7444 Nucleic Acids Research, 2009, Vol. 37, No. 22 Figure 2. Distribution of the variations found by (A) the presence of the THEMIS motif and (B) substitution type. Variations found in dbSNP were excluded. The data presented in (A) show the number of variations that occur (or not) in the context of the THEMIS motif with one mismatch allowed. For a more compete explanation of the THEMIS motif, see text. Only the diﬀerences in (A) between the distribution of the variations in the tumor and the other two types of tissue are signiﬁcant (P = 0.046). Figure 3. Genetic heterogeneity in prostate cancer. Data were obtained using the same cloning/sequencing protocol utilized for measuring genomic variation rates, with the inclusion of a degenerate PCR step prior to cloning (see ‘Materials and Methods’ section). All clones come from the same tumor sample. Numbers indicate clone number (e.g. T2 = tumor clone #2). The three clones grouped together in the bottom contain wild-type sequence. Variations are capitalized and shown in highlight. Only the minimum sequence needed to show the maximum degree of heterogeneity is shown. These variations are not present in dbSNP build 129. DISCUSSION The average number of somatic events reported here in six prostate cancers is orders of magnitude higher than previous reports (4–9). Some of those studies analyzed coding sequences (4–7), while others noncoding (8,9). Thus, selection of coding region mutations during tumor evolution cannot be responsible for this diﬀerence in vari- ation frequencies. In contrast, either the tumor type (prostate) or the PCR-free methodology we used may be responsible for our ﬁnding. PCR-based analysis of various tumors has revealed less extensive but signiﬁcant tumor- to-tumor mutation and mutated ‘driver’ gene heterogene- ity (4–7). Most of the mutations reported here are in intergenic regions and thus presumably ‘passengers’ (i.e. not tumor ‘drivers’; 16). If distinct cells of the same tumor contain diﬀerent passengers, then they may also contain diﬀerent drivers. This possibility can only be assessed by single cell/molecule methods such as the one we employed here. Before embarking on full-scale cancer genome projects with techniques that may miss most mutations in heterogeneous tumors it may be worthwhile ﬁrst to use single cell/molecule approaches to classify tumors based on their degree of heterogeneity. Then the appro- priate method can be employed to the full project based on tumor type (heterogeneous or not). We report here an average tumor mutation frequency that signiﬁcantly exceeds the current estimates (4–9). We believe that this ﬁnding has important biological con- sequences for prostate tumorigenesis. In addition to ﬁnding signiﬁcantly higher mutation frequency in tumor DNA, we observed that prostate tumors contain distinct types of mutations: unlike normal prostate and blood from the same patient, tumor mutations ﬁt the THEMIS motif (11), suggesting a common etiology. We do not know the exact molecular mechanism generating these