The Pathway-Informed Deep Learning Models in Cancer Research: A Survey

Biological pathways play an important role in complex disease research, drug development, and precision medicine. Recently, tens of pathway-informed deep learning models in cancer research have been proposed due to their interpretability and high performance. However, there is still a lack of reviews that have a specific focus on the application strategy of pathway information in the pathway-informed deep learning models. Hence, we surveyed the pathway-informed deep learning models in cancer research. In this survey, the pathway information used in pathway-informed models was summarized into four categories; pathway-informed deep learning models were divided into three major categories and seven subcategories based on the pathway information utilized and the strategies employed for its application. For each subcategory, the application strategy of pathway information is illustrated, and the advantages and disadvantages of the pathway-informed models are summarized. Besides, the commonly used interpretability methods and pathway databases are provided to assist in the design of more effective models. Finally, the challenges faced in developing better pathway-informed deep learning models are presented.