Publications

Publicly Sharable, Qualitopix

Aims: Recently, human epidermal growth factor 2 (HER2)-low (i.e. HER2 score 1+ or 2+ without amplification) breast cancer patients became eligible for trastuzumab–deruxtecan treatment. To improve assay standardisation and detection of HER2-low in a quantitative manner, we conducted an external quality assessment-like study in the Netherlands. Dynamic range cell lines and immunohistochemistry (IHC) calibrators were used to quantify HER2 expression and to assess interlaboratory variability. Methods and results: Three blank slides with a dynamic range cell line and an IHC calibrator were stained with routine HER2 assays by 35 laboratories. Four different antibody clones were used: 19 (54.3%) 4B5, six (17.1%) A0485, five (14.3%) DG44 (HercepTest) and five (14.3%) SP3. Laboratories used two different detection kits for 4B5 assays: 14 (73.7%) ultraView and five (26.3%) OptiView. Variability of HER2 expression in cell lines, measured with artificial intelligence software, was median (min–max) = negative core 0.5% (0.0–57.0), 1+ core 4.3% (1.6–71.3), 2+ core 42.8% (30.4–92.6) and 3+ core 96.2% (91.8–98.8). The calibrators DG44 and 4B5 OptiView had the highest analytical sensitivity, closely followed by 4B5 ultraView. SP3 was the least sensitive. Calibrators of A0485 assays were not analysable due to background staining. Conclusions: As assays were validated for detecting HER2-amplified tumours, not all assays and antibodies proved suitable for HER2-low detection. Some tests showed distinct expression in the negative cell line. Dynamic range cell line controls and quantitative analysis using calibrators demonstrated more interlaboratory variability than commonly appreciated. Revalidation of HER2 tests by laboratories is needed to ensure clinical applicable HER2-low assays.

Maaike Anna Hempenius, Maran A. Eenkhoorn, Henrik Høeg, David J. Dabbs, Bert van der Vegt, Seshi R. Sompuram, Nils A. ‘t Hart

Publicly Sharable, Qualitopix

Andrew Dodson, Suzanne Parry

Publicly Sharable, Qualitopix

Quality control of immunohistochemistry (IHC) slides is crucial to ascertain accurate patient management. Visual assessment is the most commonly used method to assess the quality of IHC slides from patient samples in daily pathology routines. Control tissues for IHC slides are typically obtained from prior cases containing normal tissues or specific antigen-expressing disease samples, especially tumors. Since such samples eventually run out, and tumors may be heterogeneous, constant expression levels from one control sample to the next cannot be guaranteed. With the increasing availability of standardized cell lines, the diagnostic utility of these cell lines as alternatives to traditional laboratory-derived controls can be explored. Further, stain quality of this cell line material can probably be better monitored with readout methods such as image analysis and artificial intelligence (AI) than with visual readout methods, where accuracy is influenced by the training and experience of the pathologists and technicians. In this study, we present the results of our investigation into AI-measured stain quality of standardized cell lines designed as controls for HER2 and PD-L1 IHC stainings. Using five IHC autostainers from the same manufacturer and type, we quantified cell membrane expression levels of these cell lines after staining using Qualitopix™, an AI algorithm for measuring stain quality control. Over a 24-month period of weekly AI measurements, we observed multiple unexpected variations, particularly in low and medium-expressing cell lines. To further investigate these fluctuations, we assessed both inter-stainer variation and intra-run variations, revealing differences between the stainers and the slide slots within the stainers. To finalize our study, we performed HER2 and PD-L1 stainings on calibrator slides to measure limit of detection to detect variance per stainer and slot. Our findings prompted extra maintenance from the manufacturer in one of the highly fluctuating stainers, which reduced variation. In conclusion, AI appears to be an effective approach to monitor immunohistochemical stain quality of standardized control cell lines for therapeutic protein targets HER2 and PD-L1, and to trace the underlying errors. This may be crucial for accurate patient management.

Sven van Kempen, W.J. Ghlowy Gerritsen, Tri Q. Nguyen, Carmen van Dooijeweert, Nikolas Stathonikos, Roel Broekhuizen, Loïs Peters, Paul J. van Diest

Publicly Sharable, Qualitopix, preprint

David Dabbs, Emina Torlakovic, Soren Nielsen, Suzanne C. Parry, Jing Yu, Catherine Stoos, Beth Clark, Henrik Høeg, Jeppe Thagaard, Seshi Sompuram, Stephen Naber, Yukako Yagi, James Sayre, Kodela Vani, Mélissande Cossutta, Francoise Soussaline, Alexandre Papine, Nils t'Hart, Matthias Szabolcs, Bharat Jasani, Mary Kinloch, Luis Chiriboga, Keith Miller, Steve Bogen