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Background. Endometriosis is the most prevalent gynecological disease with elusive etiology. The mysterious entity and the lack of noninvasive diagnostic methods affect women’s lives negatively. This study is aimed at finding the relationship between miR-340-5p, 92a-3p, and miR-381-3p and the pathogenesis of endometriosis in endometrial mesenchymal stem-like cells (eMSCs) of endometriosis and assessing their potential as a noninvasive biomarker in plasma. Methods. Peripheral blood and eMSC specimens were collected from suspected women of endometriosis before laparoscopy. Total RNA was isolated from plasma and cultured eMSCs to synthesize complementary DNA. The expression of miR-340-5p, miR-92a-3p, and miR-381-3p was analyzed by RT-qPCR. To understand these miRNAs’ role, we also did a bioinformatic analysis. Results. There was a downregulation of miR-340-5p, miR-92a-3p, and miR-381-3p in plasma, and the upregulation of miR-340-5p and the downregulation of miR-92a-3p and miR-381-3p in eMSCs of women with endometriosis. There was a positive concordance between the expression of miR-92a-3p and miR-381-3p in plasma and eMSCs. Our study also showed three genes, Solute Carrier Family 6 Member 8 (SLC6A8), Zinc Finger Protein 264 (ZNF264), and mouse double minute 2 (MDM2), as common targets of these miRNAs. Conclusions. This study has been one of the first attempts to examine the expression of miR-340-5p, miR-92a-3p, and miR-381-3p in both plasma and eMSCs and revealed their possible role in endometriosis based on in silico analysis. Biomarkers pave the way to develop a new therapeutic approach to the management or treatment of endometriosis patients. Our result as a first report shows that combined levels of miRNAs 340-5p and 381-3p may have the potential to be utilized as diagnostic biomarkers for endometriosis.

Breast cancer is a complex disease exhibiting a great degree of heterogeneity due to different molecular subtypes. Notch signaling regulates the differentiation of breast epithelial cells during normal development and plays a crucial role in breast cancer progression through the abnormal expression of the Notch up-and down-stream effectors. To date, there are only a few patient-centered clinical studies using datasets characterizing the role of Notch signaling pathway regulators in breast cancer; thus, we investigate the role and functionality of these factors in different subtypes using publicly available databases containing records from large studies. High-throughput genomic data and clinical information extracted from TCGA were analyzed. We performed Kaplan–Meier survival and differential gene expression analyses using the HALLMARK_NOTCH_SIGNALING gene set. To determine if epigenetic regulation of the Notch regulators contributes to their expression, we analyzed methylation levels of these factors using the TCGA HumanMethylation450 Array data. Notch receptors and ligands expression is generally associated with the tumor subtype, grade, and stage. Furthermore, we showed gene expression levels of most Notch factors were associated with DNA methylation rate. Modulating the expression levels of Notch receptors and effectors can be a potential therapeutic approach for breast cancer. As we outline herein, elucidating the novel prognostic and regulatory roles of Notch implicate this pathway as an essential mediator controlling breast cancer progression.

Recent genetic findings and correlated developments in genomic techniques have led to the commercialization of novel diagnostic platforms for studying disease or evaluating therapeutic results in patients. This field is known as ''personalized medicine,'' and uses the patient's genetic structure to tailor approaches for patient specific disease detection, treatment, or prevention. Personalized medicine is embedded in the belief that since individuals have unique features at the molecular, physiological, environmental exposure, and behavioral levels, they may need to have mediations provided to them for diseases they have that are tailored to these unique characteristics. Personalized diagnostic tests are used to identify patient-to-patient differences in gene or protein expression levels, which performance as indicators for drug treatments or disease prognosis. In order, medical experts be able to better answer questions such as: ''who must be treated with which drug?'' and ''How should the treatment be ordered?'' Clinical genetic testing began over 30 years ago with the accessibility of mutation detection. Since then, the field has intensely altered to include genome sequencing and genome-wide analyses using microarrays and nextgeneration sequencing. The identification of deoxyribonucleic acid (DNA) sequence variants related with common diseases stimulated the availability of testing for personal disease risk estimation, and created commercial opportunities for direct-to-consumer genetic testing companies that examine these variants. This genetic risks, are the key components of the personalized medicine, which aims to apply personal genomic and other relevant data into a patient's clinical valuation to more accurately guide medical management. Direct-to-consumer (DTC) DNA testing, by providing a wide range of personal genomic information directly to its consumers. These companies, illustrated by the well-established 23andMe, usually carry out an analysis of single nucleotide polymorphisms (SNPs) using DNA extracted from a saliva sample. These genetic data are then assimilated and provided direct to the customer, with different interpretation.

Background: Breast cancer (BC) is the most common cancer in women. The incidence and morbidity of BC are expected to rise rapidly. The stage at which BC is diagnosed has a significant impact on clinical outcomes. When detected early, an overall 5-year survival rate of up to 90% is possible. Although numerous studies have been conducted to assess the prognostic and diagnostic values of non-coding RNAs (ncRNAs) in breast cancer, their overall potential remains unclear. In this field of study, there are various systematic reviews and meta-analysis studies that report volumes of data. In this study, we tried to collect all these systematic reviews and meta-analysis studies in order to re-analyze their data without any restriction to breast cancer or non-coding RNA type, to make it as comprehensive as possible.Methods: Three databases, namely, PubMed, Scopus, and Web of Science (WoS), were searched to find any relevant meta-analysis studies. After thoroughly searching, the screening of titles, abstracts, and full-text and the quality of all included studies were assessed using the AMSTAR tool. All the required data including hazard ratios (HRs), sensitivity (SENS), and specificity (SPEC) were extracted for further analysis, and all analyses were carried out using Stata.Results: In the prognostic part, our initial search of three databases produced 10,548 articles, of which 58 studies were included in the current study. We assessed the correlation of non-coding RNA (ncRNA) expression with different survival outcomes in breast cancer patients: overall survival (OS) (HR = 1.521), disease-free survival (DFS) (HR = 1.33), recurrence-free survival (RFS) (HR = 1.66), progression-free survival (PFS) (HR = 1.71), metastasis-free survival (MFS) (HR = 0.90), and disease-specific survival (DSS) (HR = 0.37). After eliminating low-quality studies, the results did not change significantly. In the diagnostic part, 22 articles and 30 datasets were retrieved from 8,453 articles. The quality of all studies was determined. The bivariate and random-effects models were used to assess the diagnostic value of ncRNAs. The overall area under the curve (AUC) of ncRNAs in differentiated patients is 0.88 (SENS: 80% and SPEC: 82%). There was no difference in the potential of single and combined ncRNAs in differentiated BC patients. However, the overall potential of microRNAs (miRNAs) is higher than that of long non-coding RNAs (lncRNAs). No evidence of publication bias was found in the current study. Nine miRNAs, four lncRNAs, and five gene targets showed significant OS and RFS between normal and cancer patients based on pan-cancer data analysis, demonstrating their potential prognostic value.Conclusion: The present umbrella review showed that ncRNAs, including lncRNAs and miRNAs, can be used as prognostic and diagnostic biomarkers for breast cancer patients, regardless of the sample sources, ethnicity of patients, and subtype of breast cancer.

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Background: Colorectal cancer (CRC) with a high prevalence is recognized as the fourth most common cause of cancer-related death globally. Over the past decade, there has been growing interest in the network of tumor cells, stromal cells, immune cells, blood vessel cells, and fibroblasts that comprise the tumor microenvironment (TME) to identify new therapeutic interventions.Methods: Databases, such as Google Scholar, PubMed, and Scopus, were searched to provide an overview of the recent research progress related to targeting the TME as a novel therapeutic approach.Results: Tumor microenvironment as a result of the cross talk between these cells may result in either advantages or disadvantages in tumor development and metastasis, affecting the signals and responses from the surrounding cells. Whilst chemotherapy has led to an improvement in CRC patients' survival, the metastatic aspect of the disease remains difficult to avoid. Conclusions:The present review emphasizes the structure and function of the TME, alterations in the TME, its role in the incidence and progression of CRC, the effects on tumor development and metastasis, and also the potential of its alterations as therapeutic targets. It should be noted that providing novel studies in this field of research might help us to achieve practical therapeutic strategies based on their interaction.

To designate the probable most important differentially expressed genes and genetic pathways in Wilms tumor and assess their expression and diagnostic potential by RT-PCR and statistical analysis. Systematic review of the literature and various bioinformatics analysis was carried out to gather and narrow down data. The expression of end-resulting genes was compared in Wilms tumor and normal tissue samples using RT-PCR. Statistical tests reported the diagnostic accuracy of genes and their correlation with clinicopathological features. Four genes including CDH1, NCAM1, EGF, and IGF2 were designated. The panel combining them has 100% sensitivity and specificity in differentiating tumors from normal tissue. Eight pathways, most involved in cell–cell and cell-basal matrix junction interactions, were found to be associated with disease pathogenesis. The suggested genes should undergo further evaluation to be validated as diagnostic biomarkers. Further research on the eight proposed pathways is recommended.