Genome-wide cell-free DNA fragmentation in patients with cancer

Stephen Cristiano, Alessandro Leal, Jillian Phallen, Jacob Fiksel, Vilmos Adleff, Daniel C. Bruhm, Sarah Østrup Jensen, Jamie E. Medina, Carolyn Hruban, James R. White, Doreen N. Palsgrove, Noushin Niknafs, Valsamo Anagnostou, Patrick Forde, Jarushka Naidoo, Kristen Marrone, Julie Brahmer, Brian D. Woodward, Hatim Husain, Karlijn L. van Rooijen & 16 others Mai Britt Worm Ørntoft, Anders Husted Madsen, Cornelis J.H. van de Velde, Marcel Verheij, Annemieke Cats, Cornelis J.A. Punt, Geraldine R. Vink, Nicole C.T. van Grieken, Miriam Koopman, Remond J.A. Fijneman, Julia S. Johansen, Hans Jørgen Nielsen, Gerrit A. Meijer, Claus Lindbjerg Andersen, Robert B Scharpf, Victor E Velculescu

Research output: Contribution to journalLetter

Abstract

Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.

Original languageEnglish (US)
Pages (from-to)385-389
Number of pages5
JournalNature
Volume570
Issue number7761
DOIs
StatePublished - Jun 20 2019

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DNA Fragmentation
Genome
DNA
Neoplasms
Bile Duct Neoplasms
Pancreatic Ducts
Area Under Curve
Stomach
Breast
Leukocytes
Lung
Mutation

ASJC Scopus subject areas

  • General

Cite this

Genome-wide cell-free DNA fragmentation in patients with cancer. / Cristiano, Stephen; Leal, Alessandro; Phallen, Jillian; Fiksel, Jacob; Adleff, Vilmos; Bruhm, Daniel C.; Jensen, Sarah Østrup; Medina, Jamie E.; Hruban, Carolyn; White, James R.; Palsgrove, Doreen N.; Niknafs, Noushin; Anagnostou, Valsamo; Forde, Patrick; Naidoo, Jarushka; Marrone, Kristen; Brahmer, Julie; Woodward, Brian D.; Husain, Hatim; van Rooijen, Karlijn L.; Ørntoft, Mai Britt Worm; Madsen, Anders Husted; van de Velde, Cornelis J.H.; Verheij, Marcel; Cats, Annemieke; Punt, Cornelis J.A.; Vink, Geraldine R.; van Grieken, Nicole C.T.; Koopman, Miriam; Fijneman, Remond J.A.; Johansen, Julia S.; Nielsen, Hans Jørgen; Meijer, Gerrit A.; Andersen, Claus Lindbjerg; Scharpf, Robert B; Velculescu, Victor E.

In: Nature, Vol. 570, No. 7761, 20.06.2019, p. 385-389.

Research output: Contribution to journalLetter

Cristiano, S, Leal, A, Phallen, J, Fiksel, J, Adleff, V, Bruhm, DC, Jensen, SØ, Medina, JE, Hruban, C, White, JR, Palsgrove, DN, Niknafs, N, Anagnostou, V, Forde, P, Naidoo, J, Marrone, K, Brahmer, J, Woodward, BD, Husain, H, van Rooijen, KL, Ørntoft, MBW, Madsen, AH, van de Velde, CJH, Verheij, M, Cats, A, Punt, CJA, Vink, GR, van Grieken, NCT, Koopman, M, Fijneman, RJA, Johansen, JS, Nielsen, HJ, Meijer, GA, Andersen, CL, Scharpf, RB & Velculescu, VE 2019, 'Genome-wide cell-free DNA fragmentation in patients with cancer', Nature, vol. 570, no. 7761, pp. 385-389. https://doi.org/10.1038/s41586-019-1272-6
Cristiano S, Leal A, Phallen J, Fiksel J, Adleff V, Bruhm DC et al. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature. 2019 Jun 20;570(7761):385-389. https://doi.org/10.1038/s41586-019-1272-6
Cristiano, Stephen ; Leal, Alessandro ; Phallen, Jillian ; Fiksel, Jacob ; Adleff, Vilmos ; Bruhm, Daniel C. ; Jensen, Sarah Østrup ; Medina, Jamie E. ; Hruban, Carolyn ; White, James R. ; Palsgrove, Doreen N. ; Niknafs, Noushin ; Anagnostou, Valsamo ; Forde, Patrick ; Naidoo, Jarushka ; Marrone, Kristen ; Brahmer, Julie ; Woodward, Brian D. ; Husain, Hatim ; van Rooijen, Karlijn L. ; Ørntoft, Mai Britt Worm ; Madsen, Anders Husted ; van de Velde, Cornelis J.H. ; Verheij, Marcel ; Cats, Annemieke ; Punt, Cornelis J.A. ; Vink, Geraldine R. ; van Grieken, Nicole C.T. ; Koopman, Miriam ; Fijneman, Remond J.A. ; Johansen, Julia S. ; Nielsen, Hans Jørgen ; Meijer, Gerrit A. ; Andersen, Claus Lindbjerg ; Scharpf, Robert B ; Velculescu, Victor E. / Genome-wide cell-free DNA fragmentation in patients with cancer. In: Nature. 2019 ; Vol. 570, No. 7761. pp. 385-389.
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abstract = "Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57{\%} to more than 99{\%} among the seven cancer types at 98{\%} specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75{\%} of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91{\%} of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.",
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T1 - Genome-wide cell-free DNA fragmentation in patients with cancer

AU - Cristiano, Stephen

AU - Leal, Alessandro

AU - Phallen, Jillian

AU - Fiksel, Jacob

AU - Adleff, Vilmos

AU - Bruhm, Daniel C.

AU - Jensen, Sarah Østrup

AU - Medina, Jamie E.

AU - Hruban, Carolyn

AU - White, James R.

AU - Palsgrove, Doreen N.

AU - Niknafs, Noushin

AU - Anagnostou, Valsamo

AU - Forde, Patrick

AU - Naidoo, Jarushka

AU - Marrone, Kristen

AU - Brahmer, Julie

AU - Woodward, Brian D.

AU - Husain, Hatim

AU - van Rooijen, Karlijn L.

AU - Ørntoft, Mai Britt Worm

AU - Madsen, Anders Husted

AU - van de Velde, Cornelis J.H.

AU - Verheij, Marcel

AU - Cats, Annemieke

AU - Punt, Cornelis J.A.

AU - Vink, Geraldine R.

AU - van Grieken, Nicole C.T.

AU - Koopman, Miriam

AU - Fijneman, Remond J.A.

AU - Johansen, Julia S.

AU - Nielsen, Hans Jørgen

AU - Meijer, Gerrit A.

AU - Andersen, Claus Lindbjerg

AU - Scharpf, Robert B

AU - Velculescu, Victor E

PY - 2019/6/20

Y1 - 2019/6/20

N2 - Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.

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