bluuebunny/crossref_metadata_2025_split huggingface dataset:
The efficiency of clinical trial designs for predictive biomarker validation
Authors: Young KY , Laird A. , Zhou XH 
Published: June 2010

Background The rapid advance of molecular genetic technology and of molecular diagnostics companies have set the stage for a new era in personalized treatments. Biomarkers such as gene expressions may be integrated into the anatomically based tumor-node-metastasis staging system to provide information for risk stratification and treatment selection. With the assumption that preliminary results show evidence that a biomarker has predictive value, the marker-based designs are geared to assess the purported predictive value in a clinical trial. Purpose In this article, we compared the efficiency of the traditional design, which does not involve a biomarker, to several alternative designs in terms of the sample size required in each trial. Methods We first derived the variance formulas for the two-sample t-tests under the various designs when the biomarker assay is imperfect, and then conducted numerical and simulation studies to evaluate the performance of the various designs. Results Based on numerical and simulation studies, we conclude that the marker-based strategy designs are less efficient than the traditional design in general. Since the biomarker assay is imperfect in a realistic setting, the estimated sample size for each alternative design is influenced by the sensitivity and specificity of the assay and the prevalence of the biomarker in the population of interest as well as the parameters involved in a standard sample size calculation. Limitations Due to limitations of a simulation study, it is not clear whether our results can be generalized to other parameter settings that are different from the ones used in the simulation study. Conclusions The marker-based strategy designs are less efficient than the traditional design in general. If there is no treatment effect among marker-negative patients, it is still feasible to use the marker-based strategy design I if the assay sensitivity is high. If the treatment effect among marker-negative patients is half of the effect among marker-positive patients, the marker prevalence must be relatively high and the sensitivity of the assay must be very high for the marker-based strategy design I to approximate the efficiency of the traditional design. The efficiency of the marker-based strategy design II relative to the traditional design is low in all scenarios considered under the current study. Clinical Trials 2010; 7: 557—566. http://ctj.sagepub.com
Bayesian adaptive randomization designs for targeted agent development
Authors: Lee J. Jack , Xuemin Gu  , Suyu Liu  
Published: June 2010

Background With better understanding of the disease’s etiology and mechanism, many targeted agents are being developed to tackle the root cause of problems, hoping to offer more effective and less toxic therapies. Targeted agents, however, do not work for everyone. Hence, the development of target agents requires the evaluation of prognostic and predictive markers. In addition, upon the identification of each patient’s marker profile, it is desirable to treat patients with best available treatments in the clinical trial accordingly. Methods Many designs have recently been proposed for the development of targeted agents. These include the simple randomization design, marker stratified design, marker strategy design, efficient targeted design, etc. In contrast to the frequentist designs with equal randomization, we propose novel Bayesian adaptive randomization designs that allow evaluating treatments and markers simultaneously, while providing more patients with effective treatments according to the patients’ marker profiles. Early stopping rules can be implemented to increase the efficiency of the designs. Results Through simulations, the operating characteristics of different designs are compared and contrasted. By carefully choosing the design parameters, types I and II errors can be controlled for Bayesian designs. By incorporating adaptive randomization and early stopping rules, the proposed designs incorporate rational learning from the interim data to make informed decisions. Bayesian design also provides a formal way to incorporate relevant prior information. Compared with previously published designs, the proposed design can be more efficient, more ethical, and is also more flexible in the study conduct. Limitations Response adaptive randomization requires the response to be assessed in a relatively short time period. The infrastructure must be set up to allow timely and more frequent monitoring of interim results. Conclusion Bayesian adaptive randomization designs are distinctively suitable for the development of multiple targeted agents with multiple biomarkers. Clinical Trials 2010; 7: 584—596. http://ctj.sagepub.com
Assessing contamination and compliance in the prostate component of the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial
Authors: Pinsky Paul F , Black Amanda , Kramer Barnett S , Miller Anthony , Prorok Philip C , Berg Christine 
Published: June 2010

Background Recently, the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial published 7-year complete prostate cancer mortality results, which showed no benefit of screening with prostate specific antigen (PSA) and digital rectal examination (DRE). An issue of concern was the substantial level of ‘contamination’, or use of PSA and DRE in control arm men. Purpose To provide a detailed description of contamination in PLCO. Methods Surveys inquiring about the most recent PSA and DRE use were given to a sample of control arm men throughout the screening phase of PLCO (years 0—5). A probability model was utilized to translate survey results into actual frequency counts of tests. To assess the impact of contamination, Surveillance, Epidemiology, and End Results (SEER) incidence rates from the pre-screening era (1985—1987) as well as contemporaneous rates, were applied to PLCO person-years of observation. Results Of 38,350 control arm men, 2427 were surveyed. Pre-trial screening and college education were statistically significantly associated with increased contamination rates. The estimated mean number of screening PSAs (DREs) in the control arm was 2.7 (1.1); this compares to 5.0 (3.5) in the screened arm. 1984 and 2538 prostate cancers were observed in the control and screened arms, respectively, during the screening phase. In the absence of screening, 960 and 949 would have been expected; with contemporaneous incidence rates, 1630 and 1611 were expected. Limitations Due to the limitations of the surveys, in terms of both reach and scope, the exact level of PSA and DRE use in control arm men cannot be known. Conclusions Use of prostate screening by control arm men was substantial, but also substantially less than in screened arm men. Detailed quantitative analyses of screening use across arms are critical for understanding current and future findings from the prostate component of PLCO. Clinical Trials 2010; 7: 303—311. http:// ctj.sagepub.com
Predicting missing quality of life data that were later recovered: an empirical comparison of approaches
Authors: Fielding Shona , Fayers Peter , Ramsay Craig 
Published: June 2010

Background and Purpose The aim was to compare simple imputation, multiple imputation, and modeling approaches to deal with ‘missing’ quality of life data. Data were obtained from five clinical trials, which employed a reminder system for follow-up questionnaires. Previous studies have compared imputation strategies by artificially removing data according to prespecified mechanisms. Our approach differs from previous study as actual collected data are utilized. Methods Data obtained by reminder were initially treated as missing. These missing values were imputed using a variety of simple and multiple imputation strategies. The trials were analyzed using the imputed datasets, and the resulting treatment effects compared to analyses using the full dataset including responses following reminders. A repeated measures model was also carried out on the available data and the pattern mixture models were employed. The accuracy of the different strategies was assessed by calculating the bias seen in the calculated treatment difference compared to the actual observed treatment difference. Results Baseline carried forward or last value carried forward were shown to be the best simple imputation methods in this setting. Multiple imputation using a regression model or predictive mean match model tended to provide treatment difference estimates with the least bias when compared to the actual observed data. Pattern mixture models did not perform well. Overall, the multiple imputation procedures were generally the least biased approaches. Limitations A number of imputation and modeling procedures have been investigated but this list is not exhaustive. All the example datasets come from the same data source and perhaps studies from additional disease areas would have been useful. However, we feel the results are generalizable to other quality of life outcomes and clinical areas. Conclusions Multiple imputation is recommended for missing quality of life data as it makes the assumption of missing at random which in the quality of life setting is more plausible than the assumption of missing completely at random for which most simple imputation methods are based. Pattern mixture models can be complex and did not perform well in this setting. Clinical Trials 2010; 7: 333—342. http://ctj.sagepub.com
Properties of CD34+ CML stem/progenitor cells that correlate with different clinical responses to imatinib mesylate
Authors: Jiang Xiaoyan , Forrest Donna , Nicolini Franck , Turhan Ali , Guilhot Joelle , Yip Calvin , Holyoake Tessa , Jorgensen Heather , Lambie Karen , Saw Kyi Min , Pang Emily , Vukovic Ranko , Lehn Paeta , Ringrose Ashley , Yu Miao , Brinkman Ryan R. , Smith Clay , Eaves Allen , Eaves Connie 
Published: June 2010

Abstract
Imatinib mesylate (IM) induces clinical remissions in chronic-phase chronic myeloid leukemia (CML) patients but IM resistance remains a problem. We recently identified several features of CML CD34+ stem/progenitor cells expected to confer resistance to BCR-ABL-targeted therapeutics. From a study of 25 initially chronic-phase patients, we now demonstrate that some, but not all, of these parameters correlate with subsequent clinical response to IM therapy. CD34+ cells from the 14 IM nonresponders demonstrated greater resistance to IM than the 11 IM responders in colony-forming cell assays in vitro (P < .001) and direct sequencing of cloned transcripts from CD34+ cells further revealed a higher incidence of BCR-ABL kinase domain mutations in the IM nonresponders (10%-40% vs 0%-20% in IM responders, P < .003). In contrast, CD34+ cells from IM nonresponders and IM responders were not distinguished by differences in BCR-ABL or transporter gene expression. Interestingly, one BCR-ABL mutation (V304D), predicted to destabilize the interaction between p210BCR-ABL and IM, was detectable in 14 of 20 patients. T315I mutant CD34+ cells found before IM treatment in 2 of 20 patients examined were preferentially amplified after IM treatment. Thus, 2 properties of pretreatment CML stem/progenitor cells correlate with subsequent response to IM therapy. Prospective assessment of these properties may allow improved patient management.
Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients
Authors: Broyl Annemiek , Hose Dirk , Lokhorst Henk , de Knegt Yvonne , Peeters Justine , Jauch Anna , Bertsch Uta , Buijs Arjan , Stevens-Kroef Marian , Beverloo H. Berna , Vellenga Edo , Zweegman Sonja , Kersten Marie-Josée , van der Holt Bronno , el Jarari Laila , Mulligan George , Goldschmidt Hartmut , van Duin Mark , Sonneveld Pieter 
Published: June 2010

Abstract
To identify molecularly defined subgroups in multiple myeloma, gene expression profiling was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/GMMG-HD4 trial. Hierarchical clustering identified 10 subgroups; 6 corresponded to clusters described in the University of Arkansas for Medical Science (UAMS) classification, CD-1 (n = 13, 4.1%), CD-2 (n = 34, 1.6%), MF (n = 32, 1.0%), MS (n = 33, 1.3%), proliferation-associated genes (n = 15, 4.7%), and hyperdiploid (n = 77, 24.1%). Moreover, the UAMS low percentage of bone disease cluster was identified as a subcluster of the MF cluster (n = 15, 4.7%). One subgroup (n = 39, 12.2%) showed a myeloid signature. Three novel subgroups were defined, including a subgroup of 37 patients (11.6%) characterized by high expression of genes involved in the nuclear factor kappa light-chain-enhancer of activated B cells pathway, which include TNFAIP3 and CD40. Another subgroup of 22 patients (6.9%) was characterized by distinct overexpression of cancer testis antigens without overexpression of proliferation genes. The third novel cluster of 9 patients (2.8%) showed up-regulation of protein tyrosine phosphatases PRL-3 and PTPRZ1 as well as SOCS3. To conclude, in addition to 7 clusters described in the UAMS classification, we identified 3 novel subsets of multiple myeloma that may represent unique diagnostic entities.
Proteomic cell surface phenotyping of differentiating acute myeloid leukemia cells
Authors: Hofmann Andreas , Gerrits Bertran , Schmidt Alexander , Bock Thomas , Bausch-Fluck Damaris , Aebersold Rudolf , Wollscheid Bernd 
Published: June 2010

Abstract
Immunophenotyping by flow cytometry or immunohistochemistry is a clinical standard procedure for diagnosis, classification, and monitoring of hematologic malignancies. Antibody-based cell surface phenotyping is commonly limited to cell surface proteins for which specific antibodies are available and the number of parallel measurements is limited. The resulting limited knowledge about cell surface protein markers hampers early clinical diagnosis and subclassification of hematologic malignancies. Here, we describe the mass spectrometry based phenotyping of 2 all-trans retinoic acid treated acute myeloid leukemia model systems at an unprecedented level to a depth of more than 500 membrane proteins, including 137 bona fide cell surface exposed CD proteins. This extensive view of the leukemia surface proteome was achieved by developing and applying new implementations of the Cell Surface Capturing (CSC) technology. Bioinformatic and hierarchical cluster analysis showed that the applied strategy reliably revealed known differentiation-induced abundance changes of cell surface proteins in HL60 and NB4 cells and it also identified cell surface proteins with very little prior information. The extensive and quantitative analysis of the cell surface protein landscape from a systems biology perspective will be most useful in the clinic for the improved subclassification of hematologic malignancies and the identification of new drug targets.
Multiple functions of Ldb1 required for β-globin activation during erythroid differentiation
Authors: Song Sang-Hyun , Kim AeRi , Ragoczy Tobias , Bender M. A. , Groudine Mark , Dean Ann 
Published: June 2010

AbstractLdb1 and erythroid partners SCL, GATA-1, and LMO2 form a complex that is required to establish spatial proximity between the β-globin locus control region and gene and for transcription activation during erythroid differentiation. Here we show that Ldb1 controls gene expression at multiple levels. Ldb1 stabilizes its erythroid complex partners on β-globin chromatin, even though it is not one of the DNA-binding components. In addition, Ldb1 is necessary for enrichment of key transcriptional components in the locus, including P-TEFb, which phosphorylates Ser2 of the RNA polymerase C-terminal domain for efficient elongation. Furthermore, reduction of Ldb1 results in the inability of the locus to migrate away from the nuclear periphery, which is necessary to achieve robust transcription of β-globin in nuclear transcription factories. Ldb1 contributes these critical functions at both embryonic and adult stages of globin gene expression. These results implicate Ldb1 as a factor that facilitates nuclear relocation for transcription activation.
A high-throughput pipeline for the design of real-time PCR signatures
Authors: Vijaya Satya Ravi , Kumar Kamal , Zavaljevski Nela , Reifman Jaques 
Published: June 2010

Abstract

Background
Pathogen diagnostic assays based on polymerase chain reaction (PCR) technology provide high sensitivity and specificity. However, the design of these diagnostic assays is computationally intensive, requiring high-throughput methods to identify unique PCR signatures in the presence of an ever increasing availability of sequenced genomes.

Results
We present the Tool for PCR Signature Identification (TOPSI), a high-performance computing pipeline for the design of PCR-based pathogen diagnostic assays. The TOPSI pipeline efficiently designs PCR signatures common to multiple bacterial genomes by obtaining the shared regions through pairwise alignments between the input genomes. TOPSI successfully designed PCR signatures common to 18 Staphylococcus aureus genomes in less than 14 hours using 98 cores on a high-performance computing system.

Conclusions
TOPSI is a computationally efficient, fully integrated tool for high-throughput design of PCR signatures common to multiple bacterial genomes. TOPSI is freely available for download at http://www.bhsai.org/downloads/topsi.tar.gz.
Inferring linkage disequilibrium from non-random samples†
Authors: Wang Minghui , Jia Tianye , Jiang Ning , Wang Lin , Hu Xiaohua , Luo Zewei 
Published: June 2010

Abstract

Background
Linkage disequilibrium (LD) plays a fundamental role in population genetics and in the current surge of studies to screen for subtle genetic variants affecting complex traits. Methods widely implemented in LD analyses require samples to be randomly collected, which, however, are usually ignored and thus raise the general question to the LD community of how the non-random sampling affects statistical inference of genetic association. Here we propose a new approach for inferring LD using a sample un-randomly collected from the population of interest.

Results
Simulation study was conducted to mimic generation of samples with various degrees of non-randomness from the simulated populations of interest. The method developed in the paper outperformed its rivals in adequately estimating the disequilibrium parameters in such sampling schemes. In analyzing a 'case and control' sample with β-thalassemia, the current method presented robustness to non-random sampling in contrast to two commonly used methods.

Conclusions
Through an intensive simulation study and analysis of a real dataset, we demonstrate the robustness of the proposed method to non-randomness in sampling schemes and the significant improvement of the method to provide accurate estimates of the disequilibrium parameter. This method provides a route to improve statistical reliability in association studies.
High gene expression of inflammatory markers and IL-17A correlates with severity of injection site reactions of Atlantic salmon vaccinated with oil-adjuvanted vaccines
Authors: Mutoloki Stephen , Cooper Glenn A , Marjara Inderjit S , Koop Ben F , Evensen Øystein 
Published: June 2010

AbstractBackgroundTwo decades after the introduction of oil-based vaccines in the control of bacterial and viral diseases in farmed salmonids, the mechanisms of induced side effects manifested as intra-abdominal granulomas remain unresolved. Side effects have been associated with generation of auto-antibodies and autoimmunity but the underlying profile of inflammatory and immune response has not been characterized. This study was undertaken with the aim to elucidate the inflammatory and immune mechanisms of granuloma formation at gene expression level associated with high and low side effect (granuloma) indices.Groups of Atlantic salmon parr were injected intraperitoneally with oil-adjuvanted vaccines containing either high or low concentrations ofAeromonas salmonicidaorMoritella viscosaantigens in order to induce polarized (severe and mild) granulomatous reactions. The established granulomatous reactions were confirmed by gross and histological methods at 3 months post vaccination when responses were known to have matured. The corresponding gene expression patterns in the head kidneys were profiled using salmonid cDNA microarrays followed by validation by real-time quantitative PCR (qPCR). qPCR was also used to examine the expression of additional genes known to be important in the adaptive immune response.ResultsGranulomatous lesions were observed in all vaccinated fish. The presence of severe granulomas was associated with a profile of up-regulation of innate immunity-related genes such as complement factors C1q and C6, mannose binding protein, lysozyme C, C-type lectin receptor, CD209, Cathepsin D, CD63, LECT-2, CC chemokine and metallothionein. In addition, TGF-β (p = 0.001), IL-17A (p = 0.007) and its receptor (IL-17AR) (p = 0.009) representing TH17 were significantly up-regulated in the group with severe granulomas as were arginase and IgM. None of the genes directly reflective of TH1 T cell lineage (IFN-γ, CD4) or TH2 (GATA-3) responses were differentially expressed.ConclusionsGranulomatous reactions following vaccination with oil-based vaccines in Atlantic salmon have the profile of strong expression of genes related to innate immune responses. The expression of TGF-β, IL-17A and its receptor suggests an involvement of TH17 T cell lineage and is in conformity with strong infiltration of neutrophils and macrophages into inflamed areas. Arginase upregulation shows that macrophages in these reactions are alternatively activated, indicating also a TH2-profile. To what extent the expression of IL-17A and its receptor reflects an autoimmune vaccine-based reaction remains elusive but would be in conformity with previous observations of autoimmune reactions in salmon when vaccinated with oil-based vaccines.
Identification of functional TFAP2A and SP1 binding sites in new TFAP2A-modulated genes
Authors: Orso Francesca , Corà Davide , Ubezio Benedetta , Provero Paolo , Caselle Michele , Taverna Daniela 
Published: June 2010

AbstractBackgroundDifferent approaches have been developed to dissect the interplay between transcription factors (TFs) and their cis-acting sequences on DNA in order to identify TF target genes. Here we used a combination of computational and experimental approaches to identify novel direct targets of TFAP2A, a key TF for a variety of physiological and pathological cellular processes. Gene expression profiles of HeLa cells either silenced for TFAP2A by RNA interference or not were previously compared and a set of differentially expressed genes was revealed.ResultsThe regulatory regions of 494 TFAP2A-modulated genes were analyzed for the presence of TFAP2A binding sites, employing the canonical TFAP2A Positional Weight Matrix (PWM) reported in Jasparhttp://jaspar.genereg.net/. 264 genes containing at least 2 high score TFAP2A binding sites were identified, showing a central role in "Cellular Movement" and "Cellular Development". In an attempt to identify TFs that could cooperate with TFAP2A, a statistically significant enrichment for SP1 binding sites was found for TFAP2A-activated but not repressed genes. The direct binding of TFAP2A or SP1 to a random subset of TFAP2A-modulated genes was demonstrated by Chromatin ImmunoPrecipitation (ChIP) assay and the TFAP2A-driven regulation of DCBLD2/ESDN/CLCP1 gene studied in details.ConclusionsWe proved that our computational approaches applied to microarray selected genes are valid tools to identify functional TF binding sites in gene regulatory regions as confirmed by experimental validations. In addition, we demonstrated a fine-tuned regulation of DCBLD2/ESDN transcription by TFAP2A.