HDAC‐inhibitor (S)‐8 disrupts HDAC6‐PP1 complex prompting A375 melanoma cell growth arrest and apoptosis

Histone deacetylase inhibitors (HDACi) are agents capable of inducing growth arrest and apoptosis in different tumour cell types. Previously, we reported a series of novel HDACi obtained by hybridizing SAHA or oxamflatin with 1,4‐benzodiazepines. Some of these hybrids proved effective against haematological and solid cancer cells and, above all, compound (S)‐8 has emerged for its activities in various biological systems. Here, we describe the effectiveness of (S)‐8 against highly metastatic human A375 melanoma cells by using normal PIG1 melanocytes as control. (S)‐8 prompted: acetylation of histones H3/H4 and α‐tubulin; G₀/G₁ and G₂/M cell cycle arrest by rising p21 and hypophos‐phorylated RB levels; apoptosis involving the cleavage of PARP and caspase 9, BAD protein augmentation and cytochrome c release; decrease in cell motility, invasiveness and pro‐angiogenic potential as shown by results of wound‐healing assay, down‐regulation of MMP‐2 and VEGF‐A/VEGF‐R2, besides TIMP‐1/TIMP‐2 up‐regulation; and also intracellular accumulation of melanin and neutral lipids. The pan‐caspase inhibitor Z‐VAD‐fmk, but not the antioxidant N‐acetyl‐cysteine, contrasted these events. Mechanistically, (S)‐8 allows the disruption of cytoplasmic HDAC6‐protein phosphatase 1 (PP1) complex in A375 cells thus releasing the active PP1 that dephosphorylates AKT and blocks its downstream pro‐survival signalling. This view is consistent with results obtained by: inhibiting PP1 with Calyculin A; using PPP1R2‐transfected cells with impaired PP1 activity; monitoring drug‐induced HDAC6‐PP1 complex re‐shuffling; and, abrogating HDAC6 expression with specific siRNA. Altogether, (S)‐8 proved very effective against melanoma A375 cells, but not normal melanocytes, and safe to normal mice thus offering attractive clinical prospects for treating this aggressive malignancy.     

Evaluating supervised and unsupervised background noise correction in human gut microbiome data

The ability to predict human phenotypes and identify biomarkers of disease from metagenomic data is crucial for the development of therapeutics for microbiome-associated diseases. However, metagenomic data is commonly affected by technical variables unrelated to the phenotype of interest, such as sequencing protocol, which can make it difficult to predict phenotype and find biomarkers of disease. Supervised methods to correct for background noise, originally designed for gene expression and RNA-seq data, are commonly applied to microbiome data but may be limited because they cannot account for unmeasured sources of variation. Unsupervised approaches address this issue, but current methods are limited because they are ill-equipped to deal with the unique aspects of microbiome data, which is compositional, highly skewed, and sparse. We perform a comparative analysis of the ability of different denoising transformations in combination with supervised correction methods as well as an unsupervised principal component correction approach that is presently used in other domains but has not been applied to microbiome data to date. We find that the unsupervised principal component correction approach has comparable ability in reducing false discovery of biomarkers as the supervised approaches, with the added benefit of not needing to know the sources of variation apriori. However, in prediction tasks, it appears to only improve prediction when technical variables contribute to the majority of variance in the data. As new and larger metagenomic datasets become increasingly available, background noise correction will become essential for generating reproducible microbiome analyses.     

The new low-toxic histone deacetylase inhibitor S-(2) induces apoptosis in various acute myeloid leukaemia cells

Histone deacetylase inhibitors (HDACi) induce tumour cell cycle arrest and/or apoptosis, and some of them are currently used in cancer therapy. Recently, we described a series of powerful HDACi characterized by a 1,4-benzodiazepine (BDZ) ring hybridized with a linear alkyl chain bearing a hydroxamate function as Zn(++)--chelating group. Here, we explored the anti-leukaemic properties of three novel hybrids, namely the chiral compounds (S)-2 and (R)-2, and their non-chiral analogue 4, which were first comparatively tested in promyelocytic NB4 cells. (S)-2 and partially 4--but not (R)-2--caused G0/G1 cell-cycle arrest by up-regulating cyclin G2 and p21 expression and down-regulating cyclin D2 expression, and also apoptosis as assessed by cell morphology and cytofluorimetric assay, histone H2AX phosphorylation and PARP cleavage. Notably, these events were partly prevented by an anti-oxidant. Moreover, novel HDACi prompted p53 and α-tubulin acetylation and, consistently, inhibited HDAC1 and 6 activity. The rank order of potency was (S)-2 > 4 > (R)-2, reflecting that of other biological assays and addressing (S)-2 as the most effective compound capable of triggering apoptosis in various acute myeloid leukaemia (AML) cell lines and blasts from patients with different AML subtypes. Importantly, (S)-2 was safe in mice (up to 150 mg/kg/week) as determined by liver, spleen, kidney and bone marrow histopathology; and displayed negligible affinity for peripheral/central BDZ-receptors. Overall, the BDZ-hydroxamate (S)-2 showed to be a low-toxic HDACi with powerful anti-proliferative and pro-apototic activities towards different cultured and primary AML cells, and therefore of clinical interest to support conventional anti-leukaemic therapy.     

VIAF, a conserved inhibitor of apoptosis (IAP)-interacting factor that modulates caspase activation

Inhibitor of apoptosis (IAP) proteins are involved in the suppression of apoptosis, signal transduction, cell cycle control and gene regulation. Here we describe the cloning and characterization of viral IAP-associated factor (VIAF), a highly conserved, ubiquitously expressed phosphoprotein with limited homology to members of the phosducin family that associates with baculovirus Op-IAP. VIAF bound Op-IAP both in vitro and in intact cells, with each protein displaying a predominantly cytoplasmic localization. VIAF lacks a consensus IAP binding motif, and overexpression of VIAF failed to prevent Op-IAP from protecting human cells from a variety of apoptotic stimuli, suggesting that VIAF does not function as an IAP antagonist. VIAF was unable to directly inhibit caspase activation in vitro and a reduction of VIAF protein levels by RNA interference led to a decrease in Bax-mediated caspase activation, suggesting that VIAF functions to co-regulate the apoptotic cascade. Finally, VIAF is a substrate for ubiquitination mediated by Op-IAP. Thus, VIAF is a novel IAP-interacting factor that functions in caspase activation during apoptosis.     

Classification and Visualization Based on Derived Image Features: Application to Genetic Syndromes

Data transformations prior to analysis may be beneficial in classification tasks. In this article we investigate a set of such transformations on 2D graph-data derived from facial images and their effect on classification accuracy in a high-dimensional setting. These transformations are low-variance in the sense that each involves only a fixed small number of input features. We show that classification accuracy can be improved when penalized regression techniques are employed, as compared to a principal component analysis (PCA) pre-processing step. In our data example classification accuracy improves from 47% to 62% when switching from PCA to penalized regression. A second goal is to visualize the resulting classifiers. We develop importance plots highlighting the influence of coordinates in the original 2D space. Features used for classification are mapped to coordinates in the original images and combined into an importance measure for each pixel. These plots assist in assessing plausibility of classifiers, interpretation of classifiers, and determination of the relative importance of different features.     

Effectiveness of the Histone Deacetylase Inhibitor (S)-2 against LNCaP and PC3 Human Prostate Cancer Cells

Histone deacetylase inhibitors (HDACi) represent a promising class of epigenetic agents with anticancer properties. Here, we report that (S)-2, a novel hydroxamate-based HDACi, shown previously to be effective against acute myeloid leukemia cells, was also a potent inducer of apoptosis/differentiation in human prostate LNCaP and PC3 cancer cells. In LNCaP cells (S)-2 was capable of triggering H3/H4 histone acetylation, H2AX phosphorylation as a marker of DNA damage and producing G₀/G₁ cell cycle arrest. Consistently, (S)-2 led to enhanced expression of both the protein and mRNA p21 levels in LNCaP cells but, contrary to SAHA, not in normal non-tumorigenic prostate PNT1A cells. Mechanistic studies demonstrated that (S)-2-induced apoptosis in LNCaP cells developed through the cleavage of pro-caspase 9 and 3 and of poly(ADP-ribose)-polymerase accompanied by the dose-dependent loss of mitochondrial membrane potential. Indeed, the addition of the pan-caspase inhibitor Z-VAD-fmk greatly reduced drug-mediated apoptosis while the antioxidant N-acetyl-cysteine was virtually ineffective. Importantly, preliminary data with nude mice xenografted with LNCaP cells showed that (S)-2 prompted a decrease in the tumor volume and an increase in H2AX phosphorylation within the cancer cells. Moreover, the highly metastatic prostate cancer PC3 cells were also sensitive to (S)-2 that: i) induced growth arrest and moderate apoptosis; ii) steered cells towards differentiation and neutral lipid accumulation; iii) reduced cell invasiveness potential by decreasing the amount of MMP-9 activity and up-regulating TIMP-1 expression; and iv) inhibited cell motility and migration through the Matrigel. Overall, (S)-2 has proven to be a powerful HDACi capable of inducing growth arrest, cell death and/or differentiation of LNCaP and PC3 prostate cancer cells and, due to its low toxicity and efficacy in vivo, might also be of clinical interest to support conventional prostate cancer therapy.     

Powerful testing via hierarchical linkage disequilibrium in haplotype association studies

Marginal tests based on individual SNPs are routinely used in genetic association studies. Studies have shown that haplotype‐based methods may provide more power in disease mapping than methods based on single markers when, for example, multiple disease‐susceptibility variants occur within the same gene. A limitation of haplotype‐based methods is that the number of parameters increases exponentially with the number of SNPs, inducing a commensurate increase in the degrees of freedom and weakening the power to detect associations. To address this limitation, we introduce a hierarchical linkage disequilibrium model for disease mapping, based on a reparametrization of the multinomial haplotype distribution, where every parameter corresponds to the cumulant of each possible subset of a set of loci. This hierarchy present in the parameters enables us to employ flexible testing strategies over a range of parameter sets: from standard single SNP analyses through the full haplotype distribution tests, reducing degrees of freedom and increasing the power to detect associations. We show via extensive simulations that our approach maintains the type I error at nominal level and has increased power under many realistic scenarios, as compared to single SNP and standard haplotype‐based studies. To evaluate the performance of our proposed methodology in real data, we analyze genome‐wide data from the Wellcome Trust Case‐Control Consortium.