Wen-Xing Li

In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database.

There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents.

Comprehensive tissue-specific gene set enrichment analysis and transcription factor analysis of breast cancer by integrating 14 gene expression datasets

Breast cancer is the most commonly diagnosed malignancy in women. Several key genes and pathways have been proven to correlate with breast cancer pathology. This study sought to explore the differences in key transcription factors (TFs), transcriptional regulation networks and dysregulated pathways in different tissues in breast cancer. We employed 14 breast cancer datasets from NCBI-GEO and performed an integrated analysis in three different tissues including breast, blood and saliva. The results showed that there were eight genes (CEBPD, EGR1, EGR2, EGR3, FOS, FOSB, ID1 and NFIL3) down-regulated in breast tissue but up-regulated in blood tissue. Furthermore, we identified several unreported tissue-specific TFs that may contribute to breast cancer, including ATOH8, DMRT2, TBX15 and ZNF367. The dysregulation of these TFs damaged lipid metabolism, development, cell adhesion, proliferation, differentiation and metastasis processes. Among these pathways, the breast tissue showed the most serious impairment and the blood tissue showed a relatively moderate damage, whereas the saliva tissue was almost unaffected. This study could be helpful for future biomarker discovery, drug design, and therapeutic and predictive applications in breast cancers.

Interactions of Methylenetetrahydrofolate Reductase Gene Polymorphisms, Folate, and Homocysteine on Blood Pressure in a Chinese Hypertensive Population.

BACKGROUND High blood pressure is related to cardiovascular diseases. We aimed to explore the interactions of methylenetetrahydrofolate reductase (MTHTR) gene C677T and A1298C mutations and folate/homocysteine (Hcy) status on blood pressure in a Chinese hypertensive population. METHODS The clinical data in the present study derived from a previous trial (NCT00520247). Genotypes in Hcy pathway enzymes were detected by PCR-RFLP methods. Supine blood pressure was measured with a mercury sphygmomanometer. Serum Hcy was measured by high-performance liquid chromatography, and serum folate was measured by chemiluminescent immunoassay. RESULTS This study showed that hyperhomocysteinemia independently elevated diastolic blood pressure (DBP) (β (SE): 2.02 (0.85), p = 0.018). Furthermore, individuals with high Hcy and MTHFR1298AC + CC genotypes showed higher DBP than the normal Hcy and 1298AA carriers (β (SE): 1.81 (0.54), p = 0.001). This correlation was verified by the trend test (p = 0.003). However, polymorphisms of MTHFR C677T, MTR A2756G or MTRR A66G do not affect baseline blood pressure level. CONCLUSIONS The present study demonstrated that the MTHFR A1298C mutation accompanied by hyperhomocysteinemia jointly elevated DBP. Further studies are necessary to confirm the role of these genotypes and Hcy on blood pressure in a larger population.

Proteome-wide prediction of targets for aspirin: new insight into the molecular mechanism of aspirin

Besides its anti-inflammatory, analgesic and anti-pyretic properties, aspirin is used for the prevention of cardiovascular disease and various types of cancer. The multiple activities of aspirin likely involve several molecular targets and pathways rather than a single target. Therefore, systematic identification of these targets of aspirin can help us understand the underlying mechanisms of the activities. In this study, we identified 23 putative targets of aspirin in the human proteome by using binding pocket similarity detecting tool combination with molecular docking, free energy calculation and pathway analysis. These targets have diverse folds and are derived from different protein family. However, they have similar aspirin-binding pockets. The binding free energy with aspirin for newly identified targets is comparable to that for the primary targets. Pathway analysis revealed that the targets were enriched in several pathways such as vascular endothelial growth factor (VEGF) signaling, Fc epsilon RI signaling and arachidonic acid metabolism, which are strongly involved in inflammation, cardiovascular disease and cancer. Therefore, the predicted target profile of aspirin suggests a new explanation for the disease prevention ability of aspirin. Our findings provide a new insight of aspirin and its efficacy of disease prevention in a systematic and global view.

Meta-Analysis of Parkinson’s Disease and Alzheimer’s Disease Revealed Commonly Impaired Pathways and Dysregulation of NRF2-Dependent Genes

Many lines of evidence suggest that Parkinsons disease (PD) and Alzheimers disease (AD) have common characteristics, such as mitochondrial dysfunction and oxidative stress. As the underlying molecular mechanisms are unclear, we perform a meta-analysis with 9 microarray datasets of PD studies and 7 of AD studies to explore it. Functional enrichment analysis revealed that PD and AD both showed dysfunction in the synaptic vesicle cycle, GABAergic synapses, phagosomes, oxidative phosphorylation, and TCA cycle pathways, and AD had more enriched genes. Comparing the differentially expressed genes between AD and PD, we identified 54 common genes shared by more than six tissues. Among them, 31 downregulated genes contained the antioxidant response element (ARE) consensus sequence bound by NRF2. NRF2 is a transcription factor, which protects cells against oxidative stress through coordinated upregulation of ARE-driven genes. To our surprise, although NRF2 was upregulated, its target genes were all downregulated. Further exploration found that MAFF was upregulated in all tissues and significantly negatively correlated with the 31 NRF2-dependent genes in diseased conditions. Previous studies have demonstrated over-expressed small MAFs can form homodimers and act as transcriptional repressors. Therefore, MAFF might play an important role in dysfunction of NRF2 regulatory network in PD and AD.

Folate Deficiency and Gene Polymorphisms of MTHFR, MTR and MTRR Elevate the Hyperhomocysteinemia Risk.

BACKGROUND Hyperhomocysteinemia (HHcy) is an independent risk factor for cardiovascular diseases (CVDs). We aimed to investigate the joint effect of homocysteine metabolism gene polymorphisms, as well as the folate deficiency on the risk of HHcy in a Chinese hypertensive population. METHODS This study enrolled 480 hypertensive patients aged 28 - 75 from six hospitals in different Chinese regions from 9/2005 - 12/2005. Known genotypes of methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, methionine synthase (MTR) A2756G, and methionine synthase reductase (MTRR) A66G were detected by PCRRFLP methods. Serum Hcy was measured by high-performance liquid chromatography and serum folate was measured by chemiluminescent immunoassay. RESULTS MTHFR C677T and MTR A2756G can independently elevate the risk of HHcy (TT vs. CC + CT, p < 0.001 and AG + GG vs. AA, p = 0.026, respectively), whereas MTHFR A1298C decreased HHcy risk (AC + CC vs. AA, p < 0.001) and showed a protective effect against HHcy risk. Importantly, the joint effect of these risk genotypes showed significantly higher odds of HHcy than non-risk genotypes, especially the patients with four risk genotypes. It is noteworthy that this deleterious effect was aggravated by folate deficiency. These findings were verified by generalized multifactor dimensionality reduction model (p = 0.001) and a cumulative effects model (p < 0.001). CONCLUSIONS We have first demonstrated that the joint effect of homocysteine metabolism gene polymorphisms and folate deficiency lead to dramatic elevations in the HHcy risk.

Integrated analysis of ischemic stroke datasets revealed sex and age difference in anti-stroke targets

Ischemic stroke is a common neurological disorder and the burden in the world is growing. This study aims to explore the effect of sex and age difference on ischemic stroke using integrated microarray datasets. The results showed a dramatic difference in whole gene expression profiles and influenced pathways between males and females, and also in the old and young individuals. Furthermore, compared with old males, old female patients showed more serious biological function damage. However, females showed less affected pathways than males in young subjects. Functional interaction networks showed these differential expression genes were mostly related to immune and inflammation-related functions. In addition, we found ARG1 and MMP9 were up-regulated in total and all subgroups. Importantly, IL1A, ILAB, IL6 and TNF and other anti-stroke target genes were up-regulated in males. However, these anti-stroke target genes showed low expression in females. This study found huge sex and age differences in ischemic stroke especially the opposite expression of anti-stroke target genes. Future studies are needed to uncover these pathological mechanisms, and to take appropriate pre-prevention, treatment and rehabilitation measures.

Integrated Analysis of Alzheimer's Disease and Schizophrenia Dataset Revealed Different Expression Pattern in Learning and Memory.

Alzheimers disease (AD) and schizophrenia (SZ) are both accompanied by impaired learning and memory functions. This study aims to explore the expression profiles of learning or memory genes between AD and SZ. We downloaded 10 AD and 10 SZ datasets from GEO-NCBI for integrated analysis. These datasets were processed using RMA algorithm and a global renormalization for all studies. Then Empirical Bayes algorithm was used to find the differentially expressed genes between patients and controls. The results showed that most of the differentially expressed genes were related to AD whereas the gene expression profile was little affected in the SZ. Furthermore, in the aspects of the number of differentially expressed genes, the fold change and the brain region, there was a great difference in the expression of learning or memory related genes between AD and SZ. In AD, the CALB1, GABRA5, and TAC1 were significantly downregulated in whole brain, frontal lobe, temporal lobe, and hippocampus. However, in SZ, only two genes CRHBP and CX3CR1 were downregulated in hippocampus, and other brain regions were not affected. The effect of these genes on learning or memory impairment has been widely studied. It was suggested that these genes may play a crucial role in AD or SZ pathogenesis. The different gene expression patterns between AD and SZ on learning and memory functions in different brain regions revealed in our study may help to understand the different mechanism between two diseases.

The identification and molecular mechanism of anti-stroke traditional Chinese medicinal compounds.

Stroke is a worldwide epidemic disease with high morbidity and mortality. The continuously exploration of anti-stroke medicines and molecular mechanism has a long way to go. In this study, in order to screen candidate anti-stroke compounds, more than 60000 compounds from traditional Chinese medicine (TCM) database were computationally analyzed then docked to the 15 known anti-stroke targets. 192 anti-stroke plants for clinical therapy and 51 current anti-stroke drugs were used to validate docking results. Totally 2355 candidate anti-stroke compounds were obtained. Among these compounds, 19 compounds are structurally identical with 16 existing drugs in which part of them have been used for anti-stroke treatment. Furthermore, these candidate compounds were significantly enriched in anti-stroke plants. Based on the above results, the compound-target-plant network was constructed. The network reveals the potential molecular mechanism of anti-stroke for these compounds. Most of candidate compounds and anti-stroke plants are tended to interact with target NOS3, PSD-95 and PDE5A. Finally, using ADMET filter, we identified 35 anti-stroke compounds with favorable properties. The 35 candidate anti-stroke compounds offer an opportunity to develop new anti-stroke drugs and will improve the research on molecular mechanism of anti-stroke.

Corrigendum: In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database

Scientific Reports 6: Article number: 25462; published online: 05 May 2016; updated: 10 October 2016 .