Detection and characterization of lung cancer using cell-free DNA fragmentomes

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

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Detection and characterization of lung cancer using cell-free DNA fragmentomes. / Mathios, Dimitrios; Johansen, Jakob Sidenius; Cristiano, Stephen; Medina, Jamie E.; Phallen, Jillian; Larsen, Klaus R.; Bruhm, Daniel C.; Niknafs, Noushin; Ferreira, Leonardo; Adleff, Vilmos; Chiao, Jia Yuee; Leal, Alessandro; Noe, Michael; White, James R.; Arun, Adith S.; Hruban, Carolyn; Annapragada, Akshaya V.; Jensen, Sarah Østrup; Ørntoft, Mai Britt Worm; Madsen, Anders Husted; Carvalho, Beatriz; de Wit, Meike; Carey, Jacob; Dracopoli, Nicholas C.; Maddala, Tara; Fang, Kenneth C.; Hartman, Anne Renee; Forde, Patrick M.; Anagnostou, Valsamo; Brahmer, Julie R.; Fijneman, Remond J.A.; Nielsen, Hans Jørgen; Meijer, Gerrit A.; Andersen, Claus Lindbjerg; Mellemgaard, Anders; Bojesen, Stig E.; Scharpf, Robert B.; Velculescu, Victor E.

I: Nature Communications, Bind 12, Nr. 1, 5060, 12.2021.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Mathios, D, Johansen, JS, Cristiano, S, Medina, JE, Phallen, J, Larsen, KR, Bruhm, DC, Niknafs, N, Ferreira, L, Adleff, V, Chiao, JY, Leal, A, Noe, M, White, JR, Arun, AS, Hruban, C, Annapragada, AV, Jensen, SØ, Ørntoft, MBW, Madsen, AH, Carvalho, B, de Wit, M, Carey, J, Dracopoli, NC, Maddala, T, Fang, KC, Hartman, AR, Forde, PM, Anagnostou, V, Brahmer, JR, Fijneman, RJA, Nielsen, HJ, Meijer, GA, Andersen, CL, Mellemgaard, A, Bojesen, SE, Scharpf, RB & Velculescu, VE 2021, 'Detection and characterization of lung cancer using cell-free DNA fragmentomes', Nature Communications, bind 12, nr. 1, 5060. https://doi.org/10.1038/s41467-021-24994-w

APA

Mathios, D., Johansen, J. S., Cristiano, S., Medina, J. E., Phallen, J., Larsen, K. R., Bruhm, D. C., Niknafs, N., Ferreira, L., Adleff, V., Chiao, J. Y., Leal, A., Noe, M., White, J. R., Arun, A. S., Hruban, C., Annapragada, A. V., Jensen, S. Ø., Ørntoft, M. B. W., ... Velculescu, V. E. (2021). Detection and characterization of lung cancer using cell-free DNA fragmentomes. Nature Communications, 12(1), [5060]. https://doi.org/10.1038/s41467-021-24994-w

Vancouver

Mathios D, Johansen JS, Cristiano S, Medina JE, Phallen J, Larsen KR o.a. Detection and characterization of lung cancer using cell-free DNA fragmentomes. Nature Communications. 2021 dec.;12(1). 5060. https://doi.org/10.1038/s41467-021-24994-w

Author

Mathios, Dimitrios ; Johansen, Jakob Sidenius ; Cristiano, Stephen ; Medina, Jamie E. ; Phallen, Jillian ; Larsen, Klaus R. ; Bruhm, Daniel C. ; Niknafs, Noushin ; Ferreira, Leonardo ; Adleff, Vilmos ; Chiao, Jia Yuee ; Leal, Alessandro ; Noe, Michael ; White, James R. ; Arun, Adith S. ; Hruban, Carolyn ; Annapragada, Akshaya V. ; Jensen, Sarah Østrup ; Ørntoft, Mai Britt Worm ; Madsen, Anders Husted ; Carvalho, Beatriz ; de Wit, Meike ; Carey, Jacob ; Dracopoli, Nicholas C. ; Maddala, Tara ; Fang, Kenneth C. ; Hartman, Anne Renee ; Forde, Patrick M. ; Anagnostou, Valsamo ; Brahmer, Julie R. ; Fijneman, Remond J.A. ; Nielsen, Hans Jørgen ; Meijer, Gerrit A. ; Andersen, Claus Lindbjerg ; Mellemgaard, Anders ; Bojesen, Stig E. ; Scharpf, Robert B. ; Velculescu, Victor E. / Detection and characterization of lung cancer using cell-free DNA fragmentomes. I: Nature Communications. 2021 ; Bind 12, Nr. 1.

Bibtex

@article{b752130a56114224a4a2204133a212b8,
title = "Detection and characterization of lung cancer using cell-free DNA fragmentomes",
abstract = "Non-invasive approaches for cell-free DNA (cfDNA) assessment provide an opportunity for cancer detection and intervention. Here, we use a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation in a prospective study of 365 individuals at risk for lung cancer. We validate the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 lung cancer patients. Combining fragmentation features, clinical risk factors, and CEA levels, followed by CT imaging, detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites distinguished individuals with small cell lung cancer from those with non-small cell lung cancer with high accuracy (AUC = 0.98). A higher fragmentation score represented an independent prognostic indicator of survival. This approach provides a facile avenue for non-invasive detection of lung cancer.",
author = "Dimitrios Mathios and Johansen, {Jakob Sidenius} and Stephen Cristiano and Medina, {Jamie E.} and Jillian Phallen and Larsen, {Klaus R.} and Bruhm, {Daniel C.} and Noushin Niknafs and Leonardo Ferreira and Vilmos Adleff and Chiao, {Jia Yuee} and Alessandro Leal and Michael Noe and White, {James R.} and Arun, {Adith S.} and Carolyn Hruban and Annapragada, {Akshaya V.} and Jensen, {Sarah {\O}strup} and {\O}rntoft, {Mai Britt Worm} and Madsen, {Anders Husted} and Beatriz Carvalho and {de Wit}, Meike and Jacob Carey and Dracopoli, {Nicholas C.} and Tara Maddala and Fang, {Kenneth C.} and Hartman, {Anne Renee} and Forde, {Patrick M.} and Valsamo Anagnostou and Brahmer, {Julie R.} and Fijneman, {Remond J.A.} and Nielsen, {Hans J{\o}rgen} and Meijer, {Gerrit A.} and Andersen, {Claus Lindbjerg} and Anders Mellemgaard and Bojesen, {Stig E.} and Scharpf, {Robert B.} and Velculescu, {Victor E.}",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s).",
year = "2021",
month = dec,
doi = "10.1038/s41467-021-24994-w",
language = "English",
volume = "12",
journal = "Nature Communications",
issn = "2041-1723",
publisher = "nature publishing group",
number = "1",

}

RIS

TY - JOUR

T1 - Detection and characterization of lung cancer using cell-free DNA fragmentomes

AU - Mathios, Dimitrios

AU - Johansen, Jakob Sidenius

AU - Cristiano, Stephen

AU - Medina, Jamie E.

AU - Phallen, Jillian

AU - Larsen, Klaus R.

AU - Bruhm, Daniel C.

AU - Niknafs, Noushin

AU - Ferreira, Leonardo

AU - Adleff, Vilmos

AU - Chiao, Jia Yuee

AU - Leal, Alessandro

AU - Noe, Michael

AU - White, James R.

AU - Arun, Adith S.

AU - Hruban, Carolyn

AU - Annapragada, Akshaya V.

AU - Jensen, Sarah Østrup

AU - Ørntoft, Mai Britt Worm

AU - Madsen, Anders Husted

AU - Carvalho, Beatriz

AU - de Wit, Meike

AU - Carey, Jacob

AU - Dracopoli, Nicholas C.

AU - Maddala, Tara

AU - Fang, Kenneth C.

AU - Hartman, Anne Renee

AU - Forde, Patrick M.

AU - Anagnostou, Valsamo

AU - Brahmer, Julie R.

AU - Fijneman, Remond J.A.

AU - Nielsen, Hans Jørgen

AU - Meijer, Gerrit A.

AU - Andersen, Claus Lindbjerg

AU - Mellemgaard, Anders

AU - Bojesen, Stig E.

AU - Scharpf, Robert B.

AU - Velculescu, Victor E.

N1 - Publisher Copyright: © 2021, The Author(s).

PY - 2021/12

Y1 - 2021/12

N2 - Non-invasive approaches for cell-free DNA (cfDNA) assessment provide an opportunity for cancer detection and intervention. Here, we use a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation in a prospective study of 365 individuals at risk for lung cancer. We validate the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 lung cancer patients. Combining fragmentation features, clinical risk factors, and CEA levels, followed by CT imaging, detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites distinguished individuals with small cell lung cancer from those with non-small cell lung cancer with high accuracy (AUC = 0.98). A higher fragmentation score represented an independent prognostic indicator of survival. This approach provides a facile avenue for non-invasive detection of lung cancer.

AB - Non-invasive approaches for cell-free DNA (cfDNA) assessment provide an opportunity for cancer detection and intervention. Here, we use a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation in a prospective study of 365 individuals at risk for lung cancer. We validate the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 lung cancer patients. Combining fragmentation features, clinical risk factors, and CEA levels, followed by CT imaging, detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites distinguished individuals with small cell lung cancer from those with non-small cell lung cancer with high accuracy (AUC = 0.98). A higher fragmentation score represented an independent prognostic indicator of survival. This approach provides a facile avenue for non-invasive detection of lung cancer.

U2 - 10.1038/s41467-021-24994-w

DO - 10.1038/s41467-021-24994-w

M3 - Journal article

C2 - 34417454

AN - SCOPUS:85113257362

VL - 12

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

IS - 1

M1 - 5060

ER -

ID: 286314755