Toward implementing virtual control groups in nonclinical safety studies.

Historical data from control groups in animal toxicity studies is currently mainly used for comparative purposes to assess validity and robustness of study results. Due to the highly controlled environment in which the studies are performed and the homogeneity of the animal collectives it has been proposed to use the historical data for building so-called virtual control groups, which could replace partly or entirely the concurrent control. This would constitute a substantial contribution to the reduction of animal use in safety studies. Before the concept can be implemented, the prerequisites regarding data collection, curation and statistical evaluation together with a validation strategy need to be identified to avoid any impairment of the study outcome and subsequent consequences for human risk assessment. To further assess and develop the concept of virtual control groups the transatlantic think tank for toxicology (t4) sponsored a workshop with stakeholders from the pharmaceutical and chemical industry, academia, FDA, pharmaceutical, contract research organizations (CROs), and non-governmental organizations in Washington, which took place in March 2023. This report summarizes the current efforts of a European initiative to share, collect and curate animal control data in a centralized database and the first approaches to identify optimal matching criteria between virtual controls and the treatment arms of a study as well as first reflections about strategies for a qualification procedure and potential pitfalls of the concept.

Animal safety studies are usually performed with three groups of animals where increasing amounts of the test chemical are given to the animals and one control group where the animals do not receive the test chemical. The design of such studies, the characteristics of the animals, and the measured parameters are often very similar from study to study. Therefore, it has been suggested that measurement data from the control groups could be reused from study to study to lower the total number of animals per study. This could reduce animal use by up to 25% for such standardized studies. A workshop was held to discuss the pros and cons of such a concept and what would have to be done to implement it without threatening the reliability of the study outcome or the resulting human risk assessment.

Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker.

Chronic kidney disease (CKD) affects 8 to 16% people worldwide, with an increasing incidence and prevalence of end-stage kidney disease (ESKD). The effective management of CKD is confounded by the inability to identify patients at high risk of progression while in early stages of CKD. To address this challenge, a renal biopsy transcriptome-driven approach was applied to develop noninvasive prognostic biomarkers for CKD progression. Expression of intrarenal transcripts was correlated with the baseline estimated glomerular filtration rate (eGFR) in 261 patients. Proteins encoded by eGFR-associated transcripts were tested in urine for association with renal tissue injury and baseline eGFR. The ability to predict CKD progression, defined as the composite of ESKD or 40% reduction of baseline eGFR, was then determined in three independent CKD cohorts. A panel of intrarenal transcripts, including epidermal growth factor (EGF), a tubule-specific protein critical for cell differentiation and regeneration, predicted eGFR. The amount of EGF protein in urine (uEGF) showed significant correlation (P < 0.001) with intrarenal EGF mRNA, interstitial fibrosis/tubular atrophy, eGFR, and rate of eGFR loss. Prediction of the composite renal end point by age, gender, eGFR, and albuminuria was significantly (P < 0.001) improved by addition of uEGF, with an increase of the C-statistic from 0.75 to 0.87. Outcome predictions were replicated in two independent CKD cohorts. Our approach identified uEGF as an independent risk predictor of CKD progression. Addition of uEGF to standard clinical parameters improved the prediction of disease events in diverse CKD populations with a wide spectrum of causes and stages.

Type 2 Diabetes Remission After Gastric Bypass: What Is the Best Prediction Tool for Clinicians?

BACKGROUND: Statistical models and scores have been recently suggested to predict remission of type 2 diabetes after bypass surgery, but their relevance in routine clinical practice still needs evaluation. Our objective was to assess these methods on a French cohort and to compare them with other easy-to-use models. METHODS: We investigated a cohort of 84 diabetic obese subjects who underwent Roux-en-Y gastric bypass surgery. Diabetes remission 1 year after surgery was defined based on the American Diabetes Association criteria. We tested six methods from the literature and four other models to predict remission of diabetes after bypass surgery using pre-operative bioclinical parameters. Predictive methods for diabetes remission were assessed using cross-validation error rates when appropriate. RESULTS: Sixty percent of the subjects had diabetes remission. Models from the literature had high error rates in our cohort (from 22.6 to 40.5 %), while published simple scoring systems behaved much better (15.9 and 16.7 %). Using other apprehensible models learned on our cohort did not improve the prediction error (from 17.2 to 19.9 %). CONCLUSIONS: We showed that the scoring system DiaRem is easy to use and provides the best prediction error (15.9 %) compared to other methods. We additionally propose a DiaRem score threshold of ≤6 for likely remission of a subject 1 year after surgery, which may be considered in clinical decision-making.

PTK2 expression and immunochemotherapy outcome in chronic lymphocytic leukemia.

Addition of rituximab (R) to fludarabine and cyclophosphamide (FC) has significantly improved patient outcomes in chronic lymphocytic leukemia (CLL). Whether baseline gene expression can identify patients who will benefit from immunochemotherapy over chemotherapy alone has not been determined. We assessed genome-wide expression of 300 pretreatment specimens from a subset of 552 patients in REACH, a study of FC or R-FC in relapsed CLL. An independent test set was derived from 282 pretreatment specimens from CLL8, a study of FC or R-FC in treatment-naïve patients. Genes specific for benefit from R-FC were determined by assessing treatment-gene interactions in Cox proportional hazards models. REACH patients with higher pretreatment protein tyrosine kinase 2 (PTK2) messenger RNA levels derived greater benefit from R-FC, with significant improvements in progression-free survival, independent of known prognostic factors in a multivariate model. Examination of PTK2 gene expression in CLL8 patients yielded similar results. Furthermore, PTK2 inhibition blunted R-dependent cell death in vitro. This retrospective analysis from 2 independent trials revealed that increased PTK2 expression is associated with improved outcomes for CLL patients treated with R-FC vs FC. PTK2 expression may be a useful biomarker for patient selection in future trials. These trials were registered at www.clinicaltrials.gov as #NCT00090051 (REACH) and #NCT00281918 (CLL8).

Cardiovascular risk markers associated with arterial calcification in patients with chronic kidney disease Stages 3 and 4.

BACKGROUND: The contribution of pro-inflammatory markers to cardiovascular (CV) risk and vascular calcification in chronic kidney disease (CKD) remains largely to be elucidated. We investigated the association between plasma levels of several biomarkers and calcification volume in three different vascular beds in CKD Stages 3 and 4 patients. METHODS: This is a cross-sectional, exploratory study in patients with an estimated glomerular filtration rate (eGFR) ≥20 and ≤45 mL/min/1.73 m2 and serum phosphorus ≥3.5 and <6.0 mg/dL enrolled in a previously published randomized, double blind, placebo-controlled single-centre trial. Ethylenediaminetetraacetic acid (EDTA) plasma samples were collected at baseline before patients received study medication and analysed for the presence of a number of biomarkers. Coronary artery calcium (CAC), thoracic aortic calcification (TAC) and abdominal aortic calcification (AAC) volumes were measured using standard electron-beam computed tomography protocols. Associations were adjusted for age, sex, smoking, body mass index, diabetes mellitus status, low-density lipoprotein cholesterol (LDL-C), systolic blood pressure and eGFR. RESULTS: Associations with CAC were found for ß2-microglobulin (B2M), fibroblast growth factor 23 (FGF23), interleukin-8 (IL-8) and IL-18. AAC was associated with: B2M, FGF23 and IL-2 receptor alpha (IL-2 RA). TAC was associated with: B2M, FGF23, IL-2 RA, IL-18 and tumour necrosis factor receptor type I. For most of the analysed biomarkers, there were non-significant trends of associations with calcification. CONCLUSIONS: This exploratory study found that elevated plasma levels of several inflammatory biomarkers are significantly associated with arterial calcification in CKD Stages 3 and 4 patients. A greater understanding of inflammation and calcification in CKD patients may help the development of CV risk-assessment algorithms for better management of these patients.

Inactivation of TP53 correlates with disease progression and low miR-34a expression in previously treated chronic lymphocytic leukemia patients.

In chronic lymphocytic leukemia (CLL) patients, disruptions of the TP53 tumor suppressor pathway by 17p13 deletion (del17p), somatic TP53 mutations, or downregulation of microRNA-34a have been associated with a poor prognosis. So far, the impact of the various TP53 defects has not been evaluated in a large cohort of previously treated and relapsed CLL patients. Here, we present the results of TP53 gene sequencing and fluorescence in situ hybridization for del17p in a phase 3 clinical trial (REACH [Rituximab in the Study of Relapsed Chronic Lymphocytic Leukemia]). Of the 457 patients, 52 had TP53 mutations and 37 had del17p. In 24 (46%) of the TP53 mutated patients, no del17p was found and in 9 of the del17p patients, no TP53 mutation was identified. Based on a predicted proportion of TP53 disruption, a complete disruption of TP53 function, either by a combination of point mutations and/or del17p, was associated with a high risk for disease progression. Progression-free survival of patients with a heterozygous TP53 mutation was not significantly different from patients with a completely intact TP53 locus. In addition, only a complete loss of TP53 function correlated with low microRNA-34a expression levels. This trial was registered at www.clinicaltrials.gov as #NCT00090051.

Quantitative chemical proteomics profiling differentiates erlotinib from gefitinib in EGFR wild-type non-small cell lung carcinoma cell lines.

Although both erlotinib and gefitinib target the EGF receptor (EGFR), erlotinib is effective in patients with EGFR wild-type or mutated tumors, whereas gefitinib is only beneficial for patients with activating mutations. To determine whether these differences in clinical outcomes can be attributed to their respective protein interaction profiles, a label-free, quantitative chemical proteomics study was conducted. Using this method, 24 proteins were highlighted in the binding profiles of erlotinib and gefitinib. Unlike gefinitib, erlotinib displaced the ternary complex formed by integrin-linked kinase (ILK), α-parvin, and PINCH (IPP). The docking of erlotinib in the three-dimensional structure of ILK showed that erlotinib has the ability to bind to the ATP-binding site, whereas gefitinib is unlikely to bind with high affinity. As the IPP complex has been shown to be involved in epithelial-to-mesenchymal transition (EMT) and erlotinib sensitivity has been correlated with EMT status, we used a cellular model of inducible transition and observed that erlotinib prevented EMT in a more efficient way than gefitinib by acting on E-cadherin expression as well as on IPP levels. A retrospective analysis of the MERIT trial indicated that, besides a high level of E-cadherin, a low level of ILK could be linked to clinical benefit with erlotinib. In conclusion, we propose that, in an EGFR wild-type context, erlotinib may have a complementary mode of action by inhibiting IPP complex activities, resulting in the slowing down of the metastatic process of epithelial tumors.

Effect of FCGR2A and FCGR3A variants on CLL outcome.

Polymorphisms of activating Fc-γ receptors (FCGRs) on natural killer cells and macrophages result in variable affinity for immunoglobulin G1 monoclonal antibodies and subsequently modulate antibody-dependent cellular cytotoxicity (ADCC) activity. Whether single-nucleotide polymorphisms of FCGRs correlate with survival of chronic lymphocytic leukemia (CLL) patients treated with a monoclonal antibody containing regimen is unclear. We assessed the FCGR3A and FCGR2A genotype of patients enrolled in the REACH trial, where patients received fludarabine and cyclophosphamide (FC) or rituximab plus FC (R-FC). FCGR3A and FCGR2A polymorphisms did not demonstrate prognostic significance in the FC arm (P = .42 and P = .64, respectively) or R-FC arm (P = .41 and P = .88, respectively) with respect to progression free survival. Patients with intermediate affinity genotypes (FV and HR) benefited significantly from addition of rituximab (hazard ratio = 0.55 [0.37-0.8 CI]; P = .0017 and hazard ratio = 0.63 [0.44-0.9 CI]; P = .011, respectively). Similar benefit was suggested for patients with high- affinity VV and HH (hazard ratio = 0.86 [0.4-1.84 CI]; P = .7 and hazard ratio = 0.7 [0.41-1.18 CI]; P = .18, respectively) and low-affinity FF and RR (hazard ratio = 0.85 [0.56-1.29 CI]; P = .44 and hazard ratio = 0.82 [0.47-1.42 CI]; P = .48, respectively). Overall, our results suggest that FCGR2A and FCGR3A polymorphisms do not significantly influence the outcomes of relapsed or refractory CLL patients treated with FC or the monoclonal antibody regimen R-FC.

A longitudinal study of gene expression in healthy individuals.

BACKGROUND: The use of gene expression in venous blood either as a pharmacodynamic marker in clinical trials of drugs or as a diagnostic test requires knowledge of the variability in expression over time in healthy volunteers. Here we defined a normal range of gene expression over 6 months in the blood of four cohorts of healthy men and women who were stratified by age (22-55 years and > 55 years) and gender. METHODS: Eleven immunomodulatory genes likely to play important roles in inflammatory conditions such as rheumatoid arthritis and infection in addition to four genes typically used as reference genes were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR), as well as the full genome as represented by Affymetrix HG U133 Plus 2.0 microarrays. RESULTS: Gene expression levels as assessed by qRT-PCR and microarray were relatively stable over time with approximately 2% of genes as measured by microarray showing intra-subject differences over time periods longer than one month. Fifteen genes varied by gender. The eleven genes examined by qRT-PCR remained within a limited dynamic range for all individuals. Specifically, for the seven most stably expressed genes (CXCL1, HMOX1, IL1RN, IL1B, IL6R, PTGS2, and TNF), 95% of all samples profiled fell within 1.5-2.5 Ct, the equivalent of a 4- to 6-fold dynamic range. Two subjects who experienced severe adverse events of cancer and anemia, had microarray gene expression profiles that were distinct from normal while subjects who experienced an infection had only slightly elevated levels of inflammatory markers. CONCLUSION: This study defines the range and variability of gene expression in healthy men and women over a six-month period. These parameters can be used to estimate the number of subjects needed to observe significant differences from normal gene expression in clinical studies. A set of genes that varied by gender was also identified as were a set of genes with elevated expression in a subject with iron deficiency anemia and another subject being treated for lung cancer.

A pairwise alignment algorithm which favors clusters of blocks.

Pairwise sequence alignments aim to decide whether two sequences are related and, if so, to exhibit their related domains. Recent works have pointed out that a significant number of true homologous sequences are missed when using classical comparison algorithms. This is the case when two homologous sequences share several little blocks of homology, too small to lead to a significant score. On the other hand, classical alignment algorithms, when detecting homologies, may fail to recognize all the significant biological signals. The aim of the paper is to give a solution to these two problems. We propose a new scoring method which tends to increase the score of an alignment when "blocks" are detected. This so-called Block-Scoring algorithm, which makes use of dynamic programming, is worth being used as a complementary tool to classical exact alignments methods. We validate our approach by applying it on a large set of biological data. Finally, we give a limit theorem for the score statistics of the algorithm.

Identification of stop codon readthrough genes in Saccharomyces cerevisiae.

We specifically sought genes within the yeast genome controlled by a non-conventional translation mechanism involving the stop codon. For this reason, we designed a computer program using the yeast database genomic regions, and seeking two adjacent open reading frames separated only by a unique stop codon (called SORFs). Among the 58 SORFs identified, eight displayed a stop codon bypass level ranging from 3 to 25%. For each of the eight sequences, we demonstrated the presence of a poly(A) mRNA. Using isogenic [PSI(+)] and [psi(-)] yeast strains, we showed that for two of the sequences the mechanism used is a bona fide readthrough. However, the six remaining sequences were not sensitive to the PSI state, indicating either a translation termination process independent of eRF3 or a new stop codon bypass mechanism. Our results demonstrate that the presence of a stop codon in a large ORF may not always correspond to a sequencing error, or a pseudogene, but can be a recoding signal in a functional gene. This emphasizes that genome annotation should take into account the fact that recoding signals could be more frequently used than previously expected.

Towards a computational model for -1 eukaryotic frameshifting sites.

MOTIVATION: Unconventional decoding events are now well acknowledged, but not yet well formalized. In this study, we present a bioinformatics analysis of eukaryotic -1 frameshifting, in order to model this event. RESULTS: A consensus model has already been established for -1 frameshifting sites. Our purpose here is to provide new constraints which make the model more precise. We show how a machine learning approach can be used to refine the current model. We identify new properties that may be involved in frameshifting. Each of the properties found was experimentally validated. Initially, we identify features of the overall model that are to be simultaneously satisfied. We then focus on the following two components: the spacer and the slippery sequence. As a main result, we point out that the identity of the primary structure of the so-called spacer is of great importance. AVAILABILITY: Sequences of the oligonucleotides in the functional tests are available at http://www.igmors.u-psud.fr/rousset/bioinformatics/.

Translational readthrough of the PDE2 stop codon modulates cAMP levels in Saccharomyces cerevisiae.

The efficiency of translation termination in yeast can vary several 100-fold, depending on the context around the stop codon. We performed a computer analysis designed to identify yeast open reading frames (ORFs) containing a readthrough motif surrounding the termination codon. Eight ORFs were found to display inefficient stop codon recognition, one of which, PDE2, encodes the high-affinity cAMP phosphodiesterase. We demonstrate that Pde2p stability is very impaired by the readthrough-dependent extension of the protein. A 20-fold increase in readthrough of PDE2 was observed in a [PSI+] as compared with a [psi-] strain. Consistent with this observation, an important increase in cAMP concentration was observed in suppressor backgrounds. These results provide a molecular explanation for at least some of the secondary phenotypes associated with suppressor backgrounds.