Improving Pathological Assessment of Breast Cancer by Employing Array-Based Transcriptome Analysis

Abstract

Breast cancer research has paved the way of personalized oncology with the introduction of hormonal therapy and the measurement of estrogen receptor as the first widely accepted clinical biomarker. The expression of another receptor—HER2/ERBB2/neu—was initially a sign of worse prognosis, but targeted therapy has granted improved outcome for these patients so that today HER2 positive patients have better prognosis than HER2 negative patients. Later, the introduction of multigene assays provided the pathologists with an unbiased assessment of the tumors’ molecular fingerprint. The recent FDA approval of complete microarray pipelines has opened new possibilities for the objective classification of breast cancer samples. Here we review the applications of microarrays for determining ER and HER2 status, molecular subtypes as well as predicting prognosis and grade for breast cancer patients. An open question remains the role of single genes within such signatures. Openly available microarray datasets enable the execution of an independent cross-validation of new marker and signature candidates. In summary, we review the current state regarding clinical applications of microarrays in breast cancer molecular pathology.

Expression of the MHC Class II Pathway in Triple-Negative Breast Cancer Tumor Cells Is Associated with a Good Prognosis and Infiltrating Lymphocytes

“…Analysis was restricted to the 199 patients whose tumors were ER − , PR − , and were classified as basal intrinsic breast cancer subtype (25). Basal TNBC tumors were identified based on the St. Gallen criteria (28) using the procedure described by the authors of the Kaplan-Meier Plotter tool (29). …”

A Multigene Assay Determines Risk of Recurrence in Patients with Triple-Negative Breast Cancer

“…45) was used to perform correlative analysis of publicly available gene expression datasets. The intrinsic subtype classification provided by the Kaplan-Meier Plotter tool was used to select cases for analysis (46). The following selections were applied to all analyses: only one JetSet best probe (47) for each gene was used in the multigene classifier that calculates the mean expression of the selected probes, relapse-free survival was selected for the analysis, patients were censored at the follow-up threshold (60 months), biased arrays were excluded, and redundant samples were removed.…”

Endocrine sensitivity of estrogen receptor‐positive breast cancer is negatively correlated with aspartate‐β‐hydroxylase expression

“…(6) Clinically, ER- positive, HER2-negative, and low Ki-67 index breast cancer is classified as the luminal A-like subtype, which shows a good response to endocrine therapy; the remaining ER-positive breast cancers (ER-positive, high Ki-67 index and/or HER2positive) fall into the luminal B-like subtype, which shows a relatively poor response to endocrine therapy. (22,23) As in clinical subtyping, the platform developed by Gy€ orffy et al (24) classifies luminal A and luminal B subtypes based on the expression levels of ESR1, MKI67, and ERBB2. There was no difference in RFS between the ASPH-high and ASPH-low groups of patients with luminal A-like breast cancer (N = 347, P = 0.95; Fig.…”