In order to circumvent this potential problem, we also analyzed formalin ﬁxed normal tissue from the same slides, in addition to non-ﬁxed blood DNA from the same patients. We purposely chose to analyze relatively advanced prostate tumors (Gleason score 6–7), reasoning that failure to identify an increased alteration frequency by this point in tumor evolution may indicate that genomic instability does not play a major role in prostate cancer progression. After sequencing 100 kb of total DNA from blood lymphocytes, normal prostates and tumor prostates taken from six men with prostate cancer, we identiﬁed 46 variations in the tumors, 30 in the normal prostates and 26 in the blood DNAs. Each of these variations was conﬁrmed in independent sequencing reactions using both forward and reverse primers. Excluding variations found in dbSNP build 129 (www.ncbi.nlm.nih.gov/SNP/; presumed to be polymorphisms) resulted in 20 variations remaining in the tumors, 5 in normal prostates and 4 in the blood DNA. The only statistically signiﬁcant diﬀerences were between the mean tumor and normal prostate DNA variation frequency, and the mean tumor and blood DNA variation frequency (Figure 1A; see ‘Materials and Methods’ section). Although our analysis is based on distinct sequences from each sample type (normal prostate, tumor and blood), the randomness of the cloning methodology and of the analyzed data (evidenced by e.g. G/C content and chromosomal distri- bution; Supplementary Figure S2) makes it possible to measure variation frequencies across each type of genome. Subtracting genomic variation frequencies between tumor and normal prostate can thus estimate the frequency of small-scale somatic events in the tumor. The diﬀerence between tumor and normal prostate varia- tion frequencies shown in Figure 1A corresponds to 1.8 (±1.0) million somatic alterations per prostate tumor cell genome. The relatively high standard deviation can be attributed to the existence of both tumors with higher (2.6 ± 0.6 million) and lower (1.0 ± 0.36 million) genomic instability frequencies (Supplementary Figure S3), a ﬁnding evident by the distribution of the variation fre- quency per sample (Figure 1B). The absolute number of variations and base pairs sequenced per sample is pre- sented in Supplementary Table S1, along with the sequence surrounding each variation. Distinct etiologies may result in speciﬁc types of variations in the tumor or in a speciﬁc DNA sequence context. Thus, we decided to test these variations for the presence of a speciﬁc motif we have previously found to be overrepresented at the sites of tumor DNA mutations in several genes (THEMIS motif; 11). We report that variations in the tumor DNA occur in the context of the THEMIS motif (with one mismatch allowed) signiﬁcantly more often (78%) than in the normal prostate and blood DNA (33%; two-sided P = 0.046) (Figure 2A), suggesting distinct molecular etiology in the tumors. In contrast, the distribution of the variations by substitution type did not vary signiﬁcantly between tumor and controls (Figure 2B). The methodology we utilized for estimating variation frequencies was based on the premise that prostate Nucleic Acids Research, 2009, Vol. 37, No. 22 7443 Figure 1. Genomic variation rate is signiﬁcantly higher in prostate tumors. Variation rates were calculated by our cloning/sequencing protocol (see ‘Materials and Methods’ section). Variations found in dbSNP build 129 were excluded. (A) Mean genomic variation rate. Mean variation rate = mean number of variations/Kb sequenced. The mean genomic variation rate is signiﬁcantly diﬀerent between prostate tumor and the other two tissue types (normal prostate and blood; P < 0.05). (B) Individual genomic variation rate in six prostate cancer patients. Variation rate = number of variations/Kb sequenced. Normal, normal prostate; Tumor, prostate tumor. When not visible, the blood rate is identical to the normal prostate rate, except for sample 1, for which no blood was available. tumors may be genetically heterogeneous. Although the results presented in Figure 1A suggest a signiﬁcant fre- quency of genomic instability in prostate tumors, they do not address the issue of cancer heterogeneity. In order to probe the existence of heterogeneity in prostate cancer, we employed the same methodology that we used to measure variation frequencies, but with the addition of a degenerate PCR step before cloning (see ‘Materials and Methods’ section). This modiﬁcation resulted in the gen- eration of multiple individual sequences from a small number (10–15) of the same genomic regions for both tumor and control DNA, after sequencing 60–100 clones per sample. The ﬁrst prostate tumor sample we analyzed showed extensive heterogeneity in one of those genomic regions, speciﬁcally in the tumor (Figure 3). A diﬀerent tumor sample showed a lower degree of heterogeneity (two variations in each of three genomic regions, one of these regions being the same region shown in Figure 3). Thus, we conclude that there is signiﬁcant but variable degree of genetic heterogeneity in prostate tumor genomes. Likewise, prostate tumors show a variable degree of genomic instability (Figure 1B).