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Epithelial ovarian cancer (EOC) can be considered as a stressful and challenging disease among all women in the world, which has been associated with a poor prognosis and its molecular pathogenesis has remained unclear. In recent years, RNA Sequencing (RNA-seq) has become a functional and amazing technology for profiling gene expression. In the present study, RNA-seq raw data from Sequence Read Archive (SRA) of six tumor and normal ovarian sample was extracted, and then analysis and statistical interpretation was done with Linux and R Packages from the open-source Bioconductor. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of key genes and pathways involved in EOC. We identified 1091 Differential Expression Genes (DEGs) which have been reported in various studies of ovarian cancer as well as other types of cancer. Among them, 333 genes were up-regulated and 273 genes were down-regulated. In addition, Differentially Expressed Genes (DEGs) including RPL41, ALDH3A2, ERBB2, MIEN1, RBM25, ATF4, UPF2, DDIT3, HOXB8 and IL17D as well as Ribosome and Glycolysis/Gluconeogenesis pathway have had the potentiality to be used as targets for EOC diagnosis and treatment. In this study, unlike that of any other studies on various cancers, ALDH3A2 was most down-regulated gene in most KEGG pathways, and ATF4 was most up-regulated gene in leucine zipper domain binding term. In the other hand, RPL41 as a regulatory of cellular ATF4 level was up-regulated in many term and pathways and augmentation of ATF4 could justify the increase of RPL41 in the EOC. Pivotal pathways and significant genes, which were identified in the present study, can be used for adaptation of different EOC study. However, further molecular biological experiments and computational processes are required to confirm the function of the identified genes associated with EOC.

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.

© The Author(s) 2021. Open AccessThis article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing,adaptation, distribution and reproduction in any medium or format, as long as you giveappropriate credit to the original author(s) and the source, provide a link to the CreativeCommons license, and indicate if changes were made. The images or other third partymaterial in this article are included in the article’s Creative Commons license, unlessindicated otherwise in a credit line to the material. If material is not included in thearticle’s Creative Commons license and your intended use is not permitted by statutoryregulation or exceeds the permitted use, you will need to obtain permission directly fromthe copyright holder. To view a copy of this license, visithttp://creativecommons.org/licenses/by/4.0/., 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.

Worldwide prostate cancer (PCa) is recognized as the second most common diagnosed cancer and the fifth leading cause of cancer death among men globally. Rising incidence rates of PCa have been observed over the last few decades. It is necessary to improve prostate cancer detection, diagnosis, treatment and survival. However, there are few reliable biomarkers for early prostate cancer diagnosis and prognosis. In the current study, systems biology method was applied for transcriptomic data analysis to identify potential biomarkers for primary PCa. We firstly identified differentially expressed genes (DEGs) between primary PCa and normal samples. Then the DEGs were mapped in Wikipathways and gene ontology database to conduct functional categories enrichment analysis. 1575 unique DEGs with adjusted p-value < 0.05 were achieved from two sets of DEGs. 132 common DEGs between two sets of DEGs were retrieved. The final DEGs were selected from 60 common upregulated and 72 common downregulated genes between datasets. In conclusion, we demonstrated some potential biomarkers (FOXA1, AGR2, EPCAM, CLDN3, ERBB3, GDF15, FHL1, NPY, DPP4, and GADD45A) and HIST2H2BE as a candidate one which are tightly correlated with the pathogenesis of PCa.

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.

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.

Cellular redox homeostasis is the important tool for normal cell function and survival. Oxidants, reductants and antioxidants are the players to maintain cellular homeostasis balance. However, in some conditions like cancer, the concentration and activation of these players are disturbed. This study walks you through the molecular mechanism of redox homeostasis to describe how expression level of these players would help colorectal cancer (CRC) cells continue proliferation and survive in the hypoxic environment of tumor. We proposed that O2-concentration is not detrimentally high in CRC cells since expression level of MnSOD didn’t change noticeably. We also suggested that High proliferative CRC cells obtain their energy by oxidation of H2S in or Electron transport chain (ETC) and keep the adequate concentration of H2S by diminishing the expression level of enzymes involved in sulfide oxidation pathway. Reduction in hydrogen sulfide oxidation results in a decrease in the level of GSH. Glutathione peroxidase enzyme requires GSH to convert H2O2into oxygen and water. Therefore, Level of hydrogen peroxide stays high which leads to an increase in cell proliferation. Furthermore, we analyzed the expression level of transcription factors sensitive to redox messengers.

Motivation: There are important molecular information hidden in the ocean of big data could be achieved by recognizing true relationships between different molecules. Human mind is very limited to find all molecular connections. Therefore, we introduced an integrated data mining strategy to find all possible relationships between molecular components in a biological context. To demonstrate how this approach works, we applied it on proto-oncogene c-Src. Results: Here we applied a data mining scheme on genomic, literature and signaling databases to obtain necessary biological information for pathway inference. Using R programming language, two large edgelists were constructed from KEGG and OmniPath signaling databases. Next, An R script was developed by which pathways were discovered by assembly of edge information in the constructed signaling networks. Then, valid pathways were distinguished from the invalid ones using molecular information in articles and genomic data analysis. Pathway inference was performed on predicted pathways starting with Src and ending with the DEGs whose expression were affected by c-Src overactivation. Moreover, some positive and negative feedback loops were proposed based on the gene expression results. In fact, this simple but practical flowchart will open new insights into interactions between cellular components and help biologists look for new possible molecular relationships that have not been reported neither in signaling databases nor as a signaling pathway.

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.

Epithelial-Mesenchymal Transition (EMT) is the major player of tumor invasiveness whose inhibition is challenged by the redundancy of multiple inducing factors in the tumor microenvironment. Here, we applied a systems pharmacology approach by integrating network-based analyses with multiple bioinformatic resources to propose a combinatorial drug regimen that reverses EMT phenotype in aggressive cancers. The results demonstrated that histone deacetylases were central targets to relay tumor-host interactions by tuning the expression of multiple epithelial versus mesenchymal genes. Moreover, SRC and IKBK served as the principal intracellular kinases regulating information flow from tumor microenvironment to multiple signaling pathways associated with EMT. To experimentally validate these predictions, we inhibited the pinpointed targets with already prescribed drugs and observed that whereas low dose mono-therapy failed to limit cell dispersion in a three-dimensional (3D) microfluidic device as a metric of EMT, the combinatorial regimen fully inhibited dispersion and invasion of cancer cells in collagen spheroids toward co-cultured endothelial cells while maintaining their survival. Taking into account Food and Drug Administered (FDA)-approval as well as safety profiles of the proposed drugs, we offer a combinatorial regimen with immediate translational implications to inhibit EMT in aggressive cancers. Besides, our study provides a grasp on the interdisciplinary methodologies behind a plethora of the introduced biologist-friendly bioinformatic tools for bench and bed cancer scientists to help them effectively plan their experiments.