Research and Therapeutic Approaches in Stem Cell Genome Editing by CRISPR Toolkit.

The most widely used genome editing toolkit is CRISPR (clustered regularly interspaced short palindromic repeats). It provides the possibility of replacing and modifying DNA and RNA nucleotides. Furthermore, with advancements in biological technology, inhibition and activation of the transcription of specific gene(s) has become possible. Bioinformatics tools that target the evolution of CRISPR-associated protein 9 (Cas9) turn this protein into a vehicle that is specific for a DNA or RNA region with single guide RNA (sgRNA). This toolkit could be used by researchers to investigate the function of stem cell gene(s). Here, in this review article, we cover recent developments and applications of this technique in stem cells for research and clinical purposes and discuss different CRISPR/Cas technologies for knock-out, knock-in, activation, or inhibition of gene expression. Additionally, a comparison of several deliveries and off-target detecting strategies is discussed.

Association of Polymorphisms in miR146a, an Inflammation-Associated MicroRNA, with the Risk of Idiopathic Recurrent Spontaneous Miscarriage: A Case-Control Study.

It has been established that microRNAs (miRNAs) are involved in the regulation of immune responses and serve as biomarkers of inflammatory diseases as well as recurrent spontaneous miscarriage (RSM). Herein, we aimed to study the relationship between three functional miR146a gene polymorphisms with idiopathic RSM (IRSM) susceptibility. We recruited 161 patients with IRSM and 177 healthy women with at least one live birth and without a history of abortion. Genotyping was performed using RFLP-PCR and ARMS-PCR methods. We found that the rs6864584 T/C decreased the risk of IRSM under dominant TT+TC vs. CC (OR = 0.029) and allelic C vs. T (OR = 0.028) contrast models. Regarding rs2961920 A/C and rs57095329 A/G polymorphisms, the enhanced risk of IRSM was observed under different genetic contrasted models, including the codominant CC vs. AA (OR = 2.81 for rs2961920) and codominant GG vs. AA (OR = 2.36 for rs57095329). After applying a Bonferroni correction, haplotype analysis revealed a 51% decreased risk of IRSM regarding the ACA genotype combination. This is the first study reporting that miR146a rs57095329 A/G, rs2961920A/C, and rs6864584 T/C polymorphisms are associated with the risk of IRSM in a southern Iranian population. Performing replicated case-control studies on other ethnicities is warranted to outline the precise effects of the studied variants on the risk of gestational trophoblastic disorders.

Association between HOTAIR Polymorphisms and Lymphoma.

INTRODUCTION: The long non-coding RNA, HOTAIR, involved in cancer initiation and development. OBJECTIVE: The aim of present study was to investigate the association of single nucleotide polymorphisms in the HOTAIR gene with lymphoma. METHODS: We conducted a case-control study of 156 individuals with non-Hodgkin Lymphoma (NHL), 53 individuals with Hodgkin's lymphoma (HL), and 245 unrelated healthy individuals to identify the genotype frequencies of each polymorphism. Genotyping of the SNPs (rs920778 T>C, rs1899663 G>T, rs4759314 A>G and rs12826786 C>T) was carried out using the polymerase chain reaction-restriction fragment length polymorphism. RESULTS AND CONCLUSION: The finding showed that rs1899663 variant of HOTAIR gene significantly decreased the risk of NHL in codominant, dominant, over-dominant and allelic inheritance models. We did not find any association between HOTAIR rs12826786, rs920788 and rs4759314 variants and NHL. The results indicated that neither the overall chi-square comparison of the cases and controls, nor the logistic regression analysis showed any association between HOTAIR polymorphisms and HL. Conclusively, our findings showed that rs1899663 of HOTAIR significantly decreased the risk of non-Hodgkin Lymphoma.

Association between the IL-1A, IL-1B and IL-1R polymorphisms and lymphoma.

We investigate the impact of IL-1A, IL-1B and IL-1R1 polymorphism on lymphoma. This study consisted of 155 Non-Hodgkin's lymphoma (NHL) patients 55 Hodgkin's lymphoma (HL) patients and 150 healthy individuals. PCR-RFLP method and ARMS PCR were used for genotyping of IL-1A rs3783553, IL-1B rs3917356, rs16944, IL-1R1 rs10490571 and IL-1A rs3783550 polymorphism. The results showed that the CC genotype of rs3783550 as well Ins/del of rs3783553 increased the risk of NHL. In contrast the AG genotype of rs3917356 and AG also AG + AA genotype of rs10490571 decreased the risk of NHL. The result revealed that the CC genotype of rs3783550 and AG genotype of rs3917356 increased risk of HL.

Transcriptome and Network Dissection of Microsatellite Stable and Highly Instable Colorectal Cancer.

Background: Colorectal cancer (CRC) is one of the most common cancers worldwide with high number of mortality every year. Microsatellite instability (MSI) is a considerable feature of CRC which affects prognosis and treatment. High level of MSI or MSI-high (MSI-H) colorectal cancer has better prognosis and immunotherapy response, while microsatellite stable (MSS) CRC has better response to 5-fluorouracil (5-FU)-based chemotherapy. More studies are needed, specifically on MSS CRC which has worse prognosis, to further reveal biological differences and similarities between MSS and MSI colorectal cancer, which may equip us with the knowledge to develop more promising therapeutic approaches to target both types or be more effective for each type. Methods: We aimed to find affected biological processes and their regulators in both type, MSS and MSI-H, of CRC; as well as reveal specific ones in each type. We applied meta- and network analysis on freely available transcriptome data in MSS and MSI-H colorectal cancer from gene expression omnibus (GEO) database to detect common differentially expressed genes (DEGs) and critical biological processes and predict their most significant regulators. Results: Our results demonstrate considerable up and downregulation in cell cycle and lipid catabolism processes, respectively; and introduced MYC and FOXM1 as two central and up-stream regulators of DEGs in both type of CRC. Chemokine-mediated processes displayed up-regulation in MSI-H type, while metastasis-related processes showed more activation in MSS CRC. Additionally, DACH1 and TP53 were detected as two important transcription factors that differentially expressed just in MSS and MSI-H, respectively. Conclusion: Our results can explain why MSI and MSS CRC display different immunotherapy response, prognosis, and metastasis feature. Moreover, our predicted up-stream regulators in the regulatory networks may be promising therapeutic targets.

The Roles of miRNAs in Medulloblastoma: A Systematic Review.

Medulloblastoma is considered one of the most threatening malignant brain tumors with an extremely high mortality rate in children. In the medulloblastoma, there are several genes and mutations found to work in an unregulated manner that works together to push the cells into a cancerous state. With the discovery of non-coding RNAs such as microRNAs (miRNAs), it has been shown that a different layer of gene regulations may be disrupted which would cause cancer. This fact led scientists to put their focus on the role of miRNAs in cancer. A mature miRNA contains a seed sequence which gives the miRNA to identify and attach to the interest mRNA; this attachment may lead degradation of mRNA or suppress of translation of the mRNA. The expression of miRNAs in medulloblastoma shows that some of these non-coding RNAs are overexpressed (OncomiRs) which help cells to proliferate and keep their stemness features. On the other hand, there are other forms of these miRNAs which normally inhibit cell proliferation and promote cell differentiation (tumor suppressor). These are down-regulated during cancer progression. In this systematic review, we attempted to gather several important studies on miRNAs' role in medulloblastoma tumors and the importance of these non-coding RNAs in the future study of cancer.

Application of an Artificial Neural Network in the Diagnosis of Chronic Lymphocytic Leukemia.

Introduction Chronic lymphocytic leukemia (CLL) is one of the most common types of leukemia, and the early diagnosis of patients coincides with their proper treatment and survival. If patients are diagnosed late or proper treatment is not applied, it may lead to harmful results. Several methods could be used for the diagnosis of leukemia; some of these include complete blood count (CBC), immunophenotyping, lymph node biopsy, chest X-ray, computerized tomography (CT) scan, and ultrasound. Most of these methods are time-consuming and an application of more than one method will result as intended. This acknowledgment stresses the necessity of rapid and proper diagnosis for leukemia based on clinical and medical findings, inasmuch as it was decided to apply the artificial neural network (ANN) in order to identify a molecular biomarker for rapid leukemia diagnosis from blood samples and evaluate its potential for the detection of cancer. Materials & methods The independent sample t-test was applied with the Statistical Package for the Social Sciences (SPSS; IBM Corp, Armonk, NY, US) software on the microarray gene expression data of Gene Expression Omnibus (GEO) datasets (GSE22529); 12 genes that had shown the highest differences (among parameters whose p-value was less than 0.01) were selected for further ANN analysis. The selected genes of 53 patients were applied to the training network algorithm, with a learning rate of 0.1. Results The results showed a high accuracy of the relationship between the output of the trained network and the test data. The area under the receiver operating characteristic (ROC) curve was 0.991, which provides proof of the precision and the relationship with identifying Gelsolin as a potential biomarker for this research. Conclusions With these results, it was concluded that the training process of the ANN could be applied to rapid CLL diagnosis and finding a potential biomarker. Besides, it is suggested that this method could be performed to diagnose other forms of cancer in order to get a rapid and reliable outcome.

Bioinformatics Analysis of Key Genes and Pathways for Medulloblastoma as a Therapeutic Target

Introduction: One of the major challenges in cancer treatment is the lack of specific and accurate treatment in cancer. Data analysis can help to understand the underlying molecular mechanism that leads to better treatment. Increasing availability and reliability of DNA microarray data leads to increase the use of these data in a variety of cancers. This study aimed at applying and evaluating microarray data analyzing, identification of important pathways and gene network for medulloblastoma patients to improve treatment approaches especially target therapy. Methods: In the current study, Microarray gene expression data (GSE50161) were extracted from Geo datasets and then analyzed by the affylmGUI package to predict and investigate upregulated and downregulated genes in medulloblastoma. Then, the important pathways were determined by using software and gene enrichment analyses. Pathways visualization and network analyses were performed by Cytoscape. Results: A total number of 249 differentially expressed genes (DEGs) were identified in medulloblastoma compared to normal samples. Cell cycle, p53, and FoxO signaling pathways were indicated in medulloblastoma, and CDK1, CCNB1, CDK2, and WEE1 were identified as some of the important genes in the medulloblastoma. Conclusion: Identification of critical and specific pathway in any disease, in our case medulloblastoma, can lead us to better clinical management and accurate treatment and target therapy.