Universität zu Köln

Mora, Ariane, Schmidt, Christina ORCID: 0000-0002-3867-0881, Balderson, Brad, Frezza, Christian ORCID: 0000-0002-3293-7397 and Bodén, Mikael (2024). SiRCle (Signature Regulatory Clustering) model integration reveals mechanisms of phenotype regulation in renal cancer. Genome Medicine, 16 (1). pp. 1-26. Springer Nature. ISSN 1756-994X

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Abstract

[Artikel-Nr. 144] Background: Clear cell renal cell carcinoma (ccRCC) tumours develop and progress via complex remodelling of the kidney epigenome, transcriptome, proteome and metabolome. Given the subsequent tumour and inter-patient heterogeneity, drug-based treatments report limited success, calling for multi-omics studies to extract regulatory relationships, and ultimately, to develop targeted therapies. Yet, methods for multi-omics integration to reveal mechanisms of phenotype regulation are lacking. Methods: Here, we present SiRCle (Signature Regulatory Clustering), a method to integrate DNA methylation, RNA-seq and proteomics data at the gene level by following central dogma of biology, i.e. genetic information proceeds from DNA, to RNA, to protein. To identify regulatory clusters across the different omics layers, we group genes based on the layer where the gene’s dysregulation first occurred. We combine the SiRCle clusters with a variational autoencoder (VAE) to reveal key features from omics’ data for each SiRCle cluster and compare patient subpopulations in a ccRCC and a PanCan cohort. Results: Applying SiRCle to a ccRCC cohort, we showed that glycolysis is upregulated by DNA hypomethylation, whilst mitochondrial enzymes and respiratory chain complexes are translationally suppressed. Additionally, we identify metabolic enzymes associated with survival along with the possible molecular driver behind the gene’s perturbations. By using the VAE to integrate omics’ data followed by statistical comparisons between tumour stages on the integrated space, we found a stage-dependent downregulation of proximal renal tubule genes, hinting at a loss of cellular identity in cancer cells. We also identified the regulatory layers responsible for their suppression. Lastly, we applied SiRCle to a PanCan cohort and found common signatures across ccRCC and PanCan in addition to the regulatory layer that defines tissue identity. Conclusions: Our results highlight SiRCle’s ability to reveal mechanisms of phenotype regulation in cancer, both specifically in ccRCC and broadly in a PanCan context. SiRCle ranks genes according to biological features.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code Mora, Ariane UNSPECIFIED UNSPECIFIED UNSPECIFIED Schmidt, Christina UNSPECIFIED https://orcid.org/0000-0002-3867-0881 UNSPECIFIED Balderson, Brad UNSPECIFIED UNSPECIFIED UNSPECIFIED Frezza, Christian UNSPECIFIED https://orcid.org/0000-0002-3293-7397 UNSPECIFIED Bodén, Mikael UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-814874
Identification Number:	10.1186/s13073-024-01415-3
Journal or Publication Title:	Genome Medicine
Volume:	16
Number:	1
Page Range:	pp. 1-26
Number of Pages:	26
Date:	4 December 2024
Publisher:	Springer Nature
ISSN:	1756-994X
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences Faculty of Medicine
Divisions:	CECAD - Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases Faculty of Mathematics and Natural Sciences > Department of Biology > Institute for Genetics
Subjects:	Life sciences Medical sciences Medicine
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/81487