Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes

Llaneza Lago, Sergio, Fraser, William D. and Green, Darrell ORCID: https://orcid.org/0000-0002-0217-3322 (2024) Bayesian unsupervised clustering identifies clinically relevant osteosarcoma subtypes. Briefings in Bioinformatics. ISSN 1467-5463 (In Press)

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Abstract

Identification of cancer subtypes is a critical step for developing precision medicine. Most cancer subtyping is based on the analysis of RNA sequencing (RNA-seq) data from patient cohorts using unsupervised machine learning methods such as hierarchical cluster analysis but these computational approaches disregard the heterogeneous composition of individual cancer samples. Here, we used a more sophisticated unsupervised Bayesian model termed Latent Process Decomposition (LPD), which handles individual cancer sample heterogeneity and deconvolutes the structure of transcriptome data to provide clinically relevant information. The work was performed in the paediatric tumour osteosarcoma, which is a prototypical model for a rare and heterogeneous cancer. The LPD model detected three osteosarcoma subtypes. The subtype with the poorest prognosis was validated using independent patient datasets. This new stratification framework will be important for more accurate diagnostic labelling, expediting precision medicine and improving clinical trial success. Our results emphasise the importance of using more sophisticated machine learning approaches (and for teaching deep learning and artificial intelligence) for RNA-seq data analysis, which may assist drug targeting and clinical management.

Item Type:	Article
Uncontrolled Keywords:	sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups:	Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health Faculty of Medicine and Health Sciences > Research Groups > Musculoskeletal Medicine
Depositing User:	LivePure Connector
Date Deposited:	04 Dec 2024 01:42
Last Modified:	09 Dec 2024 01:39
URI:	https://ueaeprints.uea.ac.uk/id/eprint/97892
DOI:

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