Prostate cancer (PCa) is a common malignant tumor with increasing incidence and high heterogeneity among males worldwide. In the era of big data and artificial intelligence, the paradigm of biomarker discovery is shifting from traditional experimental and small data-based identification toward big data-driven and systems-level screening. Complex interactions between genetic factors and environmental effects provide opportunities for systems modeling of PCa genesis and evolution. We hereby review the current research frontiers in informatics for PCa clinical translation. First, the heterogeneity and complexity in PCa development and clinical theranostics are introduced to raise the concern for PCa systems biology studies. Then biomarkers and risk factors ranging from molecular alternations to clinical phenotype and lifestyle changes are explicated for PCa personalized management. Methodologies and applications for multi-dimensional data integration and computational modeling are discussed. The future perspectives and challenges for PCa systems medicine and holistic healthcare are finally provided.

Early diagnosis and surveillance for metastasis and recurrences are critical issues of urologic cancer. Deregulation of long non-coding RNAs (lncRNAs) has been implicated in urologic malignancies and represents potential markers or therapeutic targets. However, the utility of lncRNA as biomarkers appears to be overstated due to heterogeneous or irreproducible results from different studies. Thus, a critical and cautious review on the biomarker potential of lncRNAs is needed. This review provides an update on new findings of lncRNA-based markers for urologic cancer. The diverse mechanisms and associated examples of lncRNAs involved during the carcinogenesis of prostate cancer, bladder cancer and renal cancer were discussed in a more balanced and critical manner, as were the suitability of lncRNAs as diagnostic or prognostics markers.

Background: Prostate cancer (PCa) is occurred with increasing incidence and heterogeneous pathogenesis. Although clinical strategies are accumulated for PCa prevention, there is still a lack of sensitive biomarkers for the holistic management in PCa occurrence and progression. Based on systems biology and artificial intelligence, translational informatics provides new perspectives for PCa biomarker prioritization and carcinogenic survey.Methods: In this study, gene expression and miRNA-mRNA association data were integrated to construct conditional networks specific to PCa occurrence and progression, respectively. Based on network modeling, hub miRNAs with significantly strong single-line regulatory power were topologically identified and those shared by the condition-specific network systems were chosen as candidate biomarkers for computational validation and functional enrichment analysis.Results: Nine miRNAs, i.e., hsa-miR-1-3p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-182-5p, hsa-miR-198, hsa-miR-22-3p, hsa-miR-24-3p, hsa-miR-34a-5p, and hsa-miR-499a-5p, were prioritized as key players for PCa management. Most of these miRNAs achieved high AUC values (AUC > 0.70) in differentiating different prostate samples. Among them, seven of the miRNAs have been previously reported as PCa biomarkers, which indicated the performance of the proposed model. The remaining hsa-miR-22-3p and hsa-miR-499a-5p could serve as novel candidates for PCa predicting and monitoring. In particular, key miRNA-mRNA regulations were extracted for pathogenetic understanding. Here hsa-miR-145-5p was selected as the case and hsa-miR-145-5p/NDRG2/AR and hsa-miR-145-5p/KLF5/AR axis were found to be putative mechanisms during PCa evolution. In addition, Wnt signaling, prostate cancer, microRNAs in cancer etc. were significantly enriched by the identified miRNAs-mRNAs, demonstrating the functional role of the identified miRNAs in PCa genesis.Conclusion: Biomarker miRNAs together with the associated miRNA-mRNA relations were computationally identified and analyzed for PCa management and carcinogenic deciphering. Further experimental and clinical validations using low-throughput techniques and human samples are expected for future translational studies.

Parkinson’s disease (PD) is a neurodegenerative disorder in elderly people. The personalized diagnosis and treatment remain challenges all over the world. In recent years, natural products are becoming potential therapies for many complex diseases due to their stability and low drug resistance. With the development of informatics technologies, data-driven natural product discovery and healthcare is becoming reality. For PD, however, the relevant research and tools for natural products are quite limited. Here in this review, we summarize current available databases, tools, and models for general natural product discovery and synthesis. These useful resources could be used and integrated for future PD-specific natural product investigations. At the same time, the challenges and opportunities for future natural-product-based PD care will also be discussed.

It still remains a great challenge to efficiently treat malignant cancers which severely threaten human health. Photodynamic therapy (PDT) as a localized therapeutic modality has improved the therapeutic efficacy via chemical damage through reactive oxygen species (ROS). However, their efficacy is severely hampered by insufficient targeted delivery of photosensitizers owing to the lack of suitable carrier with facile preparation process and the clinical applicability. Herein, we applied clinically approved human serum albumin as the nanoreactor to encapsulate photosensitizers Chlorin e6 (Ce6) for enhancing their tumor accumulation and subsequently potent PDT effect against bladder cancer models. Albumin-loaded Chlorin e6 nanoparticles (CA-NPs) with rational nanoscale size exhibit increased reactive oxygen species production and excellent resistance to photobleaching. Moreover, CA-NPs could be efficiently internalized by tumor cells and locate in the lysosome, while they rapidly translocate to cytosol after irradiation to induce remarkable cytotoxicity (IC50 ∼5.8 μg/ml). Furthermore, CA-NPs accumulate effectively in tumor tissue to afford total eradication of murine bladder tumor after single injection. More importantly, we also evidence the superior PDT effect in fresh human bladder tumor tissues via abundant reactive oxygen species generation and subsequent cell apoptosis. These findings demonstrate that human serum albumin acts as a universal tool to load small organic photoactivatable molecule with remarkable effectiveness and readiness for clinical translation.