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Review
. 2020 Sep 29;12(10):2801.
doi: 10.3390/cancers12102801.

Mechanisms of Acquired BRAF Inhibitor Resistance in Melanoma: A Systematic Review

Affiliations
Review

Mechanisms of Acquired BRAF Inhibitor Resistance in Melanoma: A Systematic Review

Ilaria Proietti et al. Cancers (Basel). .

Abstract

This systematic review investigated the literature on acquired v-raf murine sarcoma viral oncogene homolog B1 (BRAF) inhibitor resistance in patients with melanoma. We searched MEDLINE for articles on BRAF inhibitor resistance in patients with melanoma published since January 2010 in the following areas: (1) genetic basis of resistance; (2) epigenetic and transcriptomic mechanisms; (3) influence of the immune system on resistance development; and (4) combination therapy to overcome resistance. Common resistance mutations in melanoma are BRAF splice variants, BRAF amplification, neuroblastoma RAS viral oncogene homolog (NRAS) mutations and mitogen-activated protein kinase kinase 1/2 (MEK1/2) mutations. Genetic and epigenetic changes reactivate previously blocked mitogen-activated protein kinase (MAPK) pathways, activate alternative signaling pathways, and cause epithelial-to-mesenchymal transition. Once BRAF inhibitor resistance develops, the tumor microenvironment reverts to a low immunogenic state secondary to the induction of programmed cell death ligand-1. Combining a BRAF inhibitor with a MEK inhibitor delays resistance development and increases duration of response. Multiple other combinations based on known mechanisms of resistance are being investigated. BRAF inhibitor-resistant cells develop a range of 'escape routes', so multiple different treatment targets will probably be required to overcome resistance. In the future, it may be possible to personalize combination therapy towards the specific resistance pathway in individual patients.

Keywords: BRAF inhibitors; melanoma; metastasis; microenvironment; resistance; therapy.

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Conflict of interest statement

The authors declare no conflict of interest. Catherine Rees is a professional medical writer employed by Springer Healthcare Communications. Her medical writing services were funded by Pierre Fabre. The funder had no role in the design of the review; in the collection, analyses, or interpretation of data; or in the decision to publish the results.

Figures

Figure 1
Figure 1
The MAPK signaling pathway (A) in a BRAF inhibitor-sensitive cell showing sites of action of BRAF inhibitors and MEK inhibitors, and (B) after BRAF inhibitor resistance development [78]. Mechanisms of resistance are numbered: (1) upregulation of RTK; (2) BRAF amplification; (3) BRAF alternative splicing; (4) loss of NF1; (6) ERK activation; (7) loss of PTEN; and (8) activation of alternative signaling pathways. BRAF, v-Raf murine sarcoma viral oncogene homolog B; ERK, extracellular signal-regulated kinase; GFR, growth factor receptor; mTOR, mammalian target of rapamycin; NF1, neurofibromin 1; PTEN, phosphatase and tensin homolog; RTK, receptor tyrosine kinase. From Tanda et al. Frontiers in Molecular Biosciences 2020, 7, 154 [78]. © 2020 Tanda, Vanni, Boutros, Andreotti, Bruno, Ghiorzo and Spagnolo.
Figure 2
Figure 2
Heat map analysis of genes differentially expressed in cells with BRAF inhibitor sensitivity (A375P), acquired BRAF inhibitor resistance (A375P/Mdr) and innate BRAF inhibitor resistance (SK-MEL-2) [88]. SK-MEL-2 cells have wild-type BRAF and are resistant to BRAF inhibitors because these agents lack activity against wild-type BRAF. From Ahn et al. Biomol 2019, 27, 302–310 [88]. Copyright ©2019, The Korean Society of Applied Pharmacology.
Figure 3
Figure 3
Transcription factor motif analysis of BRAF inhibitor resistance in cellular models of malignant melanoma [141]. Red indicates transcription factors relevant to upregulated genes and blue indicates transcription factors relevant to downregulated genes. (a) Schematic representation of differentially expressed genes in a drug resistance model and transcription factor motifs associated with regulated target genes. Upregulated factors are depicted in red and downregulated factors in blue. (b) Hierarchical transcription factor network with master regulators on top and downstream targets at bottom. Sets of transcription factor target genes are identified in enrichment analysis based on sequence motifs. (c) Hierarchical network model illustrates how therapy resistance in cancer selects for specific transcriptional master regulators to rewire target genes in effector pathways in a concerted fashion. From Zecena et al. BMC Syst Biol 2018, 12, 33 [141]. Copyright © 2018, Zecena, Tveit, Wang, Farhat, Panchal, Liu, Singh, Sanghera, Bainiwal, Teo, Meyskens, Liu-Smith, and Filipp.

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