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Comparative Study
. 2021 Sep 23;16(9):e0255580.
doi: 10.1371/journal.pone.0255580. eCollection 2021.

Looking for more reliable biomarkers in breast cancer: Comparison between routine methods and RT-qPCR

Emanuele Caselli  1 , Cristina Pelliccia  1 , Valeria Teti  1 , Guido Bellezza  1 , Martina Mandarano  1 , Ivana Ferri  1 , Kerstin Hartmann  2 , Mark Laible  2 , Ugur Sahin  2 , Zsuzsanna Varga  3 , Chiara Lupi  4 , Fabrizio Stracci  4   5 , Angelo Sidoni  1
Affiliations
Comparative Study

Looking for more reliable biomarkers in breast cancer: Comparison between routine methods and RT-qPCR

Emanuele Caselli et al. PLoS One. .

Abstract

Purpose: Decades of quality control efforts have raised the standards of immunohistochemistry (IHC), the principle method used for biomarker testing in breast cancer; however, computational pathology and reverse transcription quantitative PCR (RT-qPCR) may also hold promise for additional substantial improvements.

Methods: Herein, we investigated discrepancies in the assessment of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and marker of proliferation Ki67 comparing routinely obtained IHC (and FISH) data (ORI) with the results of manual (REV) and semi-automated (DIA) re-evaluation of the original IHC slides and then with RNA expression data from the same tissue block using the MammaTyper® (MT) gene expression assay.

Results: Correlation for ER and PR was high between ORI IHC and the other three study methods (REV, DIA and RT-qPCR). For HER2, 10 out of 96 discrepant cases can be detected between ORI and REV that involved at least one call in the equivocal category (except for one case). For Ki67, 22 (29.1%) cases were categorized differently by either REV alone (n = 17), DIA alone (n = 15) or both (n = 10) and 28 cases (29.2%) for RT-qPCR. Most of the discrepant Ki67 cases changed from low to high between the original and following assessment and belonged to the intermediate Ki67 expression range (between 9 and 30%).

Conclusions: Determination of the breast cancer biomarkers ER, PR, HER2 and Ki67 at the mRNA level shows high degree of correlation with IHC and compares well with correlations between original with subsequent independent manual or semi-automated IHC assessments. The use of methods with wider dynamic range and higher reproducibility such as RT-qPCR may offer more precise assessment of endocrine responsiveness, improve Ki67 standardization and help resolve HER2 cases that remain equivocal or ambiguous by IHC/FISH. In summary, our findings seem to configure RT-qPCR as a complementary method to be used in cases of either equivocal results or presenting, at the traditional determination assays, biomarkers expressions close to the cut-off values.

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Conflict of interest statement

Kerstin Hartmann, Mark Laible, Ugur Sahin: Salary and stock ownership BioNTech Diagnostics GmbH / BioNTech AG. These commercial affiliations do not alter our adherence to PLOS ONE policies on sharing data and materials. Mark Laible: Patent ownership of WO 2015/024942, Commercialized as MammaTyper (TM) Kit. The other authors declare that they have no conflict of interest.

Figures

Fig 1
Fig 1. Study design.
Fig 2
Fig 2. Correlation between original (ORI) and paired re-evaluated (REV) or digital image analyzed (DIA) samples for IHC.
Bland-Altman plots showing differences between original, re-evaluated and digital image analysis for ER (A, B), PR (C, D) and Ki67 (E, F). Cut-off value at ±10% is shown by red dotted lines. Scatterplots showing correlation between original, re-evaluated and digital image analysis for Ki67 (G, H). Cut-off value at 20% for Ki67 is shown by black dotted lines. Red dots highlight discordant cases between original and either re-evaluated or digital image analysis.
Fig 3
Fig 3
Comparison between IHC and RT-qPCR (MammaTyper®) for estrogen receptor (A, B), progesterone receptor (C, D), proliferation marker Ki67 (E, F) and human epidermal growth factor receptor 2 (G, H). Scatterplots with ORI IHC ER scores (A) or DIA IHC ER score (B) on the y-axis and ESR1 RU values on the x-axis. Cut-off values at 1% for IHC and 0.0 RU for RT-qPCR are shown by black dotted lines. Scatterplots with ORI IHC PR scores (C) or DIA IHC PR score (D) on the y-axis and PGR RU values on the x-axis. Cut-off values at 1% for IHC and 0.0 RU for RT-qPCR are shown by black dotted lines. Scatterplots with ORI IHC Ki67 scores (E) or DIA IHC Ki67 score (F) on the y-axis and MKI67 RU values on the x-axis. Cut-off values at 20% for IHC and 0.0 RU for RT-qPCR are shown by black dotted lines. Scatterplots showing correlation between IHC determination (ORI and REV) and RT-qPCR assessment for ERBB2/HER2 (G, H). Black dotted lines represent the respective cut-off for the RT-qPCR assay (ERBB2: 0.0) and for the positivity of the IHC staining (HER2: 2+). Second dotted line on the x-axis represents a second cut-off for ERBB2 (-0.7) after introduction of an equivocal zone.
Fig 4
Fig 4. HER2 IHC/FISH discrepancies.
Schematic analysis of discrepancies in HER2: a. between the original assessment (ORI) and re-evaluation (REV) and b. between IHC (ORI) and RT-qPCR. Positive calls are indicated by red filled boxes. Negatives calls are presented in green and equivocal calls in grey, according to the 2013 ASCO/CAP guidelines in force at the time of the study.
Fig 5
Fig 5
Subtype redistribution after re-evaluation (REV) (A), semi-automated analysis (DIA), (B) and RT-qPCR measurement (C).
See this image and copyright information in PMC

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