Literature DB >> 33068406

Project Score database: a resource for investigating cancer cell dependencies and prioritizing therapeutic targets.

Lisa Dwane1,2, Fiona M Behan1,2, Emanuel Gonçalves1, Howard Lightfoot1, Wanjuan Yang1, Dieudonne van der Meer1, Rebecca Shepherd1, Miguel Pignatelli1, Francesco Iorio1,2,3, Mathew J Garnett1,2.   

Abstract

CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR-Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets.
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Entities:  

Year:  2021        PMID: 33068406      PMCID: PMC7778984          DOI: 10.1093/nar/gkaa882

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  19 in total

Review 1.  What makes a good drug target?

Authors:  Isabella Gashaw; Peter Ellinghaus; Anette Sommer; Khusru Asadullah
Journal:  Drug Discov Today       Date:  2011-09-16       Impact factor: 7.851

2.  Trial watch: phase II and phase III attrition rates 2011-2012.

Authors:  John Arrowsmith; Philip Miller
Journal:  Nat Rev Drug Discov       Date:  2013-08       Impact factor: 84.694

3.  Innovation in the pharmaceutical industry: New estimates of R&D costs.

Authors:  Joseph A DiMasi; Henry G Grabowski; Ronald W Hansen
Journal:  J Health Econ       Date:  2016-02-12       Impact factor: 3.883

4.  Open Targets: a platform for therapeutic target identification and validation.

Authors:  Gautier Koscielny; Peter An; Denise Carvalho-Silva; Jennifer A Cham; Luca Fumis; Rippa Gasparyan; Samiul Hasan; Nikiforos Karamanis; Michael Maguire; Eliseo Papa; Andrea Pierleoni; Miguel Pignatelli; Theo Platt; Francis Rowland; Priyanka Wankar; A Patrícia Bento; Tony Burdett; Antonio Fabregat; Simon Forbes; Anna Gaulton; Cristina Yenyxe Gonzalez; Henning Hermjakob; Anne Hersey; Steven Jupe; Şenay Kafkas; Maria Keays; Catherine Leroy; Francisco-Javier Lopez; Maria Paula Magarinos; James Malone; Johanna McEntyre; Alfonso Munoz-Pomer Fuentes; Claire O'Donovan; Irene Papatheodorou; Helen Parkinson; Barbara Palka; Justin Paschall; Robert Petryszak; Naruemon Pratanwanich; Sirarat Sarntivijal; Gary Saunders; Konstantinos Sidiropoulos; Thomas Smith; Zbyslaw Sondka; Oliver Stegle; Y Amy Tang; Edward Turner; Brendan Vaughan; Olga Vrousgou; Xavier Watkins; Maria-Jesus Martin; Philippe Sanseau; Jessica Vamathevan; Ewan Birney; Jeffrey Barrett; Ian Dunham
Journal:  Nucleic Acids Res       Date:  2016-11-29       Impact factor: 16.971

5.  Prioritization of cancer therapeutic targets using CRISPR-Cas9 screens.

Authors:  Fiona M Behan; Francesco Iorio; Gabriele Picco; Kosuke Yusa; Mathew J Garnett; Emanuel Gonçalves; Charlotte M Beaver; Giorgia Migliardi; Rita Santos; Yanhua Rao; Francesco Sassi; Marika Pinnelli; Rizwan Ansari; Sarah Harper; David Adam Jackson; Rebecca McRae; Rachel Pooley; Piers Wilkinson; Dieudonne van der Meer; David Dow; Carolyn Buser-Doepner; Andrea Bertotti; Livio Trusolino; Euan A Stronach; Julio Saez-Rodriguez
Journal:  Nature       Date:  2019-04-10       Impact factor: 49.962

6.  MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens.

Authors:  Wei Li; Han Xu; Tengfei Xiao; Le Cong; Michael I Love; Feng Zhang; Rafael A Irizarry; Jun S Liu; Myles Brown; X Shirley Liu
Journal:  Genome Biol       Date:  2014       Impact factor: 13.583

7.  Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells.

Authors:  Wanjuan Yang; Jorge Soares; Patricia Greninger; Elena J Edelman; Howard Lightfoot; Simon Forbes; Nidhi Bindal; Dave Beare; James A Smith; I Richard Thompson; Sridhar Ramaswamy; P Andrew Futreal; Daniel A Haber; Michael R Stratton; Cyril Benes; Ultan McDermott; Mathew J Garnett
Journal:  Nucleic Acids Res       Date:  2012-11-23       Impact factor: 16.971

Review 8.  Targeted therapy for HER2 positive breast cancer.

Authors:  Jason A Incorvati; Shilpan Shah; Ying Mu; Janice Lu
Journal:  J Hematol Oncol       Date:  2013-06-03       Impact factor: 17.388

9.  Unsupervised correction of gene-independent cell responses to CRISPR-Cas9 targeting.

Authors:  Francesco Iorio; Fiona M Behan; Emanuel Gonçalves; Shriram G Bhosle; Elisabeth Chen; Rebecca Shepherd; Charlotte Beaver; Rizwan Ansari; Rachel Pooley; Piers Wilkinson; Sarah Harper; Adam P Butler; Euan A Stronach; Julio Saez-Rodriguez; Kosuke Yusa; Mathew J Garnett
Journal:  BMC Genomics       Date:  2018-08-13       Impact factor: 3.969

10.  Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval.

Authors:  Emily A King; J Wade Davis; Jacob F Degner
Journal:  PLoS Genet       Date:  2019-12-12       Impact factor: 5.917

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  14 in total

1.  The Cancer Surfaceome Atlas integrates genomic, functional and drug response data to identify actionable targets.

Authors:  Zhongyi Hu; Jiao Yuan; Meixiao Long; Junjie Jiang; Youyou Zhang; Tianli Zhang; Mu Xu; Yi Fan; Janos L Tanyi; Kathleen T Montone; Omid Tavana; Ho Man Chan; Xiaowen Hu; Robert H Vonderheide; Lin Zhang
Journal:  Nat Cancer       Date:  2021-12-13

Review 2.  Computational estimation of quality and clinical relevance of cancer cell lines.

Authors:  Lucia Trastulla; Javad Noorbakhsh; Francisca Vazquez; James McFarland; Francesco Iorio
Journal:  Mol Syst Biol       Date:  2022-07       Impact factor: 13.068

Review 3.  Synthetic Vulnerabilities in the KRAS Pathway.

Authors:  Marta Roman; Elizabeth Hwang; E Alejandro Sweet-Cordero
Journal:  Cancers (Basel)       Date:  2022-06-08       Impact factor: 6.575

4.  Unleashing Cell-Intrinsic Inflammation as a Strategy to Kill AML Blasts.

Authors:  Jana M Ellegast; Gabriela Alexe; Amanda Hamze; Shan Lin; Hannah J Uckelmann; Philipp J Rauch; Maxim Pimkin; Linda S Ross; Neekesh V Dharia; Amanda L Robichaud; Amy Saur Conway; Delan Khalid; Jennifer A Perry; Mark Wunderlich; Lina Benajiba; Yana Pikman; Behnam Nabet; Nathanael S Gray; Stuart H Orkin; Kimberly Stegmaier
Journal:  Cancer Discov       Date:  2022-07-06       Impact factor: 38.272

5.  The 2021 Nucleic Acids Research database issue and the online molecular biology database collection.

Authors:  Daniel J Rigden; Xosé M Fernández
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

6.  Systematic functional interrogation of human pseudogenes using CRISPRi.

Authors:  Ming Sun; Yunfei Wang; Caishang Zheng; Yanjun Wei; Jiakai Hou; Peng Zhang; Wei He; Xiangdong Lv; Yao Ding; Han Liang; Chung-Chau Hon; Xi Chen; Han Xu; Yiwen Chen
Journal:  Genome Biol       Date:  2021-08-23       Impact factor: 17.906

7.  ACE: a probabilistic model for characterizing gene-level essentiality in CRISPR screens.

Authors:  Elizabeth R Hutton; Christopher R Vakoc; Adam Siepel
Journal:  Genome Biol       Date:  2021-09-23       Impact factor: 13.583

8.  Screening and predicted value of potential biomarkers for breast cancer using bioinformatics analysis.

Authors:  Xiaoyu Zeng; Gaoli Shi; Qiankun He; Pingping Zhu
Journal:  Sci Rep       Date:  2021-10-21       Impact factor: 4.379

9.  Prognostic Significance of Dysregulated Epigenomic and Chromatin Modifiers in Cervical Cancer.

Authors:  Aswathy Mary Paul; Madhavan Radhakrishna Pillai; Rakesh Kumar
Journal:  Cells       Date:  2021-10-05       Impact factor: 6.600

Review 10.  CRISPR Screens in Synthetic Lethality and Combinatorial Therapies for Cancer.

Authors:  Laia Castells-Roca; Eudald Tejero; Benjamín Rodríguez-Santiago; Jordi Surrallés
Journal:  Cancers (Basel)       Date:  2021-03-30       Impact factor: 6.639

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