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Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine

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Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine biomolecules Review Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine Ryuji Hamamoto 1,2,*, Masaaki Komatsu 1,2, Ken Takasawa 1,2 , Ken Asada 1,2 and Syuzo Kaneko 1 1 Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; [email protected] (M.K.); [email protected] (K.T.); [email protected] (K.A.); [email protected] (S.K.) 2 Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan * Correspondence: [email protected]; Tel.: +81-3-3547-5271 Received: 1 December 2019; Accepted: 27 December 2019; Published: 30 December 2019 Abstract: To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. So far, given that genetic and epigenetic studies tend to be accomplished independently, physiological relationships between genetics and epigenetics in diseases remain almost unknown. Since this situation may be a disadvantage to developing precision medicine, the integrated understanding of genetic variation and epigenetic deregulation appears to be now critical. Importantly, the current progress of artificial intelligence (AI) technologies, such as machine learning and deep learning, is remarkable and enables multimodal analyses of big omics data. In this regard, it is important to develop a platform that can conduct multimodal analysis of medical big data using AI as this may accelerate the realization of precision medicine. In this review, we discuss the importance of genome-wide epigenetic and multiomics analyses using AI in the era of precision medicine. Keywords: epigenetics; precision medicine; DNA methylation; histone modifications; machine learning; deep learning 1. Introduction Barack Obama, the 44th president of the United States, stated his intention to fund an amount of $215 million to the “Precision Medicine Initiative” in his 2015 State of the Union Address [1]. Since then, precision medicine has frequently been used as a term that contains concepts of personalized medicine worldwide. Generally, precision medicine refers to a medical model that proposes the customization of healthcare with medical decisions, treatments, practices or products tailored to individual patients. Biomolecules 2020, 10, 62; doi:10.3390/biom10010062 www.mdpi.com/journal/biomolecules Biomolecules 2020, 10, 62 2 of 21 Biomolecules 2020, 10, x 2 of 20 individual patients. In this model, diagnostic testing is often employed for selecting appropriate and In this model, diagnostic testing is often employed for selecting appropriate and optimal therapies optimal therapies based on the context of a patient’s genetic content or other molecular or cellular basedBiomolecules on the context2020, 10, x of a patient’s genetic content or other molecular or cellular analyses [2].2 Toof 20 date, analyses [2]. To date, most precision medicine interventions consist of genetic profiling, including the most precision medicine interventions consist of genetic profiling, including the detection of predictive detectionindividual of predictive patients. biomarkers In this model, [3]. Itdia hasgnostic been testing repeatedly is often reported employed that for this selecting may identify appropriate patients and biomarkers [3]. 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It has been it has repeatedly also been reported reported that thatthis may only identify a small patients number of a small number of patients benefit from current precision medicine, and it is of no benefit for most patientsat risk benefit for a specific from current disease precisionor a severe medicine, variant of anda disease it is ofand no allow benefit for preventive for most tumor interventions patients to [ 4,5]. tumor patients [4,5]. In addition, it has been stated that the MD Anderson Cancer Center found that In addition,reduce the it hasburden been of stateddisease that and the improve MD Anderson quality of life. 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These proteomics results indicate data, should that we be involved,definitely andneed integrated to explore analyses the involved,possibility and integrated that more analyses patients ofcan different benefit from type precisions of omics medicine. data are To considered extend precision to be ofmedicine, paramount not of different types of omics data are considered to be of paramount importance. In this review article, importance.only genomicIn this review data but article, also weother highlight omics data, the current such as knowledge epigenetic andof the proteomics importance data, of epigeneticshould be we highlight the current knowledge of the importance of epigenetic data in precision medicine by data in involvedprecision, and medicine integrated by analysesdescribing, of different in part typesicular, of the omics integrated data are consideredanalysis of to multiomics be of paramount data, describing, in particular, the integrated analysis of multiomics data, including epigenetic data, using includingimportance. epigenetic In thisdata, review using article, machine we highlight learning the and current deep knowledgelearning technologies. of the importance of epigenetic machinedata in learning precision and medicine deep learning by describing, technologies. in particular, the integrated analysis of multiomics data, including epigenetic data, using machine learning and deep learning technologies. 2. Characteristics2. Characteristics of Epigenetics of Epigenetics and and Technologies Technologies for forEpigenetics Epigenetics Analysis Analysis 2. Characteristics of Epigenetics and Technologies for Epigenetics Analysis 2.1.2.1. General General Characteristics Characteristics of Epigenetics of Epigenetics In 2.1.principle,In principle,General epi-geneticsCharacteristics epi-genetics is of the Epigenetics is thestudy study of heri of heritabletable phenotype phenotype changes changes without without altering altering the theDNA DNA sequencesequence [7].In [ 7Theprinciple,]. 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