Chromosomal copy number heterogeneity predicts survival rates across cancers

Erik van Dijk; Tom van den Bosch; Kristiaan J Lenos; Khalid El Makrini; Lisanne E Nijman; Hendrik F B van Essen; Nico Lansu; Michiel Boekhout; Joris H Hageman; Rebecca C Fitzgerald; Cornelis J A Punt; Jurriaan B Tuynman; Hugo J G Snippert; Geert J P L Kops; Jan Paul Medema; Bauke Ylstra; Louis Vermeulen; Daniël M Miedema

doi:10.1038/s41467-021-23384-6

Chromosomal copy number heterogeneity predicts survival rates across cancers

Erik van Dijk, Tom van den Bosch, Kristiaan J Lenos, Khalid El Makrini, Lisanne E Nijman, Hendrik F B van Essen, Nico Lansu, Michiel Boekhout, Joris H Hageman, Rebecca C Fitzgerald, Cornelis J A Punt, Jurriaan B Tuynman, Hugo J G Snippert, Geert J P L Kops, Jan Paul Medema, Bauke Ylstra, Louis Vermeulen, Daniël M Miedema

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Abstract

Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

Original language	English
Article number	3188
Pages (from-to)	1-12
Journal	Nature Communications
Volume	12
Issue number	1
DOIs	https://doi.org/10.1038/s41467-021-23384-6
Publication status	Published - Dec 2021

Keywords

Adolescent
Adult
Aged
Aged, 80 and over
Child
Computer Simulation
DNA Copy Number Variations
Datasets as Topic
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Genetic Heterogeneity
Genomics
Humans
Male
Middle Aged
Models, Genetic
Mutation
Neoplasms/genetics
Prognosis
Progression-Free Survival
Risk Assessment/methods
Survival Rate
Tumor Microenvironment/genetics
Young Adult

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10.1038/s41467-021-23384-6

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van Dijk, E., van den Bosch, T., Lenos, K. J., El Makrini, K., Nijman, L. E., van Essen, H. F. B., Lansu, N., Boekhout, M., Hageman, J. H., Fitzgerald, R. C., Punt, C. J. A., Tuynman, J. B., Snippert, H. J. G., Kops, G. J. P. L., Medema, J. P., Ylstra, B., Vermeulen, L., & Miedema, D. M. (2021). Chromosomal copy number heterogeneity predicts survival rates across cancers. Nature Communications, 12(1), 1-12. Article 3188. https://doi.org/10.1038/s41467-021-23384-6

@article{ff1f2efdfc9b449fa62388ac01f01a86,

title = "Chromosomal copy number heterogeneity predicts survival rates across cancers",

abstract = "Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.",

keywords = "Adolescent, Adult, Aged, Aged, 80 and over, Child, Computer Simulation, DNA Copy Number Variations, Datasets as Topic, Female, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genetic Heterogeneity, Genomics, Humans, Male, Middle Aged, Models, Genetic, Mutation, Neoplasms/genetics, Prognosis, Progression-Free Survival, Risk Assessment/methods, Survival Rate, Tumor Microenvironment/genetics, Young Adult",

author = "{van Dijk}, Erik and {van den Bosch}, Tom and Lenos, {Kristiaan J} and {El Makrini}, Khalid and Nijman, {Lisanne E} and {van Essen}, {Hendrik F B} and Nico Lansu and Michiel Boekhout and Hageman, {Joris H} and Fitzgerald, {Rebecca C} and Punt, {Cornelis J A} and Tuynman, {Jurriaan B} and Snippert, {Hugo J G} and Kops, {Geert J P L} and Medema, {Jan Paul} and Bauke Ylstra and Louis Vermeulen and Miedema, {Dani{\"e}l M}",

note = "Funding Information: This work was supported by Amsterdam UMC and Oncode, by CRUK and MRC for the development and characterization of organoids, by a KWF and an intramural grant of the Pathology department of Amsterdam UMC to B.Y., by a talent development grant of the AG&M institute of Amsterdam UMC and a Young Investigator Grant of KWF to D.M.M.; L.V. is a New York Stem Cell Foundation—Robertson Investigator. We thank The Cancer Genome Atlas, the International Cancer Genome Consortium, the TRA-CERx consortium and J. Brenton for providing data. Publisher Copyright: {\textcopyright} 2021, The Author(s).",

year = "2021",

month = dec,

doi = "10.1038/s41467-021-23384-6",

language = "English",

volume = "12",

pages = "1--12",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

number = "1",

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van Dijk, E, van den Bosch, T, Lenos, KJ, El Makrini, K, Nijman, LE, van Essen, HFB, Lansu, N, Boekhout, M , Hageman, JH, Fitzgerald, RC, Punt, CJA, Tuynman, JB, Snippert, HJG , Kops, GJPL, Medema, JP, Ylstra, B, Vermeulen, L & Miedema, DM 2021, 'Chromosomal copy number heterogeneity predicts survival rates across cancers', Nature Communications, vol. 12, no. 1, 3188, pp. 1-12. https://doi.org/10.1038/s41467-021-23384-6

TY - JOUR

T1 - Chromosomal copy number heterogeneity predicts survival rates across cancers

AU - van Dijk, Erik

AU - van den Bosch, Tom

AU - Lenos, Kristiaan J

AU - El Makrini, Khalid

AU - Nijman, Lisanne E

AU - van Essen, Hendrik F B

AU - Lansu, Nico

AU - Boekhout, Michiel

AU - Hageman, Joris H

AU - Fitzgerald, Rebecca C

AU - Punt, Cornelis J A

AU - Tuynman, Jurriaan B

AU - Snippert, Hugo J G

AU - Kops, Geert J P L

AU - Medema, Jan Paul

AU - Ylstra, Bauke

AU - Vermeulen, Louis

AU - Miedema, Daniël M

N1 - Funding Information: This work was supported by Amsterdam UMC and Oncode, by CRUK and MRC for the development and characterization of organoids, by a KWF and an intramural grant of the Pathology department of Amsterdam UMC to B.Y., by a talent development grant of the AG&M institute of Amsterdam UMC and a Young Investigator Grant of KWF to D.M.M.; L.V. is a New York Stem Cell Foundation—Robertson Investigator. We thank The Cancer Genome Atlas, the International Cancer Genome Consortium, the TRA-CERx consortium and J. Brenton for providing data. Publisher Copyright: © 2021, The Author(s).

PY - 2021/12

Y1 - 2021/12

N2 - Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

AB - Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

KW - Adolescent

KW - Adult

KW - Aged

KW - Aged, 80 and over

KW - Child

KW - Computer Simulation

KW - DNA Copy Number Variations

KW - Datasets as Topic

KW - Female

KW - Gene Expression Profiling

KW - Gene Expression Regulation, Neoplastic

KW - Genetic Heterogeneity

KW - Genomics

KW - Humans

KW - Male

KW - Middle Aged

KW - Models, Genetic

KW - Mutation

KW - Neoplasms/genetics

KW - Prognosis

KW - Progression-Free Survival

KW - Risk Assessment/methods

KW - Survival Rate

KW - Tumor Microenvironment/genetics

KW - Young Adult

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U2 - 10.1038/s41467-021-23384-6

DO - 10.1038/s41467-021-23384-6

M3 - Article

C2 - 34045449

SN - 2041-1723

VL - 12

SP - 1

EP - 12

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 3188

ER -

Chromosomal copy number heterogeneity predicts survival rates across cancers

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