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Background The PAM50 assay is used routinely in clinical practice to determine breast cancer prognosis and management; however, research assessing how technical variation and intratumoral heterogeneity contribute to misclassification and reproducibility of these tests is limited. Methods We evaluated the impact of intratumoral heterogeneity on the reproducibility of results for the PAM50 assay by testing RNA extracted from formalin-fixed paraffin embedded breast cancer blocks sampled at distinct spatial locations. Samples were classified according to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, Basal-like, or Normal-like) and risk of recurrence with proliferation score (ROR-P, high, medium, or low). Intratumoral heterogeneity and technical reproducibility (replicate assays on the same RNA) were assessed as percent categorical agreement between paired intratumoral and replicate samples. Euclidean distances between samples, calculated across the PAM50 genes and the ROR-P score, were compared for concordant vs. discordant samples. Results Technical replicates (N = 144) achieved 93% agreement for ROR-P group and 90% agreement on PAM50 subtype. For spatially distinct biological replicates (N = 40 intratumoral replicates), agreement was lower (81% for ROR-P and 76% for PAM50 subtype). The Euclidean distances between discordant technical replicates were bimodal, with discordant samples showing higher Euclidian distance and biologic heterogeneity. Conclusion The PAM50 assay achieved very high technical reproducibility for breast cancer subtyping and ROR-P, but intratumoral heterogeneity is revealed by the assay in a small proportion of cases.

Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients with breast cancer. In prior clinical trials, DNA-based approaches have been emphasized, but recent data suggest that RNA-based assessment can capture pathway differences conveniently and may be streamlined with other RNA-based genomic risk scores. Thus, we used RNA expression to study genomic instability (HRD and TP53 pathways) in context of the breast cancer immune microenvironment in three datasets (total n = 4,892), including 1,942 samples from the Carolina Breast Cancer Study, a population-based study that oversampled Black (n = 1,026) and younger women (n = 1,032). Across all studies, 36.9% of estrogen receptor (ER)-positive and 92.6% of ER-negative breast cancer had presence of at least one genomic instability signature. TP53 and HRD status were significantly associated with immune expression in both ER-positive and ER-negative breast cancer. RNA-based genomic instability signatures were associated with higher PD-L1, CD8 T-cell marker, and global and multimarker immune cell expression. Among tumors with genomic instability signatures, adaptive immune response was associated with improved recurrence-free survival regardless of ER status, highlighting genomic instability as a candidate marker for predicting immunotherapy response. Leveraging a convenient, integrated RNA-based approach, this analysis shows that genomic instability interacts with immune response, an important target in breast cancer overall and in Black women who experience higher frequency of TP53 and HR deficiency. Significance: Despite promising advances in breast cancer immunotherapy, predictive biomarkers that are valid across diverse populations and breast cancer subtypes are needed. Genomic instability signatures can be coordinated with other RNA-based scores to define immunogenic breast cancers and may have value in stratifying immunotherapy trial participants.

Background: Obese women have higher risk of aggressive breast tumors and distant metastasis. However, obesity has rarely been assessed in association with metastasis in diverse populations. Methods: In the Carolina Breast Cancer Study Phase 3 (2008–2013), waist-to-hip ratio (WHR), body mass index (BMI), and molecular subtype [PAM50 risk-of-recurrence (ROR) score] were assessed. Obesity measures were evaluated in association with metastasis within five years of diagnosis, overall and stratified by race and ROR score. Absolute risk of metastasis and risk differences between strata were calculated using the Kaplan–Meier estimator, adjusted for age, grade, stage, race, and ER status. Relative frequency of metastatic site and multiplicity were estimated in association with obesity using generalized linear models. Results: High-WHR was associated with higher risk of metastasis (5-year risk difference, RD, 4.3%; 95% confidence interval, 2.2–6.5). It was also associated with multiple metastases and metastases at all sites except brain. The 5-year risk of metastasis differed by race (11.2% and 6.9% in Black and non-Black, respectively) and ROR score (19.5% vs. 6.6% in high vs. low-to-intermediate ROR-PT). Non-Black women and those with low-to-intermediate ROR scores had similar risk in high- and low-WHR strata. However, among Black women and those with high ROR, risk of metastasis was elevated among high-WHR (RDBlack/non-Black = 4.6%, RDHigh/Low-Int = 3.1%). Patterns of metastasis were similar by BMI. Conclusions: WHR is associated with metastatic risk, particularly among Black women and those with high-risk tumors. Impact: Understanding how risk factors for metastasis interact may help in tailoring care plans and surveillance among patients with breast cancer.

Background:Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied.Methods:To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes.Results: Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50–3.78).Conclusions:HRD is associated with poor prognosis and enriched in the tumors of black women.Impact:RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

Supplementary Figure from RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse Patients with Breast Cancer

Supplemental Figure 1 shows differential expression analysis of immune scores according to TP53 and HRD status, stratified by estrogen receptor status in CBCS.

Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients with breast cancer. In prior clinical trials, DNA-based approaches have been emphasized, but recent data suggest that RNA-based assessment can capture pathway differences conveniently and may be streamlined with other RNA-based genomic risk scores. Thus, we used RNA expression to study genomic instability (HRD and TP53 pathways) in context of the breast cancer immune microenvironment in three datasets (total n = 4,892), including 1,942 samples from the Carolina Breast Cancer Study, a population-based study that oversampled Black (n = 1,026) and younger women (n = 1,032). Across all studies, 36.9% of estrogen receptor (ER)-positive and 92.6% of ER-negative breast cancer had presence of at least one genomic instability signature. TP53 and HRD status were significantly associated with immune expression in both ER-positive and ER-negative breast cancer. RNA-based genomic instability signatures were associated with higher PD-L1, CD8 T-cell marker, and global and multimarker immune cell expression. Among tumors with genomic instability signatures, adaptive immune response was associated with improved recurrence-free survival regardless of ER status, highlighting genomic instability as a candidate marker for predicting immunotherapy response. Leveraging a convenient, integrated RNA-based approach, this analysis shows that genomic instability interacts with immune response, an important target in breast cancer overall and in Black women who experience higher frequency of TP53 and HR deficiency.Significance:Despite promising advances in breast cancer immunotherapy, predictive biomarkers that are valid across diverse populations and breast cancer subtypes are needed. Genomic instability signatures can be coordinated with other RNA-based scores to define immunogenic breast cancers and may have value in stratifying immunotherapy trial participants.

Supplemental table 3 shows five-year recurrence hazard ratios for immune classes among ER-negative and ER-positive cases in CBCS.

Tumor-infiltrating lymphocytes play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest in formalin-fixed paraffin embedded tissue sections. Forty-four antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with regulatory T-cell (Treg) markers (CD4, CD25, and FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n = 75), we confirmed subtype-specific immune profiles, including enrichment of Treg markers in Basal-likes. This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with breast cancer subtype, suggesting possible prognostic, or targetable differences. The breast cancer immune microenvironment was analyzed with the nanoString GeoMx® Digital Spatial Profiler (DSP) in cases from the Carolina Breast Cancer Study. Basal-like breast cancers showed increased expression of markers for regulatory T cells. The results were highly reproducible between whole sections and tissue microarrays.

Background: Immunotherapy is a rapidly evolving treatment option in breast cancer; However, the breast cancer immune microenvironment is understudied in Black and younger ( Methods: We used histologic and RNA-based immunoprofiling methods to characterize the breast cancer immune landscape in 1,952 tumors from the Carolina Breast Cancer Study (CBCS), a population-based study that oversampled Black (n = 1,030) and young women (n = 1,039). We evaluated immune response leveraging markers for 10 immune cell populations, compared profiles to those in The Cancer Genome Atlas (TCGA) Project [n = 1,095 tumors, Black (n = 183), and young women (n = 295)], and evaluated in association with clinical and demographic variables, including recurrence. Results: Consensus clustering identified three immune clusters in CBCS (adaptive-enriched, innate-enriched, or immune-quiet) that varied in frequency by race, age, tumor grade and subtype; however, only two clusters were identified in TCGA, which were predominantly comprised of adaptive-enriched and innate-enriched tumors. In CBCS, the strongest adaptive immune response was observed for basal-like, HER2-positive (HER2+), triple-negative breast cancer (TNBC), and high-grade tumors. Younger patients had higher proportions of adaptive-enriched tumors, particularly among estrogen receptor (ER)-negative (ER−) cases. Black patients had higher frequencies of both adaptive-enriched and innate-enriched tumors. Immune clusters were associated with recurrence among ER− tumors, with adaptive-enriched showing the best and innate-enriched showing the poorest 5-year recurrence-free survival. Conclusions: These data suggest that immune microenvironments are intricately related to race, age, tumor subtype, and grade. Impact: Given higher mortality among Black and young women, more defined immune classification using cell-type–specific panels could help explain higher recurrence and ultimately lead to targetable interventions.

Background: Black women suffer 40% higher mortality from breast cancer (BC) compared to non-Hispanic white women, and the underlying causes of these disparities remain uncertain. Growing evidence supports the importance of the immune microenvironment in BC survival, but immune response differences by race are poorly understood. We sought to characterize the immune microenvironment of BC to evaluate how phenotypes of immune response vary across race and tumor intrinsic subtype to impact clinical outcomes. Methods: We leveraged the Carolina Breast Cancer Study (CBCS), a large population-based study that oversampled young (≤50) and black women with invasive breast cancer and collected tumor tissue on >95% of participants. We curated a 48-gene panel representative of 13 individual immune cell types, and performed NanoString gene expression profiling on tissue from 1957 BC patients, including 1033 (53%) Black and 924 (47%) Non-Black women. Consensus clustering was used to identify phenotypes of immune response, and individual immune cell scores were calculated as the median expression of cell-type markers. Immune phenotypes and cell-type scores were compared against validated protein markers and H&E-based quantification of TILs from corresponding tissue microarrays (TMAs). We estimated associations of immune classes with BC intrinsic subtype, ROR-PT scores (calculated as low, medium and high), age and race using relative frequency differences (RFDs), adjusting for age and tumor stage. Cell type scores were compared by race using Welch’s t-tests and adjusted for multiple comparisons with the Benjamani-Hochberg procedure. Results: We identified three BC immune phenotypes primarily defined by features related to an Adaptive-enriched, Innate-enriched, or a Quiet immune microenvironment. These expression-based groups correlated with histological evidence of immune cells from corresponding TMAs. Similarly, expression-based cell scores correlated strongly with protein-based quantification of immune cells from corresponding TMAs (e.g. B-cell score vs. CD19 immunofluorescence, rho=0.75; ICOS RNA counts vs. protein; Rho=0.76). Both Adaptive-enriched and Innate-enriched tumors were associated with high ROR-PT scores [RFD for Adaptive-enriched vs. Quiet: 24.1% (95% CI 19.3-28.8); Innate-enriched vs. Quiet RFD: 13.1 (95% CI 9.1-17); frequencies: 37.2%, 26.2% and 10% for Adaptive, Innate and Quiet, respectively], the basal-like intrinsic subtype [RFD for Adaptive-enriched vs. Quiet: 19.4% (95% CI 14.3-24.6); Innate-enriched vs. Quiet RFD: 9.8 (95% CI 5.6-14.1); frequencies: 43.4%, 27.4% and 8.9% respectively] and Black race [RFD for Adaptive-enriched vs. Quiet: 16.1% (95% CI 10.3-21.9); Innate-enriched vs. Quiet RFD: 9.5 (95% CI 3.9-15); frequencies 60.5%, 53.5% and 42.5% respectively]. After adjusting for tumor subtype, the Adaptive-enriched class remained associated with Black race (RFD for Adaptive-Enriched vs Quiet: 7.5% (95% CI 1.4-13.6). Conversely, tumors in the immune-quiet group were primarily non-basal (90%) with low ROR-PT scores (86.7%). Within the Adaptive-enriched class, Black women displayed decreased CD8 T cell scores (p=0.05) but increased T-reg cell scores (p=0.02) relative to Non-Black women. Conclusion: Immune response appears to be intricately related to race and tumor subtype, with black women having strong associations with adaptive-enriched and innate-enriched immune microenvironments. Differences in CD8 T cell and Treg expression suggest that even within broad classes of immune response, racial differences in specific cell-type distributions exist. Immune response differences may be targetable to improve treatment response, and therefore it is important to identify race- and subtype-specific differences in immune microenvironments. Citation Format: Alina M Hamilton, Linnea T Olsson, Benjamin C Calhoun, Katherine A Hoadley, Melissa A Troester. Racial differences in breast cancer immune microenvironments [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SS1-05.

While mammographic breast density is associated with breast cancer risk in humans, there is no comparable surrogate risk measure in mouse and rat mammary glands following various environmental exposures. In the current study, mammary glands from mice and rats subjected to reproductive factors and exposures to environmental chemicals that have been shown to influence mammary gland development and/or susceptibility to mammary tumors were evaluated for histologic density by manual and automated digital methods. Digital histological density detected changes due to hormonal stimuli/reproductive factors (parity), dietary fat, and exposure to environmental chemicals, such as benzophenone-3 and a combination of perfluorooctanoic acid and zeranol. Thus, digital analysis of mammary gland density offers a high throughput method that can provide a highly reproducible means of comparing a measure of histological density across independent experiments, experimental systems, and laboratories. This methodology holds promise for the detection of environmental impacts on mammary gland structure in mice and rats that may be comparable to human breast density, thus potentially allowing comparisons between rodent models and human breast cancer studies.

Background: Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied. Methods: To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes. Results : Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50–3.78). Conclusions: HRD is associated with poor prognosis and enriched in the tumors of black women. Impact: RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

PURPOSE: Black women have a 40% increased risk of breast cancer-related mortality. These outcome disparities may reflect differences in tumor pathways and a lack of targetable therapies for specific subtypes that are more common in Black women. Hepatocyte Growth Factor (HGF) is a targetable pathway that promotes breast cancer tumorigenesis, is associated with basal-like breast cancer, and differentially expressed by race. This study assessed whether a 38-gene HGF expression signature is associated with recurrence and survival in Black and non-Black women. METHODS: Study participants included 1,957 invasive breast cancer cases from the Carolina Breast Cancer Study. The HGF signature was evaluated in association with recurrence (n=1,251, 171 recurrences), overall, and breast-cancer specific mortality (n=706, 190/328 breast cancer/overall deaths) using Cox proportional hazard models. RESULTS: Women with HGF positive tumors had higher recurrence rates [HR 1.88, 95%CI (1.19, 2.98)], breast cancer specific mortality [HR: 1.90, 95%CI (1.26, 2.85)], and overall mortality [HR: 1.69; 95%CI (1.17, 2.43)]. Among Black women, HGF positivity was significantly associated with higher 5-year rate of recurrence [HR: 1.73; 95%CI (1.01, 2.99)], but this association was not significant in non-Black women [HR 1.68; 95%CI (0.72, 3.90)]. Among Black women, HGF-positive tumors had elevated breast cancer-specific mortality [HR 1.80, 95%CI (1.05, 3.09)], which was not significant in non-Black women [HR:1.52; 95%CI (0.78, 2.99)]. CONCLUSION: This multi-gene HGF signature is a poor-prognosis feature for breast cancer and may identify patients who could benefit from HGF-targeted treatments, an unmet need for Black and triple negative patients.

Summary: Martini and colleagues performed genetic ancestry estimation on a unique international triple-negative breast cancer (TNBC) study enriched for participants with African ancestry. They identified gene signatures indicative of ancestry in race-associated TNBC and found ancestry-associated immunologic differences that may contribute to racial disparities in breast cancer. See related article by Martini et al., p. 2530 (5).

Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.

Background: Breast cancers in recently postpartum women may have worse outcomes, but studies examining tumor molecular features by pregnancy recency have shown conflicting results. Methods: This analysis used Carolina Breast Cancer Study data to examine clinical and molecular tumor features among women less than 50 years of age who were recently (≤10 years prior) or remotely (>10 years prior) postpartum, or nulliparous. Prevalence odds ratios (POR) and 95% confidence intervals (CI) were estimated using multivariable models. Results: Recently postpartum women (N = 618) were more frequently lymph node–positive [POR (95% CI): 1.66 (1.26–2.19)], estrogen receptor (ER)-negative [1.37 (1.02–1.83)], and IHC-based triple negative [1.57 (1.00–2.47)] compared with nulliparous (N = 360) women. Some differences were identified between recent versus remotely postpartum; smaller tumor size [0.67 (0.52–0.86)], p53 wildtype [0.53 (0.36–0.77)], and non–basal-like phenotype [0.53 (0.33–0.84)] were more common among recently postpartum. Recently postpartum (vs. nulliparous) had significant enrichment for adaptive immunity, T cells, B cells, CD8 T cells, activated CD8 T cells/natural killer (NK) cells, and T follicular helper (Tfh) cells and higher overall immune cell scores. These differences were attenuated in remotely (compared with recently) postpartum women. Conclusions: These results suggest a dominant effect of parity (vs. nulliparity) and a lesser effect of pregnancy recency on tumor molecular features, although tumor immune microenvironments were altered in association with pregnancy recency. Impact: Our study is unique in examining tumor immune microenvironment and RNA-based markers according to time since last childbirth. Future studies should examine the interplay between tumor features, postdiagnostic treatment, and outcomes among recently postpartum women. See related commentary by McDonald et al., p. 518

Background: TP53 and estrogen receptor (ER) both play essential roles in breast cancer development and progression, with recent research revealing cross-talk between TP53 and ER signaling pathways. Although many studies have demonstrated heterogeneity of risk factor associations across ER subtypes, associations by TP53 status have been inconsistent. Methods: This case–case analysis included incident breast cancer cases (47% Black) from the Carolina Breast Cancer Study (1993–2013). Formalin-fixed paraffin-embedded tumor samples were classified for TP53 functional status (mutant-like/wild-type-like) using a validated RNA signature. For IHC-based TP53 status, mutant-like was classified as at least 10% positivity. We used two-stage polytomous logistic regression to evaluate risk factor heterogeneity due to RNA-based TP53 and/or ER, adjusting for each other and for PR, HER2, and grade. We then compared this with the results when using IHC-based TP53 classification. Results: The RNA-based classifier identified 55% of tumors as TP53 wild-type-like and 45% as mutant-like. Several hormone-related factors (oral contraceptive use, menopausal status, age at menopause, and pre- and postmenopausal body mass index) were associated with TP53 mutant-like status, whereas reproductive factors (age at first birth and parity) and smoking were associated with ER status. Multiparity was associated with both TP53 and ER. When classifying TP53 status using IHC methods, no associations were observed with TP53. Associations observed with RNA-based TP53 remained after accounting for basal-like subtype. Conclusions: This case–case study found breast cancer risk factors associated with RNA-based TP53 and ER. Impact: RNA-based TP53 and ER represent an emerging etiologic schema of interest in breast cancer prevention research.

Targeted mRNA expression panels, measuring up to 800 genes, are used in academic and clinical settings due to low cost and high sensitivity for archived samples. Most samples assayed on targeted panels originate from bulk tissue comprised of many cell types, and cell-type heterogeneity confounds biological signals. Reference-free methods are used when cell-type-specific expression references are unavailable, but limited feature spaces render implementation challenging in targeted panels. Here, we presentDeCompress, a semi-reference-free deconvolution method for targeted panels.DeCompressleverages a reference RNA-seq or microarray dataset from similar tissue to expand the feature space of targeted panels using compressed sensing. Ensemble reference-free deconvolution is performed on this artificially expanded dataset to estimate cell-type proportions and gene signatures. In simulated mixtures, four public cell line mixtures, and a targeted panel (1199 samples; 406 genes) from the Carolina Breast Cancer Study,DeCompressrecapitulates cell-type proportions with less error than reference-free methods and finds biologically relevant compartments. We integrate compartment estimates intocis-eQTL mapping in breast cancer, identifying a tumor-specificcis-eQTL forCCR3(C-C Motif Chemokine Receptor 3) at a risk locus.DeCompressimproves upon reference-free methods without requiring expression profiles from pure cell populations, with applications in genomic analyses and clinical settings.

Basal-like breast cancers (BBC) exhibit subtype-specific phenotypic and transcriptional responses to stroma, but little research has addressed how stromal-epithelial interactions evolve during early BBC carcinogenesis. It is also unclear how common genetic defects, such as p53 mutations, modify these stromal-epithelial interactions. To address these knowledge gaps, we leveraged the MCF10 progression series of breast cell lines (MCF10A, MCF10AT1, and MCF10DCIS) to develop a longitudinal, tissue-contextualized model of p53-deficient, pre-malignant breast. Acinus asphericity, a morphogenetic correlate of cell invasive potential, was quantified with optical coherence tomography imaging, and gene expression microarrays were performed to identify transcriptional changes associated with p53 depletion and stromal context. Co-culture with stromal fibroblasts significantly increased the asphericity of acini derived from all three p53-deficient, but not p53-sufficient, cell lines, and was associated with the upregulation of 38 genes. When considered as a multigene score, these genes were upregulated in co-culture models of invasive BBC with increasing stromal content, as well as in basal-like relative to luminal breast cancers in two large human datasets. Taken together, stromal-epithelial interactions during early BBC carcinogenesis are dependent upon epithelial p53 status, and may play important roles in the acquisition of an invasive morphologic phenotype.

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization and iterative data visualization and biological validation. The approach was evaluated using a large cohort ($N=\kern0.5em 1649$) from the Carolina Breast Cancer Study, two cohorts of moderate sample size ($N=359$ and$130$) and a small published dataset ($N=12$). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoString’s commercial package, without diminishing biological variation, especially in long-term longitudinal multiphase or multisite cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization and visualization of NanoString nCounter data are an imperative component of study design that influences results in downstream analyses.

The metabolic landscape of the prostate changes with malignant transformation, and metabolomics is a means of identifying diagnostic and prognostic biomarkers for prostate cancer. Epidemiology and registry studies containing archival formalin-fixed paraffin-embedded (FFPE) specimens are a rich resource for this work but this method of tissue preservation presents a challenge due to loss of metabolites. We optimized global metabolic profiling in FFPE tissue and identified metabolites distinguishing tumor from normal prostate tissue, and aggressive from non-aggressive prostate cancer. For optimization of metabolomics in FFPE tissues, we obtained matched frozen and FFPE tumor tissue from 62 prostate cancer cases who underwent radical prostatectomy (RP) at the University of North Carolina (UNC) hospital, of which 24 also had adjacent normal prostate tissue. To identify metabolites associated with tumor aggressiveness, we obtained matched tumor and normal FFPE tissue from 60 prostate cancer patients (Gleason ≥4+3, n=30; Gleason ≤3+4, n=30) who underwent RP participating in the UNC Health Registry/Cancer Survivorship Cohort. Following log transformation and imputation of missing values with the minimum observed value for each compound, Welch's two-sample t-test was used to identify biochemicals that differed significantly between groups. Random forest analysis evaluated predictive accuracy of metabolites for distinguishing tumor from normal prostate tissue. We identified 768 compounds of known identity in frozen and 119 in matched FFPE tissues. Therefore, only 15% of the metabolites detected in frozen samples were recovered from corresponding FFPE tissue, with 80% of these common to both FFPE and matched frozen tissues. We found a predictive accuracy of 78% and 67% for frozen and FFPE tissue, respectively, for distinguishing tumor from normal. Of 39 metabolites significantly altered between matched tumor and normal FFPE tissue, 47% belonged to the lipid class, and despite a greater number of significantly altered metabolites in frozen tissue (246), the proportion belonging to the lipid class was similar (50%). Citrate, integral to normal prostate metabolism, and citrulline, involved in nitric oxide synthesis, had significantly lower levels in aggressive versus non-aggressive tumors. Cell membrane phospholipids were found at significantly higher levels in aggressive tumors. Common patterns of altered metabolites in tumor vs. normal prostate were observed irrespective of tissue preservation method, despite loss of a large proportion of metabolites during the process of FFPE. As such, FFPE studies are feasible particularly when lipid metabolism is of interest as this class appears one of the best preserved in FFPE. This work will pave the way for incorporating metabolomics profiling of FFPE specimens into epidemiology and registry-based studies of prostate cancer. Citation Format: Sophia Rachael Halliday, Linnea T. Olsson, Alina Hamilton, Sivapriya Ramamoorthy, Jason Kitchen, Erin Kirk, Laura Farnan, Adrian Gerstel, Melissa A. Troester, Jannette T. Bensen, Sara E. Wobker, Emma Allott. Metabolomics profiling of formalin-fixed paraffin-embedded prostate tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2347.

SUMMARY Immune checkpoint blockade (ICB) has improved outcomes in some cancers. A major limitation of ICB is that most patients fail to respond, which is partly attributable to immunosuppression. Obesity appears to improve immune checkpoint therapies in some cancers, but impacts on breast cancer (BC) remain unknown. In lean and obese mice, tumor progression and immune reprogramming were quantified in BC tumors treated with anti-programmed death-1 (PD-1) or control. Obesity augments tumor incidence and progression. Anti-PD-1 induces regression in lean mice and potently abrogates progression in obese mice. BC primes systemic immunity to be highly responsive to obesity, leading to greater immunosuppression, which may explain greater anti-PD-1 efficacy. Anti-PD-1 significantly reinvigorates antitumor immunity despite persistent obesity. Laminin subunit beta-2 (Lamb2), downregulated by anti-PD-1, significantly predicts patient survival. Lastly, a microbial signature associated with anti-PD-1 efficacy is identified. Thus, anti-PD-1 is highly efficacious in obese mice by reinvigorating durable antitumor immunity., In brief Pingili et al. show that breast cancer exacerbates obesity-driven immunosuppression. Anti-PD-1 reinvigorates antitumor immunity in the tumor microenvironment, mammary fat pad, and peripherally. Lamb2, downregulated by anti-PD-1 in tumors, associates with obesity and poor survival in patients. A microbial signature associated with immune checkpoint inhibitor efficacy is identified., Graphical Abstract

Background: Black breast cancer patients have p53 loss in 60% of their tumors, compared to 35% p53 loss in white breast cancer patients. The tumor suppressor p53 has pleiotropic effects on DNA repair, as it regulates both error prone and error-free DNA repair pathways. These effects on DNA repair represent molecular vulnerabilities that influence chemotherapy response, both directly and indirectly through the activation of immune responses. While studies have begun to elucidate DNA repair imbalance and immune response in human cancer, little is known about how these pathways differ by race. Methods: To study DNA repair and immune response in breast cancer, we performed gene expression analysis on FFPE samples from the Carolina Breast Cancer Study (CBCS), a large population-based study that oversampled black and younger women. We curated a list of DNA repair genes representing regulators of error prone and error free DNA repair. Pathways included Nucleotide Excision Repair (NER), Fanconi Anemia (FA), Mismatch repair (MMR), Base Excision Repair (BER), Homologous Recombination (HR), Translesion Synthesis (TLS), Alternative End Joining (AEJ), Checkpoint, and APOBEC. In addition, we developed a 50-gene immune panel representing 12 individual immune cell types (B cells, T cells, Treg cells, T help cells, T follicular helper cells, CD8 T cells, NK cells, Eosinophils, Neutrophils, M1 & M2 Macrophages) and both adaptive and innate arms of the immune system. A total of 1464 patients (53% black, 53% under 50) were included in the current analysis. We used consensus clustering to identify groups of patients based on DNA repair gene expression and used linear regression to estimate the relative frequency differences between these classes and demographic and clinical characteristics. Results: We found that breast cancers grouped into four clusters based on DNA repair gene expression. One cluster, ‘Repair High’, represented 32% of the tumors, and had high expression of NER, NHEJ, HR, and FA genes, suggesting a broad DNA repair response. Another group, ‘HR/FA High’ represented 23% of the tumors and was enriched for high expression of HR and FA genes. An “APOBEC High” group consisted of 32% of the tumors and was enriched for high expression of APOBEC family genes (APOBEC3D, APOBEC1, APOBEC3A, APOBEC3H, APOBEC3B). Finally, 13% of tumors, had a ‘Heterogeneous Repair’ pattern of high expression of HR, NHEJ, and FA genes, but lower expression of NER genes. The HR/FA and Heterogeneous Repair groups were enriched for TP53 mutant-like tumors (93% vs. 5% and 61% vs. 38% Mutant vs. Wildtype respectively). In addition, the Heterogeneous Repair group was enriched for Hormone Receptor positive samples ([RFD] 8.2% (0.613, 15.3), 77% vs. 23% in positive vs. negative respectively), while the HR/FA High group was significantly enriched for TNBC ([RFD] HR/FA: 51.2% (45.1, 57.1), 75% vs. 25% TNBC vs. non-TNBC respectively). The Repair High group was the only group enriched for non-black race ([RFD]: 10.4% (4.0, 16.7), 42% vs. 58% in blacks vs. non-blacks respectively). Finally, DNA repair classes were associated with immune scores, with the APOBEC High tumors having a significantly higher Eosinophil score (p = 0.021) and Neutrophil score (p = 0.007) compared to the other four groups. Conclusion: DNA repair expression is highly variable across breast tumors and may depend upon TP53 status, tumor subtype, and race. Differential immune marker expression by DNA repair group suggests some DNA repair groups may have differential response to immune-targeted therapies. DNA repair, immune response, and race are inter-related in breast cancer and unraveling and ultimately targeting breast cancer disparities may require coordinated evaluation of these pathways. Citation Format: Andrea Walens, Alina M Hamilton, Markia A Smith, Xiaohua Gao, Erin L Kirk, Stephen D Hursting, Katherine A Hoadley, Cyrus Vaziri, Melissa A Troester. Dna repair imbalance and immune response in breast cancer mortality disparities [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS19-03.

A small fraction of cancer patients with advanced disease survive significantly longer than patients with clinically comparable tumors. Molecular mechanisms for exceptional responses to therapy have been identified by genomic analysis of tumor biopsies from individual patients. Here, we analyzed tumor biopsies from an unbiased cohort of 111 exceptional responder patients using multiple platforms to profile genetic and epigenetic aberrations as well as the tumor microenvironment. Integrative analysis uncovered plausible mechanisms for the therapeutic response in nearly a quarter of the patients. The mechanisms were assigned to four broad categories���DNA damage response, intracellular signaling, immune engagement, and genetic alterations characteristic of favorable prognosis���with many tumors falling into multiple categories. These analyses revealed synthetic lethal relationships that may be exploited therapeutically and rare genetic lesions that favor therapeutic success, while also providing a wealth of testable hypotheses regarding oncogenic mechanisms that may influence the response to cancer therapy. Profiling multi-platform genomics of 110 cancer patients with an exceptional therapeutic response, Wheeler et al. identify putative molecular mechanisms explaining this survival phenotype in ���23% of cases. Therapeutic success is related to rare molecular features of responding tumors, exploiting synthetic lethality and oncogene addiction.

Background Multigene assays for breast cancer are becoming more commonly used for research, diagnostic, and treatment-selection purposes. These assays are commonly based on a single tumor sample, so this study assesses whether clinically-relevant multigene scores are subject to misclassification due to technical variation or intratumoral heterogeneity. Methods Using FFPE blocks, tumors from 37 patients were sampled at different pathologist-selected spatial locations, targeting regions with distinct histological appearance. A second pathologist assessed mitotic activity and presence of immune infiltration for each specimen. Gene expression was quantified using the PAM50 assay. Samples were classified with respect to intrinsic subtype (Luminal A, Luminal B, HER2-enriched, or Basal-like) and risk of recurrence with proliferation score (ROR-P, high vs. med/low). Euclidean distances between samples were calculated across the 50 genes, and the distribution of Euclidean distances were compared for samples that were concordant vs. discordant for each multigene classifier for PAM50 or ROR-P. Results Of the 37 tumors, 11 had samples with discordant PAM50 subtype and 7 had samples with discordant ROR-P group (75% and 83% agreement, respectively). The Euclidean distance between paired samples with discordant PAM50 intrinsic subtype or ROR-P score was significantly greater than that among concordant tumors. Samples discordant for ROR-P had more heterogeneity in histological characteristics, while discordance of PAM50 subtype call was generally not predicted by heterogeneity of these histological characteristics. Conclusion The concordance of PAM50 subtype calls and ROR-P, despite oversampling of heterogenous-appearing tumor regions, demonstrates reproducibility of the PAM50 classifier for breast cancer tumor intrinsic subtyping. However, assay sampling strategies for histologically heterogeneous tumors merit further consideration. Citation Format: Amber N. Hurson, Alina Hamilton, Linnea T. Olsson, Erin L. Kirk, Benjamin C. Calhoun, Joseph Geradts, Mark E. Sherman, Melissa A. Troester. Intratumoral heterogeneity of prognostic multigene signatures for breast cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-068.

Background: Tumor infiltrating lymphocytes (TILs) play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. Methods: To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling (DSP) of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest (ROIs) in formalin-fixed paraffin embedded tissue sections. 44 antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. Results: In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with Regulatory T cell (Treg) markers (CD4, CD25, FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n=75), we confirmed subtype-specific immune profiles, including enrichment of Treg markers in Basal-likes. Conclusion: This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with BC subtype, suggesting possible prognostic or targetable differences. Citation Format: Andrea Walens, Linnea T. Olsson, Xiaohua Gao, Alina M. Hamilton, Erin L. Kirk, Stephanie M. Cohen, Bentley R. Midkiff, Yongjuan Xia, Mark E. Sherman, Nana Nikolaishvili-Feinberg, Katherine A. Hoadley, Melissa A. Troester, Benjamin C. Calhoun. Protein-based immune profiles of basal-like vs luminal breast cancers [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PO-090.

Background: High levels of tumor infiltrating lymphocytes have been associated with favorable prognosis in triple negative and HER2-positive breast cancer (BC), especially in tumors with high mutation burden. Recently, our group showed that TP53 functional defects are strongly associated with black race in the Carolina Breast Cancer Study (CBCS). However, the immune microenvironment has been inconsistently associated with racial disparities in BC. Methods: To characterize immune phenotypes in BC, we curated a 50-gene NanoString immune panel and validated the gene set using RNA sequencing data from The Cancer Genome Atlas (TCGA). We applied the NanoString panel in the CBCS and estimated associations with immune infiltrates, BC intrinsic subtype, proliferation scores, p53 mutation signature and race using relative frequency differences (RFDs) as the measure of association. Results: Our 50-gene immune panel produced sample groupings in TCGA similar to that observed with the deconvolution algorithm, CIBERSORT. In CBCS (n=1208), we identified three immune groups primarily defined by features related to either adaptive immunity, innate immunity, or a quiet immune environment. Confirming that our expression-based groups reflect the tumor immune microenvironment, these immune groups correlated with histological evidence of immune cells from H&E slides in both TCGA and CBCS. The adaptive-enriched group was strongly associated with young age (≤50 years), high tumor grade, higher proliferation scores and the basal-like intrinsic subtype. TP53 mutant-like status was strongly associated with the adaptive-enriched immune group (RFD: 25.3%, p Conclusions: Our immune panel defines groups of BCs according to type of immune infiltration. Consistent with previous literature, we show that adaptive immunity is associated with aggressive breast tumors in CBCS. In addition, our data suggest an immunomodulatory effect of TP53 functional status–a variable we have previously associated with race in the CBCS. We provide evidence for a role of the immune microenvironment in racial disparities of BC. Further characterization of individual immune cell populations by race could reveal potential targets for BC intervention strategies that improve survivorship disparities. Citation Format: Alina M. Hamilton, Linnea T. Olsson, Benjamin C. Calhoun, Katherine A. Hoadley, Melissa A. Troester. Association of immune microenvironment and race in the Carolina Breast Cancer Study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1184.

Breast cancer is the second leading cause of cancer-related deaths in women in the United States. Although breast cancer mortality rates have dropped over the last few decades, the mortality rate for Black women is still 40% higher than White women. Even among the breast cancer subtype with the best prognosis (ER+/HER2-), Black women still have a higher risk of recurrence (ROR) by PAM50. Some work has been done to uncover differences in the biology of breast cancer between White and Black women, but there has been little study of how immune responses differ by race. To identify spatial relationships between tumor and specific immune subpopulations in the microenvironment of breast cancer, we used the GeoMx (NanoString) platform to perform digital spatial profiling (DSP) of tumor whole sections and tumor microarrays (TMA) from the Carolina Breast Cancer Study (CBCS), a large population-based study that oversampled for Black and younger women. DSP identifies relationships among immune subpopulations, analyzing approximately 40 immune markers in areas selected for CD45, CD68, or pan-cytokeratin content. Thus regions of interest (ROIs) can be selected to evaluate immune ‘hot spots' and the tumor microenvironment, separately. In whole tumor slides, we found that immune hot spots (high CD45 infiltrated ROIs) had elevated expression of many immune markers, suggesting that there was a widespread, robust immune response that included Macrophages, Dendritic cells, and B-cells in addition to T-cells. However, we also observed that immune markers were detectable in tumor-enriched areas, and that tumor-enriched areas had distinct immune signals depending upon subtype, with Regulatory T cell (Treg) markers being higher in Basal-like breast cancers and Dendritic cell markers being higher in Luminal A breast cancers. Extending these findings to tumor-enriched ROIs on TMAs, we evaluated 76 patients and once again found subtype-specific immune responses, including enrichment of Treg markers in Basal-like breast cancers. Receiver operating characteristic (ROC) analysis of Treg marker expression as a predictor for Basal-like versus Luminal A breast cancer had an area under the curve (AUC) score of 0.754, pointing to Treg markers as an effective predictor of breast cancer subtype. With DSP analysis, immune marker expression can elucidate spatial differences in the tumor microenvironment and predict breast cancer subtype and other clinicopathologic and prognostic features. Our data demonstrates that both whole slide and TMA specimens can be used to understand the breast cancer microenvironment by subtype. The contribution of race to these immune responses will require larger numbers of tumors of specific subtypes, as there are strong immune response differences by subtype. Citation Format: Andrea Walens, Linnea Olsson, Xiaohua Gao, Alina Hamilton, Erin Kirk, Katherine Hoadley, Ben Calhoun, Melissa Troester. Uncovering spatial relationships of the tumor microenvironment in the Carolina Breast Cancer Study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5389.

Evidence suggests that environmental substances regulating estrogenic pathways during puberty may be detrimental to the developing mammary gland (MG). Manganese (Mn) is a trace mineral required for normal physiological processes. Prepubertal exposure to Mn induces precocious puberty in rats, an event associated with early elevations in puberty-related hormones, including estradiol (E2). However, until now the effect of Mn-induced precocious MG development has not been determined. Therefore, we assessed the ability of prepubertal Mn exposure to advance normal MG development and alter E2 driven pathways involved in tumorigenesis. Sprague Dawley female rats were gavaged daily with either 10 mg/kg manganese chloride (MnCl2) or saline (control) from postnatal day (PND) 12 through PND 30. Blood and MGs were collected on PNDs 30 and 120. Compared to controls, serum E2 levels on PND 30 were elevated (p

Arsenic (As) is a prevalent environmental toxin; readily accessible for human consumption and has been identified as an endocrine disruptor. However, it is not known what impact As has on female sexual maturation. Therefore, in the present study, we investigated the effects of prepubertal exposure on mammary gland development and pubertal onset in female rats. Results showed that prepubertal exposure to 10mg/kg of arsenite (As(III)) delayed vaginal opening (VO) and prepubertal mammary gland maturation. We determined that As accumulates in the liver, disrupts hepatocyte function and suppresses serum levels of the puberty related hormone insulin-like growth factor 1 (IGF-1) in prepubertal animals. Overall, this is the first study to show that prepubertal exposure to As(III) acts peripherally to suppresses circulating levels of IGF-1 resulting in delayed sexual maturation. Furthermore, this study identifies a critical window of increased susceptibility to As(III) that may have a lasting impact on female reproductive function.