Robustness of biomarker determination in breast cancer by RT-qPCR: impact of tumor cell content, DCIS and non-neoplastic breast tissue

Improving Prognosis of Surrogate Assay for Breast Cancer Patients by Absolute Quantitation of Ki67 Protein Levels Using Quantitative Dot Blot (QDB) Method

Background

Immunohistochemistry (IHC)-based surrogate assay is the prevailing method in daily clinical practice to determine the necessity of chemotherapy for Luminal-like breast cancer patients worldwide. It relies on Ki67 scores to separate Luminal A-like from Luminal B-like breast cancer subtypes. Yet, IHC-based Ki67 assessment is known to be plagued with subjectivity and inconsistency to undermine the performance of the surrogate assay. A novel method needs to be explored to improve the clinical utility of Ki67 in daily clinical practice.

Materials and Methods

The Ki67 protein levels in a cohort of 253 specimens were assessed with IHC and quantitative dot blot (QDB) methods, respectively, and used to assign these specimens into Luminal A-like and Luminal B-like subtypes accordingly. Their performances were compared with the Kaplan–Meier, univariate, and multivariate survival analyses of the overall survival (OS) of Luminal-like patients.

Results

The surrogate assay based on absolutely quantitated Ki67 levels (cutoff at 2.31 nmol/g) subtyped the Luminal-like patients more effectively than that based on Ki67 scores (cutoff at 14%) (Log rank test, p = 0.00052 vs. p = 0.031). It is also correlated better with OS in multivariate survival analysis [hazard ratio (HR) at 6.89 (95% CI: 2.66–17.84, p = 0.0001) vs. 2.14 (95% CI: 0.89–5.11, p = 0.087)].

Conclusions

Our study showed that the performance of the surrogate assay may be improved significantly by measuring Ki67 levels absolutely, quantitatively, and objectively using the QDB method.

Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry-based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.