ABSTRACT
Women of African ancestry (Black women) are more likely to have aggressive breast tumors than White
women, and the survival gap between Black and White women is 40%. The tumor immune milieu and its
interaction with tumor cells may play a pivotal role in explaining this disparity. African ancestry is associated
with a stronger response to immune activation, and breast tumors from Black women have significantly more
tumor-infiltrating lymphocytes and CD8+ T cells than White women. Despite this, Black women fare worse than
White women with breast cancer, and this at odds with a wealth of studies that show a strong presence of
tumor-infiltrating immune cells is correlated with better outcomes. This apparent paradox may be reconciled
with Schreiber’s immunoediting model, wherein immune cells interact with the tumor to shape tumor
immunogenicity. Because women of African descent have stronger immune responses, we hypothesize that
their own immune systems select for more aggressive breast tumors by way of immunoediting.
To address this novel hypothesis, we will use frozen breast tumor and blood samples from Roswell
Park Comprehensive Cancer Center to obtain a single dataset that will be used to investigate two related
research aims. First, we will compare spatial patterns of immune infiltration and genetic diversity within a tumor
sample. If immune infiltrates are exerting a selective pressure on tumor cells, spatial regions of high immune
infiltration should correspond to lower tumor genetic diversity and these regions are also expected to display
molecular signatures of immunoediting, manifested as neoantigen depletion, mutations in antigen presenting
genes, immunosuppression, or exclusion. To examine this, tissue cores will be extracted from breast tumors
from 80 patients (40 Black, 40 White) – one core from a region of high immune infiltration and one from low
infiltration. Whole exome sequencing and RNA-seq will be performed on each tumor core, and sequence data
will be examined for genetic diversity and immunoediting using established bioinformatic methods. Second, we
will compare breast tumors from Black and White women for immune subsets inferred from RNA-seq data and
molecular signatures of immunoediting. We expect that tumors from Black patients will have stronger overall
immune responses inferred from RNA-seq data and tumors that show more evidence of immunoediting.
Our proposal will employ a suite of bioinformatics techniques to compare the tumor-immune co-
evolutionary landscape in breast tumors from Black and White women. Our results may have implications for
immunotherapy efficacy by race and may open new avenues for the design of effective combinatory therapies
that are personalized for a patient’s immune milieu and/or ancestral background.