Spi-1/PU.1 activates transcription through clustered DNA occupancy in erythroleukemia.

Acute leukemias are characterized by deregulation of transcriptional networks that control the lineage specificity of gene expression. The aberrant overexpression of the Spi-1/PU.1 transcription factor leads to erythroleukemia. To determine how Spi-1 mechanistically influences the transcriptional program, we combined a ChIP-seq analysis with transcriptional profiling in cells from an erythroleukemic mouse model. We show that Spi-1 displays a selective DNA-binding that does not often cause transcriptional modulation. We report that Spi-1 controls transcriptional activation and repression partially through distinct Spi-1 recruitment to chromatin. We revealed several parameters impacting on Spi-1-mediated transcriptional activation. Gene activation is facilitated by Spi-1 occupancy close to transcriptional starting site of genes devoid of CGIs. Moreover, in those regions Spi-1 acts by binding to multiple motifs tightly clustered and with similar orientation. Finally, in contrast to the myeloid and lymphoid B cells in which Spi-1 exerts a physiological activity, in the erythroleukemic cells, lineage-specific cooperating factors do not play a prevalent role in Spi-1-mediated transcriptional activation. Thus, our work describes a new mechanism of gene activation through clustered site occupancy of Spi-1 particularly relevant in regard to the strong expression of Spi-1 in the erythroleukemic cells.

SMETHILLIUM: spatial normalization method for Illumina infinium HumanMethylation BeadChip.

SUMMARY: DNA methylation is a major epigenetic modification in human cells. Illumina HumanMethylation27 BeadChip makes it possible to quantify the methylation state of 27 578 loci spanning 14 495 genes. We developed a non-parametric normalization method to correct the spatial background noise in order to improve the signal-to-noise ratio. The prediction performance of the proposed method was assessed on three fully methylated samples and three fully unmethylated DNA samples. We demonstrate that the spatial normalization outperforms BeadStudio to predict the methylation state of a given locus. AVAILABILITY AND IMPLEMENTATION: A R script and the data are available at the following address: http://bioinfo.curie.fr/projects/smethillium.

PTPN22 R620W genotype-phenotype correlation analysis and gene-environment interaction study in early rheumatoid arthritis: results from the ESPOIR cohort.

OBJECTIVES: To investigate genotype-phenotype correlation and gene-environment interaction between PTPN22 R620W environmental factors such as tobacco/hormonal treatments in an inception cohort of RA patients. METHODS: An intra-cohort study including 532 Caucasian RA patients genotyped for the PTPN22 rs2476601 polymorphism was performed. Anti-CCP and RF status at baseline, presence of bone erosions at 1 year, HLADR1 and/or DR4 status, demography, comorbidities, exposure to tobacco with the cumulative dose in pack-years, hormonal treatments and treatments received for RA were collected. Logistic regression was performed to estimate the ORs and multiplicative interaction with adjustment for confounding factors. Gene-environment interaction was estimated by the relative excess risk due to interaction (RERI), attributable proportion (AP) and synergy index (SI). RESULTS: PTPN22 620W risk allele was associated with ACPA production [odds ratio (OR) = 2.21, 95% CI 1.4, 3.4, P < 0.0001]. Hormonal treatment exposition and smoking were found to act with a protective effect against ACPA production (OR = 0.44, 95% CI 0.3, 0.7, P = 0.001) and early bone erosion (OR = 0.56, 95% CI 0.4-0.8, P = 0.003), respectively, and independently of HLADR and PTPN22 status. No evidence for a gene-environment interaction was detected. CONCLUSION: These data provide new insights into the pathogenesis of RA, underlying the pivotal key role of environmental factors in the typical heterogeneity of RA.

Impact of Prior Bevacizumab Treatment on VEGF-A and PlGF Levels and Outcome Following Second-Line Aflibercept Treatment: Biomarker Post Hoc Analysis of the VELOUR Trial.

PURPOSE: Aflibercept is a targeted anti-VEGF therapy used to treat patients with metastatic colorectal cancer (mCRC) following progression on oxaliplatin-based regimens. This post hoc study evaluated the effect of prior bevacizumab treatment and growth factor levels on patient outcomes associated with aflibercept in the VELOUR phase III trial. EXPERIMENTAL DESIGN: Baseline biomarker plasma concentrations were measured using a bead-based multiplex assay. Patients were grouped according to prior bevacizumab treatment, second-line treatment, and serum biomarker concentrations, and analyzed for overall survival (OS) and progression-free survival (PFS). RESULTS: Plasma samples were available for 553 patients (placebo n = 265; aflibercept n = 288), of which 169 had received prior bevacizumab. Nine biomarkers implicated in angiogenesis or bevacizumab resistance correlated with prior bevacizumab therapy. VEGF-A and placental growth factor (PlGF) were the most significantly increased in patients who had received prior bevacizumab compared with those who had not received prior bevacizumab. In the placebo group, patients with high VEGF-A (>144 pg/mL) levels at baseline had worse OS and PFS compared with patients with lower levels at baseline (9.6 vs. 12.9 months). This was also seen in patients who received placebo and had high baseline PlGF (>8 pg/mL; 9.7 vs. 11.7 months). In the aflibercept group, prolonged OS and PFS were observed regardless of baseline VEGF-A or PlGF levels. CONCLUSIONS: High VEGF-A and PlGF serum levels may underlie development of resistance to bevacizumab in patients with mCRC. Aflibercept retains its activity regardless of baseline VEGF-A and PlGF levels and may be an effective second-line treatment for patients with bevacizumab-induced resistance.

Identification of sarilumab pharmacodynamic and predictive markers in patients with inadequate response to TNF inhibition: a biomarker substudy of the phase 3 TARGET study.

INTRODUCTION: Interleukin-6 (IL-6) orchestrates formation of an inflammatory pannus, leading to joint damage in rheumatoid arthritis (RA). Sarilumab is a human monoclonal antibody blocking the IL-6Rα. In TARGET (NCT01709578), a phase 3 study in adults with moderate-to-severe RA and inadequate response or intolerance to tumour necrosis factor inhibitors, subcutaneous sarilumab 200 mg or 150 mg every 2 weeks (q2w) plus conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) significantly reduced disease activity versus placebo plus csDMARDs. METHODS: Circulating levels of biomarkers associated with synovial inflammation (matrix metalloproteinase 3 (MMP-3), collagen type I MMP-cleaved fragment (C1M), collagen type III MMP-cleaved fragment (C3M)), myeloid (soluble intercellular adhesion molecule 1 (sICAM-1), IL-8 and calprotectin) and lymphoid activation (chemokine, CXC motif, ligand 13 (CXCL13), CXCL10, B cell-activating factor) and bone remodelling (receptor activator of nuclear factor-κB ligand (RANKL), osteoprotegerin and osteocalcin) were evaluated in patients from a TARGET substudy. RESULTS: Sarilumab significantly decreased C1M, C3M, CXCL13, MMP-3 and total RANKL levels at week 24 versus placebo; some markers were significantly suppressed at week 2 and normalised to levels in healthy controls. Levels of sICAM-1 were predictive of disease activity score by C-reactive protein and clinical disease activity index low disease activity (LDA) response in the sarilumab 200 mg q2w group at week 12. A trend was observed in which patients with lower sICAM-1 levels at baseline had better response compared with patients with higher sICAM-1. CONCLUSIONS: Sarilumab plus csDMARDs decreased circulating biomarkers of synovial inflammation and bone resorption; sICAM-1 was predictive of achieving LDA with sarilumab. TRIAL REGISTRATION NUMBER: NCT01709578; Post-results.

SHIPS: Spectral Hierarchical clustering for the Inference of Population Structure in genetic studies.

Inferring the structure of populations has many applications for genetic research. In addition to providing information for evolutionary studies, it can be used to account for the bias induced by population stratification in association studies. To this end, many algorithms have been proposed to cluster individuals into genetically homogeneous sub-populations. The parametric algorithms, such as Structure, are very popular but their underlying complexity and their high computational cost led to the development of faster parametric alternatives such as Admixture. Alternatives to these methods are the non-parametric approaches. Among this category, AWclust has proven efficient but fails to properly identify population structure for complex datasets. We present in this article a new clustering algorithm called Spectral Hierarchical clustering for the Inference of Population Structure (SHIPS), based on a divisive hierarchical clustering strategy, allowing a progressive investigation of population structure. This method takes genetic data as input to cluster individuals into homogeneous sub-populations and with the use of the gap statistic estimates the optimal number of such sub-populations. SHIPS was applied to a set of simulated discrete and admixed datasets and to real SNP datasets, that are data from the HapMap and Pan-Asian SNP consortium. The programs Structure, Admixture, AWclust and PCAclust were also investigated in a comparison study. SHIPS and the parametric approach Structure were the most accurate when applied to simulated datasets both in terms of individual assignments and estimation of the correct number of clusters. The analysis of the results on the real datasets highlighted that the clusterings of SHIPS were the more consistent with the population labels or those produced by the Admixture program. The performances of SHIPS when applied to SNP data, along with its relatively low computational cost and its ease of use make this method a promising solution to infer fine-scale genetic patterns.

Independent transcriptional reprogramming and apoptosis induction by cisplatin.

Neither the molecular mechanisms whereby cancer cells intrinsically are or become resistant to the DNA-damaging agent cisplatin nor the signaling pathways that account for cisplatin cytotoxicity have thus far been characterized in detail. In an attempt to gain further insights into the molecular cascades elicited by cisplatin (leading to resistance or underpinning its antineoplastic properties), we comparatively investigated the ability of cisplatin, C2-ceramide and cadmium dichloride, alone or in the presence of an array of mitochondrion-protective agents, to trigger the permeabilization of purified mitochondria. In addition, we compared the transcriptional response triggered by cisplatin, C2-ceramide and cadmium dichloride in non-small cell lung carcinoma A549 cells. Finally, we assessed the capacity of cisplatin, C2-ceramide and cadmium dichloride to reduce the clonogenic potential of a battery of yeast strains lacking proteins involved in the regulation of cell death, DNA damage signaling and stress management. This multipronged experimental approach revealed that cisplatin elicits signaling pathways that are for the most part "private," i.e., that manifest limited overlap with the molecular cascades ignited by other inducers of mitochondrial apoptosis, and triggers apoptosis mainly in a transcription-independent fashion. Indeed, bona fide cisplatin-response modifiers that we have recently identified by a functional genome-wide siRNA screen are either not transcriptionally regulated during cisplatin-induced cell death or their transcriptional modulation reflects the activation of an adaptive response promoting cisplatin resistance.

Prognostic impact of vitamin B6 metabolism in lung cancer.

Patients with non-small cell lung cancer (NSCLC) are routinely treated with cytotoxic agents such as cisplatin. Through a genome-wide siRNA-based screen, we identified vitamin B6 metabolism as a central regulator of cisplatin responses in vitro and in vivo. By aggravating a bioenergetic catastrophe that involves the depletion of intracellular glutathione, vitamin B6 exacerbates cisplatin-mediated DNA damage, thus sensitizing a large panel of cancer cell lines to apoptosis. Moreover, vitamin B6 sensitizes cancer cells to apoptosis induction by distinct types of physical and chemical stress, including multiple chemotherapeutics. This effect requires pyridoxal kinase (PDXK), the enzyme that generates the bioactive form of vitamin B6. In line with a general role of vitamin B6 in stress responses, low PDXK expression levels were found to be associated with poor disease outcome in two independent cohorts of patients with NSCLC. These results indicate that PDXK expression levels constitute a biomarker for risk stratification among patients with NSCLC.

Should we abandon the t-test in the analysis of gene expression microarray data: a comparison of variance modeling strategies.

High-throughput post-genomic studies are now routinely and promisingly investigated in biological and biomedical research. The main statistical approach to select genes differentially expressed between two groups is to apply a t-test, which is subject of criticism in the literature. Numerous alternatives have been developed based on different and innovative variance modeling strategies. However, a critical issue is that selecting a different test usually leads to a different gene list. In this context and given the current tendency to apply the t-test, identifying the most efficient approach in practice remains crucial. To provide elements to answer, we conduct a comparison of eight tests representative of variance modeling strategies in gene expression data: Welch's t-test, ANOVA [1], Wilcoxon's test, SAM [2], RVM [3], limma [4], VarMixt [5] and SMVar [6]. Our comparison process relies on four steps (gene list analysis, simulations, spike-in data and re-sampling) to formulate comprehensive and robust conclusions about test performance, in terms of statistical power, false-positive rate, execution time and ease of use. Our results raise concerns about the ability of some methods to control the expected number of false positives at a desirable level. Besides, two tests (limma and VarMixt) show significant improvement compared to the t-test, in particular to deal with small sample sizes. In addition limma presents several practical advantages, so we advocate its application to analyze gene expression data.

EMA - A R package for Easy Microarray data analysis.

BACKGROUND: The increasing number of methodologies and tools currently available to analyse gene expression microarray data can be confusing for non specialist users. FINDINGS: Based on the experience of biostatisticians of Institut Curie, we propose both a clear analysis strategy and a selection of tools to investigate microarray gene expression data. The most usual and relevant existing R functions were discussed, validated and gathered in an easy-to-use R package (EMA) devoted to gene expression microarray analysis. These functions were improved for ease of use, enhanced visualisation and better interpretation of results. CONCLUSIONS: Strategy and tools proposed in the EMA R package could provide a useful starting point for many microarrays users. EMA is part of Comprehensive R Archive Network and is freely available at http://bioinfo.curie.fr/projects/ema/.

miR-181a and miR-630 regulate cisplatin-induced cancer cell death.

MicroRNAs (miRNA) are noncoding RNAs that regulate multiple cellular processes, including proliferation and apoptosis. We used microarray technology to identify miRNAs that were upregulated by non-small cell lung cancer (NSCLC) A549 cells in response to cisplatin (CDDP). The corresponding synthetic miRNA precursors (pre-miRNAs) per se were not lethal when transfected into A549 cells yet affected cell death induction by CDDP, C2-ceramide, cadmium, etoposide, and mitoxantrone in an inducer-specific fashion. Whereas synthetic miRNA inhibitors (anti-miRNAs) targeting miR-181a and miR-630 failed to modulate the response of A549 to CDDP, pre-miR-181a and pre-miR-630 enhanced and reduced CDDP-triggered cell death, respectively. Pre-miR-181a and pre-miR-630 consistently modulated mitochondrial/postmitochondrial steps of the intrinsic pathway of apoptosis, including Bax oligomerization, mitochondrial transmembrane potential dissipation, and the proteolytic maturation of caspase-9 and caspase-3. In addition, pre-miR-630 blocked early manifestations of the DNA damage response, including the phosphorylation of the ataxia-telangiectasia mutated (ATM) kinase and of two ATM substrates, histone H2AX and p53. Pharmacologic and genetic inhibition of p53 corroborated the hypothesis that pre-miR-630 (but not pre-miR-181a) blocks the upstream signaling pathways that are ignited by DNA damage and converge on p53 activation. Pre-miR-630 arrested A549 cells in the G0-G1 phase of the cell cycle, correlating with increased levels of the cell cycle inhibitor p27(Kip1) as well as with reduced proliferation rates and resulting in greatly diminished sensitivity of A549 cells to the late S-G2-M cell cycle arrest mediated by CDDP. Altogether, these results identify miR-181a and miR-630 as novel modulators of the CDDP response in NSCLC.