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Pathology Report

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Breast Cancer Radiation Therapy
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Abstract

The pathology report should provide accurate diagnostic, prognostic and predictive information, including information about completeness of resection, according to timeliness required for tissue-processing without delaying clinical care. The pathology report should deliver unambiguous communication between the pathologists and the clinicians, but also emphasizing unusual or biologically divergent findings that might influence clinical management and disease understanding.

The pathological report is often expected to provide the “absolute truth”. However, even with the addition of molecular pathology, including biomarkers and multigene tests, the findings are not exhaustive and should be evaluated in the context of the individual patient, discussed and reviewed if needed in the multidisciplinary setting, with a pathologist taking active part in the discussion and indicating the limitation of the pathological evaluation.

For novel biomarkers including multigene tests to be clinically implementable, clinical as well as analytical validity needs to be consolidated. While some biomarkers show prognostic/predictive information in population-based studies, they may currently not be sufficiently reproducible for clinical use.

The pathologist is responsible for staying up-to-date with optimal evaluation of biomarkers and for interpreting the increasingly complex, combined biological picture and presenting it as precisely as possible to the clinicians in order to provide a basis for subsequent treatment decisions.

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References

  1. Yu YH, Mo QG, Zhu X, et al. Axillary fine needle aspiration cytology is a sensitive and highly specific technique for the detection of axillary lymph node metastasis: a meta-analysis and systematic review. Cytopathology. 2016;27:59–69.

    Article  Google Scholar 

  2. Brennan ME, Turner RM, Ciatto S, et al. Ductal carcinoma in situ at core-needle biopsy: meta-analysis of underestimation and predictors of invasive breast cancer. Radiology. 2011;260:119–28.

    Article  Google Scholar 

  3. Garvey EM, Senior DA, Pockaj BA, et al. Rates of residual disease with close but negative margins in breast cancer surgery. Breast. 2015;24:413–7.

    Article  Google Scholar 

  4. Houssami N, MacAskill P, Marinovich ML, et al. Meta-analysis of the impact of surgical margins on local recurrence in women with early-stage invasive breast cancer treated with breast-conserving therapy. Eur J Cancer. 2010;46:3219–32.

    Article  Google Scholar 

  5. Denkert C, Budczies J, von Minckwitz G, Wienert S, Loibl S, Klauschen F. Strategies for developing Ki67 as a useful biomarker in breast cancer. Breast. 2015;24:S67–72.

    Article  Google Scholar 

  6. Denkert C, Budczies J, Regan MM, et al. Clinical and analytical validation of Ki-67 in 9069 patients from IBCSG VIII + IX, BIG1-98 and GeparTrio trial: systematic modulation of interobserver variance in a comprehensive in silico ring trial. Breast Cancer Res Treat. 2019;176:557–68.

    Article  Google Scholar 

  7. Nielsen TO, Leung SCY, Rimm DL, et al. Assessment of Ki67 in breast cancer: updated recommendations from the International Ki67 in Breast Cancer Working Group. J Natl Cancer Inst. 2021;113(7):808–19.

    Article  Google Scholar 

  8. Stålhammar G, Fuentes Martinez N, Lippert M, et al. Digital image analysis outperforms manual biomarker assessment in breast cancer. Mod Pathol. 2016;29:318–29.

    Article  Google Scholar 

  9. Ongaro E, Gerratana L, Cinausero M, et al. Comparison of primary breast cancer and paired metastases: biomarkers discordance influence on outcome and therapy. Future Oncol. 2018;14:849–59.

    Article  CAS  Google Scholar 

  10. Sighoko D, Liu J, Hou N, Gustafson P, Huo D. Discordance in hormone receptor status among primary, metastatic, and second primary breast cancers: biological difference or misclassification? Oncologist. 2014;19:592–601.

    Article  Google Scholar 

  11. Houssami N, Macaskill P, Balleine RL, Bilous M, Pegram MD. HER2 discordance between primary breast cancer and its paired metastasis: tumour biology or test artefact? Insights through meta-analysis. Breast Cancer Res Treat. 2011;129:659–74.

    Article  CAS  Google Scholar 

  12. Yates LR, Gerstung M, Knappskog S, et al. Subclonal diversification of primary breast cancer revealed by multiregion sequencing. Nat Med. 2015;21:751–9.

    Article  CAS  Google Scholar 

  13. Ng CKY, Bidard F-C, Piscuoglio S, et al. Genetic heterogeneity in therapy-naïve synchronous primary breast cancers and their metastases. Clin Cancer Res. 2017;23:4402–15.

    Article  CAS  Google Scholar 

  14. Viale G. Characterization and clinical impact of residual disease after neoadjuvant chemotherapy. Breast. 2013;22(Suppl 2):S88–91.

    Article  Google Scholar 

  15. Symmans WF, Wei C, Gould R, et al. Long-term prognostic risk after neoadjuvant chemotherapy associated with residual cancer burden and breast cancer subtype. J Clin Oncol. 2017;35:1049–60.

    Article  CAS  Google Scholar 

  16. Namura M, Tsunoda H, Yagata H, et al. Discrepancies between pathological tumour responses and estimations of complete response by magnetic resonance imaging after neoadjuvant chemotherapy differ by breast cancer subtype. Clin Breast Cancer. 2018;18:128–34.

    Article  CAS  Google Scholar 

  17. Ballesio L, Gigli S, Di Pastena F, et al. Magnetic resonance imaging tumour regression shrinkage patterns after neoadjuvant chemotherapy in patients with locally advanced breast cancer: correlation with tumour biological subtypes and pathological response after therapy. Tumour Biol. 2017;39:101042831769454.

    Article  Google Scholar 

  18. Prat A, Carey LA, Adamo B, et al. Molecular features and survival outcomes of the intrinsic subtypes within Her2-positive breast cancer. J Natl Cancer Inst. 2014;106.

    Google Scholar 

  19. Bartlett JMS, Bayani J, Marshall A, et al. Comparing breast cancer multiparameter tests in the OPTIMA prelim trial: no test is more equal than the others. J Natl Cancer Inst. 2016;108(9):djw050.

    Article  Google Scholar 

  20. Buus R, Sestak I, Kronenwett R, et al. Molecular drivers of Onco type DX, Prosigna, EndoPredict, and the Breast Cancer Index: a TransATAC study. J Clin Oncol. 2021;39(2):126–35.

    Article  CAS  Google Scholar 

  21. Sestak I, Buus R, Cuzick J, et al. Comparison of the performance of 6 prognostic signatures for estrogen receptor–positive breast cancer a secondary analysis of a randomized clinical trial. JAMA Oncol. 2018;4:545–53.

    Article  Google Scholar 

  22. Vallon-Christersson J, Häkkinen J, Cecilia H, et al. Cross comparison and prognostic assessment of breast cancer multigene signatures in a large population-based contemporary clinical series. Sci Rep. 2019;9:12184.

    Article  Google Scholar 

  23. Paik S, Shak S, Kim C, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817–26.

    Article  CAS  Google Scholar 

  24. Buyse M, Loi S, van’t Veer L, et al. Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst. 2006;98:1183–92.

    Article  CAS  Google Scholar 

  25. Van de Vijver M, He YD, van’t Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002;347:1999–2009.

    Article  Google Scholar 

  26. Cuvelier C, President B, Maillet B, et al. UEMS specialists section of pathology declaration on molecular pathology. 2013.

    Google Scholar 

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Correspondence to Trine Tramm .

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Tramm, T., Moinfar, F. (2022). Pathology Report. In: Kaidar-Person, O., Meattini, I., Poortmans, P. (eds) Breast Cancer Radiation Therapy. Springer, Cham. https://doi.org/10.1007/978-3-030-91170-6_8

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  • DOI: https://doi.org/10.1007/978-3-030-91170-6_8

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