Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation

Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

Abstract GS4-08: Clinical utility of repeated circulating tumor cell (CTC) enumeration as early treatment monitoring tool in metastatic breast cancer (MBC) - a global pooled analysis with individual patient data

Background:

Several studies suggest clinical utility of serial circulating tumor cell (CTC) enumeration as a means of assessing response status in metastatic breast cancer (MBC). The aim of this study is to conduct a comprehensive pooled analysis comprising globally available data to further define and explore the role of CTC enumeration as a tool for early treatment monitoring in patients with MBC with a focus on the predictive power in different breast cancer subtypes and clinical settings.

Methods:

In a global effort, peer-reviewed published studies with data on repeated CTC assessments (CellSearch® technology; Menarini Silicon Biosystems; Bologna, Italy) in MBC patients were screened and investigators were asked to provide individual patient data for this pooled analysis. 2761 cases from 32 data sets with data on both baseline and one follow up CTC assessments were included in the analysis (median time interval between the two CTC assessments 35 days). Data were analyzed using log rank tests and Cox regressions to evaluate the association between serial CTC enumeration results and overall survival (OS) in the full patient cohort and defined subgroups.

Results:

588 (21.3%) patients had no CTCs at both time points (neg/neg), 236 (8.5%) patients were CTC negative at baseline and CTC positive at follow up (neg/pos), 712 (25.8%) patients converted from CTC positive at baseline to CTC negative (pos/neg), and 1225 (44.4%) patients had at least one CTC at both time points (pos/pos). Log rank tests showed significant differences in OS between these four CTC change groups (p &lt; 0.0001 for all pairwise comparisons except for the comparison between neg/pos and pos/neg, p = 0.015). Median OS for the neg/neg, neg/pos, pos/neg and pos/pos group was 45.6, 26.1, 34.6, and 17.6 months, respectively. Hazard ratios (HR) (reference group neg/neg) were 1.38 (95% CI 1.16 - 1.64) for the pos/neg group, 1.78 (95% CI 1.43 - 2.22) for the neg/pos group, and 3.06 (95% CI 2.63 - 3.56) for the pos/pos group. Results were similar if a cutoff of 5 CTCs was used for CTC positivity (pos/neg group: HR 1.43, 95% CI 1.25 - 1.63; neg/pos group: HR 2.39, 95% CI 1.91 - 2.99; pos/pos group: HR 3.54, 95% CI 3.12 - 4.02).

In total, 2586 patients could be assigned to different tumor subtypes based on known hormone receptor (ER) and HER2 status of the primary tumor: 1513 (58.5%) patients had a luminal-like tumor (ER positive, HER2 negative), 682 (26.4%) patients had a HER2-positive tumor, and 391 (15.1%) patients had a triple-negative tumor. In patients with luminal-like tumors, the hazard ratios were 1.67 (95% CI 1.29 - 2.17), 2.01 (95% CI 1.45 - 2.77), and 3.87 (95% CI 3.09 - 4.83) for the pos/neg, neg/pos, and pos/pos group, respectively. In patients with HER2-positive tumors, the neg/pos group (HR 1.68, 95% CI 1.12 - 2.53) and the pos/pos group (HR 2.11, 95% CI 1.58 - 2.83) showed significantly worse OS compared to the neg/neg group, while in triple-negative patients, the pos/pos group had a significantly shorter OS compared to the neg/neg group (HR 2.99, 95% CI 2.11 - 4.24).

The results will be up-dated by inclusion of additional large data sets (CALGB 40502, CALGB 40503, COMET, SWOG S0500, TBCRC 001) for the analysis to be presented at SABCS 2020.

Conclusion:

This large pooled analysis confirms that at a median of 35 days after treatment initiation, follow-up CTC assessments strongly predict overall survival. These results suggest potential clinical utility of CTC monitoring as early response marker in MBC, especially in luminal-like tumors.

Citation Format: Wolfgang J Janni, Tracy C. Yab, Daniel F. Hayes, Massimo Cristofanilli, Francois-Clement Bidard, Michail Ignatiadis, Meredith M. Regan, Catherine Alix-Panabières, William E. Barlow, Carlos Caldas, Lisa A. Carey, Luc Dirix, Tanja Fehm, Jose A. Garcia-Saenz, Paola Gazzaniga, Daniele Generali, Lorenzo Gerratana, Rafael Gisbert-Criado, William Jacot, Zefei Jiang, Evi Lianidou, Mark J.M. Magbanua, Luis Manso, Dimitrios Mavroudis, Volkmar Müller, Elisabetta Munzone, Klaus Pantel, Jean-Yves Pierga, Brigitte Rack, Sabine Riethdorf, Hope S. Rugo, Kostandinos Sideras, Stefan Sleijfer, Jeffrey Smerage, Justin Stebbing, Leon W.M.M. Terstappen, José Vidal-Martínez, Rita Zamarchi, Karthik Giridhar, Thomas W.P. Friedl, Minetta C. Liu. Clinical utility of repeated circulating tumor cell (CTC) enumeration as early treatment monitoring tool in metastatic breast cancer (MBC) - a global pooled analysis with individual patient data [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr GS4-08.

Circulating Tumor Cells in Breast Cancer Patients Treated by Neoadjuvant Chemotherapy: A Meta-analysis

Background

We conducted a meta-analysis in nonmetastatic breast cancer patients treated by neoadjuvant chemotherapy (NCT) to assess the clinical validity of circulating tumor cell (CTC) detection as a prognostic marker.

Methods

We collected individual patient data from 21 studies in which CTC detection by CellSearch was performed in early breast cancer patients treated with NCT. The primary end point was overall survival, analyzed according to CTC detection, using Cox regression models stratified by study. Secondary end points included distant disease-free survival, locoregional relapse-free interval, and pathological complete response. All statistical tests were two-sided.

Results

Data from patients were collected before NCT (n = 1574) and before surgery (n = 1200). CTC detection revealed one or more CTCs in 25.2% of patients before NCT; this was associated with tumor size (P < .001). The number of CTCs detected had a detrimental and decremental impact on overall survival (P < .001), distant disease-free survival (P < .001), and locoregional relapse-free interval (P < .001), but not on pathological complete response. Patients with one, two, three to four, and five or more CTCs before NCT displayed hazard ratios of death of 1.09 (95% confidence interval [CI] = 0.65 to 1.69), 2.63 (95% CI = 1.42 to 4.54), 3.83 (95% CI = 2.08 to 6.66), and 6.25 (95% CI = 4.34 to 9.09), respectively. In 861 patients with full data available, adding CTC detection before NCT increased the prognostic ability of multivariable prognostic models for overall survival (P < .001), distant disease-free survival (P < .001), and locoregional relapse-free interval (P = .008).

Conclusions

CTC count is an independent and quantitative prognostic factor in early breast cancer patients treated by NCT. It complements current prognostic models based on tumor characteristics and response to therapy.

Soluble biomarker signature to predict outcome of patients with non-small-cell lung cancer (NSCLC) treated with anti-PD1/PDL1 monoclonal antibodies

e20685

Background: Immunotherapy with anti-PD1/PDL1 monoclonal antibodies has become the second line standard treatment for most patients diagnosed of advanced Non-Small-Cell lung cancer (NSCLC). The aim of this study is to assess the utility of circulating biomarkers such as sPDL1, sPDL2, sCD137, sIDO, sTIM3, sCD28, sCD27, sCTLA4, sHVEM, sLAG3, sCD80 and sGITR for predicting efficacy of immunotherapy with anti-PD1/PDL1 therapies. Methods: Blood samples were collected before treatment from 50 NSCLC patients who received anti PD1/PDL1 therapies (second line). Plasma biomarkers´ levels were measured by Multiplex bead-based assays. Continuous variables were categorized using the median as a cut-off. Non parametric test were used for correlations between analytical variables and clinical-pathological parameters and response rate analysis. For survival analysis (progression free survival-PFS and overall survival-OS) Kaplan Meier curves and long-rank test were performed. Results: 50 patients met inclusion criteria. Biomarkers associated with better outcome in terms of Response Rate or PFS were sPDL1, sIDO, sCD137 and sGITR. Median plasma levels of sPDL1, sCD137, sIDO and sGITR were 80.5, 168.7, 64.92s and 114.43 ng/ml respectively. ORR was higher in patients with high levels of CD137 (75 vs 25%, p = 0.28), GITR (83.3 vs 16.7%, p = 0.009) and sPDL1 (66.7 vs 33.3%, p = 0.07). Median PFS was significantly higher for patients with high sPDL1 levels (NR vs 3 months, p = 0.017), and there was a favourable trend for patients with higher serum levels of CD137 (NR vs 5.07, p = 0.11), sIDO (NR vs 5.57 months, p = 0.08); and sGITR (14.33 vs 5.57 months, p = 0.16). Combination of these biomarkers allowed the identification of three groups: group1 (0-1 positive biomarker), group2 (2 positive biomarkers) and group 3 (3 or 4 positive biomarkers), with significant differences in ORR (8.3 vs 25 vs 66.7%, p = 0.01), PFS (median 3.2, 1.1 and NR months, p = 0.01) and OS (median 2.3, 5.0 and NR months, p = 0.02). Conclusions: Circulating immune markers can be reliable detected in plasma of advanced NSCLC patients. In patients treated with anti-PD1 antibodies. sCD137, sIDO, sGITR and sPDL1 seem to be related to the degree of response or PFS. Combination of these biomarkers might be helpful to predict efficacy of immunotherapy treatment.

The clinical use of circulating tumor cells (CTCs) enumeration for staging of metastatic breast cancer (MBC): International expert consensus paper

BACKGROUND

The heterogeneity of metastatic breast cancer (MBC) necessitates novel biomarkers allowing stratification of patients for treatment selection and drug development. We propose to use the prognostic utility of circulating tumor cells (CTCs) for stratification of patients with stage IV disease.

METHODS

In a retrospective, pooled analysis of individual patient data from 18 cohorts, including 2436 MBC patients, a CTC threshold of 5 cells per 7.5 ml was used for stratification based on molecular subtypes, disease location, and prior treatments. Patients with ≥ 5 CTCs were classified as Stage IVaggressive, those with < 5 CTCs as Stage IVindolent. Survival was analyzed using Kaplan-Meier curves and the log rank test.

RESULTS

For all patients, Stage IVindolent patients had longer median overall survival than those with Stage IVaggressive (36.3 months vs. 16.0 months, P < 0.0001) and similarly for de novo MBC patients (41.4 months Stage IVindolent vs. 18.7 months Stage IVaggressive, p < 0.0001). Moreover, patients with Stage IVindolent disease had significantly longer overall survival across all disease subtypes compared to the aggressive cohort: hormone receptor-positive (44 months vs. 17.3 months, P < 0.0001), HER2-positive (36.7 months vs. 20.4 months, P < 0.0001), and triple negative (23.8 months vs. 9.0 months, P < 0.0001). Similar results were obtained regardless of prior treatment or disease location.

CONCLUSIONS

We confirm the identification of two subgroups of MBC, Stage IVindolent and Stage IVaggressive, independent of clinical and molecular variables. Thus, CTC count should be considered an important tool for staging of advanced disease and for disease stratification in prospective clinical trials.

Abstract P2-08-08: Circulating tumor cells count-based nomograms to predict survival of metastatic breast cancer patients: Results from the European pooled analysis

Background: The European Pooled Analysis of CTC (EPAC) in metastatic breast cancer, based on 1,944 individual data from patients with various tumor types and clinical settings (Bidard et al, Lancet Oncol 2014), has established CTC count (CellSearch) at baseline and during therapy as a level of evidence 1 independent prognostic biomarker and demonstrated its superiority over serum blood markers. As part of the study pre-planned objectives, we sought to establish nomograms allowing accurate individual survival predictions.

Methods: Using individual data from 17 centers, we built simplified multivariate prognostic models taking into account the independent prognostic clinico-pathological (CP) characteristics including CTC count, dichotomized using the 5CTC/7.5ml threshold, at baseline and at 3-5 weeks after the start of a new treatment regimen, and derived nomograms for progression-free survival (PFS) and overall survival (OS) prediction at baseline and after 3-5 weeks of treatment. We report here the internal validation of these nomograms. Discrimination of the models was assessed using the c-index estimated by a jackknife procedure and the calibration was visually assessed through 10-fold crossvalidated calibration plots at 1,2,3 years for OS and 1,2 years for PFS.

Results: Multivariate models at baseline for PFS and OS were fitted on 1501 and 568 individual patient data with CTC count at baseline and CTC count at baseline and after 3-5 weeks, respectively. Models include tumor subtype, the number of previous chemotherapy lines (0/1/≥2), PS, age (&lt;=50/&gt;50-65/&gt;65 years), metastasis-free intervals (0/&gt;0-3/&gt;3 years), metastatic sites (liver and CNS) and CTC count at baseline and eventually at 3-5 weeks of treatment. The C-index increased from 0.722 to 0.755 (increase in C-index:0.033, 95% CI [0.019;0.045]) when adding baseline CTC to the CP only model for OS (n=1501). For those patients with CTC values at 3-5 weeks (n=568), there was an additional increase in the C-index when adding CTC at 3-5 weeks to a model with already CP and baseline CTC from 0.731 to 0.743 (increase in C-index 0.013, 95% CI [-0.004;0.025]). The model with CP and baseline CTC counts showed a good calibration for OS at 1,2,3 years and the model with CP, baseline CTC and CTC count at 3-5 weeks a moderately good calibration. Similar results were obtained for PFS.

Conclusion: From the largest database with individual CTC data, we were able to build PFS and OS survival nomograms, with satisfactory discrimination and calibration. Our planned next step is to validate the nomogram in an additional cohort.

Citation Format: Bidard F-C, Peeters D, Fehm T, Nole F, Gisbert-Criado R, Mavroudis D, Grisanti S, Generali D, Garcia-Saenz JA, Stebbing J, Caldas C, Gazzaniga P, Manso L, Zamarchi R, Fernandez de Lascoiti A, de Mattos-Arruda L, Ignatiadis M, van Laere SJ, Meier-Stiegen F, Sandri M-T, Vidal-Martinez J, Politaki E, Consoli F, Bottini A, Diaz-Rubio E, Krell J, Dawson S-J, Raimondi C, Rutten A, Janni W, Munzone E, Carañana V, Agelaki S, Almici C, Dirix L, Solomayer E, Zorzino L, Reis-Filho JS, Squifflet P, Pantel K, Beije N, Sleijfers S, Pierga J-Y, Michiels S. Circulating tumor cells count-based nomograms to predict survival of metastatic breast cancer patients: Results from the European pooled analysis. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-08-08.

Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data

BACKGROUND

We aimed to assess the clinical validity of circulating tumour cell (CTC) quantification for prognostication of patients with metastatic breast cancer by undertaking a pooled analysis of individual patient data.

METHODS

We contacted 51 European centres and asked them to provide reported and unreported anonymised data for individual patients with metastatic breast cancer who participated in studies between January, 2003, and July, 2012. Eligible studies had participants starting a new line of therapy, data for progression-free survival or overall survival, or both, and CTC quantification by the CellSearch method at baseline (before start of new treatment). We used Cox regression models, stratified by study, to establish the association between CTC count and progression-free survival and overall survival. We used the landmark method to assess the prognostic value of CTC and serum marker changes during treatment. We assessed the added value of CTCs or serum markers to prognostic clinicopathological models in a resampling procedure using likelihood ratio (LR) χ(2) statistics.

FINDINGS

17 centres provided data for 1944 eligible patients from 20 studies. 911 patients (46·9%) had a CTC count of 5 per 7·5 mL or higher at baseline, which was associated with decreased progression-free survival (hazard ratio [HR] 1·92, 95% CI 1·73-2·14, p<0·0001) and overall survival (HR 2·78, 95% CI 2·42-3·19, p<0·0001) compared with patients with a CTC count of less than 5 per 7·5 mL at baseline. Increased CTC counts 3-5 weeks after start of treatment, adjusted for CTC count at baseline, were associated with shortened progression-free survival (HR 1·85, 95% CI 1·48-2·32, p<0·0001) and overall survival (HR 2·26, 95% CI 1·68-3·03) as were increased CTC counts after 6-8 weeks (progression-free survival HR 2·20, 95% CI 1·66-2·90, p<0·0001; overall survival HR 2·91, 95% CI 2·01-4·23, p<0·0001). Survival prediction was significantly improved by addition of baseline CTC count to the clinicopathological models (progression-free survival LR 38·4, 95% CI 21·9-60·3, p<0·0001; overall survival LR 64·9, 95% CI 41·3-93·4, p<0·0001). This model was further improved by addition of CTC change at 3-5 weeks (progression-free survival LR 8·2, 95% CI 0·78-20·4, p=0·004; overall survival LR 11·5, 95% CI 2·6-25·1, p=0·0007) and at 6-8 weeks (progression-free survival LR 15·3, 95% CI 5·2-28·3; overall survival LR 14·6, 95% CI 4·0-30·6; both p<0·0001). Carcinoembryonic antigen and cancer antigen 15-3 concentrations at baseline and during therapy did not add significant information to the best baseline model.

INTERPRETATION

These data confirm the independent prognostic effect of CTC count on progression-free survival and overall survival. CTC count also improves the prognostication of metastatic breast cancer when added to full clinicopathological predictive models, whereas serum tumour markers do not.

FUNDING

Janssen Diagnostics, the Nuovo-Soldati foundation for cancer research.

Abstract PD6-5: Pooled analysis of circulating tumor cells in metastatic breast cancer: Findings from 1944 individual patients data

Background: Clinical validity of CTCs (CellSearch®) in metastatic breast cancer (MBC) patients has previously been assessed in studies with limited statistical power. We aimed to pool all European studies to obtain high-level evidence on the prognostic value of CTCs, to investigate their effects across different clinico-pathological characteristics and therapies and to further validate the MD Anderson/Institut Curie/Fox Chase CTC-based prognostic nomogram established in first-line treated MBC patients (Giordano et al, Clin Cancer Res 2013).

Material and methods: Methods were predefined in a written protocol. In December 2012, we searched for eligible studies that accrued patients in 2003-2012. We contacted all European laboratories using CellSearch®. We used likelihood ratio tests (LR) in Cox regression models stratified by study to assess the independent prognostic value of CTC when added to a clinicopathological (CP) model for progression-free (PFS) and overall survival (OS). Landmark analyses were used to assess the prognostic effect of early changes in CTC. The CTC-based nomogram (http://cancernomograms.com/CTCOnline.html) score was retrieved for every patient; we calculated C-indices, drew calibration plots and Kaplan-Meier curves according to quintiles of the nomogram score.

Results: We collected individual data of 1944 MBC patients, from 20 different studies (some unpublished), from 17 centers in 7 European countries. We observed 1507 PFS events and 929 deaths. Baseline CTC count was significantly associated with several patient characteristics, such as performance status (PS, p&lt;10-4), synchronous metastasis (p&lt;10- 2) tumor subtype (p&lt;10-4), liver & bone metastases (p&lt;10-4), CEA & CA15-3 levels (p&lt;10-4). The CP model for OS included PS, MBC subtypes, number of previous lines of treatment, patient's age, metastasis-free interval, metastatic sites (p&lt;0.01 for all). In a multivariate analysis containing the CP model parameters and CTC count at baseline, elevated CTC count (≥5) was a significant independent predictor of OS (n = 1444, HR = 2.7, 95%CI [2.2-3.2], LR p&lt;10-4). Baseline serum markers added either no or marginal effect to the CP plus baseline CTC model for OS. In contrast, early changes in CTC status at week 3-5 significantly added prognostic information for OS to the model with CP factors and baseline CTC+ (n = 569, HR = 1.8 [2.2-3.2], LR p&lt;0.001). In the population of interest (MBC treated by first line chemotherapy, n = 402 patients, 176 deaths), the CTC-based nomogram exhibited a good C-index for OS (0.69), was well calibrated and showed clear separation of the survival curves. Additional results, including subgroup analyses by tumor subtype and treatments will be presented at the meeting.

Conclusions: This pooled analysis is the largest study ever reported on CTC in MBC, with a previously unreached statistical power. It provides a clear level-of-evidence 1 on the independent prognostic value of CTCs before and during treatment in MBC. Also, the CTC-based prognostic nomogram is independently validated.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr PD6-5.

External quality assurance of circulating tumor cell enumeration using the CellSearch(®) system: a feasibility study

BACKGROUND

Circulating tumor cells (CTCs) are cells that have detached from solid tumors and entered the blood. CTCs can be detected, among others, by semi-automated immunomagnetic enrichment and image cytometry using CellSearch® (Veridex, Raritan, NJ). We studied the feasibility of external quality assurance (EQA) of the entire CellSearch procedure from blood draw to interpretation of results in multiple laboratories.

METHODS

Blood samples from six cancer patients and controls were distributed to 14 independent laboratories to test between-laboratory, between-assay, and between-instrument variation. Additionally, between-operator variability was assessed through the interpretation of blinded images of all blood samples on a website.

RESULTS

Shipment and storage of samples had no influence on CTC values. Between-instrument (coefficient of variation (CV) < 12%) and between-assay variation was low (CV ≤ 20%), indicating high reproducibility. However, between-laboratory CV ranged from 45 to 64%. Although inter-operator agreement on image interpretation (Fleiss' κ statistics) ranged from "substantial" to "almost perfect," image interpretation, particularly of samples containing high numbers of apoptotic cells, was the main contributor to between-laboratory variation.

CONCLUSIONS

This multicenter study shows the feasibility of an EQA program for CTC detection in patient samples, and the importance of continuation of such a program for the harmonization of CTC enumeration.