dc.contributor.author | Vyse, S | |
dc.contributor.author | Howitt, A | |
dc.contributor.author | Huang, PH | |
dc.date.accessioned | 2017-05-23T16:29:14Z | |
dc.date.issued | 2017-06-16 | |
dc.identifier.citation | Journal of molecular biology, 2017, 429 (12), pp. 1767 - 1786 | |
dc.identifier.issn | 0022-2836 | |
dc.identifier.uri | https://repository.icr.ac.uk/handle/internal/657 | |
dc.identifier.eissn | 1089-8638 | |
dc.identifier.doi | 10.1016/j.jmb.2017.04.018 | |
dc.description.abstract | Despite the recent approval of third-generation therapies, overcoming resistance to epidermal growth factor receptor (EGFR) inhibitors remains a major challenge in non-small cell lung cancer. Conceptually, synthetic lethality holds the promise of identifying non-intuitive targets for tackling both acquired and intrinsic resistance in this setting. However, translating these laboratory findings into effective clinical strategies continues to be elusive. Here, we provide an overview of the synthetic lethal approaches that have been employed to study EGFR inhibitor resistance and review the oncogene and non-oncogene signalling mechanisms that have thus far been unveiled by synthetic lethality screens. We highlight the potential challenges associated with progressing these discoveries into the clinic including context dependency, signalling plasticity, and tumour heterogeneity, and we offer a perspective on emerging network biology and computational solutions to exploit these phenomena for cancer therapy and biomarker discovery. We conclude by presenting a number of tangible steps to bolster our understanding of fundamental synthetic lethality mechanisms and advance these findings beyond the confines of the laboratory. | |
dc.format | Print-Electronic | |
dc.format.extent | 1767 - 1786 | |
dc.language | eng | |
dc.language.iso | eng | |
dc.publisher | ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | |
dc.subject | Humans | |
dc.subject | Carcinoma, Non-Small-Cell Lung | |
dc.subject | Epidermal Growth Factor | |
dc.subject | Antineoplastic Agents | |
dc.subject | Drug Resistance | |
dc.subject | Gene Regulatory Networks | |
dc.subject | Drug Discovery | |
dc.subject | ErbB Receptors | |
dc.subject | Biomarkers, Tumor | |
dc.subject | Synthetic Lethal Mutations | |
dc.title | Exploiting Synthetic Lethality and Network Biology to Overcome EGFR Inhibitor Resistance in Lung Cancer. | |
dc.type | Journal Article | |
dcterms.dateAccepted | 2017-04-27 | |
rioxxterms.versionofrecord | 10.1016/j.jmb.2017.04.018 | |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0 | |
rioxxterms.licenseref.startdate | 2017-06 | |
rioxxterms.type | Journal Article/Review | |
dc.relation.isPartOf | Journal of molecular biology | |
pubs.issue | 12 | |
pubs.notes | No embargo | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology/Protein Networks | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular and Systems Oncology | |
pubs.organisational-group | /ICR | |
pubs.organisational-group | /ICR/Primary Group | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Cancer Biology/Protein Networks | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology | |
pubs.organisational-group | /ICR/Primary Group/ICR Divisions/Molecular Pathology/Molecular and Systems Oncology | |
pubs.publication-status | Published | |
pubs.volume | 429 | |
pubs.embargo.terms | No embargo | |
icr.researchteam | Protein Networks | |
icr.researchteam | Molecular and Systems Oncology | |
dc.contributor.icrauthor | Huang, Paul | |