Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays.

Tissue microarrays (TMAs) have been used in thousands of cancer biomarker studies. To what extent batch effects, measurement error in biomarker levels between slides, affects TMA-based studies has not been assessed systematically. We evaluated 20 protein biomarkers on 14 TMAs with prospectively collected tumor tissue from 1448 primary prostate cancers. In half of the biomarkers, more than 10% of biomarker variance was attributable to between-TMA differences (range, 1-48%). We implemented different methods to mitigate batch effects (R package To understand cancer, researchers need to know which molecules tumor cells use. These so-called ‘biomarkers’ tag cancer cells as being different from healthy cells, and can be used to predict how aggressive a tumor may be, or how well it might respond to treatment. A popular technique for assessing biomarkers across multiple tumors is to use tissue microarrays. This involves taking samples from different tumors and embedding them in a block of wax, which is then cut into micro-thin slices and stained with reagents that can detect specific biomarkers, such as proteins. Each block contains hundreds of samples, which all experience the same conditions. So, any patterns detected in the staining are likely to represent real variations in the biomarkers present. Many cancer studies, however, often compare samples from multiple tissue microarrays, which may increase the risk of technical artifacts: for example, staining may look stronger in one batch of tissue samples than another, even though the amount of biomarker present in these different arrays is roughly the same. These ‘batch effects’ could potentially bias the results of the experiment and lead to the identification of misleading patterns. To evaluate how batch effects impact tissue microarray studies, Stopsack et al. examined 14 wax blocks which contained tumor samples from 1,448 men with prostate cancer. This revealed that for some biomarkers, but not others, there were noticeable differences between tissue microarrays that were clearly the result of batch effects. Stopsack et al. then tested six different ways of fixing these discrepancies using statistical methods. All six approaches were successful, even if the arrays included tumors with different characteristics, such as tumors that had been diagnosed more or less recently. This work highlights the importance of considering batch effects when using tissue microarrays to study cancer. Stopsack et al. have used their statistical approaches to develop freely available software which can reduce the biases that sometimes arise from these technical artifacts. This could help researchers avoid misleading patterns in their data and make it easier to detect real variations in the biomarkers present between tumor samples.

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© 2021, Stopsack et al.

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KS, ST, MW, TG, JV, KP, SF, MF, ML, TL, LM No competing interests declared, PK reports the following disclosures for the last 24-month period: he has investment interest in Convergent Therapeutics Inc, Cogent Biosciences, Context Therapeutics LLC, DRGT, Mirati, Placon, PrognomIQ, SnyDevRx and XLink, he is a company board member for Context Therapeutics LLC and Convergent Therapeutics, he is a company founder for XLink and Convergent Therapeutics, and is/was a consultant/scientific advisory board member for Anji, Candel, DRGT, Immunis, AI (previously OncoCellMDX), Janssen, Progenity, PrognomIQ, Seer Biosciences, SynDevRX, Tarveda Therapeutics, and Veru, and serves on data safety monitoring boards for Genentech/Roche and Merck. He reports spousal association with Bayer, GP reports the following disclosures for the last 24-month period: he had investment interest in CRA Health; he is a co-founder and company board member of Phaeno Biotechnology; he is a consultant / scientific advisory board member for Konica-Minolta, Delfi Diagnostics and Foundation Medicine; he serves on a data safety monitoring board for Geisinger. None of these activities are related to the content of this article