Biological networks, such as genetic regulatory networks and protein interaction networks, provide important information for studying gene/protein activities. In this paper, we propose a new method, NetBoosting, for incorporating a priori biological network information in analyzing high dimensional genomics data. Specially, we are interested in constructing prediction models for disease phenotypes of interest based on genomics data, and at the same time identifying disease susceptible genes. We employ the gradient descent boosting procedure to build an additive tree model and propose a new algorithm to utilize the network structure in fitting small tree weak learners. We illustrate by simulation studies and a real data example that, by making use of the network information, NetBoosting outperforms a few existing methods in terms of accuracy of prediction and variable selection.
Adverse environmental conditions have large impacts on plant growth and crop production. One of the crucial mechanisms that plants use in variable and stressful natural environments is gene expression modulation through epigenetic modification. In this study, two rice varieties with different drought resistance levels were cultivated under drought stress from tilling stage to seed filling stage for six successive generations. The variations in DNA methylation of the original generation (G0) and the sixth generation (G6) of these two varieties in normal condition (CK) and under drought stress (DT) at seedling stage were assessed by using Methylation Sensitive Amplification Polymorphism (MSAP) method. The results revealed that drought stress had a cumulative effect on the DNA methylation pattern of both varieties, but these two varieties had different responses to drought stress in DNA methylation. The DNA methylation levels of II-32B (sensitive) and Huhan-3 (resistant) were around 39% and 32%, respectively. Genome-wide DNA methylation variations among generations or treatments accounted for around 13.1% of total MSAP loci in II-32B, but was only approximately 1.3% in Huhan-3. In II-32B, 27.6% of total differentially methylated loci (DML) were directly induced by drought stress and 3.2% of total DML stably transmitted their changed DNA methylation status to the next generation. In Huhan-3, the numbers were 48.8% and 29.8%, respectively. Therefore, entrainment had greater effect on Huhan-3 than on II-32B. Sequence analysis revealed that the DML were widely distributed on all 12 rice chromosomes and that it mainly occurred on the gene’s promoter and exon region. Some genes with DML respond to environmental stresses. The inheritance of epigenetic variations induced by drought stress may provide a new way to develop drought resistant rice varieties.
In comparative proteomics studies, LC-MS/MS data is generally quantified using one or both of two measures: the spectral count, derived from the identification of MS/MS spectra, or some measure of ion abundance derived from the LC-MS data. Here we contrast the performance of these measures and show that ion abundance is the more sensitive. We also examine how the conclusions of a comparative analysis are influenced by the manner in which the LC-MS/MS data is ‘rolled up’ to the protein level, and show that divergent conclusions obtained using different rollups can be informative. Our analysis is based on two publicly available reference data sets, BIATECH-54 and CPTAC, which were developed for the purpose of assessing methods used in label-free differential proteomic studies. We find that the use of the ion abundance measure reveals properties of both data sets not readily apparent using the spectral count.
mass spectrometry; comparative proteomics; ion abundance; spectral count; ion competition
Although randomized studies have high internal validity, generalizability of the estimated causal effect from randomized clinical trials to real-world clinical or educational practice may be limited. We consider the implication of randomized assignment to treatment, as compared with choice of preferred treatment as it occurs in real-world conditions. Compliance, engagement, or motivation may be better with a preferred treatment, and this can complicate the generalizability of results from randomized trials. The doubly randomized preference trial (DRPT) is a hybrid randomized and nonrandomized design that allows for estimation of the causal effect of randomization versus treatment preference. In the DRPT, individuals are first randomized to either randomized assignment or choice assignment. Those in the randomized assignment group are then randomized to treatment or control, and those in the choice group receive their preference of treatment versus control. Using the potential outcomes framework, we apply the algebra of conditional independence to show how the DRPT can be used to derive an unbiased estimate of the causal effect of randomization versus preference for each of the treatment and comparison conditions. Also, we show how these results can be implemented using full matching on the propensity score. The methodology is illustrated with a DRPT of introductory psychology students who were randomized to randomized assignment or preference of mathematics versus vocabulary training. We found a small to moderate benefit of preference versus randomization with respect to the mathematics outcome for those who received mathematics training.
generalizability; causal inference; conditional independence; propensity score matching; treatment preference
Recent proteomic studies have identified proteins related to specific
phenotypes. In addition to marginal association analysis for individual
proteins, analyzing pathways (functionally related sets of proteins) may yield
additional valuable insights. Identifying pathways that differ between
phenotypes can be conceptualized as a multivariate hypothesis testing problem:
whether the mean vector μ of a
p-dimensional random vector X is
μ0. Proteins within the same biological
pathway may correlate with one another in a complicated way, and type I error
rates can be inflated if such correlations are incorrectly assumed to be absent.
The inflation tends to be more pronounced when the sample size is very small or
there is a large amount of missingness in the data, as is frequently the case in
proteomic discovery studies. To tackle these challenges, we propose a
regularized Hotelling’s T2
(RHT) statistic together with a non-parametric
testing procedure, which effectively controls the type I error rate and
maintains good power in the presence of complex correlation structures and
missing data patterns. We investigate asymptotic properties of the
RHT statistic under pertinent assumptions and compare
the test performance with four existing methods through simulation examples. We
apply the RHT test to a hormone therapy proteomics data
set, and identify several interesting biological pathways for which blood serum
concentrations changed following hormone therapy initiation.
proteomics; pathway analysis; regularization; Hotelling’s T2
Embryonic definitive endoderm (DE) generates the epithelial compartment of vital organs such as liver, pancreas, and intestine. However, purification of DE in mammals has not been achieved, limiting the molecular “definition” of endoderm, and hindering our understanding of DE development and attempts to produce endoderm from sources such as embryonic stem (ES) cells. Here, we describe purification of mouse DE using fluorescence-activated cell sorting (FACS) and mice harboring a transgene encoding enhanced green fluorescent protein (eGFP) inserted into the Sox17 locus, which is expressed in the embryonic endoderm. Comparison of patterns of signaling pathway activation in native mouse DE and endoderm-like cells generated from ES cells produced novel culture modifications that generated Sox17-eGFP+ progeny whose gene expression resembled DE more closely than achieved with standard methods. These studies also produced new FACS methods for purifying DE from nontransgenic mice and mouse ES cell cultures. Parallel studies of a new human SOX17-eGFP ES cell line allowed analysis of endoderm differentiation in vitro, leading to culture modifications that enhanced expression of an endoderm-like signature. This work should accelerate our understanding of mechanisms regulating DE development in mice and humans, and guide further use of ES cells for tissue replacement.
Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultra-high density array that tiles the promoters of 56 cell cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs--many with RT-PCR-validated periodic expression during the cell cycle, show altered expression in human cancers, and are regulated in expression by specific oncogenic stimuli, stem cell differentiation, or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53- dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell growth control.
Intestinal barrier dysfunction occurs in many intestinal diseases, in which proinflammatory cytokines play critical roles. However, researchers are still on the way to defining the underlying mechanisms and to evaluate therapeutic strategies for restoring intestinal barrier function. Berberine, a drug that has clinically been used to treat gastroenteritis and diarrhea for thousands of years, has been shown to protect barrier function in both endothelial and epithelial cells, but the mechanisms are completely unknown. In this study, we investigate the protective actions of berberine on barrier function and the underlying mechanisms in Caco-2 monolayers challenged with IFN-γ and TNF-α. Caco-2 monolayers were treated without or with simultaneous IFN-γ and TNF-α in the absence or presence of berberine. Both transepithelial electrical resistance (TER) and paracellular permeability were measured to evaluate barrier function. The expression and distribution of tight junction proteins ZO-1, occluding, and claudin-1 were respectively analyzed by immunoblot or immunofluorescence. The expressions of phosphorylated myosin light chain (pMLC), MLC kinase (MLCK) and hypoxia-inducible factor-1α (HIF-1α) were determined by immunoblot. The translocation of NF-κB p65 to nuclei was analyzed by immunofluorescence and immunoblot, respectively. The results showed that berberine significantly attenuated TER decrease and paracellular permeability increase in Caco-2 monolayers treated with IFN-γ and TNF-α. Berberine also dramatically alleviated IFN-γ and TNF-α-induced morphological alteration of tight junction proteins ZO-1, occluding, and claudin-1. The increase of both MLC phosphorylation and MLCK protein expression induced by IFN-γ and TNF-α was significantly inhibited by berberine treatment. Additionally, berberine suppressed the activation of HIF-1α, but not NF-κB. Taken together, it is suggested that berberine attenuates IFN-γ and TNF-α-induced intestinal epithelial barrier dysfunction by inhibiting the signaling pathway of MLCK-dependent MLC phosphorylation mediated by HIF-1α.
Whether the well-known metabolic switch AMP-activated protein kinase (AMPK) is involved in the insulin-sensitizing effect of calorie restriction (CR) is unclear. In this study, we investigated the role of AMPK in the insulin-sensitizing effect of CR in skeletal muscle. Wild-type (WT) and AMPK-α2−/− mice received ad libitum (AL) or CR (8 weeks at 60% of AL) feeding. CR increased the protein level of AMPK-α2 and phosphorylation of AMPK-α2. In WT and AMPK-α2−/− mice, CR induced comparable changes of body weight, fat pad weight, serum triglycerides, serum nonesterified fatty acids, and serum leptin levels. However, decreasing levels of fasting/fed insulin and fed glucose were observed in WT mice but not in AMPK-α2−/− mice. Moreover, CR-induced improvements of whole-body insulin sensitivity (evidenced by glucose tolerance test/insulin tolerance test assays) and glucose uptake in skeletal muscle tissues were abolished in AMPK-α2−/− mice. Furthermore, CR-induced activation of Akt-TBC1D1/TBC1D4 signaling, inhibition of mammalian target of rapamycin−S6K1−insulin receptor substrate-1 pathway, and induction of nicotinamide phosphoribosyltransferase−NAD+−sirtuin-1 cascade were remarkably impaired in AMPK-α2−/− mice. CR serum increased stability of AMPK-α2 protein via inhibiting the X chromosome-linked ubiquitin-specific protease 9–mediated ubiquitylation of AMPK-α2. Our results suggest that AMPK may be modulated by CR in a ubiquitylation-dependent manner and acts as a chief dictator for the insulin-sensitizing effects of CR in skeletal muscle.
Five new diketopiperazine derivatives, (3Z,6E)-1-N-methyl-3-benzylidene-6-(2S-methyl-3-hydroxypropylidene)piperazine-2,5-dione (1), (3Z,6E)-1-N-methyl-3-benzylidene-6-(2R-methyl-3-hydroxypropylidene)piperazine-2,5-dione (2), (3Z,6Z)-3-(4-hydroxybenzylidene)-6-isobutylidenepiperazine-2,5-dione (3), (3Z,6Z)-3-((1H-imidazol-5-yl)-methylene)-6-isobutylidenepiperazine-2,5-dione (4), and (3Z,6S)-3-benzylidene-6-(2S-but-2-yl)piperazine-2,5-dione (5), were isolated from the marine-derived actinomycete Streptomyces sp. FXJ7.328. The structures of 1–5 were determined by spectroscopic analysis, CD exciton chirality, the modified Mosher’s, Marfey’s and the C3 Marfey’s methods. Compound 3 showed modest antivirus activity against influenza A (H1N1) virus with an IC50 value of 41.5 ± 4.5 μM. In addition, compound 6 and 7 displayed potent anti-H1N1 activity with IC50 value of 28.9 ± 2.2 and 6.8 ± 1.5 μM, respectively. Due to the lack of corresponding data in the literature, the 13C NMR data of (3Z,6S)-3-benzylidene-6-isobutylpiperazine-2,5-dione (6) were also reported here for the first time.
Streptomyces; diketopiperazine derivatives; antivirus activity; H1N1
In oral squamous cell carcinoma (OSCC), metastasis to lymph nodes is associated with a 50% reduction in 5-year survival. To identify a metastatic gene set based on DNA copy number abnormalities (CNAs) of differentially expressed genes, we compared DNA and RNA of OSCC cells laser-microdissected from non-metastatic primary tumors (n = 17) with those from lymph node metastases (n = 20), using Affymetrix 250K Nsp single-nucleotide polymorphism (SNP) arrays and U133 Plus 2.0 arrays, respectively. With a false discovery rate (FDR)<5%, 1988 transcripts were found to be differentially expressed between primary and metastatic OSCC. Of these, 114 were found to have a significant correlation between DNA copy number and gene expression (FDR<0.01). Among these 114 correlated transcripts, the corresponding genomic regions of each of 95 transcripts had CNAs differences between primary and metastatic OSCC (FDR<0.01). Using an independent dataset of 133 patients, multivariable analysis showed that the OSCC–specific and overall mortality hazards ratio (HR) for patients carrying the 95-transcript signature were 4.75 (95% CI: 2.03–11.11) and 3.45 (95% CI: 1.84–6.50), respectively. To determine the degree by which these genes impact cell survival, we compared the growth of five OSCC cell lines before and after knockdown of over-amplified transcripts via a high-throughput siRNA–mediated screen. The expression-knockdown of 18 of the 26 genes tested showed a growth suppression ≥30% in at least one cell line (P<0.01). In particular, cell lines derived from late-stage OSCC were more sensitive to the knockdown of G3BP1 than cell lines derived from early-stage OSCC, and the growth suppression was likely caused by increase in apoptosis. Further investigation is warranted to examine the biological role of these genes in OSCC progression and their therapeutic potentials.
Neck lymph node metastasis is the most important prognostic factor in oral squamous cell carcinoma (OSCC). To identify genes associated with this critical step of OSCC progression, we compared DNA copy number aberrations and gene expression differences between tumor cells found in metastatic lymph nodes versus those in non-metastatic primary tumors. We identified 95 transcripts (87 genes) with metastasis-specific genome abnormalities and gene expression. Tested in an independent cohort of 133 OSCC patients, the 95 gene signature was an independent risk factor of disease-specific and overall death, suggesting a disease progression phenotype. We knocked down the expression of over-amplified genes in five OSCC cell lines. Knockdown of 18 of the 26 tested genes suppressed the cell growth in at least one cell line. Interestingly, cell lines derived from late-stage OSCC were more sensitive to the knockdown of G3BP1 than cell lines derived from early-stage OSCC. The knockdown of G3BP1 increased programmed cell death in the p53-mutant but not wild-type OSCC cell lines. Taken together, we demonstrate that CNA–associated transcripts differentially expressed in carcinoma cells with an aggressive phenotype (i.e., metastatic to lymph nodes) can be biomarkers with both prognostic information and functional relevance. Moreover, results suggest that G3BP1 is a potential therapeutic target against late-stage p53-negative OSCC.
isoAsp-Gly-Arg (isoDGR) is a derivative of the Asn-Gly-Arg (NGR) motif, which is used as a targeted delivery tool to aminopeptidase N (CD13) positive cells. Recent studies have shown that cyclic isoDGR (CisoDGRC) has a more efficient affinity with αvβ3, a type of integrin that overexpresses in tumor cells. Antimicrobial peptides (AMPs) are an efficient antitumor peptide that specifically kills tumor cells. In the present study, we designed antimicrobial peptides containing the CisoDGRC motif (CDAK) and assessed its antitumor activity for CD13−/αvβ3+ breast cancer cells (MCF-7 and MDA-MB-231) in vitro and in vivo.
In vitro: We assessed the cytotoxicity of CDAK for MCF-7 and MDA-MB-231 breast cancer cells, the human umbilical vein endothelial cell (HUVEC), and human foreskin fibroblasts (HFF). We performed an apoptosis assay using Annexin-V/PI, DNA ladder, mitochondrial membrane potential, and Caspase-3 and Bcl-2. The effect on cell cycles and affinity with cell were tested using flow cytometry and fluorescent microscopy and the effect on invasion was analyzed using an invasion assay. CDAK was injected intravenously into tumor-bearing athymic nude mice in vivo experiment.
CDAK showed cytotoxic activity in MCF-7 and MDA-MB-231 cells, whereas HUVEC and HFF were less sensitive to the peptides. CDAK induced apoptosis, reduced mitochondrial membrane potential, promoted Caspase-3, and inhibited Bcl-2 expression in the two breast cancer cell lines. In addition, CDAK inhibited proliferation of cancer cell through S phase arrest, and own selective affinity with MCF-7 and MDA-MB-231cells, inhibited the invasion of MDA-MB-231 cells. In vivo, CDAK significant inhibited the progression of the tumor and the generation of neovascularization.
Antimicrobial peptides containing the CisoDGRC (CDAK) motif could efficiently exhibit the antitumor activity for CD13−/αvβ3+ breast cancer cells.
Exome sequencing constitutes an important technology for the study of human hereditary diseases and cancer. However, the ability of this approach to identify copy number alterations in primary tumor samples has not been fully addressed. Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv. Using data from 86 paired normal and primary tumor samples, we identified losses and gains of complete chromosomes or large genomic regions, as well as smaller regions affecting a minimum of one gene. Comparison with high-resolution comparative genomic hybridization (CGH) arrays revealed a high sensitivity and a low number of false positives in the copy number estimation between both approaches. We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays. Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.
This study was to investigate the effect of nicotine on insulin sensitivity and explore the underlying mechanisms. Treatment of Sprague-Dawley rats with nicotine (3 mg/kg/day) for 6 weeks reduced 43% body weight gain and 65% blood insulin level, but had no effect on blood glucose level. Both insulin tolerance test and glucose tolerance test demonstrated that nicotine treatment enhanced insulin sensitivity. Pretreatment of rats with hexamethonium (20 mg/kg/day) to antagonize peripheral nicotinic receptors except for α7 nicotinic acetylcholine receptor (α7-nAChR) had no effect on the insulin sensitizing effect of nicotine. However, the insulin sensitizing effect but not the bodyweight reducing effect of nicotine was abrogated in α7-nAChR knockout mice. Further, chronic treatment with PNU-282987 (0.53 mg/kg/day), a selective α7-nAChR agonist, significantly enhanced insulin sensitivity without apparently modifying bodyweight not only in normal mice but also in AMP-activated kinase-α2 knockout mice, an animal model of insulin resistance with no sign of inflammation. Moreover, PNU-282987 treatment enhanced phosphorylation of signal transducer and activator of transcription 3 (STAT3) in skeletal muscle, adipose tissue and liver in normal mice. PNU-282987 treatment also increased glucose uptake by 25% in C2C12 myotubes and this effect was total abrogated by STAT3 inhibitor, S3I-201. All together, these findings demonstrated that nicotine enhanced insulin sensitivity in animals with or without insulin resistance, at least in part via stimulating α7-nAChR-STAT3 pathway independent of inflammation. Our results contribute not only to the understanding of the pharmacological effects of nicotine, but also to the identifying of new therapeutic targets against insulin resistance.
The energy status of a cell plays a key role in its survival, and the exposure of eukaryotic cells to the hypoxia that accompanies the depletion of intracellular ATP triggers specific systemic adaptive responses. AMP-activated protein kinase (AMPK) has emerged as a key regulator of energy metabolism in the heart and plays a critical role in inducing these responses. However, the specific mechanism responsible for AMPK activation in cardiomyocytes at very early stages of hypoxia remain unclear. The goals of this study were to assess the relative contribution to AMPK activation of phosphorylation by AMPK kinase (AMPKK) and of positive allosterism due to AMP:ATP ratios in the early stages of hypoxia. Our results demonstrated that, compared with normoxic controls, neither intracellular AMP concentrations nor AMP:ATP ratios significantly increased within 1h of hypoxia onset. In contrast, a SAMS peptide phosphorylation assay and an immunoblot analysis revealed significant increases in both AMPK activity and ACC phosphorylation within 5min of hypoxic treatment. Furthermore, exposure of cardiomyocytes to hypoxia significantly increased AMPK phosphorylation within 5min, by 3- to 4-fold compared with controls (P<0.01), while overall levels of AMPKα protein did not differ between aerobic and anoxic cardiomyocytes. We also observed increased AMPKK activity in anoxic cardiomyocytes, through use of an α312 substrate. Taken together, our findings demonstrate that in the early stage of hypoxia in cardiomyocytes, increases in AMPK activity occur prior to and independently of increases in AMP concentration or in the AMP:ATP ratio. Instead, under these circumstances, AMPK is primarily activated by phosphorylation of the conserved Thr-172 residue in its activation loop by its upstream kinase AMPKK.
Cardiomyocytes; hypoxia; AMPK; AMP; AMPK kinase
Oral and oropharyngeal squamous cell carcinomas (OSCC) are among the most common cancers worldwide, with approximately 60% 5-yr survival rate. To identify potential markers for disease progression, we used Affymetrix U133 plus 2.0 arrays to examine the gene expression profiles of 167 primary tumor samples from OSCC patients, 58 uninvolved oral mucosae from OSCC patients and 45 normal oral mucosae from patients without oral cancer, all enrolled at one of the three University of Washington-affiliated medical centers between 2003 to 2008. We found 2,596 probe sets differentially expressed between 167 tumor samples and 45 normal samples. Among 2,596 probe sets, 71 were significantly and consistently up- or down-regulated in the comparison between normal samples and uninvolved oral samples and between uninvolved oral samples and tumor samples. Cox regression analyses showed that 20 of the 71 probe sets were significantly associated with progression-free survival. The risk score for each patient was calculated from coefficients of a Cox model incorporating these 20 probe sets. The hazard ratio (HR) associated with each unit change in the risk score adjusting for age, gender, tumor stage, and high-risk HPV status was 2.7 (95% CI: 2.0–3.8, p = 8.8E-10). The risk scores in an independent dataset of 74 OSCC patients from the MD Anderson Cancer Center was also significantly associated with progression-free survival independent of age, gender, and tumor stage (HR 1.6, 95% CI: 1.1–2.2, p = 0.008). Gene Set Enrichment Analysis showed that the most prominent biological pathway represented by the 71 probe sets was the Integrin cell surface interactions pathway. In conclusion, we identified 71 probe sets in which dysregulation occurred in both uninvolved oral mucosal and cancer samples. Dysregulation of 20 of the 71 probe sets was associated with progression-free survival and was validated in an independent dataset.
Recent advances in tissue microarray technology have allowed immunohistochemistry to become a powerful medium-to-high throughput analysis tool, particularly for the validation of diagnostic and prognostic biomarkers. However, as study size grows, the manual evaluation of these assays becomes a prohibitive limitation; it vastly reduces throughput and greatly increases variability and expense. We propose an algorithm—Tissue Array Co-Occurrence Matrix Analysis (TACOMA)—for quantifying cellular phenotypes based on textural regularity summarized by local inter-pixel relationships. The algorithm can be easily trained for any staining pattern, is absent of sensitive tuning parameters and has the ability to report salient pixels in an image that contribute to its score. Pathologists’ input via informative training patches is an important aspect of the algorithm that allows the training for any specific marker or cell type. With co-training, the error rate of TACOMA can be reduced substantially for a very small training sample (e.g., with size 30). We give theoretical insights into the success of co-training via thinning of the feature set in a high dimensional setting when there is “sufficient” redundancy among the features. TACOMA is flexible, transparent and provides a scoring process that can be evaluated with clarity and confidence. In a study based on an estrogen receptor (ER) marker, we show that TACOMA is comparable to, or outperforms, pathologists’ performance in terms of accuracy and repeatability.
The structural maintenance of chromosome 1 (Smc1) protein is a member of the highly conserved cohesin complex and is involved in sister chromatid cohesion. In response to ionizing radiation, Smc1 is phosphorylated at two sites, Ser-957 and Ser-966, and these phosphorylation events are dependent on the ATM protein kinase. In this study, we describe the generation of two novel ELISAs for quantifying phospho-Smc1Ser-957 and phospho-Smc1Ser-966. Using these novel assays, we quantify the kinetic and biodosimetric responses of human cells of hematological origin, including immortalized cells, as well as both quiescent and cycling primary human PBMC. Additionally, we demonstrate a robust in vivo response for phospho-Smc1Ser-957 and phospho-Smc1Ser-966 in lymphocytes of human patients after therapeutic exposure to ionizing radiation, including total-body irradiation, partial-body irradiation, and internal exposure to 131I. These assays are useful for quantifying the DNA damage response in experimental systems and potentially for the identification of individuals exposed to radiation after a radiological incident.
DNA double-strand breaks (DSBs) are among the most lethal lesions associated with genome stability, which, when destabilized, predisposes organs to cancers. DSBs are primarily fixed either with little fidelity by non-homologous end joining (NHEJ) repair or with high fidelity by homology-directed repair (HDR). The phosphorylated form of H2AX on serine 139 (γ-H2AX) is a marker of DSBs. In this study, we explored if the protein phosphatase PP6 is involved in DSB repair by depletion of its expression in human cancer cell lines, and determined PP6 expression in human breast cancer tissues by immunohistochemistry staining. We found that bacterially produced PP6c (the catalytic subunit of PP6)-containing heterotrimeric combinations exhibit phosphatase activity against γ-H2AX in the in vitro phosphatase assays. Depletion of PP6c or PP6R2 led to persistent high levels of γ-H2AX after DNA damage and a defective HDR. Chromatin immunoprecipitation assays demonstrated that PP6c was recruited to the region adjacent to the DSB sites. Expression of PP6c, PP6R2 and PP6R3 in human breast tumors was significantly lower than those in benign breast diseases. Taken together, our results suggest that γ-H2AX is a physiological substrate of PP6 and PP6 is required for HDR and its expression may harbor a protective role during the development of breast cancer.
protein phosphatase; PP6; γ-H2AX; DNA double-strand break; homology-directed repair
Severe burn injury results in the loss of intestinal barrier function, however, the underlying mechanism remains unclear. Myosin light chain (MLC) phosphorylation mediated by MLC kinase (MLCK) is critical to the pathophysiological regulation of intestinal barrier function. We hypothesized that the MLCK-dependent MLC phosphorylation mediates the regulation of intestinal barrier function following burn injury, and that MLCK inhibition attenuates the burn-induced intestinal barrier disfunction.
Male balb/c mice were assigned randomly to either sham burn (control) or 30% total body surface area (TBSA) full thickness burn without or with intraperitoneal injection of ML-9 (2 mg/kg), an MLCK inhibitor. In vivo intestinal permeability to fluorescein isothiocyanate (FITC)-dextran was measured. Intestinal mucosa injury was assessed histologically. Tight junction proteins ZO-1, occludin and claudin-1 was analyzed by immunofluorescent assay. Expression of MLCK and phosphorylated MLC in ileal mucosa was assessed by Western blot. Intestinal permeability was increased significantly after burn injury, which was accompanied by mucosa injury, tight junction protein alterations, and increase of both MLCK and MLC phosphorylation. Treatment with ML-9 attenuated the burn-caused increase of intestinal permeability, mucosa injury, tight junction protein alterations, and decreased MLC phosphorylation, but not MLCK expression.
The MLCK-dependent MLC phosphorylation mediates intestinal epithelial barrier dysfunction after severe burn injury. It is suggested that MLCK-dependent MLC phosphorylation may be a critical target for the therapeutic treatment of intestinal epithelial barrier disruption after severe burn injury.
DNA amplifications, leading to the overexpression of oncogenes, are a cardinal feature of lung cancer and directly contribute to its pathogenesis. To uncover novel such alterations, we performed an array-based comparative genomic hybridization survey of 128 non-small cell lung cancer cell lines and tumors. Prominent among our findings, we identified recurrent high-level amplification at cytoband 22q11.21 in 3% of lung cancer specimens, with another 11% of specimens exhibiting low-level gain spanning that locus. The 22q11.21 amplicon core contained eight named genes, only four of which were overexpressed (by transcript profiling) when amplified. Among these, CRKL encodes an adaptor protein functioning in signal transduction, best known as a substrate of the BCR-ABL kinase in chronic myelogenous leukemia. RNA interference-mediated knockdown of CRKL in lung cancer cell lines with (but not without) amplification led to significantly decreased cell proliferation, cell-cycle progression, cell survival, and cell motility and invasion. In addition, overexpression of CRKL in immortalized human bronchial epithelial cells led to EGF-independent cell growth. Our findings indicate that amplification and resultant overexpression of CRKL contributes to diverse oncogenic phenotypes in lung cancer, with implications for targeted therapy, and highlighting a role of adapter proteins as primary genetic drivers of tumorigenesis.
CRKL; lung cancer; DNA amplification; genomic profiling; adapter protein
We generated extensive transcriptional and proteomic profiles from a Her2-driven mouse model of breast cancer that closely recapitulates human breast cancer. This report makes these data publicly available in raw and processed forms, as a resource to the community. Importantly, we previously made biospecimens from this same mouse model freely available through a sample repository, so researchers can obtain samples to test biological hypotheses without the need of breeding animals and collecting biospecimens.
Twelve datasets are available, encompassing 841 LC-MS/MS experiments (plasma and tissues) and 255 microarray analyses of multiple tissues (thymus, spleen, liver, blood cells, and breast). Cases and controls were rigorously paired to avoid bias.
In total, 18,880 unique peptides were identified (PeptideProphet peptide error rate ≤1%), with 3884 and 1659 non-redundant protein groups identified in plasma and tissue datasets, respectively. Sixty-one of these protein groups overlapped between cancer plasma and cancer tissue.
Conclusions and clinical relevance
These data are of use for advancing our understanding of cancer biology, for software and quality control tool development, investigations of analytical variation in MS/MS data, and selection of proteotypic peptides for MRM-MS. The availability of these datasets will contribute positively to clinical proteomics.
Breast cancer; Her2; mouse; proteome; transcriptome
In the title compound, [Cd(C2H8N2)3](GeF6), the CdII atom, lying on a 32 symmetry site, is coordinated by six N atoms from three ethylenediamine (en) ligands in a distorted octahedral geometry. The Ge atom also lies on a 32 symmetry site and is coordinated by six F atoms. The en ligand has a twofold rotation axis passing through the mid-point of the C—C bond. The F atom is disordered over two sites with equal occupancy factors. In the crystal, the [Cd(en)3]2+ cations and [GeF6]2− anions are connected through N—H⋯F hydrogen bonds, forming a three-dimensional supramolecular network.
Recent evidence suggests that the observed clinical distinctions between lung tumors in smokers and never smokers (NS) extend beyond specific gene mutations, such as EGFR, EML4-ALK, and KRAS, some of which have been translated into targeted therapies. However, the molecular alterations identified thus far cannot explain all of the clinical and biological disparities observed in lung tumors of NS and smokers. To this end, we performed an unbiased genome-wide, comparative study to identify novel genomic aberrations that differ between smokers and NS.
High resolution whole genome DNA copy number profiling of 69 lung adenocarcinomas from smokers (n = 39) and NS (n = 30) revealed both global and regional disparities in the tumor genomes of these two groups. We found that NS lung tumors had a greater proportion of their genomes altered than those of smokers. Moreover, copy number gains on chromosomes 5q, 7p, and 16p occurred more frequently in NS. We validated our findings in two independently generated public datasets. Our findings provide a novel line of evidence distinguishing genetic differences between smoker and NS lung tumors, namely, that the extent of segmental genomic alterations is greater in NS tumors. Collectively, our findings provide evidence that these lung tumors are globally and genetically different, which implies they are likely driven by distinct molecular mechanisms.
Genomic instability, the propensity of aberrations in chromosomes, plays a critical role in the development of many diseases. High throughput genotyping experiments have been performed to study genomic instability in diseases. The output of such experiments can be summarized as high dimensional binary vectors, where each binary variable records aberration status at one marker locus. It is of keen interest to understand how aberrations may interact with each other, as it provides insight into the process of the disease development. In this paper, we propose a novel method, LogitNet, to infer such interactions among these aberration events. The method is based on penalized logistic regression with an extension to account for spatial correlation in the genomic instability data. We conduct extensive simulation studies and show that the proposed method performs well in the situations considered. Finally, we illustrate the method using genomic instability data from breast cancer samples.
Conditional Dependence; Graphical Model; Lasso; Loss-of-Heterozygosity; Regularized Logistic Regression