Research concerning the epigenome over the years has systematically and sequentially shown substantial development and we have moved from global inhibition of modifications of the epigenome toward identification and targeted therapy against tumor-specific epigenetic mechanisms. In accordance with this approach, several drugs with epigenetically modulating activity have received considerable attention and appreciation, and recently emerging scientific evidence is uncovering details of their mode of action. High-throughput technologies have considerably improved our existing understanding of tumor suppressors, oncogenes, and signaling pathways that are key drivers of cancer. In this review, we summarize the general epigenetic mechanisms in cancer, including: the post-translational modification of DNA methyltransferase and its mediated inactivation of Ras association domain family 1 isoform A, Sonic hedgehog signaling, Wnt signaling, Notch signaling, transforming growth factor signaling, and natural products with epigenetic modification ability. Moreover, we introduce the importance of nanomedicine for delivery of natural products with modulating ability to epigenetic machinery in cancer cells. Such in-depth and comprehensive knowledge regarding epigenetic dysregulation will be helpful in the upcoming era of molecular genomic pathology for both detection and treatment of cancer. Epigenetic information will also be helpful when nanotherapy is used for epigenetic modification.
epigenetic; modification; methylation; natural products; cancer
Several single nucleotide polymorphisms (SNPs) of renin-angiotensin system (RAS) genes are associated with hypertension (HT) but most of them are focusing on single locus effects. Here, we introduce an unbalanced function based on multifactor dimensionality reduction (MDR) for multiloci genotypes to detect high order gene-gene (SNP-SNP) interaction in unbalanced cases and controls of HT data. Eight SNPs of three RAS genes (angiotensinogen, AGT; angiotensin-converting enzyme, ACE; angiotensin II type 1 receptor, AT1R) in HT and non-HT subjects were included that showed no significant genotype differences. In 2- to 6-locus models of the SNP-SNP interaction, the SNPs of AGT and ACE genes were associated with hypertension (bootstrapping odds ratio [Boot-OR] = 1.972~3.785; 95%, confidence interval (CI) 1.26~6.21; P < 0.005). In 7- and 8-locus model, SNP A1166C of AT1R gene is joined to improve the maximum Boot-OR values of 4.050 to 4.483; CI = 2.49 to 7.29; P < 1.63E − 08. In conclusion, the epistasis networks are identified by eight SNP-SNP interaction models. AGT, ACE, and AT1R genes have overall effects with susceptibility to hypertension, where the SNPs of ACE have a mainly hypertension-associated effect and show an interacting effect to SNPs of AGT and AT1R genes.
Indoxyl sulfate (IS) contributes to oxidative stress and endothelial dysfunction in chronic kidney disease patients. However, the role of mitochondria in IS-induced oxidative stress is not very clear. In this study, we examined whether mitochondria play a pivotal role in modulating the effects of antioxidants during IS treatment. In the context of human umbilical vein endothelial cells, we found that IS had a dose-dependent antiproliferative effect. In addition, we used flow cytometry to demonstrate that the level of reactive oxygen species increased in a dose-dependent manner after treatment with IS. High doses of IS also corresponded to increased mitochondrial depolarization and decreased mitochondrial DNA copy number and mitochondrial mass. However, these effects could be reversed by the addition of antioxidants, namely, vitamin C and N-acetylcysteine. Thus, our results suggest that IS-induced oxidative stress and antiproliferative effect can be attributed to mitochondrial dysfunction and impaired biogenesis and that these processes can be protected by treatment with antioxidants.
Cryptocarya-derived natural products were reported to have several biological effects such as the antiproliferation of some cancers. The possible antioral cancer effect of Cryptocarya-derived substances was little addressed as yet. In this study, we firstly used the methanolic extracts of C. concinna Hance roots (MECCrt) to evaluate its potential function in antioral cancer bioactivity. We found that MECCrt significantly reduced cell viability of two oral cancer Ca9-22 and CAL 27 cell lines in dose-responsive manners (P < 0.01). The percentages of sub-G1 phase and annexin V-positive of MECCrt-treated Ca9-22 and CAL 27 cell lines significantly accumulated (P < 0.01) in a dose-responsive manner as evidenced by flow cytometry. These apoptotic effects were associated with the findings that intracellular ROS generation was induced in MECCrt-treated Ca9-22 and CAL 27 cell lines in dose-responsive and time-dependent manners (P < 0.01). In a dose-responsive manner, MECCrt also significantly reduced the mitochondrial membrane potential in these two cell lines (P < 0.01–0.05). In conclusion, we demonstrated that MECCrt may have antiproliferative potential against oral cancer cells involving apoptosis, ROS generation, and mitochondria membrane depolarization.
Apoptosis is a key mechanism for enhanced cellular radiosensitivity in radiation therapy. Studies suggest that Akt signaling may play a role in apoptosis and radioresistance. This study evaluates the possible modulating role of amiloride, an antihypertensive agent with a modulating effect to alternative splicing for regulating apoptosis, in the antiproliferative effects induced by ionizing radiation (IR) in glioblastoma multiforme (GBM) 8401 cells. Analysis of cell viability showed that amiloride treatment significantly inhibited cell proliferation in irradiated GBM8401 cells (p<0.05) in a time-dependent manner, especially in cells treated with amiloride with IR post-treatment. In comparison with GBM8401 cells treated with amiloride alone, with GBM8401 cells treated with IR alone, and with human embryonic lung fibroblast control cells (HEL 299), GBM8401 cells treated with IR combined with amiloride showed increased overexpression of phosphorylated Akt, regardless of whether IR treatment was performed before or after amiloride administration. The alternative splicing pattern of apoptotic protease-activating factor-1 (APAF1) in cells treated with amiloride alone, IR alone, and combined amiloride-IR treatments showed more consistent cell proliferation compared to that in other apoptosis-related genes such as baculoviral IAP repeat containing 5 (BIRC5), Bcl-X, and homeodomain interacting protein kinase-3 (HIPK3). In GBM8401 cells treated with amiloride with IR post-treatment, the ratio of prosurvival (-XL,-LC) to proapoptotic (-LN,-S) splice variants of APAF1 was lower than that seen in cells treated with amiloride with IR pretreatment, suggesting that proapoptotic splice variants of APAF1 (APAF1-LN,-S) were higher in the glioblastoma cells treated with amiloride with IR post-treatment, as compared to glioblastoma cells and fibroblast control cells that had received other treatments. Together, these results suggest that amiloride modulates cell radiosensitivity involving the Akt phosphorylation and the alternative splicing of APAF1, especially for the cells treated with amiloride with IR post-treatment. Therefore, amiloride may improve the effectiveness of radiation therapy for GBMs.
Treatment of irradiated GBM tumors with amiloride inhibited cell proliferation in a time-dependent manner. Drug treatment alone showed increased expression of pAkt.
Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer.
Alzheimer's disease (AD) is the main cause of dementia for older people. Although several antidementia drugs such as donepezil, rivastigmine, galantamine, and memantine have been developed, the effectiveness of AD drug therapy is still far from satisfactory. Recently, the single nucleotide polymorphisms (SNPs) have been chosen as one of the personalized medicine markers. Many pharmacogenomics databases have been developed to provide comprehensive information by associating SNPs with drug responses, disease incidence, and genes that are critical in choosing personalized therapy. However, we found that some information from different sets of pharmacogenomics databases is not sufficient and this may limit the potential functions for pharmacogenomics. To address this problem, we used approximate string matching method and data mining approach to improve the searching of pharmacogenomics database. After computation, we can successfully identify more genes linked to AD and AD-related drugs than previous online searching. These improvements may help to improve the pharmacogenomics of AD for personalized medicine.
This study computationally determines the contribution of clinicopathologic factors correlated with 5-year survival in oral squamous cell carcinoma (OSCC) patients primarily treated by surgical operation (OP) followed by other treatments. From 2004 to 2010, the program enrolled 493 OSCC patients at the Kaohsiung Medical Hospital University. The clinicopathologic records were retrospectively reviewed and compared for survival analysis. The Apriori algorithm was applied to mine the association rules between these factors and improved survival. Univariate analysis of demographic data showed that grade/differentiation, clinical tumor size, pathology tumor size, and OP grouping were associated with survival longer than 36 months. Using the Apriori algorithm, multivariate correlation analysis identified the factors that coexistently provide good survival rates with higher lift values, such as grade/differentiation = 2, clinical stage group = early, primary site = tongue, and group = OP. Without the OP, the lift values are lower. In conclusion, this hospital-based analysis suggests that early OP and other treatments starting from OP are the key to improving the survival of OSCC patients, especially for early stage tongue cancer with moderate differentiation, having a better survival (>36 months) with varied OP approaches.
Long noncoding RNA (lncRNA) function is described in terms of related gene expressions, diseases, and cancers as well as their polymorphisms. Potential modulators of lncRNA function, including clinical drugs, natural products, and derivatives, are discussed, and bioinformatic resources are summarized. The improving knowledge of the lncRNA regulatory network has implications not only in gene expression, diseases, and cancers, but also in the development of lncRNA-based pharmacology.
Alternative splicing is a major diversification mechanism in the human transcriptome and proteome. Several diseases, including cancers, have been associated with dysregulation of alternative splicing. Thus, correcting alternative splicing may restore normal cell physiology in patients with these diseases. This paper summarizes several alternative splicing-related diseases, including cancers and their target genes. Since new cancer drugs often target spliceosomes, several clinical drugs and natural products or their synthesized derivatives were analyzed to determine their effects on alternative splicing. Other agents known to have modulating effects on alternative splicing during therapeutic treatment of cancer are also discussed. Several commonly used bioinformatics resources are also summarized.
RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently, RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA editing may be a potential target for therapeutic natural products. In this review, we provide a literature overview of the biological functions of RNA editing on gene expression, diseases, cancers, and drugs. The bioinformatics resources of RNA editing were also summarized.
An essential task in a genomic analysis of a human disease is limiting the number of strongly associated genes when studying susceptibility to the disease. The goal of this study was to compare computational tools with and without feature selection for predicting osteoporosis outcome in Taiwanese women based on genetic factors such as single nucleotide polymorphisms (SNPs). To elucidate relationships between osteoporosis and SNPs in this population, three classification algorithms were applied: multilayer feedforward neural network (MFNN), naive Bayes, and logistic regression. A wrapper-based feature selection method was also used to identify a subset of major SNPs. Experimental results showed that the MFNN model with the wrapper-based approach was the best predictive model for inferring disease susceptibility based on the complex relationship between osteoporosis and SNPs in Taiwanese women. The findings suggest that patients and doctors can use the proposed tool to enhance decision making based on clinical factors such as SNP genotyping data.
Antrodia camphorata (AC) is well known in Taiwan as a traditional Chinese medicine. The aim of this study was to investigate whether a fermented culture broth of AC could inhibit melanoma proliferation and progression via suppression of the Wnt/β-catenin signaling pathway. In this study, we observed that AC treatment resulted in decreased cell viability and disturbed Wnt/β-catenin cascade in B16F10 and/or B16F1 melanoma cells. This result was accompanied by a decrease in the expression of Wnt/β-catenin transcriptional targets, including c-Myc and survivin. Furthermore, treatment of melanoma cells with AC resulted in a significant increase in apoptosis, which was associated with DNA fragmentation, cytochrome c release, caspase-9 and -3 activation, PARP degradation, Bcl-2/Bax dysregulation, and p53 expression. We also observed that AC caused G1 phase arrest mediated by a downregulation of cyclin D1 and CDK4 and increased p21 and p27 expression. In addition, we demonstrated that non- and subcytotoxic concentrations of AC markedly inhibited migration and invasion of highly metastatic B16F10 cells. The antimetastatic effect of AC was further confirmed by reductions in the levels of MMP-2, MMP-9, and VEGF expression. These results suggest that Antrodia camphorata may exert antitumor activity by downregulating the Wnt/β-catenin pathways.
Serial analysis of gene expression (SAGE) is a powerful quantification technique for gene expression data. The huge
amount of tag data in SAGE libraries of samples is difficult to analyze with current SAGE analysis tools. Data is often not
provided in a biologically significant way for cross‐analysis and ‐comparison, thus limiting its application.
Hence, an integrated software platform that can perform such a complex task is required. Here, we implement set theory for
cross‐analyzing gene expression data among different SAGE libraries of tissue sources; up‐ or down‐regulated
tissue‐specific tags can be identified computationally. Extract‐SAGE employs a genetic algorithm (GA) to reduce the
number of genes among the SAGE libraries. Its representative tag mining will facilitate the discovery of the candidate genes with
discriminating gene expression.
This software and user manual are freely available at
SAGE; genetic algorithm; set theory; software
Grape seeds extract (GSE) is a famous health food supplement for its antioxidant property. Different concentrations of GSE may have different impacts on cellular oxidative/reduction homeostasis. Antiproliferative effect of GSE has been reported in many cancers but rarely in oral cancer.
The aim of this study is to examine the antioral cancer effects of different concentrations of GSE in terms of cell viability, apoptosis, reactive oxygen species (ROS), mitochondrial function, and DNA damage.
High concentrations (50–400 μg/ml) of GSE dose-responsively inhibited proliferation of oral cancer Ca9-22 cells but low concentrations (1–10 μg/ml) of GSE showed a mild effect in a MTS assay. For apoptosis analyses, subG1 population and annexin V intensity in high concentrations of GSE-treated Ca9-22 cells was increased but less so at low concentrations. ROS generation and mitochondrial depolarization increased dose-responsively at high concentrations but showed minor changes at low concentrations of GSE in Ca9-22 cells. Additionally, high concentrations of GSE dose-responsively induced more γH2AX-based DNA damage than low concentrations.
Differential concentrations of GSE may have a differentially antiproliferative function against oral cancer cells via differential apoptosis, oxidative stress and DNA damage.
GSE; Apoptosis; Oxidative stress; DNA damage; Oral cancer
It is becoming more understandable that an existing challenge for translational research is the development of pharmaceuticals that appropriately target reactive oxygen species (ROS)-mediated molecular networks in cancer cells. In line with this approach, there is an overwhelmingly increasing list of many non-marine drugs and marine drugs reported to be involved in inhibiting and suppressing cancer progression through ROS-mediated cell death. In this review, we describe the strategy of oxidative stress-based therapy and connect the ROS modulating effect to the regulation of apoptosis and autophagy. Finally, we focus on exploring the function and mechanism of cancer therapy by the autophagy modulators including inhibitors and inducers from non-marine drugs and marine drugs.
reactive oxygen species; autophagy; marine drugs; autophagy inhibitors; autophagy inducers
Hypoxia inducible factor 1α (HIF-1α) is a stress-responsive transcription factor to hypoxia and its expression is correlated to tumor progression and angiogenesis. Several single nucleotide polymorphisms (SNPs) of HIF-1α gene in the oxygen-dependent degradation (ODD) domain was reportedly associated with increased HIF-1α activity.
In this study, we focused on the relationship between SNP 1772 C > T (rs11549465) of HIF-1α gene and its breast cancer risk, as well as its correlation with HIF-1α expression and tumor angiogenesis. Ninety six breast cancer patients and 120 age-matched controls were enrolled. We found that 1772 T allele of HIF-1α gene was associated with increased breast cancer risk (adjusted OR = 14.51; 95% CI: 6.74-31.24). This SNP was not associated with clinicopathologic features of angiogenesis such as VEGF activity and the micro-vessel density and survival of breast cancer patients.
Taken together, the 1772 C > T of HIF-1α gene is a potential biomarker for breast cancer susceptibility.
HIF-1α; SNPs; Breast cancer; Association study; Survival
Genetic regulators and signaling pathways are important for the formation of blood vessels. Transcription factors controlling vein identity, intersegmental vessels (ISV) growth and caudal vein plexus (CVP) formation in zebrafish are little understood as yet. Here, we show the importance of the nuclear receptor subfamily member 1A (nr2f1a) in zebrafish vascular development. Amino acid sequence alignment and phylogenetic analysis of nr2f1a is highly conserved among the vertebrates. Our in situ hybridization results showed nr2f1a mRNA is expressed in the lateral plate mesoderm at 18 somite stage and in vessels at 24–30 hpf, suggesting its roles in vasculization. Consistent with this morpholino-based knockdown of nr2fla impaired ISV growth and failed to develop fenestrated vascular structure in CVP, suggesting that nr2f1a has important roles in controlling ISV and CVP growth. Consequently, nr2f1a morphants showed pericardial edema and circulation defects. We further demonstrated reduced ISV cells and decreased CVP endothelial cells sprouting in nr2f1a morphants, indicating the growth impairment of ISV and CVP is due to a decrease of cell proliferation and migration, but not results from cell death in endothelial cells after morpholino knockdown. To test molecular mechanisms and signals that are associated with nr2f1a, we examined the expression of vascular markers. We found that a loss of nr2f1a results in a decreased expression of vein/ISV specific markers, flt4, mrc1, vascular markers stabilin and ephrinb2. This indicates the regulatory role of nr2f1a in controlling vascular development. We further showed that nr2f1a likely interact with Notch signaling by examining nr2f1a expression in rbpsuh morphants and DAPT-treatment embryos. Together, we show nr2f1a plays a critical role for vascular development in zebrafish.
Facial emotion perception (FEP) can affect social function. We previously reported that parts of five tested single-nucleotide polymorphisms (SNPs) in the MET and AKT1 genes may individually affect FEP performance. However, the effects of SNP-SNP interactions on FEP performance remain unclear.
This study compared patients with high and low FEP performances (n = 89 and 93, respectively). A particle swarm optimization (PSO) algorithm was used to identify the best SNP barcodes (i.e., the SNP combinations and genotypes that revealed the largest differences between the high and low FEP groups).
The analyses of individual SNPs showed no significant differences between the high and low FEP groups. However, comparisons of multiple SNP-SNP interactions involving different combinations of two to five SNPs showed that the best PSO-generated SNP barcodes were significantly associated with high FEP score. The analyses of the joint effects of the best SNP barcodes for two to five interacting SNPs also showed that the best SNP barcodes had significantly higher odds ratios (2.119 to 3.138; P < 0.05) compared to other SNP barcodes. In conclusion, the proposed PSO algorithm effectively identifies the best SNP barcodes that have the strongest associations with FEP performance.
This study also proposes a computational methodology for analyzing complex SNP-SNP interactions in social cognition domains such as recognition of facial emotion.
Particle swarm optimization; Single-nucleotide polymorphism; SNP interaction; Facial emotion perception; Algorithm
Prostate cancer is a gland tumor in the male reproductive system. It is a multifaceted and genomically complex disease. Transmembrane protease, serine 2 and v-ets erythroblastosis virus E26 homolog (TMPRSS2-ERG) gene fusions are the common molecular signature of prostate cancer. Although tremendous advances have been made in unraveling various facets of TMPRSS2-ERG-positive prostate cancer, many research findings must be sequentially collected and re-interpreted. It is important to understand the activation or repression of target genes and proteins in response to various stimuli and the assembly in signal transduction in TMPRSS2-ERG fusion-positive prostate cancer cells. Accordingly, we divide this multi-component review ofprostate cancer cells into several segments: 1) The role of TMPRSS2-ERG fusion in genomic instability and methylated regulation in prostate cancer and normal cells; 2) Signal transduction cascades in TMPRSS2-ERG fusion-positive prostate cancer; 3) Overexpressed genes in TMPRSS2-ERG fusion-positive prostate cancer cells; 4) miRNA mediated regulation of the androgen receptor (AR) and its associated protein network; 5) Quantitative control of ERG in prostate cancer cells; 6) TMPRSS2-ERG encoded protein targeting; In conclusion, we provide a detailed understanding of TMPRSS2-ERG fusion related information in prostate cancer development to provide a rationale for exploring TMPRSS2-ERG fusion-mediated molecular network machinery.
ORAI1 channels play an important role for breast cancer progression and metastasis. Previous studies indicated the strong correlation between breast cancer and individual single nucleotide polymorphisms (SNPs) of ORAI1 gene. However, the possible SNP-SNP interaction of ORAI1 gene was not investigated.
To develop the complex analyses of SNP-SNP interaction, we propose a genetic algorithm (GA) to detect the model of breast cancer association between five SNPs (rs12320939, rs12313273, rs7135617, rs6486795 and rs712853) of ORAI1 gene. For individual SNPs, the differences between case and control groups in five SNPs of ORAI1 gene were not significant. In contrast, GA-generated SNP models show that 2-SNP (rs12320939-GT/rs6486795-CT), 3-SNP (rs12320939-GT/rs12313273-TT/rs6486795-TC), 5-SNP (rs12320939-GG/rs12313273-TC/rs7135617-TT/rs6486795-TT/rs712853-TT) have higher risks for breast cancer in terms of odds ratio analysis (1.357, 1.689, and 13.148, respectively).
Taken together, the cumulative effects of SNPs of ORAI1 gene in breast cancer association study were well demonstrated in terms of GA-generated SNP models.
Single nucleotide polymorphism; Genetic algorithm; SNP interaction; Breast cancer
In addition to the previous investigations of bioactivity of aqueous extract of the edible Gracilaria tenuistipitata (AEGT) against H2O2-induced DNA damage and hepatitis C virus replication, the purpose of this study is to evaluate the potential therapeutic properties of AEGT against inflammation and hepatotoxicity using lipopolysaccharide (LPS)-stimulated mouse RAW 264.7 cells, primary rat peritoneal macrophages and carbon tetrachloride (CCl4)-induced acute hepatitis model in rats. AEGT concentration-dependently inhibited the elevated RNA and protein levels of inducible nitric oxide synthase and cyclooxygenase-2, thereby reducing nitric oxide and prostaglandin E2 levels, respectively. Moreover, AEGT significantly suppressed the production of LPS-induced proinflammatory cytokines, including interleukin (IL)-1β, IL-6 and tumor necrosis factor-α. These inhibitory effects were associated with the suppression of nuclear factor-kappa B activation and mitogen-activated protein kinase phosphorylation by AEGT in LPS-stimulated cells. In addition, we highlighted the hepatoprotective and curative effects of AEGT in a rat model of CCl4-intoxicated acute liver injury, which was evident from reduction in the elevated serum aspartate aminotransferase and alanine aminotransferase levels as well as amelioration of histological damage by pre-treatment or post-treatment of AEGT. In conclusion, the results demonstrate that AEGT may serve as a potential supplement in the prevention or amelioration of inflammatory diseases.
Determining the complex relationship between diseases, polymorphisms in human genes and environmental factors is challenging. Multifactor dimensionality reduction (MDR) has proven capable of effectively detecting statistical patterns of epistasis. However, MDR has its weakness in accurately assigning multi-locus genotypes to either high-risk and low-risk groups, and does generally not provide accurate error rates when the case and control data sets are imbalanced. Consequently, results for classification error rates and odds ratios (OR) may provide surprising values in that the true positive (TP) value is often small.
To address this problem, we introduce a classifier function based on the ratio between the percentage of cases in case data and the percentage of controls in control data to improve MDR (MDR-ER) for multi-locus genotypes to be classified correctly into high-risk and low-risk groups. In this study, a real data set with different ratios of cases to controls (1∶4) was obtained from the mitochondrial D-loop of chronic dialysis patients in order to test MDR-ER. The TP and TN values were collected from all tests to analyze to what degree MDR-ER performed better than MDR.
Results showed that MDR-ER can be successfully used to detect the complex associations in imbalanced data sets.