Sparsest factor analysis for clustering variables: a matrix decomposition approach

We propose a new procedure for sparse factor analysis (FA) such that each variable loads only one common factor. Thus, the loading matrix has a single nonzero element in each row and zeros elsewhere. Such a loading matrix is the sparsest possible for certain number of variables and common factors. For this reason, the proposed method is named sparsest FA (SSFA). It may also be called FA-based variable clustering, since the variables loading the same common factor can be classified into a cluster. In SSFA, all model parts of FA (common factors, their correlations, loadings, unique factors, and unique variances) are treated as fixed unknown parameter matrices and their least squares function is minimized through specific data matrix decomposition. A useful feature of the algorithm is that the matrix of common factor scores is re-parameterized using QR decomposition in order to efficiently estimate factor correlations. A simulation study shows that the proposed procedure can exactly identify the true sparsest models. Real data examples demonstrate the usefulness of the variable clustering performed by SSFA

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response

Cholesterol catalyses Aβ42 aggregation through a heterogeneous nucleation pathway in the presence of lipid membranes.

Alzheimer's disease is a neurodegenerative disorder associated with the aberrant aggregation of the amyloid-β peptide. Although increasing evidence implicates cholesterol in the pathogenesis of Alzheimer's disease, the detailed mechanistic link between this lipid molecule and the disease process remains to be fully established. To address this problem, we adopt a kinetics-based strategy that reveals a specific catalytic role of cholesterol in the aggregation of Aβ42 (the 42-residue form of the amyloid-β peptide). More specifically, we demonstrate that lipid membranes containing cholesterol promote Aβ42 aggregation by enhancing its primary nucleation rate by up to 20-fold through a heterogeneous nucleation pathway. We further show that this process occurs as a result of cooperativity in the interaction of multiple cholesterol molecules with Aβ42. These results identify a specific microscopic pathway by which cholesterol dramatically enhances the onset of Aβ42 aggregation, thereby helping rationalize the link between Alzheimer's disease and the impairment of cholesterol homeostasis

Evaluating Nuclei Concentration in Amyloid Fibrillation Reactions Using Back-Calculation Approach

Background: In spite of our extensive knowledge of the more than 20 proteins associated with different amyloid diseases, we do not know how amyloid toxicity occurs or how to block its action. Recent contradictory reports suggest that the fibrils and/or the oligomer precursors cause toxicity. An estimate of their temporal concentration may broaden understanding of the amyloid aggregation process. Methodology/Principal Findings: Assuming that conversion of folded protein to fibril is initiated by a nucleation event, we back-calculate the distribution of nuclei concentration. The temporal in vitro concentration of nuclei for the model hormone, recombinant human insulin, is estimated to be in the picomolar range. This is a conservative estimate since the back-calculation method is likely to overestimate the nuclei concentration because it does not take into consideration fibril fragmentation, which would lower the amount of nuclei Conclusions: Because of their propensity to form aggregates (non-ordered) and fibrils (ordered), this very low concentration could explain the difficulty in isolating and blocking oligomers or nuclei toxicity and the long onset time for amyloid diseases

A dual role of transient receptor potential melastatin 2 channel in cytotoxicity induced by silica nanoparticles

Silica nanoparticles (NPs) have remarkable applications. However, accumulating evidence suggests NPs can cause cellular toxicity by inducing ROS production and increasing intracellular Ca2+ ([Ca2+]i), but the underlying molecular mechanism is largely unknown. Transient receptor potential melastatin 2 (TRPM2) channel is known to be a cellular redox potential sensor that provides an important pathway for increasing the [Ca2+]i under oxidative stress. In this study, we examined the role of TRPM2 channel in silica NPs-induced oxidative stress and cell death. By quantitation of cell viability, ROS production, [Ca2+]i, and protein identification, we showed that TRPM2 channel is required for ROS production and Ca2+ increase induced by silica NPs through regulating NADPH oxidase activity in HEK293 cells. Strikingly, HEK293 cells expressing low levels of TRPM2 were more susceptible to silica NPs than those expressing high levels of TRPM2. Macrophages from young mice showed significantly lower TRPM2 expression than those from senescent mice and had significantly lower viability after silica NPs exposure than those from senescent ones. Taken together, these findings demonstrate for the first time that TRPM2 channel acts as an oxidative stress sensor that plays a dual role in silica NPs-induced cytotoxicity by differentially regulating the NADPH oxidase activity and ROS generation

Deregulation of Rab and Rab Effector Genes in Bladder Cancer

Growing evidence indicates that Rab GTPases, key regulators of intracellular transport in eukaryotic cells, play an important role in cancer. We analysed the deregulation at the transcriptional level of the genes encoding Rab proteins and Rab-interacting proteins in bladder cancer pathogenesis, distinguishing between the two main progression pathways so far identified in bladder cancer: the Ta pathway characterized by a high frequency of FGFR3 mutation and the carcinoma in situ pathway where no or infrequent FGFR3 mutations have been identified. A systematic literature search identified 61 genes encoding Rab proteins and 223 genes encoding Rab-interacting proteins. Transcriptomic data were obtained for normal urothelium samples and for two independent bladder cancer data sets corresponding to 152 and 75 tumors. Gene deregulation was analysed with the SAM (significant analysis of microarray) test or the binomial test. Overall, 30 genes were down-regulated, and 13 were up-regulated in the tumor samples. Five of these deregulated genes (LEPRE1, MICAL2, RAB23, STXBP1, SYTL1) were specifically deregulated in FGFR3-non-mutated muscle-invasive tumors. No gene encoding a Rab or Rab-interacting protein was found to be specifically deregulated in FGFR3-mutated tumors. Cluster analysis showed that the RAB27 gene cluster (comprising the genes encoding RAB27 and its interacting partners) was deregulated and that this deregulation was associated with both pathways of bladder cancer pathogenesis. Finally, we found that the expression of KIF20A and ZWINT was associated with that of proliferation markers and that the expression of MLPH, MYO5B, RAB11A, RAB11FIP1, RAB20 and SYTL2 was associated with that of urothelial cell differentiation markers. This systematic analysis of Rab and Rab effector gene deregulation in bladder cancer, taking relevant tumor subgroups into account, provides insight into the possible roles of Rab proteins and their effectors in bladder cancer pathogenesis. This approach is applicable to other group of genes and types of cancer

CD38 promotes pristane-induced chronic inflammation and increases susceptibility to experimental lupus by an apoptosis-driven and TRPM2-dependent mechanism

In this study, we investigated the role of CD38 in a pristane-induced murine model of lupus. CD38-deficient (Cd38-/-) but not ART2-deficient (Art2-/-) mice developed less severe lupus compared to wild type (WT) mice, and their protective phenotype consisted of (i) decreased IFN-I-stimulated gene expression, (ii) decreased numbers of peritoneal CCR2hiLy6Chi inflammatory monocytes, TNF-α-producing Ly6G+ neutrophils and Ly6Clo monocytes/macrophages, (iii) decreased production of anti-single-stranded DNA and anti-nRNP autoantibodies, and (iv) ameliorated glomerulonephritis. Cd38-/- pristane-elicited peritoneal exudate cells had defective CCL2 and TNF-α secretion following TLR7 stimulation. However, Tnf-α and Cxcl12 gene expression in Cd38-/- bone marrow (BM) cells was intact, suggesting a CD38-independent TLR7/TNF-α/CXCL12 axis in the BM. Chemotactic responses of Cd38-/- Ly6Chi monocytes and Ly6G+ neutrophils were not impaired. However, Cd38-/- Ly6Chi monocytes and Ly6Clo monocytes/macrophages had defective apoptosis-mediated cell death. Importantly, mice lacking the cation channel TRPM2 (Trpm2-/-) exhibited very similar protection, with decreased numbers of PECs, and apoptotic Ly6Chi monocytes and Ly6Clo monocytes/macrophages compared to WT mice. These findings reveal a new role for CD38 in promoting aberrant inflammation and lupus-like autoimmunity via an apoptosis-driven mechanism. Furthermore, given the implications of CD38 in the activation of TRPM2, our data suggest that CD38 modulation of pristane-induced apoptosis is TRPM2-dependent.We would like to thank Dr. Yasuo Mori for providing the Tr pm 2−/− mice, Clara Sánchez for animal husbandry at the IPBLN-CSIC Animal Facility, and Thomas S. Simpler and Uma Mudunuru for animal husbandry at the University of Alabama at Birmingham (UAB). We would also like to thank Laura Montosa from the Centro de Instrumentación Cientifica (CIC) at the Universidad de Granada (UGR) for technical support with microscopy, as well as Mohamed Tassi and Ana Santos at CIC, UGR, and Sandra García-Jiménez, Victoria Romero-del-Amo, Gemma Palencia-López, and Samuel Ruiz-Santiago at Campus Formación Granada for tissue preparations, H&E staining, and other staining procedures. Work performed in the Sancho lab was supported in part by the European Commission in collaboration with the following Funding Agencies: (i) Junta de Andalucía (J.A.), Consejería Innovación Ciencia y Empresa y Consejería Educación y Ciencia, Project: PC08-CTS-04046 to J.S. and M.Z., and (ii) Ministerio de Economía y Competitividad (MINECO), Projects: SAF-2011-27261 to J.S. and M.Z. and SAF2014-55088-R to R.M. Work performed in the Lund lab was supported by funds provided by UAB.S

Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases

Protein kinases are the most common protein domains implicated in cancer, where somatically acquired mutations are known to be functionally linked to a variety of cancers. Resequencing studies of protein kinase coding regions have emphasized the importance of sequence and structure determinants of cancer-causing kinase mutations in understanding of the mutation-dependent activation process. We have developed an integrated bioinformatics resource, which consolidated and mapped all currently available information on genetic modifications in protein kinase genes with sequence, structure and functional data. The integration of diverse data types provided a convenient framework for kinome-wide study of sequence-based and structure-based signatures of cancer mutations. The database-driven analysis has revealed a differential enrichment of SNPs categories in functional regions of the kinase domain, demonstrating that a significant number of cancer mutations could fall at structurally equivalent positions (mutational hotspots) within the catalytic core. We have also found that structurally conserved mutational hotspots can be shared by multiple kinase genes and are often enriched by cancer driver mutations with high oncogenic activity. Structural modeling and energetic analysis of the mutational hotspots have suggested a common molecular mechanism of kinase activation by cancer mutations, and have allowed to reconcile the experimental data. According to a proposed mechanism, structural effect of kinase mutations with a high oncogenic potential may manifest in a significant destabilization of the autoinhibited kinase form, which is likely to drive tumorigenesis at some level. Structure-based functional annotation and prediction of cancer mutation effects in protein kinases can facilitate an understanding of the mutation-dependent activation process and inform experimental studies exploring molecular pathology of tumorigenesis

Amyloid Plaques Beyond Aβ: A Survey of the Diverse Modulators of Amyloid Aggregation

Aggregation of the amyloid-β (Aβ) peptide is strongly correlated with Alzheimer’s disease (AD). Recent research has improved our understanding of the kinetics of amyloid fibril assembly and revealed new details regarding different stages in plaque formation. Presently, interest is turning toward studying this process in a holistic context, focusing on cellular components which interact with the Aβ peptide at various junctures during aggregation, from monomer to cross-β amyloid fibrils. However, even in isolation, a multitude of factors including protein purity, pH, salt content, and agitation affect Aβ fibril formation and deposition, often producing complicated and conflicting results. The failure of numerous inhibitors in clinical trials for AD suggests that a detailed examination of the complex interactions that occur during plaque formation, including binding of carbohydrates, lipids, nucleic acids, and metal ions, is important for understanding the diversity of manifestations of the disease. Unraveling how a variety of key macromolecular modulators interact with the Aβ peptide and change its aggregation properties may provide opportunities for developing therapies. Since no protein acts in isolation, the interplay of these diverse molecules may differentiate disease onset, progression, and severity, and thus are worth careful consideration

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta