Women with luminal breast cancers generally have a good prognosis (92% five-year survival). However, Latina/Hispanic women with luminal breast cancer are 30% more likely to present with advanced luminal breast cancer and twice as likely to die. Disparities persist even when accounting for socioeconomic factors. Whether this is due to a more aggressive biologic subtype remains unclear. Here, we aim to identify the signaling networks and intercellular interactions that drive poor prognosis in luminal breast cancer patients and use this data to tailor therapeutic interventions to improve survival. The tumor microenvironment, which is highly heterogeneous, plays an essential role in cancer progression. An additional layer of information lies in the spatial organization of the tissue, with cells coming in close proximity in order to exchange signals over short distances. Thus, to understand the network of interactions and signaling between cells, there is a need for single-cell measurements of multiple cellular features in the intact tissue. Sequential Fluorescence in Situ Hybridization (seqFISH), developed in the lab of Dr. Long Cai, enables precise quantification of several hundreds to several thousands of mRNA transcripts in single cells, preserving the structure of the tissue. In this methodology, fluorescently labeled probes are hybridized onto the fixed tissue, giving rise to a fluorescent signal whenever the corresponding mRNA is present. The tissue is sequentially imaged, washed and re-hybridized, resulting in a unique barcode for each mRNA. seqFISH has been demonstrated both on cell cultures and on whole organs and has been shown to be highly accurate and repetitive. We will use this methodology and combine it with multiplex antibody staining to line mRNA expression with protein localization and modifications. Combining these experimental methodologies with advanced image analysis tools developed by the Long lab will allow an in-depth investigating of the cellular stated and signaling pathways within malignant tissues. Correlating findings between patients, as well as between samples from the same patient taken over time, could potentially provide a deep understanding of the factors leading to poor prognosis, which can in turn improve diagnostics of luminal breast cancer.

Note: This abstract was not presented at the conference.

Citation Format: Michal Polonsky, Krista Round, Victoria Seewaldt, Long Cai. Analysis of luminal breast cancer tumor microenvironment using seqFISH [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr B117.