The Prediction Analysis of Microarray 50 (PAM50) Gene Expression Classifier Utilized in Indeterminate-Risk Breast Cancer Patients in Hungary: A Consecutive 5-Year Experience.

BACKGROUND: Breast cancer has been categorized into molecular subtypes using immunohistochemical staining (IHC) and fluorescence in situ hybridization (FISH) since the early 2000s. However, recent research suggests that gene expression testing, specifically Prosigna® Prediction Analysis of Microarray 50 (PAM50), provides more accurate classification methods. In this retrospective study, we compared the results of IHC/FISH and PAM50 testing. We also examined the impact of various PAM50 parameters on overall survival (OS) and progression-free survival (PFS). RESULTS: We analyzed 42 unilateral breast cancer samples, with 18 classified as luminal A, 10 as luminal B, 8 as Human epidermal growth factor receptor 2 (HER2)-positive, and 6 as basal-like using PAM50. Interestingly, 17 out of the 42 samples (40.47%) showed discordant results between histopathological assessment and the PAM50 classifier. While routine IHC/FISH resulted in classification differences for a quarter to a third of samples within each subtype, all basal-like tumors were misclassified. Hormone receptor-positive tumors (hazard rate: 8.7803; p = 0.0085) and patients who had higher 10-year recurrence risk scores (hazard rate: 1.0539; p = 0.0201) had shorter OS and PFS. CONCLUSIONS: Our study supports the existing understanding of molecular subtypes in breast cancer and emphasizes the overlap between clinical characteristics and molecular subtyping. These findings underscore the value of gene expression profiling, such as PAM50, in improving treatment decisions for breast cancer patients.

PD-1, PD-L1 and CTLA-4 in pregnancy-related - and in early-onset breast cancer: A comparative study.

PURPOSE: We aimed to compare the immunohistochemical expression of PD-1, PD-L1 and CTLA-4 of pregnancy-related breast cancer (PRBC) and early onset non-PRBC (YWBC), and their prognosis prediction potential was correlated to that of conventional clinicopathological factors. METHODS: Twenty-one PRBC cases were paired with 21 YWBC in this matched case-control study. Immune-checkpoint markers (ICM) were evaluated with immunohistochemistry (IHC) on whole slides using the following antibodies: PD-1 (NAT-105), PD-L1 (28-8) and CTLA-4 (F-8). IHC score was defined as the percentage of positive cells, assessed separately among tumor cells, intratumoral lymphocytes and peritumoral lymphocytes. RESULTS: The optimal threshold of PD-L1 expression of tumor cells occurred at 10% for overall survival (OS, AUC = 0.847, p = 0.009), and at 1% for disease-free survival (DFS, AUC = 0.795, p = 0.010). For PD-L1 expression on intratumoral lymphocytes, the optimal cut-off was 1% (AUC = 0.763, p = 0.048). Considering PD-1, PD-L1 and CTLA-4 expression, no significant difference occurred between PRBC and YWBC (p > 0.05 for all comparisons). PD-1, PD-L1 expressed on peritumoral lymphocytes and CTLA-4 failed, but PD-L1 expressed on tumor cells and on intratumoral lymphocytes was suitable to distinguish patient cohorts with different OS and DFS (p ≤ 0.011 for all comparisons). Higher PD-L1 expression was associated with poor prognosis. PD-L1 expressed on tumor cells represented an independent association with OS (p = 0.023) and DFS (p = 0.032). CONCLUSIONS: Our results suggest that PRBC and YWBC do not differ in the expression of PD-1, PD-L1 and CTLA-4. However, our findings emphasize the relevance of PD-L1 expression in early-onset breast cancer, as an independent negative predictor of prognosis.