The use of digital pathology for the histomorphologic profiling of pathological specimens is expanding the precision and specificity of quantitative tissue analysis at an unprecedented scale; thus, enabling the discovery of new and functionally relevant histological features of both predictive and prognostic significance. In this study, we apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso ( ZBTB33 ), in the tumors of a large racially diverse breast cancer cohort from a designated health disparities region in the United States. Multiplex multivariate analysis of the association of Kaiso’s subcellular distribution with other breast cancer biomarkers reveals novel functional and predictive linkages between Kaiso and the autophagy-related proteins, LC3A/B, that are associated with features of the tumor immune microenvironment, survival, and race. These findings identify effective modalities of Kaiso biomarker assessment and uncover unanticipated insights into Kaiso’s role in breast cancer progression.

3534 Background: The epigenetic transcriptional regulator, Kaiso (ZBTB33) has been identified as a member of the C2H2 zinc finger proteins containing a BTB/POZ -zinc finger family of transcription factors that are implicated in development of cancer. Although, our understanding of clinical relevance of subcellular distribution (cytoplasmic/nuclear) Kaiso in the growth and survival of human Breast cancer (BC) is limited. Methods: We examined a cohort of 555 BC patients who underwent surgery for their primary BC in Greenville, NC using AI and SM approach. Results: The sub-classification BC shows, cytoplasmic Kaiso is differentially enriched in ER- BC (p=0.001) compared nuclear Kaiso (p=0.8) and is significantly enriched in the more aggressive classes LumB (p=0.0017), HER2+ (p=0.05) and TNBC (p=6.1e-07) with respect to LumA BC patients. Additionally, the survival analysis of different compartments of Kaiso demonstrates that high cytoplasmic Kaiso (HR = 16.29 (7.6 – 34.8), p = 5.5e−13) is much more predictive of poor survival compared to nuclear Kaiso (HR = 2.83 (2.02 – 3.8), p = 6.1e−11). At gene expression level, ZBTB33 mRNA levels do not correlate with either nuclear (Spearman correlation: -0.03157, p= 0.7267) or cytoplasmic levels (Spearman correlation: -0.03526, p= 0.6962) of Kaiso. Surprisingly, ZBTB33 mRNA abundance is predictive of poor overall BC survival as demonstrated in two independent publicly available BC cohorts Metabric (HR = 2.14 (1.49 − 3.08), p = 2.7e−05) and Gyorffy B et al. (HR = 1.81 (1.55 − 2.12), p = 2.5e−14). Nuclear and cytoplasmic levels of Kaiso do not show significant differences based on race p=0.27 and p=0.1 respectively. Conclusions: Our data suggest subcellular distribution of high Kaiso is associated with poor prognosis of BC survival and subcellular localizations of Kaiso may play differential biological roles in BC prognosis.

Multiplexed immunohistochemistry (mIHC) enables the detection, quantification, and localization of many markers within cell or tissue samples, leading to a better understanding of the architecture of a disease at the cellular level. Current mIHC techniques involve long staining and assay times, require dedicated and/or captive instrumentation, and entail tedious assay optimization, hindering their establishment as routine methods. Here, we demonstrate the use of the InSituPlex (R) method for spatial profiling of immuno-oncology targets in FFPE tumor tissue with the UltiMapperT I/O PD-L1 multiplex assay. The panel consists of five protein markers to profile immune infiltration and PD-L1 expression and includes CD8, CD68, PD-L1, pan CK, and SOX10 markers. The assay shows benefits of high and low expression of markers, coexpression and colocalization of proteins in single cells, and completion of staining and image acquisition in 5.5 h. Through the combination of multiplexed characterization of protein expression in whole tissue sections, fast staining workflow, and compatibility with existing instrumentation, the InSituPlex method provides a robust modality for deep phenotyping of the tumor and its microenvironment.

L'invention concerne des procedes et des compositions pour evaluer un contenu genomique a l'aide de particules codees afin d'evaluer de multiples echantillons en parallele.