176P Multiplex-immunoflourescence Spatial Patterns to Predict Triple-Negative Breast Cancer Molecular Subtypes in the IMMUcan Study
Immuno-Oncology and Technology(2023)
Abstract
IMMUcan (SPECTA NCT02834884) is a European initiative to profile the tumor microenvironment (TME) for a better understanding of immune-tumor interactions. Here, we explored the association between distinct molecular phenotypes and spatial TME patterns in the prospective neoadjuvant IMMUcan TNBC cohort. From a preliminary cohort of 132 patients, matched baseline RNA-seq and multiplex immune fluorescence (mIF) data were available for 66 cases. The mIF panel included CD8, PD1, PD-L1, granzyme B (GB), Ki67 and CK markers. Spatial TME patterns were defined by a graph-based approach detecting densely populated regions of tumor cells and their immune neighbors. TNBC molecular subtypes were derived from RNA-seq as described by Bareche et al. Area Under the Curve (AUC) was used to evaluate the accuracy of spatial patterns to predict TNBC subtypes. A total of eight distinct clusters were identified across the 66 samples, each exhibiting a specific spatial distribution of mIF markers. Two of the clusters showed high performance in predicting immunomodulatory phenotype (AUC: 0.72, 0.71, respectively). These clusters presented elevated densities of CD8+, CD8+/GB+, and CD8+/Ki67+ cells, consistent with CD8+ effector T cells. In addition, a cluster characterized by tumor cells correlated with the luminal androgen-receptor phenotype (AUC: 0.91). The basal-like phenotype was represented by a cluster exhibiting high levels of Ki67+ tumor cells (AUC: 0.61). A distinct cluster displaying an intermediate proportion of Ki67+ tumor cells was observed as well, representing the mesenchymal subtype (AUC: 0.69). These preliminary analyses revealed the presence of informative spatial patterns populating mIF data, linked to the distribution of immune/tumor markers within the TME of TNBC. Of note, these spatial patterns were associated with distinct RNA-seq TNBC subtypes. These findings suggest the predictive power of mIF markers as a potential surrogate to discern TNBC heterogeneity. Consequently, these observations, if confirmed by further validations, could facilitate the implementation of treatment strategies tailored to the TNBC molecular subtypes.
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