Genomic biomarkers for cancer assessment: implementation challenges for laboratory practice

Genomic biomarkers are an emerging class of laboratory tests, which present special implementation challenges for clinical laboratory services, compared to conventional laboratory tests. These challenges, which include analytical, bioinformatics, bioethical, interpretation and commercialization issues, represent real obstacles to widespread implementation of these tests. Technical challenges include the capacity to detect and identify many different kinds of markers for different diseases in a short time period, capacity to identify simultaneously gene rearrangements, amplification, inhibition, deletions and replications. Bioinformatics challenges include rapid analysis of genomic data, as well as the cross reference to other genomic data, and to other laboratory tests. Bioethical issues relate to consent to retain and use genetic data, which may be obtained inadvertently during analysis for genomic markers. Interpretation challenges include observations that the particular genomic markers may not be independent variables, as other undetected genomic alterations could invalidate or alter genomic marker interpretation. Further, as early experience with predictive genetic markers for cancer has shown, proprietary commercial interests may conflict with public health values of identifying genomic markers in subject populations. Based on our 10 years of experience with genomic biomarkers, important implementation strategies for genomic markers include development of:Standard high throughput analyzers capable of detecting any alteration of any genomic variant at any time. Bioinformatics analysis online, coupled to stored patient data. Laboratory service framework that preserves confidentiality but integrates genomic data with other laboratory tests. Laboratory service framework, which links consents, genomic analysis, reports to both specimen and data repositories. Overall, the laboratory service challenges for genomic markers are to manage very large analytical sets and very large data sets in finite time with responsible interpretation, all within finite funding. To meet these challenges, implementation strategies beyond the one disease, one diagnosis, one genomic marker concept must begin now.