In breast cancer, the genetic profiling of circulating cell-free DNA (cfDNA) from blood plasma was shown to have good potential for clinical use. In contrast, only a few studies were performed investigating urinary cfDNA. In this pilot study, we analyzed plasma-derived and matching urinary cfDNA samples obtained from 15 presurgical triple-negative breast cancer patients. We used a targeted next-generation sequencing approach to identify and compare genetic alterations in both body fluids. The cfDNA concentration was higher in urine compared to plasma, but there was no significant correlation between matched samples. Bioinformatical analysis revealed a total of 3339 somatic breast-cancer-related variants (VAF ≥ 3%), whereof 1222 vs. 2117 variants were found in plasma-derived vs. urinary cfDNA, respectively. Further, 431 shared variants were found in both body fluids. Throughout the cohort, the recovery rate of plasma-derived mutations in matching urinary cfDNA was 47% and even 63% for pathogenic variants only. The most frequently occurring pathogenic and likely pathogenic mutated genes were NF1, CHEK2, KMT2C and PTEN in both body fluids. Notably, a pathogenic CHEK2 (T519M) variant was found in all 30 samples. Taken together, our results indicated that body fluids appear to be valuable sources bearing complementary information regarding the genetic tumor profile.
The guanine rich locations are present in human genome. Previous studies have shown that the presence of G rich sequences and
motifs may be significant for gene activity and function. We decided to focus our interest to identify G rich motifs in promoters of
oncogenes and tumor suppressor genes. We used a set of 100 most common oncogenes and tumor suppressor genes (TSG) for this
analysis. We collected 600nt long promoters with -500 and +100 TSS (transcription start site) from the oncogenes and TSG set.
Using a computer program, we calculated the G densities using numbers and locations of G forms with 100nt moving widow. We
included G numbers from 2 to 7 guanines. Analysis shows that G density increases from -500 to +100 and more from TSS. G density
is found to be maximum within -/+100 of TSS. The results of G densities were compared with the expression data of the selected
oncogenes and tumor suppressor genes in patients with colon cancer (n=174).
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