Whole exome sequencing in 17 consanguineous Iranian pedigrees expands the mutational spectrum of inherited retinal dystrophies.

Inherited retinal dystrophies (IRDs) constitute one of the most heterogeneous groups of Mendelian human disorders. Using autozygome-guided next-generation sequencing methods in 17 consanguineous pedigrees of Iranian descent with isolated or syndromic IRD, we identified 17 distinct genomic variants in 11 previously-reported disease genes. Consistent with a recessive inheritance pattern, as suggested by pedigrees, variants discovered in our study were exclusively bi-allelic and mostly in a homozygous state (in 15 families out of 17, or 88%). Out of the 17 variants identified, 5 (29%) were never reported before. Interestingly, two mutations (GUCY2D:c.564dup, p.Ala189ArgfsTer130 and TULP1:c.1199G > A, p.Arg400Gln) were also identified in four separate pedigrees (two pedigrees each). In addition to expanding the mutational spectrum of IRDs, our findings confirm that the traditional practice of endogamy in the Iranian population is a prime cause for the appearance of IRDs.

Systems Biomedicine of Primary and Metastatic Colorectal Cancer Reveals Potential Therapeutic Targets.

Colorectal cancer (CRC) is one of the major causes of cancer deaths across the world. Patients' survival at time of diagnosis depends mainly on stage of the tumor. Therefore, understanding the molecular mechanisms from low-grade to high-grade stages of cancer that lead to cellular migration from one tissue/organ to another tissue/organ is essential for implementing therapeutic approaches. To this end, we performed a unique meta-analysis flowchart by identifying differentially expressed genes (DEGs) between normal, primary (primary sites), and metastatic samples (Colorectal metastatic lesions in liver and lung) in some Test datasets. DEGs were employed to construct a protein-protein interaction (PPI) network. A smaller network containing 39 DEGs was then extracted from the PPI network whose nodes expression induction or suppression alone or in combination with each other would inhibit tumor progression or metastasis. These DEGs were then verified by gene expression profiling, survival analysis, and multiple Validation datasets. We suggested for the first time that downregulation of mitochondrial genes, including ETHE1, SQOR, TST, and GPX3, would help colorectal cancer cells to produce more energy under hypoxic conditions through mechanisms that are different from "Warburg Effect". Augmentation of given antioxidants and repression of P4HA1 and COL1A2 genes could be a choice of CRC treatment. Moreover, promoting active GSK-3ß together with expression control of EIF2B would prevent EMT. We also proposed that OAS1 expression enhancement can induce the anti-cancer effects of interferon-gamma, while suppression of CTSH hinders formation of focal adhesions. ATF5 expression suppression sensitizes cancer cells to anchorage-dependent death signals, while LGALS4 induction recovers cell-cell junctions. These inhibitions and inductions would be another combinatory mechanism that inhibits EMT and cell migration. Furthermore, expression inhibition of TMPO, TOP2A, RFC3, GINS1, and CKS2 genes could prevent tumor growth. Besides, TRIB3 suppression would be a promising target for anti-angiogenic therapy. SORD is a poorly studied enzyme in cancer, found to be upregulated in CRC. Finally, TMEM131 and DARS genes were identified in this study whose roles have never been interrogated in any kind of cancer, neither as a biomarker nor curative target. All the mentioned mechanisms must be further validated by experimental wet-lab techniques.

AutoMap is a high performance homozygosity mapping tool using next-generation sequencing data.

Homozygosity mapping is a powerful method for identifying mutations in patients with recessive conditions, especially in consanguineous families or isolated populations. Historically, it has been used in conjunction with genotypes from highly polymorphic markers, such as DNA microsatellites or common SNPs. Traditional software performs rather poorly with data from Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS), which are now extensively used in medical genetics. We develop AutoMap, a tool that is both web-based or downloadable, to allow performing homozygosity mapping directly on VCF (Variant Call Format) calls from WES or WGS projects. Following a training step on WES data from 26 consanguineous families and a validation procedure on a matched cohort, our method shows higher overall performances when compared with eight existing tools. Most importantly, when tested on real cases with negative molecular diagnosis from an internal set, AutoMap detects three gene-disease and multiple variant-disease associations that were previously unrecognized, projecting clear benefits for both molecular diagnosis and research activities in medical genetics.

Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?

Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.

Integrated use of bioinformatic resources reveals that co-targeting of histone deacetylases, IKBK and SRC inhibits epithelial-mesenchymal transition in cancer.

With the advent of high-throughput technologies leading to big data generation, increasing number of gene signatures are being published to predict various features of diseases such as prognosis and patient survival. However, to use these signatures for identifying therapeutic targets, use of additional bioinformatic tools is indispensible part of research. Here, we have generated a pipeline comprised of nearly 15 bioinformatic tools and enrichment statistical methods to propose and validate a drug combination strategy from already approved drugs and present our approach using published pan-cancer epithelial-mesenchymal transition (EMT) signatures as a case study. We observed that histone deacetylases were critical targets to tune expression of multiple epithelial versus mesenchymal genes. Moreover, SRC and IKBK were the principal intracellular kinases regulating multiple signaling pathways. To confirm the anti-EMT efficacy of the proposed target combination in silico, we validated expression of targets in mesenchymal versus epithelial subtypes of ovarian cancer. Additionally, we inhibited the pinpointed proteins in vitro using an invasive lung cancer cell line. We found that whereas low-dose mono-therapy failed to limit cell dispersion from collagen spheroids in a microfluidic device as a metric of EMT, the combination fully inhibited dissociation and invasion of cancer cells toward cocultured endothelial cells. Given the approval status and safety profiles of the suggested drugs, the proposed combination set can be considered in clinical trials.

An insight to HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) pathogenesis; evidence from high-throughput data integration and meta-analysis.

BACKGROUND: Human T-lymphotropic virus 1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a progressive disease of the central nervous system that significantly affected spinal cord, nevertheless, the pathogenesis pathway and reliable biomarkers have not been well determined. This study aimed to employ high throughput meta-analysis to find major genes that are possibly involved in the pathogenesis of HAM/TSP. RESULTS: High-throughput statistical analyses identified 832, 49, and 22 differentially expressed genes for normal vs. ACs, normal vs. HAM/TSP, and ACs vs. HAM/TSP groups, respectively. The protein-protein interactions between DEGs were identified in STRING and further network analyses highlighted 24 and 6 hub genes for normal vs. HAM/TSP and ACs vs. HAM/TSP groups, respectively. Moreover, four biologically meaningful modules including 251 genes were identified for normal vs. ACs. Biological network analyses indicated the involvement of hub genes in many vital pathways like JAK-STAT signaling pathway, interferon, Interleukins, and immune pathways in the normal vs. HAM/TSP group and Metabolism of RNA, Viral mRNA Translation, Human T cell leukemia virus 1 infection, and Cell cycle in the normal vs. ACs group. Moreover, three major genes including STAT1, TAP1, and PSMB8 were identified by network analysis. Real-time PCR revealed the meaningful down-regulation of STAT1 in HAM/TSP samples than AC and normal samples (P = 0.01 and P = 0.02, respectively), up-regulation of PSMB8 in HAM/TSP samples than AC and normal samples (P = 0.04 and P = 0.01, respectively), and down-regulation of TAP1 in HAM/TSP samples than those in AC and normal samples (P = 0.008 and P = 0.02, respectively). No significant difference was found among three groups in terms of the percentage of T helper and cytotoxic T lymphocytes (P = 0.55 and P = 0.12). CONCLUSIONS: High-throughput data integration disclosed novel hub genes involved in important pathways in virus infection and immune systems. The comprehensive studies are needed to improve our knowledge about the pathogenesis pathways and also biomarkers of complex diseases.

Phytosomal-curcumin antagonizes cell growth and migration, induced by thrombin through AMP-Kinase in breast cancer.

Here we explored the antitumor-activity of novel-formulated-form of curcumin (phytosomal-encapsulated-curcumin) or in combination with 5-FU in breast cancer. The antiproliferative activity was assessed in 2D and 3-dimensional cell-culture-model. The migratory-behaviors of the cells were determined by migration assay. The expression levels of CyclinD1,GSK3a/b, P-AMPK, MMP9, and E-cadherin were studied by qRT-PCR and/or Western blotting. The anti-inflammatory of nano-curcumin was assessed, while antioxidant activity was evaluated by malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), and total thiols (T-SH). To understand dynamic behavior of genes, we reconstructed a Boolean network, while the robustness of this model was evaluated by Hamming distance. phytosomal-curcumin suppressed cell-growth followed by tumor-shrinkage in 3D model through perturbation of AMP-activated protein kinase. Curcumin reduced the invasiveness of MCF-7 through perturbation of E-cadherin. Moreover, phytosomal-curcumin inhibited the tumor growth in xerograph model. Histological staining of tumor tissues revealed vascular disruption and RBC extravasation, necrosis, tumor stroma, and inflammation. Co-treatment of curcumin and 5-FU reduced the lipid-peroxidation and increased MDA/SOD level. Of note, curcumin reduced cyclinD-expression in breast cancer cell treated with thrombin, and activates AMPK in a time-dependent manner. Also suppression of AMPK abrogated inhibitory effect of phytosomal-curcumin on thrombin-induced cyclin D1 over-expression, suggesting that AMPK is essential for anti-proliferative effect of this agent in breast cancer. Our finding demonstrated that phytosomal-curcumin antagonizes cell growth and migration, induced by thrombin through AMP-Kinase in breast cancer, supporting further-investigations on the therapeutic potential of this novel anticancer agent in treatment of breast cancer.

In vitro fibroblast migration by sustained release of PDGF-BB loaded in chitosan nanoparticles incorporated in electrospun nanofibers for wound dressing applications.

Migration of fibroblasts into wound area is a critical phenomenon in wound healing process. We used an appropriate system to fabricate an electrospun bioactive scaffold with controlled release of PDGF-BB in order to induce migration of primary skin fibroblast cells. First of all, protein-loaded chitosan nanoparticles based on ionic gelation interaction between chitosan and sodium tripolyphosphate were prepared. Then polycaprolactone electrospun fibers containing chitosan nanoparticles or PDGF-BB-loaded chitosan nanoparticles were prepared. Cellular attachment and morphology of cells seeded on scaffolds with or without PDGF-BB were evaluated by using a fluorescence microscope and scanning electron microscopy. Cells were well-oriented 72 h after seeding on the scaffolds containing PDGF-BB. The mean aspect ratio of populations on scaffold containing PDGF-BB-loaded chitosan nanoparticles was significantly greater than those on the scaffold containing chitosan nanoparticles but no PDGF-BB. Furthermore, the Arp2 gene, which is involved in cell protrusion formation, showed about three times more expression at mRNA level, in cells seeding on PDGF-BB-containing scaffold compared to cells seeding on scaffold containing only chitosan nanoparticles, using Real Time PCR test. Finally, under agarose migration assay results demonstrated that cells' chemotaxic behavior was more toward scaffold containing PDGF-BB compared to the PDGF-BB alone or FBS group. In addition, in terms of distance, the cell mass could grow faster, in response to scaffold containing PDGF-BB compared to FBS or PDGF-BB alone; however, the number of migrating cells might be the same or significantly higher in the latter groups.

A systems biology analysis protein-protein interaction of NASH and IBD based on comprehensive gene information.

AIM: Analysis reconstruction networks from two diseases, IBD and NASH and their relationship, based on systems biology methods. BACKGROUND: IBD and NASH are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on co-existence of these two diseases. In addition, they have some similar risk factors such as age, obesity, and insulin resistance. Therefore, systems biology approach can help to discover their relationship. METHODS: DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. Based on degree and Betweenness, hubs and bottleneck nodes were defined. RESULTS: Common genes between IBD and NASH construct a network with 99 nodes. Common genes between IBD and NASH were extracted and imported to STRING database to construct PPI network. The resulting network contained 99 nodes and 333 edges. Five genes were selected as hubs: JAK2, TLR2, TP53, TLR4 and STAT3 and five genes were selected as bottleneck including: JAK2, TP53, AGT, CYP3A4 and TLR4. These genes were hubs in analysis network that was constructed from hubs of NASH and IBD networks. CONCLUSION: Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.

Insulin producing cells generation by overexpression of miR-375 in adipose-derived mesenchymal stem cells from diabetic patients.

Diabetes Mellitus (DM) is a systematic disease, which happens because of destruction of islets of Langerhans in the pancreas and systematic resistance to insulin. The lack of donor for pancreas transplantation and risk of transplant rejection is the main challenge in the treatment of this disease. Stem cells are proper and sufficient source for creating insulin-producing cells (IPC). In this study adipose tissue was provided from diabetic patients operated for liposuction and then adipose derived stem cells (ADSCs) were isolated, characterized and then treated by lentiviruses containing miR-375, after 7, 14 and 21 days of induction, islet-like clusters (ILC) specific genes including insulin and PDX1 were evaluated by Real Time RT-PCR. Finally, immunocytochemistry was also used for evaluation of these markers in the protein level. The results were shown that insulin and PDX1 genes and proteins expression significantly increased in transduced stem cells compared to the control group. According to the results it can be concluded that islet-like clusters can be achieved from ADSCs by overexpression of miR-375.