The Genetic Landscape of Clinical Resistance to RAF Inhibition in Metastatic Melanoma

Allen, Eliezer M. Van; Wagle, Nikhil; Sucker, Antje; Treacy, Daniel J.; Johannessen, Cory M.; Goetz, Eva M.; Place, Chelsea S.; Taylor-Weiner, Amaro; Whittaker, Steven R.; Kryukov, Gregory V.; Hodis, Eran; Rosenberg, Mara; McKenna, Aaron; Cibulskis, Kristian; Farlow, Deborah N.; Zimmer, Lisa; Hillen, Uwe; Gutzmer, Ralf; Goldinger, Simone M.; Ugurel, Selma; Gogas, Helen; Egberts, Friederike; Berking, Carola; Trefzer, Uwe; Loquai, Carmen; Weide, Benjamin; Hassel, Jessica C.; Gabriel, Stacey; Carter, Scott L.; Getz, Gad; Garraway, Levi A.; Schadendorf, Dirk

doi:10.1158/2159-8290.cd-13-0617

Cited by 820 publications

(762 citation statements)

References 53 publications

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“…The elucidation of secondary mechanisms of resistance to BRAF-directed therapies has generated a substantial literature 115 , although larger datasets and meta-analyses have revealed that only a handful of changes underlie the preponderance of genomic resistance mechanisms. In the largest studies to date 20,[116][117][118] , involving 132 samples obtained at the time of clinical resistance, one or more genomic causes of resistance were identified in 58% of patients: NRAS/KRAS mutation in 20%, BRAF splice vari ants in 16%, BRAF amplification in 13%, MEK1/2 mutation in 7%, and non-MAPK-pathway alterations in 11%. Similar resistance mechanisms have been described with combined BRAF-MEK inhibition 119,120 .…”

Section: Braf-mek-inhibitor Resistance and Biomarkersmentioning

confidence: 99%

Targeted agents and immunotherapies: optimizing outcomes in melanoma

et al. 2017

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Section: Braf-mek-inhibitor Resistance and Biomarkersmentioning

confidence: 99%

Targeted agents and immunotherapies: optimizing outcomes in melanoma

et al. 2017

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“…We sequenced 80 patient tumors by WES or by targeted sequencing with a panel of 40 melanoma driver genes and genes known to be drivers of resistance to targeted therapy (Supplementary Table S4; refs. [30][31][32]. Forty-eight tumors carried V600 BRAF mutations and one a K601 mutation ( Fig.…”

Section: Identifi Cation and Validation Of Treatments For Non-v600 Mumentioning

confidence: 99%

“…We advocate that BRAF and NRAS ctDNA are monitored and further validated in prospective clinical trials and they now have a part in routine clinical practice. With targeted therapies, an increase in BRAF -mutant VAF will provide an early warning of progression, and the NRAS analysis will reveal mechanisms of resistance in approximately 30% of patients ( 32 ). In particular, on May 10, 2018.…”

Section: I I I I I I I I I I I I I I I I I I I I I I I I I Imentioning

confidence: 99%

Application of Sequencing, Liquid Biopsies, and Patient-Derived Xenografts for Personalized Medicine in Melanoma

et al. 2016

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Targeted therapies and immunotherapies have transformed melanoma care, extending median survival from ∼9 to over 25 months, but nevertheless most patients still die of their disease. The aim of precision medicine is to tailor care for individual patients and improve outcomes. To this end, we developed protocols to facilitate individualized treatment decisions for patients with advanced melanoma, analyzing 364 samples from 214 patients. Whole exome sequencing (WES) and targeted sequencing of circulating tumor DNA (ctDNA) allowed us to monitor responses to therapy and to identify and then follow mechanisms of resistance. WES of tumors revealed potential hypothesis-driven therapeutic strategies for BRAF wild-type and inhibitor-resistant BRAF-mutant tumors, which were then validated in patient-derived xenografts (PDX). We also developed circulating tumor cell–derived xenografts (CDX) as an alternative to PDXs when tumors were inaccessible or difficult to biopsy. Thus, we describe a powerful technology platform for precision medicine in patients with melanoma. Significance: Although recent developments have revolutionized melanoma care, most patients still die of their disease. To improve melanoma outcomes further, we developed a powerful precision medicine platform to monitor patient responses and to identify and validate hypothesis-driven therapies for patients who do not respond, or who develop resistance to current treatments. Cancer Discov; 6(3); 286–99. ©2015 AACR. This article is highlighted in the In This Issue feature, p. 217

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“…However, there is significant variability in the magnitude of the initial response (37,38), and most of the cases develop robust drug resistance after six months of treatment (39), despite the fact that no genetically resistant subclones have been detected before treatment, even in tumors that show modest responses. Further, different genetic resistance mechanisms can develop in the same patient (40), often at multiple metastatic sites (41). It is therefore suspected that certain extrinsic mechanisms underlie and determine the initial response, following the adaptation and acquisition of genetically robust drug resistance.…”

Section: Application To Intravital Imagingmentioning

confidence: 99%

Future Perspective of Single-Molecule FRET Biosensors and Intravital FRET Microscopy

Hirata

Kiyokawa

2016

Biophysical Journal

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Fö rster (or fluorescence) resonance energy transfer (FRET) is a nonradiative energy transfer process between two fluorophores located in close proximity to each other. To date, a variety of biosensors based on the principle of FRET have been developed to monitor the activity of kinases, proteases, GTPases or lipid concentration in living cells. In addition, generation of biosensors that can monitor physical stresses such as mechanical power, heat, or electric/magnetic fields is also expected based on recent discoveries on the effects of these stressors on cell behavior. These biosensors can now be stably expressed in cells and mice by transposon technologies. In addition, two-photon excitation microscopy can be used to detect the activities or concentrations of bioactive molecules in vivo. In the future, more sophisticated techniques for image acquisition and quantitative analysis will be needed to obtain more precise FRET signals in spatiotemporal dimensions. Improvement of tissue/organ position fixation methods for mouse imaging is the first step toward effective image acquisition. Progress in the development of fluorescent proteins that can be excited with longer wavelength should be applied to FRET biosensors to obtain deeper structures. The development of computational programs that can separately quantify signals from single cells embedded in complicated three-dimensional environments is also expected. Along with the progress in these methodologies, two-photon excitation intravital FRET microscopy will be a powerful and valuable tool for the comprehensive understanding of biomedical phenomena.Since the discovery of green fluorescent protein (GFP) (1), scientists have been widely employing this gene-encoded fluorescent protein (FP) to investigate the spatiotemporal dynamics of molecules with subcellular resolution. One of the applications of FP engineering is the development of biosensors based on the principle of Förster (or fluorescence) resonance energy transfer (FRET) (2). FRET is a nonradiative energy transfer process between two fluorophores located in close proximity to each other, and its efficiency is strongly dependent on the distance between the fluorophores. More precisely, the energy transfer rate (k t ) from a donor to an acceptor fluorophore is calculated in the following Förster's equation;where J is the overlap of donor emission and acceptor excitation spectra, k 2 is an orientation factor of transition moment (a factor determined by the relative orientation of the two fluorophores), n is a refractive index, R is the distance between the donor and acceptor fluorophores, and k f is the donor fluorescence emission speed. Therefore, FRET efficiency is determined by the distance and orientation of the two fluorophores. To measure FRET efficiency, there are roughly two methods; ratiometric analysis and lifetime analysis. Ratiometric analysis utilizes fluorescence intensity of an acceptor (e.g., yellow FP (YFP)) and a donor (e.g., cyan FP (CFP)) upon the donor excitation. Because accept...

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The Genetic Landscape of Clinical Resistance to RAF Inhibition in Metastatic Melanoma

Cited by 820 publications

References 53 publications

Targeted agents and immunotherapies: optimizing outcomes in melanoma

Targeted agents and immunotherapies: optimizing outcomes in melanoma

Application of Sequencing, Liquid Biopsies, and Patient-Derived Xenografts for Personalized Medicine in Melanoma

Future Perspective of Single-Molecule FRET Biosensors and Intravital FRET Microscopy

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