Distinct patterns of somatic alterations in a lymphoblastoid and a tumor genome derived from the same individual

Although patterns of somatic alterations have been reported for tumor genomes, little is known on how they compare with alterations present in non-tumor genomes. A comparison of the two would be crucial to better characterize the genetic alterations driving tumorigenesis. We sequenced the genomes of a lymphoblastoid (HCC1954BL) and a breast tumor (HCC1954) cell line derived from the same patient and compared the somatic alterations present in both. The lymphoblastoid genome presents a comparable number and similar spectrum of nucleotide substitutions to that found in the tumor genome. However, a significant difference in the ratio of non-synonymous to synonymous substitutions was observed between both genomes (P = 0.031). Protein–protein interaction analysis revealed that mutations in the tumor genome preferentially affect hub-genes (P = 0.0017) and are co-selected to present synergistic functions (P < 0.0001). KEGG analysis showed that in the tumor genome most mutated genes were organized into signaling pathways related to tumorigenesis. No such organization or synergy was observed in the lymphoblastoid genome. Our results indicate that endogenous mutagens and replication errors can generate the overall number of mutations required to drive tumorigenesis and that it is the combination rather than the frequency of mutations that is crucial to complete tumorigenic transformation

Distinct patterns of somatic alterations in a lymphoblastoid and a tumor genome derived from the same individual

Although patterns of somatic alterations have been reported for tumor genomes, little is known on how they compare with alterations present in non-tumor genomes. A comparison of the two would be crucial to better characterize the genetic alterations driving tumorigenesis. We sequenced the genomes of a lymphoblastoid (HCC1954BL) and a breast tumor (HCC1954) cell line derived from the same patient and compared the somatic alterations present in both. The lymphoblastoid genome presents a comparable number and similar spectrum of nucleotide substitutions to that found in the tumor genome. However, a significant difference in the ratio of non-synonymous to synonymous substitutions was observed between both genomes (P = 0.031). Protein–protein interaction analysis revealed that mutations in the tumor genome preferentially affect hub-genes (P = 0.0017) and are co-selected to present synergistic functions (P < 0.0001). KEGG analysis showed that in the tumor genome most mutated genes were organized into signaling pathways related to tumorigenesis. No such organization or synergy was observed in the lymphoblastoid genome. Our results indicate that endogenous mutagens and replication errors can generate the overall number of mutations required to drive tumorigenesis and that it is the combination rather than the frequency of mutations that is crucial to complete tumorigenic transformation

Proposal of e-learning strategy to teach Atraumatic Restorative Treatment (ART) to undergraduate and graduate students

Abstract Background The aim of this study was to evaluate e-learning strategy in teaching Atraumatic Restorative Treatment (ART) to undergraduate and graduate students. The sample comprised 76 participants—38 dental students and 38 pediatric dentistry students—in a specialization course. To evaluate knowledge improvement, participants were subjected to a test performed before and after the course. Results A single researcher corrected the tests and intraexaminer reproducibility was calculated (CCI = 0.991; 95% IC = 0.975–0.996). All students improved their performances after the e-learning course (Paired t-tests p < 0.001). The means of undergraduate students were 4.7 (initial) and 6.4 (final) and those of graduate students were 6.8 (initial) and 8.2 (final). The comparison of the final evaluation means showed a statistically significant difference (t-tests p < 0.0001). Conclusions The e-learning strategy has the potential of improving students’ knowledge in ART. Mature students perform better in this teaching modality when it is applied exclusively via distance learning

Alternative polyadenylation allows differential negative feedback of human miRNA miR-579 on its host gene ZFR.

About half of the known miRNA genes are located within protein-coding host genes, and are thus subject to co-transcription. Accumulating data indicate that this coupling may be an intrinsic mechanism to directly regulate the host gene's expression, constituting a negative feedback loop. Inevitably, the cell requires a yet largely unknown repertoire of methods to regulate this control mechanism. We propose APA as one possible mechanism by which negative feedback of intronic miRNA on their host genes might be regulated. Using in-silico analyses, we found that host genes that contain seed matching sites for their intronic miRNAs yield longer 32UTRs with more polyadenylation sites. Additionally, the distribution of polyadenylation signals differed significantly between these host genes and host genes of miRNAs that do not contain potential miRNA binding sites. We then transferred these in-silico results to a biological example and investigated the relationship between ZFR and its intronic miRNA miR-579 in a U87 cell line model. We found that ZFR is targeted by its intronic miRNA miR-579 and that alternative polyadenylation allows differential targeting. We additionally used bioinformatics analyses and RNA-Seq to evaluate a potential cross-talk between intronic miRNAs and alternative polyadenylation. CPSF2, a gene previously associated with alternative polyadenylation signal recognition, might be linked to intronic miRNA negative feedback by altering polyadenylation signal utilization

Model of intronic negative feedback regulation.

<p>After coexpression of miRNA and host gene, the miRNA directly regulates its host gene as well as CPSF2. After removal of CPSF2 the polyadenylation-complex is biased towards recognition of canonical sites. In the next transcription cycle, the canonical site that precedes the miRNA binding site is utilized. Hence, regulation of the host gene by its intronic miRNA is disabled.</p

Bioinformatics and biomolecular analyses indicate a role for APA in regulation of negative feedback.

<p>A) Comparison of APA-sites for HT miRNA host genes and NT miRNA host genes. B) After CPSF2 silencing HT miRNA host gene UTRs display a different poly(A)-site usage pattern compared to NT miRNA host gene UTRs and regular protein-coding genes’ UTRs. C) The motif discovered in upregulated APA regions after CPSF2 silencing resembles the two canonical polyadenylation sites. D) Distribution of canonical poly(A) signals across the 32UTR of HT miRNA host genes and E) NT miRNA host genes.</p

HT miRNA host genes with significant 3´UTR changes after CPSF2-silencing.

<p>HT miRNA host genes with significant 3´UTR changes after CPSF2-silencing.</p

miR-579 targets its host, ZFR, and the APA associated gene CPSF2.

<p>A) Schematic diagram of the <i>ZFR</i> gene. B) Schematic diagram of the ZFR 32UTR including polyadenylation sites and the seed matching site for miR-579. C) U87 cells were co-transfected with reporter constructs containing wildtype ZFR-32UTR or ZFR-32UTR lacking the miR-579 binding site (mut 32UTR) along with pre-miR-579 or negative control (NC). Results are expressed as Rluc/Fluc ratio relative to NC (mean ± 95% CI; n = 6; *, p < 0.05). D) In U87 cells transiently transfected with scrambled control or pre-miR-579, ZFR and CPSF2 mRNA expression was analyzed by quantitative RT-PCR. Values are mean ± 95% CI; n = 5; *, p < 0.05. E) Western blot analysis of the same samples using specific antibodies as indicated (β-Actin served as loading control; one representative experiment of three is shown). F) In U87 cells, expression changes of the long (miRNA binding site containing; red) and short (without miRNA binding site; blue) alternatively polyadenylated UTRs after transfection with pre-miR-579 or with scrambled control was determined by quantitative RT-PCR. Values are shown as miR-579 transfection relative to scrambled control (n = 5; *, p < 0.05).</p

Identification of APA genes preferentially targeted by HT miRNAs.

<p>Identification of APA genes preferentially targeted by HT miRNAs.</p