A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.
Aravind Subramanian,Rajiv Narayan,Steven M. Corsello,Steven M. Corsello,David Peck,Ted Natoli,Xiaodong Lu,Joshua Gould,John F. Davis,Andrew A. Tubelli,Jacob K. Asiedu,David L. Lahr,Jodi E. Hirschman,Zihan Liu,Melanie Donahue,Bina Julian,Mariya Khan,David Wadden,Ian Smith,Daniel D. Lam,Arthur Liberzon,Courtney Toder,Mukta Bagul,Marek Orzechowski,Oana M. Enache,Federica Piccioni,Sarah A. Johnson,Nicholas J. Lyons,Alice H. Berger,Alice H. Berger,Alykhan F. Shamji,Angela N. Brooks,Angela N. Brooks,Anita Vrcic,Corey Flynn,Jacqueline Rosains,David Y. Takeda,David Y. Takeda,Roger Hu,Desiree Davison,Justin Lamb,Kristin Ardlie,Larson Hogstrom,Peyton Greenside,Nathanael S. Gray,Nathanael S. Gray,Paul A. Clemons,Serena J. Silver,Xiaoyun Wu,Wen-Ning Zhao,Wen-Ning Zhao,Willis Read-Button,Xiaohua Wu,Stephen J. Haggarty,Stephen J. Haggarty,Lucienne Ronco,Jesse S. Boehm,Stuart L. Schreiber,Stuart L. Schreiber,Stuart L. Schreiber,John G. Doench,Joshua A. Bittker,David E. Root,Bang Wong,Todd R. Golub +64 more
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TLDR
The expanded CMap is reported, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that is shown to be highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts.About:
This article is published in Cell.The article was published on 2017-11-30 and is currently open access. It has received 1943 citations till now.read more
Citations
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Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
Tathiane M. Malta,Artem Sokolov,Andrew J. Gentles,Tomasz Burzykowski,Laila M. Poisson,John N. Weinstein,Bozena Kaminska,Joerg Huelsken,Larsson Omberg,Olivier Gevaert,Antonio Colaprico,Patrycja Czerwińska,Sylwia Mazurek,Lopa Mishra,Holger Heyn,Alexander Krasnitz,Andrew K. Godwin,Alexander J. Lazar,Joshua M. Stuart,Katherine A Hoadley,Peter W. Laird,Houtan Noushmehr,Maciej Wiznerowicz +22 more
TL;DR: Novel stemness indices for assessing the degree of oncogenic dedifferentiation are provided and it is found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors.
Journal ArticleDOI
A Cancer Cell Program Promotes T Cell Exclusion and Resistance to Checkpoint Blockade
Livnat Jerby-Arnon,Parin Shah,Michael S. Cuoco,Christopher Rodman,Mei-Ju Su,Johannes C. Melms,Rachel Leeson,Abhay Kanodia,Shaolin Mei,Jia-Ren Lin,Shu Wang,Bokang Rabasha,David Liu,Gao Zhang,Claire Margolais,Orr Ashenberg,Patrick A. Ott,Elizabeth I. Buchbinder,Rizwan Haq,F. Stephen Hodi,Genevieve M. Boland,Ryan J. Sullivan,Dennie T. Frederick,Benchun Miao,Tabea Moll,Keith T. Flaherty,Meenhard Herlyn,Russell W. Jenkins,Rohit Thummalapalli,Monika S. Kowalczyk,Israel Cañadas,Bastian Schilling,Bastian Schilling,Adam N.R. Cartwright,Adrienne M. Luoma,Shruti Malu,Patrick Hwu,Chantale Bernatchez,Marie Andrée Forget,David A. Barbie,Alex K. Shalek,Itay Tirosh,Peter K. Sorger,Kai W. Wucherpfennig,Eliezer M. Van Allen,Dirk Schadendorf,Bruce E. Johnson,Asaf Rotem,Asaf Rotem,Orit Rozenblatt-Rosen,Levi A. Garraway,Charles H. Yoon,Charles H. Yoon,Benjamin Izar,Aviv Regev +54 more
TL;DR: A resistance program expressed by malignant cells that is associated with T cell exclusion and immune evasion is identified, and this study provides a high-resolution landscape of ICI-resistant cell states, identifies clinically predictive signatures, and suggests new therapeutic strategies to overcome immunotherapy resistance.
Journal ArticleDOI
Genetic and transcriptional evolution alters cancer cell line drug response
Uri Ben-David,Benjamin A. Siranosian,Gavin Ha,Gavin Ha,Helen Tang,Yaara Oren,Yaara Oren,Kunihiko Hinohara,Kunihiko Hinohara,Craig A. Strathdee,Joshua M. Dempster,Nicholas J. Lyons,Robert Burns,Anwesha Nag,Guillaume Kugener,Beth A. Cimini,Peter Tsvetkov,Yosef E. Maruvka,Ryan O’Rourke,Ryan O’Rourke,Anthony J. Garrity,Andrew A. Tubelli,Pratiti Bandopadhayay,Pratiti Bandopadhayay,Aviad Tsherniak,Francisca Vazquez,Bang Wong,Chet Birger,Mahmoud Ghandi,Aaron R. Thorner,Joshua A. Bittker,Matthew Meyerson,Matthew Meyerson,Gad Getz,Gad Getz,Rameen Beroukhim,Todd R. Golub +36 more
TL;DR: The extent, origins and consequences of genetic variation within human cell lines are studied, providing a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.
Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens
Atray Dixit,Atray Dixit,Oren Parnas,Biyu Li,Jenny Chen,Jenny Chen,Charles P. Fulco,Charles P. Fulco,Livnat Jerby-Arnon,Nemanja D. Marjanovic,Nemanja D. Marjanovic,Danielle Dionne,Tyler Burks,Raktima Raychowdhury,Britt Adamson,Thomas M. Norman,Eric S. Lander,Eric S. Lander,Eric S. Lander,Jonathan S. Weissman,Jonathan S. Weissman,Nir Friedman,Nir Friedman,Aviv Regev,Aviv Regev,Aviv Regev +25 more
TL;DR: Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions, and posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation.
Journal ArticleDOI
Concepts of Artificial Intelligence for Computer-Assisted Drug Discovery
TL;DR: The current state-of-the art of AI-assisted pharmaceutical discovery is discussed, including applications in structure- and ligand-based virtual screening, de novo drug design, physicochemical and pharmacokinetic property prediction, drug repurposing, and related aspects.
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