Molecular Diagnostics

Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast

Abstract

Background

There is limited knowledge about DCIS cellular composition and relationship with breast cancer events (BCE).

Methods

Immunofluorescence multiplexing (MxIF) was used to image and quantify 32 cellular biomarkers in FFPE DCIS tissue microarrays. Over 75,000 DCIS cells from 51 patients (median 9 years follow-up for non-BCE cases) were analysed for profiles predictive of BCE. K-means clustering was used to evaluate cellular co-expression of epithelial markers with ER and HER2.

Results

Only ER, PR and HER2 significantly correlated with BCE. Cluster analysis identified 6 distinct cell groups with different levels of ER, Her2, cMET and SLC7A5. Clusters 1 and 3 were not significant. Clusters 2 and 4 (high ER/low HER2 and SLC7A5/mixed cMET) significantly correlated with low BCE risk (P = 0.001 and P = 0.034), while cluster 6 (high HER2/low ER, cMET and SLC7A5) correlated with increased risk (P = 0.018). Cluster 5 (similar to cluster 6, except high SLC7A5) trended towards significance (P = 0.072). A continuous expression score (Escore) based on these 4 clusters predicted likelihood of BCE (AUC = 0.79, log-rank test P = 5E–05; LOOCV AUC = 0.74, log-rank test P = 0.006).

Conclusion

Multiplexed spatial analysis of limited tissue is a novel method for biomarker analysis and predicting BCEs. Further validation of Escore is needed in a larger cohort.

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Fig. 1: A flow chart representing the total number of cells and fields of view (FOV) that were analysed and the filtering process that was used for breast cancer events (BCE) analysis.
Fig. 2: Characteristics of the clinical cohort.
Fig. 3: Contribution of cell clusters to BCE and non-BCE.
Fig. 4: Virtual H&E images for each example cluster, biomaker stains and cluster plot of the cells expressing those markers at different levels of intensity.
Fig. 5: Model performance for prediction of BCE and non-BCE.

References

  1. 1.

    Ebctcg, McGale, P., Taylor, C., Correa, C., Cutter, D., Duane, F. et al. Effect of radiotherapy after mastectomy and axillary surgery on 10-year recurrence and 20-year breast cancer mortality: meta-analysis of individual patient data for 8135 women in 22 randomised trials. Lancet 383, 2127–2135 (2014).

    Article  Google Scholar 

  2. 2.

    Cuzick, J., Sestak, I., Pinder, S. E., Ellis, I. O., Forsyth, S., Bundred, N. J. et al. Effect of tamoxifen and radiotherapy in women with locally excised ductal carcinoma in situ: long-term results from the UK/ANZ DCIS trial. Lancet Oncol. 12, 21–29 (2011).

    CAS  Article  Google Scholar 

  3. 3.

    Wapnir, I. L., Dignam, J. J., Fisher, B., Mamounas, E. P., Anderson, S. J., Julian, T. B. et al. Long-term outcomes of invasive ipsilateral breast tumor recurrences after lumpectomy in NSABP B-17 and B-24 randomized clinical trials for DCIS. J. Natl. Cancer Inst. 103, 478–488 (2011).

    Article  Google Scholar 

  4. 4.

    Sanders, M. E., Schuyler, P. A., Dupont, W. D. & Page, D. L. The natural history of low-grade ductal carcinoma in situ of the breast in women treated by biopsy only revealed over 30 years of long-term follow-up. Cancer 103, 2481–2484 (2005).

    Article  Google Scholar 

  5. 5.

    Jones, J. L. Overdiagnosis and overtreatment of breast cancer: progression of ductal carcinoma in situ: the pathological perspective. Breast Cancer Res. 8, 204 (2006).

    Article  Google Scholar 

  6. 6.

    Collins, L. C., Tamimi, R. M., Baer, H. J., Connolly, J. L., Colditz, G. A. & Schnitt, S. J. Outcome of patients with ductal carcinoma in situ untreated after diagnostic biopsy: results from the Nurses’ Health Study. Cancer 103, 1778–1784 (2005).

    Article  Google Scholar 

  7. 7.

    Elshof, L. E., Tryfonidis, K., Slaets, L., van Leeuwen-Stok, A. E., Skinner, V. P., Dif, N. et al. Feasibility of a prospective, randomised, open-label, international multicentre, phase III, non-inferiority trial to assess the safety of active surveillance for low risk ductal carcinoma in situ—The LORD study. Eur. J. Cancer 51, 1497–1510 (2015).

    Article  Google Scholar 

  8. 8.

    Fallowfield, L., Francis, A., Catt, S., Mackenzie, M. & Jenkins, V. Time for a low-risk DCIS trial: harnessing public and patient involvement. Lancet Oncol. 13, 1183–1185 (2012).

    Article  Google Scholar 

  9. 9.

    Groen, E. J., Elshof, L. E., Visser, L. L., Rutgers, E. J. T., Winter-Warnars, H. A. O., Lips, E. H. et al. Finding the balance between over- and under-treatment of ductal carcinoma in situ (DCIS). Breast 31, 274–283 (2017).

    Article  Google Scholar 

  10. 10.

    Grimm, L. J., Ryser, M. D., Partridge, A. H., Thompson, A. M., Thomas, J. S., Wesseling, J. et al. Surgical Upstaging rates for vacuum assisted biopsy proven DCIS: implications for active surveillance trials. Ann. Surg. Oncol. 24, 3534–3540 (2017).

    Article  Google Scholar 

  11. 11.

    Badve, S., A’Hern, R. P., Ward, A. M., Millis, R. R., Pinder, S. E., Ellis, I. O. et al. Prediction of local recurrence of ductal carcinoma in situ of the breast using five histological classifications: a comparative study with long follow-up. Hum. Pathol. 29, 915–923 (1998).

    CAS  Article  Google Scholar 

  12. 12.

    Badve, S. & Gokmen-Polar, Y. Tumor heterogeneity in breast cancer. Adv. Anat. Pathol. 22, 294–302 (2015).

    CAS  Article  Google Scholar 

  13. 13.

    Gerdes, M. J., Gokmen-Polar, Y., Sui, Y., Pang, A. S., LaPlante, N., Harris, A. L. et al. Single-cell heterogeneity in ductal carcinoma in situ of breast. Mod. Pathol. 31, 406–417 (2018).

    CAS  Article  Google Scholar 

  14. 14.

    Harrison, B. T., Hwang, S., Partridge, A., Thompson, A. & Schnitt, S. J. Variability in diagnostic threshold for comedo necrosis among pathologists: implications for patient eligibility for active surveillance trials of DCIS. Mod. Pathol. 31, 70 (2018).

    Google Scholar 

  15. 15.

    Solin, L. J., Gray, R., Hughes, L. L., Wood, W. C., Lowen, M. A., Badve, S. S. et al. Surgical excision without radiation for ductal carcinoma in situ of the breast: 12-year results from the ECOG-ACRIN E5194 study. J. Clin. Oncol. 33, 3938–3944 (2015).

    Article  Google Scholar 

  16. 16.

    Sagara, Y., Mallory, M. A., Wong, S., Aydogan, F., DeSantis, S., Barry, W. T. et al. Survival benefit of breast surgery for low-grade ductal carcinoma in situ: a population-based cohort study. JAMA Surg. 150, 739–745 (2015).

    Article  Google Scholar 

  17. 17.

    Kerlikowske, K., Molinaro, A. M., Gauthier, M. L., Berman, H. K., Waldman, F., Bennington, J. et al. Biomarker expression and risk of subsequent tumors after initial ductal carcinoma in situ diagnosis. J. Natl. Cancer Inst. 102, 627–637 (2010).

    CAS  Article  Google Scholar 

  18. 18.

    Bremer, T., Whitworth, P. W., Patel, R., Savala, J., Barry, T., Lyle, S. et al. A biological signature for breast ductal carcinoma in situ to predict radiotherapy benefit and assess recurrence risk. Clin. Cancer Res. 24, 5895–5901 (2018).

    Article  Google Scholar 

  19. 19.

    Solin, L. J., Gray, R., Baehner, F. L., Butler, S. M., Hughes, L. L., Yoshizawa, C. et al. A multigene expression assay to predict local recurrence risk for ductal carcinoma in situ of the breast. J. Natl. Cancer Inst. 105, 701–710 (2013).

    CAS  Article  Google Scholar 

  20. 20.

    Rakovitch, E., Nofech-Mozes, S., Hanna, W., Sutradhar, R., Baehner, F. L., Miller, D. P. et al. Multigene expression assay and benefit of radiotherapy after breast conservation in ductal carcinoma in situ. J Natl Cancer Inst. 109, djw256 (2017).

  21. 21.

    Gokmen-Polar, Y., Nakshatri, H. & Badve, S. Biomarkers for breast cancer stem cells: the challenges ahead. Biomark. Med. 5, 661–671 (2011).

    Article  Google Scholar 

  22. 22.

    Wright, H. J., Hou, J., Xu, B., Cortez, M., Potma, E. O., Tromberg, B. J. et al. CDCP1 drives triple-negative breast cancer metastasis through reduction of lipid-droplet abundance and stimulation of fatty acid oxidation. Proc. Natl. Acad. Sci. USA 114, E6556–E6565 (2017).

    CAS  Article  Google Scholar 

  23. 23.

    Yang, C., He, P., Liu, Y., He, Y., Yang, C., Du, Y. et al. Down-regulation of CEACAM1 in breast cancer. Acta Biochim. Biophys. Sin. (Shanghai). 47, 788–794 (2015).

    CAS  Article  Google Scholar 

  24. 24.

    Wakasugi, E., Kobayashi, T., Tamaki, Y., Ito, Y., Miyashiro, I., Komoike, Y. et al. p21(Waf1/Cip1) and p53 protein expression in breast cancer. Am. J. Clin. Pathol. 107, 684–691 (1997).

    CAS  Article  Google Scholar 

  25. 25.

    Nasir, A., Holzer, T. R., Chen, M., Man, M. Z. & Schade, A. E. Differential expression of VEGFR2 protein in HER2 positive primary human breast cancer: potential relevance to anti-angiogenic therapies. Cancer Cell Int. 17, 56 (2017).

    Article  Google Scholar 

  26. 26.

    Hicks, D. G., Janarthanan, B. R., Vardarajan, R., Kulkarni, S. A., Khoury, T., Dim, D. et al. The expression of TRMT2A, a novel cell cycle regulated protein, identifies a subset of breast cancer patients with HER2 over-expression that are at an increased risk of recurrence. BMC Cancer 10, 108 (2010).

    Article  Google Scholar 

  27. 27.

    Bartlett, J. M., Thomas, J., Ross, D. T., Seitz, R. S., Ring, B. Z., Beck, R. A. et al. Mammostrat as a tool to stratify breast cancer patients at risk of recurrence during endocrine therapy. Breast Cancer Res. 12, R47 (2010).

    Article  Google Scholar 

  28. 28.

    Kochel, T. J., Reader, J. C., Ma, X., Kundu, N. & Fulton, A. M. Multiple drug resistance-associated protein (MRP4) exports prostaglandin E2 (PGE2) and contributes to metastasis in basal/triple negative breast cancer. Oncotarget 8, 6540–6554 (2017).

    Article  Google Scholar 

  29. 29.

    Mao, Q. & Unadkat, J. D. Role of the breast cancer resistance protein (BCRP/ABCG2) in drug transport–an update. AAPS J. 17, 65–82 (2015).

    CAS  Article  Google Scholar 

  30. 30.

    Delou, J. M. A., Vignal, G. M., Indio-do-Brasil, V., Accioly, M. T. S., da Silva, T. S. L., Piranda, D. N. et al. Loss of constitutive ABCB1 expression in breast cancer associated with worse prognosis. Breast Cancer (Dove Med Press). 9, 415–428 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Gerdes, M. J., Sevinsky, C. J., Sood, A., Adak, S., Bello, M. O., Bordwell, A. et al. Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue. Proc. Natl Acad. Sci. USA. 110, 11982–11987 (2013).

    CAS  Article  Google Scholar 

  32. 32.

    Wilkerson, M. D. & Hayes, D. N. ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics 26, 1572–1573 (2010).

    CAS  Article  Google Scholar 

  33. 33.

    Șenbabaoğlu, Y., Michailidis, G. & Li, J. Z. Critical limitations of consensus clustering in class discovery. Sci. Rep. 4, 6207 (2014).

    Article  Google Scholar 

  34. 34.

    Cardoso, F., van’t Veer, L. J., Bogaerts, J., Slaets, L., Viale, G., Delaloge, S. et al. 70-Gene signature as an aid to treatment decisions in early-stage breast cancer. N. Engl. J. Med. 375, 717–729 (2016).

    CAS  Article  Google Scholar 

  35. 35.

    Sparano, J. A., Gray, R. J., Makower, D. F., Pritchard, K. I., Albain, K. S., Hayes, D. F. et al. Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N. Engl. J. Med. 379, 111–121 (2018).

    CAS  Article  Google Scholar 

  36. 36.

    Narod, S. A., Iqbal, J., Giannakeas, V., Sopik, V. & Sun, P. Breast cancer mortality after a diagnosis of ductal carcinoma in situ. JAMA Oncol. 1, 888–896 (2015).

    Article  Google Scholar 

  37. 37.

    Esserman, L. J., Thompson, I. M., Reid, B., Nelson, P., Ransohoff, D. F., Welch, H. G. et al. Addressing overdiagnosis and overtreatment in cancer: a prescription for change. Lancet Oncol. 15, e234–e242 (2014).

    Article  Google Scholar 

  38. 38.

    Leung, S. C. Y., Nielsen, T. O., Zabaglo, L., Arun, I., Badve, S. S., Bane, A. L. et al. Analytical validation of a standardized scoring protocol for Ki67: phase 3 of an international multicenter collaboration. NPJ Breast Cancer 2, 16014 (2016).

    Article  Google Scholar 

  39. 39.

    Leung, S. C. Y., Nielsen, T. O., Zabaglo, L. A., Arun, I., Badve, S. S., Bane, A. L. et al. Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration. Histopathology 75, 225–235 (2019).

    Article  Google Scholar 

  40. 40.

    El Ansari, R., Craze, M. L., Miligy, I., Diez-Rodriguez, M., Nolan, C. C., Ellis, I. O. et al. The amino acid transporter SLC7A5 confers a poor prognosis in the highly proliferative breast cancer subtypes and is a key therapeutic target in luminal B tumours. Breast Cancer Res. 20, 21 (2018).

    Article  Google Scholar 

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Acknowledgements

The authors gratefully acknowledge the contributions of Alex Corwin for Cell DIVE imaging workflows and quality control and Sean Dinn and Eric Williams for antibody conjugations.

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Authors

Contributions

Concept, design, interpretation and execution of the entire project: S.S.B., Y.G.-P., M.G., P.H.T., A.H. and F.G. Statistical and bioinformatics analyses and interpretation: S.C., M.T., M.Z. and Y.S. Manuscript writing: S.S.B., S.C., Y.G.-P., P.H.T., M.G., A.H. and F.G. All authors approved the manuscript.

Corresponding author

Correspondence to Sunil S. Badve.

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Ethics approval and consent to participate

The study was performed in accordance with the Declaration of Helsinki. Waiver of IRB was obtained from Indiana, and Oxford Universities.

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Not applicable.

Data availability

Additional information can be found in Supplemental data section. The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

A patent disclosure has been filed at IU for the EScore. The authors (S.S.B., Y.G.P., F.G., S.C. and A.L.H.) have been listed as inventors. S.C., Y.S., C.C., E.M., A.S., M.Z., M.G. and F.G. are employees of GE. The remaining authors do not have any competing interests..

Funding information

This study is supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA194600 to S. Badve, M. Gerdes and F. Ginty. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Badve, S.S., Cho, S., Gökmen-Polar, Y. et al. Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast. Br J Cancer (2021). https://doi.org/10.1038/s41416-020-01216-6

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