Qualification of a multiplexed tissue imaging assay and detection of novel patterns of HER2 heterogeneity in breast cancer.

Emerging data suggests that HER2 intratumoral heterogeneity (ITH) is associated with therapy resistance, highlighting the need for new strategies to assess HER2 ITH. A promising approach is leveraging multiplexed tissue analysis techniques such as cyclic immunofluorescence (CyCIF), which enable visualization and quantification of 10-60 antigens at single-cell resolution from individual tissue sections. In this study, we qualified a breast cancer-specific antibody panel, including HER2, ER, and PR, for multiplexed tissue imaging. We then compared the performance of these antibodies against established clinical standards using pixel-, cell- and tissue-level analyses, utilizing 866 tissue cores (representing 294 patients). To ensure reliability, the CyCIF antibodies were qualified against HER2 immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) data from the same samples. Our findings demonstrate the successful qualification of a breast cancer antibody panel for CyCIF, showing high concordance with established clinical antibodies. Subsequently, we employed the qualified antibodies, along with antibodies for CD45, CD68, PD-L1, p53, Ki67, pRB, and AR, to characterize 567 HER2+ invasive breast cancer samples from 189 patients. Through single-cell analysis, we identified four distinct cell clusters within HER2+ breast cancer exhibiting heterogeneous HER2 expression. Furthermore, these clusters displayed variations in ER, PR, p53, AR, and PD-L1 expression. To quantify the extent of heterogeneity, we calculated heterogeneity scores based on the diversity among these clusters. Our analysis revealed expression patterns that are relevant to breast cancer biology, with correlations to HER2 ITH and potential relevance to clinical outcomes.

Comparing syngeneic and autochthonous models of breast cancer to identify tumor immune components that correlate with response to immunotherapy in breast cancer.

BACKGROUND: The heterogeneity of the breast tumor microenvironment (TME) may contribute to the lack of durable responses to immune checkpoint blockade (ICB); however, mouse models to test this are currently lacking. Proper selection and use of preclinical models are necessary for rigorous, preclinical studies to rapidly move laboratory findings into the clinic. METHODS: Three versions of a common syngeneic model derived from the MMTV-PyMT autochthonous model were generated by inoculating 1E6, 1E5, or 1E4 cells derived from the MMTV-PyMT mouse into wildtype recipient mice. To elucidate how tumor latency and TME heterogeneity contribute to ICB resistance, comprehensive characterization of the TME using quantitative flow-cytometry and RNA expression analysis (NanoString) was performed. Subsequently, response to ICB was tested. These procedures were repeated using the EMT6 breast cancer model. RESULTS: The 3 syngeneic versions of the MMTV-PyMT model had vastly different TMEs that correlated to ICB response. The number of cells used to generate syngeneic tumors significantly influenced tumor latency, infiltrating leukocyte populations, and response to ICB. These results were confirmed using the EMT6 breast cancer model. Compared to the MMTV-PyMT autochthonous model, all 3 MMTV-PyMT syngeneic models had significantly more tumor-infiltrating lymphocytes (TILs; CD3+, CD4+, and CD8+) and higher proportions of PD-L1-positive myeloid cells, whereas the MMTV-PyMT autochthonous model had the highest frequency of myeloid cells out of total leukocytes. Increased TILs correlated with response to anti-PD-L1 and anti-CTLA-4 therapy, but PD-L1expression on tumor cells or PD-1 expression of T cells did not. CONCLUSIONS: These studies reveal that tumor cell number correlates with tumor latency, TME, and response to ICB. ICB-sensitive and resistant syngeneic breast cancer models were identified, in which the 1E4 syngeneic model was most resistant to ICB. Given the lack of benefit from ICB in breast cancer, identifying robust murine models presented here provides the opportunity to further interrogate the TME for breast cancer treatment and provide novel insights into therapeutic combinations to overcome ICB resistance.

Macrophage Biology and Mechanisms of Immune Suppression in Breast Cancer.

Macrophages are crucial innate immune cells that maintain tissue homeostasis and defend against pathogens; however, their infiltration into tumors has been associated with adverse outcomes. Tumor-associated macrophages (TAMs) represent a significant component of the inflammatory infiltrate in breast tumors, and extensive infiltration of TAMs has been linked to poor prognosis in breast cancer. Here, we detail how TAMs impede a productive tumor immunity cycle by limiting antigen presentation and reducing activation of cytotoxic T lymphocytes (CTLs) while simultaneously supporting tumor cell survival, angiogenesis, and metastasis. There is an urgent need to overcome TAM-mediated immune suppression for durable anti-tumor immunity in breast cancer. To date, failure to fully characterize TAM biology and classify multiple subsets has hindered advancement in therapeutic targeting. In this regard, the complexity of TAMs has recently taken center stage owing to their subset diversity and tightly regulated molecular and metabolic phenotypes. In this review, we reveal major gaps in our knowledge of the functional and phenotypic characterization of TAM subsets associated with breast cancer, before and after treatment. Future work to characterize TAM subsets, location, and crosstalk with neighboring cells will be critical to counteract TAM pro-tumor functions and to identify novel TAM-modulating strategies and combinations that are likely to enhance current therapies and overcome chemo- and immuno-therapy resistance.