From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine.
Shumin RenJiakun LiJulián DoradoAlejandro SierraHumbert González-DíazAliuska DuardoBai-Rong ShenPublished in: Health information science and systems (2023)
Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous development of prostate cancer has become a core obstacle in the treatment of prostate cancer. Simultaneously, the issues of overtreatment in early-stage diagnosis, oligometastasis and dormant tumor recognition, as well as personalized drug utilization, are also specific concerns that require attention in the clinical management of prostate cancer. Some typical genetic mutations have been proved to be associated with prostate cancer's initiation and progression. However, single-omic studies usually are not able to explain the causal relationship between molecular alterations and clinical phenotypes. Exploration from a systems genetics perspective is also lacking in this field, that is, the impact of gene network, the environmental factors, and even lifestyle behaviors on disease progression. At the meantime, current trend emphasizes the utilization of artificial intelligence (AI) and machine learning techniques to process extensive multidimensional data, including multi-omics. These technologies unveil the potential patterns, correlations, and insights related to diseases, thereby aiding the interpretable clinical decision making and applications, namely intelligent medicine. Therefore, there is a pressing need to integrate multidimensional data for identification of molecular subtypes, prediction of cancer progression and aggressiveness, along with perosonalized treatment performing. In this review, we systematically elaborated the landscape from molecular mechanism discovery of prostate cancer to clinical translational applications. We discussed the molecular profiles and clinical manifestations of prostate cancer heterogeneity, the identification of different states of prostate cancer, as well as corresponding precision medicine practices. Taking multi-omics fusion, systems genetics, and intelligence medicine as the main perspectives, the current research results and knowledge-driven research path of prostate cancer were summarized.
Keyphrases
- prostate cancer
- radical prostatectomy
- artificial intelligence
- machine learning
- early stage
- single cell
- big data
- decision making
- genome wide
- gene expression
- squamous cell carcinoma
- physical activity
- type diabetes
- risk assessment
- dna methylation
- papillary thyroid
- middle aged
- cardiovascular events
- coronary artery disease
- high throughput
- working memory
- copy number
- data analysis