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

Publication/Presentation Date

1-1-2017

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.

Volume

161

Issue

1

First Page

83

Last Page

94

ISSN

1573-7217

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

27771841

Department(s)

Administration and Leadership

Document Type

Article

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