Metastatic State of Colorectal Cancer can be Accurately Predicted with Methylome

被引:6
|
作者
Albaradei, Somayah [1 ,2 ]
Thafar, Maha [1 ,3 ]
Van Neste, Christophe [1 ,4 ]
Essack, Magbubah [1 ]
Bajic, Vladimir B. [1 ]
机构
[1] King Abdullah Univ Sci & Technol, Computat Biosci Res Ctr CBRC, Comp Elect & Math Sci & Engn CEMSE Div, Thuwal 239556900, Saudi Arabia
[2] King Abdulaziz Univ, Fac Comp & Informat Syst, Jeddah, Saudi Arabia
[3] Taif Univ, Fac Comp & Informat Technol, At Taif, Saudi Arabia
[4] Univ Ghent, Ctr Med Genet Ghent CMGG, Ghent, Belgium
关键词
Computational biology; Bioinformatics; Metastasis; Colorectal cancer; DNA methylation; Deep learning; Convolutional neural networks;
D O I
10.1145/3383783.3383792
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Colorectal cancer (CRC) appears to be the third most common cancer as well as the fourth most common cause of cancer deaths in the world. Its most lethal states are when it becomes metastatic. It is of interest to find tests that can quickly and accurately determine if the patient has already developed metastasis. Changes in methylation profiles have been found to be characteristic of cancers at different stages and can therefore be used to develop diagnostic panels. We developed a deep learning (DL) model (Deep2Met) using methylation profiles of patients with CRC to predict if the cancer is in its metastatic state. Results suggest that our method achieves an AUPR and an average F-score of 96.99% and 94.71%, respectively, making Deep2Met potentially useful for diagnostic purposes. The DL model Deep2Met we developed, shows promise in the diagnosis of CRC based on methylation profiles of individual patients.
引用
收藏
页码:125 / 130
页数:6
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