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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: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.

Supplementary Table S3

Supplementary Figures S1 - S11

The APOBEC family of cytidine deaminases is one of the most common endogenous sources of mutations in human cancer. Genomic studies of tumors have found that APOBEC mutational signatures are enriched in the HER2 subtype of breast cancer and are associated with immunotherapy response in diverse cancer types. However, the direct consequences of APOBEC mutagenesis on the tumor immune microenvironment have not been thoroughly investigated. To address this, we developed syngeneic murine mammary tumor models with inducible expression of APOBEC3B. We found that APOBEC activity induced antitumor adaptive immune responses and CD4+ T cell–mediated, antigen-specific tumor growth inhibition. Although polyclonal APOBEC tumors had a moderate growth defect, clonal APOBEC tumors were almost completely rejected, suggesting that APOBEC-mediated genetic heterogeneity limits antitumor adaptive immune responses. Consistent with the observed immune infiltration in APOBEC tumors, APOBEC activity sensitized HER2-driven breast tumors to anti–CTLA-4 checkpoint inhibition and led to a complete response to combination anti–CTLA-4 and anti-HER2 therapy. In human breast cancers, the relationship between APOBEC mutagenesis and immunogenicity varied by breast cancer subtype and the frequency of subclonal mutations. This work provides a mechanistic basis for the sensitivity of APOBEC tumors to checkpoint inhibitors and suggests a rationale for using APOBEC mutational signatures and clonality as biomarkers predicting immunotherapy response in HER2-positive (HER2+) breast cancers.

Legends for Figures S1-S11 and Supplementary Tables S1-S3

The APOBEC family of cytidine deaminases is one of the most common endogenous sources of mutations in human cancer. Genomic studies of tumors have found that APOBEC mutational signatures are enriched in the HER2 subtype of breast cancer and are associated with immunotherapy response in diverse cancer types. However, the direct consequences of APOBEC mutagenesis on the tumor immune microenvironment have not been thoroughly investigated. To address this, we developed syngeneic murine mammary tumor models with inducible expression of APOBEC3B. We found that APOBEC activity induced antitumor adaptive immune responses and CD4+ T cell–mediated, antigen-specific tumor growth inhibition. Although polyclonal APOBEC tumors had a moderate growth defect, clonal APOBEC tumors were almost completely rejected, suggesting that APOBEC-mediated genetic heterogeneity limits antitumor adaptive immune responses. Consistent with the observed immune infiltration in APOBEC tumors, APOBEC activity sensitized HER2-driven breast tumors to anti–CTLA-4 checkpoint inhibition and led to a complete response to combination anti–CTLA-4 and anti-HER2 therapy. In human breast cancers, the relationship between APOBEC mutagenesis and immunogenicity varied by breast cancer subtype and the frequency of subclonal mutations. This work provides a mechanistic basis for the sensitivity of APOBEC tumors to checkpoint inhibitors and suggests a rationale for using APOBEC mutational signatures and clonality as biomarkers predicting immunotherapy response in HER2-positive (HER2+) breast cancers.

Somatic mutational signatures elucidate molecular vulnerabilities to therapy and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors. Here we presentDiffsig, a model and R package for estimating the association of risk factors with mutational signatures, suggesting etiologies for the pre-defined mutational signatures.Diffsigis a Bayesian Dirichlet-multinomial hierarchical model that allows testing of any type of risk factor while taking into account the uncertainty associated with samples with a low number of observations. In simulation, we found that our method can accurately estimate risk factor-mutational signal associations. We appliedDiffsigto breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development.Diffsigis implemented as an R package available at:https://github.com/jennprk/diffsig.

DNA repair pathways have been associated with variability in hepatocellular carcinoma (HCC) clinical outcomes, but the mechanism through which DNA repair varies as a function of liver regeneration and other HCC characteristics is poorly understood. We curated a panel of 199 genes representing 15 DNA repair pathways to identify DNA repair expression classes and evaluate their associations with liver features and clinicopathologic variables in The Cancer Genome Atlas (TCGA) HCC study. We identified two groups in HCC, defined by low or high expression across all DNA repair pathways. The low-repair group had lower grade and retained the expression of classical liver markers, whereas the high-repair group had more clinically aggressive features, increased p53 mutant-like gene expression, and high liver regenerative gene expression. These pronounced features overshadowed the variation in the low-repair subset, but when considered separately, the low-repair samples included three subgroups: L1, L2, and L3. L3 had high DNA repair expression with worse progression-free (HR 1.24, 95% CI 0.81–1.91) and overall (HR 1.63, 95% CI 0.98–2.71) survival. High-repair outcomes were also significantly worse compared with the L1 and L2 groups. HCCs vary in DNA repair expression, and a subset of tumors with high regeneration profoundly disrupts liver biology and poor prognosis.

Blood group antigens are inherited traits that may play a role in immune and inflammatory processes. We investigated associations between blood groups and circulating inflammation-related molecules in 3537 non-Hispanic white participants selected from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Whole-genome scans were used to infer blood types for 12 common antigen systems based on well-characterized single-nucleotide polymorphisms. Serum levels of 96 biomarkers were measured on multiplex fluorescent bead-based panels. We estimated marker associations with blood type using weighted linear or logistic regression models adjusted for age, sex, smoking status, and principal components of population substructure. Bonferroni correction was used to control for multiple comparisons, with two-sided p values

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.

Background: Metabolic syndrome (MetS) is a systemic inflammatory state. Low physical activity (PA) could modify this patho-physiology or act as an independent contributor to inflammation. Previous studies of both conditions have identified altered levels of inflammation- and immune-related proteins based on limited sets of candidate markers. Methods: We investigated associations of MetS and low PA with circulating inflammation markers in a stratified random sample of Japanese adults (N = 774, mean age 60.7 years) within the Japan Public Health Center-based Prospective Study (JPHC) Cohort II. AHA/NHLBI criteria were used to define MetS (19%) and the bottom quartile of PA was considered low. 110 circulating biomarkers, including cytokines, chemokines, and soluble receptors were measured by multiplex bead-based and proximity-extension assays. Associations of MetS and low PA with marker quantiles were adjusted for each other and for age, sex, study site, cigarette smoking, alcohol consumption, and blood sample fasting state by ordinal logistic regression. P values were corrected for FDR. Results: MetS was significantly associated with levels of six markers: IL18R1 [odds ratio 2.37; 95% confidence interval (CI), 1.45–3.87], CRP (2.07; 95% CI, 1.48–2.90), SAP (2.08; 95% CI, 1.47–2.95), CCL19/MIP3β (2.06; 95% CI, 1.48–2.88), CXCL12/SDF1α+β (0.48; 95% CI, 0.32–0.65), and CCL28 (0.44; 95% CI, 0.27–0.71). Low PA had no significant marker associations. Conclusions: Positively associated markers with MetS are mostly Th1 immune response–related and acute phase proteins, whereas negatively associated markers are generally Th2-related. Impact: MetS is associated with a broad range of alterations in immune and inflammatory biomarkers that may contribute to risks of various chronic diseases, independent of low PA.

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.

The APOBEC family of cytidine deaminases is one of the most common endogenous sources of mutations in human cancer. Genomic studies of tumors have found that APOBEC mutational signatures are particularly enriched in the HER2 subtype of breast cancer and have been associated with immunotherapy response in diverse cancer types. However, the direct consequences of APOBEC mutagenesis on the tumor immune microenvironment have not been thoroughly investigated. To address this, we developed syngeneic murine mammary tumor models with inducible expression of APOBEC3B. We found that APOBEC activity induces an antitumor adaptive immune response and CD4+ T cell-mediated tumor growth inhibition. While polyclonal APOBEC tumors had a moderate growth defect, clonal APOBEC tumors were almost completely rejected by the immune system, suggesting that APOBEC-mediated genetic heterogeneity limits the antitumor adaptive immune response. Consistent with the observed immune infiltration in APOBEC tumors, APOBEC activity sensitized HER2-driven breast tumors to checkpoint inhibition. In human breast cancers, the relationship between APOBEC mutagenesis and immunogenicity varied by breast cancer subtype and the frequency of subclonal mutations. This work provides a mechanistic basis for the sensitivity of APOBEC tumors to checkpoint inhibitors and suggests a rationale for using APOBEC mutational signatures as a biomarker predicting immunotherapy response in HER2-positive breast cancers.SIGNIFICANCEAPOBEC mutational signatures are observed in many cancers, yet the consequences of these mutations on the tumor immune microenvironment are not well understood. Using a novel mouse model, we show that APOBEC activity sensitizes HER2-driven mammary tumors to checkpoint inhibition and could inform immunotherapy treatment strategies for HER2-positive breast cancer patients.

Introduction Prescription costs are rising, and many patients with chronic illnesses have difficulty paying for prescriptions. Missing or delaying medication because of financial concerns is common; however, the effects of cost-related nonadherence (CRN) on patient outcomes have not been described. Our objective was to determine if CRN is associated with higher all-cause and disease-specific mortality among patients living with diabetes and cardiovascular disease in a representative sample of US adults. Methods We ascertained CRN, vital status, and cause of death for 39,571 patients with diabetes, 61,968 patients with cardiovascular disease, and 124,899 patients with hypertension in the 2000 through 2014 releases of the National Health Interview Survey. We used adjusted Cox proportional hazards models to estimate associations between CRN and all-cause mortality and CRN and disease-specific mortality. Results On average, 15% of the sample reported CRN in the year before interview. After adjusting for confounders, CRN was associated with 15% to 22% higher all-cause mortality rates for all conditions (diabetes hazard ratio [HR] = 1.18; 95% CI, 1.1–1.3; cardiovascular disease [CVD] HR = 1.15; 95% CI, 1.1–1.2; hypertension HR = 1.22; 95% CI, 1.2–1.3). Relative to no CRN, CRN was associated with 8% to 18% higher disease-specific mortality rates (diabetes HR = 1.18; 95% CI, 1.0–1.4; CVD HR = 1.09; 95% CI, 1.0–1.2; hypertension HR = 1.08; 95% CI, 0.9–1.3). Conclusion Relative to full adherence, CRN is associated with higher mortality rates for patients with diabetes, cardiovascular disease, and hypertension, although associations may have weakened since 2011. Policies that increase prescription affordability may decrease mortality for patients experiencing CRN.

Objective Eating disorders (EDs) have high rates of psychiatric comorbidity. This study aimed to characterize longitudinal patterns of comorbidities in adults with EDs. Methods Sequence analysis and hierarchical clustering were applied to ages of onset and recency for select eating, substance, mood, and anxiety disorders from the 479 participants in the Collaborative Psychiatric Epidemiology Surveys with lifetime DSM-IV bulimia nervosa, binge eating disorder, or anorexia nervosa. External validators were compared across clusters using chi-square tests. Results Five clusters were identified among individuals with any lifetime ED based on longitudinal sequence of psychiatric disorder onset and remission, characterized as: (1) multi-comorbid with early onset of comorbid disorder (46%); (2) moderate preeminent anxiety with moderate comorbidity and low ED persistence (20%); (3) late ED onset with low comorbidity (15%); (4) early onset, persistent ED with low comorbidity (14%); and (5) chronic, early onset depression (5%). Clusters were well differentiated by significant differences in age, body mass index, race, and psychiatric indicators. Conclusions This study demonstrates a new method to assess clustering of comorbidity among individuals with lifetime EDs. Having a psychiatric diagnosis prior to an ED was associated with greater psychopathology and illness duration. Information on timing of diagnoses may allow for more refined comorbidity classification.

Background: Blood group antigens may play a role in immune and inflammatory processes. The aim of this analysis was to identify specific inflammatory pathways associated with blood group antigens. Methods: We investigated associations between blood type and circulating inflammatory markers in data for 3,537 non-Hispanic white participants selected from previous case-control studies nested in the Prostate, Lung, Colorectal, and Ovarian cancer screening trial. Whole genome scans were used to infer blood types for twelve common antigen systems (ABO, Duffy, Lewis, RhE, Kidd, Kell, Secretor, Lutheran, Colton, Dombrock, Auberger, and Knops) based on well-characterized single nucleotide polymorphisms. Circulating levels of 96 immune- and inflammation-related biomarkers were measured on multiplex fluorescent bead-based panels. We estimated associations between blood type and markers using design-weighted linear or logistic regression adjusted for age, sex, smoking status, and principal components of population substructure, and using a Bonferroni correction to control for multiple comparisons. Results: Among the 1,152 blood type-biomarker associations tested, we identified 10 which were significant after correction for multiple comparisons. ABO subtype was associated with levels of sVEGFR2, sVEGFR3, and sGP130, and Duffy subtype was associated with levels of CXCL6/GCP2, CXCL5/ENA78, CCL11/EOTAXIN, CXCL1/GRO, CCL2/MCP1, CCL13/MCP4, and CCL17/TARC. Post-hoc pairwise t-tests showed that individuals with type A blood had lower levels of all ABO-associated markers than individuals with type O or B blood, while individuals with type Fy(a+b-) had lower levels of all Duffy-associated markers than individuals with type Fy(a+b+) or Fy(a-b+). Conclusion: ABO blood type is associated with levels of three circulating angiogenic markers, while Duffy blood type is associated with eight chemokines. Additional work to understand the clinical implications of these differences is needed. Citation Format: Sarah C. Van Alsten, John Aversa, Loredana Santo, M. Constanza Camargo, Wen-Yi Huang, Troy Kemp, Jia Liu, Joshua Samspon, Charles S. Rabkin. Association between ABO and Duffy blood types and circulating chemokines and cytokines [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 834.

594 Background: Black women with breast cancer have higher mortality than White women. Differences in tumor biology contribute to racial disparities in breast cancer outcomes. BIRC5 gene encodes survivin, an inhibitor of apoptosis protein, and an independent marker of poor prognosis in breast cancer. Cancer patients have anti-survivin antibodies and circulating survivin-specific T cells, suggesting that survivin may be targetable. Several ongoing antibody-mediated, vaccine strategies that target survivin are being developed. Nevertheless, most survivin studies were conducted in cohorts of White women. To date, the prevalence and/or role of survivin expression in breast tumors from Black women has not been studied. Methods: Associations between BIRC5 expression, clinicopathological and molecular features were measured in the population-based Carolina Breast Cancer Study (CBCS) and The Cancer Genome Atlas (TCGA) breast cancer cohort. Gene expression was measured by Nanostring RNA counting and split into BIRC5 high (4th quartile) and low categories based on log2 gene expression values. Relative frequency differences (RFD) for the association between BIRC5 high and clinicopathologic features were estimated. RNA based p53 mutant status and homologous recombination deficiency (HRD) status were included in RFD analysis. Receiver operating characteristic (ROC) curves were used to illustrate the potential of BIRC5 expression to distinguish patients who achieved pathological complete response (pCR) after receiving neoadjuvant chemotherapy in CBCS (133 Black, 49 non-Black). Results: BIRC5 gene expression was significantly increased in tumors from 966 Black patients compared to 1,497 non-Black (p < 0.00001), adjusting for stage and subtype. BIRC5 high tumors were significantly more expressed in higher stage and basal-like breast cancer subtypes. BIRC5 high tumors were also significantly enriched for expression of genes involved in p53 loss and HRD. Furthermore, in an analysis of 182 CBCS patients, BIRC5 gene expression alone predicted pCR with similar overall AUC to ROR-PT multigene signatures (AUC 0.62 vs 0.64). Conclusions: Our study shows that survivin expression is particularly high in breast tumors from Black women. This was associated with more aggressive clinicopathological features in addition to p53 mutant and HRD status. Black women with breast cancer represent an area of unmet clinical need and could potentially benefit from anti-survivin targetable treatment strategies. Further studies are needed to help close this gap which constitutes the largest disparity among cancer-specific diseases.[Table: see text]