scholarly journals Identification of Unique miRNA Biomarkers in Colorectal Adenoma and Carcinoma Using Microarray: Evaluation of Their Putative Role in Disease Progression

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Kothandaraman Narasimhan ◽  
Kalamegam Gauthaman ◽  
Peter Natesan Pushparaj ◽  
Govindasamy Meenakumari ◽  
Adeel Gulzar Ahmed Chaudhary ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Colorectal Adenoma ◽  
Microarray Data ◽  
Gene Networks ◽  
Inverse Relationship ◽  
Colorectal Adenocarcinoma ◽  
Colon Adenocarcinoma ◽  
Cancer Therapeutics ◽  
Data Sets ◽  
Lead Candidate

MicroRNAs (miRNAs) are known to be dysregulated and play a key role in cancer progression. The present study aims to identify the miRNAs associated with colorectal adenoma and carcinoma to evaluate their role in tumor progression and metastasis using microarray. In silico analysis of miRNAs was performed on five different microarray data sets that represented the genes and miRNAs expressed in colorectal adenoma and carcinoma. We identified 10 different miRNAs that were common to both colorectal adenoma and carcinoma, namely, miR9, miR96, miR135b, miR137, miR147, miR182, miR183, miR196b, miR224, and miR503. Of these, miR135b and miR147 were significantly downregulated in colorectal adenoma but upregulated in carcinoma. In addition, we studied the gene expression profile associated with colorectal adenocarcinoma and identified three genes, namely, ZBED3, SLC10A3, and FOXQ1, that were significantly downregulated in colorectal adenoma compared to carcinoma. Interestingly, of all the miRNAs and genes associated with colorectal adenocarcinoma, the myoglobin (MB) gene was identified to be under the direct influence of miR135b, showing an inverse relationship between them in adenoma and carcinoma. Most of the identified miRNAs and associated genes are involved in signaling pathways of cell proliferation, angiogenesis, and metastasis. The present study has identified putative miRNA targets and their associated gene networks which could be used as potential biomarkers of colon adenocarcinoma. Moreover, the association of miR135b and MB gene is very unique and can be considered as a lead candidate for novel cancer therapeutics.

Identification of Candidate Genetic Markers and a Novel 4-genes Diagnostic Model in Osteoarthritis through Integrating Multiple Microarray Data

2020 ◽  
Vol 23 (8) ◽  
pp. 805-813
Author(s):  
Ai Jiang ◽  
Peng Xu ◽  
Zhenda Zhao ◽  
Qizhao Tan ◽  
Shang Sun ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Microarray Data ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Functional Enrichment ◽  
Joint Disease ◽  
Support Vector ◽  
Diagnostic Model ◽  
Data Sets

Background: Osteoarthritis (OA) is a joint disease that leads to a high disability rate and a low quality of life. With the development of modern molecular biology techniques, some key genes and diagnostic markers have been reported. However, the etiology and pathogenesis of OA are still unknown. Objective: To develop a gene signature in OA. Method: In this study, five microarray data sets were integrated to conduct a comprehensive network and pathway analysis of the biological functions of OA related genes, which can provide valuable information and further explore the etiology and pathogenesis of OA. Results and Discussion: Differential expression analysis identified 180 genes with significantly expressed expression in OA. Functional enrichment analysis showed that the up-regulated genes were associated with rheumatoid arthritis (p < 0.01). Down-regulated genes regulate the biological processes of negative regulation of kinase activity and some signaling pathways such as MAPK signaling pathway (p < 0.001) and IL-17 signaling pathway (p < 0.001). In addition, the OA specific protein-protein interaction (PPI) network was constructed based on the differentially expressed genes. The analysis of network topological attributes showed that differentially upregulated VEGFA, MYC, ATF3 and JUN genes were hub genes of the network, which may influence the occurrence and development of OA through regulating cell cycle or apoptosis, and were potential biomarkers of OA. Finally, the support vector machine (SVM) method was used to establish the diagnosis model of OA, which not only had excellent predictive power in internal and external data sets (AUC > 0.9), but also had high predictive performance in different chip platforms (AUC > 0.9) and also had effective ability in blood samples (AUC > 0.8). Conclusion: The 4-genes diagnostic model may be of great help to the early diagnosis and prediction of OA.

scholarly journals Cell Fitness: More Than Push-Ups

2021 ◽  
Vol 22 (2) ◽  
pp. 518
Author(s):  
Adam James Ferrari ◽  
Ronny Drapkin ◽  
Rajan Gogna
Keyword(s):  
Cancer Progression ◽  
Hippo Pathway ◽  
Cancer Therapeutics ◽  
Protein Isoforms ◽  
Cell Junction ◽  
Cell Competition ◽  
Molecular Features ◽  
Oncogenic Pathways ◽  
Diagnostic Potential ◽  
The Impact

Cell competition (CC) is a feature that allows tumor cells to outcompete and eliminate adjacent cells that are deemed less fit. Studies of CC, first described in Drosophila melanogaster, reveal a diversity of underlying mechanisms. In this review, we will discuss three recent studies that expand our understanding of the molecular features governing CC. In particular, we will focus on a molecular fitness fingerprint, oncogenic pathways, and the importance of cell junction stability. A fitness fingerprint, mediated by flower (hFWE) protein isoforms, dictates that cells expressing the flower-win isoforms will outcompete adjacent flower-loss-expressing cells. The impact of the flower protein isoforms is seen in cancer progression and may have diagnostic potential. The yes-associated protein (YAP) and TAZ transcription factors, central mediators of the oncogenic Hippo pathway, elevate peritumoral fitness thereby protecting against tumor progression and provide a suppressive barrier. Similarly, COL17A1 is a key component in hemidesmosome stability, and its expression in epidermal stem cells contributes to fitness competition and aging characteristics. The contributions of these pathways to disease development and progression will help define how CC is hijacked to favor cancer growth. Understanding these features will also help frame the diagnostic and therapeutic possibilities that may place CC in the crosshairs of cancer therapeutics.

scholarly journals Anti-Cancer Effects of Zotarolimus Combined with 5-Fluorouracil Treatment in HCT-116 Colorectal Cancer-Bearing BALB/c Nude Mice

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4683
Author(s):  
Geng-Ruei Chang ◽  
Chan-Yen Kuo ◽  
Ming-Yang Tsai ◽  
Wei-Li Lin ◽  
Tzu-Chun Lin ◽  
...  
Keyword(s):  
Growth Factor ◽  
Tumor Growth ◽  
Nude Mice ◽  
Colorectal Adenocarcinoma ◽  
Transforming Growth Factor ◽  
Colon Adenocarcinoma ◽  
Future Research ◽  
Related Factors ◽  
Hct 116

Zotarolimus is a semi-synthetic derivative of rapamycin and an inhibitor of mammalian target of rapamycin (mTOR) signaling. Currently, zotarolimus is used to prolong the survival time of organ grafts, but it is also a novel immunosuppressive agent with potent anti-proliferative activity. Here, we examine the anti-tumor effect of zotarolimus, alone and in combination with 5-fluorouracil, on HCT-116 colorectal adenocarcinoma cells implanted in BALB/c nude mice. Compared with the control mice, mice treated with zotarolimus or zotarolimus combined with 5-FU showed retarded tumor growth; increased tumor apoptosis through the enhanced expression of cleaved caspase 3 and extracellular signal-regulated kinase (ERK) phosphorylation; reduced inflammation-related factors such as IL-1β, TNF-α, and cyclooxygenase-2 (COX-2) protein; and inhibited metastasis-related factors such as CD44, epidermal growth factor receptor (EGFR), transforming growth factor β (TGF-β), and vascular endothelial growth factor (VEGF). Notably, mice treated with a combination of zotarolimus and 5-FU showed significantly retarded tumor growth, reduced tumor size, and increased tumor inhibition compared with mice treated with 5-FU or zotarolimus alone, indicating a strong synergistic effect. This in vivo study confirms that zotarolimus or zotarolimus combined with 5-FU can be used to retard colorectal adenocarcinoma growth and inhibit tumorigenesis. Our results suggest that zotarolimus may increase the chemo-sensitization of tumor cells. Therefore, zotarolimus alone and zotarolimus combined with 5-FU may be potential anti-tumor agents in the treatment of human colon adenocarcinoma. Future research on zotarolimus may lead to the development of new therapeutic strategies.

scholarly journals Identification of Genes Expressed in Hyperpigmented Skin Using Meta-Analysis of Microarray Data Sets

2015 ◽  
Vol 135 (10) ◽  
pp. 2455-2463 ◽  
Author(s):  
Lanlan Yin ◽  
Sergio G. Coelho ◽  
Julio C. Valencia ◽  
Dominik Ebsen ◽  
Andre Mahns ◽  
...  
Keyword(s):  
Microarray Data ◽  
Meta Analysis ◽  
Data Sets

scholarly journals Network analysis identifies DAPK3 as a potential biomarker for lymphovascular invasion and prognosis of colon adenocarcinoma

2021 ◽  
Author(s):  
Huey-Miin Chen ◽  
Justin A. MacDonald
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Network Analysis ◽  
Gene Networks ◽  
Lymphovascular Invasion ◽  
Prognostic Significance ◽  
Colon Adenocarcinoma ◽  
Poor Overall Survival ◽  
Potential Biomarker ◽  
Mesenchymal Transformation

AbstractAdenocarcinoma of the colon is the fourth most common malignancy worldwide with significant rates of mortality. Hence, the identification of novel molecular biomarkers with prognostic significance is of particular importance for improvements in treatment and patient outcome. Clinical traits and RNA-Seq data of 551 patient samples and 18,205 genes in the UCSC Toil Recompute Compendium of TCGA TARGET and GTEx datasets (restricted to |Primary_site| = colon) were obtained from the Xena platform. Weighted gene co-expression network analysis was completed, and 24 unique modules were assembled to specifically examine the association between gene networks and cancer cell invasion. One module, containing 151 genes, was significantly correlated with lymphatic invasion, a histopathological feature of higher-risk colon cancer. Search tool for the retrieval of interacting genes/proteins (STRING) and gene ontology (GO) analyses identified the module to be enriched in genes related to cytoskeletal organization and apoptotic signaling, suggesting involvement in tumor cell survival and migration along with epithelial-mesenchymal transformation. Of genes that were differentially expressed and significant for overall survival, DAPK3 (death-associated protein kinase 3) was revealed as the pseudo-hub of the module. Although DAPK3 expression was reduced in colon cancer patients, survival analysis revealed that high expression of DAPK3 was significantly correlated with greater lymphovascular invasion and poor overall survival.

Biomedical Data Mining Using RBF Neural Networks

2011 ◽  
pp. 106-111
Author(s):  
Fang Chu ◽  
Lipo Wang
Keyword(s):  
Neural Networks ◽  
Microarray Data ◽  
High Accuracy ◽  
Accurate Diagnosis ◽  
Data Sets ◽  
Biomedical Data ◽  
Rbf Neural Networks ◽  
Proper Treatment ◽  
Pattern Recognition Problem ◽  
Very High

Accurate diagnosis of cancers is of great importance for doctors to choose a proper treatment. Furthermore, it also plays a key role in the searching for the pathology of cancers and drug discovery. Recently, this problem attracts great attention in the context of microarray technology. Here, we apply radial basis function (RBF) neural networks to this pattern recognition problem. Our experimental results in some well-known microarray data sets indicate that our method can obtain very high accuracy with a small number of genes.

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