Association Between Results of a Gene Expression Signature Assay and Recurrence-Free Interval in Patients With Stage II Colon Cancer in Cancer and Leukemia Group B 9581 (Alliance).

Purpose: Conventional staging methods are inadequate to identify patients with stage II colon cancer (CC) who are at high risk of recurrence after surgery with curative intent. ColDx is a gene expression, microarray-based assay shown to be independently prognostic for recurrence-free interval (RFI) and overall survival in CC. The objective of this study was to further validate ColDx using formalin-fixed, paraffin-embedded specimens collected as part of the Alliance phase III trial, C9581.

Identification and validation of an anthracycline/cyclophosphamide-based chemotherapy response assay in breast cancer.

Background: There is no method routinely used to predict response to anthracycline and cyclophosphamide-based chemotherapy in the clinic; therefore patients often receive treatment for breast cancer with no benefit. Loss of the Fanconi anemia/BRCA (FA/BRCA) DNA damage response (DDR) pathway occurs in approximately 25% of breast cancer patients through several mechanisms and results in sensitization to DNA-damaging agents. The aim of this study was to develop an assay to detect DDR-deficient tumors associated with loss of the FA/BRCA pathway, for the purpose of treatment selection.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data.

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery.

Implications for powering biomarker discovery studies.

This study examined variations in gene expression between FFPE blocks within tumors of individual patients. Microarray data were used to measure tumor heterogeneity within and between patients and disease states. Data were used to determine the number of samples needed to power biomarker discovery studies.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods.

Accurate molecular characterization of formalin-fixed, paraffin-embedded tissues by microRNA expression profiling.

Formalin-fixed, paraffin-embedded tissues are an invaluable tool for biomarker discovery and validation. As these archived specimens are not always compatible with modern genomic techniques such as gene expression arrays, we assessed the use of microRNA (miRNA) as an alternative means for the reliable molecular characterization of formalin-fixed, paraffin-embedded tissues. Expression profiling using two different microarray platforms and multiple mouse and human formalin-fixed, paraffin-embedded tissue types resulted in the correlation ratios of miRNA expression levels between frozen and fixed tissue pairs ranging from 0.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues.

Analyzing micro-RNA expression using microarrays.

The discovery of micro-RNAs (miRNAs) and the growing appreciation of the importance of micro-RNAs in the regulation of gene expression are driving increasing interest in miRNA expression profiling. Early studies have suggested prominent roles for these genetically encoded regulatory molecules in a variety of normal biological processes and diseases, particularly cancer. However, the field of miRNA expression profiling is in its infancy.

A gene expression map of Arabidopsis thaliana development.

Regulatory regions of plant genes tend to be more compact than those of animal genes, but the complement of transcription factors encoded in plant genomes is as large or larger than that found in those of animals. Plants therefore provide an opportunity to study how transcriptional programs control multicellular development. We analyzed global gene expression during development of the reference plant Arabidopsis thaliana in samples covering many stages, from embryogenesis to senescence, and diverse organs.