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2. Phenotypic expansion of CACNA1C-associated disorders to include isolated neurological manifestations
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Lance H. Rodan, Rebecca C. Spillmann, Harley T. Kurata, Shawn M. Lamothe, Jasmine Maghera, Rami Abou Jamra, Anna Alkelai, Stylianos E. Antonarakis, Isis Atallah, Omer Bar-Yosef, Frédéric Bilan, Kathrine Bjorgo, Xavier Blanc, Patrick Van Bogaert, Yoav Bolkier, Lindsay C. Burrage, Björn U. Christ, Jorge L. Granadillo, Patricia Dickson, Kirsten A. Donald, Christèle Dubourg, Aviva Eliyahu, Lisa Emrick, Kendra Engleman, Michaela Veronika Gonfiantini, Jean-Marc Good, Judith Kalser, Chiara Kloeckner, Guus Lachmeijer, Marina Macchiaiolo, Francesco Nicita, Sylvie Odent, Emily O’Heir, Xilma Ortiz-Gonzalez, Marta Pacio-Miguez, María Palomares-Bralo, Loren Pena, Konrad Platzer, Mathieu Quinodoz, Emmanuelle Ranza, Jill A. Rosenfeld, Eliane Roulet-Perez, Avni Santani, Fernando Santos-Simarro, Ben Pode-Shakked, Cara Skraban, Rachel Slaugh, Andrea Superti-Furga, Isabelle Thiffault, Richard H. van Jaabrsveld, Marie Vincent, Hong-Gang Wang, Pia Zacher, Mercedes E. Alejandro, Mahshid S. Azamian, Carlos A. Bacino, Ashok Balasubramanyam, Hsiao-Tuan Chao, Gary D. Clark, William J. Craigen, Hongzheng Dai, Shweta U. Dhar, Lisa T. Emrick, Alica M. Goldman, Neil A. Hanchard, Fariha Jamal, Lefkothea Karaviti, Seema R. Lalani, Brendan H. Lee, Richard A. Lewis, Ronit Marom, Paolo M. Moretti, David R. Murdock, Sarah K. Nicholas, James P. Orengo, Jennifer E. Posey, Lorraine Potocki, Susan L. Samson, Daryl A. Scott, Alyssa A. Tran, Tiphanie P. Vogel, Michael F. Wangler, Shinya Yamamoto, Christine M. Eng, Pengfei Liu, Patricia A. Ward, Edward Behrens, Matthew Deardorff, Marni Falk, Kelly Hassey, Kathleen Sullivan, Adeline Vanderver, David B. Goldstein, Heidi Cope, Allyn McConkie-Rosell, Kelly Schoch, Vandana Shashi, Edward C. Smith, Jennifer A. Sullivan, Queenie K.-G. Tan, Nicole M. Walley, Pankaj B. Agrawal, Alan H. Beggs, Gerard T. Berry, Lauren C. Briere, Laurel A. Cobban, Matthew Coggins, Cynthia M. Cooper, Elizabeth L. Fieg, Frances High, Ingrid A. Holm, Susan Korrick, Joel B. Krier, Sharyn A. Lincoln, Joseph Loscalzo, Richard L. Maas, Calum A. MacRae, J. Carl Pallais, Deepak A. Rao, Edwin K. Silverman, Joan M. Stoler, David A. Sweetser, Melissa Walker, Chris A. Walsh, Cecilia Esteves, Emily G. Kelley, Isaac S. Kohane, Kimberly LeBlanc, Alexa T. McCray, Anna Nagy, Surendra Dasari, Brendan C. Lanpher, Ian R. Lanza, Eva Morava, Devin Oglesbee, Guney Bademci, Deborah Barbouth, Stephanie Bivona, Olveen Carrasquillo, Ta Chen Peter Chang, Irman Forghani, Alana Grajewski, Rosario Isasi, Byron Lam, Roy Levitt, Xue Zhong Liu, Jacob McCauley, Ralph Sacco, Mario Saporta, Judy Schaechter, Mustafa Tekin, Fred Telischi, Willa Thorson, Stephan Zuchner, Heather A. Colley, Jyoti G. Dayal, David J. Eckstein, Laurie C. Findley, Donna M. Krasnewich, Laura A. Mamounas, Teri A. Manolio, John J. Mulvihill, Grace L. LaMoure, Madison P. Goldrich, Tiina K. Urv, Argenia L. Doss, Maria T. Acosta, Carsten Bonnenmann, Precilla D’Souza, David D. Draper, Carlos Ferreira, Rena A. Godfrey, Catherine A. Groden, Ellen F. Macnamara, Valerie V. Maduro, Thomas C. Markello, Avi Nath, Donna Novacic, Barbara N. Pusey, Camilo Toro, Colleen E. Wahl, Eva Baker, Elizabeth A. Burke, David R. Adams, William A. Gahl, May Christine V. Malicdan, Cynthia J. Tifft, Lynne A. Wolfe, John Yang, Bradley Power, Bernadette Gochuico, Laryssa Huryn, Lea Latham, Joie Davis, Deborah Mosbrook-Davis, Francis Rossignol, null Ben Solomon, John MacDowall, Audrey Thurm, Wadih Zein, Muhammad Yousef, Margaret Adam, Laura Amendola, Michael Bamshad, Anita Beck, Jimmy Bennett, Beverly Berg-Rood, Elizabeth Blue, Brenna Boyd, Peter Byers, Sirisak Chanprasert, Michael Cunningham, Katrina Dipple, Daniel Doherty, Dawn Earl, Ian Glass, Katie Golden-Grant, Sihoun Hahn, Anne Hing, Fuki M. Hisama, Martha Horike-Pyne, Gail P. Jarvik, Jeffrey Jarvik, Suman Jayadev, Christina Lam, Kenneth Maravilla, Heather Mefford, J. Lawrence Merritt, Ghayda Mirzaa, Deborah Nickerson, Wendy Raskind, Natalie Rosenwasser, C. Ron Scott, Angela Sun, Virginia Sybert, Stephanie Wallace, Mark Wener, Tara Wenger, Euan A. Ashley, Gill Bejerano, Jonathan A. Bernstein, Devon Bonner, Terra R. Coakley, Liliana Fernandez, Paul G. Fisher, Laure Fresard, Jason Hom, Yong Huang, Jennefer N. Kohler, Elijah Kravets, Marta M. Majcherska, Beth A. Martin, Shruti Marwaha, Colleen E. McCormack, Archana N. Raja, Chloe M. Reuter, Maura Ruzhnikov, Jacinda B. Sampson, Kevin S. Smith, Shirley Sutton, Holly K. Tabor, Brianna M. Tucker, Matthew T. Wheeler, Diane B. Zastrow, Chunli Zhao, William E. Byrd, Andrew B. Crouse, Matthew Might, Mariko Nakano-Okuno, Jordan Whitlock, Gabrielle Brown, Manish J. Butte, Esteban C. Dell’Angelica, Naghmeh Dorrani, Emilie D. Douine, Brent L. Fogel, Irma Gutierrez, Alden Huang, Deborah Krakow, Hane Lee, Sandra K. Loo, Bryan C. Mak, Martin G. Martin, Julian A. Martínez-Agosto, Elisabeth McGee, Stanley F. Nelson, Shirley Nieves-Rodriguez, Christina G.S. Palmer, Jeanette C. Papp, Neil H. Parker, Genecee Renteria, Rebecca H. Signer, Janet S. Sinsheimer, Jijun Wan, Lee-kai Wang, Katherine Wesseling Perry, Jeremy D. Woods, Justin Alvey, Ashley Andrews, Jim Bale, John Bohnsack, Lorenzo Botto, John Carey, Laura Pace, Nicola Longo, Gabor Marth, Paolo Moretti, Aaron Quinlan, Matt Velinder, Dave Viskochil, Pinar Bayrak-Toydemir, Rong Mao, Monte Westerfield, Anna Bican, Elly Brokamp, Laura Duncan, Rizwan Hamid, Jennifer Kennedy, Mary Kozuira, John H. Newman, John A. PhillipsIII, Lynette Rives, Amy K. Robertson, Emily Solem, Joy D. Cogan, F. Sessions Cole, Nichole Hayes, Dana Kiley, Kathy Sisco, Jennifer Wambach, Daniel Wegner, Dustin Baldridge, Stephen Pak, Timothy Schedl, Jimann Shin, Lilianna Solnica-Krezel, Eric Rush, Geoffrey S. Pitt, Ping Yee Billie Au, Boston Children's Hospital, University of Alberta, Universität Leipzig [Leipzig], Geneva University Hospital (HUG), Tel Aviv University [Tel Aviv], Service Génétique Médicale [CHU Poitiers], Centre hospitalier universitaire de Poitiers (CHU Poitiers), Cibles moléculaires et thérapeutiques de la maladie d'Alzheimer (CIMoTHeMA), Université de Poitiers, Laboratoire Jacques-Louis Lions (LJLL (UMR_7598)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Baylor College of Medicine (BCM), Baylor University, Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), CHU Pontchaillou [Rennes], Institut de Génétique et Développement de Rennes (IGDR), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Lausanne University Hospital, Centre de référence Maladies Rares CLAD-Ouest [Rennes], Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Children’s Hospital of Philadelphia (CHOP ), Hospital Universitario La Paz, unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Centre hospitalier universitaire de Nantes (CHU Nantes), Duke University [Durham], University of Kansas Medical Center [Lawrence], University of Missouri System, Children's Mercy Hospital [Kansas City], Weill Cornell Medicine [New York], University of Calgary, Research reported in this paper was supported by the NIH Common Fund, through the Office of Strategic Coordination/Office of the NIH Director under award number(s) (U01HG007709 [Baylor College of Medicine] and U01HG007672 [Duke University to V.S.]). Additional funding for this project was under award number 1RO1HD090132-01A1 (Cornell University to G.P.). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional funding was provided by a Canadian Institutes of Health Research Grant (MOP-97988 to H.T.K.), and a Rowland and Muriel Haryett Fellowship (University of Alberta, to S.M.L.) and a fellowship from the Ministry of Education and Research of the Community of Madrid to M.P.M. (B2017/BMD-3721), and microgrant from the Rare Disease Foundation (P.Y.B.A. and H.T.K.). Sequencing and analysis was supported by the National Human Genome Research Institute grants UM1 HG008900 and R01 HG009141. K.A.D., B.C., and E.O. were supported the National Institute of Mental Health U01 MH119689., Universität Leipzig, Columbia University Medical Center (CUMC), Columbia University [New York], Tel Aviv University (TAU), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Unité de recherche de l'institut du thorax (ITX-lab), University of Kansas Medical Center [Kansas City, KS, USA], Weill Cornell Medicine [Cornell University], and Cornell University [New York]
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Ataxia ,Calcium Channels, L-Type ,Long QT syndrome ,Timothy syndrome ,Bioinformatics ,Article ,03 medical and health sciences ,Epilepsy ,0302 clinical medicine ,Intellectual disability ,medicine ,Missense mutation ,Humans ,Autistic Disorder ,Genetics (clinical) ,030304 developmental biology ,0303 health sciences ,[SDV.GEN]Life Sciences [q-bio]/Genetics ,business.industry ,medicine.disease ,Hypotonia ,Long QT Syndrome ,Phenotype ,Autism ,Syndactyly ,medicine.symptom ,business ,030217 neurology & neurosurgery - Abstract
International audience; Purpose:CACNA1C encodes the alpha-1-subunit of a voltage-dependent L-type calcium channel expressed in human heart and brain. Heterozygous variants in CACNA1C have previously been reported in association with Timothy syndrome and long QT syndrome. Several case reports have suggested that CACNA1C variation may also be associated with a primarily neurological phenotype.Methods:We describe 25 individuals from 22 families with heterozygous variants in CACNA1C, who present with predominantly neurological manifestations.Results:Fourteen individuals have de novo, nontruncating variants and present variably with developmental delays, intellectual disability, autism, hypotonia, ataxia, and epilepsy. Functional studies of a subgroup of missense variants via patch clamp experiments demonstrated differential effects on channel function in vitro, including loss of function (p.Leu1408Val), neutral effect (p.Leu614Arg), and gain of function (p.Leu657Phe, p.Leu614Pro). The remaining 11 individuals from eight families have truncating variants in CACNA1C. The majority of these individuals have expressive language deficits, and half have autism.Conclusion:We expand the phenotype associated with CACNA1C variants to include neurodevelopmental abnormalities and epilepsy, in the absence of classic features of Timothy syndrome or long QT syndrome.
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- 2020
3. The nicotinic receptor alpha5 coding polymorphism rs16969968 as a major target in disease: Functional dissection and remaining challenges
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Uwe Maskos, Neurobiologie intégrative des Systèmes cholinergiques / Integrative Neurobiology of Cholinergic Systems (NISC), Sorbonne Université (SU)-Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), he author has received funding to carry out the work of his laboratory described in the Review article, as indicated in the published papers. No funding has been received that is directly relevant to this Review article. The author has no conflict of interest to declare., and Institut Pasteur [Paris] (IP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)
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0301 basic medicine ,human genetics ,Single-nucleotide polymorphism ,Locus (genetics) ,Genome-wide association study ,Disease ,Receptors, Nicotinic ,Biology ,Bioinformatics ,Polymorphism, Single Nucleotide ,Biochemistry ,nicotine addiction ,drug discovery ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,[SCCO]Cognitive science ,0302 clinical medicine ,single nucleotide polymorphism ,Animals ,Humans ,nicotinic acetylcholine receptor ,Genetic association ,[SCCO.NEUR]Cognitive science/Neuroscience ,Human genetics ,3. Good health ,schizophrenia ,Nicotinic acetylcholine receptor ,030104 developmental biology ,Nicotinic agonist ,positive allosteric modulator ,Genome-wide Association Studies ,030217 neurology & neurosurgery - Abstract
International audience; Nicotinic acetylcholine receptors (nAChRs) are major signalling molecules in the central and peripheral nervous system. Over the last decade, they have been linked to a number of major human psychiatric and neurological conditions, like smoking, schizophrenia, Alzheimer's disease and many others. Human Genome-Wide Association Studies (GWAS) have robustly identified genetic alterations at a locus of chromosome 15q to several of these diseases. In this review, we discuss a major coding polymorphism in the alpha5 subunit, referred to as α5SNP, and its functional dissection in vitro and in vivo. Its presence at high frequency in many human populations lends itself to pharmaceutical intervention in the context of 'positive allosteric modulators' (PAMs). We will present the prospects of this novel treatment, and the remaining challenges to identify suitable molecules.
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- 2020
4. Quantifying model evidence for yellow fever transmission routes in Africa
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Katy A. M. Gaythorpe, Laurence Cibrelus, Tini Garske, Kévin Jean, Imperial College London, Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires (MESuRS), Conservatoire National des Arts et Métiers [CNAM] (CNAM), Pasteur-Cnam Risques infectieux et émergents (PACRI), Institut Pasteur [Paris]-Conservatoire National des Arts et Métiers [CNAM] (CNAM), World Health Organisation (WHO), Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), Funding:This work was carried out as part of the Vaccine Impact Modelling Consortium (www.vaccineimpact.org),but the views expressed are those of the authors and not necessarily those of the Consortium or its funders.The funders were given the opportunity to review this paper prior to publication,but the final decision on the content of the publication was taken by the authors.We acknowledge joint Centre funding from the UK Medical Research Council and Department for International Development. The research leading to these results has received funding from the Bill & Melinda Gates foundation (OPP1117543,OPP1157270 http://www.gatesfoundation.org/)and from the Medical Research Council (MR/R015600/1https://mrc.ukri.org/)., HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM), and Institut Pasteur [Paris] (IP)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)
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0301 basic medicine ,Viral Diseases ,Epidemiology ,Force of infection ,Statics ,Pathology and Laboratory Medicine ,law.invention ,Geographical Locations ,Bayes' theorem ,0302 clinical medicine ,law ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Aedes ,Statistics ,Medicine and Health Sciences ,Public and Occupational Health ,Biology (General) ,Ecology ,Physics ,Yellow fever ,Linear model ,Classical Mechanics ,Vaccination and Immunization ,Geography ,Transmission (mechanics) ,Infectious Diseases ,Serology ,Computational Theory and Mathematics ,INFECTIONS ,Modeling and Simulation ,Physical Sciences ,Yellow fever virus ,Life Sciences & Biomedicine ,Research Article ,Generalized linear model ,Biochemistry & Molecular Biology ,Bioinformatics ,QH301-705.5 ,Immunology ,Bayesian inference ,Models, Biological ,Biochemical Research Methods ,BAYESIAN MODEL ,Infectious Disease Epidemiology ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Yellow Fever ,Genetics ,medicine ,Animals ,Humans ,Molecular Biology ,01 Mathematical Sciences ,Ecology, Evolution, Behavior and Systematics ,Estimation ,Science & Technology ,Models, Statistical ,Biology and Life Sciences ,Computational Biology ,Bayes Theorem ,06 Biological Sciences ,medicine.disease ,030104 developmental biology ,People and Places ,Africa ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Mathematical & Computational Biology ,08 Information and Computing Sciences ,Preventive Medicine ,030217 neurology & neurosurgery - Abstract
Yellow fever is a vector-borne disease endemic in tropical regions of Africa, where 90% of the global burden occurs, and Latin America. It is notoriously under-reported with uncertainty arising from a complex transmission cycle including a sylvatic reservoir and non-specific symptom set. Resulting estimates of burden, particularly in Africa, are highly uncertain. We examine two established models of yellow fever transmission within a Bayesian model averaging framework in order to assess the relative evidence for each model’s assumptions and to highlight possible data gaps. Our models assume contrasting scenarios of the yellow fever transmission cycle in Africa. The first takes the force of infection in each province to be static across the observation period; this is synonymous with a constant infection pressure from the sylvatic reservoir. The second model assumes the majority of transmission results from the urban cycle; in this case, the force of infection is dynamic and defined through a fixed value of R0 in each province. Both models are coupled to a generalised linear model of yellow fever occurrence which uses environmental covariates to allow us to estimate transmission intensity in areas where data is sparse. We compare these contrasting descriptions of transmission through a Bayesian framework and trans-dimensional Markov chain Monte Carlo sampling in order to assess each model’s evidence given the range of uncertainty in parameter values. The resulting estimates allow us to produce Bayesian model averaged predictions of yellow fever burden across the African endemic region. We find strong support for the static force of infection model which suggests a higher proportion of yellow fever transmission occurs as a result of infection from an external source such as the sylvatic reservoir. However, the model comparison highlights key data gaps in serological surveys across the African endemic region. As such, conclusions concerning the most prevalent transmission routes for yellow fever will be limited by the sparsity of data which is particularly evident in the areas with highest predicted transmission intensity. Our model and estimation approach provides a robust framework for model comparison and predicting yellow fever burden in Africa. However, key data gaps increase uncertainty surrounding estimates of model parameters and evidence. As more mathematical models are developed to address new research questions, it is increasingly important to compare them with established modelling approaches to highlight uncertainty in structures and data., Author summary Yellow fever (YF) is notoriously under reported due to non-specific symptom spectrum and the true burden is highly uncertain as a result of a complex transmission cycle. As such, estimates surrounding YF burden are highly uncertain and the mechanisms behind transmission are often unclear. We assess these mechanisms and the resulting uncertainty by estimating two existing models of YF transmission within a product space framework. This allows us to produce updated estimates of transmission intensity and to compare the relative support for each model given the data. We find strong support for a model assuming a static force of infection, approximating the constant infection pressure from the sylvatic reservoir of YF. We also highlight areas where data is sparse, often the same areas estimated to have especially high transmission intensity. This is the first robust multi-model approach to applied YF modelling and provides a framework that could be extended to other disease models.
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- 2019
5. Tumour heterogeneity: the key advantages of single-cell analysis
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Francois Lamoureux, Marta Tellez-Gabriel, Benjamin Ory, Dominique Heymann, Marie-Françoise Heymann, Laboratorio Hematologia Oncologica y de Transplantes [Barcelona, Spain], Institut Investigacions Biomèdiques (IBB) Sant Pau [Barcelona, Spain]-Hospital de la Santa Creu i Sant Pau, Equipe LIGUE Nationale Contre le Cancer 2012, Physiopathologie des Adaptations Nutritionnelles (PhAN), Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Oncology and Metabolism [Sheffield, UK], The University of Sheffield [Sheffield, U.K.], European Associated Laboratory [Sheffield, UK] (Sarcoma Research Unit), This paper was written as a part of a research project which received funding from the Seventh Framework Programme ([FP7/2007-2013]) under grant agreement n 264817—BONE-NET. This work was supported by the Bone Cancer Research Trust (UK, research project number 144681)., European Project: 264817,EC:FP7:PEOPLE,FP7-PEOPLE-2010-ITN,BONE-NET(2011), Heymann, Dominique, and European Training Network on Cancer-Induced Bone Diseases - BONE-NET - - EC:FP7:PEOPLE2011-02-01 - 2015-01-31 - 264817 - VALID
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0301 basic medicine ,Tumour heterogeneity ,circulating tumour cells ,[SDV.CAN]Life Sciences [q-bio]/Cancer ,Disease ,Review ,Biology ,Bioinformatics ,Catalysis ,lcsh:Chemistry ,Inorganic Chemistry ,03 medical and health sciences ,Genetic Heterogeneity ,[SDV.MHEP.PED] Life Sciences [q-bio]/Human health and pathology/Pediatrics ,Single-cell analysis ,[SDV.CAN] Life Sciences [q-bio]/Cancer ,single cells ,Neoplasms ,Gene expression ,Biopsy ,medicine ,Humans ,Epigenetics ,Physical and Theoretical Chemistry ,Neoplasm Metastasis ,lcsh:QH301-705.5 ,Molecular Biology ,Spectroscopy ,[SDV.MHEP.EM] Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism ,[SDV.MHEP.RSOA] Life Sciences [q-bio]/Human health and pathology/Rhumatology and musculoskeletal system ,[SDV.MHEP.PED]Life Sciences [q-bio]/Human health and pathology/Pediatrics ,medicine.diagnostic_test ,Organic Chemistry ,General Medicine ,[SDV.MHEP.EM]Life Sciences [q-bio]/Human health and pathology/Endocrinology and metabolism ,Neoplastic Cells, Circulating ,Phenotype ,3. Good health ,Computer Science Applications ,030104 developmental biology ,lcsh:Biology (General) ,lcsh:QD1-999 ,[SDV.MHEP.RSOA]Life Sciences [q-bio]/Human health and pathology/Rhumatology and musculoskeletal system ,Cancer cell ,Cancer research ,Single-Cell Analysis ,heterogeneity - Abstract
International audience; Tumour heterogeneity refers to the fact that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation, and metastatic potential. This phenomenon occurs both between tumours (inter-tumour heterogeneity) and within tumours (intra-tumour heterogeneity), and it is caused by genetic and non-genetic factors. The heterogeneity of cancer cells introduces significant challenges in using molecular prognostic markers as well as for classifying patients that might benefit from specific therapies. Thus, research efforts for characterizing heterogeneity would be useful for a better understanding of the causes and progression of disease. It has been suggested that the study of heterogeneity within Circulating Tumour Cells (CTCs) could also reflect the full spectrum of mutations of the disease more accurately than a single biopsy of a primary or metastatic tumour. In the last years many high throughput methodologies have raised for the study of heterogeneity at different levels (i.e.: RNA, DNA, protein, epigenetic events). The aim of the current review is to stress clinical implications of tumour heterogeneity, as well as current available methodologies for their study with a specific attention to those able to assess heterogeneity at the single cell level.
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- 2016
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