Abstract
Breast cancer (BC) categorized as human epidermal growth factor receptor 2 (HER2) borderline [2+ by immunohistochemistry (IHC 2+)] presents challenges for the testing, frequently obscured by intratumoral heterogeneity (ITH). This leads to difficulties in therapy decisions. We aimed to establish prognostic models of overall survival (OS) of these patients, which take into account spatial aspects of ITH and tumor microenvironment by using hexagonal tiling analytics of digital image analysis (DIA). In particular, we assessed the prognostic value of Immunogradient indicators at the tumor–stroma interface zone (IZ) as a feature of antitumor immune response. Surgical excision samples stained for estrogen receptor (ER), progesterone receptor (PR), Ki67, HER2, and CD8 from 275 patients with HER2 IHC 2+ invasive ductal BC were used in the study. DIA outputs were subsampled by HexT for ITH quantification and tumor microenvironment extraction for Immunogradient indicators. Multiple Cox regression revealed HER2 membrane completeness (HER2 MC) (HR: 0.18, p = 0.0007), its spatial entropy (HR: 0.37, p = 0.0341), and ER contrast (HR: 0.21, p = 0.0449) as independent predictors of better OS, with worse OS predicted by pT status (HR: 6.04, p = 0.0014) in the HER2 non-amplified patients. In the HER2-amplified patients, HER2 MC contrast (HR: 0.35, p = 0.0367) and CEP17 copy number (HR: 0.19, p = 0.0035) were independent predictors of better OS along with worse OS predicted by pN status (HR: 4.75, p = 0.0018). In the non-amplified tumors, three Immunogradient indicators provided the independent prognostic value: CD8 density in the tumor aspect of the IZ and CD8 center of mass were associated with better OS (HR: 0.23, p = 0.0079 and 0.14, p = 0.0014, respectively), and CD8 density variance along the tumor edge predicted worse OS (HR: 9.45, p = 0.0002). Combining these three computational indicators of the CD8 cell spatial distribution within the tumor microenvironment augmented prognostic stratification of the patients. In the HER2-amplified group, CD8 cell density in the tumor aspect of the IZ was the only independent immune response feature to predict better OS (HR: 0.22, p = 0.0047). In conclusion, we present novel prognostic models, based on computational ITH and Immunogradient indicators of the IHC biomarkers, in HER2 IHC 2+ BC patients.
Highlights
Breast cancer (BC) is a complex and diverse disease with distinct clinical, pathological, and molecular characteristics
We explored the potential of the clinicopathological parameters, IHC, FISH, immune response, and ITH indicators for predicting
We present prognostic models for patients with human epidermal growth factor receptor 2 (HER2) IHC borderline (2+) BC patients, based on the expression levels of estrogen receptor (ER), progesterone receptor (PR), Ki67, HER2, and CD8 densities in the tumor tissue assessed by DIA
Summary
Breast cancer (BC) is a complex and diverse disease with distinct clinical, pathological, and molecular characteristics. BC has been classified into several biologically distinct subtypes: luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched (HER2), basal-like, and normal-like by gene expression profiling analysis [1, 2], requiring different treatment strategies This categorization of the BC subtypes has been adapted for clinical practice and is mainly based on immunohistochemistry (IHC) assessment of estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 expression. Novel approaches based on pathology image analytics and machine learning methods open new perspectives for predictive modeling and clinical decision support [9, 10]. Both molecular and image-based biomarkers can be explored and validated using The Cancer Genome Atlas (TCGA) Data Portal [11]
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