D3EGFR is a webserver for drug sensitivity retrieval and deep learning-guided drug sensitivity prediction of EGFR mutation-driven lung cancer.

D3EGFR是一个用于EGFR突变驱动的肺癌药物敏感性检索和基于深度学习的药物敏感性预测的网络应用平台。

Introduction

介绍

As the key oncogenic drivers in non-small cell lung cancer (NSCLC), various mutations of epidermal growth factor receptor (EGFR) with variable drug sensitivities have been the major obstacle for personalized medicine. A platform for drug sensitivity retrieval and reliable drug sensitivity prediction is desired for physician-scientists and clinicians. For the purpose, we built a database, namely D3EGFRdb, with the information of a total of 1,158 patients harboring EGFR mutations. Besides, we developed a deep learning model, namely D3EGFRAI, for drug sensitivity prediction for EGFR mutation-driven NSCLC. Accordingly, we constructed a web server, namely D3EGFR, to provide drug response retrieval through existing patient cases with specific clinical information and outcomes, and to predict drug response for patients harboring either common or rare or newly identified EGFR mutations.

作为非小细胞肺癌的关键致癌驱动因子，表皮生长因子受体（EGFR）的众多突变由于其多变的药物敏感性问题，一直是精准医疗的主要障碍。也正因如此，临床科学家和临床医生亟需可用于药物敏感性检索和可靠预测药物敏感性的平台。为此，我们建立了包含1158名EGFR突变患者信息的D3EGFRdb数据库，并开发了可预测EGFR突变驱动的非小细胞肺癌药物敏感性的D3EGFRAI模型。在此基础上，我们构建了本网站平台，以通过现有突变患者病例提供药物反应检索，并预测携带常见或罕见或新发现的EGFR突变类型的患者的药物反应。