Meta-analysis of the p53 mutation database for mutant p53 biological activity reveals a methodologic bias in mutation detection

Abstract

Purpose: Analyses of the pattern of p53 mutations have been essential for epidemiologic studies linking carcinogen exposure and cancer. We were concerned by the inclusion of dubious reports in the p53 databases that could lead to controversial analysis prejudicial to the scientific community.

Experimental design: We used the universal mutation database p53 database (21,717 mutations) combined with a new p53 mutant activity database (2,300 mutants) to perform functional analysis of 1,992 publications reporting p53 alterations. This analysis was done using a statistical approach similar to that of clinical meta-analyses.

Results: This analysis reveals that some reports of infrequent mutations are associated with almost normal activities of p53 proteins. These particular mutations are frequently found in studies reporting multiple mutations in one tumor, silent mutations, or lacking mutation hotspots. These reports are often associated with particular methodologies, such as nested PCR, for which key controls are not satisfactory.

Conclusions: We show the importance of accurate functional analysis before inferring any genetic variation. The quality of the p53 databases is essential in order to prevent erroneous analysis and/or conclusions. The availability of functional data from our new p53 web site (http://p53.free.fr and http://www.umd.be:2072/) will allow functional prescreening to identify potential artifactual data.