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Integration of genome-level data to allow identification of subtype-specific vulnerability genes as novel therapeutic targets.

Schwalbe, Edward C, H, Lalchungnunga, Lafta, Fadhel, Barrow, Timothy and Strathdee, Gordon (2021) Integration of genome-level data to allow identification of subtype-specific vulnerability genes as novel therapeutic targets. Oncogene. ISSN 1476-5594

Item Type: Article

Abstract

The identification of cancer-specific vulnerability genes is one of the most promising approaches for developing more effective and less toxic cancer treatments. Cancer genomes exhibit thousands of changes in DNA methylation and gene expression, with the vast majority likely to be passenger changes. We hypothesised that, through integration of genome-wide DNA methylation/expression data, we could exploit this inherent variability to identify cancer subtype-specific vulnerability genes that would represent novel therapeutic targets that could allow cancer-specific cell killing. We developed a bioinformatics pipeline integrating genome-wide DNA methylation/gene expression data to identify candidate subtype-specific vulnerability partner genes for the genetic drivers of individual genetic/molecular subtypes. Using acute lymphoblastic leukaemia as an initial model, 21 candidate subtype-specific vulnerability genes were identified across the five common genetic subtypes, with at least one per subtype. To confirm the approach was applicable across cancer types, we also assessed medulloblastoma, identifying 15 candidate subtype-specific vulnerability genes across three of four established subtypes. Almost all identified genes had not previously been implicated in these diseases. Functional analysis of seven candidate subtype-specific vulnerability genes across the two tumour types confirmed that siRNA-mediated knockdown induced significant inhibition of proliferation/induction of apoptosis, which was specific to the cancer subtype in which the gene was predicted to be specifically lethal. Thus, we present a novel approach that integrates genome-wide DNA methylation/expression data to identify cancer subtype-specific vulnerability genes as novel therapeutic targets. We demonstrate this approach is applicable to multiple cancer types and identifies true functional subtype-specific vulnerability genes with high efficiency.

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Additional Information: ** From PubMed via Jisc Publications Router ** History: received 08-03-2020; revised 16-06-2021; accepted 22-06-2021.
SWORD Depositor: Publication Router
Depositing User: Publication Router

Identifiers

Item ID: 13736
Identification Number: https://doi.org/10.1038/s41388-021-01923-1
ISSN: 1476-5594
URI: http://sure.sunderland.ac.uk/id/eprint/13736
Official URL: https://www.nature.com/articles/s41388-021-01923-1

Users with ORCIDS

ORCID for Edward C Schwalbe: ORCID iD orcid.org/0000-0002-1190-9469
ORCID for Lalchungnunga H: ORCID iD orcid.org/0000-0003-2718-6223
ORCID for Timothy Barrow: ORCID iD orcid.org/0000-0003-4551-3857
ORCID for Gordon Strathdee: ORCID iD orcid.org/0000-0001-9681-8429

Catalogue record

Date Deposited: 11 Aug 2021 10:10
Last Modified: 11 Aug 2021 10:15

Contributors

Author: Edward C Schwalbe ORCID iD
Author: Lalchungnunga H ORCID iD
Author: Timothy Barrow ORCID iD
Author: Gordon Strathdee ORCID iD
Author: Fadhel Lafta

University Divisions

Faculty of Health Sciences and Wellbeing > School of Nursing and Health Sciences

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