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通过局部表面几何特性解码肺癌治疗中表皮生长因子受体(EGFR)突变诱导的耐药性

Decoding the EGFR mutation-induced drug resistance in lung cancer treatment by local surface geometric properties.

作者信息

Ma Lichun, Wang Debby D, Huang Yiqing, Wong Maria P, Lee Victor H F, Yan Hong

机构信息

Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.

Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.

出版信息

Comput Biol Med. 2015 Aug;63:293-300. doi: 10.1016/j.compbiomed.2014.06.016. Epub 2014 Jun 28.

DOI:10.1016/j.compbiomed.2014.06.016
PMID:25035232
Abstract

Epidermal growth factor receptor (EGFR) mutation-induced drug resistance leads to a limited efficacy of tyrosine kinase inhibitors during lung cancer treatments. In this study, we explore the correlations between the local surface geometric properties of EGFR mutants and the progression-free survival (PFS). The geometric properties include local surface changes (four types) of the EGFR mutants compared with the wild-type EGFR, and the convex degrees of these local surfaces. Our analysis results show that the Spearman׳s rank correlation coefficients between the PFS and three types of local surface properties are all greater than 0.6 with small P-values, implying a high significance. Moreover, the number of atoms with solid angles in the ranges of [0.71, 1], [0.61, 1] or [0.5, 1], indicating the convex degree of a local EGFR surface, also shows a strong correlation with the PFS. Overall, these characteristics can be efficiently applied to the prediction of drug resistance in lung cancer treatments, and easily extended to other cancer treatments.

摘要

表皮生长因子受体(EGFR)突变诱导的耐药性导致肺癌治疗期间酪氨酸激酶抑制剂的疗效有限。在本研究中,我们探讨了EGFR突变体的局部表面几何特性与无进展生存期(PFS)之间的相关性。几何特性包括与野生型EGFR相比EGFR突变体的局部表面变化(四种类型)以及这些局部表面的凸度。我们的分析结果表明,PFS与三种局部表面特性之间的斯皮尔曼等级相关系数均大于0.6且P值较小,这意味着具有高度显著性。此外,局部EGFR表面凸度的指示值,即在[0.71, 1]、[0.61, 1]或[0.5, 1]范围内立体角的原子数,也与PFS显示出强相关性。总体而言,这些特征可有效地应用于肺癌治疗中耐药性的预测,并易于扩展到其他癌症治疗。

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Decoding the EGFR mutation-induced drug resistance in lung cancer treatment by local surface geometric properties.通过局部表面几何特性解码肺癌治疗中表皮生长因子受体(EGFR)突变诱导的耐药性
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Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis.基于结构相互作用指纹和多线性主成分分析预测 NSCLC 中 EGFR 突变对吉非替尼/厄洛替尼的敏感性。
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Identifying EGFR mutation-induced drug resistance based on alpha shape model analysis of the dynamics.
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EGFR Mutant Structural Database: computationally predicted 3D structures and the corresponding binding free energies with gefitinib and erlotinib.表皮生长因子受体(EGFR)突变结构数据库:通过计算预测的三维结构以及与吉非替尼和厄洛替尼相应的结合自由能。
BMC Bioinformatics. 2015 Mar 14;16:85. doi: 10.1186/s12859-015-0522-3.