scholarly journals An Introduction to the Mathematical Modeling in the Study of Cancer Systems Biology

2018 ◽  
Vol 17 ◽  
pp. 117693511879975 ◽  
Author(s):  
Abdallah K Alameddine ◽  
Frederick Conlin ◽  
Brian Binnall
Keyword(s):  
Mathematical Modeling ◽  
Systems Biology ◽  
Cancer Progression ◽  
Malignant Tumors ◽  
Deterministic System ◽  
Introductory Overview ◽  
Cancer Systems Biology ◽  
Heterogeneous Processes ◽  
Global Systems ◽  
Deficient Mismatch Repair

Background: Frequently occurring in cancer are the aberrant alterations of regulatory onco-metabolites, various oncogenes/epigenetic stochasticity, and suppressor genes, as well as the deficient mismatch repair mechanism, chronic inflammation, or those deviations belonging to the other cancer characteristics. How these aberrations that evolve overtime determine the global phenotype of malignant tumors remains to be completely understood. Dynamic analysis may have potential to reveal the mechanism of carcinogenesis and can offer new therapeutic intervention. Aims: We introduce simplified mathematical tools to model serial quantitative data of cancer biomarkers. We also highlight an introductory overview of mathematical tools and models as they apply from the viewpoint of known cancer features. Methods: Mathematical modeling of potentially actionable genomic products and how they proceed overtime during tumorigenesis are explored. This report is intended to be instinctive without being overly technical. Results: To date, many mathematical models of the common features of cancer have been developed. However, the dynamic of integrated heterogeneous processes and their cross talks related to carcinogenesis remains to be resolved. Conclusions: In cancer research, outlining mathematical modeling of experimentally obtained data snapshots of molecular species may provide insights into a better understanding of the multiple biochemical circuits. Recent discoveries have provided support for the existence of complex cancer progression in dynamics that span from a simple 1-dimensional deterministic system to a stochastic (ie, probabilistic) or to an oscillatory and multistable networks. Further research in mathematical modeling of cancer progression, based on the evolving molecular kinetics (time series), could inform a specific and a predictive behavior about the global systems biology of vulnerable tumor cells in their earlier stages of oncogenesis. On this footing, new preventive measures and anticancer therapy could then be constructed.

scholarly journals Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Gu ◽  
Ying Sun ◽  
Xiong Zheng ◽  
Jin Ma ◽  
Xiao-Ying Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Microarray Analysis ◽  
Cancer Progression ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Circular Rnas ◽  
Target Mrnas

Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar’s home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network.

Circular RNA hsa_circ_0078607 suppresses ovarian cancer progression by regulating miR-518a-5p/Fas signaling pathway

2020 ◽  
Author(s):  
Nan Zhang ◽  
Yue Jin ◽  
Qiubo Hu ◽  
Shanshan Cheng ◽  
Chao Wang ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Cells ◽  
Cancer Progression ◽  
Malignant Tumors ◽  
Circular Rna ◽  
Luciferase Reporter ◽  
Circular Rnas ◽  
Ovarian Cancer Cells ◽  
Cancer Pathogenesis ◽  
Direct Target

Abstract Background: Increasing researches have demonstrated the critical functions of circular RNAs (circRNAs) in the progression of malignant tumors, including ovarian cancer. In this study, we aim to investigate abnormally expression of hsa_circ_0078607 and the role of hsa_circ_0078607 during ovarian cancer pathogenesis.Methods: RT-PCR were used to detect the expression of circ_0078607 in ovarian cancer tissues. To determine the functional roles of circ_0078607 in ovarian cancer, cell proliferation and cell invasion assays were performed. Bioinformatics and luciferase reporter analysis were used to predict the target of circ_0078607.Results: In the present study, we first found that circ_0078607 was downregulated in ovarian cancer. Forced circ_0078607 expression significantly suppressed proliferation and promotes apoptosis of ovarian cancer cells. Mechanically, bioinformatics and luciferase reporter analysis identified that miR-518a-5p as a direct target of circ_0078607, while Fas as a direct target of miR-518a-5p. MiR-518a-5p negatively regulates Fas in ovarian cancer cells, while overexpression of circ_0078607 could increase the expression of Fas inhibited by miR-518a-5p. Furthermore, overexpression of circ_0078607 could inhibit the proliferation and invasion of ovarian cancer cells caused by miR-518a-5p mimic.Conclusion: The results of the present study revealed that circ_0078607 suppresses ovarian cancer progression by sponging oncogenic miR-518a-5p to induce Fas expression, which may provide new therapeutic approach for ovarian cancer.

scholarly journals The Role of Long Non-Coding RNA NNT-AS1 in Neoplastic Disease

Cancers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3086
Author(s):  
Cong Zhou ◽  
Shiwei Duan
Keyword(s):  
Cancer Progression ◽  
Cisplatin Resistance ◽  
Malignant Tumors ◽  
Human Cancer ◽  
Neoplastic Disease ◽  
Expression Levels ◽  
Cancer Breast ◽  
Non Coding Rna ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Studies have shown that non-coding RNAs (ncRNAs), especially long non-coding RNAs (lncRNAs), play an important regulatory role in the occurrence and development of human cancer. Nicotinamide nucleotide transhydrogenase-antisense 1 (NNT-AS1) is a newly-discovered cytoplasmic lncRNA. Many studies have shown that it has abnormally-high expression levels in malignant tumors, but there are also a few studies that have reported low expression levels of NNT-AS1 in gastric cancer, breast cancer, and ovarian cancer. At present, the regulatory mechanism of NNT-AS1 as a miRNA sponge, which may be an important reason affecting tumor cell proliferation, invasion, metastasis, and apoptosis is being studied in-depth. In addition, NNT-AS1 has been found to be related to cisplatin resistance. In this review, we summarize the abnormal expression of NNT-AS1 in a variety of neoplastic diseases and its diagnostic and prognostic value, and we explain the mechanism by which NNT-AS1 regulates cancer progression by competing with miRNAs. In addition, we also reveal the correlation between NNT-AS1 and cisplatin resistance and the potential clinical applications of NNT-AS1.

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