An Integrated Genome-wide CRISPRa Approach to Functionalize lncRNAs in Drug Resistance

Assaf C. Bester, Jonathan D. Lee, Alejandro Chavez, Yu Ru Lee, Daphna Nachmani, Suhani Vora, Joshua Victor, Martin Sauvageau, Emanuele Monteleone, John L. Rinn, Paolo Provero, George M. Church, John G. Clohessy, Pier Paolo Pandolfi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

217 Scopus citations

Abstract

Resistance to chemotherapy plays a significant role in cancer mortality. To identify genetic units affecting sensitivity to cytarabine, the mainstay of treatment for acute myeloid leukemia (AML), we developed a comprehensive and integrated genome-wide platform based on a dual protein-coding and non-coding integrated CRISPRa screening (DICaS). Putative resistance genes were initially identified using pharmacogenetic data from 760 human pan-cancer cell lines. Subsequently, genome scale functional characterization of both coding and long non-coding RNA (lncRNA) genes by CRISPR activation was performed. For lncRNA functional assessment, we developed a CRISPR activation of lncRNA (CaLR) strategy, targeting 14,701 lncRNA genes. Computational and functional analysis identified novel cell-cycle, survival/apoptosis, and cancer signaling genes. Furthermore, transcriptional activation of the GAS6-AS2 lncRNA, identified in our analysis, leads to hyperactivation of the GAS6/TAM pathway, a resistance mechanism in multiple cancers including AML. Thus, DICaS represents a novel and powerful approach to identify integrated coding and non-coding pathways of therapeutic relevance. A CRISPR activation screen identifies both coding and noncoding pathways involved in resistance to chemotherapy.

Original languageAmerican English
Pages (from-to)649-664.e20
JournalCell
Volume173
Issue number3
DOIs
StatePublished - 19 Apr 2018
Externally publishedYes

Bibliographical note

Funding Information:
The authors would like to thank Rory Kirchner of the Harvard Chan Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA for assistance with computational analysis. The authors would like to thank Davide Corà and Claudio Isella of the Department of Oncology, and GenoBiToUS, Genomics and Bioinformatics Service, University of Turin, Italy for assistance with computational analysis. We thank the P.P.P. laboratory members for critical discussions. This work was supported by EMBO Long-Term Fellowship ( ALTF 318-2013 ) and Fulbright awards to A.C.B. A.C. was funded by NCI ( 5T32CA009216-34 ) and a Burroughs Wellcome Fund Career Award for Medical Scientists. G.M.C was supported by NIH ( RM1 HG008525 and P50 HG005550 ). P.P.P. is supported by an NIH NCI R35 grant ( CA197529 ) and through support from the Ludwig Center at Harvard . The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the NIH. The data used for the analyses described in this manuscript were obtained from the GTEx Portal. The results published here are fully or partially based on data generated by the Cancer Target Discovery and Development (CTD 2 ) Network established by the NCI Office of Cancer Genomics.

Funding Information:
The authors would like to thank Rory Kirchner of the Harvard Chan Bioinformatics Core, Harvard T.H. Chan School of Public Health, Boston, MA for assistance with computational analysis. The authors would like to thank Davide Corà and Claudio Isella of the Department of Oncology, and GenoBiToUS, Genomics and Bioinformatics Service, University of Turin, Italy for assistance with computational analysis. We thank the P.P.P. laboratory members for critical discussions. This work was supported by EMBO Long-Term Fellowship (ALTF 318-2013) and Fulbright awards to A.C.B. A.C. was funded by NCI (5T32CA009216-34) and a Burroughs Wellcome Fund Career Award for Medical Scientists. G.M.C was supported by NIH (RM1 HG008525 and P50 HG005550). P.P.P. is supported by an NIH NCI R35 grant (CA197529) and through support from the Ludwig Center at Harvard. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the NIH. The data used for the analyses described in this manuscript were obtained from the GTEx Portal. The results published here are fully or partially based on data generated by the Cancer Target Discovery and Development (CTD2) Network established by the NCI Office of Cancer Genomics.

Publisher Copyright:
© 2018 Elsevier Inc.

Keywords

  • AML
  • AXL/GAS6
  • CRISPR
  • CRISPRa
  • TEM
  • cancer
  • cytarabine
  • drug-resistance
  • leukemia
  • lncRNA

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