Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis

Norbert Moldovan; Ymke van der Pol; Tom van den Ende; Dries Boers; Sandra Verkuijlen; Aafke Creemers; Jip Ramaker; Trang Vu; Sanne Bootsma; Kristiaan J. Lenos; Louis Vermeulen; Marieke F. Fransen; Michiel Pegtel; Idris Bahce; Hanneke van Laarhoven; Florent Mouliere

doi:https://doi.org/10.1016/j.xcrm.2023.101349

Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis

Norbert Moldovan, Ymke van der Pol, Tom van den Ende, Dries Boers, Sandra Verkuijlen, Aafke Creemers, Jip Ramaker, Trang Vu, Sanne Bootsma, Kristiaan J. Lenos, Louis Vermeulen, Marieke F. Fransen, Michiel Pegtel, Idris Bahce, Hanneke van Laarhoven, Florent Mouliere

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

Abstract

The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

Original language	English
Article number	101349
Journal	Cell Reports Medicine
Volume	5
Issue number	1
Early online date	2023
DOIs	https://doi.org/10.1016/j.xcrm.2023.101349
Publication status	Published - 16 Jan 2024

Keywords

cancer
cell-free DNA
fragmentomics
liquid biopsy
multi-modal
sequencing

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https://doi.org/10.1016/j.xcrm.2023.101349

Cite this

Moldovan, N., van der Pol, Y., van den Ende, T., Boers, D., Verkuijlen, S., Creemers, A., Ramaker, J., Vu, T., Bootsma, S., Lenos, K. J., Vermeulen, L., Fransen, M. F., Pegtel, M., Bahce, I., van Laarhoven, H., & Mouliere, F. (2024). Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis. Cell Reports Medicine, 5(1), Article 101349. https://doi.org/10.1016/j.xcrm.2023.101349

@article{593db687063143898306d3c5909dab39,

title = "Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis",

abstract = "The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.",

keywords = "cancer, cell-free DNA, fragmentomics, liquid biopsy, multi-modal, sequencing",

author = "Norbert Moldovan and {van der Pol}, Ymke and {van den Ende}, Tom and Dries Boers and Sandra Verkuijlen and Aafke Creemers and Jip Ramaker and Trang Vu and Sanne Bootsma and Lenos, {Kristiaan J.} and Louis Vermeulen and Fransen, {Marieke F.} and Michiel Pegtel and Idris Bahce and {van Laarhoven}, Hanneke and Florent Mouliere",

note = "Funding Information: The authors are thankful to Mai Tran, Dr. Wendy Onstenk, and the Amsterdam UMC Liquid Biopsy Center for the logistical support and advice. The authors are also thankful to Ilias Houda, Rimsha Shaikh, and Ezgi Ulas for their help in annotating clinical information. Y.v.d.P. and F.M. are funded by the Amsterdam UMC Liquid Biopsy Center , an initiative made possible through the Stichting Cancer Center Amsterdam . The authors would like to thank Dr. Dineika Chandrananda for comments and discussions to improve the analysis of the ichorCNA algorithm. The authors would like to thank Dr. Caitrin Crudden, Dr. Steven Wang, Dr. Yongsoo Kim, Ignas Krikstaponis, and Francesco Orlando for comments and discussions. This work was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative . N.M. and F.M. are supported by a Dutch Cancer Fund ( KWF-12822 ). The PERFECT study was financially supported by Hoffmann-La Roche, Ltd. , Basel, Switzerland. Analysis of cfDNA of the neoadjuvant CRT (nCRT) cohort was made possible through a grant of the Maag Lever Darm Stichting ( SK18-32 ). Funders have no role in the design of the study. Funding Information: The authors are thankful to Mai Tran, Dr. Wendy Onstenk, and the Amsterdam UMC Liquid Biopsy Center for the logistical support and advice. The authors are also thankful to Ilias Houda, Rimsha Shaikh, and Ezgi Ulas for their help in annotating clinical information. Y.v.d.P. and F.M. are funded by the Amsterdam UMC Liquid Biopsy Center, an initiative made possible through the Stichting Cancer Center Amsterdam. The authors would like to thank Dr. Dineika Chandrananda for comments and discussions to improve the analysis of the ichorCNA algorithm. The authors would like to thank Dr. Caitrin Crudden, Dr. Steven Wang, Dr. Yongsoo Kim, Ignas Krikstaponis, and Francesco Orlando for comments and discussions. This work was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative. N.M. and F.M. are supported by a Dutch Cancer Fund (KWF-12822). The PERFECT study was financially supported by Hoffmann-La Roche, Ltd., Basel, Switzerland. Analysis of cfDNA of the neoadjuvant CRT (nCRT) cohort was made possible through a grant of the Maag Lever Darm Stichting (SK18-32). Funders have no role in the design of the study. Conception and design, N.M. and F.M.; experiments and data collection, Y.v.d.P. J.R. S.V. and T.V.; data processing, N.M. Y.v.d.P. D.B. and F.M.; software development, N.M.; data analysis, N.M. and F.M.; sample acquisition, T.v.d.E. A.C. M.F.F. H.v.L. and I.B.; funding acquisition, M.P. H.v.L. I.B. and F.M.; manuscript draft, N.M. Y.v.d.P. and F.M.; manuscript revisions and comments, N.M. Y.v.d.P, T.v.d.E. D.B. S.V. J.R. A.C. T.V. M.F.F. M.P. H.v.L. I.B. and F.M.; supervision, F.M. F.M. is co-inventor on multiple patents related to cfDNA analysis. Other co-authors have no relevant conflict of interests. Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2024",

month = jan,

day = "16",

doi = "https://doi.org/10.1016/j.xcrm.2023.101349",

language = "English",

volume = "5",

journal = "Cell Reports Medicine",

issn = "2666-3791",

publisher = "Cell Press",

number = "1",

}

Moldovan, N, van der Pol, Y, van den Ende, T, Boers, D, Verkuijlen, S, Creemers, A, Ramaker, J, Vu, T, Bootsma, S, Lenos, KJ, Vermeulen, L , Fransen, MF , Pegtel, M , Bahce, I , van Laarhoven, H & Mouliere, F 2024, 'Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis', Cell Reports Medicine, vol. 5, no. 1, 101349. https://doi.org/10.1016/j.xcrm.2023.101349

TY - JOUR

T1 - Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis

AU - Moldovan, Norbert

AU - van der Pol, Ymke

AU - van den Ende, Tom

AU - Boers, Dries

AU - Verkuijlen, Sandra

AU - Creemers, Aafke

AU - Ramaker, Jip

AU - Vu, Trang

AU - Bootsma, Sanne

AU - Lenos, Kristiaan J.

AU - Vermeulen, Louis

AU - Fransen, Marieke F.

AU - Pegtel, Michiel

AU - Bahce, Idris

AU - van Laarhoven, Hanneke

AU - Mouliere, Florent

N1 - Funding Information: The authors are thankful to Mai Tran, Dr. Wendy Onstenk, and the Amsterdam UMC Liquid Biopsy Center for the logistical support and advice. The authors are also thankful to Ilias Houda, Rimsha Shaikh, and Ezgi Ulas for their help in annotating clinical information. Y.v.d.P. and F.M. are funded by the Amsterdam UMC Liquid Biopsy Center , an initiative made possible through the Stichting Cancer Center Amsterdam . The authors would like to thank Dr. Dineika Chandrananda for comments and discussions to improve the analysis of the ichorCNA algorithm. The authors would like to thank Dr. Caitrin Crudden, Dr. Steven Wang, Dr. Yongsoo Kim, Ignas Krikstaponis, and Francesco Orlando for comments and discussions. This work was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative . N.M. and F.M. are supported by a Dutch Cancer Fund ( KWF-12822 ). The PERFECT study was financially supported by Hoffmann-La Roche, Ltd. , Basel, Switzerland. Analysis of cfDNA of the neoadjuvant CRT (nCRT) cohort was made possible through a grant of the Maag Lever Darm Stichting ( SK18-32 ). Funders have no role in the design of the study. Funding Information: The authors are thankful to Mai Tran, Dr. Wendy Onstenk, and the Amsterdam UMC Liquid Biopsy Center for the logistical support and advice. The authors are also thankful to Ilias Houda, Rimsha Shaikh, and Ezgi Ulas for their help in annotating clinical information. Y.v.d.P. and F.M. are funded by the Amsterdam UMC Liquid Biopsy Center, an initiative made possible through the Stichting Cancer Center Amsterdam. The authors would like to thank Dr. Dineika Chandrananda for comments and discussions to improve the analysis of the ichorCNA algorithm. The authors would like to thank Dr. Caitrin Crudden, Dr. Steven Wang, Dr. Yongsoo Kim, Ignas Krikstaponis, and Francesco Orlando for comments and discussions. This work was carried out on the Dutch national e-infrastructure with the support of SURF Cooperative. N.M. and F.M. are supported by a Dutch Cancer Fund (KWF-12822). The PERFECT study was financially supported by Hoffmann-La Roche, Ltd., Basel, Switzerland. Analysis of cfDNA of the neoadjuvant CRT (nCRT) cohort was made possible through a grant of the Maag Lever Darm Stichting (SK18-32). Funders have no role in the design of the study. Conception and design, N.M. and F.M.; experiments and data collection, Y.v.d.P. J.R. S.V. and T.V.; data processing, N.M. Y.v.d.P. D.B. and F.M.; software development, N.M.; data analysis, N.M. and F.M.; sample acquisition, T.v.d.E. A.C. M.F.F. H.v.L. and I.B.; funding acquisition, M.P. H.v.L. I.B. and F.M.; manuscript draft, N.M. Y.v.d.P. and F.M.; manuscript revisions and comments, N.M. Y.v.d.P, T.v.d.E. D.B. S.V. J.R. A.C. T.V. M.F.F. M.P. H.v.L. I.B. and F.M.; supervision, F.M. F.M. is co-inventor on multiple patents related to cfDNA analysis. Other co-authors have no relevant conflict of interests. Publisher Copyright: © 2023 The Author(s)

PY - 2024/1/16

Y1 - 2024/1/16

N2 - The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

AB - The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

KW - cancer

KW - cell-free DNA

KW - fragmentomics

KW - liquid biopsy

KW - multi-modal

KW - sequencing

UR - http://www.scopus.com/inward/record.url?scp=85180591552&partnerID=8YFLogxK

U2 - https://doi.org/10.1016/j.xcrm.2023.101349

DO - https://doi.org/10.1016/j.xcrm.2023.101349

M3 - Article

C2 - 38128532

SN - 2666-3791

VL - 5

JO - Cell Reports Medicine

JF - Cell Reports Medicine

IS - 1

M1 - 101349

ER -

Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis

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Keywords

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