Metastases are the main cause of death in advanced breast cancer (BC) patients. Although chemotherapy and hormone therapy are current treatment strategies, drug resistance is frequent and still not completely understood. In this study, a bioinformatics analysis was performed on BC patients to explore the molecular mechanisms associated with BC metastasis. Microarray gene expression profiles of metastatic and non metastatic BC patients were downloaded from Gene Expression Omnibus (GEO) dataset. Raw data were normalized and merged using the Combat tool. Pathways enriched with differently expressed genes were identified and a pathway co-expression network was generated using Pearson's correlation. We identified from this network, which includes 17 pathways and 128 interactions, the pathways that most influence the network efficiency. Moreover, protein interaction network was investigated to identify hub genes of the pathway network. The prognostic role of the network was evaluated with a survival analysis using an independent dataset. In conclusion, the pathway co-expression network could contribute to understanding the mechanism and development of BC metastases.

Perturbations of pathway co-expression network identify a core network in metastatic breast cancer / C. Cava, S. Pini, D. Taramelli, I. Castiglioni. - In: COMPUTATIONAL BIOLOGY AND CHEMISTRY. - ISSN 1476-9271. - 87(2020 Aug). [10.1016/j.compbiolchem.2020.107313]

Perturbations of pathway co-expression network identify a core network in metastatic breast cancer

Donatella Taramelli;
2020-08

Abstract

Metastases are the main cause of death in advanced breast cancer (BC) patients. Although chemotherapy and hormone therapy are current treatment strategies, drug resistance is frequent and still not completely understood. In this study, a bioinformatics analysis was performed on BC patients to explore the molecular mechanisms associated with BC metastasis. Microarray gene expression profiles of metastatic and non metastatic BC patients were downloaded from Gene Expression Omnibus (GEO) dataset. Raw data were normalized and merged using the Combat tool. Pathways enriched with differently expressed genes were identified and a pathway co-expression network was generated using Pearson's correlation. We identified from this network, which includes 17 pathways and 128 interactions, the pathways that most influence the network efficiency. Moreover, protein interaction network was investigated to identify hub genes of the pathway network. The prognostic role of the network was evaluated with a survival analysis using an independent dataset. In conclusion, the pathway co-expression network could contribute to understanding the mechanism and development of BC metastases.
Pathway co-expression; Breast cancer; Metastasis; Bioinformatics; Network;
Settore MED/04 - Patologia Generale
Settore MED/07 - Microbiologia e Microbiologia Clinica
Settore MED/46 - Scienze Tecniche di Medicina di Laboratorio
20-giu-2020
COMPUTATIONAL BIOLOGY AND CHEMISTRY
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/765344
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