wuxi, 214002, Jiangsu, China
| | - Jianping Li
- Department of General Surgery, the Affiliated Hospital of Jiangnan University (original area of Wuxi Third People's Hospital), No. 585 North Xingyuan Road, Liangxi District, Wuxi, 214002, Jiangsu, China.
| | - Jingli Wang
- Department of General Surgery, the Affiliated Hospital of Jiangnan University (original area of Wuxi Third People's Hospital), No. 585 North Xingyuan Road, Liangxi District, Wuxi, 214002, Jiangsu, China
| | - Ke Wang
- Department of General Surgery, the Affiliated Hospital of Jiangnan University (original area of Wuxi Third People's Hospital), No. 585 North Xingyuan Road, Liangxi District, Wuxi, 214002, Jiangsu, China
| | - Jingqiu Sun
- Department of General Surgery, the Affiliated Hospital of Jiangnan University (original area of Wuxi Third People's Hospital), No. 585 North Xingyuan Road, Liangxi District, Wuxi, 214002, Jiangsu, China
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21
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Wang Y, Ma S, Ruzzo WL. Spatial modeling of prostate cancer metabolic gene expression reveals extensive heterogeneity and selective vulnerabilities. Sci Rep 2020; 10:3490. [PMID: 32103057 PMCID: PMC7044328 DOI: 10.1038/s41598-020-60384-w] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 02/11/2020] [Indexed: 01/24/2023] Open
Abstract
Spatial heterogeneity is a fundamental feature of the tumor microenvironment (TME), and tackling spatial heterogeneity in neoplastic metabolic aberrations is critical for tumor treatment. Genome-scale metabolic network models have been used successfully to simulate cancer metabolic networks. However, most models use bulk gene expression data of entire tumor biopsies, ignoring spatial heterogeneity in the TME. To account for spatial heterogeneity, we performed spatially-resolved metabolic network modeling of the prostate cancer microenvironment. We discovered novel malignant-cell-specific metabolic vulnerabilities targetable by small molecule compounds. We predicted that inhibiting the fatty acid desaturase SCD1 may selectively kill cancer cells based on our discovery of spatial separation of fatty acid synthesis and desaturation. We also uncovered higher prostaglandin metabolic gene expression in the tumor, relative to the surrounding tissue. Therefore, we predicted that inhibiting the prostaglandin transporter SLCO2A1 may selectively kill cancer cells. Importantly, SCD1 and SLCO2A1 have been previously shown to be potently and selectively inhibited by compounds such as CAY10566 and suramin, respectively. We also uncovered cancer-selective metabolic liabilities in central carbon, amino acid, and lipid metabolism. Our novel cancer-specific predictions provide new opportunities to develop selective drug targets for prostate cancer and other cancers where spatial transcriptomics datasets are available.
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Affiliation(s)
- Yuliang Wang
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, 98109, USA.
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, 98195, USA.
| | - Shuyi Ma
- Department of Microbiology, University of Washington, Seattle, WA, 98195, USA
| | - Walter L Ruzzo
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, 98195, USA
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA, 98102, USA
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22
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Mouse Systems Genetics as a Prelude to Precision Medicine. Trends Genet 2020; 36:259-272. [PMID: 32037011 DOI: 10.1016/j.tig.2020.01.004] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 01/06/2020] [Accepted: 01/08/2020] [Indexed: 12/17/2022]
Abstract
Mouse models have been instrumental in understanding human disease biology and proposing possible new treatments. The precise control of the environment and genetic composition of mice allows more rigorous observations, but limits the generalizability and translatability of the results into human applications. In the era of precision medicine, strategies using mouse models have to be revisited to effectively emulate human populations. Systems genetics is one promising paradigm that may promote the transition to novel precision medicine strategies. Here, we review the state-of-the-art resources and discuss how mouse systems genetics helps to understand human diseases and to advance the development of precision medicine, with an emphasis on the existing resources and strategies.
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23
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Abstract
In this chapter we will review both the rationale and experimental design for using Heterogeneous Stock (HS) populations for fine-mapping of complex traits in mice and rats. We define an HS as an outbred population derived from an intercross between two or more inbred strains. HS have been used to perform genome-wide association studies (GWAS) for multiple behavioral, physiological, and gene expression traits. GWAS using HS require four key steps, which we review: selection of an appropriate HS population, phenotyping, genotyping, and statistical analysis. We provide advice on the selection of an HS, comment on key issues related to phenotyping, discuss genotyping methods relevant to these populations, and describe statistical genetic analyses that are applicable to genetic analyses that use HS.
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24
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Comparison of post-traumatic changes in circulating and bone marrow leukocytes between BALB/c and CD-1 mouse strains. PLoS One 2019; 14:e0222594. [PMID: 31527918 PMCID: PMC6748677 DOI: 10.1371/journal.pone.0222594] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Accepted: 09/03/2019] [Indexed: 11/19/2022] Open
Abstract
This manuscript emerged from a larger third-party funded project investigating a new poly-trauma model and its influence upon secondary sepsis. The present sub-study compared selected leukocyte subpopulations in the circulation and bone marrow after polytrauma in BALB/c versus CD-1 mice. Animals underwent unilateral femur fracture, splenectomy and hemorrhagic shock. We collected blood and bone marrow for flow cytometry analysis at 24h and 48h post-trauma. Circulating granulocytes (Ly6G+CD11+) increased in both strains after trauma. Only in BALB/c mice circulating CD8+ T-lymphocytes decreased within 48h by 30%. Regulatory T-cells (Tregs, CD4+CD25+CD127low) increased in both strains by approx. 32%. Circulating Tregs and lymphocytes (CD11b-Ly6G-MHC-2+) were always at least 1.5-fold higher in BALB/c, while the bone marrow MHC-2 expression decreased in CD-1 mice (p<0.05). Overall, immune responses to polytrauma were similar in both strains. Additionally, BALB/c expressed higher level of circulating regulatory T-cells and MHC-2-positive lymphocytes compared to CD-1 mice.
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25
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Saul MC, Philip VM, Reinholdt LG, Chesler EJ. High-Diversity Mouse Populations for Complex Traits. Trends Genet 2019; 35:501-514. [PMID: 31133439 DOI: 10.1016/j.tig.2019.04.003] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/19/2019] [Accepted: 04/22/2019] [Indexed: 12/21/2022]
Abstract
Contemporary mouse genetic reference populations are a powerful platform to discover complex disease mechanisms. Advanced high-diversity mouse populations include the Collaborative Cross (CC) strains, Diversity Outbred (DO) stock, and their isogenic founder strains. When used in systems genetics and integrative genomics analyses, these populations efficiently harnesses known genetic variation for precise and contextualized identification of complex disease mechanisms. Extensive genetic, genomic, and phenotypic data are already available for these high-diversity mouse populations and a growing suite of data analysis tools have been developed to support research on diverse mice. This integrated resource can be used to discover and evaluate disease mechanisms relevant across species.
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Affiliation(s)
- Michael C Saul
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
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- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA; UNC Chapel Hill, Chapel Hill, NC, USA; SUNY Binghamton, Binghamton, NY, USA; Pittsburgh University, Pittsburgh, PA, USA
| | - Elissa J Chesler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA.
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26
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Melia T, Waxman DJ. Sex-Biased lncRNAs Inversely Correlate With Sex-Opposite Gene Coexpression Networks in Diversity Outbred Mouse Liver. Endocrinology 2019; 160:989-1007. [PMID: 30840070 PMCID: PMC6449536 DOI: 10.1210/en.2018-00949] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Accepted: 02/27/2019] [Indexed: 01/05/2023]
Abstract
Sex differences in liver gene expression are determined by pituitary growth hormone secretion patterns, which regulate sex-dependent liver transcription factors and establish sex-specific chromatin states. Hypophysectomy (hypox) identifies two major classes of liver sex-biased genes, defined by their sex-dependent positive or negative responses to pituitary hormone ablation. However, the mechanisms that underlie each hypox-response class are unknown. We sought to discover candidate, regulatory, long noncoding RNAs (lncRNAs) controlling responsiveness to hypox. We characterized gene structures and expression patterns for 15,558 mouse liver-expressed lncRNAs, including many sex-specific lncRNAs regulated during postnatal development or subject to circadian regulation. Using the high natural allelic variance of Diversity Outbred (DO) mice, we discovered tightly coexpressed clusters of sex-specific protein-coding genes (gene modules) in male and female DO liver. Remarkably, many gene modules were strongly enriched for sex-specific genes within a single hypox-response class, indicating that the genetic heterogeneity of DO mice encompasses responsiveness to hypox. Moreover, several distant gene modules were enriched for gene subsets of the same hypox-response class, highlighting the complex regulation of hypox-responsiveness. Finally, we identified eight sex-specific lncRNAs with strong negative regulatory potential, as indicated by their strong negative correlation of expression across DO mouse livers with that of protein-coding gene modules enriched for genes of the opposite sex bias and inverse hypox-response class. These findings reveal an important role for genetic factors in regulating responsiveness to hypox, and present testable hypotheses for the roles of sex-biased liver lncRNAs in controlling the sex-bias of liver gene expression.
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Affiliation(s)
- Tisha Melia
- Department of Biology and Bioinformatics Program, Boston University, Boston, Massachusetts
| | - David J Waxman
- Department of Biology and Bioinformatics Program, Boston University, Boston, Massachusetts
- Correspondence: David J. Waxman, PhD, Department of Biology, Boston University, 5 Cummington Mall, Boston, Massachusetts 02215. E-mail:
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Li J, Wang ZG, Pang LB, Zhang RH, Wang YY. Reduced CENPU expression inhibits lung adenocarcinoma cell proliferation and migration through PI3K/AKT signaling. Biosci Biotechnol Biochem 2019; 83:1077-1084. [PMID: 30849291 DOI: 10.1080/09168451.2019.1588094] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
CENPU (centromere protein U), a centromere component essential for mitosis, relates with some cancers progression. However, it is not well illustrated in lung adenocarcinoma (LAC). Here, we aimed to investigate the potential effect of CENPU on LAC progression and prognosis. In this experiment, expression level of CENPU and association between its expression and LAC patients' clinicopathological characteristics and prognosis were analyzed. The proliferation, migration and invasive abilities of LAC cells were determined by CCK-8, colony formation, transwell assays. Western blot was used to detect PI3K/AKT signaling key proteins. We found CENPU level was overexpressed in LAC tissues on comparing normal tissues. Moreover, CENPU overexpression correlated with clinicopathological variables and predicted an independent prognostic indicator in LAC patients. Functionally, CENPU downregulation significantly inhibited LAC cell proliferation, migration and invasion in, which was possibly mediated by PI3K/AKT pathway inactivation. Our findings insinuate targeting CENPU may be a potential therapeutic strategy for LAC.
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Affiliation(s)
- Jun Li
- a Department of respiratory medicine , Jinan Center Hospital Affiliated to Shandong University , Jinan , Shandong , P.R. China
| | - Zhi-Guang Wang
- b Department of Respiratory Medicine , Affiliated Hospital of Yanbian University , Yanji , Jilin , P.R. China
| | - Long-Bin Pang
- a Department of respiratory medicine , Jinan Center Hospital Affiliated to Shandong University , Jinan , Shandong , P.R. China
| | - Rong-Hua Zhang
- a Department of respiratory medicine , Jinan Center Hospital Affiliated to Shandong University , Jinan , Shandong , P.R. China
| | - Ya-Yan Wang
- b Department of Respiratory Medicine , Affiliated Hospital of Yanbian University , Yanji , Jilin , P.R. China
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28
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Advancing brain tumor epidemiology - multi-level integration and international collaboration: The 2018 Brain Tumor Epidemiology Consortium meeting report. Clin Neuropathol 2019; 37:254-261. [PMID: 30343678 PMCID: PMC6350238 DOI: 10.5414/np301148] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/24/2018] [Indexed: 12/19/2022] Open
Abstract
The Brain Tumor Epidemiology Consortium (BTEC) is an international consortium that aims to foster multicenter and inter-disciplinary collaborations that focus on research related to the etiology, outcomes, and prevention of brain tumors. The 19th annual BTEC meeting was held in Copenhagen, Denmark, on June 19 – 21, 2018. The meeting focused on forming international collaborations and integrating multiple data types for the next generation of studies in brain tumor epidemiology. The next BTEC meeting will be held in Southern California in June 2019.
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Pan Z, Li L, Fang Q, Zhang Y, Hu X, Qian Y, Huang P. Analysis of dynamic molecular networks for pancreatic ductal adenocarcinoma progression. Cancer Cell Int 2018; 18:214. [PMID: 30598639 PMCID: PMC6303882 DOI: 10.1186/s12935-018-0718-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 12/18/2018] [Indexed: 12/29/2022] Open
Abstract
Background Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest solid tumors. The rapid progression of PDAC results in an advanced stage of patients when diagnosed. However, the dynamic molecular mechanism underlying PDAC progression remains far from clear. Methods The microarray GSE62165 containing PDAC staging samples was obtained from Gene Expression Omnibus and the differentially expressed genes (DEGs) between normal tissue and PDAC of different stages were profiled using R software, respectively. The software program Short Time-series Expression Miner was applied to cluster, compare, and visualize gene expression differences between PDAC stages. Then, function annotation and pathway enrichment of DEGs were conducted by Database for Annotation Visualization and Integrated Discovery. Further, the Cytoscape plugin DyNetViewer was applied to construct the dynamic protein–protein interaction networks and to analyze different topological variation of nodes and clusters over time. The phosphosite markers of stage-specific protein kinases were predicted by PhosphoSitePlus database. Moreover, survival analysis of candidate genes and pathways was performed by Kaplan–Meier plotter. Finally, candidate genes were validated by immunohistochemistry in PDAC tissues. Results Compared with normal tissues, the total DEGs number for each PDAC stage were 994 (stage I), 967 (stage IIa), 965 (stage IIb), 1027 (stage III), 925 (stage IV), respectively. The stage-course gene expression analysis showed that 30 distinct expressional models were clustered. Kyoto Encyclopedia of Genes and Genomes analysis indicated that the up-regulated DEGs were commonly enriched in five fundamental pathways throughout five stages, including pathways in cancer, small cell lung cancer, ECM-receptor interaction, amoebiasis, focal adhesion. Except for amoebiasis, these pathways were associated with poor PDAC overall survival. Meanwhile, LAMA3, LAMB3, LAMC2, COL4A1 and FN1 were commonly shared by these five pathways and were unfavorable factors for prognosis. Furthermore, by constructing the stage-course dynamic protein interaction network, 45 functional molecular modules and 19 nodes were identified as featured regulators for all PDAC stages, among which the collagen family and integrins were considered as two main regulators for facilitating aggressive progression. Additionally, the clinical relevance analysis suggested that the stage IV featured nodes MLF1IP and ITGB4 were significantly correlated with shorter overall survival. Moreover, 15 stage-specific protein kinases were identified from the dynamic network and CHEK1 was particularly activated at stage IV. Experimental validation showed that MLF1IP, LAMA3 and LAMB3 were progressively increased from tumor initiation to progression. Conclusions Our study provided a view for a better understanding of the dynamic landscape of molecular interaction networks during PDAC progression and offered potential targets for therapeutic intervention. Electronic supplementary material The online version of this article (10.1186/s12935-018-0718-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zongfu Pan
- 1Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou, 310022 China
| | - Lu Li
- 2Department of Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310003 China
| | - Qilu Fang
- 1Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou, 310022 China
| | - Yiwen Zhang
- 1Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou, 310022 China
| | - Xiaoping Hu
- 1Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou, 310022 China
| | - Yangyang Qian
- 3Key Laboratory of Head & Neck Cancer Translational Research of Zhejiang Province, Zhejiang Cancer Hospital, Hangzhou, 310022 China
| | - Ping Huang
- 1Department of Pharmacy, Zhejiang Cancer Hospital, Hangzhou, 310022 China
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Beadnell TC, Scheid AD, Vivian CJ, Welch DR. Roles of the mitochondrial genetics in cancer metastasis: not to be ignored any longer. Cancer Metastasis Rev 2018; 37:615-632. [PMID: 30542781 PMCID: PMC6358502 DOI: 10.1007/s10555-018-9772-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Mitochondrial DNA (mtDNA) encodes for only a fraction of the proteins that are encoded within the nucleus, and therefore has typically been regarded as a lesser player in cancer biology and metastasis. Accumulating evidence, however, supports an increased role for mtDNA impacting tumor progression and metastatic susceptibility. Unfortunately, due to this delay, there is a dearth of data defining the relative contributions of specific mtDNA polymorphisms (SNP), which leads to an inability to effectively use these polymorphisms to guide and enhance therapeutic strategies and diagnosis. In addition, evidence also suggests that differences in mtDNA impact not only the cancer cells but also the cells within the surrounding tumor microenvironment, suggesting a broad encompassing role for mtDNA polymorphisms in regulating the disease progression. mtDNA may have profound implications in the regulation of cancer biology and metastasis. However, there are still great lengths to go to understand fully its contributions. Thus, herein, we discuss the recent advances in our understanding of mtDNA in cancer and metastasis, providing a framework for future functional validation and discovery.
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Affiliation(s)
- Thomas C Beadnell
- Department of Cancer Biology, The Kansas University Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA
| | - Adam D Scheid
- Department of Cancer Biology, The Kansas University Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA
| | - Carolyn J Vivian
- Department of Cancer Biology, The Kansas University Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA
| | - Danny R Welch
- Department of Cancer Biology, The Kansas University Medical Center, 3901 Rainbow Blvd, Kansas City, KS, 66160, USA.
- The University of Kansas Cancer Center, 3901 Rainbow Blvd., Kansas City, KS, 66160, USA.
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31
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Hou Y. MiR-506 inhibits cell proliferation, invasion, migration and epithelial-to-mesenchymal transition through targeting RWDD4 in human bladder cancer. Oncol Lett 2018; 17:73-78. [PMID: 30655740 DOI: 10.3892/ol.2018.9594] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 04/12/2018] [Indexed: 12/26/2022] Open
Abstract
MicroRNA (MiR)-506 serves a vital role in several types of cancer. However, the role of miR-506 in bladder cancer (BCa) progression remains to be investigated. The present study demonstrated that miR-506 expression was downregulated in BCa tissues and cell lines. Meanwhile, overexpression of miR-506 inhibited cell proliferation, migration and invasion. Additionally, upregulated miR-506 increased E-cadherin, and reduced N-cadherin and Vimentin expression levels, as markers of epithelial-to-mesenchymal transition. RWD domain containing 4 (RWDD4) was revealed to be a miR506 target in BCa cells, and the downregulation of RWDD4 was found to suppress BCa cell proliferation, migration and invasion. In summary, miR-506 may suppress the aggressive properties of human BCa cells by targeting RWDD4, and thus may be a novel therapeutic target in human BCa.
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Affiliation(s)
- Yi Hou
- Department of Urology, The Fourth People's Hospital of Shenyang, Shenyang, Liaoning 110031, P.R. China
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32
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Williams KA, Lee M, Winter JM, Gildea DE, Calagua C, Curry NL, Lichtenberg J, Ye H, Crawford NPS. Prostate cancer susceptibility gene HIST1H1A is a modulator of androgen receptor signaling and epithelial to mesenchymal transition. Oncotarget 2018; 9:28532-28546. [PMID: 29983878 PMCID: PMC6033342 DOI: 10.18632/oncotarget.25536] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Accepted: 05/01/2018] [Indexed: 01/27/2023] Open
Abstract
In 2018, approximately 165,000 new prostate cancer (PC) cases will be diagnosed, and over 29,000 men will succumb to PC in the U.S. alone. The means of assessing outcome in the clinic are inaccurate, and there is a pressing need to more precisely identify men at risk of aggressive PC. We previously identified HIST1H1A as a susceptibility gene for aggressive PC. HIST1H1A encodes H1.1, a member of the linker histone family that is involved in chromatin organization and compaction. To understand the molecular basis of aggressive PC, we have characterized how germline variation modulates susceptibility to neuroendocrine differentiation, which is a form of aggressive PC. Immunohistochemistry studies revealed that HIST1H1A is over-expressed in normal human prostate tissue compared to prostate adenocarcinoma. Functional characterization of HIST1H1A in prostate LNCaP cells indicated that HIST1HA over-expression increased cell growth, as well as the expression of neuroendocrine and epithelial-to-mesenchymal markers in vitro. Assay for Transposase-Accessible Chromatin (ATAC-seq), which is used to assess chromatin compaction and thus the transcriptional availability of individual genomic regions, demonstrated that H1.1 plays a prominent role in modulating Wnt signaling pathway genes, which are implicated in prostate tumorigenesis. These results demonstrate that HIST1H1A is a modulator of aggressive PC susceptibility.
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Affiliation(s)
- Kendra A Williams
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Minnkyong Lee
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jean M Winter
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Derek E Gildea
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Carla Calagua
- Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Natasha L Curry
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jens Lichtenberg
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Huihui Ye
- Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Nigel P S Crawford
- Genetics and Molecular Biology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA.,Current address: Sanofi, Bridgewater, New Jersey, USA
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Winter JM, Curry NL, Gildea DM, Williams KA, Lee M, Hu Y, Crawford NPS. Modifier locus mapping of a transgenic F2 mouse population identifies CCDC115 as a novel aggressive prostate cancer modifier gene in humans. BMC Genomics 2018; 19:450. [PMID: 29890952 PMCID: PMC5996485 DOI: 10.1186/s12864-018-4827-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 05/25/2018] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND It is well known that development of prostate cancer (PC) can be attributed to somatic mutations of the genome, acquired within proto-oncogenes or tumor-suppressor genes. What is less well understood is how germline variation contributes to disease aggressiveness in PC patients. To map germline modifiers of aggressive neuroendocrine PC, we generated a genetically diverse F2 intercross population using the transgenic TRAMP mouse model and the wild-derived WSB/EiJ (WSB) strain. The relevance of germline modifiers of aggressive PC identified in these mice was extensively correlated in human PC datasets and functionally validated in cell lines. RESULTS Aggressive PC traits were quantified in a population of 30 week old (TRAMP x WSB) F2 mice (n = 307). Correlation of germline genotype with aggressive disease phenotype revealed seven modifier loci that were significantly associated with aggressive disease. RNA-seq were analyzed using cis-eQTL and trait correlation analyses to identify candidate genes within each of these loci. Analysis of 92 (TRAMP x WSB) F2 prostates revealed 25 candidate genes that harbored both a significant cis-eQTL and mRNA expression correlations with an aggressive PC trait. We further delineated these candidate genes based on their clinical relevance, by interrogating human PC GWAS and PC tumor gene expression datasets. We identified four genes (CCDC115, DNAJC10, RNF149, and STYXL1), which encompassed all of the following characteristics: 1) one or more germline variants associated with aggressive PC traits; 2) differential mRNA levels associated with aggressive PC traits; and 3) differential mRNA expression between normal and tumor tissue. Functional validation studies of these four genes using the human LNCaP prostate adenocarcinoma cell line revealed ectopic overexpression of CCDC115 can significantly impede cell growth in vitro and tumor growth in vivo. Furthermore, CCDC115 human prostate tumor expression was associated with better survival outcomes. CONCLUSION We have demonstrated how modifier locus mapping in mouse models of PC, coupled with in silico analyses of human PC datasets, can reveal novel germline modifier genes of aggressive PC. We have also characterized CCDC115 as being associated with less aggressive PC in humans, placing it as a potential prognostic marker of aggressive PC.
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Affiliation(s)
- Jean M Winter
- Metastasis Genetics Section, Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA.,Present address: Dame Roma Mitchell Cancer Research Laboratories, Adelaide Health and Medical Sciences, The University of Adelaide, Adelaide, South Australia, 5000, Australia
| | - Natasha L Curry
- Metastasis Genetics Section, Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Derek M Gildea
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Kendra A Williams
- Metastasis Genetics Section, Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Minnkyong Lee
- Metastasis Genetics Section, Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Ying Hu
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, NIH, Rockville, MD, 20892, USA
| | - Nigel P S Crawford
- Metastasis Genetics Section, Genetics and Molecular Biology Branch, National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA. .,, Present address: Sanofi, 55 Corporate Dr., Bridgewater, NJ, 08897, USA.
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Muñoz-Fuentes V, Cacheiro P, Meehan TF, Aguilar-Pimentel JA, Brown SDM, Flenniken AM, Flicek P, Galli A, Mashhadi HH, Hrabě de Angelis M, Kim JK, Lloyd KCK, McKerlie C, Morgan H, Murray SA, Nutter LMJ, Reilly PT, Seavitt JR, Seong JK, Simon M, Wardle-Jones H, Mallon AM, Smedley D, Parkinson HE. The International Mouse Phenotyping Consortium (IMPC): a functional catalogue of the mammalian genome that informs conservation. CONSERV GENET 2018; 19:995-1005. [PMID: 30100824 PMCID: PMC6061128 DOI: 10.1007/s10592-018-1072-9] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 05/03/2018] [Indexed: 01/08/2023]
Abstract
The International Mouse Phenotyping Consortium (IMPC) is building a catalogue of mammalian gene function by producing and phenotyping a knockout mouse line for every protein-coding gene. To date, the IMPC has generated and characterised 5186 mutant lines. One-third of the lines have been found to be non-viable and over 300 new mouse models of human disease have been identified thus far. While current bioinformatics efforts are focused on translating results to better understand human disease processes, IMPC data also aids understanding genetic function and processes in other species. Here we show, using gorilla genomic data, how genes essential to development in mice can be used to help assess the potentially deleterious impact of gene variants in other species. This type of analyses could be used to select optimal breeders in endangered species to maintain or increase fitness and avoid variants associated to impaired-health phenotypes or loss-of-function mutations in genes of critical importance. We also show, using selected examples from various mammal species, how IMPC data can aid in the identification of candidate genes for studying a condition of interest, deliver information about the mechanisms involved, or support predictions for the function of genes that may play a role in adaptation. With genotyping costs decreasing and the continued improvements of bioinformatics tools, the analyses we demonstrate can be routinely applied.
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Affiliation(s)
- Violeta Muñoz-Fuentes
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Pilar Cacheiro
- Clinical Pharmacology, William Harvey Research Institute, School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ UK
| | - Terrence F. Meehan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Juan Antonio Aguilar-Pimentel
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany
| | - Steve D. M. Brown
- Medical Research Council Harwell Institute (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD UK
| | - Ann M. Flenniken
- The Centre for Phenogenomics, Toronto, ON M5T 3H7 Canada
- Mount Sinai Hospital, Toronto, ON M5G 1X5 Canada
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | | | - Hamed Haseli Mashhadi
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - Martin Hrabě de Angelis
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
- School of Life Science Weihenstephan, Technische Universität München, Alte Akademie 8, 85354 Freising, Germany
| | - Jong Kyoung Kim
- Department of New Biology, DGIST, Daegu, 42988 Republic of Korea
| | - K. C. Kent Lloyd
- Mouse Biology Program, University of California, Davis, CA 95618 USA
| | - Colin McKerlie
- The Centre for Phenogenomics, Toronto, ON M5T 3H7 Canada
- Mount Sinai Hospital, Toronto, ON M5G 1X5 Canada
- The Hospital for Sick Children, Toronto, ON M5G 1X84 Canada
| | - Hugh Morgan
- Medical Research Council Harwell Institute (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD UK
| | | | - Lauryl M. J. Nutter
- The Centre for Phenogenomics, Toronto, ON M5T 3H7 Canada
- The Hospital for Sick Children, Toronto, ON M5G 1X84 Canada
| | - Patrick T. Reilly
- PHENOMIN-iCS, 1 Rue Laurent Fries, 67404 Illkirch Cedex, Alsace France
| | - John R. Seavitt
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
| | - Je Kyung Seong
- Laboratory of Developmental Biology and Genomics, College of Veterinary Medicine, Interdisciplinary Program for Bioinformatics and Program for Cancer Biology, Seoul National University, Seoul, Republic of Korea
| | - Michelle Simon
- Medical Research Council Harwell Institute (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD UK
| | | | - Ann-Marie Mallon
- Medical Research Council Harwell Institute (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD UK
| | - Damian Smedley
- Clinical Pharmacology, William Harvey Research Institute, School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ UK
| | - Helen E. Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
| | - the IMPC consortium
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD UK
- Clinical Pharmacology, William Harvey Research Institute, School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ UK
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany
- Medical Research Council Harwell Institute (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD UK
- The Centre for Phenogenomics, Toronto, ON M5T 3H7 Canada
- Mount Sinai Hospital, Toronto, ON M5G 1X5 Canada
- Wellcome Trust Sanger Institute, Cambridge, CB10 1SA UK
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany
- School of Life Science Weihenstephan, Technische Universität München, Alte Akademie 8, 85354 Freising, Germany
- Department of New Biology, DGIST, Daegu, 42988 Republic of Korea
- Mouse Biology Program, University of California, Davis, CA 95618 USA
- The Hospital for Sick Children, Toronto, ON M5G 1X84 Canada
- The Jackson Laboratory, Bar Harbor, ME 04609 USA
- PHENOMIN-iCS, 1 Rue Laurent Fries, 67404 Illkirch Cedex, Alsace France
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
- Laboratory of Developmental Biology and Genomics, College of Veterinary Medicine, Interdisciplinary Program for Bioinformatics and Program for Cancer Biology, Seoul National University, Seoul, Republic of Korea
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35
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Abstract
Tumour heterogeneity poses a substantial problem for the clinical management of cancer. Somatic evolution of the cancer genome results in genetically distinct subclones in the primary tumour with different biological properties and therapeutic sensitivities. The problem of heterogeneity is compounded in metastatic disease owing to the complexity of the metastatic process and the multiple biological hurdles that the tumour cell must overcome to establish a clinically overt metastatic lesion. New advances in sequencing technology and clinical sample acquisition are providing insights into the phylogenetic relationship of metastases and primary tumours at the level of somatic tumour genetics while also illuminating fundamental mechanisms of the metastatic process. In addition to somatically acquired genetic heterogeneity in the tumour cells, inherited population-based genetic heterogeneity can profoundly modify metastatic biology and further complicate the development of effective, broadly applicable antimetastatic therapies. Here, we examine how genetic heterogeneity impacts metastatic disease and the implications of current knowledge for future research endeavours and therapeutic interventions.
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36
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Brinker AE, Vivian CJ, Koestler DC, Tsue TT, Jensen RA, Welch DR. Mitochondrial Haplotype Alters Mammary Cancer Tumorigenicity and Metastasis in an Oncogenic Driver-Dependent Manner. Cancer Res 2017; 77:6941-6949. [PMID: 29070615 DOI: 10.1158/0008-5472.can-17-2194] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 09/20/2017] [Accepted: 10/19/2017] [Indexed: 12/13/2022]
Abstract
Using a novel mouse model, a mitochondrial-nuclear exchange model termed MNX, we tested the hypothesis that inherited mitochondrial haplotypes alter primary tumor latency and metastatic efficiency. Male FVB/N-Tg(MMTVneu)202Mul/J (Her2) transgenic mice were bred to female MNX mice having FVB/NJ nuclear DNA with either FVB/NJ, C57BL/6J, or BALB/cJ mtDNA. Pups receiving the C57BL/6J or BALB/cJ mitochondrial genome (i.e., females crossed with Her2 males) showed significantly (P < 0.001) longer tumor latency (262 vs. 293 vs. 225 days), fewer pulmonary metastases (5 vs. 7 vs. 15), and differences in size of lung metastases (1.2 vs. 1.4 vs. 1.0 mm diameter) compared with FVB/NJ mtDNA. Although polyoma virus middle T-driven tumors showed altered primary and metastatic profiles in previous studies, depending upon nuclear and mtDNA haplotype, the magnitude and direction of changes were not the same in the HER2-driven mammary carcinomas. Collectively, these results establish mitochondrial polymorphisms as quantitative trait loci in mammary carcinogenesis, and they implicate distinct interactions between tumor drivers and mitochondria as critical modifiers of tumorigenicity and metastasis. Cancer Res; 77(24); 6941-9. ©2017 AACR.
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Affiliation(s)
- Amanda E Brinker
- Department of Cancer Biology, The University of Kansas Medical Center, Kansas City, Kansas.,Department of Molecular and Integrative Physiology, The University of Kansas Medical Center, Kansas City, Kansas.,Heartland Center for Mitochondrial Medicine, The University of Kansas Medical Center, Kansas City, Kansas
| | - Carolyn J Vivian
- Department of Cancer Biology, The University of Kansas Medical Center, Kansas City, Kansas.,Heartland Center for Mitochondrial Medicine, The University of Kansas Medical Center, Kansas City, Kansas
| | - Devin C Koestler
- Department of Biostatistics, The University of Kansas Medical Center, Kansas City, Kansas.,The University Kansas Cancer Center, The University of Kansas Medical Center, Kansas City, Kansas
| | - Trevor T Tsue
- Department of Cancer Biology, The University of Kansas Medical Center, Kansas City, Kansas
| | - Roy A Jensen
- The University Kansas Cancer Center, The University of Kansas Medical Center, Kansas City, Kansas.,Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, Kansas City, Kansas
| | - Danny R Welch
- Department of Cancer Biology, The University of Kansas Medical Center, Kansas City, Kansas. .,Department of Molecular and Integrative Physiology, The University of Kansas Medical Center, Kansas City, Kansas.,Heartland Center for Mitochondrial Medicine, The University of Kansas Medical Center, Kansas City, Kansas.,The University Kansas Cancer Center, The University of Kansas Medical Center, Kansas City, Kansas
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37
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van der Weyden L, Karp NA, Swiatkowska A, Adams DJ, Speak AO. Genome wide in vivo mouse screen data from studies to assess host regulation of metastatic colonisation. Sci Data 2017; 4:170129. [PMID: 28895944 PMCID: PMC5827107 DOI: 10.1038/sdata.2017.129] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 07/28/2017] [Indexed: 02/02/2023] Open
Abstract
The process of metastasis is a multi-stage cascade with prior studies suggesting that the colonisation of the secondary site is the rate limiting step. This process involves contributions from the tumour cells and also non-tumour intrinsic factors such as the stroma and the haematopoietic system. In this study, we present data from screening 810 genetically-modified mouse lines with the experimental metastasis assay where intravenous delivery of murine metastatic melanoma B16-F10 cells was used to assess the formation of pulmonary metastasic foci. To date, these data have been studied with a two-step process cumulating in an integrative data analysis to identify genes controlling metastatic colonisation. We present the raw data, and a description to support fresh analyses where researchers can look both within and across gene sets to further elucidate process that regulate metastatic colonisation.
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Affiliation(s)
| | - Natasha A Karp
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK.,Quantitative Biology, IMED, AstraZeneca, Darwin Building (Unit 310), Cambridge Science Park, Milton Road, Cambridge CB4 0WG, UK
| | | | - David J Adams
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
| | - Anneliese O Speak
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
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38
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Suwanmanee T, Ferris MT, Hu P, Gui T, Montgomery SA, Pardo-Manuel de Villena F, Kafri T. Toward Personalized Gene Therapy: Characterizing the Host Genetic Control of Lentiviral-Vector-Mediated Hepatic Gene Delivery. Mol Ther Methods Clin Dev 2017; 5:83-92. [PMID: 28480308 PMCID: PMC5415322 DOI: 10.1016/j.omtm.2017.03.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 03/30/2017] [Indexed: 12/21/2022]
Abstract
The success of lentiviral vectors in curing fatal genetic and acquired diseases has opened a new era in human gene therapy. However, variability in the efficacy and safety of this therapeutic approach has been reported in human patients. Consequently, lentiviral-vector-based gene therapy is limited to incurable human diseases, with little understanding of the underlying causes of adverse effects and poor efficacy. To assess the role that host genetic variation has on efficacy of gene therapy, we characterized lentiviral-vector gene therapy within a set of 12 collaborative cross mouse strains. Lentiviral vectors carrying the firefly luciferase cDNA under the control of a liver-specific promoter were administered to female mice, with total-body and hepatic luciferase expression periodically monitored through 41 weeks post-vector administration. Vector copy number per diploid genome in mouse liver and spleen was determined at the end of this study. We identified major strain-specific contributions to overall success of transduction, vector biodistribution, maximum luciferase expression, and the kinetics of luciferase expression throughout the study. Our results highlight the importance of genetic variation on gene-therapeutic efficacy; provide new models with which to more rigorously assess gene therapy approaches; and suggest that redesigning preclinical studies of gene-therapy methodologies might be appropriate.
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Affiliation(s)
- Thipparat Suwanmanee
- Gene Therapy Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Martin T. Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Peirong Hu
- Gene Therapy Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tong Gui
- Gene Therapy Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Stephanie A. Montgomery
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tal Kafri
- Gene Therapy Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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