			Home About us Contact

Marker Validation (marker + validation)

Distribution by Scientific Domains

Life Sciences	75%

Selected Abstracts

Unsupervised immunophenotypic profiling of chronic lymphocytic leukemia

CYTOMETRY, Issue 3 2006
Luzette K. Habib
Abstract Background Proteomics and functional genomics have revolutionized approaches to disease classification. Like proteomics, flow cytometry (FCM) assesses concurrent expression of many proteins, with the advantage of using intact cells that may be differentially selected during analysis. However, FCM has generally been used for incremental marker validation or construction of predictive models based on known patterns, rather than as a tool for unsupervised class discovery. We undertook a retrospective analysis of clinical FCM data to assess the feasibility of a cell-based proteomic approach to FCM by unsupervised cluster analysis. Methods Multicolor FCM data on peripheral blood (PB) and bone marrow (BM) lymphocytes from 140 consecutive patients with B-cell chronic lymphoproliferative disorders (LPDs), including 81 chronic lymphocytic leukemia (CLLs), were studied. Expression was normalized for CD19 totals, and recorded for 10 additional B-cell markers. Data were subjected to hierarchical cluster analysis using complete linkage by Pearson's correlation. Analysis of CLL in PB samples (n = 63) discovered three major clusters. One cluster (14 patients) was skewed toward "atypical" CLL and was characterized by high CD20, CD22, FMC7, and light chain, and low CD23. The remaining two clusters consisted almost entirely (48/49) of cases recorded as typical BCLL. The smaller "typical" BCLL cluster differed from the larger cluster by high CD38 (P = 0.001), low CD20 (P = 0.001), and low CD23 (P = 0.016). These two typical BCLL clusters showed a trend toward a difference in survival (P = 0.1090). Statistically significant cluster stability was demonstrated by expanding the dataset to include BM samples, and by using a method of random sampling with replacement. Conclusions This study supports the concept that unsupervised immunophenotypic profiling of FCM data can yield reproducible subtypes of lymphoma/chronic leukemia. Expanded studies are warranted in the use of FCM as an unsupervised class discovery tool, akin to other proteomic methods, rather than as a validation tool. © 2006 International Society for Analytical Cytology [source]

Development of molecular markers linked to the wheat powdery mildew resistance gene Pm4b and marker validation for molecular breeding

PLANT BREEDING, Issue 2 2008
Y. J. Yi
Abstract Powdery mildew, caused by Blumeria graminis (DC.) E.O. Speer f. sp. tritici, is an important disease in wheat (Triticum aestivum L.). Bulk segregant analysis (BSA) was employed to identify SRAP (sequence-related amplified polymorphism), sequence tagged site (STS) and simple sequence repeat (SSR) markers linked to the Pm4b gene, which confers good resistance to powdery mildew in wheat. Out of 240 SRAP primer combinations tested, primer combinations Me8/Em7 and Me12/Em7 yielded 220-bp and 205-bp band, respectively, each of them associated with Pm4b. STS- 241 also linked to Pm4b with a genetic distance of 4.9 cM. Among the eight SSR markers located on wheat chromosome 2AL, Xgwm382 was found to be polymorphic and linked to Pm4b with a genetic distance of 11.8 cM. Further analysis was carried out using the four markers to investigate marker validation for marker-assisted selection (MAS). The results showed that a combination of the linked markers STS,241, Me8/Em7,220 and Xgwm382 could be used for marker-assisted selection of the resistance gene Pm4b in wheat breeding programmes. [source]

Validation of Surrogate Markers in Multiple Randomized Clinical Trials with Repeated Measurements

BIOMETRICAL JOURNAL, Issue 8 2003
Ariel Alonso
Abstract Part of the recent literature on the validation of biomarkers as surrogate endpoints proposes to undertake the validation exercise in a multi-trial context which led to a definition of validity in terms of the quality of both trial level and individual level association between the surrogate and the true endpoints (Buyse et al., 2000). These authors concentrated on continuous univariate responses. However, in many randomized clinical studies, repeated measurements are encountered on either or both endpoints. When both the surrogate and true endpoints are measured repeatedly over time, one is confronted with the modelling of bivariate longitudinal data. In this work, we show how such a joint model can be implemented in the context of surrogate marker validation. In addition, another challenge in this setting is the formulation of a simple and meaningful concept of "surrogacy". We propose the use of a new measure, the so-called variance reduction factor, to evaluate surrogacy at the trial and individual level. On the other hand, most of the work published in this area assume that only one potential surrogate is going to be evaluated. We also show that this concept will let us evaluate surrogacy when more than one surrogate variable is available for the analysis. The methodology is illustrated on data from a meta-analysis of five clinical trials comparing antipsychotic agents for the treatment of chronic schizophrenia. [source]