Prognostic significance of nucleolar assessment in invasive breast cancer. Issue 5 (26th March 2020) - Elsharawy, Khloud A; Toss, Michael S; Raafat, Sara; Ball, Graham; Green, Andrew R; Aleskandarany, Mohammed A; Dalton, Leslie W; Rakha, Emad A
Abstract : Aims: Nucleolar morphometric features have a potential role in the assessment of the aggressiveness of many cancers. However, the role of nucleoli in invasive breast cancer (BC) is still unclear. The aims of this study were to investigate the optimal method for scoring nucleoli in IBC and their prognostic significance, and to refine the grading of breast cancer (BC) by incorporating nucleolar score. Methods and results: Digital images acquired from haematoxylin and eosin‐stained sections from a large BC cohort were divided into training ( n  = 400) and validation ( n  = 1200) sets for use in this study. Four different assessment methods were evaluated in the training set to identify the optimal method associated with the best performance and significant prognostic value. These were: (i) a modified Helpap method; (ii) counting prominent nucleoli (size ≥2.5 µm) in 10 field views (FVs); (iii) counting prominent nucleoli in five FVs; and (iv) counting prominent nucleoli in one FV. The optimal method was applied to the validation set and to an external validation set, i.e. data from The Cancer Genome Atlas ( n  = 743). Scoring prominent nucleoli in five FVs showed the highest interobserver concordance rate (intraclass correlation coefficient of 0.8) and a significant association with BC‐specific survival ( P  < 0.0001). A high nucleolar score was associated with younger age, larger tumour size, and higher grade. Incorporation of nucleolar score in the Nottingham grading system resulted in a higher significant association with survival than the conventional grade. Conclusions: Quantification of nucleolar prominence in five FVs is a cost‐efficient and reproducible morphological feature that can predict BC behaviour and can provide an alternative to pleomorphism to improve BC grading performance.