No retraction, correction or concern found when last checked on Oct 31, 2026.

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

Christopher Abbosh, Alexander M. Frankell, Thomas Harrison and 97 more (opens in a new tab)

Nature · 2023

doi:10.1038/s41586-023-05776-4 (opens in a new tab)

Abstract

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy. Measurements of subclonal expansion of ctDNA in the plasma before surgery may enable the prediction of future metastatic subclones, offering the possibility for early intervention in patients with non-small-cell lung cancer.

Shown for reading. Its publisher allows quoting it, not republishing it.

References 76

1.
Moding EJ, Nabet BY, Alizadeh AA, Diehn M. Detecting Liquid Remnants of Solid Tumors: Circulating Tumor DNA Minimal Residual Disease. Cancer Discov. 2021;11:2968-2986.
Not in our library10.1158/2159-8290.cd-21-0634 (opens in a new tab)
2.
Jamal-Hanjani M, et al. Tracking the Evolution of Non-Small-Cell Lung Cancer. N Engl J Med. 2017;376:2109-2121.
Not in our library10.1056/nejmoa1616288 (opens in a new tab)
3.
Chabon JJ, et al. Integrating genomic features for non-invasive early lung cancer detection. Nature. 2020;580:245-251.
Not in our library10.1038/s41586-020-2140-0 (opens in a new tab)
4.
Circulating Tumor DNA as a Prognostic Biomarker in Localized Non-small Cell Lung Cancer · 2020
Not checked
5.
Xia L, et al. Perioperative ctDNA-based Molecular Residual Disease Detection for Non-Small Cell Lung Cancer: A Prospective Multicenter Cohort Study (LUNGCA-1). Clin Cancer Res. 2021.
Not in our library10.1158/1078-0432.ccr-21-3044 (opens in a new tab)
6.
Chaudhuri AA, et al. Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling. Cancer Discov. 2017;7:1394-1403.
Not in our library10.1158/2159-8290.cd-17-0716 (opens in a new tab)
7.
Abbosh C, et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature. 2017;545:446-451.
Not in our library10.1038/nature22364 (opens in a new tab)
8.
Gale D, et al. Residual ctDNA after treatment predicts early relapse in patients with early-stage non-small cell lung cancer. Annals of Oncology. 2022;33.
Not in our library10.1016/j.annonc.2022.02.007 (opens in a new tab)
9.
Powles T, et al. ctDNA guiding adjuvant immunotherapy in urothelial carcinoma. Nature. 2021;595:432-437.
Not in our library10.1038/s41586-021-03642-9 (opens in a new tab)
10.
Tie J, et al. Circulating Tumor DNA Analysis Guiding Adjuvant Therapy in Stage II Colon Cancer. N Engl J Med. 2022;386:2261-2272.
Not in our library10.1056/nejmoa2200075 (opens in a new tab)
11.
Parikh AR, et al. Liquid versus tissue biopsy for detecting acquired resistance and tumor heterogeneity in gastrointestinal cancers. Nat Med. 2019;25:1415-1421.
Not in our library10.1038/s41591-019-0561-9 (opens in a new tab)
12.
Multifocal clonal evolution characterized using circulating tumour DNA in a case of metastatic breast cancer · 2015
No notice
13.
Herberts C, et al. Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer. Nature. 2022.
Not in our library10.1038/s41586-022-04975-9 (opens in a new tab)
14.
Lung cancer: diagnosis and management NICE guideline [NG122].
Not in our library
15.
Zheng Z, et al. Anchored multiplex PCR for targeted next-generation sequencing. Nat Med. 2014;20:1479-1484.
Not in our library10.1038/nm.3729 (opens in a new tab)
16.
Abbosh C, Birkbak NJ, Swanton C. Early stage NSCLC - challenges to implementing ctDNA-based screening and MRD detection. Nat Rev Clin Oncol. 2018;15:577-586.
Not in our library10.1038/s41571-018-0058-3 (opens in a new tab)
17.
Newman AM, et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat Med. 2014;20:548-554.
Not in our library10.1038/nm.3519 (opens in a new tab)
18.
GSVA: gene set variation analysis for microarray and RNA-Seq data · 2013
No notice
19.
Liberzon A, et al. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1:417-425.
Not in our library10.1016/j.cels.2015.12.004 (opens in a new tab)
20.
Biswas D, et al. A clonal expression biomarker associates with lung cancer mortality. Nat Med. 2019;25:1540-1548.
Not in our library10.1038/s41591-019-0595-z (opens in a new tab)
21.
Burrell RA, et al. Replication stress links structural and numerical cancer chromosomal instability. Nature. 2013;494:492-496.
Not in our library10.1038/nature11935 (opens in a new tab)
22.
Wang ZC, et al. Profiles of genomic instability in high-grade serous ovarian cancer predict treatment outcome. Clin Cancer Res. 2012;18:5806-5815.
Not in our library10.1158/1078-0432.ccr-12-0857 (opens in a new tab)
23.
GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancers · 2011
No notice
24.
Shih DJH, et al. Genomic characterization of human brain metastases identifies drivers of metastatic lung adenocarcinoma. Nat Genet. 2020;52:371-377.
Not in our library10.1038/s41588-020-0592-7 (opens in a new tab)
25.
COSMIC: the Catalogue Of Somatic Mutations In Cancer · 2018
No notice
26.
Garcia-Murillas I, et al. Assessment of Molecular Relapse Detection in Early-Stage Breast Cancer. JAMA Oncol. 2019;5:1473-1478.
Not in our library10.1001/jamaoncol.2019.1838 (opens in a new tab)
27.
TRACERx 421 primary paper. 2022.
Not in our library
28.
Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition · 2021
No notice
29.
McGranahan N, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016;351:1463-1469.
Not in our library10.1126/science.aaf1490 (opens in a new tab)
30.
The evolution of non-small cell lung cancer metastases in TRACERx · 2023
No notice
31.
Genomic–transcriptomic evolution in lung cancer and metastasis · 2023
No notice
32.
Moding EJ, et al. Circulating Tumor DNA Dynamics Predict Benefit from Consolidation Immunotherapy in Locally Advanced Non-Small Cell Lung Cancer. Nat Cancer. 2020;1:176-183.
Not in our library10.1038/s43018-019-0011-0 (opens in a new tab)
33.
Chen K, et al. Perioperative Dynamic Changes in Circulating Tumor DNA in Patients with Lung Cancer (DYNAMIC). Clin Cancer Res. 2019;25:7058-7067.
Not in our library10.1158/1078-0432.ccr-19-1213 (opens in a new tab)
34.
Li N, et al. Perioperative circulating tumor DNA as a potential prognostic marker for operable stage I to IIIA non-small cell lung cancer. Cancer. 2021.
Not in our library10.1002/cncr.33985 (opens in a new tab)
35.
Kurtz DM, et al. Enhanced detection of minimal residual disease by targeted sequencing of phased variants in circulating tumor DNA. Nat Biotechnol. 2021;39:1537-1547.
Not in our library10.1038/s41587-021-00981-w (opens in a new tab)
36.
Cohen JD, et al. Detection of low-frequency DNA variants by targeted sequencing of the Watson and Crick strands. Nat Biotechnol. 2021;39:1220-1227.
Not in our library10.1038/s41587-021-00900-z (opens in a new tab)
37.
Gydush G, et al. Massively parallel enrichment of low-frequency alleles enables duplex sequencing at low depth. Nat Biomed Eng. 2022;6:257-266.
Not in our library10.1038/s41551-022-00855-9 (opens in a new tab)
38.
Van Loo P, et al. Allele-specific copy number analysis of tumors. Proc Natl Acad Sci U S A. 2010;107:16910-16915.
Not in our library10.1073/pnas.1009843107 (opens in a new tab)
39.
The Life History of 21 Breast Cancers · 2012
Corrected
40.
Roth A, et al. PyClone: statistical inference of clonal population structure in cancer. Nat Methods. 2014;11:396-398.
Not in our library10.1038/nmeth.2883 (opens in a new tab)
41.
Visualizing tumor evolution with the fishplot package for R · 2016
No notice
42.
Frankell AM, Colliver E, Mcgranahan N, Swanton C. cloneMap: a R package to visualise clonal heterogeneity. bioRxiv. 2022;2022.07.26.501523.
Not in our library10.1101/2022.07.26.501523 (opens in a new tab)
43.
Birkbak NJ, Mcgranahan N. Cancer Cell Review Cancer Genome Evolutionary Trajectories in Metastasis. Cancer Cell. 2020;37:8-19.
Not in our library10.1016/j.ccell.2019.12.004 (opens in a new tab)
44.
Rosenthal R, et al. Neoantigen-directed immune escape in lung cancer evolution. Nature. 2019;567:479-485.
Not in our library10.1038/s41586-019-1032-7 (opens in a new tab)
45.
Lai Z, et al. VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research. Nucleic Acids Res. 2016;44:e108.
Not in our library10.1093/nar/gkw227 (opens in a new tab)
46.
Signorell A, Aho K, Alfons A, Anderegg N, Aragon T. DescTools: Tools for descriptive statistics. R package version 0.99.
Not in our library
47.
Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139-140.
Not in our library10.1093/bioinformatics/btp616 (opens in a new tab)
48.
limma powers differential expression analyses for RNA-sequencing and microarray studies · 2015
No notice
49.
Yu G, He Q-Y. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. Mol Biosyst. 2016;12:477-479.
Not in our library10.1039/c5mb00663e (opens in a new tab)
50.
Kassambara A. Pipe-Friendly Framework for Basic Statistical Tests [R package rstatix version 0.7.1]. 2022.
Not in our library
51.
Kuznetsova A, Brockhoff PB, Christensen RHB. lmerTest Package: Tests in Linear Mixed Effects Models. J Stat Softw. 2017;82:1-26.
Not in our library
52.
Sanchez-Vega F, et al. Oncogenic Signaling Pathways in The Cancer Genome Atlas. Cell. 2018;173:321-337.
Not in our library10.1016/j.cell.2018.03.035 (opens in a new tab)
53.
Bielski CM, et al. Genome doubling shapes the evolution and prognosis of advanced cancers. Nat Genet. 2018;50:1189-1195.
Not in our library10.1038/s41588-018-0165-1 (opens in a new tab)
54.
Jaccard/Tanimoto similarity test and estimation methods for biological presence-absence data · 2019
No notice
55.
Larsson J. Area-Proportional Euler and Venn Diagrams with Ellipses [R package eulerr version 7.0.0. 2022.
Not in our library
56.
Yu G. Convert Plot to ‘grob’ or ‘ggplot’ Object [R package ggplotify version 0.1.0. 2021.
Not in our library
57.
Therneau TM. A Package for Survival Analysis in R. 2021.
Not in our library
58.
Wiesweg M. survivalAnalysis: High-Level Interface for Survival Analysis and Associated Plots. 2022.
Not in our library
59.
Kassambara A, Kosinski M, Biecek P. survminer: Drawing Survival Curves using ‘ggplot2’. 2021.
Not in our library
60.
R: A language and environment for statistical computing. 2021.
Not in our library
61.
Wickham H, et al. Welcome to the tidyverse. J Open Source Softw. 2019;4:1686.
Not in our library
62.
R package data.table version 1.14.6. 2022.
Not in our library
63.
Read Excel Files [R package readxl version 1.4.1]. 2022.
Not in our library
64.
Klik M. Lightning Fast Serialization of Data Frames [R package fst version 0.9.8]. 2022.
Not in our library
65.
Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations · 2013
No notice
66.
Turner JA, Bolen CR, Blankenship DM. Quantitative gene set analysis generalized for repeated measures, confounder adjustment, and continuous covariates. BMC Bioinformatics. 2015;16:272.
Not in our library10.1186/s12859-015-0707-9 (opens in a new tab)
67.
Meng H, Yaari G, Bolen CR, Avey S, Kleinstein SH. Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE). PLoS Comput Biol. 2019;15:e1006899.
Not in our library10.1371/journal.pcbi.1006899 (opens in a new tab)
68.
Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847-2849.
Not in our library10.1093/bioinformatics/btw313 (opens in a new tab)
69.
Wickham H. ggplot2: Elegant Graphics for Data Analysis. 2016.
Not in our library
70.
Kassambara A. ggpubr:‘ggplot2’ based publication ready plots. 2020.
Not in our library
71.
Slowikowski K. Automatically Position Non-Overlapping Text Labels with ‘ggplot2’ [R package ggrepel version 0.9.2]. 2022.
Not in our library
72.
Categorical Scatter (Violin Point) Plots [R package ggbeeswarm version 0.7.1]. 2022.
Not in our library
73.
Scale Functions for Visualization [R package scales version 1.2.1]. 2022.
Not in our library
74.
Pedersen TL. Accelerating 'ggplot2' [R package ggforce version 0.4.1]. 2022.
Not in our library
75.
Wilke CO. cowplot: Streamlined Plot Theme and Plot Annotations for ‘ggplot2’;. R package version. 2020.
Not in our library
76.
LiquidCNA: Tracking subclonal evolution from longitudinal liquid biopsies using somatic copy number alterations · 2021
Not checked

Cited by papers we hold 5

Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation · 2024
No notice
The two sides of chromosomal instability: drivers and brakes in cancer · 2024
No notice
Cancer biomarkers: Emerging trends and clinical implications for personalized treatment · 2024
No notice
The evolution of non-small cell lung cancer metastases in TRACERx · 2023
No notice
Genomic–transcriptomic evolution in lung cancer and metastasis · 2023
No notice

Questions about this paper

We email you if it is retracted, withdrawn, corrected or flagged.

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.