ABSTRACT
Breast cancer (BC) patients aged <40 years at diagnosis experience aggressive disease and poorer survival compared with women diagnosed with BC at 40 to 49 years, but the age-related biology is described to little extent. Here, we explored transcriptional alterations in BC to gain better understanding of age-related tumor biology. We studied a subset of the Bergen in-house cohort (n = 127; age range, 26-49 years) and used the NanoString Breast Cancer 360 expression panel on formalin-fixed paraffin-embedded BC tissue, and publicly available global BC messenger RNA expression data (n = 204, age range, 22-49 years), to explore differentially expressed genes between the young (age <40 years) and older (age 40-49 years) patients. Unsupervised hierarchical clustering was applied to identify gene expression-based patient clusters. We applied established computational approaches to define the PAM50 subtypes, risk of recurrence scores (ROR), and risk groups and to infer the proportions of 22 immune cell types from bulk gene expression profiles of patients aged <50 years at BC diagnosis. Differentially expressed genes and gene sets were investigated using OncoEnrichR and g:Profiler to describe functional profiles and pathway enrichment. We identified 4 age-related patient clusters presenting distinct characteristics of PAM50 subtypes and ROR profiles, which demonstrated independent prognostic value when adjusted for traditional clinicopathologic variables and the known molecular subtypes. Our findings showed better survival than expected in the basal-enriched cluster 2 and in triple-negative and basal-like BC. Deconvolution analyses of immunophenotypes indicated higher levels of M0 and M1 macrophages than M2 macrophages in subsets of young BC. Our approach identifies age-based patient clusters with distinct clinicopathologic profiles, to a large extent overlapping with the PAM50 subtypes, although with independent prognostic values in multivariate survival analyses. The patient clusters provided new insight in the immune cell distribution across tumor subtypes, potentially contributing to survival differences between the clusters and the molecular subtypes and indicating age-related mechanisms improving outcome. Our study confirms the applicability of ROR as a valid prognosticator also in a young BC cohort.
ABSTRACT
BACKGROUND: Despite successful implementation of drugs targeting the human epidermal growth factor receptor 2 (HER2) receptor in breast and gastric cancers, the potential of HER2 as a therapeutic target in other cancers has been less studied, including endometrial cancer. We investigated expression levels of HER2 (ERBB2) in a large cohort of endometrial cancer lesions, also including complex atypical hyperplasia and metastatic lesions. METHODS: 67 precursor lesions, 790 primary endometrial cancers and 383 metastatic lesions were investigated for HER2 expression in relation to clinicopathologic features and outcome. Protein levels were assessed by immunohistochemistry (using the HercepTest and staining index (SI) criteria), mRNA levels by microarrays and amplification status by chromogenic in situ hybridisation. RESULTS: High HER2 protein levels were significantly associated with features of aggressive disease and increased mRNA ERBB2 levels. HER2 expression defined by the SI proved to be a better predictor of survival compared with the HercepTest. A discordant HER2 expression pattern between paired primary and metastatic lesions was detected, revealing substantial reduction in HER2 expression from primary to metastatic disease. CONCLUSIONS: Loss of HER2 expression is common in metastatic endometrial cancer lesions and assessment of HER2 levels in the metastatic lesions may be important to define the potential benefit of anti-HER2 treatments in endometrial cancer patients.
