Early changes in circulating tumor cells are …...2015/07/17 · CTCs associated with response and...

CTCs associated with response and survival in NENs

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Early changes in circulating tumor cells are associated with response and

survival following treatment of metastatic neuroendocrine neoplasms

Mohid S Khan1, 2, 3, Amy A Kirkwood 4, Theodora Tsigani1, Helen Lowe1,

Robert Goldstein1, John A Hartley1, Martyn E Caplin2, Tim Meyer1,5

1 UCL Cancer Institute, London 2 Neuroendocrine Tumour Unit, Department of Gastroenterology, Royal Free

Hospital, London 3 Department of Gastroenterology, University Hospital of Wales, Cardiff &

Vale University Hospital Board, Cardiff 4 Cancer Research UK & UCL Cancer Trials Centre, London 5 Department of Oncology, Royal Free Hospital, London

Running title: CTCs associated with response and survival in NENs

Keywords: neuroendocrine tumors, circulating neoplastic cells, circulating

tumor cells, biological markers, prognosis

Funding: The work was funded by UCL Experimental Cancer Medicine Centre

grant C34/A7279, the IPSEN fund Clinical Research Fellowship (MK), Quiet

Cancer Appeal, and the NIHR UCLH Biomedical Research Centre.

No conflicts of interest declared.

Address for correspondence:

Prof Tim Meyer UCL Cancer Institute University College London 72 Huntley Street, London WC1E 6BT email; [email protected] Tel; 0207 679 6731, Fax; 0203 108 2025

The results have been presented in part at the Annual General Meeting of the

American Society of Clinical Oncology 1-5 June 2012 Chicago IL and the 8th Annual ENETS Conference, 9-11 March 2011, in Lisbon, Portugal

Word count 2826/5000; 6 figures and tables

Research. on June 30, 2020. © 2015 American Association for Cancerclincancerres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on July 21, 2015; DOI: 10.1158/1078-0432.CCR-15-1008

http://clincancerres.aacrjournals.org/


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Statement of Translational Relevance There are an increasing range of therapeutic options available for patients

with neuroendocrine neoplasms (NEN) but no validated predictive biomarkers

to direct treatment selection or sequence. Having previously demonstrated the

prognostic relevance of circulating tumor cells (CTCs) in NENs, we have

evaluated their role as predictive biomarkers in response to therapy. We show

a poor outcome group can be defined by the presence of >8 CTCs at 3-5

weeks post-therapy, or by a <50% fall or a rise in CTC number at the same

time point compared to baseline. The association of change in CTC number

is an independent prognostic variable and allows serial monitoring of

response to therapy. These findings will require further external validation but

may present the opportunity for adaptive trials in NENs, in which evidence

based sequencing strategies can be defined.





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Abstract

Purpose: To investigate post-treatment circulating tumor cell counts in

patients with neuroendocrine neoplasms (NEN) as a predictive biomarker for

disease progression and overall survival.

Experimental Design: Patients with metastatic NENs commencing therapy

were prospectively recruited (n=138). Blood samples were obtained for

evaluation of circulating tumor cells (CTCs) using the CellSearch™ platform

and for chromogranin A (CgA) at baseline, 3-5 (median 4.3) weeks and 10-15

(median 13.7) weeks after commencing therapy. Radiological response and

overall survival (OS) data were collected.

Results: There was a significant association between first post-treatment CTC

count and progressive disease (PD) (P<0.001). Only 8% of patients with a

favorable ‘CTC response’ (0 CTCs at baseline and 0 at first post-treatment

time-point; or ≥50% reduction from baseline) had PD compared with 60% in

the unfavorable group (<50% reduction or increase). Changes in CTCs were

strongly associated with OS (P<0.001), the best prognostic group being

patients with 0 CTCs before and after therapy; followed by those with ≥50%

reduction in CTCs (Hazard Ratio HR 3.31); with those with a <50% reduction

or increase in CTCs (HR 5.07) having the worst outcome. In multivariate

analysis, changes in CTCs had the strongest association with OS (HR 4.13,

P=0.0002). Changes in CgA were not significantly associated with survival.

Conclusion: Changes in CTCs are associated with response to treatment and

overall survival in metastatic NENs suggesting CTCs may be useful as

surrogate markers to direct clinical decision-making.





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Introduction Neuroendocrine neoplasms (NENs) are heterogeneous with respect to clinical

behavior, prognosis and response to therapy.[1] Additionally, for metastatic

disease, there are an increasing number of therapeutic options available

including somatostatin analogues[2 3], chemotherapy[4], sunitinib[5],

everolimus[6], peptide receptor radionuclide therapy and loco-regional therapy.

Whilst guidelines have been developed to direct clinical management[7-9],

there is a clear need for more evidence to support clinical decision making

and, in the absence of robust predictive or response biomarkers, treatment

selection and sequencing represents a significant challenge. The need for

validated surrogate biomarkers for survival is particularly pressing in this

tumor group since survival is often very prolonged. In recent trials objective

response rates have been low and benefits in progression free survival (PFS)

have not translated into clear increases in overall survival[2 3 5 6].

The most widely used circulating biomarker, chromogranin A (CgA), has not

been convincingly validated as a surrogate biomarker for overall survival in

response to therapy. Changes in serum CgA and neurone-specific enolase

(NSE) have been found to correlate with PFS and radiological response in the

RADIANT-1 prospective clinical trial evaluating everolimus in pancreatic

NENs.[10] However, these were subgroup analyses and were not confirmed in

the PROMID study where changes in CgA did not reflect response or time-to-

progression with Octreotide LAR.[2]

In other tumor types, circulating tumor cells (CTCs) have been shown to

predict clinical outcome at an early time point following treatment. Using the

CellSearch™ platform, prospective studies in patients with metastatic breast,





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colon, prostate and lung cancer have demonstrated that the persistence of

CTC levels above a predefined prognostic threshold was associated with an

adverse outcome[11-16]. We have previously demonstrated that CTCs are

detectable in the blood of patients with metastatic NEN and that their

presence is of prognostic significance in terms of disease progression and

overall survival (OS)[17 18]. However, the relevance of post-treatment CTC

levels has not been evaluated in NEN and our aim in this study was to explore

the relationship between CTC response to treatment and clinical outcomes

including overall survival.

Materials and Methods

This was a single-institution study conducted at the Royal Free Hospital,

London, United Kingdom and was approved by the local ethics committee

(East London & The City REC Alpha 09/H0704/44). Eligible participants were

≥18 years old with metastatic disease, had histologically proven NEN and

were scheduled to embark on a new NEN-specific therapy. Patients were

required to have measurable disease according to RECIST 1·1.[19] Patients

who had undergone systemic anticancer therapy or embolization within the

previous four months were excluded since recent treatment has been shown

to affect CTC count in other tumors.[14 20] Patients receiving concomitant long-

term somatostatin analogues were permitted. All patients provided written

informed consent prior to entering the study.

All patients had blood samples taken at baseline (within four weeks prior to

commencing treatment) for CTC enumeration and plasma CgA. Further





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samples were taken at 3-5 weeks (first post-treatment sample: PT1) and at

10-15 weeks (second post-treatment sample: PT2) after commencing

treatment. CTC enumeration was performed at the UCL ECMC GCLP Facility

(UCL Cancer Institute) using the FDA approved CellSearch™ system

(Janssen Diagnostics) as described previously.[21] Blood samples were

collected in 10-mL CellSave tubes, maintained at room temperature and

analyzed within 96 hours according to manufacturer instructions. All

evaluations were performed without knowledge of the clinical status of the

patients by two independent operators (M.S.K., T.T. or H.L.). Technical details

of the CellSearch™ platform including accuracy, precision, and reproducibility,

have been described elsewhere.[21] Previously, using a training and validation

dataset in NEN patients, we have validated a prognostic cutoff of one with

respect to the number of CTCs detected.[18]

Data were collected on primary site, previous treatments, Eastern

Cooperative Oncology Group performance status, and grade of tumor based

on Ki-67 proliferation index according to European Neuroendocrine Tumour

Society (ENETS) Guidelines.[7 8] Baseline assessments included hepatic

tumor burden from four to six slices of a computed tomography/magnetic

resonance imaging scan, selected at the level of greatest disease, and

categorized as: ≤25%; 25 to ≤50%; 50% to ≤75%; or ≥75%; based on the

relative area of tumor to normal liver. CgA was evaluated on plasma samples

at baseline and 3-5 weeks after commencement of treatment using an in-

house standardized laboratory assay.





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Analysis was performed using SPSS for Windows (SPSS, Chicago, IL), Stata

version 12.1 (StataCorp, Texas) and GraphPad Prism (GraphPad Software,

San Diego, CA), where P values <0·05 were considered significant. Since

CgA was not normally distributed (even when transformed onto a logarithmic

scale), this was analyzed in two groups: > and ≤ 2X the upper limit of normal

(ULN; 120 pmol/L), consistent with previous studies.[10] Due to small numbers

in subgroups, burden groups 25≤50%, 50≤75% and >75% were combined for

multivariate analysis. Similarly, performance status groups 2, 3, and 4 were

combined. Age was analyzed as a continuous variable, and hazard ratios

(HRs) are presented for an increase in 10-years.

Response to treatment was assessed by RECIST 1.1 by an independent

radiologist blind to study on a post-treatment scan (CT or MRI) at intervals of

between 3-6 months after therapy (see online Table S1). Association between

changes in CTCs or CgA and radiological response were analyzed by χ2 (or

Fisher’s) test. OS was estimated using Kaplan-Meier methods from

commencement of treatment to date of death resulting from NEN, or to date of

last follow-up. Information regarding death was sought by the investigators.

Survival curves were compared using log-rank testing. Cox proportional

hazards regression analysis was used to obtain univariate hazard ratios [22] for

OS. The associations between baseline and post-treatment CTCs and OS

were evaluated by different analytical methods: presence and absence of

CTCs as described previously[23], and changes in CTCs. Factors found to be

significant on univariate analysis were included in multivariate analysis in

addition to age.





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Results

One-hundred and thirty-eight patients with metastatic NEN were recruited

between August 2009 and August 2011. Baseline characteristics are shown in

Table 1 and treatments were prescribed as clinically indicated. The most

commonly used treatments were somatostatin analogues (SST) (34),

chemotherapy (29), PRRT (40) and TAE (18) (see online Table S1). All

patients had liver metastases and mid-gut NENs represented the largest

subgroup (59%). The majority (81%) had grade 1 or 2 tumors and 97% had a

performance status of <2. Overall, 51% had received previous anti-cancer

therapy and 41% were receiving long-term SST. Patients had been diagnosed

a median of 26 months (range 1 to 149 months) before recruitment. The

median follow-up was 33 months (range, 1 to 58 months) and 70 (51%)

patients had met the survival endpoint of death at the time of analysis.

Baseline blood samples were taken for CTC analysis in all cases, and 60% of

patients had at least one CTC detected. PT1 samples were taken in 118

patients (86%) at the first time-point (3-5 weeks after commencing treatment,

median 4.3 weeks), and in 92 patients (67%) at the PT2 time-point (10-15

weeks, median 13.7 weeks). Reasons for missing post-treatment samples

included death or inability to return to hospital at the appropriate time-point.

Association between CTCs with radiological response

Initially, we investigated the ability of PT1 CTC counts to predict radiological

response to therapy, evaluated in 112 cases. Cases were divided into tertiles





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based on CTC count (0, 1-8, >8). There was a significant association between

the PT1 CTC count and PD (Table 2). Only 4% of those with no CTCs at PT1

progressed as compared with 65% of those with CTC count >8. In addition,

we examined the association of dynamic changes in CTC with response by

comparing the PT1 CTC count with the baseline count. Patients were divided

into three groups; Group A: zero CTCs at baseline and zero CTCs at PT1,

Group B: a reduction of 50% or more from baseline CTC, Group C: all other

changes in CTCs including a reduction of less than 50% or any increase. Only

8% (5/60) of patients with a favorable CTC change (group A or B) had

progressive disease compared with 60% (24/40) in group C, suggesting that

dynamic change in CTC count in response to therapy is strongly associated

with radiological response to therapy (P<0.001) (Table 2).

A similar analysis was performed with CgA using a threshold of 120 pmol/L for

static measurements. For dynamic change we divided the population into

tertiles giving rise to the groups 1, 2 and 3 as shown in Table 2. In contrast to

our findings with CTC enumeration, we did not identify any association

between CgA as a static or dynamic marker and radiological response.

Association between CTCs and overall survival

We have previously shown that CTC count is prognostic for survival and

confirm here, that with prolonged follow-up, there remains a highly significant

difference in overall survival between those with, and those without, baseline

CTCs; HR 3.88, 95% CI: 2.15-7.00, P<0.001) (Figure 1A). Therefore the

baseline CTC count needed to be considered a potential cofounder when





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assessing the prognostic implications of the post-treatment CTC counts. To

account for this, the effect of number of baseline CTCs (not just as a

dichotomous variable) was further investigated. Cases were divided into

tertiles based on baseline CTC count and the PT1 CTC count (0, 1-8, >8).

Using Cox proportional hazards regression, the effect of baseline and,

separately, PT1 CTC counts, on overall survival was evaluated by univariate

analyses. Then the effect of PT1, adjusted for the baseline CTC, was

analyzed by including both variables in the model (Table 3). Post-treatment

CTC counts were strongly associated with overall survival and, after

correction for baseline counts, the PT1 count showed some association with

survival although did not quite reach statistical significance (P=0.06). Kaplan-

Meier survival curves for baseline and PT1 CTC counts are shown in online

Figure S1A and B. A PT1 CTC count of >8 was associated with a median OS

of 10.7 months (HR 5.13, 95% CI: 2.70-9.74) while a CTC count of 1-8 was

associated with a median OS of 31.2 months (HR 3.08, 95% CI: 2.70-9.74)

and the median OS for those with 0 CTCs (reference group) was not reached

at 54 months). Similarly for the PT2 CTC count; a CTC count of >8 was

associated with an OS of 13.3 months (HR 4.23, 95% CI: 2.19-8.18) while a

CTC count of 1-8 was associated with an OS of 21.5 months (HR 2.49, 95%

CI: 1.20-5.16) and the median OS for those with 0 CTCs (reference group)

was 49.1 months.

The association of CgA with overall survival was also investigated and, while

baseline levels did not reach significance at the threshold of 120pmol/L, the

uncorrected post-treatment levels were significant (P=0.023) but lost





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significance after correction for baseline (Table 3). Kaplan-Meier survival

curves for baseline and post-treatment CgA are shown in online Figure S1 C

and D

Dynamic changes in CTCs from baseline to PT1 and PT2 were also analyzed

in the groups based on percentage change at first post-treatment sample from

baseline CTC as described above (group A, B and C). Using Cox-proportional

hazards regression, the effect of changes in CTCs on survival were analyzed

(Table 4 and Figure 1B). Changes in CTC count at PT1 were strongly

associated with OS (P<0.001) with the best outcome observed in group A

(median OS not reached at 54 months, reference group) followed by group B:

(median OS 35.5 months, HR 3.31, 95% CI: 1.50–7.32) and the worst

outcome in group C (median OS 21.5 months, HR 5.07, 95% CI: 2.48–10.38).

When looking at the PT2 (10-15 weeks), only 10 patients changed groups. All

the patients in group A at first post-treatment time-point remained in group A;

one patient went from group C to group A; 5 went from group C to group B; 4

went from group B to group C. Therefore, it was not surprising to see a similar

associations with these groups and OS (Table 4 and Figure 1C).

Change from baseline CTCs at PT1, grade, tumour burden and age were put

into a multivariate model; backwards selection (with a cut off for inclusion of

p=0.1) was used and only the change from baseline CTCs and grade

remained significant as independent prognostic factors (Table 5). This was a

similar finding when analyzing the PT2, but with age remaining in the model,





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although not significant. Change in CTCs had the strongest association with

OS in terms of HR (P=0.0002).

We also evaluated dynamic changes in CgA but found no association

between changes in CgA and overall survival (online Table S2 and Figure

1D).

Discussion The increasing number of therapeutic options available for patients with NEN

has not been matched with development of robust predictive markers to aid

treatment selection and sequencing. Ki67 has been proposed as a marker to

select patients for cytotoxic chemotherapy[24] and there is some evidence

demonstrating response rate increases with tumor Ki67 index[25 26]. However,

overall, higher Ki67 is an adverse prognostic factor and this underlines the

importance of distinguishing between markers that are predictive of response

to therapy and those that are prognostic alone. For sunitinib and everolimus

which have been recently approved for the treatment of pancreatic NENs,

there are no predictive biomarkers available. In the absence of predictive

biomarkers that can be used to select therapy, a biomarker that provides an

early indicator of radiological response and long term benefit would potentially

be valuable, allowing the early discontinuation of toxic, ineffective and

expensive therapy in place of alternative approaches. To demonstrate that the

marker predicts treatment benefit, it is required to show that an early

treatment induced change in the marker impacts on clinically relevant

outcomes such as tumor progression and overall survival. For NENs, this type





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of biomarker would be particularly appealing since the response to treatment

can be delayed and survival prolonged.

In this study we have evaluated CTCs as both static and dynamic markers

before and after therapy, and their association with disease progression and

overall survival. First, with long follow-up and a robust survival endpoint, we

confirm our previous findings that CTC presence is highly prognostic for

overall survival. Second, we show that there is a strong association between

both radiological progression and overall survival, and CTC count at 3-5

weeks post-therapy. Third, we show that those who maintain undetectable

CTCs post-therapy or have a ≥ 50% fall have a much reduced chance of

progression and superior survival compared with those that have a <50% fall

or a rise in CTC count. Moreover, these dynamic changes in CTC counts are

associated with overall survival that is independent of tumor grade. In this

study we also compared early and late post-treatment points but there did not

seem to be a clear advantage of the later time point and this is consistent with

similar studies in prostate and colorectal cancer. Overall, our findings suggest

that the measurement of CTCs at a very early time point following therapy can

provide evidence of treatment benefit in terms of both radiological progression

and survival.

Other studies in epithelial tumors have demonstrated the predictive value of

post-treatment CTC measurements but have applied a single threshold for

favorable and unfavorable response[11 13 27]. We believe that both dynamic and

static assessment of CTCs provide relevant information. Our method of





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analyzing percentage changes in CTCs following treatment avoids the

potential for small changes in CTC number to move patients across

prognostic thresholds and also avoids ignoring major changes in CTC number

which do not cross a threshold[28].

Whether the prognosis in the poor outcome group could be improved by early

switching to an alternative therapy remains a key question which would

require prospective evaluation in a randomized trial. Such a study has

recently been reported in advanced breast cancer in which the patients with

persistently elevated CTCs after the first cycle of chemotherapy were

randomized to continue with the same regimen or switch to a second line

regimen[29]. This strategy failed to improve OS in the group that switched, but

it remains unclear if this was due to the lack of clinical activity of the second

line therapy in a group with inherently poor outlook and chemo-refractory

disease. Having effective alternative therapy is therefore essential for this

strategy to succeed and we will obtain some evidence for this in the ongoing

SEQTOR trial (NCT02246127) which will compare everolimus and

chemotherapy sequencing in pancreatic NENs.

Although our study is the first to prospectively address dynamic CTC changes

in response to therapy in patients with NEN, it does have some limitations.

First, this was a single center study and second, the population was

heterogeneous with respect to primary site and therapy. Both of these issues

are addressed in the ongoing CALM-NET study (NCT02075606) evaluating

the role of CTCs as a dynamic biomarker in mid-gut NENs treated with





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Somatuline Autogel and by the incorporation of CTC analysis into the

SEQTOR trial.

In summary, we demonstrate that early post-treatment CTC change is

associated with radiological response and survival presenting an opportunity

to explore biomarker-led sequencing studies in patients with NEN.





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Author Contribution

Conception and design: Mohid S Khan, Amy A Kirkwood, John Hartley, Martyn Caplin, Tim Meyer

Administrative support: Mohid S Khan, Martyn Caplin, Tim Meyer

Provision of study materials or patients: Mohid S Khan, John Hartley, Martyn Caplin, Tim Meyer

Collection and assembly of data: Mohid S Khan, Theodora Tsigani, Helen Lowe, Amy A Kirkwood, R Goldstein

Data analysis and interpretation: Mohid S Khan, Theodora Tsigani, Helen Lowe, Amy A Kirkwood, R Goldstein,

Tim Meyer

Manuscript writing: Mohid S Khan, Amy A Kirkwood, Martyn Caplin, Tim Meyer

Final approval of manuscript: Mohid S Khan, Theodora Tsigani, Helen Lowe, Amy A Kirkwood, R Goldstein,

John Hartley, Martyn Caplin, Tim Meyer

Acknowledgement We thank the National Institute of Health Research (NIHR), Experimental

Cancer Medicine Centre Network (ECMC) for their financial support. TM is

partly funded by UCLH/UCL Department of Health's NIHR Biomedical

Research Centers funding scheme.





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References

1. Yao JC, Hassan M, Phan A, Dagohoy C, Leary C, Mares JE, et al. One hundred years after "carcinoid": epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J Clin Oncol 2008;26(18):3063-72.

2. Rinke A, Muller HH, Schade-Brittinger C, Klose KJ, Barth P, Wied M, et al. Placebo-controlled, double-blind, prospective, randomized study on the effect of octreotide LAR in the control of tumor growth in patients with metastatic neuroendocrine midgut tumors: a report from the PROMID Study Group. J Clin Oncol 2009;27(28):4656-63.

3. Caplin ME, Pavel M, Cwikla JB, Phan AT, Raderer M, Sedlackova E, et al. Lanreotide in metastatic enteropancreatic neuroendocrine tumors. The New England journal of medicine 2014;371(3):224-33.

4. Weatherstone K, Meyer T. Streptozocin-based chemotherapy is not history in neuroendocrine tumours. Target Oncol 2012;7(3):161-8.

5. Raymond E, Dahan L, Raoul JL, Bang YJ, Borbath I, Lombard-Bohas C, et al. Sunitinib malate for the treatment of pancreatic neuroendocrine tumors. The New England journal of medicine 2011;364(6):501-13.

6. Yao JC, Shah MH, Ito T, Bohas CL, Wolin EM, Van Cutsem E, et al. Everolimus for advanced pancreatic neuroendocrine tumors. The New England journal of medicine 2011;364(6):514-23.

7. Falconi M, Bartsch DK, Eriksson B, Kloppel G, Lopes JM, O'Connor JM, et al. ENETS Consensus Guidelines for the management of patients with digestive neuroendocrine neoplasms of the digestive system: well-differentiated pancreatic non-functioning tumors. Neuroendocrinology 2012;95(2):120-34.

8. Pape UF, Perren A, Niederle B, Gross D, Gress T, Costa F, et al. ENETS Consensus Guidelines for the management of patients with neuroendocrine neoplasms from the jejuno-ileum and the appendix including goblet cell carcinomas. Neuroendocrinology 2012;95(2):135-56.

9. Pavel M, Baudin E, Couvelard A, Krenning E, Oberg K, Steinmuller T, et al. ENETS Consensus Guidelines for the management of patients with liver and other distant metastases from neuroendocrine neoplasms of foregut, midgut, hindgut, and unknown primary. Neuroendocrinology 2012;95(2):157-76.

10. Yao JC, Pavel M, Phan AT, Kulke MH, Hoosen S, St Peter J, et al. Chromogranin A and neuron-specific enolase as prognostic markers in patients with advanced pNET treated with everolimus. The Journal of clinical endocrinology and metabolism 2011;96(12):3741-9.

11. Cristofanilli M, Hayes DF, Budd GT, Ellis MJ, Stopeck A, Reuben JM, et al. Circulating tumor cells: a novel prognostic factor for newly diagnosed metastatic breast cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2005;23(7):1420-30.

12. Cristofanilli M, Budd GT, Ellis MJ, Stopeck A, Matera J, Miller MC, et al. Circulating tumor cells, disease progression, and survival in metastatic





18

breast cancer. The New England journal of medicine 2004;351(8):781-91.

13. de Bono JS, Scher HI, Montgomery RB, Parker C, Miller MC, Tissing H, et al. Circulating tumor cells predict survival benefit from treatment in metastatic castration-resistant prostate cancer. Clinical cancer research : an official journal of the American Association for Cancer Research 2008;14(19):6302-9.

14. Cohen SJ, Punt CJ, Iannotti N, Saidman BH, Sabbath KD, Gabrail NY, et al. Relationship of circulating tumor cells to tumor response, progression-free survival, and overall survival in patients with metastatic colorectal cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2008;26(19):3213-21.

15. Krebs MG, Sloane R, Priest L, Lancashire L, Hou JM, Greystoke A, et al. Evaluation and prognostic significance of circulating tumor cells in patients with non-small-cell lung cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2011;29(12):1556-63.

16. Scher HI, Heller G, Molina A, Attard G, Danila DC, Jia X, et al. Circulating tumor cell biomarker panel as an individual-level surrogate for survival in metastatic castration-resistant prostate cancer. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2015;33(12):1348-55.

17. Khan MS, Tsigani T, Rashid M, Rabouhans JS, Yu D, Luong TV, et al. Circulating tumor cells and EpCAM expression in neuroendocrine tumors. Clinical cancer research : an official journal of the American Association for Cancer Research 2011;17(2):337-45.

18. Khan MS, Kirkwood A, Tsigani T, Garcia-Hernandez J, Hartley JA, Caplin ME, et al. Circulating tumor cells as prognostic markers in neuroendocrine tumors. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2013;31(3):365-72.

19. Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). European journal of cancer 2009;45(2):228-47.

20. Hayes DF, Cristofanilli M, Budd GT, Ellis MJ, Stopeck A, Miller MC, et al. Circulating tumor cells at each follow-up time point during therapy of metastatic breast cancer patients predict progression-free and overall survival. Clinical cancer research : an official journal of the American Association for Cancer Research 2006;12(14 Pt 1):4218-24.

21. Allard WJ, Matera J, Miller MC, Repollet M, Connelly MC, Rao C, et al. Tumor cells circulate in the peripheral blood of all major carcinomas but not in healthy subjects or patients with nonmalignant diseases. Clinical cancer research : an official journal of the American Association for Cancer Research 2004;10(20):6897-904.

22. Zimpfer A, Went P, Tzankov A, Pehrs AC, Lugli A, Maurer R, et al. Rare expression of KIT (CD117) in lymphomas: a tissue microarray study of 1166 cases. Histopathology 2004;45(4):398-404.

23. Khan MS, Kirkwood A, Tsigani T, Garcia-Hernandez J, Hartley JA, Caplin ME, et al. Circulating Tumor Cells As Prognostic Markers in





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Neuroendocrine Tumors. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2012.

24. Vilar E, Salazar R, Perez-Garcia J, Cortes J, Oberg K, Tabernero J. Chemotherapy and role of the proliferation marker Ki-67 in digestive neuroendocrine tumors. Endocrine-related cancer 2007;14(2):221-32.

25. Turner NC, Strauss SJ, Sarker D, Gillmore R, Kirkwood A, Hackshaw A, et al. Chemotherapy with 5-fluorouracil, cisplatin and streptozocin for neuroendocrine tumours. Br J Cancer 2010;102(7):1106-12.

26. Sorbye H, Welin S, Langer SW, Vestermark LW, Holt N, Osterlund P, et al. Predictive and prognostic factors for treatment and survival in 305 patients with advanced gastrointestinal neuroendocrine carcinoma (WHO G3): the NORDIC NEC study. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO 2013;24(1):152-60.

27. Cohen SJ, Punt CJ, Iannotti N, Saidman BH, Sabbath KD, Gabrail NY, et al. Prognostic significance of circulating tumor cells in patients with metastatic colorectal cancer. Annals of oncology : official journal of the European Society for Medical Oncology / ESMO 2009;20(7):1223-9.

28. Bardia A, Haber DA. Solidifying liquid biopsies: can circulating tumor cell monitoring guide treatment selection in breast cancer? Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2014;32(31):3470-1.

29. Smerage JB, Barlow WE, Hortobagyi GN, Winer EP, Leyland-Jones B, Srkalovic G, et al. Circulating tumor cells and response to chemotherapy in metastatic breast cancer: SWOG S0500. Journal of clinical oncology : official journal of the American Society of Clinical Oncology 2014;32(31):3483-9.





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Table 1 Demographic and Clinical Characteristics of Patients with NENs. ECOG PS, Eastern Cooperative Oncology Group performance status; SST, somatostatin analogue therapy; TAE, transarterial embolization; PRRT, peptide receptor radionuclide therapy

Primary Site

Pancreatic Midgut Broncho-pulmonary

Unknown Primary

Hindgut Total

No of patients 31 81 12 11 3 138 Age, years Median Range

51·5 (23-72)

63 (34-85)

50·5 (30-77)

63 (31-78)

74 (43-75)

60 (23-85)

Sex Male Female

20 11

47 34

4 8

4 7

1 2

76 62

Grade 1 2 3

9 7 15

48 28 5

4 6 2

2 6 3

0 2 1

63 49 26

Burden of Liver metastases, % ≤ 25 25 to ≤ 50 50 to ≤ 75 > 75

10 13 3 5

35 30 11 5

7 3 2 0

4 4 2 1

1 0 1 1

57 50 19 12

Duration of diagnosis, months Median Range

33 (1-145)

30 (1-149)

20 (9-116)

15 (1-67)

18 (5-22)

26 (1-149)

ECOG PS 0 1 2 3 4

22 9 0 0 0

49 28 3 0 1

8 4 0 0 0

6 5 0 0 0

1 2 0 0 0

86 48 3 0 1

Previous treatment Resection of primary SST Chemotherapy TAE PRRT Interferon Liver resection

15 8 14 2 10 3 6

43 43 9 13 4 2 8

5 3 3 0 0 0 0

0 2 6 2 1 0 0

1 1 1 0 0 0 0

64 57 33 17 15 5 14





21

Table 2 Association between changes in CTCs and CgA and response to therapy. astable disease or partial response Disease

Controla Disease

Progression 1st Post-treatment CTC

0 1-8 >8

47/49 15/25 9/26

2/49

10/25 17/26

P<0.001

Changes in CTCs Group A 0-0 CTCs Group B ≥50% reduction Group C All others

35/36 20/24 16/40

1/36 4/24

24/40

P<0.001

1st Post-treatment CgA CgA≤120 CgA>120

24/35 44/59

11/35 15/59

P=0.53

Changes in CgA Group 1 >27% reduction Group 2 ≤27% reduction or <12% increase Group 3 ≥12% increase

19/29 24/32

24/32

10/29 8/32

8/32

P=0.61





22

Table 3 Effect of baseline and first post-treatment time-point CTC and CgA on OS aadjusted for baseline CTC count badjusted for baseline CgA

CgA Baseline ≤120

>120 1.00

1.49 (0.89-2.50) 0.13 21/48

49/90

CgA Post treatment

≤120 >120

1.00 1.99 (1.09-3.63)

0.023 14/38 44/69

CgA Post treatmentb

≤120 >120

1.00 01.90 (0.96-3.77)

0.06 14/38 44/69

OS HR (95% CI) p-value Events/n CTC Baseline 0 1.00 <0.001 14/55 1-8 2.91 (1.51-5.61) 25/42 >8 5.38 (2.84-10.18) 31/41 CTC Post treatment

0 1.00 <0.001 17/58 1-8 3.08 (1.59-5.96) 19/30 >8 5.13 (2.70-9.74) 23/30 CTC Post treatmenta

0 1.00 0.06 17/58 1-8 2.18 (0.95-4.98) 19/30 >8 2.93 (1.16-7.40) 23/30





23

Table 4 Effect on overall survival of changes in CTCs after treatment with groups according to percentage change of first post-treatment sample time-point (3-5 weeks, median 4.3) from baseline CTC count and of second post-treatment sample time-point (10-15 weeks, median 13.7)

1st Post-treatment time-point 2nd Post-treatment time-pointGroup Events/n OS HR(95% CI) p-value Events/n OS HR(95% CI) p-value A: Zero CTCs at baseline and time point 1 10/43 1.00 <0.001 8/33 1.00 <0.001 B: A reduction of 50% or more 16/28 3.31 (1.50 – 7.32) 16/26 3.53 (1.50 – 8.28) C: All others 33/47 5.07 (2.48 – 10.38) 25/33 5.57 (2.49 – 12.43)





24

Table 5 Multivariate Cox regression analysis to evaluate effect of prognostic factors on overall survival (OS). Change from baseline CTCs, grade, tumour burden and age were put into a multivariate model, backwards selection was used and only the change from baseline CTCs and grade (and age when analyzing the 2nd post-treatment time-point) remained in the model with change in CTCs the strongest predictor of OS OS HR (95% CI) P-value Events/n Analysis with 1st post-treatment time-point

Change from baseline (CTCs) Zero CTCs at baseline and post-treatment A reduction of 50% or more All others

1.00

2.92 (1.30-6.55) 4.13 (1.98- 8.63)

0.0002

10/43 16/28 33/47

Grade 1 2 3

1.00

0.85 (0.45-1.61) 2.63 (1.38-5.02)

0.0046

23/56 18/40 18/23

Analysis with 2nd post-treatment time-point

Change from baseline (CTCs) Zero CTCs at baseline and post-treatment A reduction of 50% or more All others

1.00

3.13 (1.37-7.42) 4.85 (2.12-11.07)

0.0002

8/31 16/26 25/33

Grade 1 2 3

1.00

0.95 (0.48-1.89) 4.36 (1.94-9.80)

0.0017

20/44 16/32 13/16

Age (for an increase of 10 years) 1.27 (0.98-1.65) 0.074 49/92





25

Figure 1 Kaplan-Meier survival curves demonstrating (A) effect of presence of baseline CTCs on overall survival OS; (B) OS dependent on changes in CTCs at first post-treatment time-point (3-5 weeks) compared to baseline CTC in groups (Group A: 0 CTCs at baseline and 0 CTCs post-treatment; Group B: ≥50% reduction in CTCs; Group C: all others) (C) OS dependent on changes in CTCs at second post-treatment time-point (10-15 weeks) compared to baseline CTC in groups (Group A: 0 CTCs at baseline and 0 CTCs post-treatment; Group B: ≥50% reduction in CTCs; Group C: all others) (D) OS dependent on changes in CgA at first post-treatment time-point (Group 1: >27% reduction; Group 2: ≤27% reduction or <12% increase; Group 3: ≥12% increase)




Published OnlineFirst July 21, 2015.Clin Cancer Res Mohid S Khan, Amy A Kirkwood, Theodora Tsigani, et al. neuroendocrine neoplasmsresponse and survival following treatment of metastatic Early changes in circulating tumor cells are associated with

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