early detection of residual breast cancer through a robust ... · hr: 35.84 (7.9 –161.32) p-value
TRANSCRIPT
Introduction• The potential utility of circulating tumor DNA (ctDNA) to detect minimal residual disease (MRD) following surgery and/or adjuvant therapy
and to monitor metastatic disease has been demonstrated in breast cancer.1-4
• Plasma ctDNA levels have been shown to correlate with changes in tumor burden, thereby providing an earlier measure of treatment response5,6 and to discriminate patients with and without eventual clinical recurrence post-surgery.2,3
• We previously reported early detection of lung cancer recurrence using a personalized tumor-specific approach;7,8 an improved version of this assay for patient-specific ctDNA detection was developed and made available for research use only (Signatera™ RUO).
Objectives The aim of the study was to determine the ‘lead interval’ between detection of ctDNA in plasma and clinical detection of overt metastatic
disease.
Methods
Clinical Protocol• Patients diagnosed with non-metastatic breast cancer with high risk of reccurence were prospectively recruited starting in Dec 2013.
• Eligible patients were followed up with semi-annual blood sampling for ctDNA analysis, along with concomitant clinical examination, and biochemical measurements, including CA 15-3 (Figure 1).
– All patients had completed adjuvant chemotherapy within 3 years of entering the study.
Figure 1. Schematic of Clinical Sample Collection
Conclusions• Plasma ctDNA was detected ahead of clinical or radiological relapse in 16/18 (89%) relapsed
patients. – Of the two relapsed patients who were not detected in the study, one patient had a local recurrence while the other had recently completed chemotherapy, and neither of the relapses were confirmed by biopsy.
• Metastatic relapse was predicted with a lead time of up to 2 years (median=8.9 months; range: 0.5–24.0 months).
• None of the 31 non-relapsing patients were ctDNA-positive at any time point (across 156 plasma samples).
• Our results demonstrate the use of a scalable patient-specific ctDNA approach capable of identifying residual disease in breast cancer patients with a high degree of sensitivity ahead of clinical or radiological detection of metastatic recurrence.
References
SAN ANTONIO BREAST CANCER SYMPOSIUM 2018San Antonio, Texas, USA | December 4–8, 2018
ctDNA Status at 1st Timepoint
0 25 50 75 100
75
Months After Surgery
Rel
aps-
Free
Sur
viva
l
100
50
25
0
| | ||| | | | |
| | | | | | | | | | | | |
ctDNA Status at Any TimepointA B
HR: 11.78 (4.28–32.46)p-value <0.001
| | | | | | | | | | | | | | | | | | | | | |
75
100
50
25
00 25 50 75 100
Months After Surgery
ctDNA NegativectDNA Positive
Rel
apse
Fre
e Su
rviv
al
HR: 35.84 (7.9 –161.32)p-value <0.001
ctDNA NegativectDNA Positive
Personalized, 16-plex assays accurately detect ctDNA ahead of clinical relapse. The figure depicts a summary of each patient’s (n=49) treatment regimen along with results of serial plasma samples (n=208) analyzed. Patients are categroized into three groups based on cancer subtype. Circles represent ctDNA status; solid black circles (ctDNA positive) indicate samples with at least two positve targets.
Personalized ctDNA detection in serial plasma samples predicts recurrence-free survival. A. Relapse-free survival according to the detection of ctDNA in the first post-surgical plasma sample. B. Relapse-free survival according to the detection of ctDNA in any follow-up plasma sample post-surgery. Data are from n=49 patients.
Figure 6. Personalized ctDNA Detection in Serial Plasma Samples Predicts Recurrence-Free Survival
Abstract number #1266
Lead Time: 721 Days
A
0.01
1.00
470 652 1078876 1246
Varia
nt A
llele
Fre
quen
cy (%
)
0
50
100
150
200
250
0.001
0.1
≤ 0.001
CA 15-3
Lead Time: 611 DaysE026: HR+
CA 15-3 Baseline
Days After Surgery Days After Surgery
E
CA 15-3 Baseline
110 306 518 690
Lead Time: 570 Days
E033: TNBC
CA
15-3
Days After Surgery
Var
iant
Alle
le F
requ
ency
(%)
0
50
100
150
200
250
0.01
0.1
1
10
≤ 0.001
C D
Days After Surgery
E040: HR-/HER2+
CA 15-3 Baseline
15711426 1615
Var
iant
Alle
le F
requ
ency
(%)
CA
15-3
0
50
100
150
200
250
≤ 0.001
Lead Time: 313 Days
0.01
1
10
1258
0.1
F
CA
15-3
B
CA 15-3 Baseline
330 673498 890 1093 1268 1400
E017: HR+
0
50
100
150
200
250
≤ 0.001
0.01
0.1
Var
iant
Alle
le F
requ
ency
(%)
476 660 856 961
Varia
nt A
llele
Fre
quen
cy (%
)
E029: TNBC
CA
15-3
0
50
100
150
200
250
0.01
1.00
≤ 0.001
0.1
Lead Time: 258 Days
CA 15-3 Baseline
Days After Surgery
Med
ian
VA
F (%
) of P
ositi
ve T
arge
ts
ctDNANegative ctDNA PositiveMolecular Relapse Clinical Relapse
CA 15-3 Mean VAF
0.1
1.0
10.0
Num
ber o
f Pos
itive
Tar
gets
First Time Point
LastTime Point
2
4
6
8
10
12
14
First Time Point
LastTime Point
Figure 5. Personalized Profiling Detects Rising ctDNA Ahead of Clinical Relapse
Figure 3. Patient Summaries
1 2 3 4
Timepoints
Obtain whole blood samples at longitudinal timepoints (eg, every 3 months)
Cell-free DNA extraction and patient-speci�c 16-plex PCR
Analyze ultra-deep NGS data for each of the 16 patient-speci�c mutations to detect presence of ctDNA
Analyze sequencing from tumor biopsy and matched normal blood at initial timepoint
Identify patient-speci�c, somatic variants and design custom 16-plex panel for each patient
1 2
3 4 5
11
13
16
1
4
7
LEAD TIME
MOLECULAR RELAPSE CLINICAL RELAPSE
VA
RIA
NT
ALL
ELE
FR
EQ
UE
NC
Y (
%)
DAYS AFTER SURGERY
0.01
1.00
≤ 0.001
0.1
First 50 women re-consented and included for Signatera study
Tumour biopsy tissue collected1 excluded due to insufficient
tumour DNA for WESWES to identify somatic
variants (n=49)
Non relapsed patients (n=31) total of 156 plasma samples
analysed
Relapsed patients (n=18) total of 52 plasma samples analyzed
Serial plasma samples collected (n=218)
Serial plasma samples analysed (n=215)
16 individual variants selected per patient
197 women on follow up after surgery and adjuvant therapy
188 women followed up
9 excluded for not meeting inclusion criteria
1 failed sequencing QC6 failed concordance QC
3 plasma samples excluded due to insufficient DNA for WES
Figure 2. Schematic of Molecular Protocol - ctDNA Analysis
The VAF distribution of custom assay in each patient’s primary tumour tissue
Breast Cancer Subtype
Total Patients (n)
Relapsed Patients(n)
Relapses Detected n (%)
PPV(%)
NPV(%)
Median Lead Time (Days)
HR+/HER2- 34 11 9 (82) 100 92 301
HER2+ 8 2 2 (100) 100 100 164
TNBC 7 5 5 (100) 100 100 258
Total 49 18 16 (89) 100 94 285
Table 1. Summary Table by Breast Cancer Subtype
Var
iant
Alle
le F
requ
ency
(%
)
0.0
0.2
0.4
0.6
0.8
1.0
E025
E042
E035
E012
E004
E018
E013
E038
E006
E043
E010
E041
E014
E005
E034
E039
E027
E021
E023
E017
E019
E032
E026
E020
E008
E047
E031
E036
E030
E022
E011
E044
E003
E016
E009
E002
E001
E037
E045
E007
E028
E040
E048
E015
E024
E049
E033
E046
E029
HR+/HER2- HER2+ TNBC
Patient Samples
Molecular Protocol - ctDNA Analysis (SignateraTM RUO)• The workflow of the molecular protocol is outlined in Figure 2.
• For the 49 women with breast cancer who were monitored in this study, exomic alterations were determined through paired-end sequencing of FFPE tumor-tissue specimens and matched normal DNA.
• Patient-specific somatic variants were identified by analyses of primary tumor and matched normal whole exome sequencing samples.
• Serial plasma samples were analyzed with the corresponding custom 16-plex assay panels using the SignateraTM RUO workflow in a blinded manner; a total of 208 samples were analyzed for ctDNA detection.
• Samples were considered ctDNA positive if at least two patient-specific targets were called and met the qualifying confidence score threshold.
Figure 4. Tumor Variant Allele Frequency Distribution in Signatera Patient-Specific Assays
A-E. Plasma levels of ctDNA across serial plasma time points for five breast cancer patients (one per panel). Mean VAFs are denoted by dark blue circle and solid lines represent the average VAF profile over time. The lead time is calculated as the time interval between clinical relapse (red triangle) and molecular relapse (blue triangle). CA 15-3 levels are graphed over time (teal circle) and the baseline levels are marked in light blue. F. Summary of percent variant allele frequency (VAF) and number of targets detected at molecular and clinical relapse for all ctDNA positive samples. Data are from 13 relapsed patients, excluding 3 patients with only one plasma time point.
1. Beaver JA et al. Detection of cancer DNA in plasma of patients with early-stage breast cancer. Clin Cancer Res. 2014;20(10):2643-2650.2. Garcia-Murillas I et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci Transl Med. 2015;7(302):302ra133.3. Olsson E et al. Serial monitoring of circulating tumor DNA in patients with primary breast cancer for detection of occult metastatic disease. EMBO Mol Med. 2015;7(8):1034-1047.4. Shaw JA et al. Genomic analysis of circulating cell-free DNA infers breast cancer dormancy. Genome Res. 2012;22(2):220-231.5. Dawson SJ et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med. 2013;368(13):1199-1209.6. Ma F et al. ctDNA dynamics: a novel indicator to track resistance in metastatic breast cancer treated with anti-HER2 therapy. Oncotarget. 2016;7(40):66020-66031.7. Abbosh C et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature. 2017;545(7655):446-451.8. Jamal-Hanjani M et al. Detection of ubiquitous and heterogeneous mutations in cell-free DNA from patients with early-stage non-small-cell lung cancer. Ann of Oncol. 2016;27(5):862-867.
Results
PPV, Positive Predicitive Value [True Positive/(True Positive+False Positive)]; NPV, Negative Predictive Value [True Negative/(False Negative+True Negative)]
Early Detection of Residual Breast Cancer through a Robust, Scalable and Personalized Analysis of Circulating Tumour DNA (ctDNA) Antedates Overt Metastatic RecurrenceRaoul C. Coombes1, Anne Armstrong2, Samreen Ahmed3, Karen Page4, Robert K. Hastings2, Raheleh Salari5, Himanshu Sethi5, Anna-Rita Boydell1, Svetlana V. Shchegrova5, Daniel Fernandez-Garcia4, Kelly LT Gleason1, Kate Goddard1, Dave S. Guttery4, Zoe J. Assaf5, Mustafa Balcioglu5, David A. Moore6, Lindsay Primrose4, Samantha L. Navarro5, Alexey Aleshin5, Farah Rehman1, Bradley J. Toghill 4, Maggie C. Louie 5, Cheng-Ho Jimmy Lin5, Bernhard G. Zimmermann5, Jacqueline A. Shaw4
1Imperial College London, United Kingdom; 2The Christie Foundation NHS Trust, United Kingdom; 3Leicester Royal Infirmary, United Kingdom; 4The University of Leicester, United Kingdom; 5Natera, San Carlos, CA, United States; 6University College London, United Kingdom.
This presentation is the intellectual property of the author/presenter. Contact Jacqueline Shaw at [email protected] for permission to reprint and distribute.
RESEARCH USE ONLY