Citations

AbstractObjectivesPolycythemia vera (PV)‐related symptoms may not be adequately controlled with conventional therapy. This current analysis of the RESPONSE trial evaluated the effects of ruxolitinib compared with standard therapy on quality of life (QoL) and symptoms in patients with PV who were hydroxyurea resistant/intolerant.MethodsIn the previously reported primary analysis, ruxolitinib achieved the primary composite endpoint of hematocrit control and ≥35% reduction in spleen volume at Week 32. The current analysis evaluated patient‐reported outcomes using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire‐Core 30 (EORTC QLQ‐C30), the Myeloproliferative Neoplasm Symptom Assessment Form (MPN‐SAF), the Pruritus Symptom Impact Scale (PSIS), and the Patient Global Impression of Change (PGIC).ResultsCompared with standard therapy, ruxolitinib was associated with greater improvements in global health status/QoL, functional subscales, and individual symptom scores of the EORTC QLQ‐C30. At Week 32, more patients in the ruxolitinib arm (44%) achieved a ≥10‐point improvement in global health status/QoL vs. standard therapy (9%). Improvements in MPN‐SAF symptom scores were consistent with improvements in EORTC QLQ‐C30, PSIS, and PGIC scores.ConclusionsRuxolitinib provides clinically relevant improvements in QoL and ameliorates symptom burden in patients with PV who are hydroxyurea resistant/intolerant.

Abstract Summary: The development of the Infinium HumanMethylation450 BeadChip enables epigenome-wide association studies at a reduced cost. One observation of the 450K data is that many CpG sites the beadchip interrogates have very large measurement errors. Including these noisy CpGs will decrease the statistical power of detecting relevant associations due to multiple testing correction. We propose to use intra-class correlation coefficient (ICC), which characterizes the relative contribution of the biological variability to the total variability, to filter CpGs when technical replicates are available. We estimate the ICC based on a linear mixed effects model by pooling all the samples instead of using the technical replicates only. An ultra-fast algorithm has been developed to address the computational complexity and CpG filtering can be completed in minutes on a desktop computer for a 450K data set of over 1000 samples. Our method is very flexible and can accommodate any replicate design. Simulations and a real data application demonstrate that our whole-sample ICC method performs better than replicate-sample ICC or variance-based method. Availability and implementation: CpGFilter is implemented in R and publicly available under CRAN via the R package ‘CpGFilter’. Contact: chen.jun2@mayo.edu or xlin@hsph.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Abstract Pancreatic ductal adenocarcinoma (PDAC) offers an optimal model for discovering “druggable” molecular pathways that participate in inflammation-associated cancer development. Chronic pancreatitis, a common prolonged inflammatory disease, behaves as a well-known premalignant condition that contributes to PDAC development. Although the mechanisms underlying the pancreatitis-to-cancer transition remain to be fully elucidated, emerging evidence supports the hypothesis that the actions of proinflammatory mediators on cells harboring Kras mutations promote neoplastic transformation. Recent elegant studies demonstrated that the IL17 pathway mediates this phenomenon and can be targeted with antibodies, but the downstream mechanisms by which IL17 functions during this transition are currently unclear. In this study, we demonstrate that IL17 induces the expression of REG3β, a well-known mediator of pancreatitis, during acinar-to-ductal metaplasia and in early pancreatic intraepithelial neoplasia (PanIN) lesions. Furthermore, we found that REG3β promotes cell growth and decreases sensitivity to cell death through activation of the gp130-JAK2-STAT3-dependent pathway. Genetic inactivation of REG3β in the context of oncogenic Kras-driven PDAC resulted in reduced PanIN formation, an effect that could be rescued by administration of exogenous REG3β. Taken together, our findings provide mechanistic insight into the pathways underlying inflammation-associated pancreatic cancer, revealing a dual and contextual pathophysiologic role for REG3β during pancreatitis and PDAC initiation. Cancer Res; 75(22); 4852–62. ©2015 AACR.

Abstract Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. Cancer Epidemiol Biomarkers Prev; 24(11); 1680–91. ©2015 AACR.

Abstract Summary: One central theme of modern high-throughput genomic data analysis is to identify relevant genomic features as well as build up a predictive model based on selected features for various tasks such as personalized medicine. Correlating the large number of ‘omics’ features with a certain phenotype is particularly challenging due to small sample size (n) and high dimensionality (p). To address this small n, large p problem, various forms of sparse regression models have been proposed by exploiting the sparsity assumption. Among these, network-constrained sparse regression model is of particular interest due to its ability to utilize the prior graph/network structure in the omics data. Despite its potential usefulness for omics data analysis, no efficient R implementation is publicly available. Here we present an R software package ‘glmgraph’ that implements the graph-constrained regularization for both sparse linear regression and sparse logistic regression. We implement both the L1 penalty and minimax concave penalty for variable selection and Laplacian penalty for coefficient smoothing. Efficient coordinate descent algorithm is used to solve the optimization problem. We demonstrate the use of the package by applying it to a human microbiome dataset, where phylogeny structure among bacterial taxa is available. Availability and implementation: ‘glmgraph’ is implemented in R and C++ Armadillo and publicly available under CRAN. Contact: chen.jun2@mayo.edu or hongzhe@upenn.edu Supplementary information: Supplementary data are available at Bioinformatics online.

The microtubule-associated protein, tau, is the principal component of paired helical filaments (PHFs) in Alzheimer's disease. PHF-tau is highly phosphorylated and a total of 25 sites of phosphorylation have so far been identified. Many of these sites are serine or threonine residues that are immediately followed in the sequence by proline residues, and hence are candidate phosphorylation sites for proline-directed kinases. In vitro, glycogen synthase kinase-3 (GSK-3), extracellular signal-related kinase-1 and -2, and mitogen-activated protein kinases, p38 kinase and c-jun N-terminal kinase, all phosphorylate many of these sites, although with different efficiencies for particular sites. Phosphorylation studies in transfected cells and neurons show that GSK-3 phosphorylates tau more extensively than do these other proline-directed kinases. Mutations in tau have been shown to affect in vitro phosphorylation of tau by GSK-3. The Arg406-->Trp (R406W) tau mutation also affects tau phosphorylation in cells.