Inam Haider, Sokirniy Ivan, Rao Yiyun, Shah Anushka, Naeemikia Farnaz, O'Brien Edward, Dong Cheng, McCandlish David M, Pritchard Justin R
Department of Biomedical Engineering, 211 Wartik Lab, The Pennsylvania State University, University Park, PA 16802, USA.
The Huck Institute for the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA.
iScience. 2021 Oct 26;24(11):103343. doi: 10.1016/j.isci.2021.103343. eCollection 2021 Nov 19.
Genomic data can facilitate personalized treatment decisions by enabling therapeutic hypotheses in individual patients. Mutual exclusivity has been an empirically useful signal for identifying activating mutations that respond to single agent targeted therapies. However, a low mutation frequency can underpower this signal for rare variants. We develop a resampling based method for the direct pairwise comparison of conditional selection between sets of gene pairs. We apply this method to a transcript variant of anaplastic lymphoma kinase (ALK) in melanoma, termed ALK that was suggested to predict sensitivity to ALK inhibitors and we find that it is not mutually exclusive with key melanoma oncogenes. Furthermore, we find that ALK is not likely to be sufficient for cellular transformation or growth, and it does not predict single agent therapeutic dependency. Our work strongly disfavors the role of ALK as a targetable oncogenic driver that might be sensitive to single agent ALK treatment.
基因组数据能够通过为个体患者提出治疗假设来促进个性化治疗决策。互斥性一直是识别对单药靶向治疗有反应的激活突变的一个经验上有用的信号。然而,低突变频率会使这个信号对于罕见变异的效力不足。我们开发了一种基于重采样的方法,用于直接成对比较基因对集合之间的条件选择。我们将此方法应用于黑色素瘤中一种间变性淋巴瘤激酶(ALK)的转录变体,即ALK,该变体被认为可预测对ALK抑制剂的敏感性,我们发现它与关键的黑色素瘤致癌基因并非互斥。此外,我们发现ALK不太可能足以促成细胞转化或生长,并且它不能预测单药治疗依赖性。我们的工作强烈不支持ALK作为可能对单药ALK治疗敏感的可靶向致癌驱动因子的作用。