ABSTRACT
Cervical Cancer (CC) is one of the most prevalent neoplasms among women, considered the leading cause of gynecological death worldwide, and the fourth most common type of cancer. Regional metastasis is closely related to the low effectiveness of treatment, and validating biomarkers can optimize accuracy in diagnosis and prognosis. Among the potential biomarkers associated with disease metastasis are circular RNAs (circRNAs), whose altered expression has been linked to CC progression. In this context, this systematic review aims to compile information on the clinical-pathological significance and describe the biological function of circRNAs. Inclusion and exclusion criteria were used to include relevant literature, followed by in silico analysis. Additionally, we employed the UALCAN tools to search for host genes of circRNAs and expression data, miRTargetLink 2.0 to predict interactions of microRNA target genes and the Cytoscape software to predict possible interactions of microRNA target genes. According to the research, most circRNAs were found to be overexpressed and described as regulators of processes such as invasion, cell proliferation, apoptosis and migration. They were also implicated in clinical significance, including metastasis, TNM staging and microRNA interactions. CircRNAs may participate in critical processes in tumorigenesis; therefore, understanding the underlying molecular mechanisms of gene regulation in CC can contribute to the accuracy of diagnosis, prognosis and therapy.
ABSTRACT
The selection of proper reference genes is critical for accurate gene expression analysis in all fields of biological and medical research, mainly because there are many distinctions between different tissues and specimens. Given this variability, even in known classic reference genes, demands of a comprehensive analysis platform is needed to identify the most suitable genes for each study. For this purpose, we present an analysis tool for assisting in decision-making in the analysis of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) data. EndoGeneAnalyzer, an open-source web tool for reference gene analysis in RT-qPCR studies, was used to compare the groups/conditions under investigation. This interactive application offers an easy-to-use interface that allows efficient exploration of datasets. Through statistical and stability analyses, EndoGeneAnalyzer assists in the select of the most appropriate reference gene or set of genes for each condition. It also allows researchers to identify and remove unwanted outliers. Moreover, EndoGeneAnalyzer provides a graphical interface to compare the evaluated groups, providing a visually informative differential analysis.
Subject(s)
Gene Expression Profiling , Real-Time Polymerase Chain Reaction , Reference Standards , Reverse Transcriptase Polymerase Chain ReactionABSTRACT
Gastric cancer (GC) is a highly prevalent and deadly malignant neoplasm worldwide. Currently, long non-coding RNAs (lncRNAs) have recently been identified as crucial regulators implicated in GC development and progression. Dysregulated expression of lncRNAs is commonly associated with enhanced tumor migration, invasiveness, and therapy resistance, highlighting their potential as promising targets for clinical applications. This review offers a comprehensive historical overview of lncRNAs in GC, describes the molecular mechanisms, and discusses the prospects and challenges of establishing lncRNAs as precision biomarkers.
ABSTRACT
Acute Lymphoblastic Leukemia (ALL) is a neoplasm of the hematopoietic system defined as a clonal expansion of an abnormal lymphoid precursor cell. It mostly affects children under five years of age and is the most common tumor to afflict pediatric patients. The expression of the human telomerase gene (hTERT) in patients with ALL has been studied as a biomarker and could become a new therapeutic target. We evaluate the role of hTERT gene expression in ALL pediatric patients, through quantitative real-time PCR technique, and the possible correlation between hTERT expression and clinical variables: gender, age, white blood cells (WBC), gene fusions, and immunophenotyping. The analysis between healthy controls and ALL patients (N = 244) was statistically significant (p < 0.001), demonstrating hTERT overexpression in these patients. In comparison with the usual set of clinical variables, the data were not statistically significant (p > 0.05), indicating that hTERT is equally overexpressed among patients regardless of gender, age, gene fusions, and immunophenotyping. Moreover, patients who presented a higher hTERT expression level had a significant (p < 0.0001) lower overall survival rate. In summary, hTERT expression emerges as an important molecular pathway in leukemogenesis regardless patient's clinical variables, thus, the data here presented pointed it as a valuable biomarker in pediatric acute lymphoblastic leukemia and a promising target for new therapeutic and prognostic measures.
