PlumX Metrics
Embed PlumX Metrics

Leveraging transcriptional dynamics to improve BRAF inhibitor responses in melanoma

EBioMedicine, ISSN: 2352-3964, Vol: 48, Page: 178-190
2019
  • 60
    Citations
  • 0
    Usage
  • 75
    Captures
  • 6
    Mentions
  • 16
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    60
  • Captures
    75
  • Mentions
    6
    • News Mentions
      6
      • News
        6
  • Social Media
    16
    • Shares, Likes & Comments
      16
      • Facebook
        16

Most Recent News

Single-Cell Level Variability May Help Predict Responses to BRAF Inhibitors in Melanoma

New targeted therapy options, such as BRAF and MEK inhibitors, offer advanced treatment for patients with melanoma; however, genetic variability often means that patients will

Article Description

Melanoma is a heterogeneous tumour, but the impact of this heterogeneity upon therapeutic response is not well understood. Single cell mRNA analysis was used to define the transcriptional heterogeneity of melanoma and its dynamic response to BRAF inhibitor therapy and treatment holidays. Discrete transcriptional states were defined in cell lines and melanoma patient specimens that predicted initial sensitivity to BRAF inhibition and the potential for effective re-challenge following resistance. A mathematical model was developed to maintain competition between the drug-sensitive and resistant states, which was validated in vivo. Our analyses showed melanoma cell lines and patient specimens to be composed of >3 transcriptionally distinct states. The cell state composition was dynamically regulated in response to BRAF inhibitor therapy and drug holidays. Transcriptional state composition predicted for therapy response. The differences in fitness between the different transcriptional states were leveraged to develop a mathematical model that optimized therapy schedules to retain the drug sensitive population. In vivo validation demonstrated that the personalized adaptive dosing schedules outperformed continuous or fixed intermittent BRAF inhibitor schedules. Our study provides the first evidence that transcriptional heterogeneity at the single cell level predicts for initial BRAF inhibitor sensitivity. We further demonstrate that manipulating transcriptional heterogeneity through personalized adaptive therapy schedules can delay the time to resistance. This work was funded by the National Institutes of Health. The funder played no role in assembly of the manuscript.

Bibliographic Details

http://www.sciencedirect.com/science/article/pii/S2352396419306279; http://dx.doi.org/10.1016/j.ebiom.2019.09.023; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85073010725&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/31594749; https://linkinghub.elsevier.com/retrieve/pii/S2352396419306279; https://dx.doi.org/10.1016/j.ebiom.2019.09.023; https://www.ebiomedicine.com/article/S2352-3964(19)30627-9/fulltext?utm_campaign=EBM%20-%20Editor%27s%20Choice%20-%20Social&utm_content=104562327&utm_medium=social&utm_source=twitter&hss_channel=tw-2550149892; http://www.thelancet.com/article/S2352396419306279/abstract; http://www.thelancet.com/article/S2352396419306279/fulltext; http://www.thelancet.com/article/S2352396419306279/pdf; https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(19)30627-9/abstract; https://www.ebiomedicine.com/article/S2352-3964(19)30627-9/fulltext?utm_campaign=EBM%20-%20Editor%27s%20Choice%20-%20Social&utm_content=104562329&utm_medium=social&utm_source=twitter&hss_channel=tw-2550149892; https://www.thelancet.com/journals/ebiom/article/PIIS2352-3964(19)30627-9/fulltext; https://www.ebiomedicine.com/article/S2352-3964(19)30627-9/fulltext?utm_campaign=EBM%20-%20Editor%27s%20Choice%20-%20Social&utm_content=104562326&utm_medium=social&utm_source=twitter&hss_channel=tw-2550149892; https://www.ebiomedicine.com/article/S2352-3964(19)30627-9/fulltext; https://www.ebiomedicine.com/article/S2352-3964(19)30627-9/abstract#.XZpZIcgn3sE.twitter; https://www.ebiomedicine.com/article/S2352-3964(19)30627-9/fulltext?utm_campaign=EBM%20-%20Editor%27s%20Choice%20-%20Social&utm_content=104562328&utm_medium=social&utm_source=twitter&hss_channel=tw-2550149892

Smalley, Inna; Kim, Eunjung; Li, Jiannong; Spence, Paige; Wyatt, Clayton J; Eroglu, Zeynep; Sondak, Vernon K; Messina, Jane L; Babacan, Nalan Akgul; Maria-Engler, Silvya Stuchi; De Armas, Lesley; Williams, Sion L; Gatenby, Robert A; Chen, Y Ann; Anderson, Alexander R A; Smalley, Keiran S M

Elsevier BV

Biochemistry, Genetics and Molecular Biology

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know