In breast cancer research, it is important to identify genomic markers associated with prognosis. Multiple microarray gene expression profiling studies have been conducted, searching for prognosis markers. Genomic markers identified from the analysis of single datasets often suffer a lack of reproducibility because of small sample sizes. Integrative analysis of data from multiple independent studies has a larger sample size and may provide a cost-effective solution.
We collect four breast cancer prognosis studies with gene expression measurements. An accelerated failure time (AFT) model with an unknown error distribution is adopted to describe survival. An integrative sparse boosting approach is employed for marker selection. The proposed model and boosting approach can effectively accommodate heterogeneity across multiple studies and identify genes with consistent effects.
Simulation study shows that the proposed approach outperforms alternatives including meta-analysis and intensity approaches by identifying the majority or all of the true positives, while having a low false positive rate. In the analysis of breast cancer data, 44 genes are identified as associated with prognosis. Many of the identified genes have been previously suggested as associated with tumorigenesis and cancer prognosis. The identified genes and corresponding predicted risk scores differ from those using alternative approaches. Monte Carlo-based prediction evaluation suggests that the proposed approach has the best prediction performance.
Integrative analysis may provide an effective way of identifying breast cancer prognosis markers. Markers identified using the integrative sparse boosting analysis have sound biological implications and satisfactory prediction performance.
Breast cancer prognosis; Gene Expression; Integrative analysis; Sparse boosting
Conbercept is a genetically engineered homodimeric protein for the treatment of wet age-related macular degeneration (wet AMD) that functions by blocking VEGF-family proteins. Its huge, highly variable architecture makes characterization and development of a functional assay difficult. In this study, the primary structure, number of disulfide linkages and glycosylation state of conbercept were characterized by high-performance liquid chromatography, mass spectrometry, and capillary electrophoresis. Molecular modeling was then applied to obtain the spatial structural model of the conbercept–VEGF-A complex, and to study its inter-atomic interactions and dynamic behavior. This work was incorporated into a platform useful for studying the structure of conbercept and its ligand binding functions.
Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010–2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere.
Evidence continues to accumulate showing that tumors contain a minority population of cells responsible for tumor initiation, growth, and recurrence. These are termed “cancer stem cells” (CSCs). Functional assays have identified the self-renewal and tumor-initiation capabilities of CSCs. Moreover, recent studies have revealed that these CSCs is responsible for chemotherapy resistance within a tumor. Several mechanisms of chemoresistance have been proposed, including increased Wnt/â-catenin and Notch signaling, as well as high expression levels of adenosine triphosphate-binding cassette transporters, an active DNA repair capacity, and slow rate of self-renewal. Nanoscale drug-delivery systems, which transport therapeutically active molecules, prolong circulation, and improve biodistribution in the body, may allow more effective and specific therapies to address the challenges posed by CSCs. In particular, some nanovehicles are being exploited for selective drug delivery to CSCs and show promising results. In this review, we highlight the mechanisms of drug resistance and the novel strategies using nanoscale drugs to eliminate CSCs.
drug resistance, drug delivery, chemoresistance, Wnt; â-catenin signaling, Notch signaling
High-throughput gene profiling studies have been extensively conducted, searching for markers associated with cancer development and progression. In this study, we analyse cancer prognosis studies with right censored survival responses. With gene expression data, we adopt the weighted gene co-expression network analysis (WGCNA) to describe the interplay among genes. In network analysis, nodes represent genes. There are subsets of nodes, called modules, which are tightly connected to each other. Genes within the same modules tend to have co-regulated biological functions. For cancer prognosis data with gene expression measurements, our goal is to identify cancer markers, while properly accounting for the network module structure. A two-step sparse boosting approach, called Network Sparse Boosting (NSBoost), is proposed for marker selection. In the first step, for each module separately, we use a sparse boosting approach for within-module marker selection and construct module-level ‘super markers ’. In the second step, we use the super markers to represent the effects of all genes within the same modules and conduct module-level selection using a sparse boosting approach. Simulation study shows that NSBoost can more accurately identify cancer-associated genes and modules than alternatives. In the analysis of breast cancer and lymphoma prognosis studies, NSBoost identifies genes with important biological implications. It outperforms alternatives including the boosting and penalization approaches by identifying a smaller number of genes/modules and/or having better prediction performance.
Expansion of CAG/CTG trinucleotide repeats (TNRs) in humans is associated with a number of neurological and neurodegenerative disorders including Huntington’s disease. Increasing evidence suggests that formation of a stable DNA hairpin within CAG/CTG repeats during DNA metabolism leads to TNR instability. However, the molecular mechanism by which cells recognize and repair CAG/CTG hairpins is largely unknown. Recent studies have identified a novel DNA repair pathway specifically removing (CAG)n/(CTG)n hairpins, which is considered a major mechanism responsible for TNR instability. The hairpin repair (HPR) system targets the repeat tracts for incisions in the nicked strand in an error-free manner. To determine the substrate spectrum of the HPR system and its ability to process smaller hairpins, which may be the intermediates for CAG/CTG expansions, we constructed a series of CAG/CTG hairpin heteroduplexes containing different numbers of repeats (from 5 to 25) and examined their repair in human nuclear extracts. We show here that although repair efficiencies differ slightly among these substrates, removal of the individual hairpin structures all involve endonucleolytic incisions within the repeat tracts in the nicked DNA strand. Analysis of the repair intermediates defined specific incision sites for each substrate, which were all located within the repeat regions. Mismatch repair proteins are not required for, nor do they inhibit, the processing of smaller hairpin structures. These results suggest that the HPR system ensures CAG/CTG stability primarily by removing various sizes of (CAG)n/(CTG)n hairpin structures during DNA metabolism.
Trinucleotide repeats; Hairpin repair; Endonucleolytic incision; MutSβ
Conflicting findings exist regarding the link between environmental factors and development of Alzheimer's disease (AD) in a variety of transgenic mouse models of AD. In the present study, we investigated the effect of behavioral stress on the onset and progression of Aβ pathology in the brains of TgCRND8 mice, a transgenic mouse model of AD. One group of TgCRND8 mice was subjected to restraint stress starting at 1 month of age until they were 3 months old, while restraint stress in the second group started at 4 months of age until they were 6 months old. After 2 months of treatment, no differences in the soluble, formic acid extracted, or histologically detected Aβ deposition in the cortical and hippocampal levels were found between non-stressed and stressed mice. These results showed that restraint stress alone failed to aggravate amyloid pathology when initiated either before or after the age of amyloid plaque deposition in TgCRND8 mice, suggesting that if stress aggravated AD phenotype, it may not be via an amyloid-related mechanism in the TgCRND8 mice. These findings are indicative that plaque load per se may not be used as a significant criterion for evaluating the effect of stress on AD patients.
Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods.
Although in cancer research microarray gene profiling studies have been successful in identifying genetic variants predisposing to the development and progression of cancer, the identified markers from analysis of single datasets often suffer low reproducibility. Among multiple possible causes, the most important one is the small sample size hence the lack of power of single studies. Integrative analysis jointly considers multiple heterogeneous studies, has a significantly larger sample size, and can improve reproducibility. In this article, we focus on cancer prognosis studies, where the response variables are progression-free, overall, or other types of survival. A group minimax concave penalty (GMCP) penalized integrative analysis approach is proposed for analyzing multiple heterogeneous cancer prognosis studies with microarray gene expression measurements. An efficient group coordinate descent algorithm is developed. The GMCP can automatically accommodate the heterogeneity across multiple datasets, and the identified markers have consistent effects across multiple studies. Simulation studies show that the GMCP provides significantly improved selection results as compared with the existing meta-analysis approaches, intensity approaches, and group Lasso penalized integrative analysis. We apply the GMCP to four microarray studies and identify genes associated with the prognosis of breast cancer.
integrative analysis; cancer prognosis; microarray; penalized selection
CD133 has been identified as a putative cancer stem cell marker in colorectal cancer (CRC). However, the clinical and prognostic significance of CD133 in CRC remains controversial.
Publications were identified which assessed the clinical or prognostic significance of CD133 in CRC up to October 2012. A meta-analysis was performed to clarify the association between CD133 expression and clinical outcomes.
A total of 12 studies met the inclusion criteria, and comprised 3652 cases. Analysis of these data showed that CD133 was not significantly associated with the depth of CRC invasion (odds ratio [OR] = 1.44, 95% confidence interval [CI]: 0.77–2.68, Z = 1.15, P = 0.252) or tumor differentiation (OR = 0.63, 95% CI: 0.28–1.46, Z = −1.06, P = 0.286). Also, there was no statistically significant association of CD133 with lymph node metastasis (OR = 1.16, 95% CI: 0.87–1.54, Z = 1.05, P = 0.315) or lymphatic invasion (OR = 1.08, 95% CI: 0.81–1.43, Z = 0.53, P = 0.594). However, in identified studies, overexpression of CD133 was highly correlated with reduced overall survival (relative risk [RR] = 2.14, 95% CI: 1.45–3.17, Z = 3.81, P = 0.0001).
CD133 may play an important role in the progression of CRC, and overexpression of CD133 is closely related with poorer patient survival. If these findings are confirmed by well-designed prospective studies, CD133 may be a useful maker for clinical applications.
CD133; Cancer stem cell; Colorectal cancer; Prognosis
signaling pathways and transcriptional effectors responsible for directing
mammalian lens development provide key regulatory molecules that can inform our understanding of human eye defects. The hedgehog genes encode extracellular signaling proteins responsible for patterning and tissue formation during embryogenesis. Signal transduction of this pathway is mediated through activation of the transmembrane proteins smoothened and patched, stimulating downstream signaling resulting in the activation or repression of hedgehog target genes. Hedgehog signaling is implicated in eye development, and defects in hedgehog signaling components have been shown to result in defects of the retina, iris, and lens.
We assessed the consequences of constitutive hedgehog signaling in the developing mouse lens using Cre-LoxP technology to express the conditional M2 smoothened allele in the embryonic head and lens ectoderm.
Although initial lens development appeared normal, morphological defects were apparent by E12.5 and became more significant at later stages of embryogenesis. Altered lens morphology correlated with ectopic expression of FoxE3, which encodes a critical gene required for human and mouse lens development. Later, inappropriate expression of the epithelial marker Pax6, and as well as fiber cell markers c-maf and Prox1 also occurred, indicating a failure of appropriate lens fiber cell differentiation accompanied by altered lens cell proliferation and cell death.
Our findings demonstrate that the ectopic activation of downstream effectors of the hedgehog signaling pathway in the mouse lens disrupts normal fiber cell differentiation by a mechanism consistent with a sustained epithelial cellular developmental program driven by FoxE3.
This study shows the ability of the lens to respond to altered Smoothened activity. Constitutive activation of Smoothened in the surface ectoderm and derivatives, including the lens results in altered expression of lens markers and abnormal lens differentiation and morphology.
This study investigated the rapid onset of bronchodilation effect and compared lung function changes following budesonide/formoterol (Symbicort Turbuhaler®) inhalation in Chinese patients with moderate-severe chronic obstructive pulmonary disease (COPD) and bronchial asthma.
In this open-label, parallel-group clinical study, patients eligible for study were divided into COPD group (n=62, mean age 68.16±8.75 years) and asthma group (n=30, mean age 45.80±12.35 years). Lung function tests (include FEV1, FVC, FEV1/FVC, and IC) were performed at baseline (t=0 min time point, value before inhalation of budesonide/formoterol), and then eligible patients received two inhalations of budesonide/formoterol (160/4.5 μg). Lung function tests were reassessed at t=3, 10 and 30 min time point. The primary end-point was lung function change 3 min after drug inhalation, and the secondary end-points were comparison of the gas flow rate (ΔFEV1) and volume responses (ΔFVC, ΔIC) between COPD and asthma patients after inhalation of budesonide/formoterol.
Compared with the baseline, all patients significantly improved their lung function (included FEV1, FVC, FEV1/FVC, and IC) at 3 min (P<0.05). Greater bronchodilation efficacy was found in the asthma group compared with the COPD group (P<0.05). In the asthmatic patients, the curves of FEV1, FVC, FEV1/FVC, IC, showed improvement with an ascending trend at all time points from 3 to 30 min. Whereas in the COPD patients, only the curves of FEV1, FVC, IC showed similar pattern. We found that ΔFVC was significantly higher than ΔFEV1 in both groups (P<0.05), but no significant difference between ΔIC and ΔFEV1 (P>0.05). Compared with COPD group, asthma group had higher level of ΔFEV1 and ΔIC (P<0.05), but no significant difference for ΔFVC can be found.
Budesonide/formoterol has a fast onset of bronchodilation effect in patients with moderate-severe COPD and asthma. Greater efficacy was found in the asthma group compared with the COPD group. The gas flow rate and volume responses in patients with COPD differ from those with asthma after inhalation of Budesonide/formoterol.
Budesonide/formoterol; chronic obstructive pulmonary disease; bronchial asthma; lung function test
To evaluate the efficacy and toxicity of the combination regimen of paclitaxel, cisplatin and 5-FU (PCF) as first-line or second-line therapy in patients with advanced gastric and esophagogastric junction (EGJ) adenocarcinoma in China.
The patients were treated with paclitaxel 150 mg/m2 on d1; fractionated cisplatin 15 mg/m2 and continuous infusion 5-FU 600 mg/(m2·d) intravenously on d1-d5 of a 21-d cycle until disease progression or unacceptable toxicities.
Seventy-five patients have been enrolled, among which, 41 received PCF regimen as the first-line therapy (group A) and 34 received the regimen as the second-line therapy (group B) with the median age of 59 years old and Karnofsky performance status (KPS) score ≥80. Toxicities were analyzed in all 75 patients. Seventy-one patients were evaluable for efficacy. The median overall survival (mOS) was 12.0 months (95% CI: 7.9-16.2 months) in group A and 7.3 months (95% CI: 4.3-10.3 months) in group B, respectively. The median progression-free survival (mPFS) was 5.7 months (95% CI: 4.1-7.2 months) and 5.0 months (95% CI: 3.1-6.9 months), respectively. The response rate (CR+PR) was 40% (16/40; 95% CI: 24.9-56.7%) in group A and 22.6% (7/31; 95% CI: 9.6-41.1%) in group B. Major grade 3 or 4 adverse events include neutropenia (41.3%), febrile neutropenia (9.3%), nausea/anorexia (10.7%), and vomiting (5.3%). There was no treatment-related death.
The combination chemotherapy with PCF is active and tolerable as first-line and second-line therapy in Chinese patients with advanced gastric and EGJ adenocarcinoma. The response and survival of PCF are same as those of DCF, but the tolerance is much better.
Advanced gastric cancer; esophagogastric junction (EGJ); adenocarcinoma; paclitaxel
Evidence from previous psycholinguistic research suggests that phonological units such as phonemes have a privileged role during phonological planning in Dutch and English (aka the segment-retrieval hypothesis). However, the syllable-retrieval hypothesis previously proposed for Mandarin assumes that only the entire syllable unit (without the tone) can be prepared in advance in speech planning. Using Cantonese Chinese as a test case, the present study was conducted to investigate whether the syllable-retrieval hypothesis can be applied to other Chinese spoken languages. In four implicit priming (form-preparation) experiments, participants were asked to learn various sets of prompt-response di-syllabic word pairs and to utter the corresponding response word upon seeing each prompt. The response words in a block were either phonologically related (homogeneous) or unrelated (heterogeneous). Participants' naming responses were significantly faster in the homogeneous than in the heterogeneous conditions when the response words shared the same word-initial syllable (without the tone) (Exps.1 and 4) or body (Exps.3 and 4), but not when they shared merely the same word-initial phoneme (Exp.2). Furthermore, the priming effect observed in the syllable-related condition was significantly larger than that in the body-related condition (Exp. 4). Although the observed syllable priming effects and the null effect of word-initial phoneme are consistent with the syllable-retrieval hypothesis, the body-related (sub-syllabic) priming effects obtained in this Cantonese study are not. These results suggest that the syllable-retrieval hypothesis is not generalizable to all Chinese spoken languages and that both syllable and sub-syllabic constituents are legitimate planning units in Cantonese speech production.
Genetic researchers often collect disease related quantitative traits in addition to disease status because they are interested in understanding the pathophysiology of disease processes. In genome-wide association (GWA) studies, these quantitative phenotypes may be relevant to disease development and serve as intermediate phenotypes or they could be behavioral or other risk factors that predict disease risk. Statistical tests combining both disease status and quantitative risk factors should be more powerful than case-control studies, as the former incorporates more information about the disease. In this paper, we proposed a modified inverse-variance weighted meta-analysis method to combine disease status and quantitative intermediate phenotype information. The simulation results showed that when an intermediate phenotype was available, the inverse-variance weighted method had more power than did a case-control study of complex diseases, especially in identifying susceptibility loci having minor effects. We further applied this modified meta-analysis to a study of imputed lung cancer genotypes with smoking data in 1154 cases and 1137 matched controls. The most significant SNPs came from the CHRNA3-CHRNA5-CHRNB4 region on chromosome 15q24–25.1, which has been replicated in many other studies. Our results confirm that this CHRNA region is associated with both lung cancer development and smoking behavior. We also detected three significant SNPs—rs1800469, rs1982072, and rs2241714—in the promoter region of the TGFB1 gene on chromosome 19 (p = 1.46×10−5, 1.18×10−5, and 6.57×10−6, respectively). The SNP rs1800469 is reported to be associated with chronic obstructive pulmonary disease and lung cancer in cigarette smokers. The present study is the first GWA study to replicate this result. Signals in the 3q26 region were also identified in the meta-analysis. We demonstrate the intermediate phenotype can potentially enhance the power of complex disease association analysis and the modified meta-analysis method is robust to incorporate intermediate phenotype or other quantitative risk factor in the analysis.
Meridians, acupoints, and Chinese herbs are important components of traditional Chinese medicine (TCM). They have been used for disease treatment and prevention and as alternative and complementary therapies. Systems biology integrates omics data, such as transcriptional, proteomic, and metabolomics data, in order to obtain a more global and complete picture of biological activity. To further understand the existence and functions of the three components above, we reviewed relevant research in the systems biology literature and found many recent studies that indicate the value of acupuncture and Chinese herbs. Acupuncture is useful in pain moderation and relieves various symptoms arising from acute spinal cord injury and acute ischemic stroke. Moreover, Chinese herbal extracts have been linked to wound repair, the alleviation of postmenopausal osteoporosis severity, and anti-tumor effects, among others. Different acupoints, variations in treatment duration, and herbal extracts can be used to alleviate various symptoms and conditions and to regulate biological pathways by altering gene and protein expression. Our paper demonstrates how systems biology has helped to establish a platform for investigating the efficacy of TCM in treating different diseases and improving treatment strategies.
In high-throughput -omics studies, markers identified from analysis of single data sets often suffer from a lack of reproducibility because of sample limitation. A cost-effective remedy is to pool data from multiple comparable studies and conduct integrative analysis. Integrative analysis of multiple -omics data sets is challenging because of the high dimensionality of data and heterogeneity among studies. In this article, for marker selection in integrative analysis of data from multiple heterogeneous studies, we propose a 2-norm group bridge penalization approach. This approach can effectively identify markers with consistent effects across multiple studies and accommodate the heterogeneity among studies. We propose an efficient computational algorithm and establish the asymptotic consistency property. Simulations and applications in cancer profiling studies show satisfactory performance of the proposed approach.
High-dimensional data; Integrative analysis; 2-norm group bridge
Despite the development of various systems to generate live recombinant Salmonella Typhimurium vaccine strains, little work has been performed to systematically evaluate and compare their relative immunogenicity. Such information would provide invaluable guidance for the future rational design of live recombinant Salmonella oral vaccines.
To compare vaccine strains encoded with different antigen delivery and expression strategies, a series of recombinant Salmonella Typhimurium strains were constructed that expressed either the enhanced green fluorescent protein (EGFP) or a fragment of the hemagglutinin (HA) protein from the H5N1 influenza virus, as model antigens. The antigens were expressed from the chromosome, from high or low-copy plasmids, or encoded on a eukaryotic expression plasmid. Antigens were targeted for expression in either the cytoplasm or the outer membrane. Combinations of strategies were employed to evaluate the efficacy of combined delivery/expression approaches. After investigating in vitro and in vivo antigen expression, growth and infection abilities; the immunogenicity of the constructed recombinant Salmonella strains was evaluated in mice. Using the soluble model antigen EGFP, our results indicated that vaccine strains with high and stable antigen expression exhibited high B cell responses, whilst eukaryotic expression or colonization with good construct stability was critical for T cell responses. For the insoluble model antigen HA, an outer membrane expression strategy induced better B cell and T cell responses than a cytoplasmic strategy. Most notably, the combination of two different expression strategies did not increase the immune response elicited.
Through systematically evaluating and comparing the immunogenicity of the constructed recombinant Salmonella strains in mice, we identified their respective advantages and deleterious or synergistic effects. Different construction strategies were optimally-required for soluble versus insoluble forms of the protein antigens. If an antigen, such as EGFP, is soluble and expressed at high levels, a low-copy plasmid-cytoplasmic expression strategy is recommended; since it provokes the highest B cell responses and also induces good T cell responses. If a T cell response is preferred, a eukaryotic expression plasmid or a chromosome-based, cytoplasmic-expression strategy is more effective. For insoluble antigens such as HA, an outer membrane expression strategy is recommended.
Salmonella Typhimurium; Live oral vaccine; Soluble and insoluble antigens; Construction strategies; Immunological comparison
Since the antiretroviral therapy (ART) was introduced to patients infected by human immunodeficiency virus (HIV), the HIV related mortality and morbidity have been significantly reduced. The major obstacle for long-term successful anti-HIV treatment is the emergence of drug resistant mutants. Current data of drug resistance was mainly obtained on HIV-1 subtype B but rarely on non-B virus, even more rare with newly emerged circulating recombinant forms (CRFs). The lack of such data limits the rational management of ART for the increasing number of patients infected by non-subtype B virus. In this study, a HIV-1 CRF07_BC strain CNGZD was isolated from a HIV patient and its genome was sequenced and deposited in GenBank (JQ423923). Potential drug resistant mutants of this CRF07_BC virus strain were selected in PBMCs cultures in the presence of Nevirapine (NVP), which is the most frequently used antiretroviral drug in China. Four combination profiles of mutations were identified in the NVP-selected mutants, which were initiated with A98G, V108I, Y181C and I135T/I382L and followed by more than two other mutations at the end of the selections, respectively. A total of seven previously reported mutations (A98G, V106M, V108I, I135T, Y181C, V189I, K238N) and seven novel mutations (P4H, T48I, I178M, V314A, I382L/V, T386A) in the reverse transcriptase gene were found in these NVP-selected mutants. Phenotypic analysis in the NVP-selected mutants showed that all the mutations, except P4H, contribute to NVP resistance. Among them, V106M and Y181C reduce NVP susceptibility for more than 20-fold, while the other mutations cause less than 20 folds drug resistance. Although the information obtained in this in vitro selection study may not fully cover resistant mutations which will actually occur in patients, it has still provided useful information for rational management of ART in patients infected with HIV CRF_BC subtype.
Aberrant DNA methylation plays important roles in carcinogenesis. However, the functional significance of genome-wide hypermethylation and hypomethylation of gene promoters in carcinogenesis currently remain unclear.
Based on genome-wide methylation data for five cancer types, we showed that genes with promoter hypermethylation were highly consistent in function across different cancer types, and so were genes with promoter hypomethylation. Functions related to “developmental processes” and “regulation of biology processes” were significantly enriched with hypermethylated genes but were depleted of hypomethylated genes. In contrast, functions related to “cell killing” and “response to stimulus”, including immune and inflammatory response, were associated with an enrichment of hypomethylated genes and depletion of hypermethylated genes. We also observed that some families of cytokines secreted by immune cells, such as IL10 family cytokines and chemokines, tended to be hypomethylated in various cancer types. These results provide new hints for understanding the distinct functional roles of genome-wide hypermethylation and hypomethylation of gene promoters in carcinogenesis.
Genes with promoter hypermethylation and hypomethylation are highly consistent in function across different cancer types, respectively, but these two groups of genes tend to be enriched in different functions associated with cancer. Especially, we speculate that hypomethylation of gene promoters may play roles in inducing immunity and inflammation disorders in precancerous conditions, which may provide hints for improving epigenetic therapy and immunotherapy of cancer.
C-src is an evolutionarily conserved proto-oncogene that regulates cell proliferation, differentiation and apoptosis. In our previous studies, we have reported that another proto-oncogene, c-erbB2, plays an important role in primordial follicle activation and development. We also found that c-src was expressed in mammalian ovaries, but its functions in primordial follicle activation remain unclear. The objective of this study is to investigate the role and mechanism of c-src during the growth of primordial follicles.
Ovaries from 2-day-old rats were cultured in vitro for 8 days. Three c-src-targeting and one negative control siRNA were designed and used in the present study. PCR, Western blotting and primordial follicle development were assessed for the silencing efficiency of the lentivirus c-src siRNA and its effect on primordial follicle onset. The expression of c-src mRNA and protein in primordial follicle growth were examined using the PCR method and immunohistochemical staining. Furthermore, the MAPK inhibitor PD98059, the PKC inhibitor Calphostin and the PI3K inhibitor LY294002 were used to explore the possible signaling pathways of c-src in primordial folliculogenesis.
The results showed that Src protein was distributed in the ooplasmic membrane and the granulosa cell membrane in the primordial follicles, and c-src expression level increased with the growth of primordial follicle. The c-src -targeting lentivirus siRNAs had a silencing effect on c-src mRNA and protein expression. Eight days after transfection of rat ovaries with c-src siRNA, the GFP fluorescence in frozen ovarian sections was clearly discernible under a fluorescence microscope, and its relative expression level was 5-fold higher than that in the control group. Furthermore, the c-src-targeting lentivirus siRNAs lowered its relative expression level 1.96 times. We also found that the development of cultured primordial follicles was completely arrested after c-src siRNA knockdown of c-src expression. Furthermore, our studies demonstrated that folliculogenesis onset was inhibited by Calphostin, PD98059 or LY294002 treatment,but none of them down-regulated c-src expression. In contrast, the expression levels of p-PKC, p-ERK1/2 and p-PI3K in the follicles were clearly decreased by c-src siRNA transfection. Correspondingly, both Calphostin and LY294002 treatment resulted in a decrease in the p-PKC level in follicles, but no change was observed in the PD98059 group. Finally, LY294002 treatment decreased the p-PI3K expression level in the follicles, but no changes were observed in the PD98059 and Calphostin groups.
C-src plays an important role in regulating primordial follicle activation and growth via the PI3K-PKC- ERK1/2 pathway.
Background and methods:
Curcumin has extraordinary anticancer properties but has limited use due to its insolubility in water and instability, which leads to low systemic bioavailability. We have developed a novel nanoparticulate formulation of curcumin encapsulated in stearic acid-g-chitosan oligosaccharide (CSO-SA) polymeric micelles to overcome these hurdles.
The synthesized CSO-SA copolymer was able to self-assemble to form nanoscale micelles in aqueous medium. The mean diameter of the curcumin-loaded CSO-SA micelles was 114.7 nm and their mean surface potential was 18.5 mV. Curcumin-loaded CSO-SA micelles showed excellent internalization ability that increased curcumin accumulation in cancer cells. Curcumin-loaded CSO-SA micelles also had potent antiproliferative effects on primary colorectal cancer cells in vitro, resulting in about 6-fold greater inhibition compared with cells treated with a solution containing an equivalent concentration of free curcumin. Intravenous administration of curcumin-loaded CSO-SA micelles marginally suppressed tumor growth but did not increase cytotoxicity to mice, as confirmed by no change in body weight. Most importantly, curcumin-loaded CSO-SA micelles were effective for inhibiting subpopulations of CD44+/CD24+ cells (putative colorectal cancer stem cell markers) both in vitro and in vivo.
The present study identifies an effective and safe means of using curcumin-loaded CSO-SA micelles for cancer therapy.
chitosan oligosaccharide; polymeric micelle; curcumin; drug delivery; colorectal cancer; cancer stem cells
Inorganic polyphosphate (poly-P), guanosine pentaphosphate (pppGpp) and guanosine tetraphosphate (ppGpp) are ubiquitous in bacteria. These molecules play a variety of important physiological roles associated with stress resistance, persistence, and virulence. In the bacterial pathogen Mycobacterium tuberculosis, the identities of the proteins responsible for the metabolism of polyphosphate and (p)ppGpp remain to be fully established. M. tuberculosis encodes two PPX-GppA homologues, Rv0496 (MTB-PPX1) and Rv1026, which share significant sequence similarity with bacterial exopolyphosphatase (PPX) and guanosine pentaphosphate 5′-phosphohydrolase (GPP) proteins. Here we delineate the respective biochemical activities of the Rv0496 and Rv1026 proteins and benchmark these against the activities of the PPX and GPP proteins from Escherichia coli. We demonstrate that Rv0496 functions as an exopolyphosphatase, showing a distinct preference for relatively short-chain poly-P substrates. In contrast, Rv1026 has no detectable exopolyphosphatase activities. Analogous to the E. coli PPX and GPP enzymes, the exopolyphosphatase activities of Rv0496 are inhibited by pppGpp and, to a lesser extent, by ppGpp alarmones, which are produced during the bacterial stringent response. However, neither Rv0496 nor Rv1026 have the ability to hydrolyze pppGpp to ppGpp; a reaction catalyzed by E. coli PPX and GPP. Both the Rv0496 and Rv1026 proteins have modest ATPase and to a lesser extent ADPase activities. pppGpp alarmones inhibit the ATPase activities of Rv1026 and, to a lesser extent, the ATPase activities of Rv0496. We conclude that PPX-GppA family proteins may not possess all the catalytic activities implied by their name and may play distinct biochemical roles involved in polyphosphate and (p)ppGpp metabolic pathways.
As an important component of the solid electrolyte interface in lithium ion batteries and an effective blanket breeding material in fusion reactor, the mechanical property of Li2O is of great interest but is not well understood. Here we show that the polycrystalline Li2O nanowires were formed in situ by touching and pulling lithium hydroxide under electron beam (e-beam) illumination. The Li2O nanowires sustained an enhanced elongation (from 80% to 176%) under low dose e-beam irradiation near room temperature as compared with that (from 51% to 57%) without e-beam irradiation. The extremely high deformability could be understood by the fast Li2O diffusion under e-beam irradiation and tensile stress condition. The large elongation without e-beam irradiation implies that nano-structured Li2O is ductile near room temperature.
In high throughput cancer genomic studies, results from the analysis of single datasets often suffer from a lack of reproducibility because of small sample sizes. Integrative analysis can effectively pool and analyze multiple datasets and provides a cost effective way to improve reproducibility. In integrative analysis, simultaneously analyzing all genes profiled may incur high computational cost. A computationally affordable remedy is prescreening, which fits marginal models, can be conducted in a parallel manner, and has low computational cost.
An integrative prescreening approach is developed for the analysis of multiple cancer genomic datasets. Simulation shows that the proposed integrative prescreening has better performance than alternatives, particularly including prescreening with individual datasets, an intensity approach and meta-analysis. We also analyze multiple microarray gene profiling studies on liver and pancreatic cancers using the proposed approach.
The proposed integrative prescreening provides an effective way to reduce the dimensionality in cancer genomic studies. It can be coupled with existing analysis methods to identify cancer markers.