92 research outputs found

    Epigenetic control of the basal-like gene expression profile via Interleukin-6 in breast cancer cells

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    <p>Abstract</p> <p>Background</p> <p>Basal-like carcinoma are aggressive breast cancers that frequently carry p53 inactivating mutations, lack estrogen receptor-α (ERα) and express the cancer stem cell markers CD133 and CD44. These tumors also over-express Interleukin 6 (IL-6), a pro-inflammatory cytokine that stimulates the growth of breast cancer stem/progenitor cells.</p> <p>Results</p> <p>Here we show that p53 deficiency in breast cancer cells induces a loss of methylation at <it>IL-6 </it>proximal promoter region, which is maintained by an IL-6 autocrine loop. IL-6 also elicits the loss of methylation at the <it>CD133 </it>promoter region 1 and of <it>CD44 </it>proximal promoter, enhancing <it>CD133 </it>and <it>CD44 </it>gene transcription. In parallel, IL-6 induces the methylation of estrogen receptor (ERα) promoter and the loss of ERα mRNA expression. Finally, IL-6 induces the methylation of <it>IL-6 </it>distal promoter and of <it>CD133 </it>promoter region 2, which harbour putative repressor regions.</p> <p>Conclusion</p> <p>We conclude that IL-6, whose methylation-dependent autocrine loop is triggered by the inactivation of p53, induces an epigenetic reprogramming that drives breast carcinoma cells towards a basal-like/stem cell-like gene expression profile.</p

    Impact of the Type of Dialysis on Time to Transplantation: Is It Just a Matter of Immunity?

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    Background: Renal transplantation represents the therapeutic gold standard in patients with end stage renal disease (ESRD). Still the role of pre-transplant dialysis in affecting time to transplantation has yet to be determined. We wanted to verify whether the type of renal replacement therapy (hemodialysis vs. peritoneal dialysis) affects time to transplantation and to identify clinical features related to the longer time to transplantation. Methods: We performed a retrospective single-center observational study on patients who had received a transplant in the Bologna Transplant Unit from 1991 to 2019, described through the analysis of digital transplant list documents for sex, age, body mass index (BMI), blood group, comorbidities, underlying disease, serology, type of dialysis, time to transplantation, Panel Reactive Antibodies (PRA) max, number of preformed anti Human Leukocyte Antigens (HLA) antibodies. A p-value &lt; 0.05 was considered statistically significant. Results: In the 1619 patients analyzed, we observed a significant difference in time to transplant, PRA max and Preformed Antibodies Number between patients who received Hemodialysis (HD) and Peritoneal dialysis (PD). Then we performed a multiple regression analysis with all the considered factors in order to identify features that support these differences. The clinical variables that independently and directly correlate with longer time to transplantation are PRA max (p &lt; 0.0001), Antibodies number (p &lt; 0.0001) and HD (p &lt; 0.0001); though AB blood group (p &lt; 0.0001), age (p &lt; 0.003) and PD (p &lt; 0.0001) inversely correlate with time to transplantation. Conclusions: In our work, PD population received renal transplants in a shorter period of time compared to HD and turned out to be less immunized. Considering immunization, the type of dialysis impacts both on PRA max and on anti HLA antibodies
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