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Heterogeneous circulating tumor cells correlate with responses to neoadjuvant chemotherapy and prognosis in patients with locally advanced breast cancer

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Abstract

Neoadjuvant chemotherapy (NCT) is the standard treatment for patients with locally advanced breast cancer (LABC). The predictive value of heterogeneous circulating tumor cells (CTCs) in NCT response has not been determined. All patients were staged as LABC, and blood samples were collected at the time of biopsy, and after the first and eighth NCT courses. Patients were divided into High responders (High-R) and Low responders (Low-R) according to Miller–Payne system and changes in Ki-67 levels after NCT treatment. A novel SE-i·FISH strategy was applied to detect CTCs. Heterogeneities were successfully analyzed in patients undergoing NCT. Total CTCs increased continuously and were higher in Low-R group, while in High-R group, CTCs increased slightly during NCT before returning to baseline levels. Triploid and tetraploid chromosome 8 increased in Low-R but not High-R group. The number of small CTCs in Low-R group increased significantly until the last sample, however, remained constant in High-R group. The patients with more CTCs had shorter PFS and OS than those with less CTCs after the eighth course of NCT. Total CTCs following NCT could predict patients’ responses. More detailed characterizations of CTC blood profiles may improve predictive capacity and treatments of LABC.

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Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files. Other remaining data and materials are available from the authors upon reasonable request.

References

  1. Sung H et al (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3):209–249

    Article  PubMed  Google Scholar 

  2. Yamauchi K et al (2008) Induction of cancer metastasis by cyclophosphamide pretreatment of host mice: an opposite effect of chemotherapy. Cancer Res 68(2):516–520

    CAS  PubMed  Google Scholar 

  3. Comen E, Norton L, Massagué J (2011) Clinical implications of cancer self-seeding. Nat Rev Clin Oncol 8(6):369–377

    PubMed  Google Scholar 

  4. Bidard FC et al (2018) Circulating tumor cells in breast cancer patients treated by neoadjuvant chemotherapy: a meta-analysis. J Natl Cancer Inst 110(6):560–567

    PubMed  Google Scholar 

  5. Caixeiro NJ et al (2014) Circulating tumour cells–a bona fide cause of metastatic cancer. Cancer Metastasis Rev 33(2–3):747–756

    CAS  PubMed  Google Scholar 

  6. Molloy TJ et al (2011) The prognostic significance of tumour cell detection in the peripheral blood versus the bone marrow in 733 early-stage breast cancer patients. Breast Cancer Res 13(3):R61

    PubMed  PubMed Central  Google Scholar 

  7. Chong MH et al (2012) The dynamic change of circulating tumour cells in patients with operable breast cancer before and after chemotherapy based on a multimarker QPCR platform. Br J Cancer 106(10):1605–1610

    CAS  PubMed  PubMed Central  Google Scholar 

  8. van Dalum G et al (2015) Circulating tumor cells before and during follow-up after breast cancer surgery. Int J Oncol 46(1):407–413

    PubMed  Google Scholar 

  9. Nolé F et al (2008) Variation of circulating tumor cell levels during treatment of metastatic breast cancer: prognostic and therapeutic implications. Ann Oncol 19(5):891–897

    PubMed  Google Scholar 

  10. Pierga JY et al (2017) Circulating tumour cells and pathological complete response: independent prognostic factors in inflammatory breast cancer in a pooled analysis of two multicentre phase II trials (BEVERLY-1 and -2) of neoadjuvant chemotherapy combined with bevacizumab. Ann Oncol 28(1):103–109

    PubMed  Google Scholar 

  11. Riethdorf S et al (2017) Prognostic impact of circulating tumor cells for breast cancer patients treated in the neoadjuvant “Geparquattro” trial. Clin Cancer Res 23(18):5384–5393

    CAS  PubMed  Google Scholar 

  12. Andergassen U et al (2016) Real-time RT-PCR systems for CTC detection from blood samples of breast cancer and gynaecological tumour patients (review). Oncol Rep 35(4):1905–1915

    CAS  PubMed  Google Scholar 

  13. Ozkumur E et al (2013) Inertial focusing for tumor antigen-dependent and -independent sorting of rare circulating tumor cells. Sci Transl Med 5(179):17947

    Google Scholar 

  14. Passerini V et al (2016) The presence of extra chromosomes leads to genomic instability. Nat Commun 7:10754

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Gordon DJ, Resio B, Pellman D (2012) Causes and consequences of aneuploidy in cancer. Nat Rev Genet 13(3):189–203

    CAS  PubMed  Google Scholar 

  16. Kops GJ, Weaver BA, Cleveland DW (2005) On the road to cancer: aneuploidy and the mitotic checkpoint. Nat Rev Cancer 5(10):773–785

    CAS  PubMed  Google Scholar 

  17. Ogston KN et al (2003) A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival. Breast 12(5):320–327

    PubMed  Google Scholar 

  18. Lin PP (2015) Integrated EpCAM-independent subtraction enrichment and iFISH strategies to detect and classify disseminated and circulating tumors cells. Clin Transl Med 4(1):38

    PubMed  PubMed Central  Google Scholar 

  19. Lin PP et al (2017) Comprehensive in situ co-detection of aneuploid circulating endothelial and tumor cells. Sci Rep 7(1):9789

    PubMed  PubMed Central  Google Scholar 

  20. Magee R, Rigoutsos I (2020) On the expanding roles of tRNA fragments in modulating cell behavior. Nucleic Acids Res 48(17):9433–9448

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Heitzer E et al (2019) Current and future perspectives of liquid biopsies in genomics-driven oncology. Nat Rev Genet 20(2):71–88

    CAS  PubMed  Google Scholar 

  22. Matikas A et al (2022) Detection of circulating tumour cells before and following adjuvant chemotherapy and long-term prognosis of early breast cancer. Br J Cancer 126(11):1563–1569

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Pierga JY et al (2008) Circulating tumor cell detection predicts early metastatic relapse after neoadjuvant chemotherapy in large operable and locally advanced breast cancer in a phase II randomized trial. Clin Cancer Res 14(21):7004–7010

    CAS  PubMed  Google Scholar 

  24. Onstenk W et al (2015) Improved circulating tumor cell detection by a combined EpCAM and MCAM cell search enrichment approach in patients with breast cancer undergoing neoadjuvant chemotherapy. Mol Cancer Ther 14(3):821–827

    CAS  PubMed  Google Scholar 

  25. Kasimir-Bauer S et al (2016) Does primary neoadjuvant systemic therapy eradicate minimal residual disease? Analysis of disseminated and circulating tumor cells before and after therapy. Breast Cancer Res 18(1):20

    PubMed  PubMed Central  Google Scholar 

  26. Mego M et al (2012) Expression of epithelial-mesenchymal transition-inducing transcription factors in primary breast cancer: The effect of neoadjuvant therapy. Int J Cancer 130(4):808–816

    CAS  PubMed  Google Scholar 

  27. Li X et al (2018) Clinical significance of detecting CSF-derived tumor cells in breast cancer patients with leptomeningeal metastasis. Oncotarget 9(2):2705–2714

    PubMed  Google Scholar 

  28. Zhang J et al (2018) Circulating tumor cells with karyotyping as a novel biomarker for diagnosis and treatment of nasopharyngeal carcinoma. BMC Cancer 18(1):1133

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Ye Z et al (2019) Detecting and phenotyping of aneuploid circulating tumor cells in patients with various malignancies. Cancer Biol Ther 20(4):546–551

    CAS  PubMed  Google Scholar 

  30. Luo S et al (2021) Optimal strategy for colorectal cancer patients’ diagnosis based on circulating tumor cells and circulating tumor endothelial cells by subtraction enrichment and immunostaining-fluorescence in situ hybridization combining with CEA and CA19-9. J Oncol 2021:1517488

    PubMed  PubMed Central  Google Scholar 

  31. Lin AY et al (2021) Identification and comprehensive co-detection of necrotic and viable aneuploid cancer cells in peripheral blood. Cancers (Basel) 13(20):5108

    CAS  PubMed  Google Scholar 

  32. Zhang T et al (2021) Role of aneuploid circulating tumor cells and CD31(+) circulating tumor endothelial cells in predicting and monitoring anti-angiogenic therapy efficacy in advanced NSCLC. Mol Oncol 15(11):2891–2909

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Mi J et al (2022) Case report: post-therapeutic laryngeal carcinoma patient possessing a high ratio of aneuploid CTECs to CTCs rapidly developed de novo malignancy in pancreas. Front Oncol 12:981907

    PubMed  PubMed Central  Google Scholar 

  34. Camara O et al (2007) The relevance of circulating epithelial tumor cells (CETC) for therapy monitoring during neoadjuvant (primary systemic) chemotherapy in breast cancer. Ann Oncol 18(9):1484–1492

    CAS  PubMed  Google Scholar 

  35. Ignatiadis M et al (2008) Prognostic value of the molecular detection of circulating tumor cells using a multimarker reverse transcription-PCR assay for cytokeratin 19, mammaglobin A, and HER2 in early breast cancer. Clin Cancer Res 14(9):2593–2600

    CAS  PubMed  Google Scholar 

  36. Pachmann K et al (2008) Monitoring the response of circulating epithelial tumor cells to adjuvant chemotherapy in breast cancer allows detection of patients at risk of early relapse. J Clin Oncol 26(8):1208–1215

    PubMed  Google Scholar 

  37. Fisher B, Fisher ER (1967) The organ distribution of disseminated 51 Cr-labeled tumor cells. Cancer Res 27(2):412–420

    CAS  PubMed  Google Scholar 

  38. Fisher B, Fisher ER, Feduska N (1967) Trauma and the localization of tumor cells. Cancer 20(1):23–30

    CAS  PubMed  Google Scholar 

  39. Miglietta L et al (2010) Prognostic value of estrogen receptor and Ki-67 index after neoadjuvant chemotherapy in locally advanced breast cancer expressing high levels of proliferation at diagnosis. Oncology 79(3–4):255–261

    CAS  PubMed  Google Scholar 

  40. Li L et al (2017) Prognostic values of Ki-67 in neoadjuvant setting for breast cancer: a systematic review and meta-analysis. Future Oncol 13(11):1021–1034

    CAS  PubMed  Google Scholar 

  41. Miglietta L et al (2013) A prognostic model based on combining estrogen receptor expression and Ki-67 value after neoadjuvant chemotherapy predicts clinical outcome in locally advanced breast cancer: extension and analysis of a previously reported cohort of patients. Eur J Surg Oncol 39(10):1046–1052

    CAS  PubMed  Google Scholar 

  42. Lee AJ et al (2011) Chromosomal instability confers intrinsic multidrug resistance. Cancer Res 71(5):1858–1870

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Li Y et al (2014) Clinical significance of phenotyping and karyotyping of circulating tumor cells in patients with advanced gastric cancer. Oncotarget 5(16):6594–6602

    PubMed  PubMed Central  Google Scholar 

  44. Wan JF et al (2018) Aneuploidy of chromosome 8 and mutation of circulating tumor cells predict pathologic complete response in the treatment of locally advanced rectal cancer. Oncol Lett 16(2):1863–1868

    PubMed  PubMed Central  Google Scholar 

  45. Li Y et al (2018) Evolutionary expression of HER2 conferred by chromosome aneuploidy on circulating gastric cancer cells contributes to developing targeted and chemotherapeutic resistance. Clin Cancer Res 24(21):5261–5271

    CAS  PubMed  Google Scholar 

  46. Ito H et al (2016) Change in number and size of circulating tumor cells with high telomerase activity during treatment of patients with gastric cancer. Oncol Lett 12(6):4720–4726

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Aceto N et al (2014) Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell 158(5):1110–1122

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhang D et al (2017) Circulating tumor microemboli (CTM) and vimentin+ circulating tumor cells (CTCs) detected by a size-based platform predict worse prognosis in advanced colorectal cancer patients during chemotherapy. Cancer Cell Int 17:6

    PubMed  PubMed Central  Google Scholar 

  49. Li QQ et al (2011) Involvement of NF-kappaB/miR-448 regulatory feedback loop in chemotherapy-induced epithelial-mesenchymal transition of breast cancer cells. Cell Death Differ 18(1):16–25

    PubMed  Google Scholar 

  50. Chockley PJ et al (2018) Epithelial-mesenchymal transition leads to NK cell-mediated metastasis-specific immunosurveillance in lung cancer. J Clin Invest 128(4):1384–1396

    PubMed  PubMed Central  Google Scholar 

  51. Somasundaram R, Herlyn D (2009) Chemokines and the microenvironment in neuroectodermal tumor-host interaction. Semin Cancer Biol 19(2):92–96

    CAS  PubMed  Google Scholar 

  52. Coupland LA, Chong BH, Parish CR (2012) Platelets and P-selectin control tumor cell metastasis in an organ-specific manner and independently of NK cells. Cancer Res 72(18):4662–4671

    CAS  PubMed  Google Scholar 

  53. Reymond N, d’Agua BB, Ridley AJ (2013) Crossing the endothelial barrier during metastasis. Nat Rev Cancer 13(12):858–870

    CAS  PubMed  Google Scholar 

  54. Smerage JB et al (2014) Circulating tumor cells and response to chemotherapy in metastatic breast cancer: SWOG S0500. J Clin Oncol 32(31):3483–3489

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Kim YR et al (2018) Selective killing of circulating tumor cells prevents metastasis and extends survival. J Hematol Oncol 11(1):114

    PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors wish to thank all the patients and family members for participating in this study.

Funding

This work was supported by the Natural Science Foundation of China (81572607, 82203118 and 81572602).

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Author notes

  1. Ge Ma, Jingyi Wang and Jingyue Fu contributed equally to this work.

Authors and Affiliations

  1. Department of Breast Surgery, The First Affiliated Hospital With Nanjing Medical University, 300 Guang-Zhou Road, Nanjing, 210029, China

    Ge Ma, Jingyue Fu, Rui Chen, Mengdi Liang, Minghui Li, Tiansong Xia, Xiaoan Liu & Shui Wang

  2. Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, 211166, China

    Ge Ma, Tiansong Xia & Shui Wang

  3. Department of Breast Surgery, The Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University, 29 Xinglong Lane, Changzhou, 213003, China

    Jingyi Wang

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  1. Ge Ma
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Contributions

GM carried out the conceptualization, project administration, formal analysis, writing – original draft, and writing – review and editing. JW carried out project administration and data analysis. JF carried out the data curation and methodology. RC participated in project administration and data processing. ML participated in writing – original draft and writing – review and editing. ML carried out the data analysis. TX carried out the conceptualization and project administration. XL carried out the conceptualization and funding acquisition. SW carried out the conceptualization, supervision, and funding acquisition.

Corresponding authors

Correspondence to Tiansong Xia, Xiaoan Liu or Shui Wang.

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Conflict of interest

The authors declared no potential conflicts of interest. Prior presentation: This work has been presented in part at the 2019 ASCO Annual Meeting.

Ethical approval

Samples were collected at the First Affiliated Hospital with Nanjing Medical University. Ethics approval was obtained from the institutional ethics committee of the First Affiliated Hospital with Nanjing Medical University.

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Written informed consent was obtained from all participants.

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Ma, G., Wang, J., Fu, J. et al. Heterogeneous circulating tumor cells correlate with responses to neoadjuvant chemotherapy and prognosis in patients with locally advanced breast cancer. Breast Cancer Res Treat 201, 27–41 (2023). https://doi.org/10.1007/s10549-023-06942-y

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