Abstract
Triple-negative breast cancer, the poorest-prognosis breast cancer subtype, lacks clinically approved biomarkers for patient risk stratification and treatment management. Prior literature has shown that interrogation of the tumor-immune microenvironment may be a promising approach to fill these gaps. Recently developed high-dimensional tissue imaging technology, such as multiplexed ion beam imaging, provide spatial context to protein expression in the microenvironment, allowing in-depth characterization of cellular processes. We demonstrate that profiling the functional proteins involved in cell-to-cell interactions in the microenvironment can predict recurrence and overall survival. We highlight the immunological relevance of the immunoregulatory proteins PD-1, PD-L1, IDO, and Lag3 by tying interactions involving them to recurrence and survival. Multivariate analysis reveals that our methods provide additional prognostic information compared to clinical variables. In this work, we present a computational pipeline for the examination of the tumor-immune microenvironment using multiplexed ion beam imaging that produces interpretable results, and is generalizable to other cancer types.
Highlights
Triple-negative breast cancer, the poorest-prognosis breast cancer subtype, lacks clinically approved biomarkers for patient risk stratification and treatment management
We further examined a subset of functional proteins, the immunoregulatory proteins PD-1, PD-L1, IDO, and Lag[3], which are in consideration as immunotherapy targets[9,44,45,46,47,48]
Previous research involving Triple-negative breast cancer (TNBC) and multiplexed imaging did not analyze the prognostic relevance of protein co-expression patterns and cell-to-cell interactions
Summary
Triple-negative breast cancer, the poorest-prognosis breast cancer subtype, lacks clinically approved biomarkers for patient risk stratification and treatment management. Developed high-dimensional tissue imaging technology, such as multiplexed ion beam imaging, provide spatial context to protein expression in the microenvironment, allowing in-depth characterization of cellular processes. The absence of common breast cancer hormonal targets and high heterogeneity among TNBC tumors makes treatment management difficult, creating a need for more advanced interrogation of cellular processes within TNBC tumors[8]. Administered treatments, such as checkpoint inhibitors, only provide benefit to a small proportion of treated patients and are associated with high cost and toxicity[9]. MIBI enables in-depth analysis of the TIME, measuring the expression of more than 40 proteins simultaneously while preserving spatial information[29] and avoiding spectral overlap[30] and autofluorescence[31]
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