Abstract
BackgroundThe extent of cellular heterogeneity in breast cancer could have potential impact on diagnosis and long-term outcome. However, pathology evaluation is limited to biomarker immunohistochemical staining and morphology of the bulk cancer. Inter-cellular heterogeneity of biomarkers is not usually assessed. As an initial evaluation of the extent of breast cancer cellular heterogeneity, we conducted quantitative and spatial imaging of Estrogen Receptor (ER), Progesterone Receptor (PR), Epidermal Growth Factor Receptor-2 (HER2), Ki67, TP53, CDKN1A (P21/WAF1), CDKN2A (P16INK4A), CD8 and CD20 of a tissue microarray (TMA) representing subtypes defined by St. Gallen surrogate classification.MethodsQuantitative, single cell-based imaging was conducted using an Immunofluorescence protein multiplexing platform (MxIF) to study protein co-expression signatures and their spatial localization patterns. The range of MxIF intensity values of each protein marker was compared to the respective IHC score for the TMA core. Extent of heterogeneity in spatial neighborhoods was analyzed using co-occurrence matrix and Diversity Index measures.ResultsOn the 101 cores from 59 cases studied, diverse expression levels and distributions were observed in MxIF measures of ER and PR among the hormonal receptor-positive tumor cores. As expected, Luminal A-like cancers exhibit higher proportions of cell groups that co-express ER and PR, while Luminal B-like (HER2-negative) cancers were composed of ER+, PR- groups. Proliferating cells defined by Ki67 positivity were mainly found in groups with PR-negative cells. Triple-Negative Breast Cancer (TNBC) exhibited the highest proliferative fraction and incidence of abnormal P53 and P16 expression. Among the tumors exhibiting P53 overexpression by immunohistochemistry, a group of TNBC was found with much higher MxIF-measured P53 signal intensity compared to HER2+, Luminal B-like and other TNBC cases. Densities of CD8 and CD20 cells were highest in HER2+ cancers. Spatial analysis demonstrated variability in heterogeneity in cellular neighborhoods in the cancer and the tumor microenvironment. ConclusionsProtein marker multiplexing and quantitative image analysis demonstrated marked heterogeneity in protein co-expression signatures and cellular arrangement within each breast cancer subtype. These refined descriptors of biomarker expressions and spatial patterns could be valuable in the development of more informative tools to guide diagnosis and treatment.
Highlights
Breast Cancer is a highly heterogeneous disease
Cheung et al Breast Cancer Research (2021) 23:114 descriptors of biomarker expressions and spatial patterns could be valuable in the development of more informative tools to guide diagnosis and treatment
In order to determine if multiplex‐ ing platform (MxIF) measurements of breast biomarkers reflect IHC results, we compared the distribution of normalized Estrogen Receptor (ER) and Progesterone Receptor (PR) MxIF signals from individual cells between cores that were scored by IHC as negative, weak, moderately or strongly stained for the majority of the cells (Fig. 1A–D)
Summary
Breast Cancer is a highly heterogeneous disease. Methods to classify different clinicopathologic types of breast cancers range from evaluation of the immunohistochemical (IHC) staining of hormonal and protein biomarkers (Estrogen receptor ER, Progesterone receptor PR and Epidermal Growth Factor Receptor HER2/ neu), etc., to molecular profiling and intrinsic subtyping based on RNA expression [1,2,3] and integrated transcriptomics with copy number aberrations (IntClust) [4,5,6,7] in bulk populations of cancer cells. Detailed analysis of ER+ cancers with long-term outcome data has identified integrative molecular subtypes that are associated with increased risk of long-term recurrence [18]. These findings suggest that additional specificity within this spectrum may be helpful in improving the characterization of this subtype. As an initial evalua‐ tion of the extent of breast cancer cellular heterogeneity, we conducted quantitative and spatial imaging of Estrogen Receptor (ER), Progesterone Receptor (PR), Epidermal Growth Factor Receptor-2 (HER2), Ki67, TP53, CDKN1A (P21/ WAF1), CDKN2A (P16INK4A), CD8 and CD20 of a tissue microarray (TMA) representing subtypes defined by St. Gallen surrogate classification
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