Liu Dingxie, Liu Xuan, Xing Mingzhao
Laboratory for Cellular and Molecular Thyroid Research; Division of Endocrinology and Metabolism; Johns Hopkins University School of Medicine; Baltimore, MD USA.
Department of Electrical and Computer Engineering; Johns Hopkins University; Baltimore, MD USA.
Cell Cycle. 2014;13(2):208-19. doi: 10.4161/cc.26971. Epub 2013 Oct 29.
Drug resistance is a major obstacle in the targeted therapy of melanoma using BRAF/MEK inhibitors. This study was to identify BRAF V600E-associated oncogenic pathways that predict resistance of BRAF-mutated melanoma to BRAF/MEK inhibitors. We took in silico approaches to analyze the activities of 24 cancer-related pathways in melanoma cells and identify those whose activation was associated with BRAF V600E and used the support vector machine (SVM) algorithm to predict the resistance of BRAF-mutated melanoma cells to BRAF/MEK inhibitors. We then experimentally confirmed the in silico findings. In a microarray gene expression dataset of 63 melanoma cell lines, we found that activation of multiple oncogenic pathways preferentially occurred in BRAF-mutated melanoma cells. This finding was reproduced in 5 additional independent melanoma datasets. Further analysis of 46 melanoma cell lines that harbored BRAF mutation showed that 7 pathways, including TNFα, EGFR, IFNα, hypoxia, IFNγ, STAT3, and MYC, were significantly differently expressed in AZD6244-resistant compared with responsive melanoma cells. A SVM classifier built on this 7-pathway activation pattern correctly predicted the response of 10 BRAF-mutated melanoma cell lines to the MEK inhibitor AZD6244 in our experiments. We experimentally showed that TNFα, EGFR, IFNα, and IFNγ pathway activities were also upregulated in melanoma cell A375 compared with its sub-line DRO, while DRO was much more sensitive to AZD6244 than A375. In conclusion, we have identified specific oncogenic pathways preferentially activated in BRAF-mutated melanoma cells and a pathway pattern that predicts resistance of BRAF-mutated melanoma to BRAF/MEK inhibitors, providing novel clinical implications for melanoma therapy.
耐药性是使用BRAF/MEK抑制剂对黑色素瘤进行靶向治疗的主要障碍。本研究旨在确定与BRAF V600E相关的致癌途径，这些途径可预测BRAF突变型黑色素瘤对BRAF/MEK抑制剂的耐药性。我们采用计算机方法分析黑色素瘤细胞中24条与癌症相关途径的活性，并确定那些激活与BRAF V600E相关的途径，然后使用支持向量机（SVM）算法预测BRAF突变型黑色素瘤细胞对BRAF/MEK抑制剂的耐药性。随后，我们通过实验证实了计算机分析的结果。在一个包含63个黑色素瘤细胞系的微阵列基因表达数据集中，我们发现多种致癌途径的激活优先发生在BRAF突变型黑色素瘤细胞中。这一发现在另外5个独立的黑色素瘤数据集中得到了重现。对46个携带BRAF突变的黑色素瘤细胞系的进一步分析表明，与敏感的黑色素瘤细胞相比，包括TNFα、EGFR、IFNα、缺氧、IFNγ、STAT3和MYC在内的7条途径在对AZD6244耐药的黑色素瘤细胞中表达存在显著差异。基于这7条途径激活模式构建的SVM分类器在我们的实验中正确预测了10个BRAF突变型黑色素瘤细胞系对MEK抑制剂AZD6244的反应。我们通过实验表明，与黑色素瘤细胞A375的亚系DRO相比，A375中TNFα、EGFR、IFNα和IFNγ途径的活性也上调，而DRO对AZD6244的敏感性远高于A375。总之，我们已经确定了在BRAF突变型黑色素瘤细胞中优先激活的特定致癌途径以及一种可预测BRAF突变型黑色素瘤对BRAF/MEK抑制剂耐药性的途径模式，为黑色素瘤治疗提供了新的临床启示。
