Background/aim: Esophageal cancer (EC) is the eighth most common cancer with a highly aggressive potency. Considering the poor survival of esophageal carcinoma there is a need for useful molecular biomarkers for prevention and early detection. Our aim was to determine the significance of altered microRNA (miRNA) expression in esophageal cancer, in relation to lifestyle, social and environmental factors.
Materials And Methods: The relative expression levels of the following miRNAs: miR-21, miR-143, miR-196a, miR-203, miR-205 and miR-221 were monitored in control and esophageal squamous-cell carcinoma (ESCC) samples using real-time polymerase chain reaction (RT-PCR). miRNA expression pattern of tumor tissues were evaluated according to patients' social status, living condition, smoking and drinking habits alone and in combinations.
Results: miR-21, miR-143, miR-203, miR-205 and miR-221 were over-expressed in esophageal cancer compared with normal tissues. Increased expression of miR-205 was related to smoking, while excessive alcohol consumption showed a correlation with under-expression of miR-143, miR-203 and miR-205 in tumor samples. Significant associations were detected between reduced expression of miR-143, miR-203 and low social status, and combination of smoking and heavy drinking.
Conclusion: Alterations of miRNA expression in ESCC can be correlated with the presence of common risk factors. The altered expression of certain miRNAs could be used as novel molecular markers of esophageal carcinoma.
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Microrna
January 2025
Amity Institute of Biotechnology, Amity University Uttar Pradesh, Noida, 20130, India.
MicroRNA (miRNA) modulation has emerged as a promising strategy in cancer immunotherapy, particularly in converting "cold" tumors with limited immune cell infiltration into "hot" tumors responsive to immunotherapy. miRNAs regulate immune cell recruitment and activation within the tumor microenvironment, influencing tumor behavior targeting specific miRNAs in cold tumors aims to enhance the immune response, potentially improving therapeutic efficacy. Despite ongoing research challenges, such as tumor complexity and treatment resistance, miRNA-based therapies offer personalized approaches with potential ethical considerations.
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Department of Immunology, Immunology Research Center, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Background: Since there is currently no cure for amyotrophic lateral sclerosis (ALS), it is essential to search for diagnostic biomarkers and novel treatments to reduce the severity of this disease. One of these treatment approaches is stem cell transplantation.
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BMC Endocr Disord
January 2025
Gastroenterology and Hepatology Research Center, Institute of Basic and Clinical Physiology Sciences, of Clinical Biochemistry, Kerman University of Medical Sciences, Jahad Boulevard Avicenna Avenue, Kerman, 7619813159, Iran.
Obesity and atherosclerosis are significant metabolic diseases characterized by disrupted lipid metabolism. MicroRNAs (miRNAs) are small, conserved, non-coding RNA sequences consisting of approximately 22 nucleotides, playing crucial roles in biological and pathological functions. Among these, miR-33a/b is particularly associated with metabolic diseases, notably obesity and atherosclerosis.
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Clinical Research Center, Jiading District Central Hospital Affiliated to Shanghai University of Medicine and Health Sciences, Shanghai, 201800, China.
Background: Circular (circ)RNAs have emerged as crucial contributors to cancer progression. Nonetheless, the expression regulation, biological functions, and underlying mechanisms of circRNAs in mediating hepatocellular carcinoma (HCC) progression remain insufficiently elucidated.
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Sci Rep
January 2025
Department of Traditional Chinese Medicine, People's Hospital of Guangxi Zhuang Autonomous Region, 6 Taoyuan Road, Qingxiu District, Nanning City, Guangxi Zhuang Autonomous Region, People's Republic of China.
Stomach adenocarcinoma (STAD) is a common malignancy with high heterogeneity and a lack of highly precise treatment options. We downloaded the multiomics data of STAD patients in The Cancer Genome Atlas (TCGA)-STAD cohort, which included mRNA, microRNA, long non-coding RNA, somatic mutation, and DNA methylation data, from the sxdyc website. We synthesized the multiomics data of patients with STAD using 10 clustering methods, construct a consensus machine learning-driven signature (CMLS)-related prognostic models by combining 10 machine learning methods, and evaluated the prognosis models using the C-index.
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