Detection of circulating and disseminated neuroblastoma cells using the Imagestream
Flow Cytometer for use as predictive and pharmacodynamic biomarkers
Swathi Merugu1, Lindi Chen1, Elizabeth Gavens1,2, Hany Gabra2, Mark Brougham3, Guy
Makin4,5, Antony Ng6, Dermot Murphy7, Alem S. Gabriel1, Michael L. Robinson1, Jennifer H.
Wright1, Susan A. Burchill8, Angharad Humphreys9, Nick Bown9, David Jamieson10 and
Deborah A. Tweddle1,2*
1Wolfson Childhood Cancer Research Centre, Northern Institute for Cancer Research,
Newcastle University; 2Great North Children’s Hospital, Newcastle; 3Royal Hospital for Sick
Children, Edinburgh; 4Royal Manchester Children’s Hospital; 5Manchester Academic Health
Sciences Centre, University of Manchester; 6Royal Hospital for Sick Children, Bristol; 7Royal
Hospital for Sick Children, Glasgow, 8Leeds Institute of Medical Research, St James’s
University Hospital, Leeds, LS9 7TF, 9Northern Genetics Service, Newcastle upon Tyne
Hospitals NHS Trust, 10Northern Institute for Cancer Research, Newcastle University, U.K.
Running title: Circulating and disseminated tumour cells in neuroblastoma
Key words: Neuroblastoma (NB), Circulating tumour cell (CTC), Disseminated tumour cell
(DTC), Disialoganglioside (GD2), Imagestream Imaging flow cytometer (ISx).
Financial support
This work was funded by a Newcastle University Overseas Research Studentship Award (S.
Merugu), the Children’s Cancer & Leukaemia Group (CCLG) & Little Princess Trust
(CCLGA 2016 08)(S. Merugu, D. Tweddle, L. Chen, D. Jamieson), Children with Cancer
UK (S. Merugu), the Newcastle upon Tyne Hospitals NHS Charity (E. Gavens, D. Tweddle,
L. Chen), the DUBOIS Childhood Cancer Fund, SPARKS (11NCL05) (L. Chen, D.
Tweddle), Neuroblastoma UK & Niamh’s Next Step (L. Chen, D. Tweddle) the North of
England Children’s Cancer Research Fund (D. Tweddle), Santander Universities &
1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
1
Association of Physicians intercalated scholarship (J. Wright), Mrs Anna Upjohn (M.
Robinson), Cancer Research UK (CRUK-C9380/A25138) (D. Jamieson, E. Gavens), Action
Medical Research/Great Ormond Street Hospital Children’s Charity (GN2390)(A. Gabriel, D.
Tweddle) and the Sir Bobby Robson Foundation (for purchase of the Image Stream flow
cytometer). The authors acknowledge the support of the National Institute for Health
Research Clinical Research Network: Cancer (UKCRNID16957) and the Experimental
Cancer Medicines Centre (ECMC) Paediatric network (G. Makin, D. Murphy, A. Ng, D.
Tweddle).
*Corresponding author: Deborah A. Tweddle, Wolfson Childhood Cancer Research
Centre, Northern Institute for Cancer Research, Newcastle University, Level 6, Herschel
Building, Brewery Lane, Newcastle upon Tyne, NE1 7RU, U.K. Tel: +44 (0)191 208 2230,
Fax: +44 (0) 191 208 4301; Email: [email protected]
Conflict of Interest
The authors declare no potential conflicts of interest
Word Count = 5, 095
Total number of Figures & Tables: = 6
Statement of translational relevance
This the first study to show that circulating tumour cell (CTCs) and disseminated tumour
cells (DTCs) are detectable in neuroblastoma (NB) patient samples at diagnosis and relapse
using the Imagestream imaging flow cytometer. Increased p53 and p21 expression in
CTCs/DTCs following MDM2 antagonist treatment may be a useful pharmacodynamic
proof-of-mechanism biomarker for early phase clinical trials. Enumeration of CTCs at
diagnosis in high-risk NB patients with bone marrow infiltration should be further
2
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
2
investigated as a predictive biomarker of bone marrow response to first line induction
chemotherapy.
3
48
49
3
Abstract
Purpose: Circulating tumour cells (CTCs) serve as non-invasive tumour biomarkers in many
types of cancer. Our aim was to detect CTCs from patients with neuroblastoma for use as
predictive and pharmacodynamic biomarkers. Experimental Design: We collected matched
blood and bone marrow samples from 40 neuroblastoma patients to detect GD2+ve/ CD45-ve
neuroblastoma CTCs from blood and disseminated tumour cells (DTCs) from bone marrow
(BM) using the Imagestream Imaging flow cytometer (ISx). In 6 cases circulating free DNA
(cfDNA) extracted from plasma isolated from the CTC sample was analysed by high-density
single nucleotide polymorphism (SNP) arrays. Results: CTCs were detected in 26/42 blood
samples (1-264/ml) and DTCs in 25/35 BM samples (57-291544/ml). Higher numbers of
CTCs in newly diagnosed, high-risk neuroblastoma patients correlated with failure to obtain a
complete BM metastatic response after induction chemotherapy (p< 0.01). Ex-vivo Nutlin-3
(MDM2 inhibitor) treatment of blood and BM increased p53 and p21 expression in CTCs and
DTCs compared with DMSO controls. In 5/6 cases cfDNA analysed by SNP arrays revealed
copy number abnormalities associated with neuroblastoma. Conclusion: This is the first
study to show that CTCs and DTCs are detectable in NB using the ISx, with concurrently
extracted cfDNA used for copy number profiling, and may be useful as pharmacodynamic
biomarkers in early phase clinical trials. Further investigation is required to determine if CTC
numbers are predictive biomarkers of BM response to first line induction chemotherapy.
4
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
4
Introduction
Neuroblastoma (NB) is a heterogeneous tumour occurring in 10.2 per million children. It has
one of the lowest survival rates of all childhood cancers, with only 67 percent of patients
surviving to five years (1). Treatment of NB depends on the International Neuroblastoma
Risk Group (INRG) classification which is determined by patient age, stage and genetics
including MYCN gene amplification, classifying patients as low, intermediate or high-risk (2).
For high-risk patients defined in Europe as metastatic disease over 1 year of age or MYCN
amplified, intensive multimodality approaches are used including induction chemotherapy,
surgical resection of the primary tumour, consolidation with myeloablative therapy and
autologous stem cell rescue and local radiotherapy followed by immunotherapy and
differentiation therapy. Despite an improved initial response to treatment survival remains
poor (<50% at 5 years) due to eventual drug resistant relapse (3).
To better understand tumour evolution and drug resistance, it is important to consider intra-
tumoural heterogeneity (4), but performing multiple biopsies from different tumour areas is
not feasible in most patients. Studying circulating tumour cells (CTCs) from blood may
inform intra-tumour heterogeneity and tumour evolution (5,6), and such studies are gaining
importance in the clinic as their detection is a non-invasive procedure involving only the
collection of peripheral blood (7). However, as CTCs are very rare, present in around one in
106 leucocytes in prostate cancer patients (8), it is important to increase sensitivity in
detection assays by including an enrichment step.
Technologies recently developed for CTC analysis include microfluidic devices with
antibody-coated microspots (CTC chip), high-throughput microfluidic mixing devices
(Herringbone- Chip) (9), or ultrasound-based isolation in microfluidic devices (10). A
dielectrophoretic array method has been used to isolate disseminated tumour cells (DTCs)
5
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
5
from bone marrow (BM) from NB patients for tumour genetic analysis (11), and magnetic
bead-based enrichment has been developed to isolate DTCs from BM samples using anti-
GD2 and NCAM antibodies (12). The Amnis Image Stream Imaging flow Cytometer (ISx)
combines the features of classical flow cytometry, including an impartial analysis of a large
number of cells in a short period of time with essential features of fluorescence microscopy
allowing multiparameter cell analysis (13).
Detection of circulating free DNA and circulating tumour DNA (ctDNA) in plasma or serum
of cancer patient blood is another type of liquid biopsy with higher levels detected in patients
with metastatic disease (14). Recent studies have shown the feasibility of detecting ctDNA in
cell free DNA (cfDNA) extracted from plasma to determine genetic aberrations including in
NB (15-19).
In the present study, we detected CTCs and DTCs from NB patient blood and BM samples
identified by GD2 expression and the absence of CD45 expression using the ISx. We show
that higher numbers of CTCs in newly diagnosed patients with high-risk NB are associated
with a failure to achieve a complete BM metastatic response after first line induction therapy
and that CTCs and DTCs can be used as pharmacodynamic biomarkers of novel targeted
treatments e.g. MDM2 inhibitors in early phase clinical trials. To our knowledge this is the
first study to report use of the ISx to detect NB CTCs and DTCs in NB clinical samples.
6
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
6
Materials and Methods
Cell Culture
A panel of human NB cell lines, N-type (SHSY5Y (20-22), NGP (23), and NBLW-N
(24,25)) and S- type (SHEP, SKNAS & NBLW-S (20,21)) were used to develop a protocol
for detection of NB cells using the ISx. Cell lines were routinely maintained in RPMI
medium supplemented with 10% v/v Fetal Bovine Serum (FBS, Gibco) and 1% v/v
penicillin-streptomycin (Sigma) in 5% CO2 in air in a humidified incubator at 37oC, regularly
tested and found to be free from Mycoplasma using MycoAlert™ (Lonza, Basel,
Switzerland). Authentication of the NBLW cell line was performed as described previously
(26). NGP and SHSY5Y cell lines were authenticated using STR genotyping (New Gene
Limited, International Centre for Life, Newcastle, U.K). SKNAS, SHEP and SKNBE(2c)
(Be2C) cells were authenticated using cytogenetic analysis (27). All cell lines were used
within 6 passages or within a period of 6 months.
Detection of NB cells using the ISx
A GD2 antibody conjugated with PerCP Cy5.5 (Peridinin chlorophyll protein, BD
Pharmingen, UK, 563438, 14.G2a) and anti-neural cell adhesion molecule (NCAM)
conjugated with PE CF594 antibodies (BD Pharmingen, UK, 562328, B159) were used as
NB markers in different cell lines alongside DAPI (BD Pharmingen, UK, 564907) nuclear
staining. Imagestream data was analysed using IDEAS image stream analysis software using
methods described previously (28).
Patient samples and Clinical Study design
This study was undertaken in accordance with the ethical principles of the Declaration of
Helsinki. Following institutional review board approval (ethics reference number
14/NW/0154), local institutional approval and written informed consent from the patient or
7
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
7
carer, clinical samples (4-8ml blood and 1-3ml BM) were obtained from patients with newly
diagnosed or relapsed NB from 5 UK Paediatric Oncology Principal Treatment Centres
(Supplementary Fig. S1b-c). Samples were collected in Cell Save® (Veridex®, Menarine
diagnostics, UK) tubes, sent by post at room temperature within 72 h of collection, and
processed within 96 h of collection. In the clinical study 40 NB patients were recruited (32
high, 6 low and 2 intermediate risk), 24 were studied solely at diagnosis, 14 solely at relapse
and 2 at both diagnosis and relapse (Supplementary Fig. S1a & d). In total 42 blood samples
were studied for CTCs (1 fail) and 35 paired bone marrow samples. In 7 cases only a blood
sample was obtained (Supplementary Fig. S1c). International Neuroblastoma Risk Group
(INRG) and other clinical characteristics of patients are shown in Table 1 and Supplementary
Table T2. For ex-vivo Nutlin-3 treatment 4 blood and 2 bone marrow samples were collected
in EDTA tubes from 4 patients. Clinical information is correct up to 31/5/2018. All newly
diagnosed high-risk patients studied were treated on the European High Risk Neuroblastoma
trial (HR-NBL1) (29).
Analysis of patient samples using the ISx
Samples (blood and BM) were blocked to prevent non-specific antigen binding, red cell lysed
and enriched for non-haematopoietic cells using previously reported methods (30,31). Cells
were then permeabilised in perm-wash buffer (BD Pharmingen) and stained with
immunofluorescent antibodies including GD2-PerCp, NCAM-PE, and CD45- PE-Cy 7 (Bio
Legend, UK, 560915, H130) and nuclei stained with DAPI. Following incubation for 1h,
stained cells were washed, resuspended in PBS and processed on the ISx according to the
manufacturer’s protocol, and the presence of CTCs and DTCs detected using IDEAS
software (See Supplementary Methods- & Supplementary Fig. S2).
CTCs and DTCs were detected based on brightfield morphology, GD2 expression, a nuclear
signal and the absence of CD45 expression. Potential CTCs were gated in GD 2 and CD45
8
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
8
scatter plots and visually confirmed from immunofluorescence images, tagged and counted
manually. The numbers of DTCs were counted using IDEAS software as there were too
many to count manually. The diameter of CTCs and DTCs in NB patient blood and BM
samples was calculated as previously described (28). The mean diameter of CTCs/DTCs was
compared with the mean diameter of white blood cells (WBCs; n=5000). The number of
CTCs used to calculate diameter ranged from 4-100 and for DTCs from 4-2000. DNA ploidy
was determined in all blood and BM samples with ≥ 4 cells based on WBC DNA and
CTC/DTC DNA ratio from a DNA histogram using IDEAS software using the formula CTC
DNA Ploidy = Mean CTC DNA/ Mean WBC DNA. If the ratio of CTC DNA was >1.25 x
WBC DNA ploidy then it was considered hyperdiploid, if not diploid (32).
Collection of plasma from NB patient blood and BM samples
Plasma was separated from blood (n=3 cases) and BM (n=3 cases) samples in Cell Save tubes
by two sequential centrifugations (2,000 g, 10 min) and stored at -80°C in 1 ml aliquots.
cfDNA was isolated from aliquots of double spun plasma using the QIAamp DNA Blood
Maxi Kit (Qiagen). Following isolation the cfDNA yield was quantified using the Qubit®
Fluorometer (Thermo Fisher Scientific) as per the manufacturer’s instructions. cfDNA
fragment size was determined using 1% agarose gel electrophoresis.
Nutlin-3 treatment of NB cell lines and patient samples
Two NB cell lines, p53 wt (SHSY5Y) and p53 mutant (Be2C) (27), and blood and BM
samples were exposed to Nutlin-3 an MDM2 inhibitor, and upregulation of p53 and p21
detected by immunofluorescence using the ISx and compared with DMSO (dimethyl
sulfoxide) controls (Sigma-Aldrich, UK, D2650). Nutlin-3 (Selleckchem, UK) was dissolved
in DMSO to a stock concentration of 100µM. Cells were treated with 10µM Nutlin-3 or an
equal volume of DMSO for 24 h prior to fixation, followed by incubation with GD2 PerCp
(BD Pharmingen, UK), p53 Alexa Fluor-647 (Cell Signaling technologies, UK, 2533S, 1C12)
9
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
9
at 1:50, p21 Alexa Fluor-488 (Cell Signaling technologies, UK, 5487, 12D1) at 1:50) and
DAPI (BD Pharmingen, UK) and run on the ISx as described above. Cell cycle analysis was
performed using IDEAS software with round single in focussed cells gated on scatter plots.
Using the intensity of the DAPI histogram, mitotic cells and cells in G1, S & G2/M were gated
to observe the effect of Nutlin-3 treatment and DMSO in NB cell lines, healthy volunteer
blood samples and NB patient blood and BM samples. (See supplementary methods for more
details).
Cytogenetic analysis of NB tumours and cfDNA
Using single nucleotide polymorphism arrays (SNP) (n=11 cases), array comparative
genomic hybridisation (CGH) (n=21 cases) and multiplex ligation PCR dependent
amplification (MLPA) (n=6 cases), cytogenetic analysis was undertaken on primary tumours
or bone marrow metastases from all except 4 cases (Supplementary Table T2). For SNP
arrays DNA samples were hybridised to Infinium CytoSNP-850K v1.1 BeadChip (Illumina,
Inc) according to the manufacturer's instructions. Illumina IDAT files were analysed using
BlueFuse Multi software. Using targeted next generation sequencing (NGS) (26) p53 gene
mutational status was determined for the cases treated with Nutlin 3 (Supplementary Table
T3). Affymetrix Oncoscan arrays (OncoScan FFPE CNV) performed by Eurofins Genomics
(Ebersberg, Germany) were used for detecting copy number abnormalities from cfDNA from
plasma with CEL files analysed using Nexus (Biodiscovery) software.
Statistical analysis
Statistical tests were performed using Graph Pad Prism (version 6.04) and IDEAS® software
(Amnis-Imagestream Imaging Flow cytometer). The number of cases with BM involvement
and the presence or absence of CTCs and DTCs was assessed using a Fisher’s exact test. A
Mann Whitney U-test was used to calculate the relationship between numbers of CTCs and
DTCs with BM involvement and BM response to induction chemotherapy. To determine the
10
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
10
correlation between numbers of CTCs/DTCs detected by qRT-PCR for the NB mRNAs
tyrosine hydroxylase (TH) and PHOX2B) (33) a Spearman rank correlation test was used
(SPSS). All p values reported were two-tailed and considered significant if p≤0.05. Data is
presented as mean ± SEM.
11
212
213
214
215
216
11
Results
Detection of GD2 & NCAM expression in cell lines using the ISx
A panel of NB cell lines (n=6) comprising neuronal (N) and substrate-adherent (S) types were
used to determine expression of the NB cell surface markers (GD2 and NCAM) using the ISx.
N-type cell lines (NGP, SHSY5Y and NBLW-N) were found to express a higher percentage
of GD2 and NCAM +ve cells than S type cell lines (SHEP, NBLW-S, and SKNAS). NGP
cells were the most strongly positive N type cell line for GD2 and NCAM (Supplementary
Table T1).
Detection of CTCs and DTCs from NB samples using the ISx
CTCs and DTCs were detected from a scatter plot of cells that were GD2+ve/ CD45-ve with
an intact nucleus (Fig. 1a & e). Potential CTCs/DTCs were gated based on intensity scatter
plots of GD2 versus CD45 for one patient sample and the template saved as a standard and
used for all remaining clinical samples using IDEAS software. Dots in scatter plots were
linked to corresponding cell imagery and visualised to help define gating boundaries (Fig.1a-
f). Once a gate was defined, cell imagery of that population could be inspected and
CTCs/DTCs were visually confirmed based on a round single cell from the bright field image
(BF), with positive GD2 expression, negative CD45 expression and an intact DAPI stained
nucleus (Fig. 1a, b & c). Confirmed CTCs/DTCs were then tagged and saved for further
analysis of cell diameter and DNA ploidy.
CTCs were detected in 26/42 patient blood samples (mean=40/ml, range, 1-264/ml at
diagnosis; mean=6/ml, range, 1-39/ml at relapse, Fig. 1g). DTCs were detected in 25/35 BM
samples (mean=30,342/ml, range, 57-291, 635/ml at diagnosis; mean=2,124/ml, range, 112-
15,688/ml at relapse, Fig. 1h). Table 1 shows a summary of cases studied in relation to
12
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
12
clinical risk group and MYCN status with 32/40 (80%) cases high-risk and 26/40 (65%)
studied at diagnosis (Supplementary Fig S1a, d & e).
BM involvement with NB on either 1 or 2 aspirates and/or trephines as reported by a
consultant haematologist based on morphology was present in 24/41 cases (including 1 case
at diagnosis and relapse). In patients with reported BM involvement, CTCs were detected in
19/24 cases and DTCs in 20/21 cases (in 3 cases DTCs not studied)(Supplementary Fig S1e).
In patients without reported BM involvement CTCs were detected in 6/17 and DTCs in 5/17
cases (Table 1). The presence of CTCs or DTCs was associated with BM involvement
(p<0.01 for CTCs and p<0.0001 for DTCs, Fisher’s exact test). Similarly there was an
association between the number of CTCs and DTCs and BM involvement (p<0.0001 Mann
Whitney test, Fig. 1i & j). CTCs were detected in 2/42 cases in the absence of DTCs and BM
involvement (one low-risk and one high-risk), and in one case in the absence of DTCs and
the presence of BM involvement (Supplementary Fig 1e). In 3/35 cases DTCs were detected
in the absence of CTCs and presence of BM involvement, and in two cases in the absence of
CTCs and absence of BM involvement. There was no association between the numbers of
CTCs or DTCs and the presence of MYCN amplification in the primary tumour or other
metastatic site biopsied. CTC and DTC numbers from 16 and 21 patients respectively with
untreated high-risk NB treated on the SIOPEN HR-NBL-1 trial were compared with NB-
specific mRNA detected by qRT-PCR for TH and PHOX2B in blood and BM. There was a
weak correlation between CTC numbers and level of PHOX2B mRNA expression in BM
only (r =0.45, p< 0.05) (data not shown).
NCAM was expressed in only 3/11 GD2+ve/CD45-ve blood samples initially examined,
whereas in GD2+ve/CD45-ve cells from BM aspirates weak NCAM+ve DTCs were observed
in 9/11 samples. From these early observations, it appears that there are differences in NCAM
13
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
13
expression in NB cell lines compared with NB CTCs and DTCs. It has been reported that
polysialylated NCAM and non-polysialylated NCAM expression differ between in vitro and
in vivo conditions (34). Hence NCAM expression was not considered further to detect and
confirm CTCs/DTCs in this study.
Higher CTC numbers are associated with incomplete bone marrow response to
induction chemotherapy
To determine whether the number of CTCs or DTCs at diagnosis were associated with BM
response to chemotherapy in high-risk NB patients with BM involvement at diagnosis
(n=21), numbers of CTCs/DTCs were plotted against BM response after first line induction
therapy (COJEC or N7) (Fig. 1k & l). BM response after induction chemotherapy was
determined by the presence of neuroblastoma cell infiltration in either BM aspirate or
trephine biopsy according to the International Neuroblastoma Response Criteria Bone
Marrow Working Group classification (35). Absence of morphological evidence of NB on 2
aspirates and 2 trephines was considered a complete response (CR) i.e. BM in CR and a +ve
BM aspirate or trephine at 1 or more sites was considered an incomplete response i.e. BM not
in CR (35,36). Patients with higher numbers of CTCs at diagnosis were found to have an
incomplete BM response after first line induction therapy (Fig. 1k, p<0.01, Mann Whitney U
test). In contrast, there was no association between numbers of DTCs at diagnosis and BM
response to first line induction chemotherapy (Fig. 1l, p=0.38).
Detection of ploidy using the ISx
The DNA content of WBCs and CTCs/DTCs in the CD45 depleted blood cell population was
determined from a DNA histogram plotted using IDEAS software. On the DNA histogram of
CD45 depleted cells, visually confirmed CTCs/DTCs were overlaid to determine DNA
content of CTCs/DTCs, from which ploidy could be extrapolated (Fig. 2a & c). The ploidy 14
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
14
status determined in this way from 24/42 CTC samples and 25/35 DTC samples is shown in
Supplementary Table T2. For CTCs 19/24 samples were diploid and 5/24 hyperdiploid and
for DTCs 17/25 diploid and 8/25 hyperdiploid.
The DNA ploidy of CTCs in five cases determined using the ISx was compared with ploidy
from a corresponding primary tumour or BM aspirate determined using high density SNP
arrays. Case-No-15 CTCs were found to be diploid using the ISx (Fig. 2a) and the
corresponding primary tumour SNP array showed diploidy with multiple segmental
chromosomal abnormalities (SCA) without MYCN amplification (Fig. 2b). Case-No-33 CTCs
detected at 1st relapse were hyperdiploid using the ISx (Fig. 2c) and a SNP array performed
15 months later at further relapse on a BM aspirate showed near-triploidy (Fig. 2d). MYCN
and ALK amplification were detected in the SNP array profile from this case as well as 1p
and 6q loss as shown in Fig. 2d. MYCN and ALK amplification were the only SCAs detected
in the SNP array from a lymph node metastasis from the same patient at diagnosis when
diploidy was present. The concordance of ploidy results from 5/5 cases with primary tumour
or BM aspirate SNP arrays with CTC ploidy results from the same patients suggests that
measurement of ploidy status using the ISx is accurate and reliable (Supplementary Table
T2). In addition the ploidy from CTCs/DTCs of 3 cases determined using the ISx was
compared with the ploidy from SNP arrays performed on cfDNA collected at the same time
and found to be concordant (Supplementary Table T2). However, the low frequency of
hyperploidy indicates that ploidy could only be used to distinguish a diploid WBC from a
hyperploid CTC/DTC in a minority of cases.
Measurement of CTC/DTC diameter
Cell diameter was also investigated as an additional feature to differentiate CTCs/DTCs from
WBCs. The diameter of all CTCs and DTCs in samples with ≥4 CTCs/DTCs was measured
15
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
15
using IDEAS software in 21 and 25 samples respectively (Supplementary Fig S3a & b). A
significant difference was observed between the diameter of WBCs in blood or BM samples
versus CTCs or DTCs respectively (Wilcoxon signed rank test, p<0.0001, Supplementary Fig
S3g & h). However, after plotting the values for each patient the intra-patient variability
between CTC/DTC diameter and WBC diameter suggested cell size would not be a useful
parameter to isolate NB CTCs/DTCs from residual WBCs.
cfDNA copy number analysis using SNP arrays
cfDNA collected in Cell Save tubes (n=6 samples) was analysed by Oncoscan FFPE arrays
and copy number variations (CNV) successfully detected in 5/6 samples. In one case blood
and BM plasma were collected at the same time and the CNV found to be identifical in both
samples (Fig. 3a & b). In 3 cases MYCN amplification was detected by SNP arrays in cfDNA
(Fig 3c & d). In 2 cases the numbers of SCAs detected in the blood plasma at relapse
increased from diagnosis illustrating temporal heterogeneity (Fig. 3 c & d).
CTCs/DTCs can be used as PD biomarkers of MDM2 inhibitor activity
MDM2 inhibitors prevent binding of MDM2 to p53 so stabilising and activating p53 leading
to increased transcription of target genes including p21, which mediates a G1 cell cycle arrest.
p53 mutant Be2C cells and p53 wt SHSY5Y cells were treated with the MDM2 inhibitor
Nutlin-3 for 24h or DMSO control, immunostained with GD2, p53, p21, and DAPI and run on
the ISx. p53 and p21 expression was determined by the percentage of p53 and p21 positive
cells from intensity histograms of p53 and p21 (Fig. 4a and Supplementary Fig. S4a & b).
Mutant Be2C cells expressed a higher percentage of p53 positive cells at baseline compared
with SHSY5Y cells with no increase following Nutlin-3 treatment, whereas in SHSY5Y cells
there was a statistically significant increase in p53 expression following Nutlin -3 treatment
(Fig. 4a and Supplementary Fig. S4a & b and Fig. 5g). In p53 mutant Be2C cells there was
16
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
16
low baseline expression of p21 and no increase following Nutlin-3 treatment (Supplementary
Fig. S4b and Fig. 5h), resulting in a virtually unchanged cell cycle profile (Fig. 5f), whereas
in p53 wt SHSY5Y cells there was an almost 10 fold increase in p21 expression (Fig. 4a and
Supplementary Fig. S4a) resulting in a strong G1/S cell cycle arrest and increase in G1/S ratio
from 6.4 to 33 (Supplementary Fig. S4c and Fig. 5f).
In order to validate the panel of antibodies with GD2-PerCp, PE Cy7 CD45, p53-Alexa Fluor-
647, p21 Alexa Fluor-488 and DAPI and to compensate data with all fluorochromes, healthy
volunteer blood samples (n=3) were spiked with SHSY5Y cells or Be2c cells, treated with
Nutlin-3 for 24h or DMSO control and p53 and p21 expression measured. After 24h there
was increased expression of p53 and p21 in GD2+ve/CD45-ve SHSY5Y NB cells and
residual GD2-ve, CD45+ve WBC remaining after WBC depletion (Fig. 4b & Fig. 5g & h).
The fold increase in p21 in CD45+ve cells, although statistically significant, was not as great
as for SHSY5Y cells (Fig. 5h), resulting in an increased G1 population but unchanged G1/S
ratio after Nutlin-3 treatment (Fig. 5f). In contrast there was no change in p53, p21 or cell
cycle profile after Nutlin 3 treatment of spiked p53 mutant Be2c cells compared with DMSO
control cells (Fig 5f-h).
We next treated NB patient blood (n=4) and BM samples (n=2) with Nutlin-3 ex- vivo for 24
hr or DMSO control and measured p53 and p21 expression (Supplementary Table T3). In 4/6
samples GD2+ve cells were present but a BM and blood sample from a patient with low-risk
NB at diagnosis had no detectable GD2+ve /CD45-ve CTCs or DTCs. In the 4 Nutlin-3
treated samples (3 blood and 1 BM) with CTCs/DTCs present, increased p53 and p21
expression was seen in GD2+ve/CD45-ve CTCs and DTCs compared with DMSO control
(Fig. 4e & f, Fig. 5a, b, g & h). In Case-No-12 a high number of CTCs (n=264/ml) and
DTCs (n=6383/ml) were detected (Supp Table T3), and a histogram was generated for cell
17
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
17
cycle changes in DTCs and p53 and p21 expression in CTCs and DTCs, before and after
10µM Nutlin-3 treatment (Fig. 4e & f and Fig. 5a-b & e-h). It was not possible to generate
histograms from CTCs from the two blood samples taken at relapse due to low numbers of
CTCs (Supp Table T3). In CTCs and DTCs baseline nuclear and cytoplasmic p53 was
detectable with nuclear accumulation of p53 following Nutlin-3 treatment (Fig. 4e & f and
Fig. 5a & g). Consistent with p53 activation there was increased expression of p21 in CTCs
and DTCs following Nutlin-3 treatment (Fig. 4e & f, Fig. 5b and h), with a 12 fold increase in
p21 in DTCs (Fig. 5b). This led to an increase in the G1 population of Case-No-12 DTCs
(56% for DMSO treated and 70%-Nutlin-3 treated), but no reduction in S phase in DTCs
(Fig. 5e & f), so an unchanged G1/S ratio (9.8-DMSO and 9.2-Nutlin-3).
To determine the effect of Nutlin-3 on WBCs, 4 patient samples and 3 spiked healthy
volunteer blood samples were treated with Nutlin-3 or DMSO control and p53, p21 and cell
cycle arrest measured. Compared with NB cell lines, CTCs and DTCs there was very low
baseline expression of p53 in WBCs, but in all cases there was nuclear p53 accumulation
following Nutlin-3 treatment (Fig. 4c & d, Fig. 5c & g, Supplementary Fig. S4e), and
increased p21 expression compared with DMSO controls (Fig. 4c & d, Fig. 5d & h,
Supplementary Fig. S4f). This led to an increase in G1 population after Nutlin-3 treatment but
no change in G1/S phase ratio i.e., 9.1 after Nutlin-3 treatment compared to DMSO control
(8.7) in WBCs from Case-No-12 BM (Fig. 5f & Supplementary Fig. S4d).
18
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
18
Discussion
The aim of the present study was to detect NB CTCs from blood and DTCs from BM using
the high-resolution ISx to use as biomarkers in NB. Recently we reported CTC detection and
characterisation from patients with oesophageal, hepatocellular, thyroid and ovarian cancers
using the ISx (28,37). Various techniques have been used to detect CTCs such as DEPArray
and CTC-iChip. DEPArray has been previously used for NB cell lines and patient BM
samples (11) but the current study is, to our knowledge, the first to detect NB CTCs and
DTCs using the ISx. Previously we reported between 0-118 CTCs /ml in thyroid cancer and
0-20 CTCs/ml in hepatocellular carcinoma (28) using similar methods on the ISx. This
compares with 0-264 NB CTCs/ml and a mean of 12 CTCs/ml in the current study.
Seeger et al reported >104 NB cells per 105 nucleated cells in BM samples from 103/267
patients and >104 NB cells per 105 nucleated cells in 2/174 patient blood samples from high-
risk metastatic NB patients at diagnosis using anti-GD2 immunocytology. They concluded
that quantifying NB cells in BM and peripheral blood at diagnosis and during induction
therapy provides an important poor prognostic marker for patients with stage IV NB (38). In
our study higher number of CTCs were detected at diagnosis (1-264/ml) compared to relapse
(1-39/ml) due to clearance of CTCs from the blood by chemotherapy and likely earlier
detection of relapsed disease. It is not possible to compare the sensitivity of our method for
detection of CTCs with other published studies as CD45+ve cells were depleted prior to
analysis. In 5/17 cases where DTCs were detected without bone marrow involvement this
may have been due to sampling variation, the assessment of bone marrow on the basis of
morphology alone or NB cells passing through the bone marrow rather than homing there.
Although GD2 is expressed on > 90% of neuroblastoma bone marrow metastases at diagnosis
and relapse (39), it is possible that using this technique we are missing a small proportion of
19
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
19
tumour cells which do not express GD2. A future study should compare the sensitivity of the
ISx to detect DTCs with bone marrow examination using immunocytology and also compare
with NB specific mRNA expression by qRT-PCR. In untreated high-risk NB patients there
was a weak correlation between numbers of CTCs with the level of the NB- specific mRNA
PHOX2B detected by qRT-PCR in BM but only small numbers of patients were studied (n
=22).
Higher numbers of CTCs were detected in untreated patients with high-risk NB who did not
achieve a BM CR after first line induction therapy versus those who did, suggesting that CTC
enumeration may prove useful to guide the length of induction chemotherapy in patients with
high-risk NB in the future. However, this was not the case for DTCs, which could be due to
much higher numbers of DTCs which were not visually confirmed. These observations now
need to be extended to a larger, prospective study of high-risk NB. Due to our sample size of
40 patients including 16 relapse cases, it was not possible to evaluate the prognostic
significance of CTC/DTC numbers. DNA ploidy of tumour cells was not useful for
distinguishing CTCs from WBCs due to the presence of diploidy in the majority of NB CTCs
studied, but ploidy of CTCs/DTCs did reflect the ploidy status of the primary tumour.
We also evaluated the use of cfDNA for detection of circulating nucleic acids from blood and
BM plasma collected for CTC/DTC studies in Cell Save tubes. In NB the genomic profile of
the tumour is necessary for treatment stratification. Various methodologies have been
reported for detecting NB genomic profiles with SNP arrays now frequently used in national
reference laboratories (40). Chicard et al reported ctDNA copy number analysis using
Oncoscan arrays in 66/70 patients with copy number profiles obtained in 74% of patients
(19).
20
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
20
In 5/6 blood or bone marrow plasma samples collected at the same time as CTCs/DTCs,
CNA were detected in ctDNA using Oncoscan FFPE arrays. In one case the paired blood and
bone marrow plasma showed the same CNA confirming the usefulness of BM plasma for
detecting CNA in NB as previously reported (41), and in another case the CNA from plasma
cfDNA were identical to those in a concurrently biopsied metastatic disease site. cfDNA
extracted from blood and BM plasma isolated from samples collected in Cell Save tubes for
CTCs/DTCs could be used to detect metastatic NB tumour specific genomic alterations and
should be evaluated prospectively in future clinical trials.
We are developing MDM2 inhibitors as a novel therapy for NB (42-44) and MDM2
inhibitors are currently being evaluated in adult and paediatric early phase clinical trials
therefore we sought to establish if CTCs could be used as a circulating PD biomarker . The
optimum PD biomarker for MDM2 inhibitor activity is activation of the p53 pathway in
tumour cells detected by increased expression of a p53 induced gene. Macrophage Inhibitory
cytokine (MIC1) has been used as a surrogate marker in plasma samples (45), but elevation
of MIC1 levels are not specific for tumour cells highlighting the importance of developing
less invasive, but tumour specific pharmacodynamic proof-of-mechanism biomarkers. In the
current study detection of increased p53 and p21 expression in SHSY5Y cells following
Nutlin 3 treatment but not mutant p53 Be2C cells is consistent with our previous studies of
MDM2 inhibitors in these cell lines (46,47).
In healthy volunteer blood samples exposed to MDM2 inhibitors ex-vivo, blood spiking
studies with NB cells and then patient blood and BM samples, we demonstrated increased
p53 and p21 protein expression and an increase in G1 population in CTCs, DTCs and WBCs
after Nutlin-3 consistent with our previous studies testing p53 function in diagnostic NB
biopsies showing induction of the p53 pathway following ex-vivo irradiation (48). The
current study demonstrates proof-of-concept to use p21 as a sensitive and specific PD 21
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
21
biomarker of MDM2 inhibitor activity for CTCs and DTCs detected by the ISx, but its
usefulness for CTCs may be limited by small numbers of CTCs present in relapsed blood.
p21 expression and the G1 population also increased in WBC following Nutlin 3 highlighting
the importance of studying tumour cells rather than surrogate WBC to study proof-of-concept
PD biomarkers of MDM2 inhibitor activity.
In conclusion, this is the first study to demonstrate the clinical utility of NB CTCs detected
by the ISx as non-invasive PD biomarkers of novel therapies in early phase clinical trials. A
future, larger study is needed to investigate whether they are predictive biomarkers of
response and also to determine if they are potential prognostic biomarkers to further refine
risk stratification in high-risk NB.
22
452
453
454
455
456
457
458
459
460
461
462
22
Acknowledgements
We are very grateful to all patients and families for donating samples, to research nurses at all
study sites (Great North Children’s Hospital Newcastle (GNCH), Royal Manchester
Children’s Hospital, Royal Hospitals for Sick Children in Edinburgh, Glasgow and Bristol)
for collecting samples and to Geoff Bell (GNCH) for coordinating this national, multi-centre
study.
We are thankful to the following for providing cell lines Sue Cohn (NBLW), Barbara
Spengler (Be2C), Rogier Versteeg (NGP), Jean Bernard (SKNAS) and Penny Lovat
(SHSY5Y, SHEP). We are also grateful to Lina Hamadeh for statistical support and the
Newcastle University Flow Cytometry Core Facility.
23
463
464
465
466
467
468
469
470
471
472
473
23
References1. Berthold F, Spix C, Kaatsch P, Lampert F. Incidence, Survival, and Treatment of Localized and
Metastatic Neuroblastoma in Germany 1979–2015. Paediatric Drugs 2017;19(6):577-93 doi 10.1007/s40272-017-0251-3.
2. Monclair T, Brodeur GM, Ambros PF, Brisse HJ, Cecchetto G, Holmes K, et al. The International Neuroblastoma Risk Group (INRG) staging system: an INRG Task Force report. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2009;27(2):298-303 doi 10.1200/jco.2008.16.6876.
3. Pinto NR, Applebaum MA, Volchenboum SL, Matthay KK, London WB, Ambros PF, et al. Advances in Risk Classification and Treatment Strategies for Neuroblastoma. Journal of Clinical Oncology 2015;33(27):3008-17 doi 10.1200/JCO.2014.59.4648.
4. Swanton C. Intratumor heterogeneity: evolution through space and time. Cancer research 2012;72(19):4875-82.
5. Ding L, Ellis MJ, Li S, Larson DE, Chen K, Wallis JW, et al. Genome Remodeling in a Basal-like Breast Cancer Metastasis and Xenograft. Nature 2010;464(7291):999-1005 doi 10.1038/nature08989.
6. Yachida S. Distant Metastasis Occurs Late during the Genetic Evolution of Pancreatic Cancer. 2010;467(7319):1114-7 doi 10.1038/nature09515.
7. Mostert B, Sleijfer S, Foekens JA, Gratama JW. Circulating tumor cells (CTCs): detection methods and their clinical relevance in breast cancer. Cancer treatment reviews 2009;35(5):463-74.
8. Panteleakou Z, Lembessis P, Sourla A, Pissimissis N, Polyzos A, Deliveliotis C, et al. Detection of circulating tumor cells in prostate cancer patients: methodological pitfalls and clinical relevance. Molecular medicine 2009;15(3-4):101.
9. Yu M, Stott S, Toner M, Maheswaran S, Haber DA. Circulating tumor cells: approaches to isolation and characterization. The Journal of Cell Biology 2011;192(3):373-82 doi 10.1083/jcb.201010021.
10. Nagrath S, Sequist LV, Maheswaran S, Bell DW, Irimia D, Ulkus L, et al. Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature 2007;450(7173):1235-9.
11. Carpenter EL, Rader J, Ruden J, Rappaport EF, Hunter KN, Hallberg PL, et al. Dielectrophoretic capture and genetic analysis of single neuroblastoma tumor cells. Frontiers in oncology 2014;4:201.
12. Abbasi MR, Rifatbegovic F, Brunner C, Ladenstein R, Ambros IM, Ambros PF. Bone marrows from neuroblastoma patients: An excellent source for tumor genome analyses. Molecular Oncology 2015;9(3):545-54 doi 10.1016/j.molonc.2014.10.010.
13. Zuba-Surma EK, Ratajczak MZ. Analytical capabilities of the ImageStream cytometer. Methods in cell biology 2011;102:207-30 doi 10.1016/b978-0-12-374912-3.00008-0.
14. Gahan PB, Swaminathan R. Circulating nucleic acids in plasma and serum. Recent developments. Annals of the New York Academy of Sciences 2008;1137:1-6 doi 10.1196/annals.1448.050.
15. Combaret V, Audoynaud C, Iacono I, Favrot MC, Schell M, Bergeron C, et al. Circulating MYCN DNA as a tumor-specific marker in neuroblastoma patients. Cancer Res 2002;62(13):3646-8.
16. Huang SK, Hoon DS. Liquid biopsy utility for the surveillance of cutaneous malignant melanoma patients. Mol Oncol 2016;10(3):450-63 doi 10.1016/j.molonc.2015.12.008.
17. Jovelet C, Ileana E, Le Deley MC, Motte N, Rosellini S, Romero A, et al. Circulating Cell-Free Tumor DNA Analysis of 50 Genes by Next-Generation Sequencing in the Prospective
24
474475476477478479480481482483484485486487488489490491492493494495496497498499500501502503504505506507508509510511512513514515516517518519520521
24
MOSCATO Trial. Clinical cancer research : an official journal of the American Association for Cancer Research 2016;22(12):2960-8 doi 10.1158/1078-0432.ccr-15-2470.
18. Van Roy N, Van Der Linden M, Menten B, Dheedene A, Vandeputte C, Van Dorpe J , et al. Shallow Whole Genome Sequencing on Circulating Cell-Free DNA Allows Reliable Noninvasive Copy-Number Profiling in Neuroblastoma Patients. Clinical Cancer Research 2017;23(20):6305-14 doi 10.1158/1078-0432.ccr-17-0675.
19. Chicard M, Boyault S, Colmet Daage L, Richer W, Gentien D, Pierron G, et al. Genomic Copy Number Profiling Using Circulating Free Tumor DNA Highlights Heterogeneity in Neuroblastoma. Clinical cancer research : an official journal of the American Association for Cancer Research 2016;22(22):5564-73 doi 10.1158/1078-0432.ccr-16-0500.
20. Ross RA, Spengler BA, Biedler JL. Coordinate morphological and biochemical interconversion of human neuroblastoma cells. Journal of the National Cancer Institute 1983;71(4):741-7.
21. Biedler JL, Helson L, Spengler BA. Morphology and growth, tumorigenicity, and cytogenetics of human neuroblastoma cells in continuous culture. Cancer Res 1973;33(11):2643-52.
22. Biedler JL, Roffler-Tarlov S, Schachner M, Freedman LS. Multiple neurotransmitter synthesis by human neuroblastoma cell lines and clones. Cancer Res 1978;38(11 Pt 1):3751-7.
23. Brodeur GM, Goldstein MN. Histochemical demonstration of an increase in acetylcholinesterase in established lines of human and mouse neuroblastomas by nerve growth factor. Cytobios 1976;16(62):133-8.
24. Cohn SL, Herst CV, Maurer HS, Rosen ST. N-myc amplification in an infant with stage IVS neuroblastoma. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 1987;5(9):1441-4 doi 10.1200/jco.1987.5.9.1441.
25. Foley J, Cohn SL, Salwen HR, Chagnovich D, Cowan J, Mason KL , et al. Differential Expression of N-<em>myc</em> in Phenotypically Distinct Subclones of a Human Neuroblastoma Cell Line. Cancer Research 1991;51(23 Part 1):6338-45.
26. Chen L, Humphreys A, Turnbull L, Bellini A, Schleiermacher G, Salwen H , et al. Identification of different ALK mutations in a pair of neuroblastoma cell lines established at diagnosis and relapse. Oncotarget 2016;7(52):87301-11 doi 10.18632/oncotarget.13541.
27. Chen L, Iraci N, Gherardi S, Gamble LD, Wood KM, Perini G, et al. p53 is a Direct Transcriptional Target of MYCN in Neuroblastoma. Cancer research 2010;70(4):1377-88 doi 10.1158/0008-5472.CAN-09-2598.
28. Dent BM, Ogle LF, O'Donnell RL, Hayes N, Malik U, Curtin NJ, et al. High-resolution imaging for the detection and characterisation of circulating tumour cells from patients with oesophageal, hepatocellular, thyroid and ovarian cancers. International journal of cancer 2016;138(1):206-16 doi 10.1002/ijc.29680.
29. June 11, 2018 october 11. High Risk Neuroblastoma Study 1.8 of SIOP-Europe (SIOPEN). In ClinicalTrialsgov Identifier: NCT01704716. <https://clinicaltrials.gov/ct2/show/NCT01704716>. Accessed 2012 october 11.
30. Yang L, Lang JC, Balasubramanian P, Jatana KR, Schuller D, Agrawal A , et al. Optimization of an enrichment process for circulating tumor cells from the blood of head and neck cancer patients through depletion of normal cells. Biotechnology and Bioengineering 2009;102(2):521-34 doi 10.1002/bit.22066.
31. Liu Z, Fusi A, Klopocki E, Schmittel A, Tinhofer I, Nonnenmacher A, et al. Negative enrichment by immunomagnetic nanobeads for unbiased characterization of circulating tumor cells from peripheral blood of cancer patients. Journal of Translational Medicine 2011;9(1):70 doi 10.1186/1479-5876-9-70.
32. Ambros IM, Zellner A, Roald B, Amann G, Ladenstein R, Printz D, et al. Role of Ploidy, Chromosome 1p, and Schwann Cells in the Maturation of Neuroblastoma. New England Journal of Medicine 1996;334(23):1505-11 doi 10.1056/nejm199606063342304.
25
522523524525526527528529530531532533534535536537538539540541542543544545546547548549550551552553554555556557558559560561562563564565566567568569570
25
33. Viprey VF, Gregory WM, Corrias MV, Tchirkov A, Swerts K, Vicha A, et al. Neuroblastoma mRNAs predict outcome in children with stage 4 neuroblastoma: a European HR-NBL1/SIOPEN study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2014;32(10):1074-83 doi 10.1200/JCO.2013.53.3604.
34. Korja M, Jokilammi A, Salmi TT, Kalimo H, Pelliniemi T-T, Isola J, et al. Absence of polysialylated NCAM is an unfavorable prognostic phenotype for advanced stage neuroblastoma. BMC cancer 2009;9(1):57.
35. Burchill SA, Beiske K, Shimada H, Ambros PF, Seeger R, Tytgat GA, et al. Recommendations for the standardization of bone marrow disease assessment and reporting in children with neuroblastoma on behalf of the International Neuroblastoma Response Criteria Bone Marrow Working Group. Cancer 2017;123(7):1095-105 doi 10.1002/cncr.30380.
36. Ladenstein R, Potschger U, Pearson ADJ, Brock P, Luksch R, Castel V , et al. Busulfan and melphalan versus carboplatin, etoposide, and melphalan as high-dose chemotherapy for high-risk neuroblastoma (HR-NBL1/SIOPEN): an international, randomised, multi-arm, open-label, phase 3 trial. The Lancet Oncology 2017;18(4):500-14 doi 10.1016/s1470-2045(17)30070-0.
37. Ogle LF, Orr JG, Willoughby CE, Hutton C, McPherson S, Plummer R , et al. Imagestream detection and characterisation of circulating tumour cells – A liquid biopsy for hepatocellular carcinoma? Journal of Hepatology 2016;65(2):305-13 doi https://doi.org/10.1016/j.jhep.2016.04.014.
38. Seeger RC, Reynolds CP, Gallego R, Stram DO, Gerbing RB, Matthay KK. Quantitative tumor cell content of bone marrow and blood as a predictor of outcome in stage IV neuroblastoma: a Children's Cancer Group Study. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2000;18(24):4067-76 doi 10.1200/jco.2000.18.24.4067.
39. Schumacher-Kuckelkorn R, Volland R, Gradehandt A, Hero B, Simon T, Berthold F. Lack of immunocytological GD2 expression on neuroblastoma cells in bone marrow at diagnosis, during treatment, and at recurrence. Pediatr Blood Cancer 2017;64(1):46-56 doi 10.1002/pbc.26184.
40. Ambros IM, Brunner C, Abbasi R, Frech C, Ambros PF. Ultra-High Density SNParray in Neuroblastoma Molecular Diagnostics. Frontiers in oncology 2014;4:202- doi 10.3389/fonc.2014.00202.
41. Abbasi MR, Rifatbegovic F, Brunner C, Ladenstein R, Ambros IM, Ambros PF. Bone marrows from neuroblastoma patients: an excellent source for tumor genome analyses. Mol Oncol 2015;9(3):545-54 doi 10.1016/j.molonc.2014.10.010.
42. Chen L, Zhao Y, Halliday GC, Berry P, Rousseau RF, Middleton SA , et al. Structurally diverse MDM2-p53 antagonists act as modulators of MDR-1 function in neuroblastoma. Br J Cancer 2014;111(4):716-25 doi 10.1038/bjc.2014.325.
43. Chen L, Rousseau RF, Middleton SA, Nichols GL, Newell DR, Lunec J , et al. Pre-clinical evaluation of the MDM2-p53 antagonist RG7388 alone and in combination with chemotherapy in neuroblastoma. Oncotarget 2015;6(12):10207-21.
44. Chen L, Pastorino F, Berry P, Bonner J, Kirk C, Wood KM, et al. Preclinical evaluation of the first intravenous small molecule MDM2 antagonist alone and in combination with temozolomide in neuroblastoma. International journal of cancer 2019;144(12):3146-59 doi 10.1002/ijc.32058.
45. Ray-Coquard I, Blay J-Y, Italiano A, Le Cesne A, Penel N, Zhi J , et al. Effect of the MDM2 antagonist RG7112 on the P53 pathway in patients with MDM2-amplified, well-differentiated or dedifferentiated liposarcoma: an exploratory proof-of-mechanism study. The lancet oncology 2012;13(11):1133-40.
46. Chen L, Malcolm AJ, Wood KM, Cole M, Variend S, Cullinane C, et al. p53 is Nuclear and Functional in Both Undifferentiated and Differentiated Neuroblastoma. Cell Cycle
26
571572573574575576577578579580581582583584585586587588589590591592593594595596597598599600601602603604605606607608609610611612613614615616617618619620
26
2007;6(21):2685-96 doi 10.4161/cc.6.21.4853.47. Chen L, Zhao Y, C Halliday G, Berry P, Rousseau R, Middleton SA, et al. Structurally diverse
MDM2–p53 antagonists act as modulators of MDR-1 function in neuroblastoma. 2014.48. Tweddle DA, Malcolm AJ, Cole M, Pearson AD, Lunec J. p53 cellular localization and function
in neuroblastoma: evidence for defective G(1) arrest despite WAF1 induction in MYCN-amplified cells. The American journal of pathology 2001;158(6):2067-77.
27
621622623624625626
627
27
Table 1: Summary of patients in study according to risk group, MYCN status and bone marrow involvement (n=42)a
N =42 a
TotalNumber of patients at Diagnosis
n= 26
Number of patients at Relapse
n=16
Number of patients with CTCsd Number of patients with DTCse
Diagnosisn= 20
Relapsen= 6
Diagnosisn= 20
Relapsen= 5
Risk GroupN= 42
Low n=6
3 3 1 0 0 1
Intermediaten=2
0 2 0 0 0 0
Highn=34
23 11 19 6 20 4
MYCN statusN= 42b
MNAn=16
8 8 8 5 7 4
Non-MNAn=25
17 8 12 1 13 1
BM involvedN= 42c
Yesn=24
21 3 17 2 18 2
Non=17
5 12 3 3 2 3
a2 patients studied at diagnosis and relapse, b1 case MYCN not studied, c1 case BM not examined at relapse, d42 samples studied for CTCs (1 fail), e35 samples studied for DTCs. MNA = MYCN amplified
28
628
28
Figure 1: CTCs and bone marrow response. a Scatter plot of Intensity_MC GD2 against
Intensity_MC CD45 of patient blood sample (Case-No-22) generated using IDEAS software.
Potential CTCs were gated by visual inspection of images. b Immunofluorescence image of a
CTC (GD2+ve/CD45-ve cell) with an intact nucleus (DAPI) by analysis of a single dot (cell)
from the GD2 +ve region of the scatter plot. c Immunofluorescence image showing three cells
in a single image: a CTC (GD2+ve/CD45-ve) and WBCs in doublets (CD45+ve/GD2-ve) to
show compensation of fluorochromes. d Immunofluorescence image of a CD45 +ve region
showing a CD45+ve/GD2-ve WBC. e Scatter plot of Intensity_MC GD2 against Intensity_MC
CD45 of BM sample (Case-No-22) showing DTCs. BM cells in higher intensity GD2 gated
regions were GD2+ve/CD45-ve DTCs and the scatter plot shows very few CD45+ve cells
towards the X-axis, compared with the paired blood sample which had more CD45+ve cells. f
Immunofluorescence image showing a GD2+ve/CD45-ve DTC. g-h Scatter plots showing
numbers of CTCs in 41 patient blood samples (2 cases at both diagnosis and relapse, 1 fail)
and numbers of DTCs in 35 patient BM samples. In 26 cases ≥1 CTC was detected and in 25
cases ≥1 DTC was detected. Horizontal line represents median with range. The mean number
of CTCs and DTCs detected was 12 and 5431 per ml of blood and BM respectively. i Scatter
plot showing the association between numbers of CTCs in 41 blood samples in relation to
BM involvement (P<0.0001- Mann-Whitney-test). j Scatter plot showing the association
between numbers of DTCs in 35 BM samples and BM involvement (P<0.0001- Mann-
Whitney-test). k Scatter plot showing the number of CTCs/ml blood in 19 newly diagnosed
high-risk NB patients with BM involvement at diagnosis comparing those who achieved a
BM complete response (CR) after first line induction therapy versus patients whose BM was
not in CR. l Scatter plot showing the number of DTCs/ml in BM aspirates from 18 patients
with BM involvement who achieved a CR v those who did not after first line induction
29
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
29
therapy (mean ± SD), BM +ve = BM involvement, BM –ve = Bone marrow not involved,
Horizontal lines = median with range.
Figure 2: Ploidy determination from CTCs in NB blood samples. a DNA histogram showing
the DNA content of residual WBCs and CTCs from a blood sample (Case-No-15) following
WBC depletion. The histogram shows an overlay of the DNA content of CTCs (red peak) and
WBCs (black peak) to determine the ploidy status of CTCs. The gatings were DNA 1 (single
CTCs/WBCs) and DNA 2 (CTC/WBC doublets), but for ploidy determination, only single
CTC gatings were used and compared with a WBC DNA ratio of 1. From the histogram,
Case-No-15 was considered diploid as CTC DNA was < 1.25× WBC DNA ploidy. bi SNP
array log R ratio track of Case-No-15 primary tumour at diagnosis showing a diploid tumour
and multiple segmental chromosomal abnormalities (SCA) (2p, 4q with hyper-rearrangement,
6p, 9p, 11q, 12pq, 17q gain and 1p, 3p, 4p, 11q loss). bii B allele frequency c DNA histogram
from Case-No-33 blood sample at first relapse with DNA ploidy of CTCs determined from
WBC DNA ratio found to be hyperdiploid with CTC DNA >1.25× WBC DNA ploidy. di
Log R ratio track of Case-No-33 BM aspirate at further relapse showing near-triploidy
(whole chromosomal abnormalities-chr7,chr12, chr18, chr20, chr22 gain and chr9, chr10,
chr11, chr14, chr16, chr19 loss, and SCA-loss of 1p and 6q). dii B allele frequency. The
profile also shows amplification of MYCN and ALK on chromosome 2p which were also
present in the primary tumour at diagnosis when the tumour was diploid. Yellow straight line
on the SNP log R ratio indicates 0, normal diploid copy number and the green data points
indicate the log R ratio of all individual SNPs. An increased or decreased log R ratio
indicates gained and deleted regions of chromosomes respectively.
Figure 3: a & b Comparison of copy number profiles from corresponding cfDNA from blood
and BM (Case-No-23). ai ) SNP array log R ratio track and (aii) B allele frequency plot log R
30
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
30
ratio from Oncoscan FFPE array of cfDNA from blood and (bi) and (bii) from BM showing
the SCAs including +2p,-3q, +6p, -6q, -9p, +11p, -11q, -17p, + 17q and WCAs such as -5,
+7, -10, -19, +18 which are identical in cfDNA from both sites. The primary tumour was not
biopsied in this case at diagnosis so unavailable for comparison c & d Comparison of copy
number profiles from Case 11-diagnostic primary tumour and Case 11-R cfDNA from blood
at relapse ci & di) SNP array log R ratio track and (cii & d ii) B allele frequency plot log R
ratio c) Illumina array showing ALK and MYCN amplification together with -1p, -10q +11q
and +17q. d) Oncoscan array of Case 11-R cfDNA showing ALK and MYCN amplification -
1p and +17q and additional gains and losses including +1q, -5p, -18p, +18q. Interestingly 10q
loss and 11q gain were not detected in Case 11-R cfDNA.
Figure 4: The effect of Nutlin-3 treatment on p53 wt SHSY5Y cells, SHSY5Y cells spiked
into healthy volunteer blood, CD45+ve WBCs (blood and BM), CTCs and DTCs (Case-No-
12). ISx immunofluorescence images of (a & b) p53 wt SHSY5Y neuroblastoma cells and
spiked cells following treatment with DMSO or 10µM Nutlin-3 for 24h showing increased
p53 and p21 expression following Nutlin-3 treatment. (c & d) Case-No-12 Blood and BM
WBCs (CD45+ve/GD2-ve) showing increased nuclear p53 and p21 expression in Nutlin-3
treated cells compared with controls. (e & f) Case-No-12 CTCs and DTCs showing increased
nuclear p53 and p21 expression following Nutlin-3 treatment compared with DMSO control.
Figure 5: The effect of Nutlin-3 on p53 and p21 expression and the cell cycle in DTCs &
BM CD45+ve cells from Case No-12. a & c Histograms showing increased p53 expression in
DTCs and BM CD45+ve cells when treated with 10µM Nutlin-3 for 24 h compared with
DMSO. b & d Histograms showing increased p21 expression after Nutlin-3 treatment
compared with DMSO controls in DTCs and BM CD45+ve cells. e Histograms showing cell
cycle analysis of DTCs after Nutlin-3 treatment showing an increased G1 population. f Bar
31
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
31
chart showing cell cycle analysis of Be2C cells (p53 mutant), spiked (SPIK) Be2C cells,
SHSY5Y cells, spiked SHSY5Y cells (SPIK), WBC from healthy volunteer blood samples
(HV) (n=3), WBCs from Case-No-12 blood and BM samples, and DTCs from Case-No-12
following Nutlin-3 treatment, showing a G1 arrest in SHSY5Y cells and spiked SHSY5Y
cells and a partial G1 arrest compared with DMSO controls in all other samples except mutant
Be2C cells and spiked mutant Be2C cells. g and h Bar charts showing the percentage of cells
expressing p53 and p21 in Be2C cells (n=3), spiked Be2C cells (n=3), SHSY5Y cells (n=3),
spiked SHSY5Y cells (n=3), HV WBC (n=3), Case-No-12 blood and BM WBC and DTCc
(n=3 for Case-No-12; error bars represent analysed data from three different files using
IDEAS software) following Nutlin-3 treatment compared with DMSO controls. In SHSY5Y
cells, spiked SHSY5Y cells, HV WBCs, Case-No-12 blood and BM WBCs and DTCs
increased p53 and p21 expression was observed following Nutlin-3 compared with DMSO
controls, but not in p53 mutant Be2C cells and spiked mutant Be2C cells. For SHSY5Y cells,
spiked SHSY5Y cells, Be2C cells, spiked Be2C cells, healthy volunteer WBC (n=3), Case-
No-12 CD45+ve, blood and BM cells and DTCs, a minimum of = 1000 cells were analysed.
Paired t test, p<0.05*, p<0.01** and p<0.001***).
32
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
32