Neuroprotection of Truncated Peptide IIAVE from Isochrysis zhanjiangensis: Quantum Chemical, Molecular Docking, and Bioactivity Studies.

Parkinson's disease (PD) is a progressive neurodegenerative disorder of the elderly for which there is no cure or disease-modifying therapy. Mitochondrial dysfunction and oxidative stress play a central role in dopaminergic neurodegeneration in PD. Therefore, antioxidants are considered a promising neuroprotective approach. In in vivo activity studies, 6-OHDA-induced oxidative stress in SH-SY5Y cells was established as a model of PD for cellular experiments. IIAVE (Ile-Ile-Ala-Val-Glu) was derived from Isochrysis zhanjiangensis octapeptide (IIAVEAGC), which has a small molecular weight. The structure and antioxidant activity of IIAVE were tested in a previous study and proved to have good antioxidant potential. In this study, the chemical properties of IIAVE were calculated using quantum chemical methods, including frontier molecular orbital (FMO), molecular electrostatic potential (MEP), natural population analysis (NPA), and global reactivity properties. The interaction of IIAVE with Bcl-2 and DJ-1 was investigated using the molecular docking method. The results showed that IIAVE promoted the activation of the Keap1/Nrf2 pathway and up-regulated the expression of the superoxide dismutase 1 (SOD-1) protein by inhibiting the level of reactive oxygen species (ROS) in cells. In addition, IIAVE inhibits ROS production and prevents 6-OHDA-induced oxidative damage by restoring mitochondrial membrane potential. Furthermore, IIAVE inhibited cell apoptosis by increasing the Bcl-2/Bax ratio and inhibiting the activation of Caspase-9 and Caspase-3. Thus, IIAVE may become a potential drug for the treatment and prevention of PD.

Predicting hepatocellular carcinoma through cross-talk genes identified by risk pathways.

Hepatocellular carcinoma (HCC) is the most frequent type of liver cancer with poor survival rate and high mortality. Despite efforts on the mechanism of HCC, new molecular markers are needed for exact diagnosis, evaluation and treatment. Here, we combined transcriptome of HCC with networks and pathways to identify reliable molecular markers. Through integrating 249 differentially expressed genes with syncretic protein interaction networks, we constructed a HCC-specific network, from which we further extracted 480 pivotal genes. Based on the cross-talk between the enriched pathways of the pivotal genes, we finally identified a HCC signature of 45 genes, which could accurately distinguish HCC patients with normal individuals and reveal the prognosis of HCC patients. Among these 45 genes, 15 showed dysregulated expression patterns and a part have been reported to be associated with HCC and/or other cancers. These findings suggested that our identified 45 gene signature could be potential and valuable molecular markers for diagnosis and evaluation of HCC.

Identification of breast cancer recurrence risk factors based on functional pathways in tumor and normal tissues.

The recurrence of breast cancer (BC) is a serious therapeutic problem, and the risk factors for recurrence urgently need to be identified. In this study, we examined the functional pathways in tumor and normal tissues to more comprehensively identify biomarkers for the risk of BC recurrence. We collected tumor and normal tissue gene expression profiles of recurrent BC patients and non-recurrent BC patients from the TCGA database.We derived an expression interval (mean ± 1.96SD) based on non-recurrent patients rather than a single value, such as a mean or median. If the expression of a gene was significantly different from its normal expression interval, it was considered a differentially expressed gene. Eight pathways that significantly distinguished recurrent and non-recurrent BC patients were obtained based on 65% accuracy, and these pathways were all associated with the immune response and sensitivity to drugs. The genes in these eight pathways were also used to analyze survival, and the significance level reached 0.003 in an independent dataset (p = 0.02 in tumor and p = 0.03 in normal tissue). Our results reveal that the integration of tumor and normal tissue functional analyses can comprehensively enhance the understanding of BC prognosis.