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Protein-Protein Interaction Network could reveal the relationship between the breast and colon cancer

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TLDR
It seems that breast cancer in females interferes with the rate of colorectal cancer incidence, and there may be a common molecular origin for these malignancies occurrences.
Abstract
AIM: This study is aimed to elicit the possible correlation between breast and colon cancer from molecular prospective by analyzing and comparing pathway-based biomarkers. BACKGROUND: Breast and colon cancer are known to be frequent causes of morbidity and mortality in men and women around the world. There is some evidence that while the incident of breast cancer in young women is high, it is reported lower in the aged women. In fact, aged women are more prone to colorectal cancer than older men. . In addition, many studies showed that several biomarkers are common among these malignancies. PATIENTS AND METHODS: The genes were retrieved and compared from KEGG database and WikiPathway, and subsequently, protein-protein interaction (PPI) network was constructed and analyzed using Cytoscape v:3.2.1 software and related algorithms. RESULTS: More than forty common genes were identified among these malignancies; however, by pathways comparison, twenty genes are related to both breast and colon cancer. Centrality and cluster screening identified hub genes, including SMAD2, SMAD3, (SMAD4, MYC), JUN, BAD, TP53. These seven genes are enriched in regulation of transforming growth factor beta receptor signaling pathway, positive regulation of Rac protein signal transduction, positive regulation of mitochondrial outer membrane permeabilization involved in apoptotic signaling pathway, and positive regulation of mitotic metaphase/anaphase transition respectively. CONCLUSION: As there are numerous genes frequent between colorectal cancer and breast cancer, there may be a common molecular origin for these malignancies occurrences. It seems that breast cancer in females interferes with the rate of colorectal cancer incidence.

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Metabolomic analysis of human cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease and non-alcoholic steatohepatitis diseases.

TL;DR: In this review, it has been collected a heterogeneous set of metabolomics published studies to discovery of biomarkers in researches to introduce diagnostic biomarkers for early detection and the choice of patient-specific therapies.
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Protein-protein interaction network analysis of cirrhosis liver disease

TL;DR: The result indicates that regulation of lipid metabolism and cell survival are important biological processes involved in cirrhosis disease.
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Protein-protein interaction analysis of Alzheimer`s disease and NAFLD based on systems biology methods unhide common ancestor pathways.

TL;DR: Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases and finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.
Journal ArticleDOI

Protein-Protein Interaction Network Analysis for a Biomarker Panel Related to Human Esophageal Adenocarcinoma

TL;DR: The findings indicate nine crucial proteins could form a candidate biomarker panel for EAC, and main related terms to closely correspond with those for colorectal cancer.
Journal ArticleDOI

Evaluation of liver cirrhosis and hepatocellular carcinoma using Protein-Protein Interaction Networks.

TL;DR: There is a common molecular relationship between cirrhosis and hepatocellular cancer that may help with identification of target molecules for early treatment that is essential in cancer therapy, according to analysis of serum proteome profile of cirrhotic patients or HCC patients versus healthy controls.
References
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Journal ArticleDOI

Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Journal ArticleDOI

ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

TL;DR: ClueGO is an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes and creates a functionally organized GO/pathway term network.
Journal ArticleDOI

An automated method for finding molecular complexes in large protein interaction networks.

TL;DR: A novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes is described.
Journal ArticleDOI

The p53 tumour suppressor gene

TL;DR: The cell cycle is composed of a series of steps which can be negatively or postively regulated by various factors, chief among the negative regulators is the p53 protein, which can lead to cancer.
PatentDOI

Genomic landscapes of human breast and colorectal cancers

TL;DR: Based on analysis of exons representing 20,857 transcripts from 18,191 genes, the authors concluded that the genomic landscapes of breast and colorectal cancers are composed of a handful of commonly mutated gene "mountains" and a much larger number of gene "hills" that are mutated at low frequency.
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