The NanoString GeoMx digital spatial profiling is a new multiplexed platform that quantifies the abundance of tumor- and immune-related proteins in a spatially resolved manner. We performed DSP for the simultaneous assessment of 52 analytes within spatially resolved tissue compartments defined by pan-cytokeratin expression. We compared protein targets between 94 African American/Black and 65 European American/White cases, tumor and stromal tissue compartments, estrogen receptor alpha (ER)-positive and ER-negative cases, and explored potential biomarkers of survival. Of 33 analytes with robust signal for analysis, results were highly replicable. For a subset of markers, correlative analyses between DSP analytes and traditional immunohistochemistry scores revealed moderate to very strong associations between the two platforms. Similarly, DSP analytes and gene expression scores were concordant for 21 of 25 markers with overlap between the two datasets. Several analytes varied by ER status, and across the 25 immune markers surveyed, 14 had a significant inverse association with ER expression. B7 homolog 3 (B7-H3; encoded by CD276) was the only analyte to show a significant difference by race, being lower in both the tumor and stromal compartments in Black women. DSP markers that were associated with survival included CD8, CD25, CD56, CD127, EpCAM, ER, Ki-67, and STING. We conclude that DSP is an efficient tool for screening tumor- and immune-related markers in a simultaneous fashion and yields results that are concordant with established immune profiling assays. DSP immune analytes were inversely associated with ER expression, in agreement with a substantial body of previous work that documents higher immune infiltration in ER-negative breast cancers. This technology revealed that scores of the B7-H3 protein were significantly lower in breast cancers from Black women compared with White women, an intriguing finding that requires replication in independent and racially diverse female populations.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8732343PMC
http://dx.doi.org/10.1002/1878-0261.13017DOI Listing

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