Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. METHODS: The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling-based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. RESULTS: On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. CONCLUSION: Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias

Microarray-based classifiers and prognosis models identify subgroups with distinct clinical outcomes and high risk of AML transformation of myelodysplastic syndrome

The diagnosis of myelodysplastic syndrome (MDS) currently relies primarily on the morphologic assessment of the patient's bone marrow and peripheral blood cells. Moreover, prognostic scoring systems rely on observer-dependent assessments of blast percentage and dysplasia. Gene expression profiling could enhance current diagnostic and prognostic systems by providing a set of standardized, objective gene signatures. Within the Microarray Innovations in LEukemia study, a diagnostic classification model was investigated to distinguish the distinct subclasses of pediatric and adult leukemia, as well as MDS. Overall, the accuracy of the diagnostic classification model for subtyping leukemia was approximately 93%, but this was not reflected for the MDS samples giving only approximately 50% accuracy. Discordant samples of MDS were classified either into acute myeloid leukemia (AML) or

TRARESA: a tissue microarray-based hospital system for biomarker validation and discovery

Formalin fixed and paraffin embedded tissue (FFPE) collections in pathology departments are the largest resource for retrospective biomedical research studies. Based on the literature analysis of FFPE related research, as well as our own technical validation, we present the Translational Research Arrays (TRARESA), a tissue microarray centred, hospital based, translational research conceptual framework for both validation and/or discovery of novel biomarkers. TRARESA incorporates the analysis of protein, DNA and RNA in the same samples, correlating with clinical and pathological parameters from each case, and allowing (a) the confirmation of new biomarkers, disease hypotheses and drug targets, and (b) the postulation of novel hypotheses on disease mechanisms and drug targets based on known biomarkers. While presenting TRARESA, we illustrate the use of such a comprehensive approach. The conceptualisation of the role of FFPE-based studies in translational research allows the utilisation of this commodity, and adds to the hypothesis-generating armamentarium of existing high-throughput technologies.

Tissue microarray study for classification of breast tumors

Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erb132 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of breast tumors. (C) 2003 Elsevier Inc. All rights reserved.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

An international standardization programme towards the application of gene expression profiling in routine leukaemia diagnostics: the Microarray Innovations in LEukemia study prephase

Gene expression profiling has the potential to enhance current methods for the diagnosis of haematological malignancies. Here, we present data on 204 analyses from an international standardization programme that was conducted in 11 laboratories as a prephase to the Microarray Innovations in LEukemia (MILE) study. Each laboratory prepared two cell line samples, together with three replicate leukaemia patient lysates in two distinct stages: (i) a 5-d course of protocol training, and (ii) independent proficiency testing. Unsupervised, supervised, and r(2) correlation analyses demonstrated that microarray analysis can be performed with remarkably high intra-laboratory reproducibility and with comparable quality and reliability.

Antibody-targeted nanoparticles for cancer therapy

In recent years, nanoparticulate-mediated drug delivery research has examined a full spectrum of nanoparticles that can be used in diagnostic and therapeutic cancer applications. A key aspect of this technology is in the potential to specifically target the nanoparticles to diseased cells using a range of molecules, in particular antibodies. Antibody-nanoparticle conjugates have the potential to elicit effective targeting and release of therapeutic targets at the disease site, while minimizing off-target side effects caused by dosing of normal tissues. This article provides an overview of various antibody-conjugated nanoparticle strategies, focusing on the rationale of cell-surface receptors targeted and their potential clinical application.

Llama antibody fragments have good potential for application as HIV-1 topical microbicides

There is an urgent global need for preventative strategies against HIV-1 infections. Llama heavy-chain antibody fragments (VHH) are a class of molecules recently described as potent cross-clade HIV-1 entry inhibitors. We studied the potential of a VHH-based microbicide in an application-oriented fashion. We show that VHH can be inexpensively produced in high amounts in the GRAS organism S. cerevisiae, resulting in very pure, and endotoxin free product. VHH are very stable under conditions they might encounter during transport, storage or use by women. We developed active formulations of VHH in aqueous gel and compressed and lyophilized tablets for controlled release from an intra vaginal device. The release profile of the VHH from e.g. a vaginal ring suggests sufficient bioavailability and protective concentration of the molecule at the mucosal site at the moment of the infection. The ex vivo penetration kinetics through human tissues show that the VHH diffuse into the mucosal layer and open the possibility to create a second defense layer either by blocking the HIV receptor binding sites or by blocking the receptors of immune cells in the mucosa. In conclusion, our data show that VHH have

Recent Innovations in Antibody-Mediated, Targeted Particulate Nanotechnology and Implications for Advanced Visualisation and Drug Delivery

Research into the targeting of drug substances to a specific disease site has enjoyed sustained activity for many decades. The reason for such fervent activity is the considerable clinical advantages that can be gained when the delivery system plays a pivotal role in determining where the drug is deposited. When compared to conventional formulations where no such control exists, such as parenteral and oral systems, the sophisticated targeting device can reduce side effects and limit collateral damage to surrounding normal tissue. No more so is this important than in the area of oncology when dose-limiting side effects are often encountered as an ever present difficulty. In this review, the types of colloidal carrier commonly used in targeted drug delivery are discussed, such as gold and polymeric colloids. In particular, the process of attaching targeting capabilities is considered, with reference to antibody technologies used as the targeting motifs. Nanotechnology has brought together a means to carry both a drug and targeting ligand in self-contained constructs and their applications to both clinical therapy and diagnosis are discussed.

An antibody-lectin sandwich assay for quantifying protein glycoforms.

We describe an antibody-lectin sandwich assay for quantitation of glycoforms of proteins. The assay uses deglycosylated IgG antibody immobilized on a microtiter plate to capture the protein of interest from the sample. The particular glycoform is then identified by reaction with biotin-labeled lectin, which is measured using streptavidin/alkaline phosphatase. The assay can be adapted to quantitate any protein’s glycoforms by simply substituting the antibody and lectin with specific alternatives,