Fractionated evaluation of immunohistochemical hormone receptor expression enhances prognostic prediction in breast cancer patients treated with tamoxifen as adjuvant therapy*

Objective: To compare the prognostic prediction between dichotomized and fractionated evaluations of hormone receptor expressions. Methods: Patients with stages I–III breast cancers, who received adjuvant tamoxifen, were enrolled. The expression of estrogen receptor (ER) and progesterone receptor (PR) was evaluated by immunohistochemistry (IHC). A fractionated score (F score), the percentage of positive-staining nuclei (0=none, 1=1%–10%, 2=11%–30%, 3=31%–50%, 4=51%–70%, and 5=71%–100%), was assigned to each case. The dichotomized scoring method defines an F score >1 as positive. The prognostic values of both scores were compared by multiple Cox’s proportional hazard models of disease-free survival (DFS) and overall survival (OS). Results: Four hundred and sixteen patients with a median follow-up of 78.0 months were included. F scores for ER and PR correlated directly with DFS and OS. Although both the dichotomized and fractionated ER and PR scores were significantly associated with DFS and OS in univariate analyses, only fractionated ER and PR scores remained as independent prognostic factors of DFS and OS in the final multiple Cox’s proportional hazard models. Conclusion: Fractionated IHC hormone receptor expression evaluation enhances the prognostic prediction compared with a dichotomized assessment

Spatial analyses of immune cell infiltration in cancer: current methods and future directions.:A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers.</p