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Venn diagram of lists of enriched genes. The considered lists are: AGO2-IP (UP_AGO2 set), the list of enriched genes detected by Fan et al. [13] (UP_AGO2_Fan) and our list of enriched genes in GW182-IP sample (UP_GW182). The reported p-values refer to the closest intersection set of genes and are computed with one tail Fisher-test. (PDF 34 kb)

Analysis of miRNA expression in AGO2 and GW182-IP samples. a) miRNA expression level in AGO2-IP samples (average value from the three performed experiments) vs the expression level in IN samples (average value from the three performed experiments). The Pearson correlation values reported on the top of the picture were computed by using all the expressed miRNA, and the top 100 or 50 expressed miRNAs. The colored points refer to miRNA that have been validated by RT-PCR data. Green points refer to hsa-miR-141-3p, hsa-miR-21-5p, hsa-let-7f-5p, hsa-miR-16-5p, hsa-miR-24-3p, hsa-miR-27a-3p, hsa-miR-23a-3p. The red point refers to hsa-miR-1260a. b) Comparison of IP/IN ratios obtained by RT-PCR data (normalized by IgG control data) and microarray data (normalized by Quantile normalization). The underrepresentation of hsa-miR-1260a was confirmed by RT-PCR. c) and d) Analysis of GW182-IP samples performed as described in a) and b). (PDF 47 kb)

Empirical Cumulative Distribution Function of 3â UTR and coding region length of IP-Enriched genes. Enriched genes in AGO (1â 4) and in GW182 protein family IP selected by considering log2 IP-Enrichment of transcript greater than 1. Data are downloaded from Landthaler et al. [14]. The Empirical Cumulative Distribution Function of the 3â UTR length (top) and coding region length (bottom) of genes enriched exclusively by AGO-IP (red line), GW182-IP (blue line) and both IPs (black line) are reported. The reported p-value is computed by performing a Wilcoxon test to compare the length distributions of genes enriched exclusively in AGO-IP and in GW182-IP. (PDF 145 kb)

Summary of miRNA expression profiles switch between experiment replicas. ROC analysis of F6&F4d SVM model trained with variables calculated with miRNA expression profiles from each of the three anti-AGO2 RIP experiments. SVM models were used to classify the top 1000 and the bottom 1000 genes with respect to the IP/FT mRNA expression ratio, computed for each of the three AGO2 RIP experiments. (PDF 653 kb)

Wilcoxon test p-values summary. Wilcoxon test p-values (log10) obtained by comparing the variable values associated with the enriched/underrepresented genes sets. Three different miRNA target prediction tools (Targetscan, PITA and miRanda) were used to compute the necessary binding sites (BS) matrices. The BS matrices used to compute the p-values in the last panel were obtained by considering BS predicted by at least two of the three prediction tools. In each panel, the variables computed with the three AGO2 IN profiles were used to distinguish enriched and underrepresented genes in AGO2-IP vs FT and the variables computed with the three GW182 IN profiles were used to distinguish enriched and underrepresented genes in GW182-IP vs FT. (PDF 133 kb)

Summary of miRNA expression profiles shuffling effects. ROC analysis was performed to evaluate the performance of F6 and F4d variables, computed with simulated miRNA profiles, in distinguishing enriched/underrepresented genes in AGO2 or GW182-IP samples. Each panel reports the AUC values obtained with simulated variables. Each boxplot refers to AUC values obtained with a specific set of simulations, where the expression profile of a set of miRNAs was shuffled. The boxplot in the center was obtained by shuffling all miRNAs. The boxplots from the center to the right refer to simulations where all the miRNAs were shuffled with the exception of n top expressed miRNAs, n increasing in the right direction. The boxplots from the center to the left refer to simulations where all the miRNAs were shuffled with the exception of n low expressed miRNAs, n increasing in the left direction. The green horizontal line defines the AUC value obtained with the original miRNA expression profile. Boxplots are colored in red if less than 5% of the simulations reach the AUC original value, green otherwise. This file contains the following simulation results: A. Simulated F6 variable distinguishing AGO2 enriched vs underrepresented genes. B. Simulated F6 variable distinguishing GW182 enriched vs underrepresented genes. C. Simulated F4d variable distinguishing AGO2 enriched vs underrepresented genes. D. Simulated F6&F4d SVM model distinguishing AGO2 enriched vs underrepresented genes. (PDF 555 kb)

Overview of gene expression levels in IP and FT samples. Focus on the enriched genes in AGO2-IP and GW182-IP vs FT samples. The reported expression levels are computed as the average values of the three performed experimental replicates. (PDF 1423 kb)

The release of molecules from damaged tissues stimulates both resident and circulating stem cells to initiate a tissue repair programme. 1 However, during transplantation procedures the therapeutic efficacy of stem cells is compromised by reduced homing capability towards the target site.2,3 Furthermore, cell survival is very low and many studies focused on improving cell viability upon implantation. In this study, we performed in vitrosevere oxidative stress to select some more resistant mouse mesoangioblasts, vessel-associated progenitor stem cells endowed with the ability of multipotent mesoderm differentiation. We found that the selected subpopulation retains selfrenewal and myogenic differentiation capabilities under physiological growth conditions, showing, also, an enhancement in cell survival and migration capabilities under stress conditions respect to the unselected cells. In fact, following oxidative stress treatment the isolated cell subpopulation showed more resistance, survival and recovery properties. To evaluate whether or not the isolated cell clone showed selective advantages over the parental mesoangioblasts, we carried out in vivo experiments using immunocompromised dystrophic mice. We injected intramuscularly the Tibialis Anterior with both the selected cells and the parental cells. Actually resistant mesoangioblasts displayed markedly enhanced survival and integration capabilities into the host damaged skeletal muscle, displaying more than 70% increase in integration compared to the non-selected mesoangioblast cell population. In conclusion, the positive effects of sorting on mesoangioblast cells suggest that a selection step using oxidative stress preconditioning may provide a novel methodology to select for resistant cells that can be used in regenerative tissue applications to prevent high mortality rates upon transplantation.

The S100 gene family is the largest subfamily of calcium binding proteins of EF-hand type, expressed in tissue and cell-specific manner. S100 proteins act as intracellular regulators and as extracellular signaling. Within cells, S100 have been involved in the regulation of proliferation, differentiation, apoptosis, energy metabolism, inflammation, migration and invasion via interactions with a variety of target proteins. Extracellular S100 proteins act in an autocrine and paracrine manner through the activation of surface receptors that regulate cell proliferation, differentiation, survival and migration. More recently, there is growing interest in the S100 proteins and their relationship with different cancers because of their involvement in a variety of biological events closely related to tumorigenesis and cancer progression1. However, the occurrence, the role and the possible coordination of this group of proteins in breast cancer is still poorly known. We previously describe a large-scale proteomic investigation performed on breast cancer patients for the screening of multiple forms of S100 proteins2,3. Our results have shown that the majority of S100 proteins are preferentially expressed in the tumor mass compared with the normal adjacent tissue and that some S100 protein members were ubiquitously expressed in almost all patients, while others appeared more sporadic among the same group of patients. More interestingly, patients which developed distant metastases showed a general tendency of higher S100 protein expression, compared to the disease-free group. Present study was aimed to assess the gene expression levels of the S100 protein family members utilizing a breast cancer dataset generated on Affymetrix microarrays technologies4. GOBO (Gene expression-based Outcome for Breast cancer Online) is a user-friendly online tool that allows, also, the identification of co-expressed genes and association with outcome in an 1881 breast cancer samples. Other important association with breast cancer outome was carried out by Kaplan Meir-plotter database5. Integrating results obtained by proteomic and trascriptomic analysis of S100 proteins highlight their important involvement in breast cancer progression, and support the idea that S100 proteins are important prognostic factors, related to survival period of tumor patients. However, the specific mechanisms by which S100 proteins affect progression of breast require further study.

The chemical synthesis of novel chemotherapeutical leads is evolving thanks to possibility to design molecules with desired physical-chemical and, thus, biological properties. The imidazolium salts, recently proven effective to inhibit bacterial and/or cancer cell growth, posses an amphiphilic nature that is conferred by the imidazolium cation having a polar head generally coupled with aliphatic side chains. Thus, biological properties of imidazolium salts can be tuned through modifications involving the cation structure and/or the anion nature. By covalently linking two imidazolium rings, di-imidazolium salts were obtainedobtain differing in: i) kind of anions; ii) geometric isomerization of di-imidazolium anions; iii) length of the imidazolium alkyl side chains. Preliminarly, eleven di-imidazolium salts, differing for their anionic counterparts, were assayed for: i) antibacterial property, quantified as the minimal concentration inhibiting at least the 90% of bacterial growth (MIC90) using Escherichia coli and Micrococcus luteus as Gram-negative and Gram-positive tester strains; ii) antitumoral activity measured as the concentration inhibiting the 50% of cell growth (IC50) using SKBR-3 breast cancer cell line. All the assayed salts possesses biological activity showing i) 0.1-0.5 and 25-50 µg/ml as MIC90 values against of M. luteus, and E. coli; respectively, and ii) 30-55 µg/ml as IC50 values. Among the tested di-imidazolium salts, three were chosen to further investigate the relationship between biological efficacy and either length of alkyl side chains or imidazolium ring configurations. Geometric isomerization revealed few or no effect while a positive correlation between alkyl chain length and cell-growth inhibitory efficacy was shown. Although further studies have to be performed to elucidate the molecular mechanisms leading to cell growth arrest, this study provide insights on the attractive possibility of di-imidazolium salt exploitation as chemotherapeutical compounds whose activity can be tuned by modifying structural characteristics.

S100 gene family is the largest subfamily of calcium binding proteins, expressed in tissue and cell-specific manner. Within cells, S100 have been involved in the regulation of proliferation, differentiation, apoptosis, energy metabolism, inflammation, migration and invasion. Extracellular S100 proteins act in an autocrine and paracrine manner and regulate cell proliferation, differentiation, survival and migration. S100 proteins play important roles in the development and progression of tumors due to their multifunctional roles. However, the occurrence, the role and the possible coordination of this group of proteins in breast cancer is still poorly known. We previously describe a large-scale proteomic investigation performed on breast cancer patients for the screening of multiple forms of S100 proteins1,2. Our results have shown that the majority of S100 proteins are preferentially expressed in the tumor mass compared with the normal adjacent tissue and that some S100 protein members were ubiquitously expressed in almost all patients, while others appeared more sporadic among the same group of patients. More interestingly, patients which developed distant metastases showed a general tendency of higher S100 protein expression, compared to the disease-free group. Present study was aimed to assess the gene expression levels of the S100 protein family members utilizing a breast cancer dataset generated on Affymetrix microarrays technologies3. GOBO (Gene expression-based Outcome for Breast cancer Online) is a user-friendly online tool that allows, also, the identification of co-expressed genes and association with outcome in an 1881 breast cancer samples. Other important association with breast cancer outome was carried out by Kaplan Meir-plotter database4. Integrating results obtained by proteomic and trascriptomic analysis of S100 proteins highlight their important involvement in breast cancer progression. Future studies are needed to disclose molecular mechanisms and signaling pathways that define the multiple and specific roles of S100 proteins in breast cancer.

Our studies in the field of printing nanobiology in aqueous solution are proposed to highlight the role of water in the processes of interaction between biomolecules in drug- screening devices fabricated by bioprinting technologies and to emphasize the influence of water evaporation on the diffusion of molecules in droplets of picoliter-scale.

The first step for prevention and treatment of diseases is the accurate diagnosis. However, proper diagnostic technologies are not available in developing countries due to the lack of reliable electrical power, refrigeration and trained personnel. For this reason, there is an urgent need of low cost, rapid assays not requiring any external support. By coupling such technologies to communication infrastructures, healthcare in areas without access to medical personnel would be possible. “Paper” like substrates are ideal for fabricating such devices since they are cheap, easy to degradate after use and compatible with most of existing printing technologies [1]. We had previously shown the possibility to efficiently deposit oligonucleotides by Dip Pen Lithography(DPL) onto glass surfaces [2]. In this work, we deposited oligonucleotides on nylon substrate for the fabrication of biochips usable for detecting the activity of human topoisomerase I. Subsequently, the chip will be modified to detect the Malariacausing Plasmodium parasites through the detection of Plasmodium topoisomerase I activity [3]. We optimized oligonucleotides printing on nylon substrate, obtaining efficient deposition at 10 - 1 uM oligonucleotide concentrations, 70% relative humidity and 30% glycerol v/v. We obtained circular spots with diameter in the range of 30 - 50 microns, with the dimension being a function of dwell time (1s – 20 s). DPL operation needs ultra tiny amounts of DNA (as low as 0.5 uL, 10 - 1 uM concentration) for printing thousands of spots in a single run so reducing material consumption in comparison with standard bioprinting techniques [4]. In a first set of experiments, the printed oligonucleotides was hybridized with a fluorescence-labelled complementary probe to detect and quantify DNA after DPL deposition. In subsequent experiment, the spotted oligonucleotides generate a topoisomerase substrate, which upon reaction with the enzyme will be coupled to a fluorescently labelled oligonucleotide to allow detection of a signal. In conclusion, the combination of DPL and topoisomerase detection onto nylon substrates would be a suitable solution for point-of-care diagnostic chips fabrication.