Pulmonary venous circulating tumor cell dissemination before tumor resection and disease relapse

Abstract

Approximately 50% of patients with early-stage non-small-cell lung cancer (NSCLC) who undergo surgery with curative intent will relapse within 5 years^1,2. Detection of circulating tumor cells (CTCs) at the time of surgery may represent a tool to identify patients at higher risk of recurrence for whom more frequent monitoring is advised. Here we asked whether CellSearch-detected pulmonary venous CTCs (PV-CTCs) at surgical resection of early-stage NSCLC represent subclones responsible for subsequent disease relapse. PV-CTCs were detected in 48% of 100 patients enrolled into the TRACERx study³, were associated with lung-cancer-specific relapse and remained an independent predictor of relapse in multivariate analysis adjusted for tumor stage. In a case study, genomic profiling of single PV-CTCs collected at surgery revealed higher mutation overlap with metastasis detected 10 months later (91%) than with the primary tumor (79%), suggesting that early-disseminating PV-CTCs were responsible for disease relapse. Together, PV-CTC enumeration and genomic profiling highlight the potential of PV-CTCs as early predictors of NSCLC recurrence after surgery. However, the limited sensitivity of PV-CTCs in predicting relapse suggests that further studies using a larger, independent cohort are warranted to confirm and better define the potential clinical utility of PV-CTCs in early-stage NSCLC.

Extended Data Fig.1

a, Time-dependent receiver operating characteristic (ROC) curves showing true positive and false positive rates for the 65^th, 75^th, 85^th PV-CTC quantiles (≥3, ≥7 and ≥39 PV-CTCs/7.5ml blood respectively) alongside the previously published threshold from our pilot study (≥18 PV-CTCs/7.5ml blood). All predictions were made at 720 days. Sensitivity and specificity of each category is shown along with area under ROC curve (AUROC) value. b, Kaplan–Meier curve showing lung cancer specific relapse free survival for 98 patients stratified as PV-CTC high or low according to the 75^th quantile (≥7 PV-CTCs/7.5ml blood). The number of patients at risk for every time point is indicated below the time point and colour coded according to the high or low groups. P value, HR and relative 95% confidence intervals (CI) (two-sided log-rank test) are indicated. c, Forest plot showing the results of multivariable regression analysis for PV-CTC high or low patients (≥7 PV-CTCs/7.5ml blood). The x-axis represents the hazard ratio with the reference line (dashed) and significance is calculated using a Cox proportional hazards model.

Extended Data Fig.2

a, Consort diagram describing samples used for downstream analysis. Only patients with ≥5 PV-CTCs (29) were processed through single cell isolation (DEPArray™). Single cells were not isolated from 6 out of the 29 samples due to failures during sample loading into the DEPArray™ machine. From the remaining 23 samples, 7 patients whose single CTCs isolated did not meet morphology criteria (see methods) were excluded. 16 samples were processed for whole genome amplification (WGA) and 2 patients whose CTCs did not show good quality genomic integrity index in QC post-WGA were removed (see methods). b, Table showing cases of relapse among the patients with single PV-CTCs isolated. c, Agarose gel showing results of a QC–PCR assay used to determine the genome integrity of each sample. 0–4 bands determine the overall DNA integrity of each sample. DEPArray images of corresponding PV-CTC (cytokeratin (CK)+ stained green, CD45+ stained blue, DAPI+ stained purple) are shown above. d, Examples of copy number profiles detected in single PV-CTCs, CECs and WBC control. Blue and red indicate regions of copy number loss and gain respectively.

Extended Data Fig.3

a, Venn diagram showing the overlap of somatic mutations detected between single PV-CTCs, primary and metastatic tumour. b, Venn diagram showing the overlap of somatic mutations detected between single PV-CTCs, metastatic tumour and cfDNA isolated at the time of relapse.

Extended Data Fig.4

Heat map showing the comparison of SNVs detected in primary tumour regions, metastasis, PV-CTCs, CECs, WBCs, and cfDNA samples (cfDNA pre-surgery was isolated from peripheral blood, cfDNA surgery was isolated from the pulmonary vein and cfDNA relapse was isolated at the time of relapse). Mutations are ordered according to their clonality established by primary tumour analysis.

Fig. 1. PV-CTC detection in early NSCLC.

a, TRACERx consort diagram. 149 patients consented for pulmonary vein blood sampling between June 2014 and March 2017. 27 samples were excluded because of failures in CellSearch® enrichment and enumeration. 22 patients were defined ineligible post-surgery and the remaining 100 patients constituted the final cohort for PV-CTC enumeration. b, Distribution of the number of PV-CTCs enumerated by CellSearch® from 100 patients with early NSCLC. LUAD (blue circle) and non-LUAD (red circle) patients are indicated. c, Heat map showing clinicopathological and PV-CTC detection data; Patients are stratified according to PV-CTC detection. Histological disease type is indicated by coloured bar above the heatmap.

Fig.2. PV-CTCs as independent predictors of disease-free survival.

a, Kaplan–Meier curves showing disease-free survival (DFS) of 100 patients stratified as PV-CTC high or low based on the previously published threshold from our pilot study (≥18 PV-CTCs/7.5ml blood). The number of patients at risk for every time point is indicated below the time point and colour coded according to the high or low groups. P value, HR and relative 95% confidence intervals (CI) (two-sided log-rank test) are indicated. b, Forest plot showing the results of multivariable regression analysis for PV-CTC high or low patients (≥18 PV-CTCs/7.5ml blood). The x-axis represents the hazard ratio with the reference line (dashed) and significance is calculated using a Cox proportional hazards model. The estimated hazard ratios and their 95% CI are presented as error bars. The log-rank test used was two-sided.

Fig.3. Mutations present in the relapse tumour are detected 10 months earlier in PV-CTCs and not in the primary tumour.

a, Patient timeline from diagnosis to death (FU=follow up; PET=positron emission tomography; MR=magnetic resonance). b, Heat map showing the comparison between CNA detected in PV-CTCs or circulating epithelial cells (CECs), in primary tumour regions (R1-3), in relapse tumour (Met) and in a WBC control. Regions of loss are coloured blue, regions of gain are coloured red. Chromosomes are indicated at the top of the figure. c, Heat map showing the comparison of SNVs detected in PV-CTCs, primary tumour regions and the metastasis. Mutations are ordered according to their clonality as established by primary tumour analysis. Green dashed boxes indicate mutations that are seen in the primary tumour, but not metastasis or PV-CTCs. Blue dashed box indicates the overlap between mutations considered metastatic private by primary tumour analysis and PV-CTCs. No mutations were found in the three CECs and two WBCs. d, Evolutionary tree encompassing tumour and PV-CTCs: the relationships between identified subclones is depicted, with size of circle reflecting the number of mutations in each subclone relative to largest. Length of lines connecting tumor subclones does not carry information. The beehive plots indicate the subclonal architecture of each tumour region, with 100 representative cells shown for each region and the nested colours corresponding to the ancestry of each cell. e, Heat map showing PV-CTC private mutations that are detected in primary tumour, metastasis and cfDNA following targeted deep sequencing.