Marc Vidal, PhD
Director of Center for Cancer Systems Biology - CCSB
Office phone: 617-632-5114
Website: Center for Cancer Systems Biology
Preferred contact method: email
Area of Research
A Systems Approach to Cancer Biology
Dana-Farber Cancer Institute
450 Brookline Avenue
Boston, MA 02215
Dr. Vidal received his PhD in 1991 from Gembloux University (Belgium) for work performed at Northwestern University. He identified the yeast genes SIN3 and RPD3, and demonstrated that they encode global transcriptional regulators. During postdoctoral training at the Massachusetts General Hospital Cancer Center, he developed the reverse two-hybrid system to genetically characterize protein-protein interactions. In 2000, he joined DFCI, where his research focuses on understanding global and local properties of interactome networks.
- Chaire Francqui, Fondation Francqui, Belgium, 2005
- Abbott Bioresearch Award, Boston, MA, 2003
- Chercheur Qualifié du Fonds National de la Recherche Scientifique (Belgium), Permanent Position, 1997
ResearchA Systems Approach to Cancer Biology
Physical interactions mediated by proteins are critical for cellular function, constituting in toto complex macromolecular "interactome" networks. Systematic mapping of protein-protein, protein-DNA, protein-RNA and protein-metabolite interactions at the scale of the whole proteome advances understanding of interactome networks. Applications range from functional characterization of single proteins to discoveries on local and global systems properties of cellular networks. We generate and improve comprehensive interactome maps for multiple organisms (currently human, the model unicellular eukaryote yeast S. cerevisiae, and the model metazoan D. melanogaster). To ensure that the interactome maps we release are of the highest possible quality we carry out all experimental steps thoroughly and carefully, verifying all interacting pairs and validating them by independent, orthogonal assays.
Classical forward genetics and modern functional genomics (i.e. reverse genetics) have assigned potential functions to thousands of genes across dozens of organisms. The availability of genome sequences and the development of automated phenotypic analyses makes reverse genetics strategies based on null or nearly null alleles a major source of gene function information. Functional interpretation of (nearly) null alleles is often complicated because gene products do not operate in isolation but instead act on each other within complex and dynamic interactome networks. In interactome graphs, knockouts or knockdowns eliminate a node and ALL its edges. We have been developing alternatives to generate alleles that perturb a single interaction, or edge at a time, while maintaining all others unperturbed. Such “edgetic” alleles allow precise evaluation of the in vivo roles of individual interactions. We have provided proof-of-principle of an integrated strategy based on reverse yeast two-hybrid to isolate edgetic alleles and functionally characterize them in vivo. This strategy could be readily implemented for other biological pathways in other model organisms.
Many mutations responsible for human disease might also be edgetic. Edgetic mutations would be different in their effects and properties than the complete losses of gene products (node removal) generally accepted as primarily responsible for disease. Conventional node removal models for disease cannot reconcile with the increasingly appreciated prevalence of complex genotype-to-phenotype associations for even simple Mendelian disorders, particularly the confounding influence of allelic heterogeneity, locus heterogeneity, incomplete penetrance, and variable expressivity. We have delineated clear distinctions of mutations corresponding to node removal versus edgetic perturbations in the full set of mutations associated with human Mendelian disorders. Mutations associated with recessive disorders are more likely node removal, whereas mutations associated with dominant disorders are more likely edgetic. We have developed and tested an experimental platform that can characterize, at high throughput, edgetic interaction profiles of mutant disease proteins. We are currently using this platform at high throughput to edgetically profile cancer mutations, both the set of mutations already identified as well as the vaster set of cancer mutations being identified by cancer genome projects.
To learn more about the Vidal Lab or the Center for Cancer Systems Biology, please visit http://ccsb.dfci.harvard.edu.
- Walhout AJ, Sordella R, Lu X, Hartley JL, Temple GF, Brasch MA, Thierry-Mieg N, Vidal M. Protein interaction mapping in C. elegans using proteins involved in vulval development. Science 2000; 287:116-22.
- Ge H, Liu Z, Church GM, Vidal M. Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Nat Genet 2001; 29:482-6.
- Boulton SJ, Gartner A, Reboul J, Vaglio P, Dyson N, Hill DE, Vidal M. Combined functional genomic maps of the C. elegans DNA damage response. Science 2002; 295:127-31.
- Reboul J, Vaglio P, Rual JF, Lamesch P, Martinez M, Armstrong CM, Li S, Jacotot L, Bertin N, Janky R, Moore T, Hudson JR, Jr., Hartley JL, Brasch MA, Vandenhaute J, Boulton S, Endress GA, Jenna S, Chevet E, Papasotiropoulos V, Tolias PP, Ptacek J, Snyder M, Huang R, Chance MR, Lee H, Doucette-Stamm L, Hill DE, Vidal M. C. elegans ORFeome version 1.1: experimental verification of the genome annotation and resource for proteome-scale protein expression. Nat Genet 2003; 34:35-41.
- Li S, Armstrong CM, Bertin N, Ge H, Milstein S, Boxem M, Vidalain PO, Han JD, Chesneau A, Hao T, Goldberg DS, Li N, Martinez M, Rual JF, Lamesch P, Xu L, Tewari M, Wong SL, Zhang LV, Berriz GF, Jacotot L, Vaglio P, Reboul J, Hirozane-Kishikawa T, Li Q, Gabel HW, Elewa A, Baumgartner B, Rose DJ, Yu H, Bosak S, Sequerra R, Fraser A, Mango SE, Saxton WM, Strome S, Van Den Heuvel S, Piano F, Vandenhaute J, Sardet C, Gerstein M, Doucette-Stamm L, Gunsalus KC, Harper JW, Cusick ME, Roth FP, Hill DE, Vidal M. A map of the interactome network of the metazoan C. elegans. Science 2004; 303:540-3.
- Rual JF, Venkatesan K, Hao T, Hirozane-Kishikawa T, Dricot A, Li N, Berriz GF, Gibbons FD, Dreze M, Ayivi-Guedehoussou N, Klitgord N, Simon C, Boxem M, Milstein S, Rosenberg J, Goldberg DS, Zhang LV, Wong SL, Franklin G, Li S, Albala JS, Lim J, Fraughton C, Llamosas E, Cevik S, Bex C, Lamesch P, Sikorski RS, Vandenhaute J, Zoghbi HY, Smolyar A, Bosak S, Sequerra R, Doucette-Stamm L, Cusick ME, Hill DE, Roth FP, Vidal M . Towards a proteome-scale map of the human protein-protein interaction network. Nature 2005; 437:1173-8.
- Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Barabási AL. The human disease network. Proc Natl Acad Sci USA 2007; 104:8685-90.
- Yildirim MA, Goh KI, Cusick ME, Barabási AL, Vidal M. Drug-target network. Nat Biotechnol 2007; 25:1119-26.
- Pujana MA, Han JD, Starita LM, Stevens KN, Tewari M, Ahn JS, Rennert G, Moreno V, Kirchhoff T, Gold B, Assmann V, ElShamy WM, Rual JF, Levine D, Rozek LS, Gelman RS, Gunsalus KC, A. GR, Sobhian B, Bertin N, Venkatesan K, Ayivi-Guedehoussou N, Sole X, Hernandez P, Lazaro C, Nathanson KL, Weber BL, Cusick ME, Hill DE, Offit K, Livingston DM, Gruber SB, Parvin JD, Vidal M . Network modeling links breast cancer susceptibility and centrosome dysfunction. Nat Genet 2007; 39:1338-49.
- Yu H, Braun P, Yildirim MA, Lemmens I, Venkatesan K, Sahalie J, Hirozane-Kishikawa T, Gebreab F, Li N, Simonis N, Hao T, Rual JF, Dricot A, Vazquez A, Murray RR, Simon C, Tardivo L, Tam S, Svrzikapa N, Fan C, de Smet AS, Motyl A, Hudson ME, Park J, Xin X, Cusick ME, Moore T, Boone C, Snyder M, Roth FP, Barabási AL, Tavernier J, Hill DE, Vidal M. High-quality binary protein interaction map of the yeast interactome network. Science 2008; 322:104-10.
- Boxem M, Maliga Z, Klitgord N, Li N, Lemmens I, Mana M, de Lichtervelde L, Mul JD, van de Peut D, Devos M, Simonis N, Yildirim MA, Cokol M, Kao HL, de Smet AS, Wang H, Schlaitz AL, Hao T, Milstein S, Fan C, Tipsword M, Drew K, Galli M, Rhrissorrakrai K, Drechsel D, Koller D, Roth FP, Iakoucheva LM, Dunker AK, Bonneau R, Gunsalus KC, Hill DE, Piano F, Tavernier J, van den Heuvel S, Hyman AA, Vidal M . A protein domain-based interactome network for C. elegans early embryogenesis. Cell 2008; 134(3):534-45.
- Venkatesan K, Rual JF, Vazquez A, Stelzl U, Lemmens I, Hirozane-Kishikawa T, Hao T, Zenkner M, Xin X, Goh KI, Yildirim MA, Simonis N, Heinzmann K, Gebreab F, Sahalie JM, Cevik S, Simon C, de Smet AS, Dann E, Smolyar A, Vinayagam A, Yu H, Szeto D, Borick H, Dricot A, Klitgord N, Murray RR, Lin C, Lalowski M, Timm J, Rau K, Boone C, Braun P, Cusick ME, Roth FP, Hill DE, Tavernier J, Wanker EE, Barabási AL, Vidal M. An empirical framework for binary interactome mapping. Nat Methods 2009; 6:83-90.
- Zhong Q, Simonis N, Li QR, Charloteaux B, Heuze F, Klitgord N, Tam S, Yu H, Venkatesan K, Mou D, Swearingen V, Yildirim MA, Yan H, Dricot A, Szeto D, Lin C, Hao T, Fan C, Milstein S, Dupuy D, Brasseur R, Hill DE, Cusick ME, Vidal M. Edgetic perturbation models of human inherited disorders. Mol Syst Biol 2009; 5:321.
- Vidal M, Cusick ME, Barabási AL. Interactome networks and human disease. Cell 2011; 144:986-98.
- Rozenblatt-Rosen O, Deo RC, Padi M, Adelmant G, Calderwood MA, Rolland T, Grace M, Dricot A, Askenazi M, Tavares M, Pevzner SJ, Abderazzaq F, Byrdsong D, Carvunis AR, Chen AA, Cheng J, Correll M, Duarte M, Fan C, Feltkamp MC, Ficarro SB, Franchi R, Garg BK, Gulbahce N, Hao T, Holthaus AM, James R, Korkhin A, Litovchick L, Mar JC, Pak TR, Rabello S, Rubio R, Shen Y, Singh S, Spangle JM, Tasan M, Wanamaker S, Webber JT, Roecklein-Canfield J, Johannsen E, Barabási AL, Beroukhim R, Kieff E, Cusick ME, Hill DE, Münger K, Marto JA, Quackenbush J, Roth FP, DeCaprio JA, Vidal M. Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins. Nature 2012; 487:491-5.
- Yang, Xinping, Ph.D.
- Zhong, Quan, Ph.D.
- Yi, Song, Ph.D.
- Sanhi, Nidhi, Ph.D.
- Rolland, Thomas, Ph.D.
- Luck, Katja, Ph.D.
- Kamburov, Atanas, Ph.D.
- San Miguel, Adriana, Ph.D.
- Jailkhani, Noor, Ph.D.