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. 2023 Oct 5;13(10):2166-2179.
doi: 10.1158/2159-8290.CD-21-1252.

The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer

Austin K Mattox  1   2   3   4 , Christopher Douville  1   2   3   4 , Yuxuan Wang  1   2   3   4 , Maria Popoli  1   2   3 , Janine Ptak  1   2   3   4 , Natalie Silliman  1   2   3   4 , Lisa Dobbyn  1   2   3 , Joy Schaefer  1   2   3   4 , Steve Lu  1   2   3   4 , Alexander H Pearlman  1   2   3   4 , Joshua D Cohen  1   2   3   4 , Jeanne Tie  5   6   7 , Peter Gibbs  5   6   7 , Kamel Lahouel  8 , Chetan Bettegowda  1   2   3   9 , Ralph H Hruban  10 , Cristian Tomasetti  8 , Peiyong Jiang  11   12 , K C Allen Chan  11   12 , Yuk Ming Dennis Lo  11   12 , Nickolas Papadopoulos  1   2   3 , Kenneth W Kinzler  1   2   3 , Bert Vogelstein  1   2   3   4
Affiliations

The Origin of Highly Elevated Cell-Free DNA in Healthy Individuals and Patients with Pancreatic, Colorectal, Lung, or Ovarian Cancer

Austin K Mattox et al. Cancer Discov. .

Abstract

Cell-free DNA (cfDNA) concentrations from patients with cancer are often elevated compared with those of healthy controls, but the sources of this extra cfDNA have never been determined. To address this issue, we assessed cfDNA methylation patterns in 178 patients with cancers of the colon, pancreas, lung, or ovary and 64 patients without cancer. Eighty-three of these individuals had cfDNA concentrations much greater than those generally observed in healthy subjects. The major contributor of cfDNA in all samples was leukocytes, accounting for ∼76% of cfDNA, with neutrophils predominating. This was true regardless of whether the samples were derived from patients with cancer or the total plasma cfDNA concentration. High levels of cfDNA observed in patients with cancer did not come from either neoplastic cells or surrounding normal epithelial cells from the tumor's tissue of origin. These data suggest that cancers may have a systemic effect on cell turnover or DNA clearance.

Significance: The origin of excess cfDNA in patients with cancer is unknown. Using cfDNA methylation patterns, we determined that neither the tumor nor the surrounding normal tissue contributes this excess cfDNA-rather it comes from leukocytes. This finding suggests that cancers have a systemic impact on cell turnover or DNA clearance. See related commentary by Thierry and Pisareva, p. 2122. This article is featured in Selected Articles from This Issue, p. 2109.

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Conflict of interest statement

CONFLICT OF INTEREST STATEMENT

BV, KWK, & NP are founders of Thrive Earlier Detection, an Exact Sciences Company. BV, KWK, NP, and CD hold equity in Exact Sciences. BV, KWK, and NP are founders of Personal Genome Diagnostics. KWK, BV, & NP hold equity in are consultants to CAGE Pharma. KWK, and NP own equity in Neophore and KWK and NP are consultants to Neophore. BV is a consultant to and holds equity in Catalio Capital Management. CB is a consultant to Depuy-Synthes and Bionaut Labs. The companies named above, as well as other companies, have licensed previously described technologies related to the work described in this paper from Johns Hopkins University. BV, KWK, NP, CB, RH, CT, CD, AKM, and JDC are inventors on some of these technologies. Licenses to these technologies are or will be associated with equity or royalty payments to the inventors as well as to Johns Hopkins University. Patent applications on the work described in this paper may be filed by Johns Hopkins University. The terms of all these arrangements are being managed by Johns Hopkins University in accordance with its conflict-of-interest policies. YMDL is a scientific cofounder, past member of scientific advisory board and past consultant of Grail. YMDL and KCAC hold equities and are board members of Take2 and DRA Limited. YMDL, KCAC and PJ receive patent licensing incomes from Illumina, Sequenom, Xcelom, Grail, Take2 and DRA Limited. KCAC is a past consultant to Grail. PJ holds equities in Grail. PJ is a consultant of Take2 Technologies Limited. PJ is a Director of KingMed Future.

Figures

Figure 1.
Figure 1.. Plasma cfDNA concentrations in previously described patients.
(A) Distribution of the average concentration of cfDNA in the plasma of patients with cancer as determined by qPCR shows that it is elevated compared to normal controls. Blue line = normal controls (N = 812). Red line = patients with cancer (N = 1005). (B) The concentration of cfDNA as determined by qPCR for normal controls (N = 812), and patients with breast (N = 209), colorectal (N = 388), esophageal (N = 45), liver (N = 44), lung (N = 104), ovarian (N = 54), pancreatic (N = 93), and stomach (N = 68) cancer. Data are derived from the previously published CancerSEEK study (9). *** p < 0.001
Figure 2.
Figure 2.. Deconvolution of the plasma cfDNA methylation profile using the reference cell type matrix derived from Sun et al. (3).
The total methylation profile of plasma cfDNA was deconvoluted into 12 different tissue types using quadratic programming. The total leukocyte concentration was taken to be the sum of the concentrations of neutrophils, B cells, and T cells. Note that the y-axes for the different tissue types shown are not the same.
Figure 3.
Figure 3.. Deconvolution of the plasma cfDNA methylation profile using the reference cell type matrix derived from Moss et al. (43).
The total methylation profile of plasma cfDNA was deconvoluted into 25 different tissue types using quadratic programming The total leukocyte concentration was taken to be the sum of myeloid progenitors, monocytes, neutrophils, B cells, CD4 T cells, CD8 T cells, and NK cells. Note that the y-axes for the different tissue types shown are not the same.
Figure 4.
Figure 4.. The amount of cfDNA from evaluable tissue sources before and ~24 hours after surgery
Each color represents a separate patient (see Supplemental Table 1). * p < 0.05, ** p < 0.01, *** p < 0.001.
See this image and copyright information in PMC

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