Molecular assays for the diagnosis of minimal residual head-and-neck cancer: methods, reliability, pitfalls, and solutions.

The prognosis of cancer patients is determined by the radicalness of treatment: residual tumor cells will grow out and develop in manifest local recurrences, regional recurrences, and distant metastases. Classical diagnostic methods such as radiology and histopathology have limited sensitivities, and only by molecular techniques can minimal residual disease be detected. In tissue samples containing the normal tissue counterpart of a tumor, only tumor-specific markers can be exploited, whereas in other samples, tissue-specific markers can be used. At present, there are two main methodologies in use, one based on antigen-antibody interaction and the other based on amplified nucleic acids. The most commonly used nucleic acid markers are mutations or alterations in tumor DNA (tumor-specific markers) or differentially expressed mRNA (tissue-specific markers). Many reports and reviews have been published on the assessment of minimal residual disease by molecular markers, showing either positive or negative clinical correlations. One of the main reasons for these contradictory findings is the technical difficulty in finding the small numbers of tumor cells in the large number of normal cells, which necessitates sensitivities of the assays up to 1 tumor cell in 2 x 10(7) normal cells. These assays often are complex, demand considerable experience, and usually are laborious. In this review, we will address a number of the technical issues related to molecular assays for tumor cell detection that make use of nucleic acids as markers. Many difficulties in data interpretation are at least in part because of technical details that might have been solved by the incorporation of one or more appropriate controls. We hope that this review clarifies a number of these issues and help clinicians and investigators interested in this field to understand and weigh the contradictory findings in the published studies. This will help move the field forward and facilitate clinical implementation.