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The analysis of exonic DNA from prostate cancers has identified recurrently mutated genes, but the spectrum of genome-wide alterations has not been profiled extensively in this disease. We sequenced the genomes of 57 prostate tumors and matched normal tissues to characterize somatic alterations and to study how they accumulate during oncogenesis and progression. By modeling the genesis of genomic rearrangements, we identified abundant DNA translocations and deletions that arise in a highly interdependent manner. This phenomenon, which we term "chromoplexy," frequently accounts for the dysregulation of prostate cancer genes and appears to disrupt multiple cancer genes coordinately. Our modeling suggests that chromoplexy may induce considerable genomic derangement over relatively few events in prostate cancer and other neoplasms, supporting a model of punctuated cancer evolution. By characterizing the clonal hierarchy of genomic lesions in prostate tumors, we charted a path of oncogenic events along which chromoplexy may drive prostate carcinogenesis.


Figure 1
Figure 1. Somatic Alterations in 57 Prostate Tumor Genomes
WGS was conducted on 55 prostate adenocarcinomas and two lung metastases from neuroendocrine prostate cancers (NEPC, *) along with paired normal DNA to detect somatic rearrangements and mutations. Gains and losses of DNA copy number at sites of recurrent SNCAs were detected with Affymetrix SNP 6.0 arrays (recurrent SCNAs were not assessed for sample P07-144, hatched lines). Bottom, cancer DNA purity was evaluated by assessing allelic ratios from sequence reads covering heterozygous single-nucleotide polymorphisms at sites of chromosomal deletion (Supplemental Experimental Procedures). ETS gene fusions (ERG, ETV1) were detected by sequencing and validated by fluorescence in situ hybridization (FISH). See also Tables S1–4 and Figure S1.
Figure 2
Figure 2. Integrated Analysis of Genomic Deletions and Rearrangements Reveals Signatures of Concurrent Alterations
(A) Three scenarios by which multiple DNA double-strand breaks may be repaired. Concerted repair with minimal loss of DNA (left) results in fusion breakpoints that map to adjacent positions in the reference genome. Loss of DNA at sites of double-strand breaks may result in simple deletions (middle) or “deletion bridges” (right) that span breakpoints from distinct fusions on the reference genome. Adjacent breakpoints or deletion bridges may provide evidence for chained rearrangements. (B) For the two breakpoints of each rearrangement (labeled A and B), the probability P of a second independently generated breakpoint (a or b) falling within the observed distance (L) was assessed based on the expected local rate of rearrangements (μlocal). The x- and y- coordinates represent the negative log of P for the two breakpoints in each fusion. Rearrangements near the upper right corner of the plot are unlikely to have arisen independently of other rearrangements. Observed rearrangements are compared to simulated and scrambled data. See also Figure S2.
Figure 3
Figure 3. The ChainFinder Algorithm
(A) ChainFinder creates a graph representation of genomic breakpoints that may be linked in chains by somatic fusions, statistical adjacency or deletion bridges. ChainFinder assigns two neighboring breakpoints to the same chain if the p-value for their independent generation (P) is rejected with a false-discovery rate below 10−2. For each cycle (closed path) within the graph, all scenarios are considered where one or more rearrangements in the cycle could have arisen independently. All rearrangements in a cycle are assigned to the same chain if every such scenario is rejected with a family-wise error rate below 10−2 across all scenarios. Please see the Supplemental Experimental Procedures for additional details. (B) Circos plot of chained rearrangements in a prostate adenocarcima (P09-1042). Rearrangements depicted in the same color arose within the same chain; fusions in gray were not assigned to a chain. The inner ring depicts copy number gains and losses in blue and red, respectively. (C) The false positive rate of ChainFinder was assessed using simulated and scrambled genomes based on observed rearrangements. (D) For observed, simulated and scrambled genomes, the longest chain was compared along with the portion of breakpoints in any chain. Median values, middle quartiles, and range are indicated. See also Figure S3.
Figure 4
Figure 4. Manifestations of Chromoplexy Vary by ETS Fusion Status
(A) Circos plots of rearrangement chains in representative tumors, grouped by the presence of ETS rearrangements and CHD1 disruption. Rearrangements in the same chain are depicted in one color. Rearrangements in gray were not assigned to a chain. The inner ring shows copy number gain and loss in red and blue, respectively. (B) Rearrangement chains in ETS+ tumors contain a greater proportion of inter-chromosomal fusions than chains in ETS tumors. In (B) and (D), box plots indicate median values, middle quartiles, and range. (C) The maximum number of chromosomes involved in a single rearrangement chain (y-axis), grouped by ETS status. The total number of breakpoints in chains in each tumor is depicted on the x-axis to allow comparison of tumors with similar degree of detectable chromoplexy. (D) ETS+ chromoplexy breakpoints are enriched near DNA that is highly expressed in 16 prostate tumor transcriptomes. See also Figure S4.
Figure 5
Figure 5. Chromoplexy May Coordinately Dysregulate Multiple Cancer Genes
(A) Chromoplectic chain of 27 somatic rearrangements across 6 chromosomes in tumor P05-3852, involving fusion of TMPRSS2 and ERG and disruptive rearrangement of SMAD4. (B) The putative tumor suppressor genes CDKN1B, ETV6 and ETV3 were lost in the context of deletion bridges in a 25-rearrangement chain affecting 3 chromosomes in PR-05-3595. In both panels, selected rearrangements were assessed by PCR of tumor and normal DNA. See also Figure S5 and Table S5C.
Figure 6
Figure 6. Clonality and Evolution of Prostate Cancer
(A) Schematic representation of the clonality assessment. The allelic fractions (AFs) of sequencing reads covering heterozygous SNPs were analyzed in order to assess the clonality of somatic DNA alterations. A hypothetical tumor is shown, composed of normal cells, a caner clone and a derivative subclone. The histograms indicate the expected SNP AFs within two deleted genes, A and B. The subclonal deletion of B yields a distinct distribution of AFs compared to the clonal deletion of A. (B) Selected deletions (top) and mutations (bottom) were classified as clonal or subclonal. Proportion test p-value is listed for the indicated comparisons. Independent samples (Barbieri et al., 2012) are included for support. (C) Example of clonal (TMPRSS2-ERG) and subclonal (CDKN1B) deletions from the same tumor. Histograms show the proportion of sequencing reads containing the reference allele for heterozygous SNPs in the deleted regions. A representative immunohistochemical stain for the CDKN1B protein p27 shows discrete subclonal positivity in prostate cancer. (D) Patterns of tumor evolution were inferred based on clonality estimates. Arrows indicate the direction of clonal-subclonal hierarchy between genes that are deleted in the same sample in multiple cases. Deleted genes are represented by circles with size and color intensity reflecting the frequency of overall deletions and subclonal deletions, respectively. Ratios along the arrows indicate the number of samples demonstrating directionality of the hierarchy out of samples with deletion of both genes (ratios in parentheses refer to additional samples; Barbieri et al., 2012). The inset shows a similar analysis of point mutations (Barbieri et al., 2012). (E) The number of recurrent SCNAs and cancer DNA purity were compared across tumors with major Gleason pattern 4 versus 3. See also Figure S6.
Figure 7
Figure 7. A Continuum Model for the Genomic Evolution of Prostate Cancer
Oncogenic aberrations may accumulate in cancer genomes gradually (left), by punctuated progression (middle) or in a single catastrophic event (right). Chromoplectic rearrangements and deletions induce a modest to large degree of genomic derangement over several successive events. As indicated at bottom, larger-scale rearrangements that affect broader swaths of the genome may be more difficult for a cell to survive, and may tend to require co-occurring oncogenic lesions to become fixed in a tumor. See also Figure S7.

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