Development of metastatic brain disease involves progression through lung metastases in EGFR mutated non-small cell lung cancer.

G. In, J. Mason, Sonia Lin, P. Newton, P. Kuhn, J. Nieva
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引用次数: 5

Abstract

Lung cancer is often classified by the presence of oncogenic drivers, such as epidermal growth factor receptor (EGFR), rather than patterns of anatomical distribution. While metastatic spread may seem a random and unpredictable process, we explored the possibility of using its quantifiable nature as a measure of describing and comparing different subsets of disease. We constructed a database of 664 non-small cell lung cancer (NSCLC) patients treated at the University of Southern California Norris Comprehensive Cancer Center and the Los Angeles County Medical Center. Markov mathematical modeling was employed to assess metastatic sites in a spatiotemporal manner through every time point in progression of disease. Our findings identified a preferential pattern of primary lung disease progressing through lung metastases to the brain amongst EGFR mutated (EGFR m) NSCLC patients, with exon 19 deletions or exon 21 L858R mutations, as compared to EGFR wild type (EGFR wt). The brain was classified as an anatomic "sponge", with a higher ratio of incoming to outgoing spread, for EGFR m NSCLC. Bone metastases were more commonly identified in EGFR wt patients. Our study supports a link between the anatomical and molecular characterization of lung metastatic cancer. Improved understanding of the differential biology that drives discordant patterns of anatomic spread, based on genotype specific profiling, has the potential to improve personalized oncologic care.
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在EGFR突变的非小细胞肺癌中,转移性脑疾病的发展涉及通过肺转移的进展。
肺癌通常根据致癌驱动因素的存在进行分类,如表皮生长因子受体(EGFR),而不是解剖分布模式。虽然转移性扩散似乎是一个随机和不可预测的过程,但我们探索了使用其可量化性质作为描述和比较不同亚群疾病的衡量标准的可能性。我们建立了一个664名在南加州大学诺里斯综合癌症中心和洛杉矶县医疗中心接受治疗的非小细胞肺癌(NSCLC)患者的数据库。采用马尔可夫数学模型通过疾病进展的每个时间点以时空方式评估转移部位。我们的研究发现,与EGFR野生型(EGFR wt)相比,EGFR突变(EGFR m)非小细胞肺癌患者中,具有外显子19缺失或外显子21 L858R突变的原发性肺部疾病通过肺转移到脑的优先模式。对于非小细胞肺癌的EGFR,大脑被归类为解剖学上的“海绵”,具有较高的传入和传出扩散比例。骨转移更常见于EGFR wt患者。我们的研究支持肺转移癌的解剖和分子特征之间的联系。基于基因型特异性分析,提高对驱动不一致解剖扩散模式的差异生物学的理解,具有改善个性化肿瘤护理的潜力。
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