Purpose: Circulating tumor cell (CTC) is a well-established prognosis predictor for metastatic breast cancer (MBC), and CTC-cluster exhibits significantly higher metastasis-promoting capability than individual CTCs. Because measurement of CTCs and CTC-clusters at a single time point may underestimate their prognostic values, we aimed to analyze longitudinally collected CTCs and CTC-clusters in MBC prognostication. Methods: CTCs and CTC-clusters were enumerated in 370 longitudinally collected blood samples from 128 MBC patients. The associations between baseline, first follow-up, and longitudinal enumerations of CTCs and CTC-clusters with patient progression-free survival (PFS) and overall survival (OS) were analyzed using Cox proportional hazards models. Results: CTC and CTC-cluster counts at both baseline and first follow-up were significantly associated with patient PFS and OS. Time-dependent analysis of longitudinally collected samples confirmed the significantly unfavorable PFS and OS in patients with ≥5 CTCs, and further demonstrated the independent prognostic values by CTC-clusters compared to CTC-enumeration alone. Longitudinal analyses also identified a link between the size of CTC-clusters and patient OS: compared to the patients without any CTC, those with 2-cell CTC-clusters and ≥3-cell CTC-clusters had a hazard ratio (HR) of 7.96 [95 % confidence level (CI) 2.00–31.61, P = 0.003] and 14.50 (3.98–52.80, P < 0.001), respectively. Conclusions: In this novel time-dependent analysis of longitudinally collected CTCs and CTC-clusters, we showed that CTC-clusters added additional prognostic values to CTC enumeration alone, and a larger-size CTC-cluster conferred a higher risk of death in MBC patients.

Longitudinally collected CTCs and CTC-clusters and clinical outcomes of metastatic breast cancer / C. Wang, Z. Mu, I. Chervoneva, L. Austin, Z. Ye, G. Rossi, J.P. Palazzo, C. Sun, M. Abu-Khalaf, R.E. Myers, Z. Zhu, Y. Ba, B. Li, L. Hou, M. Cristofanilli, H. Yang. - In: BREAST CANCER RESEARCH AND TREATMENT. - ISSN 0167-6806. - 161:1(2017), pp. 83-94. [10.1007/s10549-016-4026-2]

Longitudinally collected CTCs and CTC-clusters and clinical outcomes of metastatic breast cancer

G. Rossi;
2017

Abstract

Purpose: Circulating tumor cell (CTC) is a well-established prognosis predictor for metastatic breast cancer (MBC), and CTC-cluster exhibits significantly higher metastasis-promoting capability than individual CTCs. Because measurement of CTCs and CTC-clusters at a single time point may underestimate their prognostic values, we aimed to analyze longitudinally collected CTCs and CTC-clusters in MBC prognostication. Methods: CTCs and CTC-clusters were enumerated in 370 longitudinally collected blood samples from 128 MBC patients. The associations between baseline, first follow-up, and longitudinal enumerations of CTCs and CTC-clusters with patient progression-free survival (PFS) and overall survival (OS) were analyzed using Cox proportional hazards models. Results: CTC and CTC-cluster counts at both baseline and first follow-up were significantly associated with patient PFS and OS. Time-dependent analysis of longitudinally collected samples confirmed the significantly unfavorable PFS and OS in patients with ≥5 CTCs, and further demonstrated the independent prognostic values by CTC-clusters compared to CTC-enumeration alone. Longitudinal analyses also identified a link between the size of CTC-clusters and patient OS: compared to the patients without any CTC, those with 2-cell CTC-clusters and ≥3-cell CTC-clusters had a hazard ratio (HR) of 7.96 [95 % confidence level (CI) 2.00–31.61, P = 0.003] and 14.50 (3.98–52.80, P < 0.001), respectively. Conclusions: In this novel time-dependent analysis of longitudinally collected CTCs and CTC-clusters, we showed that CTC-clusters added additional prognostic values to CTC enumeration alone, and a larger-size CTC-cluster conferred a higher risk of death in MBC patients.
Circulating tumor cell clusters (CTC-clusters); Circulating tumor cells (CTCs); Metastatic breast cancer (MBC); Prognosis; Time-dependent analysis
Settore MEDS-09/A - Oncologia medica
2017
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1121023
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