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Background: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy.Methods: Serial CTC data from 469 patients (2202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs, combined CTC status at baseline to the end of cycle 1, and tCTC. Akaike information criterion was used to select the model that best predicted PFS and OS.Results: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (56.9% ), low (23.7%), intermediate (14.5%), or high (4.9%). Patients with low, intermediate, and high tCTC patterns had statistically significant inferior PFS and OS compared with those with undetectable CTCs (P < .001). Akaike Information Criterion indicated that the tCTC model best predicted PFS and OS compared with baseline CTCs and combined CTC status at baseline to the end of cycle 1 models. Validation studies in an independent cohort of 1856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model.Conclusions: We identified 4 novel prognostic groups in MBC based on similarities in tCTC patterns during chemotherapy. Prognostic groups included patients with very poor outcome (intermediate + high CTCs, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be used for fine-tuning of CTC-based risk stratification strategies to guide future prospective clinical trials in MBC. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The prevalence of breast cancer is increasing as more women are living with the disease. Outcomes have improved as a result of progress in all major aspects of multidisciplinary care. These include surgery, radiotherapy, hormonal therapy, chemotherapy and newer targeted drugs. Two aspects merit particular attention here. First, there is an understanding now that cancer is a heterogenous disease and a 'one-size-fits-all' approach is becoming redundant, albeit slowly. Second, basic science and an appreciation of cellular molecular targets in those different types of breast cancer is being translated into the clinic and has led to the development of exciting new drugs for both triple negative and HER2-positive relapsed disease. An improved understanding of endocrine resistance remains an unmet need in drug development and here, it appears worthwhile to adopt less conventional approaches. Better trial design with a focus on biomarkers should lower barriers to regulatory approval as well as increase cost effectiveness. [ABSTRACT FROM AUTHOR]