Reliability of tumor-infiltrating lymphocyte and tertiary lymphoid structure assessment in human breast cancer

Modern Pathology

Volumn 30, Issue 9, 2017, Pages 1204-1212

  Buisseret, Laurence ^a   Desmedt, Christine ^a   Garaud, Soizic ^a   Fornili, Marco ^b   Wang, Xiaoxiao ^a   Van Den Eyden, Gert ^c   De Wind, Alexandre ^a   Duquenne, Sebastien ^a   Boisson, Anais ^a   Naveaux, Celine ^a   Rothé, Francoise ^a   Rorive, Sandrine ^d   Decaestecker, Christine ^d   Larsimont, Denis ^a   Piccart Gebhart, Martine ^a   Biganzoli, Elia ^b   Sotiriou, Christos ^a   Willard Gallo, Karen ^a  

^a JULES BORDET INSTITUTE   (Belgium)

^b UNIVERSITY OF MILAN   (Italy)

^c SINT AUGUSTINUS HOSPITAL   (Belgium)

^d Center for Microscopy and Molecular Imaging   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

EOSIN; HEMATOXYLIN; COLORING AGENT;

ARTICLE; BREAST CANCER; CANCER PATIENT; CASE CONTROL STUDY; CLINICAL ASSESSMENT; COHORT ANALYSIS; CONTROLLED STUDY; CORRELATION COEFFICIENT; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DIGITAL IMAGING; FEMALE; HISTOPATHOLOGY; HUMAN; HUMAN CELL; HUMAN TISSUE; IMMUNOCOMPETENT CELL; IMMUNOHISTOCHEMISTRY; INTERRATER RELIABILITY; INTRARATER RELIABILITY; MAJOR CLINICAL STUDY; PATHOLOGIST; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; RANDOMIZED CONTROLLED TRIAL; SCORING SYSTEM; STROMA CELL; TERTIARY LYMPHOID STRUCTURE; TISSUE SECTION; TUMOR ASSOCIATED LEUKOCYTE; TUMOR BIOPSY; BIOPSY; BREAST TUMOR; COMPARATIVE STUDY; IMMUNOLOGY; OBSERVER VARIATION; PATHOLOGY; PREDICTIVE VALUE; PROCEDURES; PROGNOSIS; REPRODUCIBILITY; STAINING;

BIOPSY; BREAST NEOPLASMS; COLORING AGENTS; EOSINE YELLOWISH-(YS); FEMALE; HEMATOXYLIN; HUMANS; IMMUNOHISTOCHEMISTRY; LYMPHOCYTES, TUMOR-INFILTRATING; OBSERVER VARIATION; PREDICTIVE VALUE OF TESTS; PROGNOSIS; REPRODUCIBILITY OF RESULTS; STAINING AND LABELING; TERTIARY LYMPHOID STRUCTURES;

EID: 85024919243     PISSN: 08933952     EISSN: 15300285     Source Type: Journal    
DOI: 10.1038/modpathol.2017.43     Document Type: Article

References (24)

1. Dushyanthen S, Beavis PA, Savas P, et al. Relevance of tumor-infiltrating lymphocytes in breast cancer. BMC Med 2015;13:202.
2. Denkert C, Loibl S, Noske A, et al. Tumor-associated lymphocytes as an independent predictor of response to neoadjuvant chemotherapy in breast cancer. J Clin Oncol 2010;28:105-113.
3. Denkert C, von Minckwitz G, Darb-Esfahani S et al. Evaluation of Tumor-Infiltrating Lymphocytes (TILs) as predictive and prognostic biomarker in different subtypes of breast cancer treated with neoadjuvant therapy-a metaanalysis of 3771 patients. Cancer Res 2017;77: S1-09.
4. Salgado R, Denkert C, Demaria S, et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: Recommendations by an International TILs Working Group 2014. Ann Oncol 2015;26:259-271.
5. Denkert C, Wienert S, Poterie A, et al. Standardized evaluation of tumor-infiltrating lymphocytes in breast cancer: Results of the ring studies of the international immuno-oncology biomarker working group. Mod Pathol 2016;29:1155-1164.
6. Dieu-Nosjean M-C, Goc J, Giraldo NA, et al. Tertiary lymphoid structures in cancer and beyond. Trends Immunol 2014;35:571-580.
7. Gu-Trantien C, Loi S, Garaud S, et al. CD4+ follicular helper T cell infiltration predicts breast cancer survival. J Clin Invest 2013;123:2873-2892.
8. Lee HJ, Kim JY, Park IA, et al. Prognostic significance of tumor-infiltrating lymphocytes and the tertiary lymphoid structures in HER2-positive breast cancer treated with adjuvant trastuzumab. Am J Clin Pathol 2015;144: 278-288.
9. Figenschau SL, Fismen S, Fenton KA, et al. Tertiary lymphoid structures are associated with higher tumor grade in primary operable breast cancer patients. BMC Cancer 2015;15:101.
10. Lee HJ, Park IA, Song IH, et al. Tertiary lymphoid structures: Prognostic significance and relationship with tumour-infiltrating lymphocytes in triplenegative breast cancer. J Clin Pathol 2016;69:422-430.
11. Buisseret L, Garaud S, de Wind A, et al. Tumorinfiltrating lymphocyte composition, organization and PD-1/PD-L1 expression are linked in breast cancer. Oncoimmunology 2017;6:e1257452.
12. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307-310.
13. Bablok PH. A new biometrical procedure for testing the equality of measurements from two different analytical methods. Application of linear regression procedures for method comparison studies in clinical chemistry, Part I. J Clin Chem Clin Biochem 1983;21: 709-720.
14. Lin LH, Hedayat A, Wu W. Statistical Tools for Measuring Agreement. Springer: New-York, 2012.
15. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2008. ISBN 3-900051-07-0, Available at: Http://www.R-pro ject.org.
16. Loi S, Sirtaine N, Piette F, et al. Prognostic and predictive value of tumor-infiltrating lymphocytes in a phase III randomized adjuvant breast cancer trial in node-positive breast cancer comparing the addition of docetaxel to doxorubicin with doxorubicin-based chemotherapy: BIG 02-98. J Clin Oncol 2013;31: 860-867.
17. Loi S, Michiels S, Salgado R, et al. Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: Results from the FinHER trial. Ann Oncol 2014;25:1544-1550.
18. Adams S, Gray RJ, Demaria S, et al. Prognostic value of tumor-infiltrating lymphocytes in triple-negative breast cancers from two phase III randomized adjuvant breast cancer trials: ECOG 2197 and ECOG 1199. J Clin Oncol 2014;32:2959-2966.
19. Swisher SK, Wu Y, Castaneda CA, et al. Interobserver agreement between pathologists assessing tumorinfiltrating lymphocytes (TILs) in breast cancer using methodology proposed by the International TILs Working Group. Ann Surg Oncol 2016;23:2242-2248.
20. Gruosso T, Gigoux M, Bertos N, et al. Abstract P4-03-08: Mechanisms of CD8+ T cell immunosuppression in triple negative breast cancer. Cancer Res 2017;77: P4-03-08; Abstract.
21. Ali HR, Dariush A, Provenzano E, et al. Computational pathology of pre-treatment biopsies identifies lymphocyte density as a predictor of response to neoadjuvant chemotherapy in breast cancer. Breast Cancer Res 2016;18:21.
22. Laurinavicius A, Plancoulaine B, Laurinaviciene A, et al. A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue. Breast Cancer Res 2014;16:R35.
23. Beck AH, Sangoi AR, Leung S, et al. Systematic analysis of breast cancer morphology uncovers stromal features associated with survival. Sci Transl Med 2011;3:108ra113.
24. Yuan Y, Failmezger H, Rueda OM, et al. Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling. Sci Transl Med 2012;4:157ra143.