Background: Gastric cancer (GC) is known for its lymph node metastasis and outstanding morbidity and mortality. Thus, improvement in the current knowledge regarding the molecular mechanism of GC is urgently needed to discover novel biomarkers involved in its progression and prognosis. Several long, non-coding RNAs (lncRNAs) play important roles in gastric tumorigenesis and metastasis. However, the signature of lncRNA-associated metastasis in GC is not fully clarified.
Methods: We determined the lncRNA and mRNA expression profiles correlating to GC with or without lymph node-metastasis based on microarray analysis. Twelve differentially expressed lncRNAs and six differentially expressed mRNAs were validated by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay.
Results: The relationships between the aberrantly expressed lncRNAs XLOC_010235 or RP11-789C1.1 and lymph node metastasis, pathologic metastasis status, distal metastasis and TNM (tumour, node, and metastasis) stage were found to be significantly different. Via survival analysis, patients who had high-expressed XLOC_010235 or low-expressed RP11-789C1.1 showed significantly worse survival than patients with inverse-expressed XLOC_010235 or RP11-789C1.1.
Conclusion: In summary, this current study highlights some evidence regarding the potential role of lncRNAs in GC and posits that specific lncRNAs can be identified as novel, poor prognostic biomarkers in GC.
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http://dx.doi.org/10.1007/s00535-015-1091-y | DOI Listing |
Adv Clin Exp Med
January 2025
Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, USA.
Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Due to the lack of symptoms until advanced stages, early diagnosis of ccRCC is challenging. Therefore, the identification of novel secreted biomarkers for the early detection of ccRCC is urgently needed.
View Article and Find Full Text PDFAlzheimers Dement
January 2025
UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK.
Introduction: Cerebrovascular dysfunction plays a critical role in the pathogenesis of dementia and related neurodegenerative disorders. Recent omics-driven research has revealed associations between vascular abnormalities and transcriptomic alterations in brain vascular cells, particularly endothelial cells (ECs) and pericytes (PCs). However, the impact of these molecular changes on dementia remains unclear.
View Article and Find Full Text PDFPlant Genome
March 2025
Department of Fundamental Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
The plant Polygonum capitatum (P. capitatum) contains a variety of flavonoids that are distributed differently among different parts. Nevertheless, differentially expressed genes (DEGs) associated with this heterogeneous distribution have not been identified.
View Article and Find Full Text PDFClin Cosmet Investig Dermatol
January 2025
Department of Clinical Laboratory, Central Hospital of Dalian University of Technology, Dalian, 116033, People's Republic of China.
Objective: Juvenile dermatomyositis (JDM) is a complex autoimmune disease, and its pathogenesis remains poorly understood. Building upon previous research on the immunological and inflammatory aspects of JDM, this study aims to investigate the role of pyroptosis in the pathogenesis of JDM using a comprehensive bioinformatics approach.
Methods: Two microarray datasets (GSE3307 and GSE11971) were obtained from the Gene Expression Omnibus database, and a list of 62 pyroptosis-related genes was compiled.
Biochem Biophys Rep
March 2025
Department of Genetics and Molecular Biology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Introduction: Gastric cancer (GC) is among the deadliest malignancies globally, characterized by hypoxia-driven pathways that promote cancer progression, including stemness mechanisms facilitating invasion and metastasis. This study aimed to develop a prognostic decision tree using genes implicated in hypoxia and stemness pathways to predict outcomes in GC patients.
Materials And Methods: GC RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to compute hypoxia and stemness scores using Gene Set Variation Analysis (GSVA) and the mRNA expression-based stemness index (mRNAsi).
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