RESUMO
Pancreatic cancer is the seventh most lethal cancer in the world. Despite its moderate prevalence, the 5-year survival rate of patients with pancreatic cancer is about 10%. Despite different therapeutic and diagnostic strategies for pancreatic cancer, this cancer is still uncontrollable in the invasive stage and can invade various body organs and cause death. Early detection for pancreatic cancer can be an excellent solution to manage treatment better and increase patients' survival rates. This study aimed to find diagnostic biomarkers between non-invasive to invasive stages of pancreatic cancer in the extracellular matrix to facilitate the early diagnosis of this cancer. Using bioinformatics analysis, we selected the appropriate datasets between non-invasive and invasive pancreatic cancer stages and categorized their genes. Then, we charted and confirmed the signaling pathways, gene ontology, protein relationships, and protein expression levels in the human samples using bioinformatics databases. Cell adhesion and hypoxia signaling pathways were observed in up-regulated genes, different phases of the cell cycle, and metabolic signaling pathways with down-regulated genes between non-invasive and invasive pancreatic cancer stages. For proper diagnostic biomarkers selection, the overexpressed genes that released protein into the extracellular matrix were examined in more detail, with 62 proteins selected and SPARC, THBS2, COL11A1, COL1A1, COL1A2, COL3A1, SERPINH1, PLAU proteins chosen. Bioinformatics analysis can more accurately assess the relationship between molecular mechanisms and key actors in pancreatic cancer invasion and metastasis to facilitate early detection and improve treatment management for patients with pancreatic cancer.
Assuntos
Perfilação da Expressão Gênica , Neoplasias Pancreáticas , Humanos , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/análise , Biomarcadores Tumorais/metabolismo , Neoplasias Pancreáticas/diagnóstico , Neoplasias Pancreáticas/genética , Transdução de Sinais/genética , Neoplasias PancreáticasRESUMO
The hedgehog (Hh) signaling pathway is an evolutionarily conserved pathway that regulates embryonic development in vertebrates. However, strong evidence suggests the role of its dysregulation in human diseases, especially cancers. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), belong to a group of human transcriptomes that do not translate into proteins. However, they can highly influence protein expression. This review will provide a comprehensive link between ncRNAs and Hh signaling pathways in different human diseases and development, providing insights into disease and cancer progression as well as emphasizing their therapeutic, prognostic, and diagnostic significance.
Assuntos
MicroRNAs , Neoplasias , RNA Longo não Codificante , Animais , Proteínas Hedgehog/genética , Humanos , MicroRNAs/genética , MicroRNAs/metabolismo , Neoplasias/genética , RNA Circular/genética , RNA Longo não Codificante/metabolismo , RNA não Traduzido/genética , RNA não Traduzido/metabolismo , Transdução de SinaisRESUMO
OBJECTIVE: Rubella is a highly contagious viral disease with a significant teratogenic effect. Various results have been published about the seroprevalence of rubella in Iran. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-systematic review and meta-analysis were conducted to assess the immunity against rubella in Iranian women. METHODS: Eleven English and Persian electronic databases including PubMed, ScienceDirect, Scopus, Web of Science, Google Scholar, Embase, Scientific Information Database, Iran doc, Iran Medex, Magiran, and Medlib were searched using the keywords: Epidemiology, Prevalence, Rubella, Women, Childbearing age, Reproductive age, and Iran. A mathematician (NS) reviewed all steps for accuracy. RESULTS: Out of 1,520 articles, 25 well-conducted studies with a total amount of 10,145 women were reviewed. The pooled prevalence rate of anti-rubella IgG was 84% (95% CI: 83%-86%). The highest prevalence rate of IgG was in Zahedan, Rasht, and Arak (each 100%), while the lowest prevalence was in Jahrom (54%). Subgroup analysis showed that from 1989 through 2012, the IgG prevalence rate increased from 78% (95% CI: 73-83%) to 99% (95% CI: 98 100%). CONCLUSIONS: Although the vaccination program seems working in Iran, some peripheral regions may be a target to improve health care policies.