Loss of the candidate tumor suppressor ZEB1 (TCF8, ZFHX1A) in Sézary syndrome

Cutaneous T-cell lymphoma is a group of incurable extranodal non-Hodgkin lymphomas that develop from the skin-homing CD4+ T cell. Mycosis fungoides and Sézary syndrome are the most common histological subtypes. Although next-generation sequencing data provided significant advances in the comprehension of the genetic basis of this lymphoma, there is not uniform consensus on the identity and prevalence of putative driver genes for this heterogeneous group of tumors. Additional studies may increase the knowledge about the complex genetic etiology characterizing this lymphoma. We used SNP6 arrays and GISTIC algorithm to prioritize a list of focal somatic copy-number alterations in a dataset of multiple sequential samples from 21 Sézary syndrome patients. Our results confirmed a prevalence of significant focal deletions over amplifications: single well-known tumor suppressors, such as TP53, PTEN, and RB1, are targeted by these aberrations. In our cohort, ZEB1 (TCF8, ZFHX1A) spans a deletion having the highest level of significance. In a larger group of 43 patients, we found that ZEB1 is affected by deletions and somatic inactivating mutations in 46.5% of cases; also, we found potentially relevant ZEB1 germline variants. The survival analysis shows a worse clinical course for patients with ZEB1 biallelic inactivation. Multiple abnormal expression signatures were found associated with ZEB1 depletion in Sézary patients we verified that ZEB1 exerts a role in oxidative response of Sézary cells. Our data confirm the importance of deletions in the pathogenesis of cutaneous T-cell lymphoma. The characterization of ZEB1 abnormalities in Sézary syndrome fulfils the criteria of a canonical tumor suppressor gene. Although additional confirmations are needed, our findings suggest, for the first time, that ZEB1 germline variants might contribute to the risk of developing this disease. Also, we provide evidence that ZEB1 activity in Sézary cells, influencing the reactive oxygen species production, affects cell viability and apoptosis

Blood and skin-derived Sezary cells: differences in proliferation-index, activation of PI3K/AKT/mTORC1 pathway and its prognostic relevance

Sézary syndrome (SS) is a rare and aggressive variant of Cutaneous T-Cell Lymphoma characterized by neoplastic distribution mainly involving blood, skin, and lymph-node. Although a role of the skin microenvironment in SS pathogenesis has long been hypothesized, its function in vivo is poorly characterized. To deepen this aspect, here we compared skin to blood-derived SS cells concurrently obtained from SS patients highlighting a greater proliferation-index and a PI3K/AKT/mTORC1 pathway activation level, particularly of mTOR protein, in skin-derived-SS cells. We proved that SDF-1 and CCL21 chemokines, both overexpressed in SS tissues, induce mTORC1 signaling activation, cell proliferation and Ki67 up-regulation in a SS-derived cell line and primary-SS cells. In a cohort of 43 SS cases, we observed recurrent copy number variations (CNV) of members belonging to this cascade, namely: loss of LKB1 (48%), PTEN (39%) and PDCD4 (35%) and gains of P70S6K (30%). These alterations represent druggable targets unraveling new therapeutic treatments as metformin here evaluated in vitro. Moreover, CNV of PTEN, PDCD4, and P70S6K, evaluated individually or in combination, are associated with reduced survival of SS patients. These data shed light on effects in vivo of skin-SS cells interaction underlying the prognostic and therapeutic relevance of mTORC1 pathway in SS

Compatible solutes from hyperthermophiles improve the quality of DNA microarrays

<p>Abstract</p> <p>Background</p> <p>DNA microarrays are among the most widely used technical platforms for DNA and RNA studies, and issues related to microarrays sensitivity and specificity are therefore of general importance in life sciences. Compatible solutes are derived from hyperthermophilic microorganisms and allow such microorganisms to survive in environmental and stressful conditions. Compatible solutes show stabilization effects towards biological macromolecules, including DNA.</p> <p>Results</p> <p>We report here that compatible solutes from hyperthermophiles increased the performance of the hybridization buffer for Affymetrix GeneChip^®arrays. The experimental setup included independent hybridizations with constant RNA over a wide range of compatible solute concentrations. The dependence of array quality and compatible solute was assessed using specialized statistical tools provided by both the proprietary Affymetrix quality control system and the open source Bioconductor suite.</p> <p>Conclusion</p> <p>Low concentration (10 to 25 mM) of hydroxyectoine, potassium mannosylglycerate and potassium diglycerol phosphate in hybridization buffer positively affected hybridization parameters and enhanced microarrays outcome. This finding harbours a strong potential for the improvement of DNA microarray experiments.</p

F-scores measuring the method performance for the different nucleotides.

<p>Complete results reporting the F-scores for all the nucleotide types and for each nucleotide module considered. The bars are colored depending on the nucleotide module: blue for the nucleobase, red for the carbohydrate and green for the phosphate.</p

Performance of the method considering first-ranked predictions.

<p>Complete results, as percentage of analyzed protein structures in which the method places a correct prediction in the first rank for the three types of nucleotide modules. Each nucleotide type is represented by a doughnut chart that is divided in three sectors, one for each nucleotide module (blue for the nucleobase, red for the carbohydrate and green for the phosphate). The size of each module sector is proportional to the percentage of proteins in which the method is successful. The columns divide the nucleotides by their architecture type: NCP stands for nucleobase-carbohydrate-phosphate (e.g. the AMP) and so on. Moreover nucleotides are grouped by their characteristic molecular feature so that rows divide them in guanine-, adenine-, flavin- and nicotinamide-containing nucleotides.</p

Results of the method after ranking predictions considering the nucleotide type.

<p>Complete results for the sc-PDB dataset divided by nucleotide type, as percentage of analyzed protein structures in which the method places a correct prediction in the first, top three, top five and top ten predictions for the three types of nucleotide modules.</p

F-score of the method at different R.M.S.D. thresholds.

<p>Average F-scores of the method (considering all the nucleotide types) for each nucleotide module and for each R.M.S.D. threshold used during the structural comparison step.</p

Minimum distance allowed for nucleotide modules from the protein surface.

<p>Minimum distance, in Ångström, allowed for a predicted nucleotide module from the solvent excluded surface. The distance is calculated considering any atom of the nucleotide module and any vertex of the mesh representing the solvent excluded surface.</p

Minimum and maximum distances allowed between nucleotide modules.

<p>These distances (in Ångström) are calculated between the centroids of nucleotide modules.</p

Comparison with another method for the prediction if nucleotide-bingind sites.

<p>Comparison between the method developed by Saito <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050240#pone.0050240-Saito1" target="_blank">[17]</a> and the methodology presented in this work. The first group of bars on the left represents the performance of Saito’s method. The other groups of bars represent the performance of our method for the different nucleotide modules. Bars are colored depending on the protein dataset: proteins binding adenine- (blue), guanine- (red) nicotinamide- (green) and flavin-containing (purple) nucleotides.</p