Evidence-based laboratory medicine in oncology drug development: from biomarkers to diagnostics.

BACKGROUND: The promise of targeted therapies in molecularly defined subsets of cancer has led to a transformation of the process of drug development in oncology. To target cancer successfully and precisely requires high-quality translational data. Such data can be generated by the use of biomarkers that answer key questions in drug development. CONTENT: Translational data for aiding in decision-making and driving cancer drug development can be generated by systematic assessments with biomarkers. Types of biomarkers that support decisions include: pharmacodynamic assessments for selecting the best compound or dosage; assessment of early tumor response with tissue biomarkers and imaging, mutation, and other assessment strategies for patient selection; and the use of markers of organ injury to detect toxicity and improve safety. Tactics used to generate biomarker data include fit-for-purpose assay validation and real-time biomarker assessments. Successfully translated and clinically informative biomarkers can mature into novel companion diagnostic tests that expand the practice of laboratory medicine. SUMMARY: Systematic biomarker assessments are a key component of the clinical development of targeted therapies for cancer. The success of these biomarker assessments requires applying basic principles of laboratory medicine to generate the data required to make informed decisions. Successful biomarkers can transition into diagnostic tests that expand the laboratory medicine armamentarium.

Correlation between arterial FDG uptake and biomarkers in peripheral artery disease.

OBJECTIVES: A prospective, multicenter (18)fluorine-fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET)/computed tomography (CT) imaging study was performed to estimate the correlations among arterial FDG uptake and atherosclerotic plaque biomarkers in patients with peripheral artery disease. BACKGROUND: Inflammation within atherosclerotic plaques is associated with instability of the plaque and future cardiovascular events. Previous studies have shown that (18)F-FDG-PET/CT is able to quantify inflammation within carotid artery atherosclerotic plaques, but no studies to date have investigated this correlation in peripheral arteries with immunohistochemical confirmation. METHODS: Thirty patients across 5 study sites underwent (18)F-FDG-PET/CT imaging before SilverHawk atherectomy (FoxHollow Technologies, Redwood City, California) for symptomatic common or superficial femoral arterial disease. Vascular FDG uptake (expressed as target-to-background ratio) was measured in the carotid arteries and aorta and femoral arteries, including the region of atherectomy. Immunohistochemistry was performed on the excised atherosclerotic plaque extracts, and cluster of differentiation 68 (CD68) level as a measure of macrophage content was determined. Correlations between target-to-background ratio of excised lesions, as well as entire arterial regions, and CD68 levels were determined. Imaging was performed during the 2 weeks before surgery in all cases. RESULTS: Twenty-one patients had adequate-quality (18)F-FDG-PET/CT peripheral artery images, and 34 plaque specimens were obtained. No significant correlation between lesion target-to-background ratio and CD68 level was observed. CONCLUSIONS: There were no significant correlations between CD68 level (as a measure of macrophage content) and FDG uptake in the peripheral arteries in this multicenter study. Differences in lesion extraction technique, lesion size, the degree of inflammation, and imaging coregistration techniques may have been responsible for the failure to observe the strong correlations with vascular FDG uptake observed in previous studies of the carotid artery and in several animal models of atherosclerosis.

A gene expression signature that classifies human atherosclerotic plaque by relative inflammation status.

BACKGROUND: Atherosclerosis is a complex disease requiring improvements in diagnostic techniques and therapeutic treatments. Both improvements will be facilitated by greater exploration of the biology of atherosclerotic plaque. To this end, we carried out large-scale gene expression analysis of human atherosclerotic lesions. METHODS AND RESULTS: Whole genome expression analysis of 101 plaques from patients with peripheral artery disease identified a robust gene signature (1514 genes) that is dominated by processes related to Toll-like receptor signaling, T-cell activation, cholesterol efflux, oxidative stress response, inflammatory cytokine production, vasoconstriction, and lysosomal activity. Further analysis of gene expression in microdissected carotid plaque samples revealed that this signature is differentially expressed in macrophage-rich and smooth muscle cell-containing regions. A quantitative PCR gene expression panel and inflammatory composite score were developed on the basis of the atherosclerotic plaque gene signature. When applied to serial sections of carotid plaque, the inflammatory composite score was observed to correlate with histological and morphological features related to plaque vulnerability. CONCLUSIONS: The robust mRNA expression signature identified in the present report is associated with pathological features of vulnerable atherosclerotic plaque and may be useful as a source of biomarkers and targets of novel antiatherosclerotic therapies.