Normalization of oligonucleotide arrays based on the least-variant set of genes

<p>Abstract</p> <p>Background</p> <p>It is well known that the normalization step of microarray data makes a difference in the downstream analysis. All normalization methods rely on certain assumptions, so differences in results can be traced to different sensitivities to violation of the assumptions. Illustrating the lack of robustness, in a striking spike-in experiment all existing normalization methods fail because of an imbalance between up- and down-regulated genes. This means it is still important to develop a normalization method that is robust against violation of the standard assumptions</p> <p>Results</p> <p>We develop a new algorithm based on identification of the least-variant set (LVS) of genes across the arrays. The array-to-array variation is evaluated in the robust linear model fit of pre-normalized probe-level data. The genes are then used as a reference set for a non-linear normalization. The method is applicable to any existing expression summaries, such as MAS5 or RMA.</p> <p>Conclusion</p> <p>We show that LVS normalization outperforms other normalization methods when the standard assumptions are not satisfied. In the complex spike-in study, LVS performs similarly to the ideal (in practice unknown) housekeeping-gene normalization. An R package called lvs is available in <url>http://www.meb.ki.se/~yudpaw</url>.</p

Detecting differential expression in microarray data: comparison of optimal procedures

BACKGROUND: Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, the false discovery rate (FDR) is the key tool for assessing the significance of these test statistics. Two recent papers have generalized two aspects: Storey et al. (2005) have introduced a likelihood ratio test statistic for two-sample situations that has desirable theoretical properties (optimal discovery procedure, ODP), but uses standard FDR assessment; Ploner et al. (2006) have introduced a multivariate local FDR that allows incorporation of standard error information, but uses the standard t-statistic (fdr2d). The relationship and relative performance of these methods in two-sample comparisons is currently unknown. METHODS: Using simulated and real datasets, we compare the ODP and fdr2d procedures. We also introduce a new procedure called S2d that combines the ODP test statistic with the extended FDR assessment of fdr2d. RESULTS: For both simulated and real datasets, fdr2d performs better than ODP. As expected, both methods perform better than a standard t-statistic with standard local FDR. The new procedure S2d performs as well as fdr2d on simulated data, but performs better on the real data sets. CONCLUSION: The ODP can be improved by including the standard error information as in fdr2d. This means that the optimality enjoyed in theory by ODP does not hold for the estimated version that has to be used in practice. The new procedure S2d has a slight advantage over fdr2d, which has to be balanced against a significantly higher computational effort and a less intuititive test statistic

Filtering genes to improve sensitivity in oligonucleotide microarray data analysis

Many recent microarrays hold an enormous number of probe sets, thus raising many practical and theoretical problems in controlling the false discovery rate (FDR). Biologically, it is likely that most probe sets are associated with un-expressed genes, so the measured values are simply noise due to non-specific binding; also many probe sets are associated with non-differentially-expressed (non-DE) genes. In an analysis to find DE genes, these probe sets contribute to the false discoveries, so it is desirable to filter out these probe sets prior to analysis. In the methodology proposed here, we first fit a robust linear model for probe-level Affymetrix data that accounts for probe and array effects. We then develop a novel procedure called FLUSH (Filtering Likely Uninformative Sets of Hybridizations), which excludes probe sets that have statistically small array-effects or large residual variance. This filtering procedure was evaluated on a publicly available data set from a controlled spiked-in experiment, as well as on a real experimental data set of a mouse model for retinal degeneration. In both cases, FLUSH filtering improves the sensitivity in the detection of DE genes compared to analyses using unfiltered, presence-filtered, intensity-filtered and variance-filtered data. A freely-available package called FLUSH implements the procedures and graphical displays described in the article

Stability of circulating miRNA in saliva: The influence of sample associated pre-analytical variables

Background and aims: Increasing evidence supports the practicability of salivary cell-free (cf) miRNA as liquid biopsy markers in cancers. Its successful translation in the clinical setting requires reproducible approaches for saliva manipulation, in order to control for pre-analytical variables influencing miRNA stability. This study aims to define the optimal conditions to maintain the integrity of saliva during collection, transport and processing with respect to cf-miRNA quantification. Materials and methods: Saliva was collected from 20 healthy subjects and 8 oral cancer patients. Two sampling methods were tested and different storage temperatures and times were evaluated. Salivary expression level of target miRNAs was quantified by qPCR. Comparison between group mean values at specific conditions were performed using paired t-tests. Agreement between measurements was evaluated using a Bland-Altman plot. Results: Different collection methods revealed comparable levels of salivary miR-484 and miR-106b-5p in both subject cohorts. MiRNAs were stable for up to 48 h at 4 °C in saliva supernatant, showing significant alteration after 96 h. Mid-term storage of supernatant at -20 °C decreased miRNA stability significantly compared to standard -80 °C. Conclusions: Cf-miRNA in saliva were slightly altered by collection methods and storage conditions, both in healthy and in pathological contexts, and remained stable for a period of time compatible with main clinical routine needs

Identification of recurrent regions of copy-number variants across multiple individuals

10.1186/1471-2105-11-147BMC Bioinformatics1

Periodontitis Stage III–IV, Grade C and Correlated Factors: A Histomorphometric Study

Background: Periodontitis is a disease that leads to serious functional and esthetic dysfunctions. Periodontitis exists in different forms, and its etiology is related to multiple component causes. Two key processes involved in the evolution of this pathology are angiogenesis and inflammatory infiltrate. The aim of this study was to understand if important factors such as smoking, gender, age, plaque, pus, and probing pocket depth could influence the histomorphological pattern of generalized stage III-IV, grade C periodontitis (GPIII-IVC), which is a particular form of periodontitis. Methods: Eighteen subjects with GPIII-IVC were enrolled in this study. The percentage of inflammatory cells and the vascular area were measured and evaluated in relation to each periodontal disease-associated factor. Results: Females showed a significant increase in the percentage of inflammatory cells compared to males (6.29% vs. 2.28%, p-value = 0.020) and it was higher in non-smokers than in smokers (4.56% vs. 3.14%, p-value = 0.048). Young patients showed a significant increase in vascular area percentage compared to older patients (0.60% vs. 0.46%, p-value = 0.0006) and this percentage was also higher in non-smokers compared to smokers (0.41% vs. 0.55%, p-value = 0.0008). The vascular area was also more than halved in subjects with residual plaque on tooth surfaces (0.74% vs. 0.36%, p-value = 0.0005). Conclusions: These results suggested that even if these factors are commonly related to the worsening of periodontal status, some of them (pus and periodontal probing depth (PPD)) do not affect the inflammatory and vascular patterns

VKORC1 and CYP2C9 polymorphisms related to adverse events in case-control cohort of anticoagulated patients

Vitamin K antagonists (VKAs) are highly effective but have a narrow therapeutic index and require routine monitoring of the INR. The primary aim of pharmacogenetics (PGx) is to optimize patient care, achieving drug treatments that are personalized according to the genetic profile of each patient. The best-characterized genes involved in VKA PGx involve pharmacokinetics (VKORC1) and pharmacodynamics (CYP2C9) of VKA metabolism. The role of these genes in clinical outcomes (bleeding and thrombosis) during oral anticoagulant (OAC) therapy is controversial. The aim of the present study was to evaluate any potential association between genotype VKORC1 and CYP2C9 and adverse events (hemorrhagic and/or thrombotic), during initiation and long-term VKA treatment, in Caucasian patients. Furthermore, we aimed to determine if the concomitant prescription of other selected drugs affected the association between genotype and adverse events.We performed a retrospective, matched case-control study to determine associations between multiple gene variants, drug intake, and any major adverse effects in anticoagulated patients, monitored in 2 Italian anticoagulation clinics.Our results show that anticoagulated patients have a high risk of adverse events if they are carriers of 1 or more genetic polymorphisms in the VKORC1 (rs9923231) and CYP2C9 (rs1799853 and rs1057910) genes.Information on CYP2C9 and VKORC1 variants may be useful to identify individualized oral anticoagulant treatment for each patient, improve management and quality of VKA anticoagulation control, and monitor drug surveillance in pharmacovigilance programs

Immune Checkpoint Inhibitors in Malignant Pleural Mesothelioma: A Systematic Review and Meta-Analysis

Many clinical trials have investigated the role of ICIs in PM, with contrasting results. We performed a systematic review and meta-analysis of clinical trials testing single-agent anti-Programmed Death -1 (PD-1)/Programmed Death-Ligand 1 (PD-L1), anti-Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) or combined treatment in PM patients, analyzing response and survival rate as well as safety data. We selected 17 studies including 2328 patients. Both OS and PFS rates were significantly higher with combined ICI treatments than with single agent anti-PD-1/PD-L1 (p < 0.001 and p = 0.006, respectively) or anti CTLA-4 (p < 0.001) treatments. ORR and DCR for all ICI treatments were 20% (95% CI 13–27%) and 56% (95% CI 45–67%), respectively, and they did not significantly differ between combined and single agent treatments (p = 0.088 and p = 0.058, respectively). The 12-month OS and 6-month PFS rates did not differ significantly (p = 0.0545 and p = 0.1464, respectively) among pre-treated or untreated patients. Combined ICI treatments had a significantly higher rate of Adverse Events (AEs) (p = 0.01). PD-L1-positive patients had a higher probability of response and survival. In conclusion, combined ICI treatments have higher efficacy than single agents but are limited by higher toxicity. Efficacy was independent of treatment line, so a customized sequential strategy should still be speculated. PD-L1 expression could influence response to ICIs; however, reliable biomarkers are warranted