CIBRA identifies genomic alterations with a system-wide impact on tumor biology

Soufyan Lakbir; Caterina Buranelli; Gerrit A. Meijer; Jaap Heringa; Remond J.A. Fijneman; Sanne Abeln

doi:10.1093/bioinformatics/btae384

CIBRA identifies genomic alterations with a system-wide impact on tumor biology

Soufyan Lakbir, Caterina Buranelli, Gerrit A. Meijer, Jaap Heringa, Remond J.A. Fijneman^*, Sanne Abeln^*

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Motivation: Genomic instability is a hallmark of cancer, leading to many somatic alterations. Identifying which alterations have a system-wide impact is a challenging task. Nevertheless, this is an essential first step for prioritizing potential biomarkers. We developed CIBRA (Computational Identification of Biologically Relevant Alterations), a method that determines the system-wide impact of genomic alterations on tumor biology by integrating two distinct omics data types: one indicating genomic alterations (e.g. genomics), and another defining a system-wide expression response (e.g. transcriptomics). CIBRA was evaluated with genome-wide screens in 33 cancer types using primary and metastatic cancer data from the Cancer Genome Atlas and Hartwig Medical Foundation. Results: We demonstrate the capability of CIBRA by successfully confirming the impact of point mutations in experimentally validated oncogenes and tumor suppressor genes (0.79 AUC). Surprisingly, many genes affected by structural variants were identified to have a strong system-wide impact (30.3%), suggesting that their role in cancer development has thus far been largely under-reported. Additionally, CIBRA can identify impact with only 10 cases and controls, providing a novel way to prioritize genomic alterations with a prominent role in cancer biology. Our findings demonstrate that CIBRA can identify cancer drivers by combining genomics and transcriptomics data. Moreover, our work shows an unexpected substantial system-wide impact of structural variants in cancer. Hence, CIBRA has the potential to preselect and refine current definitions of genomic alterations to derive more nuanced biomarkers for diagnostics, disease progression, and treatment response. Availability and implementation: The R package CIBRA is available at https://github.com/AIT4LIFE-UU/CIBRA.

Original language	English
Pages (from-to)	ii37-ii44
Number of pages	8
Journal	Bioinformatics
Volume	40
Issue number	Supplement_2
Early online date	4 Sept 2024
DOIs	https://doi.org/10.1093/bioinformatics/btae384
Publication status	Published - Sept 2024

Bibliographical note

Volume 40, Issue Supplement_2: Proceedings of ECCB2024.

Publisher Copyright:
© The Author(s) 2024. Published by Oxford University Press.

Funding

This publication and the underlying study have been made possible partly through data requested (DR-072) and made available by the Hartwig Medical Foundation (HMF) and the Center of Personalized Cancer Treatment (CPCT). The results shown here are in part based on data generated by the TCGA Research Network (https://www.cancer.gov/tcga). We thank Libio Goncalves Braz from the department of Information and Computing Sciences at Utrecht University for testing the usability of the package on multiple systems. This work was supported by PPP Allowance [LSHM19027 and LSHM21018] made available by Health~Holland, Top Sector Life Sciences & Health, to stimulate public\u2013private partnerships. This paper was published as part of a supplement financially supported by ECCB2024. R.J.A.F. reports grants and non-financial support from PersonalGenome Diagnostics, non-financial support from Delfi Diagnostics,grants from MERCK BV, grants and non-financial support fromCergentis BV, outside the submitted work; In addition, R.J.A.F.has several patents pending. S.A. reports grants and non-financialsupport from Cergentis BV, Olink, Quanterix, and a patent pending,outside the submitted work. S.L. reports non-financial supportfrom Cergentis BV and a patent pending, outside the submittedwork. J.H. reports a patent pending, outside the submitted work.G.A.M. is co-founder and board member (CSO) of CRCbioscreenBV, CSO of Health-RI (Dutch National Health Data Infrastructurefor Research & innovation), and member of the supervisory boardof IKNL (Netherlands Comprehensive Cancer Organisation). G.A.M.non-financial support from Exact Sciences, non-financial support fromSysmex, non-financial support from Sentinel CH. SpA, non-financialsupport from Personal Genome Diagnostics (PGDX), non-financialsupport from DELFI, other from Hartwig Medical Foundation, grantsfrom CZ (OWM Centrale Zorgverzekeraars groep Zorgverzekeraaru.a), other from Royal Philips, other from GlaxoSmithKline, otherfrom Keosys SARL, other from Open Clinica LLC, other from RocheDiagnostics Nederland BV, other from The Hyve BV, other from OpenText, other from SURFSara BV, other from Vancis BV, other fromCSC Computer Sciences BV, outside the submitted work; In addition,G.A.M. has several patents pending. The other authors declare nopotential conflicts of interest. This work was supported by PPP Allowance [LSHM19027 and LSHM21018] made available by Health\u223CHolland, Top Sector Life Sciences & Health, to stimulate public\u2013private partnerships. This paper was published as part of a supplement financially supported by ECCB2024.

Funders	Funder number
Hartwig Medical Foundation
MERCK BV
PersonalGenome
Center of Personalized Cancer Treatment
department of Information and Computing Sciences at Utrecht University	LSHM21018, LSHM19027
Health~Holland, Top Sector Life Sciences & Health	ECCB2024

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title = "CIBRA identifies genomic alterations with a system-wide impact on tumor biology",

abstract = "Motivation: Genomic instability is a hallmark of cancer, leading to many somatic alterations. Identifying which alterations have a system-wide impact is a challenging task. Nevertheless, this is an essential first step for prioritizing potential biomarkers. We developed CIBRA (Computational Identification of Biologically Relevant Alterations), a method that determines the system-wide impact of genomic alterations on tumor biology by integrating two distinct omics data types: one indicating genomic alterations (e.g. genomics), and another defining a system-wide expression response (e.g. transcriptomics). CIBRA was evaluated with genome-wide screens in 33 cancer types using primary and metastatic cancer data from the Cancer Genome Atlas and Hartwig Medical Foundation. Results: We demonstrate the capability of CIBRA by successfully confirming the impact of point mutations in experimentally validated oncogenes and tumor suppressor genes (0.79 AUC). Surprisingly, many genes affected by structural variants were identified to have a strong system-wide impact (30.3%), suggesting that their role in cancer development has thus far been largely under-reported. Additionally, CIBRA can identify impact with only 10 cases and controls, providing a novel way to prioritize genomic alterations with a prominent role in cancer biology. Our findings demonstrate that CIBRA can identify cancer drivers by combining genomics and transcriptomics data. Moreover, our work shows an unexpected substantial system-wide impact of structural variants in cancer. Hence, CIBRA has the potential to preselect and refine current definitions of genomic alterations to derive more nuanced biomarkers for diagnostics, disease progression, and treatment response. Availability and implementation: The R package CIBRA is available at https://github.com/AIT4LIFE-UU/CIBRA.",

author = "Soufyan Lakbir and Caterina Buranelli and Meijer, {Gerrit A.} and Jaap Heringa and Fijneman, {Remond J.A.} and Sanne Abeln",

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AU - Buranelli, Caterina

AU - Meijer, Gerrit A.

AU - Heringa, Jaap

AU - Fijneman, Remond J.A.

AU - Abeln, Sanne

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CIBRA identifies genomic alterations with a system-wide impact on tumor biology

Abstract

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