Deciphering Genomic Heterogeneity and the Internal Composition of Tumour Activities through a Hierarchical Factorisation Model

José Carbonell-Caballero, Antonio López-Quílez, David Conesa and Joaquín Dopazo
Additional contact information
José Carbonell-Caballero: Barcelona Supercomputing Center, Life Sciences Department, 08034 Barcelona, Spain
Antonio López-Quílez: Estadística e investigación Operativa, Universitat de València, 46100 Burjassot, Spain
David Conesa: Estadística e investigación Operativa, Universitat de València, 46100 Burjassot, Spain
Joaquín Dopazo: Clinical Bioinformatics Area, Fundación Progreso y Salud, Hospital Virgen del Rocio, 46100 Sevilla, Spain

Mathematics, 2021, vol. 9, issue 21, 1-24

Abstract: Genomic heterogeneity constitutes one of the most distinctive features of cancer diseases, limiting the efficacy and availability of medical treatments. Tumorigenesis emerges as a strongly stochastic process, producing a variable landscape of genomic configurations. In this context, matrix factorisation techniques represent a suitable approach for modelling such complex patterns of variability. In this work, we present a hierarchical factorisation model conceived from a systems biology point of view. The model integrates the topology of molecular pathways, allowing to simultaneously factorise genes and pathways activity matrices. The protocol was evaluated by using simulations, showing a high degree of accuracy. Furthermore, the analysis with a real cohort of breast cancer patients depicted the internal composition of some of the most relevant altered biological processes in the disease, describing gene and pathway level strategies and their observed combinations in the population of patients. We envision that this kind of approaches will be essential to better understand the hallmarks of cancer.

Keywords: bioinformatics; cancer; genomic heterogeneity; variability; matrix factorisation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/9/21/2833/pdf (application/pdf)
https://www.mdpi.com/2227-7390/9/21/2833/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:9:y:2021:i:21:p:2833-:d:674606

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().