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Simultaneous detection of circulating immunological parameters and tumor biomarkers in early stage breast cancer patients during adjuvant chemotherapy

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Abstract

Background

Chemotherapy-induced immune suppression has mainly been studied in patients with advanced cancer, but the influence of chemotherapy on the immune system in early stage cancer patients has so far not been studied systematically. The aim of the present study was to monitor the immune system during anthracycline- and taxane-based adjuvant chemotherapy in early stage breast cancer patients, to assess the impact of circulating tumor cells on selected immune parameters and to reveal putative angiogenic effects of circulating endothelial cells.

Methods

Peripheral blood samples from 20 early stage breast cancer patients were analyzed using a flow cytometric multi-color of antibodies to enumerate lymphocyte and dendritic cell subsets, as well as endothelial and tumor cells. An enzyme-linked immunosorbent assay (ELISA) was used to measure the levels of various serological factors.

Results

During chemotherapy, all immunological parameters and angiogenesis surrogate biomarkers showed significant decreases. The numbers of circulating tumor cells showed significant inverse correlations with the numbers of T helper cells, a lymphocyte subset directly related to effective anti-tumor responses. Reduced T helper cell numbers may contribute to systemic immunosuppression and, as such, the activation of dormant tumor cells.

Conclusions

From our results we conclude that adjuvant chemotherapy suppresses immune function in early stage breast cancer patients. In addition, we conclude that the presence of circulating tumor cells, defined as pan-cytokeratin+, CD326+, CD45− cells, may serve as an important indicator of a patient’s immune status. Further investigations are needed to firmly define circulating tumor cells as a predictor for the success of breast cancer adjuvant chemotherapy.

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Acknowledgments

We wish to thank all the patients and volunteers for taking part in the study, as well as the nursing and the medical staff of the Oncologic Unit at the Fondazione IRCCS Policlinico San Matteo, for their support in the acquisition of clinical samples. The authors thank Giorgia Testa and Sabrina Nigrisoli (SC Pediatria, Laboratorio di Immuno Allergologia, Fondazione IRCCS Policlinico S. Matteo, Pavia) for technical support and Paul Baines (Cardiff, UK) for English language support.

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Authors and Affiliations

  1. SC Oncologia e Laboratorio di Citofluorimetria, e Terapie Cellulari, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

    B. Rovati, S. Mariucci, S. Delfanti, D. Grasso & P. Pedrazzoli

  2. Servizio di Biometria e Statistica Medica, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

    C. Tinelli

  3. SC Pediatria, Laboratorio di Immuno Allergologia, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy

    C. Torre & M. De Amici

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  1. B. Rovati
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  2. S. Mariucci
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  3. S. Delfanti
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  4. D. Grasso
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  5. C. Tinelli
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  8. P. Pedrazzoli
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Correspondence to B. Rovati.

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All procedures involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Conflict of interest

The authors declare that they have no conflict of interest.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Funding

This work was supported by the Fondazione IRCCS Policlinico San Matteo, Pavia (Hospital Research grant n° 08067611 to P. Pedrazzoli) and “quota 5×1000 dell’imposta su reddito delle persone fisiche” designed for health research.

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Fig. 1s

Flow cytometric dot plot panels show a representative example on the gating utilized for the identification of circulating CD4 T cell memory. Panel a: CD4 lymphocyte subset identified by anti-CD4 and -CD3 expression markers; Panel b: CD4 memory subset identified from anti-CD45RO expression marker versus SSC. Panel c: the CD4 central and effector memory subsets identified from anti-CD45RO and -CD62L expression markers. The population identified by CD4+CD45RO+ overlaps to the sum of population CD4+CD45RO+CD62L+ (central memory) and CD4+CD45RO+CD62L- (effector memory) defined by CD45RO and CD62L expression markers. (PPT 144 kb)

Fig. 2s

Flow cytometric dot plot panels show an example a staining of CD25 against FoxP3 in breast cancer patients as compared to healthy females. Panels a and d show CD4 lymphocyte subset defined from anti-CD3 and -CD4 expression markers. Panels b and e show the CD4+ CD25+cells subset identified from anti-CD4 and -CD25 expression markers; Panels c and f show the T regulatory cell subset (Treg) identified by anti-FoxP3 and -CD25 expression markers. The count of Treg subset, in breast cancer patients (Panel c) as in the healthy females (Panel f), is lower to 1%. This data suggest that the CD4+CD25+ cells in these patients, are activated and not therapy resistant T regulatory cells. (PPT 248 kb)

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Rovati, B., Mariucci, S., Delfanti, S. et al. Simultaneous detection of circulating immunological parameters and tumor biomarkers in early stage breast cancer patients during adjuvant chemotherapy. Cell Oncol. 39, 211–228 (2016). https://doi.org/10.1007/s13402-015-0264-2

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