沃度保兒謨ニ因セル濕疹

Evaluation of CNA-IC50 correlations by known cancer driver mutations. Distributions of PCCs for cancer cell lines with mutated or wild-type proto-oncogenes or tumor suppressors as depicted in each figure. The rank position of negatively correlated drugs (p < 0.10) is shown. (EPS 975 kb

The Catalan Surveillance Network of SARS-CoV-2 in Sewage: design, implementation, and performance

Wastewater-based epidemiology has shown to be an efficient tool to track the circulation of SARS-CoV-2 in communities assisted by wastewater treatment plants (WWTPs). The challenge comes when this approach is employed to help Health authorities in their decision-making. Here, we describe the roadmap for the design and deployment of SARSAIGUA, the Catalan Surveillance Network of SARS-CoV-2 in Sewage. The network monitors, weekly or biweekly, 56 WWTPs evenly distributed across the territory and serving 6 M inhabitants (80% of the Catalan population). Each week, samples from 45 WWTPs are collected, analyzed, results reported to Health authorities, and finally published within less than 72 h in an online dashboard ( https://sarsaigua.icra.cat ). After 20 months of monitoring (July 20-March 22), the standardized viral load (gene copies/day) in all the WWTPs monitored fairly matched the cumulative number of COVID-19 cases along the successive pandemic waves, showing a good fit with the diagnosed cases in the served municipalities (Spearman Rho = 0.69). Here we describe the roadmap of the design and deployment of SARSAIGUA while providing several open-access tools for the management and visualization of the surveillance data.The authors wish to thank the staff from all the WWTPs monitored for their help and technical support during the sampling campaigns. The authors acknowledge the funding received from the ACA and the ASPCAT from the Catalan Government (Generalitat de Catalunya). ICRA authors acknowledge the funding provided by the Generalitat de Catalunya through the Consolidated Research Group grants ICRA-ENV 2017 SGR 1124 and ICRA-TiA 2017 SGR 1318. ICRA researchers also thank the funding from the CERCA program of the Catalan Government.Peer reviewe

Network biology identifies novel apoptosis-related proteins and synergistic drug combinations in breast cancer

Breast cancer is a very heterogeneous disease with a poor prognostic outcome, largely due to its resistance to current cancer therapies. The balance between cell proliferation and apoptosis plays a critical role in determining the overall growth or regression of the tumor in response to treatments. Hence, identifying treatments involved in apoptosis resistance is essential in order to find new therapeutic approaches. The heterogeneity of cancer is rarely due to abnormalities in single genes, but rather reflects the discontinuation of complex intercellular processes. Therefore, a useful way to describe and analyse this heterogeneity is the use of systems biology. This approach is based on the study of the interactions between the elements of a given system with the aim to understand its properties. Particularly, the use of protein-protein interaction networks gives a broader perspective of protein environment without losing the molecular details, providing a deeper understanding of the molecular mechanisms underlying complex pathological processes. Thus, the application of network biology can significantly help the elucidation of novel drug targets and more effective therapies. Since the molecular mechanisms that relate, for instance, changes in expression of the many passenger genes to breast cancer onset and progression are largely unknown, the first objective of this thesis was to identify the role of certain proteins in breast cancer apoptosis, which function on the disease is unknown. With this aim, we functionally characterized two breast cancer passenger genes, PSMC3IP and EPSTI1, to analyse their potential apoptotic role in breast cancer. We first explored the existence of direct physical interactions with annotated breast cancer-apoptotic genes, and subsequently, we examined several apoptotic markers to determine the effect of PSMC3IP and EPSTI1 gene expression modulation in two different human breast cancer cell lines. Overall, our results showed that PSMC3IP and EPSTI1 are able to modulate the extrinsic apoptotic pathway in estrogen receptor positive and triple negative breast cancer cell lines, highlighting them as potential therapeutic targets. Currently approved drug combinations are the result of empirical clinical experience, are not being rationally designed and cover only a small fraction of the potential therapeutic space. Therfore, our second objective was to implement two different network biology approaches in order to predict and validate novel synergistic drug combinations for the treatment of breast cancer, with greater clinical efficacy and reduced side effects. The first approach was based on the quantification of pathway crosstalk inhibition in therapeutic networks. We applied this measure to a set of antineoplastic (cancer drug combined with breast cancer drug) and compassive (non-cancer drug combined with breast cancer drug) combinations. We next validate experimentally the most promising drug combinations in several breast cancer cell lines. Finally, we determined whether the cytotoxic effect of the selected drug combinations was due to apoptosis induction or cell cycle arrest promotion. Overall, our findings highlight two different antineoplastic combinations as promising therapeutic strategies for triple negative breast cancer subtype. The second approach integrated the known human interactome with the basal gene expression measurements in hundreds of cancer cell lines, whose sensitivity to several drugs was previously determined. Subsequently, a weighted score in the protein network was defined in order to predict synergistic drug combinations for breast cancer treatment. Finally, we analysed the inhibitory effect of the most promising combinations in different breast cancer cell lines harbouring molecular alterations in PI3K/AKT pathway. Interestingly, our results revealed significant synergism of the drug combinations when compared to single-compound assays. Thus, suggesting this computational approach as a useful tool for the identification of effective and synergistic combinations for breast cancer treatment

Network biology identifies novel apoptosis-related proteins and synergistic drug combinations in breast cancer

Breast cancer is a very heterogeneous disease with a poor prognostic outcome, largely due to its resistance to current cancer therapies. The balance between cell proliferation and apoptosis plays a critical role in determining the overall growth or regression of the tumor in response to treatments. Hence, identifying treatments involved in apoptosis resistance is essential in order to find new therapeutic approaches. The heterogeneity of cancer is rarely due to abnormalities in single genes, but rather reflects the discontinuation of complex intercellular processes. Therefore, a useful way to describe and analyse this heterogeneity is the use of systems biology. This approach is based on the study of the interactions between the elements of a given system with the aim to understand its properties. Particularly, the use of protein-protein interaction networks gives a broader perspective of protein environment without losing the molecular details, providing a deeper understanding of the molecular mechanisms underlying complex pathological processes. Thus, the application of network biology can significantly help the elucidation of novel drug targets and more effective therapies. Since the molecular mechanisms that relate, for instance, changes in expression of the many passenger genes to breast cancer onset and progression are largely unknown, the first objective of this thesis was to identify the role of certain proteins in breast cancer apoptosis, which function on the disease is unknown. With this aim, we functionally characterized two breast cancer passenger genes, PSMC3IP and EPSTI1, to analyse their potential apoptotic role in breast cancer. We first explored the existence of direct physical interactions with annotated breast cancer-apoptotic genes, and subsequently, we examined several apoptotic markers to determine the effect of PSMC3IP and EPSTI1 gene expression modulation in two different human breast cancer cell lines. Overall, our results showed that PSMC3IP and EPSTI1 are able to modulate the extrinsic apoptotic pathway in estrogen receptor positive and triple negative breast cancer cell lines, highlighting them as potential therapeutic targets. Currently approved drug combinations are the result of empirical clinical experience, are not being rationally designed and cover only a small fraction of the potential therapeutic space. Therfore, our second objective was to implement two different network biology approaches in order to predict and validate novel synergistic drug combinations for the treatment of breast cancer, with greater clinical efficacy and reduced side effects. The first approach was based on the quantification of pathway crosstalk inhibition in therapeutic networks. We applied this measure to a set of antineoplastic (cancer drug combined with breast cancer drug) and compassive (non-cancer drug combined with breast cancer drug) combinations. We next validate experimentally the most promising drug combinations in several breast cancer cell lines. Finally, we determined whether the cytotoxic effect of the selected drug combinations was due to apoptosis induction or cell cycle arrest promotion. Overall, our findings highlight two different antineoplastic combinations as promising therapeutic strategies for triple negative breast cancer subtype. The second approach integrated the known human interactome with the basal gene expression measurements in hundreds of cancer cell lines, whose sensitivity to several drugs was previously determined. Subsequently, a weighted score in the protein network was defined in order to predict synergistic drug combinations for breast cancer treatment. Finally, we analysed the inhibitory effect of the most promising combinations in different breast cancer cell lines harbouring molecular alterations in PI3K/AKT pathway. Interestingly, our results revealed significant synergism of the drug combinations when compared to single-compound assays. Thus, suggesting this computational approach as a useful tool for the identification of effective and synergistic combinations for breast cancer treatment

Breast Cancer Genes PSMC3IP and EPSTI1 Play a Role in Apoptosis Regulation

<div><p>A key element to delineate the biology of individual tumors is the regulation of apoptosis. In this work, we functionally characterize two breast cancer associated genes, the proteasome 26S subunit ATPase 3 interacting protein (PSMC3IP) and the epithelial-stromal interaction 1 (EPSTI1), to explore their potential apoptotic role in breast cancer. We first explore the existence of direct physical interactions with annotated BC-apoptotic genes. Based on the generated interaction network, we examine several apoptotic markers to determine the effect of PSMC3IP and EPSTI1 gene expression modulation in two different human breast cancer cell lines to suggest potential molecular mechanisms to unveil their role in the disease. Our results show that PSMC3IP and EPSTI1 are able to modulate the extrinsic apoptotic pathway in estrogen receptor positive and triple negative breast cancer cell lines, highlighting them as potential therapeutic targets.</p></div

Cell viability and recovery.

<p>Cell viability was determined by MTT absorbance assays <b>(A)</b> Histograms showing the viability of PSMC3IP or EPSTI1-overexpressing MDA-MB-231 cells and <b>(B)</b> MCF-7 cells under TRAIL-induced conditions. Based on empty vector (MYC-tag) as a negative control, we do not observe a significant recovery of apoptosis-induced cells after gene overexpression. <b>(C)</b> Viability measurement of gene-depleted MDA-MB-231 cells reveals that EPSTI1 depletion reduces about 50% of viability as compared to siLUC negative control. <b>(D)</b> Intriguingly, in MCF-7 cells, both PSMC3IP and EPSTI1 depletion lead to a decreased viability under basal but not under TRAIL-treated conditions. XIAP was used as an anti-apoptotic reference in all experiments. <i>EPSTI1</i>-depleted cells were previously treated with IFN-α at 1000 U/ml for 8h. In apoptosis-induced conditions, cells were treated with TRAIL for 24h, at 80 or 100ng/mL respectively. Each bar represents the mean ±SD of three experiments performed in duplicate (*<i>P</i> <0.05, **<i>P</i> <0.01, ***<i>P</i> <0.001 vs siLUC).</p

Expression of PSMC3IP and EPSTI1 in normal and breast cancer cell lines.

<p>We inspected the endogenous expression of PSMC3IP <b>(A)</b> and EPSTI1 <b>(B)</b> in two types of breast cancer cell lines, MDA-MB-231 and MCF-7, as compared to a normal breast epithelial cell line, MCF-10A. Estimated protein levels based on densitometry (right) of the immunoblots (left) show a PSMC3IP 19- and 15-fold expression in MDA-MB-231 and MCF-7 cells, while EPSTI1 only shows 1.9- and 1.3-fold in each cell line, respectively. Protein levels were normalized based on the loading control protein β-actin. (*<i>P</i> <0.05, **P<0.01, ***<i>P</i> <0.001 vs MCF-10A cells).</p

miR-146a targets Fos expression in human cardiac cells

miR-146a is a microRNA whose transcript levels are induced in the heart upon activation of NF-kappaB, a transcription factor induced by pro-inflammatory molecules strongly related to the pathogenesis of cardiac disorders. The main goal of this study consisted in studying new roles of miR-146a in cardiac pathological processes caused by the pro-inflammatory cytokine TNF-alpha. Our results demonstrate that miR-146a transcript levels were sharply increased in cardiac ventricular tissue of transgenic mice with specific overexpression of TNF-alpha in the heart, and also in a cardiomyocyte cell line of human origin (AC16) exposed to TNF-alpha. Among all the in silico predicted miR-146a target genes, c-Fos mRNA and protein levels notably decreased after TNF-alpha treatment or miR-146a overexpression. These changes correlated with a diminution in the DNA-binding activity of AP-1, the c-Fos-containing transcription factor complex. Interestingly, AP-1 inhibition was accompanied by a reduction in matrix metalloproteinase (MMP)-9 mRNA levels in human cardiac cells. The specific regulation of this matrix metalloproteinase by miR-146a was further confirmed at the secretion and enzymatic activity levels, as well as after anti-miR-mediated miR-146a inhibition. The results reported here demonstrate that c-Fos is a direct target of miR-146a activity and that c-Fos/AP-1 pathway downregulation by miR-146a has the capacity to inhibit MMP-9 activity. Given that MMP-9 is an AP-1 target gene involved in cardiac remodeling, myocardial dysfunction and progression of heart failure, these findings suggest that miR-146a may be a new and promising therapeutic tool for treating cardiac disorders associated with enhanced inflammation in the heart

Caspase-8 activity modulation.

<p>Caspase-8 activity was quantified by measuring the chromophore levels released from caspase-8 cleaved substrates. Overexpression of PSMC3IP or EPSTI1 in TRAIL-treated MDA-MB-231 <b>(A)</b> and MCF-7 cells <b>(B)</b> decrease caspase-8 activity based on the MYC-tag empty transfection vector (Vector) as control. Caspase-8 activity was also measured after gene silencing in MDA-MB-231 <b>(C)</b> and MCF-7 <b>(D)</b> cells, under basal or TRAIL-treated conditions. Genes were silenced using specific siRNAs targeting <i>XIAP</i>, <i>PSMC3IP</i> or <i>EPSTI1</i> and siRNA against luciferase expression (siLUC) was used as a negative control. <i>EPSTI1</i>-depleted cells were previously treated with IFN-α at 1000 U/ml for 8h. MDA-MB-231 and MCF-7 cells were treated with TRAIL for 24h at 80 or 100ng/mL, respectively. XIAP was used as an anti-apoptotic reference in all experiments. Each bar represents the mean ±SD of three experiments performed in duplicate (*<i>P</i> <0.05, **<i>P</i> <0.01, ***<i>P</i> <0.001 vs MYC-tag vector in overexpression assays and vs siLUCIFERASE in silencing).</p

TRAIL-induced apoptosis in breast cancer cells.

<p><b>(A)</b> MDA-MB-231 cells treated with the apoptosis inducing ligand TRAIL at 80ng/mL for 24h show a moderate decrease in cell viability while <b>(B)</b> MCF-7 cells treated with TRAIL at 100ng/mL.for 24h show a more pronounced decrease in viability. Each bar represents the mean ±SD of three experiments performed in duplicate (*<i>P</i> <0.05, **<i>P</i> <0.01, ***<i>P</i> <0.001 vs untreated cells).</p