. 2017 Mar 24;18(1):53.

doi: 10.1186/s13059-017-1191-5.

CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA

Shuli Kang¹, Qingjiao Li¹, Quan Chen¹, Yonggang Zhou^{2

3}, Stacy Park⁴, Gina Lee⁵, Brandon Grimes⁴, Kostyantyn Krysan⁴, Min Yu⁶, Wei Wang⁷, Frank Alber¹, Fengzhu Sun¹, Steven M Dubinett^{8

9

10

11}, Wenyuan Li¹², Xianghong Jasmine Zhou^{13

14}

Affiliations

¹ Molecular and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA.
² Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA.
³ Institute for Quantitative and Computational Biosciences, University of California at Los Angeles, Los Angeles, CA, 90095, USA.
⁴ Division of Pulmonary, Critical Care Medicine, Clinical Immunology and Allergy, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
⁵ VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
⁶ Department of Stem Cell Biology and Regenerative Medicine, and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90033, USA.
⁷ Clinical Laboratory, Zhejiang Province Tongde Hospital, Hangzhou, Zhejiang Province, People's Republic of China.
⁸ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
⁹ Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
¹⁰ Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
¹¹ Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
¹² Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA. WenyuanLi@mednet.ucla.edu.
¹³ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA. XJZhou@mednet.ucla.edu.
¹⁴ Institute for Quantitative and Computational Biosciences, University of California at Los Angeles, Los Angeles, CA, 90095, USA. XJZhou@mednet.ucla.edu.

PMID: 28335812
PMCID: PMC5364586
DOI: 10.1186/s13059-017-1191-5

CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA

Shuli Kang et al. Genome Biol. 2017.

. 2017 Mar 24;18(1):53.

doi: 10.1186/s13059-017-1191-5.

Authors

Affiliations

¹ Molecular and Computational Biology, University of Southern California, Los Angeles, CA, 90089, USA.
² Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA.
³ Institute for Quantitative and Computational Biosciences, University of California at Los Angeles, Los Angeles, CA, 90095, USA.
⁴ Division of Pulmonary, Critical Care Medicine, Clinical Immunology and Allergy, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
⁵ VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA.
⁶ Department of Stem Cell Biology and Regenerative Medicine, and Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, 90033, USA.
⁷ Clinical Laboratory, Zhejiang Province Tongde Hospital, Hangzhou, Zhejiang Province, People's Republic of China.
⁸ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
⁹ Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
¹⁰ Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
¹¹ Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, 90095, USA. sdubinett@mednet.ucla.edu.
¹² Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA. WenyuanLi@mednet.ucla.edu.
¹³ Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, CA, 90095, USA. XJZhou@mednet.ucla.edu.
¹⁴ Institute for Quantitative and Computational Biosciences, University of California at Los Angeles, Los Angeles, CA, 90095, USA. XJZhou@mednet.ucla.edu.

PMID: 28335812
PMCID: PMC5364586
DOI: 10.1186/s13059-017-1191-5

Abstract

We propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. CancerLocator outperforms two established multi-class classification methods on simulations and real data, even with the low proportion of tumor-derived DNA in the cell-free DNA scenarios. CancerLocator also achieves promising results on patient plasma samples with low DNA methylation sequencing coverage.

Keywords: Cancer diagnosis; Cell-free DNA; DNA methylation; Liquid biopsy; Next-generation sequencing.

PubMed Disclaimer

Figures

**Fig. 1**
Flowchart of CancerLocator. Step 1: A set of solid tumor samples and healthy plasma samples collected from public databases and the literature are used to select the informative features (CpG clusters) that can differentiate tumor types or healthy plasma samples. Then the beta distributions of the methylation levels of these selected features for each tumor type or healthy plasma samples are learnt. Step 2: Given a plasma sample, the methylation profile of its cfDNAs is measured by whole-genome bisulfite sequencing, which is then used as input for cancer location prediction by CancerLocator

**Fig. 2**
The mixture model of methylation level (x) in a patient’s plasma cfDNA for different burdens of ctDNAs from the tumor type t. Note that x, u, and v are the methylation levels of a single CpG cluster k in cfDNA, solid tumor, and normal plasma, respectively

**Fig. 3**
The predicted ctDNA burden for simulated normal and cancer plasma samples. a Predicted ctDNA burdens for normal samples whose true ctDNA burden should be zero. b Predicted and true ctDNA burdens for cancer samples. Each *dot* represents a prediction with the true (*x-axis*) and predicted (*y-axis*) ctDNA burdens. The correct and incorrect predictions are represented by *cyan* and *red*, respectively, in both a and b

**Fig. 4**
Classification performances of three methods (CancerLocator, RF and SVM) on the ten subsets of simulation data. Each subset includes plasma cfDNA samples at certain cancer stage (represented as a ctDNA burden range)

**Fig. 5**
The relationship between ctDNA burden and tumor tissue prediction for each plasma sample of the real data. Each point represents a real plasma sample. This plot illustrates the average estimated tumor burden (*y-axis*) and the most frequently predicted tumor type (*dot color*) among ten runs for each plasma sample

**Fig. 6**
Illustration of the data partition for learning discriminating features, in both simulation and real data experiments. Note that simulation and real data experiments share the same subset (25%) of normal plasma samples

See this image and copyright information in PMC

Cited by

Leveraging locus-specific epigenetic heterogeneity to improve the performance of blood-based DNA methylation biomarkers.
Miller BF, Pisanic Ii TR, Margolin G, Petrykowska HM, Athamanolap P, Goncearenco A, Osei-Tutu A, Annunziata CM, Wang TH, Elnitski L. Miller BF, et al. Clin Epigenetics. 2020 Oct 20;12(1):154. doi: 10.1186/s13148-020-00939-w. Clin Epigenetics. 2020. PMID: 33081832 Free PMC article.
Hypomethylation in HBV integration regions aids non-invasive surveillance to hepatocellular carcinoma by low-pass genome-wide bisulfite sequencing.
Zhang H, Dong P, Guo S, Tao C, Chen W, Zhao W, Wang J, Cheung R, Villanueva A, Fan J, Ding H, Schrodi SJ, Zhang D, Zeng C. Zhang H, et al. BMC Med. 2020 Aug 3;18(1):200. doi: 10.1186/s12916-020-01667-x. BMC Med. 2020. PMID: 32741373 Free PMC article.
Cell-free DNA as a liquid biopsy for early detection of gastric cancer.
Huang ZB, Zhang HT, Yu B, Yu DH. Huang ZB, et al. Oncol Lett. 2021 Jan;21(1):3. doi: 10.3892/ol.2020.12264. Epub 2020 Nov 3. Oncol Lett. 2021. PMID: 33240409 Free PMC article. Review.
Utilization of molecular genetic approaches for colorectal cancer screening.
Emelyanova MA, Ikonnikova AY. Emelyanova MA, et al. World J Gastroenterol. 2024 Dec 14;30(46):4950-4957. doi: 10.3748/wjg.v30.i46.4950. World J Gastroenterol. 2024. PMID: 39679308 Free PMC article.
Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals.
Vavoulis DV, Cutts A, Thota N, Brown J, Sugar R, Rueda A, Ardalan A, Howard K, Matos Santo F, Sannasiddappa T, Miller B, Ash S, Liu Y, Song CX, Nicholson BD, Dreau H, Tregidgo C, Schuh A. Vavoulis DV, et al. Nat Commun. 2025 Jan 8;16(1):430. doi: 10.1038/s41467-024-55428-y. Nat Commun. 2025. PMID: 39779727 Free PMC article.

See all "Cited by" articles

References

1. Esteller M. Molecular origins of cancer epigenetics in cancer. N Engl J Med. 2008;358:1148–1159. doi: 10.1056/NEJMra072067. - DOI - PubMed
1. Ross JP, Rand KN, Molloy PL. Hypomethylation of repeated DNA sequences in cancer. Epigenomics. 2010;2:245–269. doi: 10.2217/epi.10.2. - DOI - PubMed
1. Yang Z, Jones A, Widschwendter M, Teschendorff AE. An integrative pan-cancer-wide analysis of epigenetic enzymes reveals universal patterns of epigenomic deregulation in cancer. Genome Biol. 2015;16:140. doi: 10.1186/s13059-015-0699-9. - DOI - PMC - PubMed
1. Sahnane N, Magnoli F, Bernasconi B, Tibiletti MG, Romualdi C, Pedroni M, et al. Aberrant DNA methylation profiles of inherited and sporadic colorectal cancer. Clin Epigenetics. 2015;7:131. doi: 10.1186/s13148-015-0165-2. - DOI - PMC - PubMed
1. Lee S-T, Wiemels JL. Genome-wide CpG island methylation and intergenic demethylation propensities vary among different tumor sites. Nucleic Acids Res. 2016;44:1105–1117. doi: 10.1093/nar/gkv1038. - DOI - PMC - PubMed

Publication types

Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA

Affiliations

CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA

Authors

Affiliations

Abstract

Figures

Similar articles

Cited by

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources