Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants that Confer Risk for Breast Cancer.

Breast cancer includes several subtypes with distinct characteristic biological, pathological, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate development of improved prevention and treatment approaches. Here, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case GWAS (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared to luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to 2-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among breast cancer patients. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC.

Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction.

We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10-8), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.

Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes.

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3' UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

Emotional and functional well-being in long-term breast cancer survivorship.

PURPOSE: Emotional and functional well-being (EWB and FWB) are important components of mental health and quality of life. This study aims to evaluate long-term EWB and FWB in breast cancer (BC) survivors. METHODS: The Carolina Breast Cancer Study Phase 3 oversampled Black and younger (< 50 years in age) women so that they each represent approximately 50% of the study population and assessed participants' EWB and FWB with the Functional Assessment of Cancer Therapy-Breast (FACT-B) at 5- (baseline), 25-, and 84-months post diagnosis. Multinomial logit models were used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for associations between demographic and clinical characteristics and well-being change relative to baseline. RESULTS: Among 2,781 participants with BC, average EWB and FWB improved with time since diagnosis. Persistent FWB decrements were associated with Black race [OR 1.4 (95% CI 1.2-1.7) and 1.3 (95% CI 1.1-1.6), at 25-months and 84-months respectively], older age [OR 1.4 (95% CI 1.1-1.7) and 1.5 (95% CI 1.2-1.8), respectively], no chemotherapy, and recurrence [OR 2.9 (95% CI 1.8-4.8) and 3.1 (95% CI 2.1-4.6), respectively]. EWB decrements were associated with advanced stage and recurrence. Decrements in combined (FWB+EWB) well-being were associated with recurrence at both follow-up survey timepoints [ORs 4.7 (95% CI 2.7-8.0) and 4.3 (95% CI 2.8-6.6), respectively]. CONCLUSIONS: Long-term well-being varies by demographics and clinical features, with Black women and women with aggressive disease at greatest risk of long-term decrements.

Diffsig: Associating Risk Factors with Mutational Signatures.

BACKGROUND: 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. METHODS: Here, we develop a statistical model, Diffsig, for estimating the association of one or more continuous or categorical risk factors with DNA mutational signatures. Diffsig takes into account the uncertainty associated with assigning signatures to samples as well as multiple risk factors' simultaneous effect on observed DNA mutations. RESULTS: We applied Diffsig to breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development. In simulation, our model was capable of accurately estimating expected associations in a variety of contexts. CONCLUSIONS: Diffsig allows researchers to quantify and perform inference on the associations of risk factors with mutational signatures. IMPACT: We expect Diffsig to provide more robust associations of risk factors with signatures to lead to better understanding of the tumor development process and improved models of tumorigenesis.

BIRC5 expression by race, age and clinical factors in breast cancer patients.

PURPOSE: Survivin/BIRC5 is a proliferation marker that is associated with poor prognosis in breast cancer and an attractive therapeutic target. However, BIRC5 has not been well studied among racially diverse populations where aggressive breast cancers are prevalent. EXPERIMENTAL DESIGN: We studied BIRC5 expression in association with clinical and demographic variables and as a predictor of recurrence in 2174 participants in the Carolina Breast Cancer Study (CBCS), a population-based study that oversampled Black (n = 1113) and younger (< 50 years; n = 1137) participants with breast cancer. For comparison, similar analyses were conducted in The Cancer Genome Atlas [TCGA N = 1094, Black (n = 183), younger (n = 295)]. BIRC5 was evaluated as a continuous and categorical variable (highest quartile vs. lower three quartiles). RESULTS: Univariate, continuous BIRC5 expression was higher in breast tumors from Black women relative to non-Black women in both estrogen receptor (ER)-positive and ER-negative tumors and in analyses stratified by stage (i.e., within Stage I, Stage II, and Stage III/IV tumors). Within CBCS and TCGA, BIRC5-high was associated with young age (< 50 years) and Black race, as well as hormone receptor-negative tumors, non-Luminal A PAM50 subtypes, advanced stage, and larger tumors (> 2 cm). Relative to BIRC5-low, BIRC5-high tumors were associated with poor 5-year recurrence-free survival (RFS) among ER-positive tumors, both in unadjusted models [HR (95% CI): 2.7 (1.6, 4.6)] and after adjustment for age and stage [Adjusted HR (95% CI): 1.87 (1.07, 3.25)]. However, this relationship was not observed among ER-negative tumors [Crude HR (95% CI): 0.7 (0.39, 1.2); Adjusted HR (95% CI): 0.67 (0.37, 1.2)]. CONCLUSION: Black and younger women with breast cancer have a higher burden of BIRC5-high tumors than older and non-Black women. Emerging anti-survivin treatment strategies may be an important future direction for equitable breast cancer outcomes.

Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia.

BACKGROUND: Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS: We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS: In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION: The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.

Disparities in OncotypeDx Testing and Subsequent Chemotherapy Receipt by Geography and Socioeconomic Status.

BACKGROUND: OncotypeDx is a prognostic and predictive genomic assay used in early-stage hormone receptor-positive, HER2- (HR+/HER2-) breast cancer. It is used to inform adjuvant chemotherapy decisions, but not all eligible women receive testing. We aimed to assess variation in testing by demographics and geography, and to determine whether testing was associated with chemotherapy. METHODS: For 1,615 women in the Carolina Breast Cancer Study with HR+/HER2-, Stage I-II tumors, we estimated prevalence differences (PD) and 95% confidence intervals (CI) for receipt of OncotypeDx genomic testing in association with and sociodemographic characteristics. We assessed associations between testing and chemotherapy receipt overall and by race. Finally, we calculated the proportion of eligible women receiving OncotypeDx by county-level rurality, census tract-level socioeconomic status, and Area Health Education Center regions. RESULTS: 38% (N = 609) of potentially eligible women were tested, with lower testing prevalences in Black (31%; PD, -11%; 95% CI, -16%-6%) and low-income women (24%; PD, -20%; 95% CI, -29% to -11%) relative to non-Black and higher income women. Urban participants were less likely to be tested than rural participants, though this association varied by region. Among women with low genomic risk tumors, tested participants were 29% less likely to receive chemotherapy than untested participants (95% CI, -40% to -17%). Racial differences in chemotherapy were restricted to untested women. CONCLUSIONS: Both individual and area-level socioeconomics predict likelihood of OncotypeDx testing. IMPACT: Variable adoption of OncotypeDx by socioeconomics and across geographic settings may contribute to excess chemotherapy among patients with HR+/HER2- cancers. See related In the Spotlight, p. 635.

Understanding mechanisms of racial disparities in breast cancer: an assessment of screening and regular care in the Carolina Breast Cancer Study.

PURPOSE: Screening history influences stage at detection, but regular preventive care may also influence breast tumor diagnostic characteristics. Few studies have evaluated healthcare utilization (both screening and primary care) in racially diverse screening-eligible populations. METHODS: This analysis included 2,058 women age 45-74 (49% Black) from the Carolina Breast Cancer Study, a population-based cohort of women diagnosed with invasive breast cancer between 2008 and 2013. Screening history (threshold 0.5 mammograms per year) and pre-diagnostic healthcare utilization (i.e. regular care, based on responses to "During the past ten years, who did you usually see when you were sick or needed advice about your health?") were assessed as binary exposures. The relationship between healthcare utilization and tumor characteristics were evaluated overall and race-stratified. RESULTS: Among those lacking screening, Black participants had larger tumors (5 + cm) (frequency 19.6% vs 11.5%, relative frequency difference (RFD) = 8.1%, 95% CI 2.8-13.5), but race differences were attenuated among screening-adherent participants (10.2% vs 7.0%, RFD = 3.2%, 0.2-6.2). Similar trends were observed for tumor stage and mode of detection (mammogram vs lump). Among all participants, those lacking both screening and regular care had larger tumors (21% vs 8%, RR = 2.51, 1.76-3.56) and advanced (3B +) stage (19% vs 6%, RR = 3.15, 2.15-4.63) compared to the referent category (screening-adherent and regular care). Under-use of regular care and screening was more prevalent in socioeconomically disadvantaged areas of North Carolina. CONCLUSIONS: Access to regular care is an important safeguard for earlier detection. Our data suggest that health equity interventions should prioritize both primary care and screening.

Patterns of chemotherapy receipt among patients with hormone receptor-positive, HER2-negative breast cancer.

BACKGROUND: Breast cancer chemotherapy utilization not only may differ by race and age, but also varies by genomic risk, tumor characteristics, and patient characteristics. Studies in demographically diverse populations with both clinical and genomic data are necessary to understand potential disparities by race and age. METHODS: In the Carolina Breast Cancer Study Phase 3 (2008-2013), chemotherapy receipt (yes/no) and regimen type were assessed in association with age and race among hormone receptor (HR) positive and HER2-negative tumors (n = 1862). Odds ratios were estimated for the association between demographic factors and chemotherapy receipt. RESULTS: Monotonic decreases in frequency of adjuvant chemotherapy receipt were observed over time during the study period, while neoadjuvant chemotherapy was stable. Younger age was associated with chemotherapy receipt (OR [95% CI]: 2.9 [2.4, 3.6]) and with anthracycline-based regimens (OR [95% CI]: 1.7 [1.3, 2.4]). Participants who had Medicaid (OR [95% CI]: 1.8 [1.3, 2.5]), lived in rural settings (OR [95% CI]: 1.4 [1.0, 2.0]), or were Black (OR [95% CI]: 1.5 [1.2, 1.8]) had slightly higher odds of chemotherapy, but these associations were non-significant with adjustment for stage and grade. Associations between younger age and chemotherapy receipt were strongest among women who did not receive genomic testing. CONCLUSIONS: While race was not strongly associated with chemotherapy receipt, younger age remains a strong predictor of chemotherapy receipt, even with adjustment for clinical factors and among women who receive genomic testing.

From Race to Racism and Disparities to Equity: An Actionable Biopsychosocial Approach to Breast Cancer Outcomes.

PURPOSE: Racial disparities in outcomes of breast cancer in the United States have widened over more than 3 decades, driven by complex biologic and social factors. In this review, we summarize the biological and social narratives that have shaped breast cancer disparities research across different scientific disciplines in the past, explore the underappreciated but crucial ways in which these 2 strands of the breast cancer story are interwoven, and present 5 key strategies for creating transformative interdisciplinary research to achieve equity in breast cancer treatment and outcomes. DESIGN: We first review the key differences in tumor biology in the United States between patients racialized as Black versus White, including the overrepresentation of triple-negative breast cancer and differences in tumor histologic and molecular features by race for hormone-sensitive disease. We then summarize key social factors at the interpersonal, institutional, and social structural levels that drive inequitable treatment. Next, we explore how biologic and social determinants are interwoven and interactive, including historical and contemporary structural factors that shape the overrepresentation of triple-negative breast cancer among Black Americans, racial differences in tumor microenvironment, and the complex interplay of biologic and social drivers of difference in outcomes of hormone receptor positive disease, including utilization and effectiveness of endocrine therapies and the role of obesity. Finally, we present 5 principles to increase the impact and productivity of breast cancer equity research. RESULTS: We find that social and biologic drivers of breast cancer disparities are often cyclical and are found at all levels of scientific investigation from cells to society. To break the cycle and effect change, we must acknowledge and measure the role of structural racism in breast cancer outcomes; frame biologic, psychosocial, and access factors as interwoven via mechanisms of cumulative stress, inflammation, and immune modulation; take responsibility for the impact of representativeness (or the lack thereof) in genomic and decision modeling on the ability to accurately predict the outcomes of Black patients; create research that incorporates the perspectives of people of color from inception to implementation; and rigorously evaluate innovations in equitable cancer care delivery and health policies. CONCLUSIONS: Innovative, cross-disciplinary research across the biologic and social sciences is crucial to understanding and eliminating disparities in breast cancer outcomes.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study.

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2-4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008-2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

The TRIM69-MST2 signaling axis regulates centrosome dynamics and chromosome segregation.

Stringent control of centrosome duplication and separation is important for preventing chromosome instability. Structural and numerical alterations in centrosomes are hallmarks of neoplastic cells and contribute to tumorigenesis. We show that a Centrosome Amplification 20 (CA20) gene signature is associated with high expression of the Tripartite Motif (TRIM) family member E3 ubiquitin ligase, TRIM69. TRIM69-ablation in cancer cells leads to centrosome scattering and chromosome segregation defects. We identify Serine/threonine-protein kinase 3 (MST2) as a new direct binding partner of TRIM69. TRIM69 redistributes MST2 to the perinuclear cytoskeleton, promotes its association with Polo-like kinase 1 (PLK1) and stimulates MST2 phosphorylation at S15 (a known PLK1 phosphorylation site that is critical for centrosome disjunction). TRIM69 also promotes microtubule bundling and centrosome segregation that requires PRC1 and DYNEIN. Taken together, we identify TRIM69 as a new proximal regulator of distinct signaling pathways that regulate centrosome dynamics and promote bipolar mitosis.

Molecular features of androgen-receptor low, estrogen receptor-negative breast cancers in the Carolina breast cancer study.

PURPOSE: Androgen receptor (AR) expression is absent in 40-90% of estrogen receptor (ER)-negative breast cancers. The prognostic value of AR in ER-negative patients and therapeutic targets for patients absent in AR remains poorly explored. METHODS: We used an RNA-based multigene classifier to identify AR-low and AR-high ER-negative participants in the Carolina Breast Cancer Study (CBCS; N = 669) and The Cancer Genome Atlas (TCGA; N = 237). We compared AR-defined subgroups by demographics, tumor characteristics, and established molecular signatures [PAM50 risk of recurrence (ROR), homologous recombination deficiency (HRD), and immune response]. RESULTS: AR-low tumors were more prevalent among younger (RFD = + 10%, 95% CI = 4% to 16%) participants in CBCS and were associated with HER2 negativity (RFD = - 35%, 95% CI = - 44% to - 26%), higher grade (RFD = + 17%, 95% CI = 8% to 26%), and higher risk of recurrence scores (RFD = + 22%, 95% CI = 16.1% to 28%), with similar results in TCGA. The AR-low subgroup was strongly associated with HRD in CBCS (RFD = + 33.3%, 95% CI = 23.8% to 43.2%) and TCGA (RFD = + 41.5%, 95% CI = 34.0% to 48.6%). In CBCS, AR-low tumors had high adaptive immune marker expression. CONCLUSION: Multigene, RNA-based low AR expression is associated with aggressive disease characteristics as well as DNA repair defects and immune phenotypes, suggesting plausible precision therapies for AR-low, ER-negative patients.

Influence of alcohol consumption and alcohol metabolism variants on breast cancer risk among Black women: results from the AMBER consortium.

BACKGROUND: Moderate to heavy alcohol consumption is associated with an increased risk of breast cancer. The etiologic role of genetic variation in genes involved in ethanol metabolism has not been established, with little information available among women of African ancestry. METHODS: Our analysis from the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium included 2889 U.S. Black women who were current drinkers at the time of breast cancer diagnosis (N cases = 715) and had available genetic data for four ethanol metabolism genomic regions (ADH, ALDH, CYP2E1, and ALDH2). We used generalized estimating equations to calculate genetic effects, gene* alcohol consumption (≥ 7drinks/week vs. < 7/week) interactions, and joint main plus interaction effects of up to 23,247 variants in ethanol metabolism genomic regions on odds of breast cancer. RESULTS: Among current drinkers, 21% of cases and 14% of controls reported consuming ≥ 7 drinks per week. We identified statistically significant genetic effects for rs79865122-C in CYP2E1 with odds of ER- breast cancer and odds of triple negative breast cancer, as well as a significant joint effect with odds of ER- breast cancer (≥ 7drinks per week OR = 3.92, < 7 drinks per week OR = 0.24, pjoint = 3.74 × 10-6). In addition, there was a statistically significant interaction of rs3858704-A in ALDH2 with consumption of ≥ 7 drinks/week on odds of triple negative breast cancer (≥ 7drinks per week OR = 4.41, < 7 drinks per week OR = 0.57, pint = 8.97 × 10-5). CONCLUSIONS: There is a paucity of information on the impact of genetic variation in alcohol metabolism genes on odds of breast cancer among Black women. Our analysis of variants in four genomic regions harboring ethanol metabolism genes in a large consortium of U.S. Black women identified significant associations between rs79865122-C in CYP2E1 and odds of ER- and triple negative breast cancer. Replication of these findings is warranted.

A complex systems model of breast cancer etiology: The Paradigm II Model.

BACKGROUND: Complex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers. METHODS AND FINDINGS: We developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures. CONCLUSIONS: The Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.

Identifying patient profiles of disparate care in resectable pancreas cancer using latent class analysis.

BACKGROUND AND OBJECTIVES: Disparities in pancreas cancer care are multifactorial, but factors are often examined in isolation. Research that integrates these factors in a single conceptual framework is lacking. We use latent class analysis (LCA) to evaluate the association between intersectionality and patterns of care and survival in patients with resectable pancreas cancer. METHODS: LCA was used to identify demographic profiles in resectable pancreas cancer (n = 140 344) diagnosed from 2004 to 2019 in the National Cancer Database (NCDB). LCA-derived patient profiles were used to identify differences in receipt of minimum expected treatment (definitive surgery), optimal treatment (definitive surgery and chemotherapy), time to treatment, and overall survival. RESULTS: Minimum expected treatment (hazard ratio [HR] 0.69, 95% confidence interval [CI]: 0.65, 0.75) and optimal treatment (HR 0.58, 95% CI: 0.55, 0.62) were associated with improved overall survival. Seven latent classes were identified based on age, race/ethnicity, and socioeconomic status (SES) attributes (zip code-linked education and income, insurance, geography). Compared to the referent group (≥65 years + White + med/high SES), the ≥65 years + Black profile had the longest time-to-treatment (24 days vs. 28 days) and lowest odds of receiving minimum (odds ratio [OR] 0.67, 95% CI: 0.64, 0.71) or optimal treatment (OR 0.76, 95% CI: 0.72, 0.81). The Hispanic patient profile had the lowest median overall survival-55.3 months versus 67.5 months. CONCLUSIONS: Accounting for intersectionality in the NCDB resectable pancreatic cancer patient cohort identifies subgroups at higher risk for inequities in care. LCA demonstrates that older Black patients and Hispanic patients are at particular risk for being underserved and should be prioritiz for directed interventions.

Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population.

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.

Molecular Features of Androgen-Receptor Low, Estrogen Receptor-Negative Breast Cancers in the Carolina Breast Cancer Study.

PURPOSE: Androgen receptor (AR) expression is absent in 40-90% of estrogen receptor (ER)-negative breast cancers. The prognostic value of AR in ER-negative patients and therapeutic targets for patients absent in AR remains poorly explored. METHODS: We used an RNA-based multigene classifier to identify AR-low and AR-high ER-negative participants in the Carolina Breast Cancer Study (CBCS; n=669) and The Cancer Genome Atlas (TCGA; n=237). We compared AR-defined subgroups by demographics, tumor characteristics, and established molecular signatures [PAM50 risk of recurrence (ROR), homologous recombination deficiency (HRD), and immune response]. RESULTS: AR-low tumors were more prevalent among Black (relative frequency difference (RFD) = +7%, 95% CI = 1% to 14%) and younger (RFD = +10%, 95% CI = 4% to 16%) participants in CBCS and were associated with HER2-negativity (RFD = -35%, 95% CI = -44% to -26%), higher grade (RFD = +17%, 95% CI = 8% to 26%), and higher risk of recurrence scores (RFD = +22%, 95% CI = 16.1% to 28%), with similar results in TCGA. The AR-low subgroup was strongly associated with HRD in CBCS (RFD = +33.3%, 95% CI = 23.8% to 43.2%) and TCGA (RFD = +41.5%, 95% CI = 34.0% to 48.6%). In CBCS, AR-low tumors had high adaptive immune marker expression. CONCLUSION: Multigene, RNA-based low AR expression is associated with aggressive disease characteristics as well as DNA repair defects and immune phenotypes, suggesting plausible precision therapies for AR-low, ER-negative patients.

Discrimination between Precancerous Gastric Lesions and Gastritis Using a Gastric Cancer Risk Stratification Model.

BACKGROUND: Seropositivity to certain Helicobacter pylori proteins may affect development of gastric lesions that could become cancerous. Previously, we developed a model of gastric cancer risk including gender, age, HP0305 sero-positivity, HP1564 sero-positivity, UreA antibody titer and serologically defined chronic atrophic gastritis (termed: "Lasso model"). METHODS: We evaluated the Lasso model's ability to discriminate individuals with precancerous gastric lesions (n=320) from individuals with superficial or mild atrophic gastritis (n=226) in Linqu County, China, a population at high risk for gastric cancer. We also compared its performance to the ABC Method, a gastric cancer risk stratification tool currently used in East Asia. RESULTS: For distinguishing precancerous lesions from those with gastritis, the receiver operating characteristic curve had an area under the curve (AUC) of 73.41% (95% CI: 69.10%, 77.71%) and, at Youden's Index, a sensitivity of 78.44% (59.38%, 82.50%) and specificity of 64.72% (95% CI: 58.85%, 81.42%). Positive predictive value (PPV) was 75.38% (72.78%, 82.51%). Specificity, AUC and PPV were significantly greater (p < 0.05) than those of the ABC Method. When specificity was held constant, the Lasso model had greater sensitivity, PPV and negative predictive value (NPV) than the ABC Method. However, adjusting the ABC Method for age and gender negated the Lasso model's significant improvement in AUC. CONCLUSIONS: The Lasso model for gastric cancer risk prediction can classify precancerous lesions with significantly greater AUC than the ABC Method and, at constant specificity, with greater sensitivity, PPV and NPV. However, adding age and gender to the ABC Method, as included in the Lasso model, substantially improved its performance and negated the Lasso model's advantage.