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Prognostic value of tumor cell DNA content determined by flow cytometry using formalin-fixed paraffin-embedded breast cancer tissues

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Abstract

Purpose

The use of formalin-fixed paraffin-embedded (FFPE) tumor tissues in flow cytometry (FCM)-based determination of tumor cell DNA content is more complicated than the use of fresh-frozen tissues. This study aimed to accurately measure tumor cell DNA content from FFPE tissues by separating tumor cells from stromal cells through FCM and investigating its prognostic impact.

Methods

We separately measured the DNA contents of tumor cells and stromal cells by gating with pan-cytokeratin and vimentin (FCMC/V). We evaluated tumor cell DNA contents [DNA index (DI)] of 290 FFPE tumor tissues and classified them into low and high DI groups, using a cutoff DI value determined through an unbiased computational method.

Results

The distribution of DI was bimodal, and a cutoff value was determined at a DI of 1.26. The high-DI tumors were associated with aggressive phenotypes and had significantly worse distant recurrence-free intervals (DRFI) than low-DI tumors. Multivariate analysis revealed that lymph node metastasis, Ki67, and DI were independent factors affecting DRFI. Accordingly, patients with low-DI/low-Ki67 tumors had excellent outcomes compared with other tumor types. Multiploid tumors were associated with increased lymphocytic infiltration and aggressive phenotypes.

Conclusions

The DI of FFPE tumors could be precisely determined through FCMC/V. A combination of DI and Ki67 analyses may be able to predict the prognoses of breast cancer patients with greater accuracy.

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References

  1. Pinto AE, André S, Soares J (1999) Short-term significance of DNA ploidy and cell proliferation in breast carcinoma: a multivariate analysis of prognostic markers in a series of 308 patients. J Clin Pathol 52:604–611

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Clark GM, Dressler LG, Owens MA, Pounds G, Oldaker T, McGuire WL (1989) Prediction of relapse or survival in patients with node-negative breast cancer by DNA flow cytometry. N Engl J Med 320:627–633

    Article  CAS  PubMed  Google Scholar 

  3. Michels JJ, Duigou F, Marnay J, Denoux Y, Delozier T, Chasle J (2003) Flow cytometry in primary breast carcinomas: prognostic impact of multiploidy and hypoploidy. Cytometry B Clin Cytom. 55:37–45

    Article  PubMed  Google Scholar 

  4. Pinto AE, Pereira T, Santos M et al (2013) DNA ploidy is an independent predictor of survival in breast invasive ductal carcinoma: a long-term multivariate analysis of 393 patients. Ann Surg Oncol 20:1530–1537

    Article  PubMed  Google Scholar 

  5. Hedley DW, Clark GM, Cornelisse CJ, Killander D, Kute T, Merkel D (1993) DNA cytometry consensus conference. Consensus review of the clinical utility of DNA cytometry in carcinoma of the breast. Breast Cancer Res Treat. 28:55–59

    Article  CAS  PubMed  Google Scholar 

  6. Shankey TV, Rabinovitch PS, Bagwell B et al (1993) Guidelines for implementation of clinical DNA cytometry. International Society for Analytical Cytology. Cytometry 14:472–477

    Article  CAS  Google Scholar 

  7. Ormerod MG, Tribukait B, Giaretti W (1998) Consensus report of the task force on standardisation of DNA flow cytometry in clinical pathology. DNA Flow Cytometry Task Force of the European Society for Analytical Cellular Pathology. Anal Cell Pathol 17:103–110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Corver WE, ter Haar NT (2011) High-resolution multiparameter DNA flow cytometry for the detection and sorting of tumor and stromal subpopulations from paraffin-embedded tissues. Curr Protoc Cytom. 55:7.37.1–7.37.21

    Google Scholar 

  9. Dayal JH, Sales MJ, Corver WE et al (2013) Multiparameter DNA content analysis identifies distinct groups in primary breast cancer. Br J Cancer 108:873–880

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Elston CW, Ellis IO (1991) Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology. 19:403–410

    Article  CAS  PubMed  Google Scholar 

  11. Layfield LJ, Saria EA, Conlon DH, Kerns BJ (1996) Estrogen and progesterone receptor status determined by the Ventana ES 320 automated immunohistochemical stainer and the CAS 200 image analyzer in 236 early-stage breast carcinomas: prognostic significance. J Surg Oncol 61:177–184

    Article  CAS  PubMed  Google Scholar 

  12. Morimoto K, Kim SJ, Tanei T et al (2009) Stem cell marker aldehyde dehydrogenase 1-positive breast cancers are characterized by negative estrogen receptor, positive human epidermal growth factor receptor type 2, and high Ki67 expression. Cancer Sci 100:1062–1068

    Article  CAS  PubMed  Google Scholar 

  13. Wolff AC, Hammond ME, Hicks DG et al (2013) Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J Clin Oncol 31:3997–4013

    Article  Google Scholar 

  14. Salgado R, Denkert C, Demaria S et al (2015) The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann Oncol 26:259–271

    Article  CAS  Google Scholar 

  15. Cornelisse CJ, van de Velde CJ, Caspers RJ, Moolenaar AJ, Hermans J (1987) DNA ploidy and survival in breast cancer patients. Cytometry 8:225–234

    Article  CAS  PubMed  Google Scholar 

  16. Kimmig R, Wimberger P, Kapsner T, Hillemanns P (2001) Flow cytometric DNA analysis using cytokeratin labeling for identification of tumor cells in carcinomas of the breast and the female genital tract. Anal Cell Pathol 22:165–178

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Budczies J, Klauschen F, Sinn BV et al (2012) Cutoff Finder: a comprehensive and straightforward web application enabling rapid biomarker cutoff optimization. PLoS ONE 7:e51862

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Hedley DW, Rugg CA, Gelber RD (1987) Association of DNA index and S-phase fraction with prognosis of nodes positive early breast cancer. Cancer Res 47:4729–4735

    CAS  PubMed  Google Scholar 

  19. Beerman H, Smit VT, Kluin PM, Bonsing BA, Hermans J, Cornelisse CJ (1991) Flow cytometric analysis of DNA stemline heterogeneity in primary and metastatic breast cancer. Cytometry 12:147–154

    Article  CAS  PubMed  Google Scholar 

  20. Lawry J, Rogers K, Duncan JL, Potter CW (1993) The identification of informative parameters in the flow cytometric analysis of breast carcinoma. Eur J Cancer 29A:719–723

    Article  CAS  PubMed  Google Scholar 

  21. Kallioniemi OP, Blanco G, Alavaikko M et al (1988) Improving the prognostic value of DNA flow cytometry in breast cancer by combining DNA index and S-phase fraction. A proposed classification of DNA histograms in breast cancer. Cancer. 62:2183–2190

    Article  CAS  PubMed  Google Scholar 

  22. Sparano JA, Gray RJ, Makower DF et al (2018) Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med 379:111–121

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Dieci MV, Mathieu MC, Guarneri V et al (2015) Prognostic and predictive value of tumor-infiltrating lymphocytes in two phase III randomized adjuvant breast cancer trials. Ann Oncol 26:1698–1704

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank Dr. Jun-ichiro Ikeda (Department of Pathology, Osaka University Hospital) for pathological evaluation and Dr. Wataru Kikuchi (Nittobo Medical co., ltd.) for technical assistance. This study was supported in part by the research funding from Nittobo Medical, Tokyo, Japan.

Funding

This study was supported in part by Japan Agency for Medical Research and Development under Grant Number JP17he1302014.

Author information

Authors and Affiliations

  1. Department of Breast and Endocrine Surgery, Osaka University Graduate School of Medicine, 2-2-E10 Yamadaoka, Suita, Osaka, 565-0871, Japan

    Hiroki Kusama, Masafumi Shimoda, Tomohiro Miyake, Tomonori Tanei, Naofumi Kagara, Yasuto Naoi, Kenzo Shimazu, Seung Jin Kim & Shinzaburo Noguchi

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  1. Hiroki Kusama
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  2. Masafumi Shimoda
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  3. Tomohiro Miyake
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  4. Tomonori Tanei
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  5. Naofumi Kagara
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  6. Yasuto Naoi
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  7. Kenzo Shimazu
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  8. Seung Jin Kim
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  9. Shinzaburo Noguchi
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Corresponding author

Correspondence to Masafumi Shimoda.

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Conflict of interest

Noguchi S. has been an adviser for Taiho, AstraZeneca and Novartis and has received honoraria and research funding for the other studies from AstraZeneca, Pfizer, Novartis, Chugai, Takeda, Nippon-Kayaku, Nittobo, and Sysmex.

Ethical approval

All procedures performed in studies 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.

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Electronic supplementary material

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10549_2019_5222_MOESM1_ESM.pdf

Supplementary material 1 (PDF 480 kb) Figure S1. (a) Classification of breast tumors into high-DI and low-DI tumors by FCMC/V and conventional FCM without gating. Migration from high-DI (FCMC/V) to low-DI (conventional FCM) was observed in 41 tumors and that from low-DI to high-DI in 8 tumors. (b) DRFI of patients with breast cancer of which DI was determined by the conventional FCM. Log-rank P values are shown

10549_2019_5222_MOESM2_ESM.pdf

Supplementary material 2 (PDF 440 kb) Figure S2. Kaplan–Meier curves of DRFI of patients with HR +/HER2−, node-negative breast cancer receiving no chemotherapy. Log-rank P values are shown

Supplementary material 3 (DOCX 14 kb) Table S1. Regimens for adjuvant systemic therapy

10549_2019_5222_MOESM4_ESM.docx

Supplementary material 4 (DOCX 26 kb) Table S2. Univariate and multivariate analyses of clinicopathological factors including the combination of DI and Ki67 in association with DRFI of all patients

10549_2019_5222_MOESM5_ESM.docx

Supplementary material 5 (DOCX 24 kb) Table S3. Univariate and multivariate analyses of clinicopathological factors including the combination of DI and Ki67 in association with DRFI of the hormone receptor-positive and HER2-negative subset

10549_2019_5222_MOESM6_ESM.docx

Supplementary material 6 (DOCX 26 kb) Table S4. Univariate and multivariate analyses of clinicopathological factors including the combination of DI and ploidy in association with DRFI of all patients

10549_2019_5222_MOESM7_ESM.docx

Supplementary material 7 (DOCX 25 kb) Table S5. Univariate and multivariate analyses of clinicopathological factors including the combination of DI and ploidy in association with DRFI of the hormone receptor-positive and HER2-negative subset

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Kusama, H., Shimoda, M., Miyake, T. et al. Prognostic value of tumor cell DNA content determined by flow cytometry using formalin-fixed paraffin-embedded breast cancer tissues. Breast Cancer Res Treat 176, 75–85 (2019). https://doi.org/10.1007/s10549-019-05222-y

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  • DOI: https://doi.org/10.1007/s10549-019-05222-y

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