Analysis of a Real-World Cohort of Metastatic Breast Cancer Patients Shows Circulating Tumor Cell Clusters (CTC-clusters) as Predictors of Patient Outcomes

cancers Article Analysis of a Real-World Cohort of Metastatic Breast Cancer Patients Shows Circulating Tumor Cell Clusters (CTC-clusters) as Predictors of Patient Outcomes Clotilde Costa 1,2,†, Laura Muinelo-Romay 2,3,†, Victor Cebey-López 4, Thais Pereira-Veiga 1, Inés Martínez-Pena 1, Manuel Abreu 3, Alicia Abalo 3, Ramón M. Lago-Lestón3, Carmen Abuín1, Patricia Palacios 4, Juan Cueva 4, Roberto Piñeiro 1,*,‡and Rafael López-López 1,2,3,4,‡ 1Roche-Chus Joint Unit, Translational Medical Oncology Group, Oncomet, Health Research Institute of Santiago de Compostela (IDIS), Travesía da Choupana s/n, 15706 Santiago de Compostela, Spain; [email protected] (C.C.); [email protected] (T.P.-V.); [email protected] (I.M.-P.); carmen.abuin.r[email protected] (C.A.); [email protected] (R.L.-L.) 2CIBERONC, Centro de Investigación Biomédica en Red Cáncer, 28029 Madrid, Spain; [email protected] 3 Liquid Biopsy Analysis Unit, Translational Medical Oncology Group, Health Research Institute of Santiago de Santiago de Compostela (IDIS), Travesía da Choupana s/n, 15706 Santiago de Compostela, Spain; [email protected] (M.A.); alicia.abalo.pineir[email protected] (A.A.); [email protected] (R.M.L.-L.) 4Department of Oncology, Complexo Hospitalario Universitario de Santiago de Compostela (SERGAS), 15706 Santiago de Compostela, Spain; [email protected] (V.C.-L.); [email protected] (P.P.); [email protected] (J.C.) *Correspondence: roberto.pineir[email protected]; Tel.: +34-981-955-602 †These authors contributed equally. ‡These authors jointly supervised this work. Received: 19 March 2020; Accepted: 27 April 2020; Published: 29 April 2020   Abstract: Circulating tumor cell (CTC) enumeration has emerged as a powerful biomarker for the assessment of prognosis and the response to treatment in metastatic breast cancer (MBC). Moreover, clinical evidences show that CTC-cluster counts add prognostic information to CTC enumeration, however, their significance is not well understood, and more clinical evidences are needed. We aim to evaluate the prognostic value of longitudinally collected single CTCs and CTC-clusters in a heterogeneous real-world cohort of 54 MBC patients. Blood samples were longitudinally collected at baseline and follow up. CTC and CTC-cluster enumeration was performed using the CellSearch ® system. Associations with progression-free survival (PFS) and overall survival (OS) were evaluated using Cox proportional hazards modelling. Elevated CTC counts and CTC-clusters at baseline were significantly associated with a shorter survival time. In joint analysis, patients with high CTC counts and CTC-cluster at baseline were at a higher risk of progression and death, and longitudinal analysis showed that patients with CTC-clusters had significantly shorter survival compared to patients without clusters. Moreover, patients with CTC-cluster of a larger size were at a higher risk of death. A longitudinal analysis of a real-world cohort of MBC patients indicates that CTC-clusters analysis provides additional prognostic value to single CTC enumeration, and that CTC-cluster size correlates with patient outcome. Keywords: breast cancer; metastasis; circulating tumor cells (CTCs); CTC-clusters; prognosis Cancers 2020,12, 1111; doi:10.3390/cancers12051111 www.mdpi.com/journal/cancers Cancers 2020,12, 1111 2 of 19 1. Introduction Breast cancer (BC) corresponds to the most frequent tumor type in women [ 1 ]. Nearly 30% of women initially diagnosed with early-stage BC will go on to develop metastatic lesions [ 2 ]. Disease progression and the appearance of a disseminated disease have a negative impact on the survival of these patients, being metastases responsible for 90% of deaths related to cancer [ 3 ]. Despite the positive impact of new systemic therapies incorporated to the clinic in recent years, metastatic breast cancer (MBC) remains an incurable disease. Currently, treatment selection is mainly based on the histological characterization of a biopsy from the primary tumor or metastatic sites. However, tissue biopsies have inherently associated limitations, such as restricted access and lack of representation of intratumoral heterogeneity, making them an unfeasible approach for long term disease monitoring [ 4 ]. Therefore, less invasive techniques, with the capacity to predict patient clinical outcome and to guide the treatment are needed, in order to better select the most convenient therapy. Circulating tumor cells (CTCs), those cells shed into the blood stream by both primary and metastatic tumors, are the main responsible for metastases formation at distant sites. CTCs therefore have the potential to serve as a liquid biopsy. The analysis of CTCs represents a non-invasive procedure that can be serially repeated in order to assess tumor progression in real time, and CTC enumeration may hold promise for improving cancer treatment. CTCs are frequently detected in the peripheral blood of patients with MBC, but rarely found in early BC [ 5 – 7 ]. The prognostic value of CTCs in MBC is extensively studied and has been corroborated by large studies. Thus, a CTC count of ≥ 5 cells per 7.5 mL blood detected by the CellSearch ® system is an independent predictive factor of worse progression-free survival (PFS) and overall survival (OS). The first evidence in this regard was shown in 2004 [ 8 ], and since then, many studies have confirmed these findings [ 5 , 9 – 12 ]. The highest level of evidence has been shown in a recent pooled analysis of individual patient data gathered from 1944 patients, demonstrating the clinical validity of CTC enumeration, and that CTC count improves the prognostication of MBC [ 5 ]. Moreover, other studies indicate that CTC dynamics seem to reflect treatment response, and that CTC status can serve as an indicator to monitor the effectiveness of treatments and guide subsequent therapies in BC [5,13–15]. CTCs can be found in the bloodstream of cancer patients as single cells or as aggregates known as CTC-clusters or circulating tumor microemboli [ 16 – 21 ]. Although rare in circulation, CTC-clusters show a higher ability to form distant metastases than single CTCs [ 22 – 24 ]. Key biological features of CTC-cluster reveal the molecular mechanisms underlying their enhanced metastatic potential, i.e., a low incidence of apoptosis, a hybrid epithelial/mesenchymal phenotype, and a stem cell signature acquired through the modification of epigenetic programs [ 16 , 17 , 22 , 25 , 26 ]. Similarly to CTCs, the enumeration of CTC-clusters in the blood of MBC patients has been revealed as a strong biomarker for the assessment of prognosis and response to treatment [ 27 – 30 ]. Thus, patients with CTC-clusters have significantly worse OS and PFS than those patients with only single CTCs. Recent studies have shown that CTC-cluster evaluation allows for the stratification of MBC patients with elevated baseline CTCs into different survival groups. In fact, CTC-cluster counts add prognostic value to CTC enumeration alone, and even more importantly, longitudinal evaluation of CTCs and CTC-clusters improves prognostication and treatment monitoring in patients with MBC [ 16 , 27 – 30 ]. On the other hand, recent data from a clinical trial indicates that the absolute number of CTCs, rather than the presence of CTC-clusters, are predictors of the outcome of MBC patients starting first line chemotherapy [31]. The aim of this study was to evaluate the prognostic value of CTC counts and CTC-clusters determined by CellSearch ® in an unselected cohort of MBC patients, and to examine how these relate to PFS and OS. For this purpose, we use longitudinal collected data at baseline and follow up from a heterogeneous cohort of patients diagnosed with MBC starting first line of therapy and MBC patients initiating a new line of therapy. Cancers 2020,12, 1111 3 of 19 2. Results 2.1. Patient Characteristics A total of 54 MBC patients were included in the study. The median follow up time from baseline for alive patients was 197 days (range 22–603 days). Among the patients, 27 (50.9%) were classified as having hormone receptor–positive and human epidermal growth factor receptor 2-negative tumors (HR+HER2-); 11 (20.8%) were classified as having HER2+tumors; and 15 (28.3%) as triple-negative breast cancer tumors (HR-HER2-). One patient showed an undetermined HER2 staining. Visceral metastases were present in 40 patients (74.1%), while 14 patients (25.9%) had non-visceral metastasis. Patient characteristics are detailed in Table 1. Table 1. Patient characteristics (n=54). Variables Total, n(%) Age (years), mean 58.5 <65 years 34 (63.0) ≥65 years 20 (37.0) Tumor stage IV 54 (100.0) Baseline ECOG 0 18 (33.3) 1 31 (57.4) 2 5 (9.3) Primary tumor NHG I 4 (7.4) II 26 (48.1) II 15 (27.8) Unknown 9 (16.7) Breast cancer subtypes HR+HER227 (50.9) HER2+11 (20.8) HR-HER215 (25.8) Unknown 1 (1.8) Site of metastasis * Non-visceral 14 (25.9) Visceral 40 (74.1) Number of metastatic sites <3 29 (53.7) ≥3 25 (46.3) First-line systemic therapy (n=44) Chemotherapy 23 (52.3) Hormonal therapy 15 (34.1) Target therapy #6 (13.6) Other lines (n=10) Chemotherapy 8 (80.0) Hormonal therapy 1 (10.0) Target therapy #1 (10.0) Abbreviations: ECOG Eastern Cooperative Oncology Group, NHG Nottingham histologic grade, HR hormone receptor, HER2 human epidermal growth factor receptor 2, TNBC triple negative breast cancer. * Visceral metastases were defined as lung, liver, peritoneal, and/or pleural involvement and non-visceral metastasis was defined as lymph node and/or bone involvement. #In combination with chemotherapy. 2.2. Counts of CTCs and CTC-Clusters and Association with Clinicopathological Variables CTCs and CTC-clusters were analyzed in a total of 96 blood samples collected at baseline (when patients started first-line of systemic therapy or before starting a new line of therapy) from 54 patients, of whom 38 patients had follow up samples collected (Figure S1). Among the patients analyzed at baseline, 31 (57.4%) had ≥ 5 CTCs, and 14 (25.9%) had at least one CTC-cluster (composed of ≥ 2 CTCs). Cancers 2020,12, 1111 4 of 19 Within the patients considered at follow up visit, 13 (34.2%) had ≥ 5 CTCs, and 7 (18.4%) had at least one CTC-cluster detected. The fraction of patients with ≥ 5 CTCs decreased from baseline to follow up (Table S1). CTC-clusters were exclusively found in patients with ≥ 5 CTCs, 14 of 31 (45.2%) at baseline, and 7 of 13 (53.8%) at follow up, and their presence was clearly associated with the number of CTCs (Figure S2). At baseline, 12 patients presented CTC-clusters composed by two or three cells, and two patients presented CTC-clusters composed by ≥ 4 cells. During follow up, five patients presented CTC-clusters composed by two or three cells, and two patients presented CTC-clusters composed by ≥ 4 cells. At both time points, a higher proportion of patients showing ≥ 5 CTCs and CTC-clusters was found in the HR+HER2subtype, however, we did not find significant differences on the distribution in relation to BC subtype at baseline and follow up (Table S2). No association was found between the number and location of metastases with the counts of CTCs or CTC-clusters. The presence of heterotypic clusters, defined by the detection of clustered CTCs and CD45-positive white blood cells (WBCs) ( ≥ 1 CTC and ≥ 1 CD45+cell), was also evaluated (Figure 1). At baseline, two patients (3.7%) had at least one CTC-WBC cluster detected, and at follow up three patients (7.9%) had at least one CTC-WBC cluster identified (Figure S1, Table S1). The presence of clustered CTC-WBC was associated with an elevated CTC count (≥5 CTCs/7.5 mL), both at baseline and follow up (Figure S2). Cancers 2020, 12, x FOR PEER REVIEW 4 of 20 patients, of whom 38 patients had follow up samples collected (Figure S1). Among the patients analyzed at baseline, 31 (57.4%) had ≥5 CTCs, and 14 (25.9%) had at least one CTC-cluster (composed of ≥2 CTCs). Within the patients considered at follow up visit, 13 (34.2%) had ≥ 5 CTCs, and 7 (18.4%) had at least one CTC-cluster detected. The fraction of patients with ≥5 CTCs decreased from baseline to follow up (Table S1). CTC-clusters were exclusively found in patients with ≥5 CTCs, 14 of 31 (45.2%) at baseline, and 7 of 13 (53.8%) at follow up, and their presence was clearly associated with the number of CTCs (Figure S2). At baseline, 12 patients presented CTC-clusters composed by two or three cells, and two patients presented CTC-clusters composed by ≥4 cells. During follow up, five patients presented CTC-clusters composed by two or three cells, and two patients presented CTCclusters composed by ≥4 cells. At both time points, a higher proportion of patients showing ≥5 CTCs and CTC-clusters was found in the HR+HER2subtype, however, we did not find significant differences on the distribution in relation to BC subtype at baseline and follow up (Table S2). No association was found between the number and location of metastases with the counts of CTCs or CTC-clusters. The presence of heterotypic clusters, defined by the detection of clustered CTCs and CD45positive white blood cells (WBCs) (≥1 CTC and ≥1 CD45+ cell), was also evaluated (Figure 1). At baseline, two patients (3.7%) had at least one CTC-WBC cluster detected, and at follow up three patients (7.9%) had at least one CTC-WBC cluster identified (Figure S1, Table S1). The presence of clustered CTC-WBC was associated with an elevated CTC count (≥5 CTCs/7.5 mL), both at baseline and follow up (Figure S2). These results evidenced that CTC-clusters are found in a low frequency in patients with MBC, being clearly more often found in patients with a high spread of single CTCs, before the treatment onset and during the follow up. Figure 1. Representative images of circulating tumor cell (CTC)-clusters and CTC-WBC (white blood cell) clusters isolated from 7.5 ml of blood from metastatic breast cancer (MBC) patients captured by CellSearch® system. CTCs were identified by round-oval morphology, positive staining for cytokeratins 8, 18, and 19 (CKs-PE, phycoerythrin-conjugated antibody) and DAPI (DNA dye), and negative staining for CD45 (CD45-APC, allophycocyanin-conjugated antibody 2.3. Presence of CTC-Clusters Predicts Patient Outcome at Baseline Figure 1. Representative images of circulating tumor cell (CTC)-clusters and CTC-WBC (white blood cell) clusters isolated from 7.5 ml of blood from metastatic breast cancer (MBC) patients captured by CellSearch ® system. CTCs were identified by round-oval morphology, positive staining for cytokeratins 8, 18, and 19 (CKs-PE, phycoerythrin-conjugated antibody) and DAPI (DNA dye), and negative staining for CD45 (CD45-APC, allophycocyanin-conjugated antibody. These results evidenced that CTC-clusters are found in a low frequency in patients with MBC, being clearly more often found in patients with a high spread of single CTCs, before the treatment onset and during the follow up. 2.3. Presence of CTC-Clusters Predicts Patient Outcome at Baseline Patients with ≥ 5 CTCs/7.5 mL at baseline (n=31) had a trend towards an inferior PFS (P log-rank =0.059), and they had a significantly shorter OS (P log-rank =0.017), compared to those with none or <5 CTCs (Figure 2a,b). Accordingly, Cox regression analysis showed that patients with Cancers 2020,12, 1111 5 of 19 high CTC count ( ≥ 5 CTCs) were at a higher risk of death (HR OS 3.15; 95% CI 1.16–5.55; p=0.024), but not of progression (HR PFS =2.11; 95% CI 0.95–4.69; p=0.065), than those with <5 CTCs (Table 2). In the multivariable analysis, both observations resulted in being significant after adjustment for other clinicopathological variables (described in Table S3). In CTC-cluster based analysis, patients with ≥ 1 CTC-cluster had a significantly increased risk of disease progression (HR PFS 3.95; 95% CI 1.80–8.68; p=0.0006) and death (HR OS 4.23; 95% CI 1.8–10.1; p=0.0009), and showed shorter PFS and OS (PFS and OS P log-rank <0.001) (Figure 2c,d). Importantly, both observations maintained their significance when adjusting for other clinicopathological variables (Table 2). On the other hand, the low frequency presence of CTC-WBC cluster at baseline was not able to predict patient outcomes. Patients with ≥ 5 CTCs (n=13) at follow up did not show an increased risk of progression or shorter PFS time, but they had an increased risk of death (HR OS 5.3; 95% CI 1.4–21; p=0.017) and a shorter OS (P log-rank <0.05) compared to patients with <5 CTCs/7.5 mL (Table 2, Figure 2e,f). Cox regression analysis resulted in being not significant when adjusting for other prognostic factors. In CTC-cluster based analysis, PFS or OS were not different for patients with or without CTC-clusters, although a trend was observed towards an increased risk of death (HR 3.0) (Figure 2g,h, Table 2). Similar to the baseline analysis, no prognostic value was observed when the presence of CTC-WBC cluster was evaluated. Table 2. Associations between CTCs and CTC-clusters and PFS and OS of MBC patients. Variable Total Events, n(%) HR (95% CI) pValue HR (95% CI) * pValue * Baseline Associated with PFS CTCs <5 23 11 (47.8) 1.00 1.00 ≥5 31 20 (64.5) 2.11 (0.95–4.70) 0.0649 2.82 (1.15–6.87) 0.022 CTC-clusters No 40 18 (45.0) 1.00 1.00 Yes 14 11 (78.6) 3.95 (1.80–8.68) 0.0006 4.46 (1.55–12.8) 0.005 Associated with OS CTCs <5 23 6 (26.1) 1.00 1.00 ≥5 31 17 (54.8) 3.15 (1.16–8.55) 0.024 3.33 (1.14–9.73) 0.027 CTC-clusters No 40 13 (32.5) 1.00 1.00 Yes 14 10 (71.4) 4.23 (1.8–10.1) 0.0009 6.55 (1.78–23.8) 0.004 Follow up Associated with PFS CTCs <5 25 8 (32) 1.00 1.00 ≥5 13 7 (53.8) 2.3 (0.76–6.7) 0.15 2.39 (0.47–12.04) 0.29 CTC-clusters No 31 11 (35.5) 1.00 1.00 Yes 7 4 (57.1) 1.8 (0.55–5.9) 0.33 5.05 (1.24–20.52) 0.023 Associated with OS CTCs <5 25 3 (12.0) 1.00 1.00 ≥5 13 7 (53.8) 5.3 (1.4–21) 0.017 9.6 ×1017 (0.0-Inf) 0.996 CTC-clusters No 31 6 (19.4) 1.00 1.00 Yes 7 4 (57.1) 3 (0.83–11) 0.09 29.74 (2.55–345.8) 0.006 Abbreviations: CTC circulating tumor cell, PFS progression-free survival, OS overall survival, HR hazard ratio, CI confidence interval, Inf infinity. * Adjusted for age, ECOG, subtype, number of metastatic sites, site of metastasis and treatments. Cancers 2020,12, 1111 6 of 19 Cancers 2020, 12, x FOR PEER REVIEW 6 of 20 Figure 2. CTCs and CTC-clusters at baseline and follow up, in relation to progression-free survival (PFS) and overall survival (OS). Kaplan–Meier curves displaying PFS and OS at baseline based on CTC count (≥5 CTCs/7.5 ml of blood) (a, b) and CTC-cluster count (≥1 CTC-cluster/7.5 mL of blood) (c, d), and at follow up based on CTC count (e, f) and CTC-cluster count (g, h). Figure 2. CTCs and CTC-clusters at baseline and follow up, in relation to progression-free survival (PFS) and overall survival (OS). Kaplan–Meier curves displaying PFS and OS at baseline based on CTC count ( ≥ 5 CTCs/7.5 ml of blood) ( a , b ) and CTC-cluster count ( ≥ 1 CTC-cluster/7.5 mL of blood) ( c , d ), and at follow up based on CTC count (e,f) and CTC-cluster count (g,h). Cancers 2020,12, 1111 7 of 19 2.4. Joint Analysis of CTCs and CTC-Clusters for Patient Outcome Prediction We investigated the joint effect of CTCs and CTC-clusters in our cohort by classifying patients in the three risk groups previously described [ 27 ]: <5 CTCs without any CTC-cluster (low-risk), ≥ 5 CTCs without any CTC-cluster (medium-risk), and ≥ 5 CTCs with CTC-clusters (high-risk). Patients within the high-risk group had a shorter PFS and OS (P log-rank <0.01), and an increased risk of progression and death (HR PFS 4.3; 95% CI 1.76–10.6; p=0.0013; HR OS 5.8; 95% CI 1.96–17.1; p=0.0014) compared to patients with <5 CTC (Figure 3a,b, Table 3). The group of patients from the medium-risk group did not show increased risk of progression or mortality (HR PFS 1.24; 95% CI 0.47–3.24; p=0.66; HR OS 1.8; 95% CI 0.59–5.98; p=0.28). The prognostic value of CTC-clusters remained significant in the multivariate analysis when adjusting for different clinicopathological variables, including the site of metastasis, the only significant prognostic marker in multivariable analysis in this cohort (Table S3). These data indicate that in this cohort of patients, baseline CTC-clusters are an independent prognostic factor adding value to the enumeration of CTCs alone. In addition to this analysis, we also applied a previously described threshold of ≥ 20 CTCs [ 30 , 31 ], and analyzed its relationship with patient outcome. In an initial analysis, we observed that patients with ≥ 20 CTCs at baseline were at a higher risk of death than patients with ≥ 5 CTCs (Table S4). Interestingly, when we classified patients in risk groups based on the presence or absence of CTC-clusters, we found that patients with ≥ 20 CTCs and CTC-clusters had an increased risk of death compared with patients with <20 CTCs (HR 5.5; 95% CI 2.2–13.7; p=0.0002). The prognostic value of CTC-clusters remained significant in the multivariate analysis when adjusting for different clinicopathological variables. However, when we specifically looked at the group of patients with ≥ 20 CTCs, the presence of CTC-clusters did not add prognostic information (data not shown). When focusing on patients at follow up, we observed that patients with ≥ 5 CTCs without any CTC-cluster and patients with ≥ 5 CTCs and CTC-clusters had a shorter OS (P log-rank <0.05) and increased risk of death (HR OS 5.71; 95% CI 1.11–29.42; p=0.037, and HR OS 5.0; 95% CI 1.11–22.40; p=0.035, respectively) compared to patients with <5 CTC (Figure 3c,d, Table 3). However, in Cox regression analysis adjusting for different clinicopathological variables these effects were lost. No increased risk of progression was observed in either of both groups. Taken together, and in agreement with previous reports, CTC-clusters might provide independent prognostic value in patients with elevated CTCs, particularly at baseline. Table 3. Joint effect analysis of CTCs and CTC-clusters with patient PFS and OS. Variables Total Events, n(%) HR (95% CI) pValue HR (95% CI) * pValue * Joint effect of baseline CTC and CTC-clusters Associated with PFS <5 CTC without CTC-cluster 23 9 (39.13) 1.00 1.00 ≥5 CTC without CTC-cluster 17 9 (52.84) 1.24 (0.47–3.24) 0.66 1.74 (0.57–5.30) 0.32 ≥5 CTC, ≥1 CTC-cluster 14 11 (78.57) 4.34 (1.76–10.6) 0.0013 5.16 (1.68–15.8) 0.0041 Associated with OS <5 CTC without CTC-cluster 23 6 (26.1) 1.00 1.00 ≥5 CTC without CTC-cluster 17 7 (41.18) 1.88 (0.59–5.98) 0.28 1.84 (0.50–6.82) 0.36 ≥5 CTC, ≥1 CTC-cluster 14 10 (71.43) 5.79 (1.96–17.1) 0.0014 7.79 (1.93–31.4) 0.0038 Joint effect of first follow up CTC and CTC-clusters Associated with PFS <5 CTC without CTC-cluster 25 8 (32.0) 1.00 1 ≥5 CTC without CTC-cluster 6 3 (50.0) 2.3 (0.57–9.27) 0.24 0.61 (0.08–4.53) 0.635 ≥5 CTC, ≥1 CTC-cluster 7 4 (57.1) 2.2 (0.62–7.84) 0.22 4.45 (1.01–19.59) 0.0484 Associated with OS <5 CTC without CTC-cluster 25 3 (12.0) 1.00 1.00 ≥5 CTC without CTC-cluster 6 3 (50) 5.71 (1.11–29.4) 0.037 1.2 ×1018 (0.0-Inf) 0.996 ≥5 CTC, ≥1 CTC-cluster 7 4 (57.1) 5.00 (1.11–22.4) 0.0353 2.4 ×1018 (0.0-Inf) 0.996 Abbreviations: CTC circulating tumor cell, PFS progression-free survival, OS overall survival, HR hazard ratio, CI confidence interval, Inf infinity. * Adjusted for age, ECOG, subtype, number of metastatic sites, site of metastasis and treatments. Cancers 2020,12, 1111 8 of 19 Cancers 2020, 12, x FOR PEER REVIEW 8 of 20 Interestingly, when we classified patients in risk groups based on the presence or absence of CTCclusters, we found that patients with ≥20 CTCs and CTC-clusters had an increased risk of death compared with patients with <20 CTCs (HR 5.5; 95% CI 2.2–13.7; p = 0.0002). The prognostic value of CTC-clusters remained significant in the multivariate analysis when adjusting for different clinicopathological variables. However, when we specifically looked at the group of patients with ≥ 20 CTCs, the presence of CTC-clusters did not add prognostic information (data not shown). When focusing on patients at follow up, we observed that patients with ≥5 CTCs without any CTC-cluster and patients with ≥5 CTCs and CTC-clusters had a shorter OS (Plog-rank < 0.05) and increased risk of death (HROS 5.71; 95% CI 1.11–29.42; p = 0.037, and HROS 5.0; 95% CI 1.11–22.40; p = 0.035, respectively) compared to patients with <5 CTC (Figure 3c, d, Table 3). However, in Cox regression analysis adjusting for different clinicopathological variables these effects were lost. No increased risk of progression was observed in either of both groups. Taken together, and in agreement with previous reports, CTC-clusters might provide independent prognostic value in patients with elevated CTCs, particularly at baseline. Figure 3. Risk groups regarding PFS and OS based on CTC count and CTC-clusters. Kaplan–Meier curves displaying PFS and OS of patients with <5 CTC, patients with ≥5 CTCs without CTC-clusters and patients ≥5 CTCs with CTC-clusters at baseline (a, b) and follow up (c, d). Figure 3. Risk groups regarding PFS and OS based on CTC count and CTC-clusters. Kaplan–Meier curves displaying PFS and OS of patients with <5 CTC, patients with ≥ 5 CTCs without CTC-clusters and patients ≥5 CTCs with CTC-clusters at baseline (a,b) and follow up (c,d). 2.5. Patient Outcome Prediction Based on Baseline-to-Follow up Changes of CTCs and CTC-Clusters To evaluate CTCs and CTC-clusters as early predictors of progression, changes in CTC and CTC-cluster counts from baseline to follow up in relation to clinical outcomes were analyzed on the 38 patients, from whom samples were collected at both time points. Regarding CTC analysis, patients were classified in four groups: (i) <5 CTCs both at baseline and follow up; (ii) ≥ 5 CTCs at baseline and <5 CTCs at follow up; (iii) <5 CTCs at baseline and ≥ 5 CTCs at follow up; and (iv) ≥ 5 CTCs both at baseline and follow up. Only one patient from group iii (<5 CTCs at baseline and ≥ 5 CTCs at follow up) was found in this cohort, and it was not included in the posterior analysis. Changes in CTC counts from baseline to follow up were not able to predict patient outcomes in terms of PFS, although a significant effect was observed in terms of OS. Patients with ≥ 5 CTCs, both at baseline and follow up, showed a significantly shorter OS (P log-rank =0.037), and a higher risk of death, with a HR of 3.9 (95% CI 0.97–15.8; p=0.055) (Figure 4, Table 4). With regard to CTC-cluster analysis, patients were classified into two risk groups: i) low risk, comprised of patients without CTC-clusters at both time points or with a reduction in the number Cancers 2020,12, 1111 9 of 19 from baseline to follow up; and ii) high risk, comprised of patients whose CTC-cluster count did not change or increase over time. Changes in CTC-cluster counts from baseline to follow up were not able to predict patient outcome in terms of PFS and OS, however, for patients in the high risk group, there was a clear trend towards a shorter OS (P log-rank =0.07) and increased risk of death, with a HR of 2.96 (95% CI 0.83–10.5; p=0.09) (Figure 4, Table 4). Cancers 2020, 12, x FOR PEER REVIEW 10 of 20 Figure 4. Baseline-to-follow up changes in CTCs and CTC-clusters in relation to patient outcome. Based on CTC counts, Kaplan–Meier curves displaying PFS and OS for the three risk group established: <5 CTCs both at baseline (BL) and follow up (FU); ≥5 CTCs at BL and <5 CTCs at FU; and ≥5 CTCs both at BL and FU (a, b). Based on CTC-cluster counts, Kaplan–Meier curves displaying PFS and OS for the two risk groups established, patients without CTC-clusters at both time points or with a reduction in the number from BL to FU (low risk); and patients whose CTC-cluster count did not change or increase over time (high risk) (c, d). Cancers 2020, 12, x FOR PEER REVIEW 10 of 20 Figure 4. Baseline-to-follow up changes in CTCs and CTC-clusters in relation to patient outcome. Based on CTC counts, Kaplan–Meier curves displaying PFS and OS for the three risk group established: <5 CTCs both at baseline (BL) and follow up (FU); ≥5 CTCs at BL and <5 CTCs at FU; and ≥5 CTCs both at BL and FU (a, b). Based on CTC-cluster counts, Kaplan–Meier curves displaying PFS and OS for the two risk groups established, patients without CTC-clusters at both time points or with a reduction in the number from BL to FU (low risk); and patients whose CTC-cluster count did not change or increase over time (high risk) (c, d). Figure 4. Baseline-to-follow up changes in CTCs and CTC-clusters in relation to patient outcome. Based on CTC counts, Kaplan–Meier curves displaying PFS and OS for the three risk group established: <5 CTCs both at baseline (BL) and follow up (FU); ≥ 5 CTCs at BL and <5 CTCs at FU; and ≥ 5 CTCs both at BL and FU ( a , b ). Based on CTC-cluster counts, Kaplan–Meier curves displaying PFS and OS for the two risk groups established, patients without CTC-clusters at both time points or with a reduction in the number from BL to FU (low risk); and patients whose CTC-cluster count did not change or increase over time (high risk) (c,d). Cancers 2020,12, 1111 16 of 19 particles coated with an antibody, recognizing the epithelial cell adhesion molecule (EpCAM) antigen. Enriched cells were then stained with fluorescent antibodies against cytokeratins (CKs) 8, 18, and 19, CD45, and the double-stranded DNA stain DAPI, and scanned with the microscope CellTracks Analyzer II (Menarini Silicon Biosystems). Cells were presented in a gallery for manual evaluation by two trained technicians. CTCs were identified by round-oval morphology, positive staining for PE-conjugated CKs and DAPI, and negative staining for APC-conjugated CD45 antibodies, following the criteria previously described for the CellSearch system. CTC-clusters were defined as groups of two or more individual CTCs (CKs-PE and DAPI positive and CD45-APC negative staining), with distinct non-overlapping nuclei and intact cytoplasm membranes. No additional staining of CTCs was performed after the CellSearch analysis. In addition, the interaction of CTCs with white blood cells (WBC), defined by CD45-APC positive staining and DAPI, was evaluated. 4.3. Statistical Analysis Statistical power calculations were done for two groups (<5 CTC and ≥ 5 CTCs) based on the size of the groups, 23 and 31 patients respectively; hazard ratio 0.31 of <5 CTC relative to ≥ 5 CTCs, accrual period of 1624 days, and alpha level 0.05. The resulting power analysis was 0.887. The program PS, Power and Sample Size Calculation version 3.1.6, 2018 was used for these calculations. The endpoints analyzed in this study were progression-free survival (PFS) and overall survival (OS) in relation to the number of CTCs and CTC-clusters. PFS was defined as the time from blood sample collection to the date of clinical progression or death; and OS was defined as the time from blood collection to the date of death. Patients without an endpoint event at follow up were censored. Survival analysis was performed using Kaplan–Meier method and curves compared using log-rank test. Associations between CTC and CTC-cluster counts with PFS and OS were estimated using hazard ratios (HR) and 95% confidence intervals (CI), calculated by univariate and multivariate Cox proportional hazards models. Multivariable analyses were adjusted for age, ECOG, BC subtype, site of metastasis, number of metastatic sites and treatments. CTC characteristics, i.e. CTC-clusters and CTC-WBC cluster, across breast cancers subtypes and at different time-points were compared using a Pearson Chi-squared test. Data analyses were performed in the “R” open source software environment (version 3.4.4, https://www.r-project.org/) and GraphPad Prism (version 6.01, https://www.graphpad.com/). 5. Conclusions The evaluation of the presence of CTC-clusters in a heterogeneous and small real-world cohort of MBC patients supports that the enumeration of CTC-clusters at baseline is a strong independent predictor of PFS and OS in MBC patients, and that the longitudinal monitoring of CTC-clusters might increase their prognostic value. Moreover, our analysis shows that patients with CTC-cluster of a larger size are at a higher risk of death, and that the persistent presence of CTC-cluster in the blood of patients during the course of treatment is also a predictor of a worse patient outcome. These findings in our real-world cohort of patients also support the biological significance of CTC-clusters in tumor progression. Supplementary Materials: The following are available online at http://www.mdpi.com/2072-6694/12/5/1111/s1, Figure S1: Study design, Figure S2: Association between CTC count and the presence of CTC-clusters or CTC-WBC clusters at baseline and follow up. Table S1: Study cohort analysis of CTCs and CTC-clusters. Table S2: Distribution of baseline CTCs and CTC-clusters in different BC subtypes, Table S3: Multivariable Cox regression analysis of prognostic variables included in the clinicopathological model, Table S4: Cox regression analysis for CTC count ≥ 20 versus <20, and presence versus absence of CTC-clusters. Table S5: Longitudinal changes in CTCs and CTC-clusters on relation to PFS and OS. Author Contributions: C.C. and L.M.-R. were involved in the design and conception of the study, data analysis, interpretation of the data and drafting of the manuscript. V.C.-L. was involved in acquisition of data and providing clinical input. T.P.-V., I.M.-P. and M.A. were involved in data analysis and reviewing of the manuscript. A.A. and R.M.L.-L. were involved in sample processing and recruitment and morphological evaluation and enumeration. C.A. was involved in samples processing and recruitment. P.P. and J.C. were responsible for patient recruitment, providing patient samples and clinical input. R.P. was involved in design and conception of the study, data Cancers 2020,12, 1111 17 of 19 analysis, interpretation of the data and drafting and revision of the manuscript. R.L.-L. was involved in the design and conception of the study, interpretation of the data and drafting and revision of the manuscript. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by Roche-Chus Joint Unit (IN853B 2018/03), funded by Axencia Galega de Innovaci ó n (GAIN), Conseller í a de Econom í a, Emprego e Industria and by the Instituto de Salud Carlos III (ISCIII) and FEDER (PI13/01388). L.M.-R. is supported by Asociaci ó n Española Contra el C á ncer (AECC). I.M.-P. is funded by the Training Program for Academic Stafffellowship (FPU16/01018), from the Ministry of Education and Vocational Training, Spanish Government. Acknowledgments: We would like to thank the patients who had participated in this study, and all the personnel of the Oncology Service at the University Clinical Hospital of Santiago de Compostela, for their help with patient care and sample management. Conflicts of Interest: R.L.-L. reports grants and personal fees from Roche, Merck, AstraZeneca, Bayer, Pharmamar, Leo, and personal fees and non-financial support from Bristol-Myers Squibb and Novartis, outside of the submitted work. 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