Abstract 37P
Background
Accurate determination of breast cancer (BC) biomarker status is crucial for guiding patient management decisions. Histopathologists commonly use semi-quantitative scoring systems to convert subjective observations of immunohistochemistry (IHC) marker expression into quantitative data. The APIS Breast Cancer Subtyping Kit (BCSK) detects the relative expression of mRNA target genes from invasive BC tissue. The APIS BCSK reports a positive/negative result for each biomarker alongside a molecular classification. Here, we demonstrate that by implementing additional RNA expression cut-off values, it is possible to generate a semi-quantitative result by further stratifying target expression using the APIS BCSK.
Methods
368 formalin-fixed paraffin-embedded (FFPE) samples were used. IHC scores were correlated with copy numbers as determined by digital PCR (dPCR) and were used to set copy number cut-off values corresponding to IHC classification. Generated dPCR cut-off values were used to evaluate the corresponding ΔCt values (RNA expression results derived from the APIS BCSK.
Results
The semi-quantitative approach successfully classified target expression levels. Three ΔCt cut-offs were established, facilitating classification into negative, low, medium, and high expression. Overlap in ΔCt values was observed in central IHC categories for all targets, likely due to tumor heterogeneity. Despite these discrepancies, the derived cut-off values define a semi-quantitative scale for each target (Table). Table: 37P
Summary of individual target bin,ΔCt range and category
| Target | Lower ΔCt limit | Upper ΔCt limit | Expression classification |
| ESR1 | - | <-2.162 | Negative |
| -2.162 | 0.115 | Low | |
| 0.115 | 1.215 | Medium | |
| >1.215 | - | High | |
| PGR | - | <-0.376 | Negative |
| -0.376 | 1.214 | Low | |
| 1.214 | 2.867 | Medium | |
| >2.867 | - | High | |
| ERBB2 | - | <1.080 | Negative |
| 1.08 | 1.403 | Low | |
| 1.403 | 2.054 | Medium | |
| >2.054 | - | High | |
| MKI67 | - | <-1.265 | Negative |
| -1.265 | -0.401 | Low | |
| -0.401 | 0.417 | Medium | |
| >0.417 | - | High |
Conclusions
This study has established a methodology that utilises target copy number values and IHC quantification to establish ΔCt cut-off points. With this approach, we have defined four distinct classifications, providing a semi-quantitative scale for evaluating targets with the APIS BCSK.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.