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The most common G4 DNA-forming sequence, totaling 6,675 instances and accounting for ~1.6% of the total G4 tracts genome-wide, was “gggtggggggaggggggaggg”, which characterizes several
Fig. 2. G4 DNA elicits translocations in cancer genomes. Panel A, plot of fraction of translocation breakpoints or control genomic positions (y-axis) occurring within 5 bp of hg38 genomic coordinates mapping G4 DNA-forming sequences (x-axis). Brown, translocation breakpoints in cancer genomes. Green, 0.2, 0.4, 0.6, 0.8, 1.0 and 10.0 kb before (left) and after (right) cancer translocation breakpoints. Gray, random genomic coordinates. Panel B, number of translocation breakpoints (mean ± SD) plotted for patients with (brown) and without (green) breakpoints at G4 DNA-forming sequences. Panels C and D, bar graphs of fraction of patients without (panel C) or with (panel D) translocation breakpoints at G4 DNA-forming sequences harboring pathologic mutations in the top 20 cancer-mutated genes. Panel E, net fraction of cancer patients with translocation breakpoints at G4 DNA-forming sequences harboring pathologic mutations in the top 10 most mutated genes; only hits with a Pa0.05 > 0.8 were recorded. Panel F, bar graph of percent transposable elements (TE) harboring G4 DNA-forming sequences in hg38 (orange) and at cancer translocation breakpoints (blue); all seq, all G4 DNA-forming sequences at SVA elements; main seq, most common G4 DNA-forming sequence at SVA retrotransposons (see Panel G). Panel G, list of most common G4 DNA-forming sequence at SVA elements (top); COSMIC ID, COSMIC tumor identification number; Tumor type, PRC, prostate cancer; OVC, ovarian cancer; UTC, uterine cancer; PAC, pancreatic cancer; Hg38 coor, genomic coordinate of translocation breakpoint within G4 DNA-forming sequence; TE, SVA lineage; Tot trans BP, total number of translocation breakpoints in the tumor sample.
Please cite this article as: Bacolla, A et al., Cancer mutational burden is shaped by G4 DNA, SP600125 stress and mitochondrial dysfunction, Progress in Biophysics and Molecular Biology, https://doi.org/10.1016/j.pbiomolbio.2019.03.004
6 A. Bacolla et al. / Progress in Biophysics and Molecular Biology xxx (xxxx) xxx
Please cite this article as: Bacolla, A et al., Cancer mutational burden is shaped by G4 DNA, replication stress and mitochondrial dysfunction, Progress in Biophysics and Molecular Biology, https://doi.org/10.1016/j.pbiomolbio.2019.03.004
A. Bacolla et al. / Progress in Biophysics and Molecular Biology xxx (xxxx) xxx 7
families of L1 retrotransposons, particularly L1PA2, L1PA3 and L1PA4 (Sahakyan et al., 2017). Surprisingly, only 2/738 (0.27%) translocation breakpoints were found to coincide within the L1-specific G4 sequence (Fig. 2F), suggesting either a hierarchy of susceptibility to strand-break or difficulties in mapping break-points at these repetitive DNA elements from whole genome sequencing.
Concerning the 7 translocation breakpoint-positions at SVA el-ements, these occurred in only 5 distinct units. Two translocation breakpoints were mapped to the same SVA_F, and indeed to the same coordinate on chromosome 6 (hence counted only once in the 738-set) in two separate prostate adenocarcinoma samples car-rying a total of 110 and 36 breakpoints, respectively. Two rear-rangements involved the same SVA_D element on chromosome 20 in two bladder papillary transitional cell carcinoma samples (66 and 31 breakpoints, respectively). Two breakpoints were found in a third SVA_F element on chromosome 5 in a case of pancreatic ductal carcinoma with only 10 translocation breakpoints, and in a case of ovarian mixed adenosquamous carcinoma with as many as 121 translocation junctions (Fig. 2G). The remaining two trans-locations occurred at two separate SVA_D elements, one on chro-mosome 12 and the other on chromosome 18. In conclusion, translocation breakpoints are more likely to be found at G4 DNA located in SVA elements than in L1 transposons; furthermore, it is possible that a subset of SVA elements in the human genome might be particularly unstable, yielding recurrent strand breaks in cancer.
3.2. Gene expression profiles correlate with cancer somatic mutations
3.2.1. Correlation between gene expression and somatic mutations is tumor type specific Recognizing that G4 DNA likely impacts transcription, we employed a separate set of analyses to assess the extent to which the cellular transcriptome and its regulation are associated with mutation loads in cancer genomes. To this end we analyzed the genome-wide gene expression landscape and whole exome single base substitutions and small indels from TCGA. For each gene and tumor type we computed the regression coefficient R and the associated P-value, which normalized the data from the depen-dence of R on the total number of observations (Fig. 3A). Thus, an S-plot of all P-values allowed for a direct comparison across all tu-mors, which revealed a strong variability on tissue-dependent origin in the extent to which gene expression correlates with mu-tation loads. At the extremes, TGCT displayed minimum P-values ( 0.0035), whereas SKCM exhibited the strongest positive corre-lations (P-values up to 1 10 31), and LUAD covered a continuum