State of the art survey of the buccal micronucleus assay--a first stage in the HUMN(XL) project initiative.

The study of DNA damage in exfoliated buccal cells is a minimally invasive method for monitoring populations for exposure to genotoxic agents. The presence of micronuclei (MN) and other nuclear anomalies within these cells has been shown to be associated with genetic defects in genome maintenance, accelerated ageing, genotoxic damage and some degenerative diseases. To identify important information gaps regarding these biomarkers, a new initiative was launched within the framework of the HUman MicroNucleus (HUMN) collaborative programme, the HUMN(XL) project ('XL' designating eXfoLiated cell). An invitation to join the project was sent out together with a questionnaire to all laboratories that have published on the buccal micronucleus assay. Overall, 188 messages were delivered and 58 laboratories from 25 countries agreed to participate (43 contributing data). The questionnaire was designed to collect methodological information regarding the laboratory's performance of the assay and to assess the extent and type of epidemiological data that are routinely collected. The results provide an overview of the most commonly used methods for buccal cell collection and preparation, slide preparation, staining, scoring criteria and an evaluation of epidemiological data, including demographics, genetic background, gender, health status, occupation, exposure, lifestyle and dietary habit. According to this survey, a potential base of 15 103 subjects can be included in future pooled analyses. A number of protocol discrepancies emerged, implying that method standardization is a major priority. The results of this survey will contribute to (i) identify technical and epidemiological key variables that impact on buccal MN frequency in human populations, (ii) drive the design of future intra- and interlaboratory validation studies and (iii) determine the role of MN frequency and other biomarkers, in monitoring genomic damage and predicting cancer and other degenerative diseases.