ReviewHealth information science and systems2024
From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine.
Review in Health information science and systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 12 citations in OpenAlex.
- Review
- Explainable and visualizable machine learning model development and validation for 5-year postoperative survival prediction in prostate cancer patients aged ≥ 65 years.BMC geriatrics · 2026Article
- Multimodal artificial intelligence in urologic precision oncology: from algorithm to translational medicine (a systemized narrative review).Frontiers in oncology · 2026Review
- Advancements in bone marrow biopsy: the role of omics and artificial intelligence in hematologic diagnostics.Frontiers in medicine · 2026Review
- Mushroom Bioactive Molecules as Anticancerous Agents: An Overview.Food science & nutrition · 2025Review
- Overdiagnosis and Overtreatment in Prostate Cancer.Diseases (Basel, Switzerland) · 2025Review
- Role of multi‑omics in advancing the understanding and treatment of prostate cancer (Review).Molecular medicine reports · 2025Review
- Comprehensive Integrated Analysis Reveals the Spatiotemporal Microevolution of Cancer Cells in Patients with Bone-Metastatic Prostate Cancer.Biomedicines · 2025Article
- Multi-omics insights into bone tissue injury and healing: bridging orthopedic trauma and regenerative medicine.Burns & trauma · 2025Review
- A comprehensive review on computational metabolomics: Advancing multiscale analysis throughComputational and structural biotechnology journal · 2025Review
- Identification of metastasis-related genes for predicting prostate cancer diagnosis, metastasis and immunotherapy drug candidates using machine learning approaches.Biology direct · 2024Article
- Harnessing machine learning to predict prostate cancer survival: a review.Frontiers in oncology · 2024Review
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.