التفاصيل البيبلوغرافية
| العنوان: |
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer. |
| المؤلفون: |
Shi, Yulong1,2 (AUTHOR), Li, Chongwu3 (AUTHOR), Zhang, Xinben1 (AUTHOR), Peng, Cheng1,2 (AUTHOR), Sun, Peng4 (AUTHOR), Zhang, Qian5 (AUTHOR), Wu, Leilei3 (AUTHOR), Ding, Ying6 (AUTHOR) dingying@njmu.edu.cn, Xie, Dong3 (AUTHOR) dingying@njmu.edu.cn, Xu, Zhijian1,2 (AUTHOR) dingying@njmu.edu.cn, Zhu, Weiliang1,2 (AUTHOR) dingying@njmu.edu.cn |
| المصدر: |
Briefings in Bioinformatics. May2024, Vol. 25 Issue 3, p1-10. 10p. |
| مصطلحات موضوعية: |
*INFORMATION retrieval, DEEP learning, EPIDERMAL growth factor receptors, LUNG cancer, NON-small-cell lung carcinoma |
| مستخلص: |
As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recommendations, a platform for clinical patient case retrieval and reliable drug sensitivity prediction is highly expected. Therefore, we built a database, D3EGFRdb, with the clinicopathologic characteristics and drug responses of 1339 patients with EGFR mutations via literature mining. On the basis of D3EGFRdb, we developed a deep learning-based prediction model, D3EGFRAI, for drug sensitivity prediction of new EGFR mutation-driven NSCLC. Model validations of D3EGFRAI showed a prediction accuracy of 0.81 and 0.85 for patients from D3EGFRdb and our hospitals, respectively. Furthermore, mutation scanning of the crucial residues inside drug-binding pockets, which may occur in the future, was performed to explore their drug sensitivity changes. D3EGFR is the first platform to achieve clinical-level drug response prediction of all approved small molecule drugs for EGFR mutation-driven lung cancer and is freely accessible at https://www.d3pharma.com/D3EGFR/index.phpTest. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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