A proteome-scale map of the human interactome network

Cell. 2014 Nov 20;159(5):1212-1226. doi: 10.1016/j.cell.2014.10.050.

Thomas Rolland ¹, Murat Taşan ², Benoit Charloteaux ¹, Samuel J Pevzner ³, Quan Zhong ⁴, Nidhi Sahni ¹, Song Yi ¹, Irma Lemmens ⁵, Celia Fontanillo ⁶, Roberto Mosca ⁷, Atanas Kamburov ¹, Susan D Ghiassian ⁸, Xinping Yang ¹, Lila Ghamsari ¹, Dawit Balcha ¹, Bridget E Begg ¹, Pascal Braun ¹, Marc Brehme ¹, Martin P Broly ¹, Anne-Ruxandra Carvunis ¹, Dan Convery-Zupan ¹, Roser Corominas ⁹, Jasmin Coulombe-Huntington ¹⁰, Elizabeth Dann ¹, Matija Dreze ¹, Amélie Dricot ¹, Changyu Fan ¹, Eric Franzosa ¹⁰, Fana Gebreab ¹, Bryan J Gutierrez ¹, Madeleine F Hardy ¹, Mike Jin ¹, Shuli Kang ⁹, Ruth Kiros ¹, Guan Ning Lin ⁹, Katja Luck ¹, Andrew MacWilliams ¹, Jörg Menche ⁸, Ryan R Murray ¹, Alexandre Palagi ¹, Matthew M Poulin ¹, Xavier Rambout ¹¹, John Rasla ¹, Patrick Reichert ¹, Viviana Romero ¹, Elien Ruyssinck ⁵, Julie M Sahalie ¹, Annemarie Scholz ¹, Akash A Shah ¹, Amitabh Sharma ⁸, Yun Shen ¹, Kerstin Spirohn ¹, Stanley Tam ¹, Alexander O Tejeda ¹, Shelly A Wanamaker ¹, Jean-Claude Twizere ¹¹, Kerwin Vega ¹, Jennifer Walsh ¹, Michael E Cusick ¹, Yu Xia ¹⁰, Albert-László Barabási ¹², Lilia M Iakoucheva ⁹, Patrick Aloy ¹³, Javier De Las Rivas ⁶, Jan Tavernier ⁵, Michael A Calderwood ¹, David E Hill ¹, Tong Hao ¹, Frederick P Roth ¹⁴, Marc Vidal ¹⁵

Affiliations

1 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
2 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Departments of Molecular Genetics and Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada; Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada.
3 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Boston University School of Medicine, Boston, MA 02118, USA.
4 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Department of Biological Sciences, Wright State University, Dayton, OH 45435, USA.
5 Department of Medical Protein Research, VIB, 9000 Ghent, Belgium.
6 Cancer Research Center (Centro de Investigación del Cancer), University of Salamanca and Consejo Superior de Investigaciones Científicas, Salamanca 37008, Spain.
7 Joint IRB-BSC Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain.
8 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Center for Complex Network Research (CCNR) and Department of Physics, Northeastern University, Boston, MA 02115, USA.
9 Department of Psychiatry, University of California, San Diego, La Jolla, CA 92093, USA.
10 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Bioengineering, McGill University, Montreal, QC H3A 0C3, Canada.
11 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Protein Signaling and Interactions Lab, GIGA-R, University of Liege, 4000 Liege, Belgium.
12 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Center for Complex Network Research (CCNR) and Department of Physics, Northeastern University, Boston, MA 02115, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
13 Joint IRB-BSC Program in Computational Biology, Institute for Research in Biomedicine (IRB Barcelona), Barcelona 08028, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain.
14 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Departments of Molecular Genetics and Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada; Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada; Canadian Institute for Advanced Research, Toronto M5G 1Z8, Canada. Electronic address: fritz.roth@utoronto.ca.
15 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. Electronic address: marc_vidal@dfci.harvard.edu.

PMID: 25416956 DOI: 10.1016/j.cell.2014.10.050

Abstract

Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate Cancer gene products, providing unbiased evidence for an expanded functional Cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

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