Racial Differences in PAM50 Subtypes in the Carolina Breast Cancer Study

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.

Challenges to genetic testing for germline mutations associated with breast cancer among African Americans Authors

Inequities in preventive cancer screening, diagnosis, treatment, and inferior cancer outcomes continue to pose challenges across the cancer continuum. While the exact reasons for these inferior outcomes are unknown, multiple barriers to various domains of social determinants of health (SDOH) play a vital role, leading to inequities in cancer care. These include barriers to transportation, housing, and food insecurities, contributing to delays in preventive screening and treatment. Furthermore, aggressive biologies also exist across various racial profiles with accompanying germline mutations. For example, African Americans (AAs) have a higher incidence of triple-negative breast cancer subtype and a high prevalence of BRCA1/2 gene mutations, increasing the risk of multiple cancers, warranting high-risk screening for these populations. Unfortunately, other barriers, such as financial insecurities, low health literacy rates, and lack of awareness, lead to delays in cancer screening and genetic testing, even with available high-risk screening and risk reduction procedures. In addition, physicians receive minimal interdisciplinary training to address genetic assessment, interpretation of the results, and almost no additional training in addressing the unique needs of racial minorities, leading to suboptimal delivery of genetic assessment provision resources among AAs. In this review, we discuss the confluence of factors and barriers limiting genetic testing among AAs and highlight the prevalence of germline mutations associated with increased risk of breast cancer among AAs, reflecting the need for multi-panel germline testing as well as education regarding hereditary cancer risks in underserved minorities.

Simulating the population impact of interventions to reduce racial gaps in breast cancer treatment

BACKGROUND

Inequities in guideline-concordant treatment receipt contribute to worse survival in Black breast cancer (BCa) patients. Inequity-reduction interventions (eg, navigation, bias training, tracking dashboards) can close such treatment gaps. We simulated the population-level impact of statewide implementation of inequity-reduction interventions on racial BCa inequities in North Carolina.

METHODS

Using registry-linked multi-payer claims data, we calculated Black/White inequities in endocrine (ET; n = 12,033) and chemotherapy (CTx; n = 1,819) receipt. We then built cohort- (ET and CTx), and race-stratified Markov models to simulate the potential increase in the proportion of patients receiving ET or CTx and subsequent improvements in BCa outcomes if inequity-reducing intervention were implemented statewide. We report uncertainty bounds representing 95% of simulation results.

RESULTS

75.6% and 72.1% of Black patients received ET and CTx over the 2006-2015 and 2004-2015 periods (vs 79.3 and 78.9% of White patients, respectively). Inequity-reduction interventions could increase ET and CTx receipt among Black patients to 89.9% (85.3, 94.6%) and 85.7% (80.7, 90.9%). Such interventions could also decrease 5-and 10-year BCa mortality gaps from 3.4 to 3.2 (3.0, 3.3) and from 6.7 to 6.1 (5.9, 6.4) percentage points in the ET cohorts and from 8.6 to 8.1 (7.7, 8.4) and from 8.2 to 7.8 (7.3, 8.1) percentage points in the CTx cohorts.

CONCLUSIONS

Inequity-focused interventions could improve cancer outcomes for Black patients. However, they would not fully close the racial BCa mortality gap. Addressing other inequities along cancer continuum (eg, screening, pre-and post-diagnosis risk factors) is required to achieve full equity in BCa outcomes.

Strengths and opportunities to clinical trial enrollment among BIPOC, rural dwelling patients in the northwest United States: a retrospective study

Introduction: Clinical trials investigating the safety and efficacy of experimental drugs and devices are the cornerstone of medicinal advancement. Enrolling sufficient participants in these trials is vital to ensure adequate statistical power and generalizability. Clinical trial participation is particularly low among certain populations, including medically underserved communities (i.e., rural areas) and Black, Indigenous, and People of Color (BIPOC). Methods: A retrospective study design was used to understand patient outcomes and access/barriers to clinical trial participation in the rural northwest United States. A quantitatively focused retrospective chart review was conducted for adult participants enrolled in at least one clinical trial in a single northwest health system between 1999 and 2022. Descriptive and inferential statistical analyses were performed to assess trial outcomes at a significance level 0.05. Results: The retrospective chart review yielded 833 clinical trial records with 753 individual enrolled participants. The all-cause relative frequency of death at last known follow-up amongst clinical trial participants was 8.90% (n = 67). Based on logistic regression, the death was significantly associated with the participants' age at initial trial screening (β = 0.09, p-value <0.001), those that resided in non-metro areas (β = -0.86, p-value = 0.045), and those that lived in Northeastern Montana (β = 1.27, p-value = 0.025). Additionally, death at last known follow-up was significantly associated with enrollment in 2021-2022 (β = -1.52, p-value <0.001), enrolled in more than one study (β = 0.84, p-value = 0.023), in internationally sponsored trials (β = -2.08, p-value <0.001), in Phase I (β = 5.34, p-value <0.001), in Phase II trials (β = 1.37, p-value = 0.013), diabetes as a primary trial target (β = -2.04, p-value = 0.003). Conclusion: As decentralized trial design and remote or virtual elements of traditional trials become normative, representation of rural and frontier populations is imperative to support the generalizability of trial data encouraged by the FDA.

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.

Deregulated miRNA Expression in Triple-Negative Breast Cancer of Ancestral Genomic-Characterized Latina Patients

Among patients with triple-negative breast cancer (TNBC), several studies have suggested that deregulated microRNA (miRNA) expression may be associated with a more aggressive phenotype. Although tumor molecular signatures may be race- and/or ethnicity-specific, there is limited information on the molecular profiles in women with TNBC of Hispanic and Latin American ancestry. We simultaneously profiled TNBC biopsies for the genome-wide copy number and miRNA global expression from 28 Latina women and identified a panel of 28 miRNAs associated with copy number alterations (CNAs). Four selected miRNAs (miR-141-3p, miR-150-5p, miR-182-5p, and miR-661) were validated in a subset of tumor and adjacent non-tumor tissue samples, with miR-182-5p being the most discriminatory among tissue groups (AUC value > 0.8). MiR-141-3p up-regulation was associated with increased cancer recurrence; miR-661 down-regulation with larger tumor size; and down-regulation of miR-150-5p with larger tumor size, high p53 expression, increased cancer recurrence, presence of distant metastasis, and deceased status. This study reinforces the importance of integration analysis of CNAs and miRNAs in TNBC, allowing for the identification of interactions among molecular mechanisms. Additionally, this study emphasizes the significance of considering the patients ancestral background when examining TNBC, as it can influence the relationship between intrinsic tumor molecular characteristics and clinical manifestations of the disease.

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.

Outcomes in breast cancer-does ethnicity matter?

Ethnic or racial differences in breast cancer (BC) survival outcomes have been reported, but current data are largely restricted to comparisons between African Americans and non-Hispanic whites. Most analyses have traditionally been based on self-reported race which may not always be accurate, or are oversimplified in their classification. With increasing globalization, quantification of the genetic ancestry from genomic data may offer a solution to infer the complex makeup from admixture of races. Focusing on the larger and the latest studies, we will discuss recent findings on the differing host and tumor biology that may be driving these disparities, in addition to the extrinsic environmental or lifestyle factors. Socioeconomic disparities with lower cancer literacy may lead to late presentation, poorer adherence to treatment, and other lifestyle factors such as unhealthy diet, obesity, and inadequate physical activity. These hardships may also result in greater allostatic load, which is in turn associated with aggressive BC features in disadvantaged populations. Epigenetic reprogramming may mediate the effects of the environment or lifestyle factors on gene expression, with ensuing differences in BC characteristics and outcome. There is increasing evidence that germline genetics can influence somatic gene alterations or expression, as well as modulate the tumor or immune microenvironment. Although the precise mechanisms remain elusive, this may account for the varying distribution of different BC subtypes across ethnicities. These gaps in our knowledge highlight the need to interrogate the multiomics landscape of BC in diverse populations, ideally in large-scale collaborative settings with standardized methodology for the comparisons to be statistically robust. Together with improving BC awareness and access to good quality health care, a holistic approach with insights of the biological underpinnings is much needed to eradicate ethnic disparities in BC outcomes.

Identification, characterization, and prognosis investigation of pivotal genes shared in different stages of breast cancer

One of the leading causes of death (20.1 per 100,000 women per year), breast cancer is the most prevalent cancer in females. Statistically, 95% of breast cancer are categorized as adenocarcinomas, and 55% of all patients may go into invasive phases; however, it can be successfully treated in approximately 70-80% of cases if diagnosed in the nascent stages. The emergence of breast tumor cells which are intensely resistant to conventional therapies, along with the high rate of metastasis occurrence, has highlighted the importance of finding novel strategies and treatments. One of the most advantageous schemes to alleviate this complication is to identify the common differentially expressed genes (DEGs) among primary and metastatic cancerous cells to use resultants for designing new therapeutic agents which are able to target both primary and metastatic breast tumor cells. In this study, the gene expression dataset with accession number GSE55715 was analyzed containing two primary tumor samples, three bone-metastatic samples, and three normal samples to distinguish the up- and down regulated genes in each stage compared to normal cells as control. In the next step, the common upregulated genes between the two experimental groups were detected by Venny online tool. Moreover, gene ontology, functions and pathways, gene-targeting microRNA, and influential metabolites were determined using EnrichR 2021 GO, KEGG pathways miRTarbase 2017, and HMDB 2021, respectively. Furthermore, elicited from STRING protein-protein interaction networks were imported to Cytoscape software to identify the hub genes. Then, identified hub genes were checked to validate the study using oncological databases. The results of the present article disclosed 1263 critical common DEGs (573 upregulated + 690 downregulated), including 35 hub genes that can be broadly used as new targets for cancer treatment and as biomarkers for cancer detection by evaluation of expression level. Besides, this study opens a new horizon to reveal unknown aspects of cancer signaling pathways by providing raw data evoked from in silico experiments. This study's outcomes can also be widely utilized in further lab research since it contains diverse information on common DEGs of varied stages and metastases of breast cancer, their functions, structures, interactions, and associations.

Ten-year distant-recurrence risk prediction in breast cancer by CanAssist Breast (CAB) in Dutch sub-cohort of the randomized TEAM trial

BACKGROUND

Hormone receptor (HR)-positive, HER2/neu-negative breast cancers have a sustained risk of recurrence up to 20 years from diagnosis. TEAM (Tamoxifen, Exemestane Adjuvant Multinational) is a large, multi-country, phase III trial that randomized 9776 women for the use of hormonal therapy. Of these 2754 were Dutch patients. The current study aims for the first time to correlate the ten-year clinical outcomes with predictions by CanAssist Breast (CAB)-a prognostic test developed in South East Asia, on a Dutch sub-cohort that participated in the TEAM. The total Dutch TEAM cohort and the current Dutch sub-cohort were almost similar with respect to patient age and tumor anatomical features.

METHODS

Of the 2754 patients from the Netherlands, which are part of the original TEAM trial, 592 patients' samples were available with Leiden University Medical Center (LUMC). The risk stratification of CAB was correlated with outcomes of patients using logistic regression approaches entailing Kaplan-Meier survival curves, univariate and multivariate cox-regression hazards model. We used hazard ratios (HRs), the cumulative incidence of distant metastasis/death due to breast cancer (DM), and distant recurrence-free interval (DRFi) for assessment.

RESULTS

Out of 433 patients finally included, the majority, 68.4% had lymph node-positive disease, while only a minority received chemotherapy (20.8%) in addition to endocrine therapy. CAB stratified 67.5% of the total cohort as low-risk [DM = 11.5% (95% CI, 7.6-15.2)] and 32.5% as high-risk [DM = 30.2% (95% CI, 21.9-37.6)] with an HR of 2.90 (95% CI, 1.75-4.80; P < 0.001) at ten years. CAB risk score was an independent prognostic factor in the consideration of clinical parameters in multivariate analysis. At ten years, CAB high-risk had the worst DRFi of 69.8%, CAB low-risk in the exemestane monotherapy arm had the best DRFi of 92.7% [vs CAB high-risk, HR, 0.21 (95% CI, 0.11-0.43), P < 0.001], and CAB low-risk in the sequential arm had a DRFi of 84.2% [vs CAB high-risk, HR, 0.48 (95% CI, 0.28-0.82), P = 0.009].

CONCLUSIONS

Cost-effective CAB is a statistically robust prognostic and predictive tool for ten-year DM for postmenopausal women with HR+/HER2-, early breast cancer. CAB low-risk patients who received exemestane monotherapy had an excellent ten-year DRFi.

Research Silos in Cancer Disparities: Obstacles to Improving Clinical Outcomes for Underserved Patient Populations

Despite much vaunted progress in cancer therapeutics and diagnostics, outcomes for many groups of non-White patients with cancer remain worse than those for their White compatriots. One reason for this is the lack of inclusion and representation of non-White patients in clinical trials, preclinical datasets, and among researchers, a shortfall that is gaining wide recognition within the cancer research community and the lay public. Several reviews and editorials have commented on the negative impacts of the status quo on progress in cancer research toward medical breakthroughs that help all communities and not just White patients with cancer. In this perspective, we describe the existence of research silos focused either on the impact of socioeconomic factors proceeding from systemic racism on cancer outcomes, or on genetic ancestry as it affects the molecular biology of cancer developing in specific patient populations. While both these research areas are critical for progress toward precision medicine equity, breaking down these silos will help us gain an integrated understanding of how race and racism impact cancer development, progression, and patient outcomes. Bringing this comprehensive approach to cancer disparities research will undoubtedly improve our overall understanding of how stress and environmental factors affect the molecular biology of cancer, which will lead to the development of new diagnostics and therapeutics that are applicable across cancer patient demographics.

Applying a GAN-based classifier to improve transcriptome-based prognostication in breast cancer

Established prognostic tests based on limited numbers of transcripts can identify high-risk breast cancer patients yet are approved only for individuals presenting with specific clinical features or disease characteristics. Deep learning algorithms could hold potential for stratifying patient cohorts based on full transcriptome data, yet the development of robust classifiers is hampered by the number of variables in omics datasets typically far exceeding the number of patients. To overcome this hurdle, we propose a classifier based on a data augmentation pipeline consisting of a Wasserstein generative adversarial network (GAN) with gradient penalty and an embedded auxiliary classifier to obtain a trained GAN discriminator (T-GAN-D). Applied to 1244 patients of the METABRIC breast cancer cohort, this classifier outperformed established breast cancer biomarkers in separating low- from high-risk patients (disease specific death, progression or relapse within 10 years from initial diagnosis). Importantly, the T-GAN-D also performed across independent, merged transcriptome datasets (METABRIC and TCGA-BRCA cohorts), and merging data improved overall patient stratification. In conclusion, the reiterative GAN-based training process allowed generating a robust classifier capable of stratifying low- vs high-risk patients based on full transcriptome data and across independent and heterogeneous breast cancer cohorts.

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.

Discordance between PAM50 intrinsic subtyping and immunohistochemistry in South African women with breast cancer

PURPOSE

Breast cancer is a heterogeneous disease with different gene expression profiles, treatment options and outcomes. In South Africa, tumors are classified using immunohistochemistry. In high-income countries multiparameter genomic assays are being utilized with implications for tumor classification and treatment.

METHODS

In a cohort of 378 breast cancer patients from the SABCHO study, we investigated the concordance between tumor samples classified by IHC and the PAM50 gene assay.

RESULTS

IHC classified patients as ER-positive (77.5%), PR-positive (70.6%), and HER2-positive (32.3%). These results, together with Ki67, were used as surrogates for intrinsic subtyping, and showed 6.9% IHC-A-clinical, 72.7% IHC-B-clinical, 5.3% IHC-HER2-clinical and 15.1% triple negative cancer (TNC). Typing using the PAM50 gave 19.3% luminal-A, 32.5% luminal-B, 23.5% HER2-enriched and 24.6% basal-like. The basal-like and TNC had the highest concordance, while the luminal-A and IHC-A group had the lowest concordance. By altering the cutoff for Ki67, and realigning the HER2/ER/PR-positive patients to IHC-HER2, we improved concordance with the intrinsic subtypes.

CONCLUSION

We suggest that the Ki67 be changed to a cutoff of 20-25% in our population to better reflect the luminal subtype classifications. This change would inform treatment options for breast cancer patients in settings where genomic assays are unaffordable.

Survival Disparities in US Black Compared to White Women with Hormone Receptor Positive-HER2 Negative Breast Cancer

Black women in the US have significantly higher breast cancer mortality than White women. Within biomarker-defined tumor subtypes, disparate outcomes seem to be limited to women with hormone receptor positive and HER2 negative (HR+/HER2-) breast cancer, a subtype usually associated with favorable prognosis. In this review, we present data from an array of studies that demonstrate significantly higher mortality in Black compared to White women with HR+/HER2-breast cancer and contrast these data to studies from integrated healthcare systems that failed to find survival differences. Then, we describe factors, both biological and non-biological, that may contribute to disparate survival in Black women.

Prevalence of Breast Cancer Subtypes Among Different Ethnicities and Bangladeshi Women: Demographic, Clinicopathological, and Integrated Cancer Informatics Analysis

Background

The molecular subtyping of breast cancer is related to estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). The present study aimed to systematically analyze the expression, function, and prognostic value of ER, PR, HER2, and their prevalence in different ethnic groups and among Bangladeshi breast cancer (BC) patients.

Method

This study included 25 BC patients and 25 healthy controls, aged between 25 and 70 years. The study characteristics were compared using the ANOVA and Chi-square tests. Also, the multi-Omics dataset of 775 BC patients from TCGA was analyzed for ER, PR, and HER2 in breast cancer subtypes and compared among different ethnicities.

Results

For most BD breast cancer cases, the age at diagnosis was ⩾40 years, had only a histopathological diagnosis (P-value .004), and no history of mammography or other pathological tests. For treatment, had only chemotherapy (P-value .004) and no hormone therapy (P-value <.001). The majority of patients (>60%) were of stage-II cancer and TNBC (40%) subtype. The BC ethnicity-stratified data of ER, PR, and HER2 indicated a strong correlation across all ethnicities (P-value 4.99e-35; P-value 3.79e-18). The subtypes stratified data indicated a higher percentage of Luminal A (58.3%) in Caucasians whereas Luminal B (24.3%) and HER2 (25.2%) subtypes were found higher in Asians and TNBC (36.0%) were found in Africans. However, a significantly higher frequency of TNBC (52.2%) compared to Asians (14.8%) was found in BD patients (P-value <.001). The overall survival analysis of BC subtypes demonstrated that Luminal B (P-value .005) and HER2 enriched (P-value .015) were significantly more aggressive and were dominant in the Asian population.

Conclusion

A significant association was found between BC subtypes with different ethnicities and Bangladeshi women and these findings might aid in the prevention, management, and raising of awareness against risk factors in the near future.

Expanding access to early phase trials: the CATCH-UP.2020 experience

BACKGROUND

Disparities in cancer outcomes persist for underserved populations; one important aspect of this is limited access to promising early phase clinical trials. To address this, the National Cancer Institute-funded Create Access to Targeted Cancer Therapy for Underserved Populations (CATCH-UP.2020) was created. We report the tools developed and accrual metrics of the initial year of CATCH-UP.2020 with a focus on racial, ethnic, geographic, and socioeconomically underserved populations.

METHODS

CATCH-UP.2020 is a P30 supplement awarded to 8 National Cancer Institute-designated cancer centers with existing resources to rapidly open and accrue to Experimental Therapeutics Clinical Trials Network (ETCTN) trials with emphasis on engaging patients from underserved populations. Sites used patient-based, community-based, investigator-based, and program-based tools to meet specific program goals.

RESULTS

From September 2020 to August 2021, CATCH-UP.2020 sites opened 45 ETCTN trials. Weighted average trial activation time for the 7 sites reporting this was 107 days. In the initial year, sites enrolled 145 patients in CATCH-UP.2020 with 68 (46.9%) representing racial, ethnic, rural, and socioeconomically underserved populations using the broader definition of underserved encompassed in the grant charge. During the initial year of CATCH-UP.2020, a time impacted by the COVID-19 pandemic, 15.8% (66 of 417) and 21.4% (31 of 145) of patients enrolled to ETCTN trials at network and at CATCH-UP sites, respectively, were from racial and ethnic minority groups, a more limited definition of underserved for which comparable data are available.

CONCLUSION

Targeted funding accelerated activation and accrual of early phase trials and expanded access to this therapeutic option for underserved populations.

RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse 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.

Association between Obesity, Race or Ethnicity, and Luminal Subtypes of Breast Cancer

Luminal breast cancers are the most common genomic subtype of breast cancers where Luminal A cancers have a better prognosis than Luminal B. Exposure to sex steroids and inflammatory status due to obesity are key contributors of Luminal tumor development. In this study, 1928 patients with Luminal A breast cancer and 1610 patients with Luminal B breast cancer were compared based on body mass index (BMI), age, race, menopausal status, and expressed receptors (i.e., estrogen (ER), progesterone (PR), and human epidermal growth factor receptor 2 (HER2)). Patients with Luminal B tumors had a significantly higher mean BMI (Δ = 0.69 kgm−2 [0.17, 1.21], p = 0.010) versus Luminal A. Interestingly, the risks of Luminal B tumors were higher among Black/African American patients versus White and Hispanic patients (p < 0.001 and p = 0.001, respectively). When controlled for each other, Black/African American race (p < 0.001) and increased BMI (p = 0.008) were associated with increased risks of Luminal B carcinoma, while postmenopausal status was associated with a decreased risk (p = 0.028). Increased BMI partially mediated the strong association between Black/African American race and the risk of Luminal B carcinoma. Thus, Black/African American race along with obesity seem to be associated with an increased risk of more aggressive Luminal B breast carcinomas.

Obesity and Breast Cancer Metastasis across Genomic Subtypes

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.

Racial Disparity in Quadruple Negative Breast Cancer: Aggressive Biology and Potential Therapeutic Targeting and Prevention

Simple Summary

Quadruple negative breast cancer (QNBC), a subgroup of triple negative BC, has emerged as a highly aggressive BC subtype that disproportionately afflicts and impacts Black/African-American (AA) women. In this article, we review molecular distinctions in Black/AA and White/European-American (EA) QNBC biology as well as address potential non-genetic risk factors that could be underlying this racially disparate burden. We aim to provide deeper insight and provide a framework for novel discovery of actionable therapeutic targets and identify lifestyle changes to improve outcomes for Black/AA QNBC patients.

Abstract

Black/African-American (AA) women, relative to their White/European-American (EA) counterparts, experience disproportionately high breast cancer mortality. Central to this survival disparity, Black/AA women have an unequal burden of aggressive breast cancer subtypes, such as triple-negative breast cancer (ER/PR-, HER2-wild type; TNBC). While TNBC has been well characterized, recent studies have identified a highly aggressive androgen receptor (AR)-negative subtype of TNBC, quadruple-negative breast cancer (ER/PR-, HER2-wildtype, AR-; QNBC). Similar to TNBC, QNBC disproportionately impacts Black/AA women and likely plays an important role in the breast cancer survival disparities experienced by Black/AA women. Here, we discuss the racial disparities of QNBC and molecular signaling pathways that may contribute to the aggressive biology of QNBC in Black/AA women. Our immediate goal is to spotlight potential prevention and therapeutic targets for Black/AA QNBC; ultimately our goal is to provide greater insight into reducing the breast cancer survival burden experienced by Black/AA women.

Triple negative breast cancer: Pitfalls and progress

Triple negative breast cancer (TNBC) is characterized by the lack of estrogen and progesterone receptor expression and lacks HER2 overexpression or gene amplification. It accounts for 10–15% of incident breast cancers and carries the worst prognosis. TNBC is overrepresented among Black and pre-menopausal women and is associated with significant psychological and treatment-related burdens, including financial toxicity. Like other breast cancers, TNBC is biologically heterogeneous, leading to diverse clinical and epidemiological behaviors, however, unlike the other clinical subtypes, in TNBC we still lack tumor-specific targeted therapy. Early TNBC outcomes have improved due to the intensification of therapies, including improvements in polychemotherapy and the addition of immunotherapy. Future efforts are needed to identify targetable aberrations for specific drug therapy, prevent immune evasion, and increase social-economic support. Given that the name TNBC illustrates its lack of specifically targeted and effective therapy, we look forward to being able to retire the name in favor of a group of targetable entities within what is now called “TNBC”.

Radiogenomics analysis reveals the associations of dynamic contrast-enhanced–MRI features with gene expression characteristics, PAM50 subtypes, and prognosis of breast cancer

Background

To investigate reliable associations between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) features and gene expression characteristics in breast cancer (BC) and to develop and validate classifiers for predicting PAM50 subtypes and prognosis from DCE-MRI non-invasively.

Methods

Two radiogenomics cohorts with paired DCE-MRI and RNA-sequencing (RNA-seq) data were collected from local and public databases and divided into discovery (n = 174) and validation cohorts (n = 72). Six external datasets (n = 1,443) were used for prognostic validation. Spatial–temporal features of DCE-MRI were extracted, normalized properly, and associated with gene expression to identify the imaging features that can indicate subtypes and prognosis.

Results

Expression of genes including RBP4, MYBL2, and LINC00993 correlated significantly with DCE-MRI features (q-value < 0.05). Importantly, genes in the cell cycle pathway exhibited a significant association with imaging features (p-value < 0.001). With eight imaging-associated genes (CHEK1, TTK, CDC45, BUB1B, PLK1, E2F1, CDC20, and CDC25A), we developed a radiogenomics prognostic signature that can distinguish BC outcomes in multiple datasets well. High expression of the signature indicated a poor prognosis (p-values < 0.01). Based on DCE-MRI features, we established classifiers to predict BC clinical receptors, PAM50 subtypes, and prognostic gene sets. The imaging-based machine learning classifiers performed well in the independent dataset (areas under the receiver operating characteristic curve (AUCs) of 0.8361, 0.809, 0.7742, and 0.7277 for estrogen receptor (ER), human epidermal growth factor receptor 2 (HER2)-enriched, basal-like, and obtained radiogenomics signature). Furthermore, we developed a prognostic model directly using DCE-MRI features (p-value < 0.0001).

Conclusions

Our results identified the DCE-MRI features that are robust and associated with the gene expression in BC and displayed the possibility of using the features to predict clinical receptors and PAM50 subtypes and to indicate BC prognosis.

The Landscape of Immune Microenvironments in Racially Diverse Breast Cancer Patients

BACKGROUND

Immunotherapy is a rapidly evolving treatment option in breast cancer; However, the breast cancer immune microenvironment is understudied in Black and younger (<50 years) patients.

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.

Disparities in the impact of the AJCC 8th edition staging system on differentiated thyroid cancer outcomes

BACKGROUND

The impact of AJCC8 among self-reported racial/ethnic groups on differentiated thyroid cancer (DTC) outcomes is unknown.

METHODS

Multivariate-regression evaluated the association between AJCC7 to AJCC8 stage change and race/ethnicity in patients with DTC in the NCDB. Cox-proportional-regression evaluated whether AJCC7 to AJCC8 stage change affects overall survival (OS) differently based on reported race/ethnicity.

RESULTS

After adjusting for confounders, Hispanics and Asian-Pacific-Islanders (APIs) were 27% and 12% less likely to be down-staged compared to white-non-Hispanics (WNHs) (p < 0.001); black-non-Hispanics (BNHs) had no significant down-staging difference. Down-staged patients had an increased risk of death compared to patients with unchanged staging, regardless of race/ethnicity. However, based on two-way interaction, the magnitude of this negative change on survival from down-staging was only different between WNHs (HR = 2.64) and BNHs (HR = 1.77), (p = 0.04).

CONCLUSIONS

Outcome disparities persist among self-reported racial/ethnic groups with AJCC8. Down-staged patients across all racial/ethnic groups had decreased survival compared to those with unchanged stage, with the least impact in BNHs.

Prognostic significance of RNA-based TP53 pathway function among estrogen receptor positive and negative breast cancer cases

TP53 and estrogen receptor (ER) are essential in breast cancer development and progression, but TP53 status (by DNA sequencing or protein expression) has been inconsistently associated with survival. We evaluated whether RNA-based TP53 classifiers are related to survival. Participants included 3213 women in the Carolina Breast Cancer Study (CBCS) with invasive breast cancer (stages I-III). Tumors were classified for TP53 status (mutant-like/wildtype-like) using an RNA signature. We used Cox proportional hazards models to estimate covariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer-specific survival (BCSS) among ER- and TP53-defined subtypes. RNA-based results were compared to DNA- and IHC-based TP53 classification, as well as Basal-like versus non-Basal-like subtype. Findings from the diverse (50% Black), population-based CBCS were compared to those from the largely white METABRIC study. RNA-based TP53 mutant-like was associated with BCSS among both ER-negatives and ER-positives (HR (95% CI) = 5.38 (1.84-15.78) and 4.66 (1.79-12.15), respectively). Associations were attenuated when using DNA- or IHC-based TP53 classification. In METABRIC, few ER-negative tumors were TP53-wildtype-like, but TP53 status was a strong predictor of BCSS among ER-positives. In both populations, the effect of TP53 mutant-like status was similar to that for Basal-like subtype. RNA-based measures of TP53 status are strongly associated with BCSS and may have value among ER-negative cancers where few prognostic markers have been robustly validated. Given the role of TP53 in chemotherapeutic response, RNA-based TP53 as a prognostic biomarker could address an unmet need in breast cancer.

Protein expression of the gp78 E3-ligase predicts poor breast cancer outcome based on race

Women of African ancestry suffer higher rates of breast cancer mortality compared to all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated degradation (ERAD) E3 ubiquitin ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER-positive and ER-negative tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer new insights into our understanding of racial differences in breast cancer outcomes.

Racial differences in predictive value of the 21-gene recurrence score assay: a population-based study using the SEER database

Purpose

The 21-gene recurrence score (RS) assay is currently used for predicting chemotherapeutic benefits for hormone receptor-positive (HR +) early-stage breast cancer patients without consideration regarding racial differences in that predictive value. This study aimed at demonstrating racial differences in the predictive values of the 21-gene RS assay.

Methods

The study cohort was selected from the Surveillance, Epidemiology, and End Results (SEER) database. Breast cancer-specific mortality (BCSM) was compared between patients who received chemotherapy (the “CTx group”) and those who did not (the “no CTx group”) to estimate the predictive value of the assay. This comparison was repeated for each racial group.

Results

Among 88,498 T1 − 2N0 HR + breast cancer patients who had results of 21-gene RS, 13,123 patients had RS > 25, which included 10,697 Whites, 1282 Blacks, and 1,144 Asian Americans/Pacific Islanders (AAPIs). Chemotherapy was administered to 8364 patients (63.4%). The adjusted hazard ratio for BCSM in the CTx group (vs. no CTx group) was 0.734 (95% confidence interval [CI] 0.588–0.917) in Whites, 0.748 (95% CI 0.428–1.307) in Blacks, and 1.343 (95% CI 0.558–3.233) in AAPIs. No subgroup within patients with RS > 25 among non-White women showed a significant predictive value of the 21-gene RS assay, except for Black women with grade 3 tumors.

Conclusion

The predictive value of the 21-gene RS assay for assessing chemotherapy benefit was validated in White women based on the SEER database, although the predictive value was not warranted in non-White women.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12282-022-01371-z.

Quantitative analysis of breast cancer tissue composition and associations with tumor subtype

The tumor microenvironment is an important determinant of breast cancer progression, but standard methods for describing the tumor microenvironment are lacking. Measures of microenvironment composition such as stromal area and immune infiltrate are labor-intensive and few large studies have systematically collected this data. However, digital histologic approaches are becoming more widely available, allowing high-throughput, quantitative estimation. We applied such methods to tissue microarrays of tumors from 1687 women (mean 4 cores per case) in the Carolina Breast Cancer Study Phase 3. Tumor composition was quantified as percentage of epithelium, stroma, adipose, and lymphocytic infiltrate (with the latter as presence/absence using a ≥1% cutoff). Composition proportions and presence/absence were evaluated in association with clinical and molecular features of breast cancer (intrinsic subtype and RNA-based risk of recurrence [ROR] scores) using multivariable linear and logistic regression. Lower stromal content was associated with aggressive tumor phenotypes, including triple-negative (31.1% vs. 41.6% in HR+/HER2-; RFD [95% CI]: -10.5%, [-13.1, -7.9]), Basal-like subtypes (29.0% vs. 44.0% in Luminal A; RFD [95% CI]: -14.9%, [-17.8, -12.0]), and high RNA-based PAM50 ROR scores (27.6% vs. 48.1% in ROR low; RFD [95% CI]: -20.5%, [24.3, 16.7]), after adjusting for age and race. HER2+ tumors also had lower stromal content, particularly among RNA-based HER2-enriched (35.2% vs. 44.0% in Luminal A; RFD [95% CI]: -8.8%, [-13.8, -3.8]). Similar associations were observed between immune infiltrate and tumor phenotypes. Quantitative digital image analysis of the breast cancer microenvironment showed significant associations with demographic characteristics and biological indicators of aggressive behavior.

Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression

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.

Racial differences in breast cancer outcomes by hepatocyte growth factor pathway expression

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 is 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 1957 invasive breast cancer cases from the Carolina Breast Cancer Study. The HGF signature was evaluated in association with recurrence (n = 1251, 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.

A pooled case-only analysis of obesity and breast cancer subtype among Black women in the southeastern United States

PURPOSE

To evaluate the association between obesity and the relative prevalence of tumor subtypes among Black women with breast cancer (BC).

METHODS

We conducted a pooled case-only analysis of 1,793 Black women with invasive BC recruited through three existing studies in the southeastern US. Multivariable case-only polytomous logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between obesity, measured by pre-diagnostic body mass index (BMI), and human epidermal growth factor receptor 2 + (HER2 +) and triple negative BC (TNBC) subtype relative to hormone receptor (HR) + /HER2- status (referent).

RESULTS

Among 359 premenopausal women, 55.4% of cases were HR + /HER2 -, 20.1% were HER2 + , and 24.5% were TNBC; corresponding percentages among 1,434 postmenopausal women were 59.3%, 17.0%, and 23.6%. Approximately, 50-60% of both pre- and postmenopausal women were obese (BMI > 30 kg/m²), regardless of BC subtype. We did not observe a significant association between obesity and BC subtype. Among postmenopausal women, class I obesity (BMI 35 + kg/m²) was not associated with the development of HER2 + BC (OR 0.69; 95% CI 0.42-1.14) or TNBC (OR 0.93; 95% CI 0.60-1.45) relative to HR + /HER2- tumors. Corresponding estimates among premenopausal women were 1.03 (95% CI 0.43-2.48) and 1.13 (95% CI 0.48-2.64).

CONCLUSION

In this large study of Black women with BC, there was no evidence of heterogeneity of BMI by BC subtype.

Differences in somatic TP53 mutation type in breast tumors by race and receptor status

PURPOSE

Somatic driver mutations in TP53 are associated with triple-negative breast cancer (TNBC) and poorer outcomes. Breast cancers in women of African ancestry (AA) are more likely to be TNBC and have somatic TP53 mutations than cancers in non-Hispanic White (NHW) women. Missense driver mutations in TP53 have varied functional impact including loss-of-function (LOF) or gain-of-function (GOF) activity, and dominant negative (DNE) effects. We aimed to determine if there were differences in somatic TP53 mutation types by patient ancestry or TNBC status.

METHODS

We identified breast cancer datasets with somatic TP53 mutation data, ancestry, age, and hormone receptor status. Mutations were classified for functional impact using published data and type of mutation. We assessed differences using Fisher's exact test.

RESULTS

From 96 breast cancer studies, we identified 2964 women with somatic TP53 mutations: 715 (24.1%) Asian, 258 (8.7%) AA, 1931 (65.2%) NHW, and 60 (2%) Latina. The distribution of TP53 mutation type was similar by ancestry. However, 35.8% of tumors from NHW individuals had GOF mutations compared to 29% from AA individuals (p = 0.04). Mutations with DNE activity were positively associated with TNBC (OR 1.37, p = 0.03) and estrogen receptor (ER) negative status (OR 1.38; p = 0.005).

CONCLUSIONS

Somatic TP53 mutation types did not differ by ancestry overall, but GOF mutations were more common in NHW women than AA women. ER-negative and TNBC tumors are less likely to have DNE+ TP53 mutations which could reflect biological processes. Larger cohorts and functional studies are needed to further elucidate these findings.

The DNA damage repair landscape in Black women with breast cancer

BACKGROUND

Estrogen receptor positive (ER+) breast cancer is one of the most commonly diagnosed malignancies in women irrespective of their race or ethnicity. While Black women with ER+ breast cancer are 42% more likely to die of their disease than White women, molecular mechanisms underlying this disparate outcome are understudied. Recent studies identify DNA damage repair (DDR) genes as a new class of endocrine therapy resistance driver that contributes to poor survival among ER+ breast cancer patients. Here, we systematically analyze DDR regulation in the tumors and normal breast of Black women and its impact on survival outcome.

METHOD

Mutation and up/downregulation of 104 DDR genes in breast tumor and normal samples from Black patients relative to White counterparts was assessed. For DDR genes that were differently regulated in the tumor samples from Black women in multiple datasets associations with survival outcome were tested.

RESULTS

Overall, Black patient tumors upregulate or downregulate RNA levels of a wide array of single strand break repair (SSBR) genes relative to their white counterparts and uniformly upregulate double strand break repair (DSBR) genes. This DSBR upregulation was also detectable in samples of normal breast tissue from Black women. Eight candidate DDR genes were reproducibly differently regulated in tumors from Black women and associated with poor survival. A unique DDR signature comprised of simultaneous upregulation of homologous recombination gene expression and downregulation of SSBR genes was enriched in Black patients. This signature associated with cell cycle dysregulation (p < 0.001), a hallmark of endocrine therapy resistance, and concordantly, with significantly worse survival outcomes in all datasets analyzed (hazard ratio of 9.5, p < 0.001).

CONCLUSION

These results constitute the first systematic analysis of DDR regulation in Black women and provide strong rationale for refining biomarker profiles to ensure precision medicine for underserved populations.

Gene-Level Germline Contributions to Clinical Risk of Recurrence Scores in Black and White Patients with Breast Cancer

Continuous risk of recurrence scores (CRS) based on tumor gene expression are vital prognostic tools for breast cancer. Studies have shown that Black women (BW) have higher CRS than White women (WW). Although systemic injustices contribute substantially to breast cancer disparities, evidence of biological and germline contributions is emerging. In this study, we investigated germline genetic associations with CRS and CRS disparity using approaches modeled after transcriptome-wide association studies (TWAS). In the Carolina Breast Cancer Study, using race-specific predictive models of tumor expression from germline genetics, we performed race-stratified (N = 1,043 WW, 1,083 BW) linear regressions of three CRS (ROR-S: PAM50 subtype score; proliferation score; ROR-P: ROR-S plus proliferation score) on imputed tumor genetically regulated tumor expression (GReX). Bayesian multivariate regression and adaptive shrinkage tested GReX-prioritized genes for associations with tumor PAM50 expression and subtype to elucidate patterns of germline regulation underlying GReX-CRS associations. At FDR-adjusted P < 0.10, 7 and 1 GReX prioritized genes among WW and BW, respectively. Among WW, CRS were positively associated with MCM10, FAM64A, CCNB2, and MMP1 GReX and negatively associated with VAV3, PCSK6, and GNG11 GReX. Among BW, higher MMP1 GReX predicted lower proliferation score and ROR-P. GReX-prioritized gene and PAM50 tumor expression associations highlighted potential mechanisms for GReX-prioritized gene to CRS associations. Among patients with breast cancer, differential germline associations with CRS were found by race, underscoring the need for larger, diverse datasets in molecular studies of breast cancer. These findings also suggest possible germline trans-regulation of PAM50 tumor expression, with potential implications for CRS interpretation in clinical settings. SIGNIFICANCE: This study identifies race-specific genetic associations with breast cancer risk of recurrence scores and suggests mediation of these associations by PAM50 subtype and expression, with implications for clinical interpretation of these scores.

TP53 Pathway Function, Estrogen Receptor Status, and Breast Cancer Risk Factors in the Carolina Breast Cancer Study

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.

Kinesin Family Member C1 (KIFC1/HSET): A Potential Actionable Biomarker of Early Stage Breast Tumorigenesis and Progression of High-Risk Lesions

The enigma of why some premalignant or pre-invasive breast lesions transform and progress while others do not remains poorly understood. Currently, no radiologic or molecular biomarkers exist in the clinic that can successfully risk-stratify high-risk lesions for malignant transformation or tumor progression as well as serve as a minimally cytotoxic actionable target for at-risk subpopulations. Breast carcinogenesis involves a series of key molecular deregulatory events that prompt normal cells to bypass tumor-suppressive senescence barriers. Kinesin family member C1 (KIFC1/HSET), which confers survival of cancer cells burdened with extra centrosomes, has been observed in premalignant and pre-invasive lesions, and its expression has been shown to correlate with increasing neoplastic progression. Additionally, KIFC1 has been associated with aggressive breast tumor molecular subtypes, such as basal-like and triple-negative breast cancers. However, the role of KIFC1 in malignant transformation and its potential as a predictive biomarker of neoplastic progression remain elusive. Herein, we review compelling evidence suggesting the involvement of KIFC1 in enabling pre-neoplastic cells to bypass senescence barriers necessary to become immortalized and malignant. We also discuss evidence inferring that KIFC1 levels may be higher in premalignant lesions with a greater inclination to transform and acquire aggressive tumor intrinsic subtypes. Collectively, this evidence provides a strong impetus for further investigation into KIFC1 as a potential risk-stratifying biomarker and minimally cytotoxic actionable target for high-risk patient subpopulations.

JOINT AND INDIVIDUAL ANALYSIS OF BREAST CANCER HISTOLOGIC IMAGES AND GENOMIC COVARIATES

The two main approaches in the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genomics. While both histopathology and genomics are fundamental to cancer research, the connections between these fields have been relatively superficial. We bridge this gap by investigating the Carolina Breast Cancer Study through the development of an integrative, exploratory analysis framework. Our analysis gives insights - some known, some novel - that are engaging to both pathologists and geneticists. Our analysis framework is based on Angle-based Joint and Individual Variation Explained (AJIVE) for statistical data integration and exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction. CNNs raise interpretability issues that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features.

Molecular and clinical characterization of postpartum-associated breast cancer in the Carolina Breast Cancer Study Phase I-III, 1993-2013

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 <50 years of age who were recently ( {less than or equal to} 10 years prior), or remotely (>10 years prior) postpartum, or nulliparous. Prevalence odds ratios (PORs) and 95% confidence intervals (CIs) 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)], ER negative [1.37 (1.02, 1.83)], and IHC-based triple negative [1.57 (1.00, 2.47)] compared to nulliparous (N=360) women. Some differences were identified between recent vs. 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/NK cells, Tfh cells and higher overall immune cell scores. These differences were attenuated in remotely (compared to 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, post-diagnostic treatment and outcomes among recently postpartum women.

Impact of molecular subtype and race on HR+, HER2- breast cancer survival

PURPOSE

There is an urgent need to understand the biological factors contributing to the racial survival disparity among women with hormone receptor-positive (HR+), HER2- breast cancer. In this study, we examined the impact of PAM50 subtype on 10-year mortality rate in women with HR+, HER2- breast cancer by race.

METHODS

Women with localized, HR+, HER2- breast cancer diagnosed between 2002 and 2012 from two population-based cohorts were evaluated. Archival tumors were obtained and classified by PAM50 into four molecular subtypes (i.e., luminal A, luminal B, HER2-enriched, and basal-like). The molecular subtypes within HR+, HER2- breast cancers and corresponding 10-year mortality rate were compared between Black and Non-Hispanic White (NHW) women using Cox proportional hazard ratios and survival analysis, adjusting for covariates.

RESULTS

In this study, 318 women with localized, HR+, HER2- breast cancer were included-227 Black (71%) and 91 NHW (29%). Young Black women (age ≤ 50) had the highest proportion of HR+, non-luminal A tumors (47%), compared to young NHW (10%), older Black women (31%), and older NHW (30%). Overall, women with HR+, non-luminal A subtypes had a higher 10-year mortality rate compared to HR+, luminal A subtypes after adjustment for age, stage, and income (HR 4.21 for Blacks, 95% CI 1.74-10.18 and HR 3.44 for NHW, 95% CI 1.31-9.03). Among HR+, non-luminal A subtypes there was, however, no significant racial difference in 10-yr mortality observed (Black vs. NHW: HR 1.23, 95% CI 0.58-2.58).

CONCLUSION

Molecular subtype classification highlights racial disparities in PAM50 subtype distribution among women with HR+, HER2- breast cancer. Among women with HR+, HER2- breast cancer, racial survival disparities are ameliorated after adjusting for molecular subtype.

Adherence to Endocrine Therapy and Racial Outcome Disparities in Breast Cancer

The disparity in outcomes of breast cancer for Black compared with White women in the U.S. is well known and persistent over time, with the largest disparities appearing among women with hormone receptor-positive (HR+) cancers. The racial gap in breast cancer survival first emerged in the 1980s, a time of significantmen treatment advances in early-stage breast cancer, including the introduction of adjuvant endocrine therapy. Since that time, the gap has continued to widen despite steady advances in treatment and survival of breast cancer overall. Although advanced stage at presentation and unfavorable biology undoubtedly contribute to racial differences in survival of HR+ breast, treatment disparities are increasingly acknowledged to play a key role as well. The recent recognition of racial differences in endocrine therapy use may be a key explanatory factor in the persistent racial gap in mortality of HR+ disease, and may be a key focus of intervention to improve breast cancer outcomes for Black women. IMPLICATIONS FOR PRACTICE: Black women with hormone receptor-positive breast cancer experience the greatest racial disparity in survival among all breast cancer subtypes. This survival gap appears consistently across studies and is not entirely explained by differences in presenting stage, tumor biology as assessed by genomic risk scores, or receipt of chemotherapy. Recent research highlights lower adherence to endocrine therapy (ET) for Black women. Health systems and individual providers should focus on improving communication about the importance of ET use, sharing decisions around ET, providing appropriate support for side effects and other ET-related concerns, and equitably delivering survivorship care, including ET adherence assessment.

Myocardial Function in Premenopausal Women Treated With Ovarian Function Suppression and an Aromatase Inhibitor

Background

Premenopausal women with high-risk hormone receptor (HR)-positive breast cancer often receive ovarian function suppression (OFS) with aromatase inhibitor therapy; however, abrupt menopause induction, together with further decrements in estrogen exposure through aromatase inhibition, may affect cardiovascular microcirculatory function. We examined adenosine-induced changes in left ventricular (LV) myocardial T1, a potential subclinical marker of LV microcirculatory function in premenopausal women undergoing treatment for breast cancer.

Methods

Twenty-one premenopausal women (14 with HR-positive breast cancer receiving OFS with an aromatase inhibitor and 7 comparator women with triple-negative breast cancer [TNBC] who had completed primary systemic therapy) underwent serial resting and adenosine cardiovascular magnetic resonance imaging measurements of LV myocardial T1 and LV volumes, mass, and ejection fraction. All statistical tests were 2-sided.

Results

After a median of 4.0 months (range = 3.1-5.7 months), the stress to resting ratio of LV myocardial T1 declined in women with HR-positive breast cancer (−1.3%, 95% confidence interval [CI] = −3.4% to 0.7%) relative to those with TNBC (3.2%, 95% CI = −1.2% to 7.6%, P = .02). After accounting for age, LV stroke volume, LV ejection fraction, diastolic blood pressure, and breast cancer subtype women with HR-positive breast cancer experienced a blunted T1 response after adenosine relative to women with TNBC (difference = −4.7%, 95% CI = −7.3% to −2.1%, P_difference = .002).

Conclusions

Over the brief interval examined, women with HR-positive breast cancer receiving OFS with an aromatase inhibitor experienced reductions in adenosine-associated changes in LV myocardial T1 relative to women who received nonhormonal therapy for TNBC. These findings suggest a possible adverse impact on LV myocardial microcirculatory function in premenopausal women with breast cancer receiving hormone deprivation therapy.

Identification of a Novel Inflamed Tumor Microenvironment Signature as a Predictive Biomarker of Bacillus Calmette-Guérin Immunotherapy in Non-Muscle-Invasive Bladder Cancer

PURPOSE

Improved risk stratification and predictive biomarkers of treatment response are needed for non-muscle-invasive bladder cancer (NMIBC). Here we assessed the clinical utility of targeted RNA and DNA molecular profiling in NMIBC.

EXPERIMENTAL DESIGN

Gene expression in NMIBC samples was profiled by NanoString nCounter, an RNA quantification platform, from two independent cohorts (n = 28, n = 50); targeted panel sequencing was performed in a subgroup (n = 50). Gene signatures were externally validated using two RNA sequencing datasets of NMIBC tumors (n = 438, n = 73). Established molecular subtype classifiers and novel gene expression signatures were assessed for associations with clinicopathologic characteristics, somatic tumor mutations, and treatment outcomes.

RESULTS

Molecular subtypes distinguished between low-grade Ta tumors with FGFR3 mutations and overexpression (UROMOL-class 1) and tumors with more aggressive clinicopathologic characteristics (UROMOL-classes 2 and 3), which were significantly enriched with TERT promoter mutations. However, UROMOL subclasses were not associated with recurrence after bacillus Calmette-Guérin (BCG) immunotherapy in two independent cohorts. In contrast, a novel expression signature of an inflamed tumor microenvironment (TME) was associated with improved recurrence-free survival after BCG. Expression of immune checkpoint genes (PD-L1/PD-1/CTLA-4) was associated with an inflamed TME, but not with higher recurrence rates after BCG. FGFR3 mutations and overexpression were both associated with low immune signatures.

CONCLUSIONS

Assessment of the immune TME, rather than molecular subtypes, is a promising predictive biomarker of BCG response. Modulating the TME in an immunologically "cold" tumor warrants further investigation. Integrated transcriptomic and exome sequencing should improve treatment selection in NMIBC.

Molecular subtyping of breast cancer intrinsic taxonomy with oligonucleotide microarray and NanoString nCounter

Breast cancer intrinsic subtypes have been identified based on the transcription of a predefined gene expression (GE) profiles and algorithm (PAM50). This study compared molecular subtyping with oligonucleotide microarray and NanoString nCounter assay. A total of 109 Taiwanese breast cancers (24 with adjacent normal breast tissues) were assayed with Affymetrix Human Genome U133 plus 2.0 microarrays and 144 were assayed with the NanoString nCounter while 64 patients were assayed for both platforms. Subtyping with the nearest centroid (single sample prediction) was performed, and 16 out of 24 (67%) matched normal breasts were categorized as the normal breast-like subtype. For 64 breast cancers assayed for both platforms, 41 (65%, one unclassified by microarray) were predicted with an identical subtype, resulting in a fair Kappa statistic of 0.60. Taking nCounter subtyping as the gold standard, prediction accuracy was 43% (3/7), 81% (13/16), 25% (5/20), and 100% (20/20) for basal-like, HER2-enriched, luminal A and luminal B subtype predicted from microarray GE profiles. Microarray identified more luminal B cases from luminal A subtype predicted by nCounter. It's not uncommon to use microarray for breast cancer molecular subtyping for research. Our study showed that fundamental discrepancy existed between distinct GE assays, and cross platform equivalence should be carefully appraised when molecular subtyping was conducted with oligonucleotide microarray.

Hepatocyte growth factor pathway expression in breast cancer by race and subtype

BACKGROUND

African American women have the highest risk of breast cancer mortality compared to other racial groups. Differences in tumor characteristics have been implicated as a possible cause; however, the tumor microenvironment may also contribute to this disparity in mortality. Hepatocyte growth factor (HGF) is a stroma-derived marker of the tumor microenvironment that may affect tumor progression differentially by race.

OBJECTIVE

To examine whether an HGF gene expression signature is differentially expressed by race and tumor characteristics.

METHODS

Invasive breast tumors from 1957 patients were assessed for a 38-gene RNA-based HGF gene expression signature. Participants were black (n = 1033) and non-black (n = 924) women from the population-based Carolina Breast Cancer Study (1993-2013). Generalized linear models were used to estimate the relative frequency differences (RFD) in HGF status by race, clinical, and demographic factors.

RESULTS

Thirty-two percent of tumors were positive for the HGF signature. Black women were more likely [42% vs. 21%; RFD = + 19.93% (95% CI 16.00, 23.87)] to have HGF-positive tumors compared to non-black women. Triple-negative patients had a higher frequency of HGF positivity [82% vs. 13% in non-triple-negative; RFD = + 65.85% (95% CI 61.71, 69.98)], and HGF positivity was a defining feature of basal-like subtype [92% vs. 8% in non-basal; RFD = + 81.84% (95% CI 78.84, 84.83)]. HGF positivity was associated with younger age, stage, higher grade, and high genomic risk of recurrence (ROR-PT) score.

CONCLUSION

HGF expression is a defining feature of basal-like tumors, and its association with black race and young women suggests it may be a candidate pathway for understanding breast cancer disparities.

Revisiting social MPE: an integration of molecular pathological epidemiology and social science in the new era of precision medicine

INTRODUCTION

Molecular pathological epidemiology (MPE) is an integrative transdisciplinary area examining the relationships between various exposures and pathogenic signatures of diseases. In line with the accelerating advancements in MPE, social science and its health-related interdisciplinary areas have also developed rapidly. Accumulating evidence indicates the pathological role of social-demographic factors. We therefore initially proposed social MPE in 2015, which aims to elucidate etiological roles of social-demographic factors and address health inequalities globally. With the ubiquity of molecular diagnosis, there are ample opportunities for researchers to utilize and develop the social MPE framework.

AREAS COVERED

Molecular subtypes of breast cancer have been investigated rigorously for understanding its etiologies rooted from social factors. Emerging evidence indicates pathogenic heterogeneity of neurological disorders such as Alzheimer's disease. Presenting specific patterns of social-demographic factors across different molecular subtypes should be promising for advancing the screening, prevention, and treatment strategies of those heterogeneous diseases. This article rigorously reviewed literatures investigating differences of race/ethnicity and socioeconomic status across molecular subtypes of breast cancer and Alzheimer's disease to date.

EXPERT OPINION

With advancements of the multi-omics technologies, we foresee a blooming of social MPE studies, which can address health disparities, advance personalized molecular medicine, and enhance public health.

Breast Cancer in Jamaica: Stage, Grade and Molecular Subtype Distributions Across Age Blocks, the Implications for Screening and Treatment

Background

Breast cancer is the most commonly diagnosed and leading cause of cancer-related morbidity and mortality in females worldwide. Significant disparities exist in breast cancer incidence and mortalities between low- to middle- and high-income countries. The purpose of this study was to analyze the distribution of prognostic and predictive clinicopathological features of invasive breast cancer at a single institution in Jamaica across three age groups.

Methods

Data from patients diagnosed with invasive breast cancer who underwent definitive surgery between August 2017 and September 2018 were identified. The patients were divided into three age groups (< 50, 50 - 59 and > 59 years) and the distribution of tumor size, grade, molecular subtype, nodal status and anatomic stage were determined and compared with the US population registry. Comparisons of the various characteristics were performed using the Fisher’s exact test.

Results

Ninety-nine definitive operations were performed and met the criteria for analysis. Average age at the time of diagnosis was 54 years compared to 62 years reported in the US databases. Thirty-six percent of the patients presented below age 50 years, which was twice the corresponding rate reported for Caucasian females (18%) in the USA. Fifty percent of patients in our registry had axillary lymph node metastases at presentation and they were younger than patients with negative axillary nodes (95% confidence interval (CI) -12.06 to -1.93, P = 0.007). Patients in the age group less than age 50 years were more likely to have advanced stage, high histological grade cancers compared to the older age blocks (95% CI 0.039 - 0.902, P = 0.033).

Conclusion

Invasive breast cancer presents at an earlier age in Jamaican women and is associated with poor prognostic features such as high rates of axillary lymph node metastases, high histological grade, advanced stage, triple-negative subtypes and low luminal A subtypes.

An approach for normalization and quality control for NanoString RNA expression data

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.

DeCompress: tissue compartment deconvolution of targeted mRNA expression panels using compressed sensing

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 present DeCompress, a semi-reference-free deconvolution method for targeted panels. DeCompress leverages 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, DeCompress recapitulates cell-type proportions with less error than reference-free methods and finds biologically relevant compartments. We integrate compartment estimates into cis-eQTL mapping in breast cancer, identifying a tumor-specific cis-eQTL for CCR3 (C-C Motif Chemokine Receptor 3) at a risk locus. DeCompress improves upon reference-free methods without requiring expression profiles from pure cell populations, with applications in genomic analyses and clinical settings.