Browsing by Author "Gerdes, Michael"

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    Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast
    (Springer Nature, 2021) Badve, Sunil S.; Cho, Sanghee; Gökmen-Polar, Yesim; Sui, Yunxia; Chadwick, Chrystal; McDonough, Elizabeth; Sood, Anup; Taylor, Marian; Zavodszky, Maria; Tan, Puay Hoon; Gerdes, Michael; Harris, Adrian L.; Ginty, Fiona; Pathology and Laboratory Medicine, School of Medicine
    Background: There is limited knowledge about DCIS cellular composition and relationship with breast cancer events (BCE). Methods: Immunofluorescence multiplexing (MxIF) was used to image and quantify 32 cellular biomarkers in FFPE DCIS tissue microarrays. Over 75,000 DCIS cells from 51 patients (median 9 years follow-up for non-BCE cases) were analysed for profiles predictive of BCE. K-means clustering was used to evaluate cellular co-expression of epithelial markers with ER and HER2. Results: Only ER, PR and HER2 significantly correlated with BCE. Cluster analysis identified 6 distinct cell groups with different levels of ER, Her2, cMET and SLC7A5. Clusters 1 and 3 were not significant. Clusters 2 and 4 (high ER/low HER2 and SLC7A5/mixed cMET) significantly correlated with low BCE risk (P = 0.001 and P = 0.034), while cluster 6 (high HER2/low ER, cMET and SLC7A5) correlated with increased risk (P = 0.018). Cluster 5 (similar to cluster 6, except high SLC7A5) trended towards significance (P = 0.072). A continuous expression score (Escore) based on these 4 clusters predicted likelihood of BCE (AUC = 0.79, log-rank test P = 5E-05; LOOCV AUC = 0.74, log-rank test P = 0.006). Conclusion: Multiplexed spatial analysis of limited tissue is a novel method for biomarker analysis and predicting BCEs. Further validation of Escore is needed in a larger cohort.