Multi-protein spatial signatures in ductal carcinoma in situ (DCIS) of breast

Journal article

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

Authors: Badve, SS; Cho, S; Gökmen-Polar, Y; Sui, Y; Chadwick, C

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer Nature [academic journals on nature.com]
• Journal: British Journal of Cancer
• Volume: 124
• Issue: 6
• Pages: 1150-1159
• Publication date: 2021-01-07
• DOI: 10.1038/s41416-020-01216-6
• EISSN: 1532-1827
• ISSN: 0007-0920
• Language: English
• Keywords: Biology; Genetics; Breast cancer; Cluster (spacecraft); Biomarker; Medicine; Oncology; Hierarchical clustering; Tissue microarray; Artificial intelligence; Pathology; Ductal carcinoma; Cancer; Cluster analysis; Internal medicine