Ponatinib is a novel tyrosine kinase inhibitor with potent activity against BCR-ABL with mutations including T315I, and also against fms-like tyrosine kinase 3 (FLT3). We tested interactions between ponatinib at pharmacologically relevant concentrations of 50 to 200 nM and the multidrug resistance-associated ATP-binding cassette (ABC) proteins ABCB1, ABCC1 and ABCG2. Ponatinib enhanced uptake of substrates of ABCG2 and ABCB1, but not ABCC1, in cells overexpressing these proteins, with a greater effect on ABCG2 than on ABCB1. Ponatinib potently inhibited [125I]-IAAP binding to ABCG2 and ABCB1, indicating binding to their drug substrate sites, with IC50s of 0.04 μM and 0.63 μM, respectively. Ponatinib stimulated ABCG2 ATPase activity in a concentration-dependent manner and stimulated ABCB1 ATPase activity at low concentrations, consistent with it being a substrate of both proteins at pharmacologically relevant concentrations. The ponatinib IC50s of BCR-ABL-expressing K562 cells transfected with ABCB1 and ABCG2 were approximately the same as and 2-fold higher than that of K562, respectively, consistent with ponatinib being a substrate of both proteins, but inhibiting its own transport, and resistance was also attenuated to a small degree by ponatinib-induced downregulation of ABCB1 and ABCG2 cell surface expression on resistant K562 cells. Ponatinib at pharmacologically relevant concentrations produced synergistic cytotoxicity with ABCB1 and ABCG2 substrate chemotherapy drugs and enhanced apoptosis induced by these drugs, including daunorubicin, mitoxantrone, topotecan and flavopiridol, in cells overexpressing these transport proteins. Combinations of ponatinib and chemotherapy drugs warrant further testing.
Ponatinib; ABCG2; ABCB1; multidrug resistance; leukemia
A Fe(acac)3-catalyzed decarboxylative coupling of 2-(aryl)vinyl carboxylic acids with cycloalkanes was developed by using DTBP as an oxidant through a radical process. This reaction tolerates a wide range of substrates, and products are obtained in good to excellent yields (71–95%). The reaction also shows excellent stereoselectivity, and only trans-isomers are obtained.
alkenylation; cycloalkanes; decarboxylative; Fe(acac)3; free radical; sp3 C–H bonds
Eosinophilic dermatosis of hematologic malignancy is a multifaceted dermatosis with a wide morphological spectrum, presenting as pruritic, erythematous, papular and occasionally vesicular, urticarial, nodular eruptions. Histopathologically eosinophil infiltration in the super and deep dermis was found. We reported a case of eosinophilic dermatosis of hematologic malignancy presented as urticarial and vesicular lesions in a patient with chronic lymphocytic leukemia. A skin biopsy revealed a prominent subepidermal blister and a diffuse infiltrate of eosinophils with flame figures in the dermis and subcutaneous tissue. Although flame figures associated with eosinophilic dermatosis of hematologic malignancy is rarely reported, we believe that it would not seem unusual to find them in this skin disease. Eosinophilic cellulitis, which share clinical and histological features with eosinophilic dermatosis of hematologic malignancy, has also been described as showing an association with hematoproliferative diseases. In order to clearly describe eosinophilic dermatosis in patients with hematologic malignancies, the terminology eosinophilic dermatosis of hematologic malignancy, instead of eosinophilic cellulitis, would be a more suitable term in patients with eosinophilic dermatosis.
Eosinophilic dermatosis; hematologic malignancy; flame figures; chronic lymphocytic leukemia
Besides androgens, estrogens produced in Leydig cells are also crucial for mammalian germ cell differentiation. Transforming growth factor-β1 (TGF-β1) is now known to have multiple effects on regulation of Leydig cell function. The objective of the present study is to determine whether TGF-β1 regulates estradiol (E2) synthesis in adult rat Leydig cells and then to assess the impact of TGF-β1 on Cx43-based gap junctional intercellular communication (GJIC) between Leydig cells.
Primary cultured Leydig cells were incubated in the presence of recombinant TGF-β1 and the production of E2 as well as testosterone (T) were measured by RIA. The activity of P450arom was addressed by the tritiated water release assay and the expression of Cyp19 gene was evaluated by Western blotting and real time RT-PCR. The expression of Cx43 and GJIC were investigated with immunofluorescence and fluorescence recovery after photo-bleaching (FRAP), respectively. Results from this study show that TGF-β1 down-regulates the level of E2 secretion and the activity of P450arom in a dose-dependent manner in adult Leydig cells. In addition, the expression of Cx43 and GJIC was closely related to the regulation of E2 and TGF-β1, and E2 treatment in turn restored the inhibition of TGF-β1 on GJIC.
Our results indicate, for the first time in adult rat Leydig cells, that TGF-β1 suppresses P450arom activity, as well as the expression of the Cyp19 gene, and that depression of E2 secretion leads to down-regulation of Cx43-based GJIC between Leydig cells.
Vascular cell adhesion molecule-1 (VCAM-1), an adhesion molecule, is involved in the progression of glomerular and tubulointerstitial injury. Neutrophil gelatinase-associated lipocalin (NGAL), a member of the lipocalin superfamily, has been shown to rise in both acute and chronic kidney damage. Both VCAM-1 and NGAL have been found at high levels in the urine of patients with active lupus nephritis. We investigated both as potential biomarkers for lupus nephritis.
VCAM-1 and NGAL were measured by ELISA during 1 to 8 clinic visits in 107 patients with systemic lupus erythematosus (SLE; 91% women, 51% black, 36% white, 4% Asian, 4% Hispanic, and 5% others) for a total of 190 visits. Patients’ mean age was 41 years. We analyzed the relationship between these potential urine biomarkers and the urine protein/creatinine ratio (urine Pr/Cr), the Systemic Lupus International Collaborating Clinics (SLICC) renal activity score, SLE Disease Activity Index renal descriptors, and other clinical variables.
VCAM-1 levels were strongly associated with the physician’s global estimate of disease activity (p = 0.0002), the renal visual analog scale (p < 0.0001), the urine Pr/Cr (p < 0.0001), and SLICC renal activity score (p < 0.0001). VCAM-1 levels were also associated with a urine Pr/Cr ≥ 0.5 (p < 0.0001). NGAL was not associated with any measure of disease activity or with lupus serologies.
Urine VCAM-1 had a strong association with measures of disease activity, including multiple renal activity descriptors. In contrast to previous SLE studies, NGAL failed to show any association with lupus nephritis.
SYSTEMIC LUPUS ERYTHEMATOSUS; VASCULAR CELL ADHESION MOLECULE; NEUTROPHIL GELATINASE-ASSOCIATED LIPOCALIN; LIPOCALIN; LUPUS NEPHRITIS
Male patients with systemic lupus erythematosus (SLE) are thought to be similar to female patients with SLE, but key clinical characteristics may differ. Comparisons were made between male and female patients with SLE in the Hopkins Lupus Cohort.
A total of 1979 patients in the Hopkins Lupus Cohort were included in the analysis.
The cohort consisted of 157 men (66.2% white, 33.8% African American) and 1822 women (59.8% white, 40.2% African American). The mean followup was 6.02 years (range 0–23.73). Men were more likely than women to have disability, hypertension, thrombosis, and renal, hematological, and serological manifestations. Men were more likely to be diagnosed at an older age and to have a lower education level. Women were more likely to have malar rash, photosensitivity, oral ulcers, alopecia, Raynaud’s phenomenon, or arthralgia. Men were more likely than women to have experienced end organ damage including neuropsychiatric, renal, cardiovascular, peripheral vascular disease, and myocardial infarction, and to have died. In general, differences between males and females were more numerous and striking in whites, especially with respect to lupus nephritis, abnormal serologies, and thrombosis.
Our study suggests that there are major clinical differences between male and female patients with SLE. Differences between male and female patients also depend on ethnicity. Future SLE studies will need to consider both ethnicity and gender to understand these differences.
SYSTEMIC LUPUS ERYTHEMATOSUS; GENDER; MALE LUPUS
Currently, 3 antiphospholipid assays are widely used clinically [lupus anticoagulant (LAC), anticardiolipin (aCL), and anti-β2-glycoprotein I (anti-β2-GPI)]. LAC is the most specific assay, conferring the highest risk of thrombosis and pregnancy loss, but it cannot be validly performed in an anticoagulated patient. We investigated the usefulness of antiphosphatidyl-serine/prothrombin (anti-PS/PT) and its association with thrombosis. Anti-PS/PT is strongly associated with the presence of LAC. We also studied the association of IgA antiphospholipid isotypes and specific domains of β2-GPI with thrombosis in systemic lupus erythematosus (SLE).
Stored samples from patients with SLE, with and without past thrombosis, were assayed for antibodies to the whole β2-GPI protein (IgG/IgM/IgA), to β2-GPI domain 1 (IgG), to β2-GPI domain 4/5 (IgA), aCL (IgG/IgM/IgA), and anti-PS/PT (IgG, IgM, and IgG/M). LAC was detected using the dilute Russell’s viper venom time (dRVVT) with confirmatory testing.
Anti-PS/PT IgG and IgG/M and anti-β2-GPI IgG, IgM, and IgA were highly associated with a history of LAC by dRVVT (p < 0.0001). For all thrombosis, of the traditional ELISA assays, anti-β2-GPI IgA, IgG, and aCL IgA were most associated. Anti-PS/PT IgG and IgG/M had a similar magnitude of association to the traditional ELISA. For venous thrombosis, of the traditional ELISA, anti-β2-GPI (IgG and IgA), anti-PS/PT (IgG and IgG/M), and aCL IgA were associated. Again, anti-PS/PT (IgG and IgG/M) had the same magnitude of association as the traditional ELISA. For stroke, significant association was seen with anti-β2-GPI IgA D4/5.
In anticoagulated patients, where LAC testing is not valid, anti-PS/PT, either IgG or IgG/IgM, might serve as useful alternative tests to predict a higher risk of thrombosis. Anti-PS/PT antibodies were associated with all thrombosis and with venous thrombosis. IgA isotypes in secondary antiphospholipid syndrome are associated with thrombosis. Anti-β2-glycoprotein domain 1 was not shown to be associated with thrombosis in SLE.
ANTI-PHOSPHATIDYLSERINE/PROTHROMBIN; ANTI-β2-GLYCOPROTEIN I; DOMAIN 4/5 IgA; ANTICARDIOLIPIN
To determine whether there is any seasonal variation in the activity of systemic lupus erythematosus (SLE) overall and by individual organs.
The study group comprised 2102 patients with SLE who were followed in a prospective longitudinal cohort study. In this cohort, 92.3% of the patients were women. The mean ± SD age of the patients was 47.9 ± 13.9 years, 56.3% were white, 37.1% were African American, and 3.1% were Asian. Global disease activity was recorded by the Safety of Estrogens in Lupus Erythematosus National Assessment – Systemic Lupus Erythematosus Disease Activity Index (SELENA-SLEDAI) and the physician's global assessment. Activity of each organ was also recorded using SLEDAI terms and a visual analog scale (VAS; 0 to 3).
There was significant seasonal variation in photosensitive rash (p < 0.0001), which was more frequent in the spring and summer months (p < 0.0001). There was significantly more arthritis activity in spring and summer, as measured by both SELENA-SLEDAI (p = 0.0057) and the joint VAS (p = 0.0047). A decrease in renal activity was found in the summer months compared to the rest of the year (p = 0.0397). Serositis recorded by VAS had higher activity from August to October (p = 0.0392). Anti-dsDNA levels were significantly higher during October and November (p < 0.0001). There was significant seasonal variation in antiphospholipid antibody levels (p < 0.0001) and lupus anticoagulant (p = 0.0003). We found a significant variation in activity through the year in global disease activity as measured by SELENA-SLEDAI (p = 0.048).
In the Hopkins Lupus Cohort, skin and joint activity is increased during the spring and summer, but other organs have different patterns. These seasonal variations likely reflect environmental factors that influence disease activity, including ultraviolet light and infections.
SYSTEMIC LUPUS ERYTHEMATOSUS; DISEASE ACTIVITY; SEASONAL VARIATION
Accelerated atherosclerosis is a major cause of death in systemic lupus erythematosus (SLE), yet little is known about the effect of socioeconomic status. We investigated whether education or income levels are associated with cardiovascular risk factors and outcomes in SLE.
Our study involved a longitudinal cohort of all patients with SLE enrolled in the Hopkins Lupus Cohort from 1987 through September 2011. Socioeconomic status was measured by education level (≥ 12 years or < 12) and income tertiles (> $60,000, $25,000–$60,000, or < $25,000).
A total of 1752 patients with SLE were followed prospectively every 3 months. There were 1052 whites and 700 African Americans. Current smoking, obesity, hypertension, and diabetes mellitus were more common in African Americans (p < 0.01 for all), but there was no statistical difference in the frequency of myocardial infarction or stroke. In multivariate analyses stratified by ethnicity, low income was strongly associated with most traditional cardiovascular risk factors in whites, but only with smoking and diabetes in African Americans. In whites, low income increased the risk of both myocardial infarction (OR 3.24, 95% CI 1.41–7.45, p = 0.006) and stroke (OR 2.85, 95% CI 1.56–5.21, p = 0.001); in African Americans, these relationships were not seen. Low education, in contrast, was associated with smoking in both ethnic groups.
Low income, not low education, is the socioeconomic status variable associated with cardiovascular risk factors and events. This association is most clearly demonstrable in whites.
SYSTEMIC LUPUS ERYTHEMATOSUS; SOCIOECONOMIC STATUS; EDUCATION INCOME; CARDIOVASCULAR DISEASE; MYOCARDIAL INFARCTION
A database was constructed consisting of 45,923 Salmonella pulsed-field gel electrophoresis (PFGE) patterns. The patterns, randomly selected from all submissions to CDC PulseNet during 2005 to 2010, included the 20 most frequent serotypes and 12 less frequent serotypes. Meta-analysis was applied to all of the PFGE patterns in the database. In the range of 20 to 1100 kb, serotype Enteritidis averaged the fewest bands at 12 bands and Paratyphi A the most with 19, with most serotypes in the 13−15 range among the 32 serptypes. The 10 most frequent bands for each of the 32 serotypes were sorted and distinguished, and the results were in concordance with those from distance matrix and two-way hierarchical cluster analyses of the patterns in the database. The hierarchical cluster analysis divided the 32 serotypes into three major groups according to dissimilarity measures, and revealed for the first time the similarities among the PFGE patterns of serotype Saintpaul to serotypes Typhimurium, Typhimurium var. 5-, and I 4,,12:i:-; of serotype Hadar to serotype Infantis; and of serotype Muenchen to serotype Newport. The results of the meta-analysis indicated that the pattern similarities/dissimilarities determined the serotype discrimination of PFGE method, and that the possible PFGE markers may have utility for serotype identification. The presence of distinct, serotype specific patterns may provide useful information to aid in the distribution of serotypes in the population and potentially reduce the need for laborious analyses, such as traditional serotyping.
Aim: To construct short hairpin RNAs (shRNAs) and miR30-based shRNAs against heparanase (HPSE) to compare their safety and their effects on HPSE down-modulation in vitro and in vivo to develop a more ideal therapeutic RNA interference (RNAi) vector targeting HPSE.
Methods: First, we constructed shRNAs and miR30-based shRNAs against HPSE (HPSE-shRNAs and HPSE-miRNAs) and packed them into lentiviral vectors. Next, we observed the effects of the shRNAs on knockdown for HPSE expression, adhesion, migration and invasion abilities in human malignant melanoma A375 cells in vitro. Furthermore, we compared the effects of the shRNAs on melanoma growth, metastasis and safety in xenograft models.
Results: Our data showed that these artificial miRNAs targeting HPSE could be effective RNAi agents mediated by Pol II promoters in vitro and in vivo, although these miRNAs were not more potent than the HPSE-shRNAs. It was noted that obvious lung injuries, rarely revealed previously, as well as hepatotoxicity could be caused by lentivirus-mediated shRNAs (LV shRNAs) rather than lentivirus-mediated miRNAs (LV miRNAs) in vivo. Furthermore, enhanced expression of pro-inflammatory cytokines IL-6 and TGF-β1 and endogenous mmu-miR-21a-5p were detected in lung tissues of shRNAs groups, whereas the expression of mmu-let-7a-5p, mmu-let-7b-5p and mmu-let-7c-5p were down-regulated.
Conclusion: These findings suggest that artificial miRNAs display an improved safety profile of lowered lung injury or hepatotoxicity relative to shRNAs in vivo. The mechanism of lung injuries caused by shRNAs may be correlated with changes of endogenous miRNAs in the lung. Our data here increase the flexibility of a miRNA-based RNAi system for functional genomic and gene therapy applications.
RNA interference; microRNA(miRNA); heparanase; metastasis; safety
Amyloidosis cutis dyschromica is a rarely documented variant of cutaneous amyloidosis. To date, only 26 cases have been reported.
The purpose of this study was to improve the clinical and histopathological data for this variant of amyloidosis and to highlight the immunohistochemical features of the disease. The published cases were also reviewed.
We performed a retrospective review of patients with amyloidosis cutis dyschromica in a single centre. The clinical, histopathological and immunohistochemical features were documented and analysed.
We described 10 cases of amyloidosis cutis dyschromica. Six of them were female. Five patients were from the same family, and the other 5 were sporadic. The distinguishing features of the clinical presentation included generalised mottled hyper- and hypopigmented macules, which were asymptomatic or mild pruritic. The typical onset of the lesions occurred in childhood (n = 7) and occasionally after puberty (n = 3). No evidence of systemic amyloidosis deposition was observed in these cases of amyloidosis cutis dyschromica. Amyloid deposits were observed in the papillary dermis and were positive for the Congo red stain. An immunohistochemical study showed that the amyloid expresses cytokeratins CK34βE12 and CK5/6.
We described the largest series of amyloidosis cutis dyschromica to date and reviewed the published patients. This rare disease is featured by generalised mottled hyper- and hypopigmented lesions, and it is a rare variant of primary cutaneous amyloidosis without evidence of systemic amyloid deposition. Positive staining for the cytokeratins CK34βE12 and CK5/6 in amyloidosis cutis dyschromica suggests that the amyloid is derived from keratinocytes.
Amyloidosis cutis dyschromica; Amyloid; Pigmentation disorder; Cytokeratin; Congo red; Hereditary disease
Dermatofibrosarcoma protuberans is a locally aggressive mesenchymal neoplasm. It usually presents as an indurated plaque that protrudes above the surface of the skin. Some patients have clinically persistent plaques that might be atrophic. The atrophic variant of dermatofibrosarcoma protuberans may be confused with some common skin diseases with atrophic appearance. We reported a 40-year-old woman who had a 10-year history of an atrophic dermatofibrosarcoma protuberans. Molecular analysis showed a fusion between COL1A1 exon 31 to exon 2 of PDGFB. The lesion was totally excised, with negative margins of the resection demonstrated by CD34 immunostaining. To our knowledge, this is the second case of atrophic dermatofibrosarcoma protuberans confirmed by detection of COL1A1-PDGFB fusion gene. This appears to be the first report of a fusion between COL1A1 exon 31 to exon 2 of PDGFB in atrophic dermatofibrosarcoma protuberans.
The virtual slides for this article can be found here:
Dermatofibrosarcoma protuberans; COL1A1-PDGFB; CD34; Atrophic; Sarcoma
Despite the role of aerobic glycolysis in cancer, recent studies highlight the importance of the mitochondria and biosynthetic pathways as well. PPARγ coactivator 1α (PGC1α) is a key transcriptional regulator of several metabolic pathways including oxidative metabolism and lipogenesis. Initial studies suggested that PGC1α expression is reduced in tumors compared to adjacent normal tissue. Paradoxically, other studies show that PGC1α is associated with cancer cell proliferation. Therefore the role of PGC1α in cancer and especially carcinogenesis is unclear. Using Pgc1α-/- and Pgc1α+/+ mice we show that loss of PGC1α protects mice from azoxymethane induced colon carcinogenesis. Similarly, diethylnitrosamine induced liver carcinogenesis is reduced in Pgc1α-/- mice compared to Pgc1α+/+ mice. Xenograft studies using gain and loss of PGC1α expression demonstrated that PGC1α also promotes tumor growth. Interestingly, while PGC1α induced oxidative phosphorylation and TCA cycle gene expression, we also observed an increase in the expression of two genes required for de novo fatty acid synthesis, ACC and FASN. In addition, SLC25A1 and ACLY, which are required for the conversion of glucose in to acetyl CoA for fatty acid synthesis, were also increased by PGC1α, thus linking the oxidative and lipogenic functions of PGC1α. Indeed, using 13C stable isotope tracer analysis we show that PGC1α increased de novo lipogenesis. Importantly, inhibition of fatty acid synthesis blunted these progrowth effects of PGC1α. In conclusion, these studies show for the first time that loss of PGC1α protects against carcinogenesis and that PGC1α coordinately regulates mitochondrial and fatty acid metabolism to promote tumor growth.
Cancer metabolism; Warburg Effect; oxidative metabolism; lipogenesis; transcriptional regulation
Drug repositioning offers an opportunity to revitalize the slowing drug discovery pipeline by finding new uses for currently existing drugs. Our hypothesis is that drugs sharing similar side effect profiles are likely to be effective for the same disease, and thus repositioning opportunities can be identified by finding drug pairs with similar side effects documented in U.S. Food and Drug Administration (FDA) approved drug labels. The safety information in the drug labels is usually obtained in the clinical trial and augmented with the observations in the post-market use of the drug. Therefore, our drug repositioning approach can take the advantage of more comprehensive safety information comparing with conventional de novo approach.
A probabilistic topic model was constructed based on the terms in the Medical Dictionary for Regulatory Activities (MedDRA) that appeared in the Boxed Warning, Warnings and Precautions, and Adverse Reactions sections of the labels of 870 drugs. Fifty-two unique topics, each containing a set of terms, were identified by using topic modeling. The resulting probabilistic topic associations were used to measure the distance (similarity) between drugs. The success of the proposed model was evaluated by comparing a drug and its nearest neighbor (i.e., a drug pair) for common indications found in the Indications and Usage Section of the drug labels.
Given a drug with more than three indications, the model yielded a 75% recall, meaning 75% of drug pairs shared one or more common indications. This is significantly higher than the 22% recall rate achieved by random selection. Additionally, the recall rate grows rapidly as the number of drug indications increases and reaches 84% for drugs with 11 indications. The analysis also demonstrated that 65 drugs with a Boxed Warning, which indicates significant risk of serious and possibly life-threatening adverse effects, might be replaced with safer alternatives that do not have a Boxed Warning. In addition, we identified two therapeutic groups of drugs (Musculo-skeletal system and Anti-infective for systemic use) where over 80% of the drugs have a potential replacement with high significance.
Topic modeling can be a powerful tool for the identification of repositioning opportunities by examining the adverse event terms in FDA approved drug labels. The proposed framework not only suggests drugs that can be repurposed, but also provides insight into the safety of repositioned drugs.
During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders’ quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low.
There is no consistent evidence of specific gene(s) or molecular pathways that contribute to the pathogenesis, therapeutic intervention or diagnosis of chronic fatigue syndrome (CFS). While multiple studies support a role for genetic variation in CFS, genome-wide efforts to identify associated loci remain unexplored. We employed a novel convergent functional genomics approach that incorporates the findings from single-nucleotide polymorphism (SNP) and mRNA expression studies to identify associations between CFS and novel candidate genes for further investigation.
We evaluated 116,204 SNPs in 40 CFS and 40 nonfatigued control subjects along with mRNA expression of 20,160 genes in a subset of these subjects (35 CFS subjects and 27 controls) derived from a population-based study.
Sixty-five SNPs were nominally associated with CFS (p < 0.001), and 165 genes were differentially expressed (≥4-fold; p ≤ 0.05) in peripheral blood mononuclear cells of CFS subjects. Two genes, glutamate receptor, ionotropic, kinase 2 (GRIK2) and neuronal PAS domain protein 2 (NPAS2), were identified by both SNP and gene expression analyses. Subjects with the G allele of rs2247215 (GRIK2) were more likely to have CFS (p = 0.0005), and CFS subjects showed decreased GRIK2 expression (10-fold; p = 0.015). Subjects with the T allele of rs356653 (NPAS2) were more likely to have CFS (p = 0.0007), and NPAS2 expression was increased (10-fold; p = 0.027) in those with CFS.
Using an integrated genomic strategy, this study suggests a possible role for genes involved in glutamatergic neurotransmission and circadian rhythm in CFS and supports further study of novel candidate genes in independent populations of CFS subjects.
Chronic fatigue syndrome; Genome-wide association; Gene expression; GRIK2; NPAS2; Glutamatergic neurotransmission; Circadian rhythm; Orexin signaling
To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open ‘data commoning’ culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared ‘Investigation-Study-Assay’ framework to support that vision.
Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity.
atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis.
atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.
Protein-protein interaction; Network analysis; Functional module; Disease biomarker; KEGG pathway analysis; Visualization tool; Genomics
A genetic association study is a complicated process that involves collecting phenotypic data, generating genotypic data, analyzing associations between genotypic and phenotypic data, and interpreting genetic biomarkers identified. SNPTrack is an integrated bioinformatics system developed by the US Food and Drug Administration (FDA) to support the review and analysis of pharmacogenetics data resulting from FDA research or submitted by sponsors. The system integrates data management, analysis, and interpretation in a single platform for genetic association studies. Specifically, it stores genotyping data and single-nucleotide polymorphism (SNP) annotations along with study design data in an Oracle database. It also integrates popular genetic analysis tools, such as PLINK and Haploview. SNPTrack provides genetic analysis capabilities and captures analysis results in its database as SNP lists that can be cross-linked for biological interpretation to gene/protein annotations, Gene Ontology, and pathway analysis data. With SNPTrack, users can do the entire stream of bioinformatics jobs for genetic association studies. SNPTrack is freely available to the public at http://www.fda.gov/ScienceResearch/BioinformaticsTools/SNPTrack/default.htm.
Ribonucleic acid interference (RNAi) based on microRNA (miRNA) context may provide an efficient and safe therapeutic knockdown effect and can be driven by ribonucleic acid polymerase II (RNAP II). In this study, we designed and synthesized miR155-based artificial miRNAs against heparanase (HPSE) constructed with BLOCK-iT™ Pol II miR RNAi Expression Vector Kit. The expression levels of HPSE declined significantly in both the mRNA and protein levels in HPSE-miRNA transfected melanoma cells that exhibited reduction of adhesion, migration, and invasion ability in vitro and in vivo. We also observed that HPSE miRNA could inhibit the expressions of chemokines of interleukin-8 (IL8) and chemokine (C-X-C motif) ligand 1 (CXCL1), at both the transcriptional and translational levels. Further study on its probable mechanism declared that down-regulation of IL8 and CXCL1 by HPSE-miRNA may be correlated with reduced growth-factor simulated mitogen-activated kinase (MAPK) phosphorylation including p38 MAPK, c-Jun N-terminal kinase (JNK) and extracellular-signal-regulated kinase (ERK) 1 and 2, which could be rescued by miRNA incompatible mutated HPSE cDNA. In conclusion, we demonstrated that artificial miRNAs against HPSE might serve as an alterative mean of therapy to low HPSE expression and to block the adhesion, invasion, and metastasis of melanoma cells. Furthermore, miRNA-based RNAi was also a powerful tool for gene function study.
The era of personalized medicine for cancer therapeutics has taken an important step forward in making accurate prognoses for individual patients with the adoption of high-throughput microarray technology. However, microarray technology in cancer diagnosis or prognosis has been primarily used for the statistical evaluation of patient populations, and thus excludes inter-individual variability and patient-specific predictions. Here we propose a metric called clinical confidence that serves as a measure of prognostic reliability to facilitate the shift from population-wide to personalized cancer prognosis using microarray-based predictive models. The performance of sample-based models predicted with different clinical confidences was evaluated and compared systematically using three large clinical datasets studying the following cancers: breast cancer, multiple myeloma, and neuroblastoma. Survival curves for patients, with different confidences, were also delineated. The results show that the clinical confidence metric separates patients with different prediction accuracies and survival times. Samples with high clinical confidence were likely to have accurate prognoses from predictive models. Moreover, patients with high clinical confidence would be expected to live for a notably longer or shorter time if their prognosis was good or grim based on the models, respectively. We conclude that clinical confidence could serve as a beneficial metric for personalized cancer prognosis prediction utilizing microarrays. Ascribing a confidence level to prognosis with the clinical confidence metric provides the clinician an objective, personalized basis for decisions, such as choosing the severity of the treatment.
Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60–70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the “Rule of Three” was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity.
Translational research involves utilization of clinical data to address challenges in drug discovery and development. The rationale behind this study is that the side effects observed in clinical trial and post-marketing surveillance can be translated into a screening system for use in drug discovery. As a proof-of-concept study, we developed an in silico system based on 13 hepatotoxic side effects to predict drug-induced liver injury (DILI), which is one of the most frequent causes of drug failure in clinical trial and withdrawal from post-marketing application, and also one of the most difficult clinical endpoints to predict from preclinical studies. We first identified 13 types of liver injury which yielded high prediction accuracy to distinguish drugs known to cause DILI from these don't. To effectively apply these 13 hepatotoxic side effects to the drug discovery process for DILI, we developed in silico models for each of these side effects solely based on chemical structure data. Finally, we constructed a DILI prediction system (DILIps) by combining these 13 in silico models in a consensus fashion, which yielded >91% positive predictive value for DILI in humans. The DILIps methodology can be extended in applications for addressing other drug safety issues, such as renal and cardiovascular toxicity.