PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers

Abstract

Background: Many methodologies have been used in research to identify the "intrinsic" subtypes of breast cancer commonly known as Luminal A, Luminal B, HER2-Enriched (HER2-E) and Basal-like. The PAM50 gene set is often used for gene expression-based subtyping; however, surrogate subtyping using panels of immunohistochemical (IHC) markers are still widely used clinically. Discrepancies between these methods may lead to different treatment decisions.

Methods: We used the PAM50 RT-qPCR assay to expression profile 814 tumors from the GEICAM/9906 phase III clinical trial that enrolled women with locally advanced primary invasive breast cancer. All samples were scored at a single site by IHC for estrogen receptor (ER), progesterone receptor (PR), and Her2/neu (HER2) protein expression. Equivocal HER2 cases were confirmed by chromogenic in situ hybridization (CISH). Single gene scores by IHC/CISH were compared with RT-qPCR continuous gene expression values and "intrinsic" subtype assignment by the PAM50. High, medium, and low expression for ESR1, PGR, ERBB2, and proliferation were selected using quartile cut-points from the continuous RT-qPCR data across the PAM50 subtype assignments.

Results: ESR1, PGR, and ERBB2 gene expression had high agreement with established binary IHC cut-points (area under the curve (AUC) ≥ 0.9). Estrogen receptor positivity by IHC was strongly associated with Luminal (A and B) subtypes (92%), but only 75% of ER negative tumors were classified into the HER2-E and Basal-like subtypes. Luminal A tumors more frequently expressed PR than Luminal B (94% vs 74%) and Luminal A tumors were less likely to have high proliferation (11% vs 77%). Seventy-seven percent (30/39) of ER-/HER2+ tumors by IHC were classified as the HER2-E subtype. Triple negative tumors were mainly comprised of Basal-like (57%) and HER2-E (30%) subtypes. Single gene scoring for ESR1, PGR, and ERBB2 was more prognostic than the corresponding IHC markers as shown in a multivariate analysis.

Conclusions: The standard immunohistochemical panel for breast cancer (ER, PR, and HER2) does not adequately identify the PAM50 gene expression subtypes. Although there is high agreement between biomarker scoring by protein immunohistochemistry and gene expression, the gene expression determinations for ESR1 and ERBB2 status was more prognostic.

Figure 1

Clinical PAM50 RT-qPCR breast cancer training set. Hierarchical clustering of RT-qPCR data for the PAM50 classifier genes normalized to the 5 control genes using 171 FFPE procured breast samples. Statistical selection using SigClust identified the 5 significant groups previously identified and designated as Luminal A (dark blue), Luminal B (light blue), HER2-E (pink), Basal-like (red), and Normal (green). The 16 non-neoplastic samples (grey), from reduction mammoplasty and grossly uninvolved breast tissues, all Clustered together and away from the invasive cancers. SigClust identified 4 reduction mammoplasty samples (green) that were used to train the Normal subtype.

Figure 2

ESR1 score cut-offs using training set and the GEICAM/9906 testing set. The ESR1 score is provided as a qualitative call of high, intermediate, or low. The cut-offs were based on the continuous expression of ESR1 across prototype samples in the training set. Each circle on the box plot represents an individual sample that is color coded according to IHC status. The cut-points between high, intermediate, and low classes were individually derived from the training set samples (A). Data from ESR1 gene expression over the GEICAM 9906 samples (B) are plotted on the same scale as the training set. Samples are colored according to ER IHC positivity (red) or negativity (blue) determined at a central facility.

Figure 3

Receiver Operator Characteristic (ROC) curves for ESR1, PGR, and ERBB2 for the GEICAM/9906 test set. ROC curves for the GEICAM/9906 test set were generated using the clinical IHC status (positive vs. negative) for ER, PR, and HER2/neu as compared to the continuous RT-qPCR data for ESR1, PGR, and ERBB2. The cut-points for sensitivity/specificity are based on the training set.

Figure 4

Association between HER2 status and “intrinsic” subtype. Figure (A) shows the subtype distribution within HER2+ samples by IHC/CISH. Figure (B) shows the ER/HER2 status for samples only within the HER2-E subtype.

Figure 5

Relative transcript abundance for ESR1, PGR, and ERBB2 in the Basal-like subtype. There was no difference (p > 0.05) in (A) ESR1, (B) PGR, or (C) ERBB2 expression by qPCR in Basal-like tumors, regardless of being called triple-negative or non-triple negative by IHC/CISH.

Figure 6

Kaplan-Meier plots of overall survival in GEICAM 9906 data set. When stratifying all patients with locally advanced breast cancer, regardless of chemotherapy regimen (FEC vs FEC-T), both RT-qPCR (A) and IHC/CISH (B) molecular classifications for assessing ESR1/ER and ERBB2/Her2 status were significant. However, the separation of the survival curves suggests that ER-status as assessed by qPCR has prognostic superiority to IHC (C).