Posted on Nov 16, 2022
Comparison of ER, PR, HER2 and Ki67 expression by MammaTyper® RT-qPCR and immunohistochemistry (IHC) on needle core biopsies of breast cancer
Breast cancer biomarkers help clinicians determine a patient’s breast cancer sub-type. This plays a vital role in tailoring treatment effectively.
Immunohistochemistry (IHC) a staining process that enables pathologists to visualize proteins within cells that are important in the biologic pathways of breast cancer. This can help clinicians work out how aggressive a tumour is, as well as how it will grow.
Newer multigene tests such as MammaTyper® go further in assessing intrinsic properties of breast cancer tumours that impact on tumour behaviour.
MammaTyper® RT-qPCR is a multigene test that works through an easily replicated and quantitative measurement of marker gene expression. It assesses four biomarkers that enable the classification of breast cancer into five subtypes.
The biomarkers are:
- HER2 or ERBB2 (human epidermal growth factor receptor 2)
- ER or ESR1 (estrogen receptor 1)
- PR or PGR (progesterone receptor)
- MKI67 (marker of proliferation Ki-67, a marker expressed in proliferating cells)
We need further evidence to show that MammaTyper® analysis correlates with IHC testing, to ensure that it is a reliable and valid test.
What did the researchers do?
This study was led by Dr Abeer Shabaan, a specialist breast pathologist at Queen Elizabeth Hospital. Dr Shabaan worked with a team of researchers from London and Egypt examined 137 samples of breast cancer. These were collected from biopsies taken at a large UK hospital.
The samples were tested using MammaTyper® and compared to testing of ER, PR and HER2 in samples using IHC. Ki67 was assessed visually by pathologists and using digital image analysis software.
What did they find?
The researchers concluded that MammaTyper® has a high concordance with IHC. MammaTyper® assessment of Ki67 was well matched with digital image analysis.
This means that using MammaTyper® to assess breast cancer biopsy samples is reliable, efficient and reproducible alternative for breast cancer molecular subtyping.