Department of Pathology, School of Medicine and Health Sciences, University of North Dakota, Grand Forks, ND
Sandeep K. Singhal , Kevin Gardner
Background: The multifunctional transcriptional repressor, Kaiso, is a member of the BTB/POZ (Broad complex, Tramtrak, Bric `aBrac/Pox zinc finger) family of zinc finger proteins. Kaiso protein levels in both the nucleus and the cytoplasm have each been shown to be highly sensitive and independent predictors of overall breast cancer survival. Through the use of gene signatures and/or gene modules developed through the analysis of RNA-seq data from breast cancer patients following biomarker stratification by either nuclear Kaiso, cytoplasmic Kaiso, or the Kaiso’s functional downstream target LC3A/B, we demonstrate the utility of Kaiso and LC3A/B derived signatures as predictors of treatment outcome. Methods: We used a machine Learning approach to assess a cohort of racially diverse 555 BC patients who underwent surgery for their primary BC in Greenville, NC and develop proteomics-based genomics (PbG) signatures. The cross-validated logistic regression modeling using publicly available gene expression data compiled from neoadjuvant clinical trials (N=996, JCO:30(16):1996-2004). Results: Kaiso and LC3A/B derived gene modules show accuracy in predicting pathological complete response (pCR, AUC = 0.728, 95% CI: 0.689-0.764). Moreover, predictive estimates of distant metastasis-free survival utilizing Kaiso and LC3A/B derived gene modules are also significant (overall DMFS, AUC= 0.737, 95% CI: 0.665-0.819) and (DMFS of non-pCR patients AUC= 0.71, 95% CI: 0.633-0.773). We then validate these findings in an independent, racially diverse breast cancer cohort receiving neoadjuvant treatment (N=443). Gene modules based on Kaiso and LC3A/B were also highly predictive in this independent cohort (total cohort pCR, AUC= 0.775, 95% CI: 0.687-0.838; pCR NHW (N=257), AUC= 0.762, 95% CI: 0.659-0.855; pCR Hispanic (N=125), AUC= 0.725, 95% CI: 0.493-0.873; and pCR NHB (N=42), AUC= 0.681, 95% CI:0.405-0.904). Conclusions: Combined analysis by multiplex immunofluorescence and deconvolution of gene expression data show that the protein expression of Kaiso and LC3A/B in tumors are associated with distinct tumor ecosystems where high levels cytoplasmic Kaiso are linked to an immune-suppressed tumor microenvironment.
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