Breast cancer disparities in outcomes; unmasking biological determinants associated with racial and genetic diversity

The 30th Annual Prostate Cancer Foundation Scientific Retreat Report

BACKGROUND

The 30th Annual Prostate Cancer Foundation (PCF) Scientific Retreat was held at the Omni La Costa Resort in Carlsbad, CA, from October 26 to 28, 2023. A hybrid component was included for virtual attendees.

METHODS

The Annual PCF Scientific Retreat is a leading international scientific conference focused on pioneering, unpublished, and impactful studies across the spectrum of basic through clinical prostate cancer research, as well as research from related fields with significant potential for improving prostate cancer research and patient outcomes.

RESULTS

The 2023 PCF Retreat concentrated on key areas of research, including: (i) the biology of cancer stem cells and prostate cancer lineage plasticity; (ii) mechanisms of treatment resistance; (iii) emerging AI applications in diagnostic medicine; (iv) analytical and computational biology approaches in cancer research; (v) the role of nerves in prostate cancer; (vi) the biology of prostate cancer bone metastases; (vii) the contribution of ancestry and genomics to prostate cancer disparities; (viii) prostate cancer 3D genomics; (ix) progress in new targets and treatments for prostate cancer; (x) the biology and translational applications of tumor extracellular vesicles; (xi) updates from PCF TACTICAL Award teams; (xii) novel platforms for small molecule molecular glues and binding inhibitors; and (xiii) diversity, equity and inclusion strategies for advancing cancer care equity.

CONCLUSIONS

This meeting report summarizes the presentations and discussions from the 2023 PCF Scientific Retreat. We hope that sharing this information will deepen our understanding of current and emerging research and drive future advancements in prostate cancer patient care.

The DARC side of genetics in cancer: Breast cancer disparities

Highlighting the Distinguished Speakers Symposium on "The Future of Human Genetics and Genomics," this collection of articles is based on presentations at the ASHG 2023 Annual Meeting in Washington, DC, in celebration of all our field has accomplished in the past 75 years, since the founding of ASHG in 1948.

The VEGF-Hypoxia Signature Is Upregulated in Basal-like Breast Tumors from Women of African Ancestry and Associated with Poor Outcomes in Breast Cancer

PURPOSE

Black women experience the highest breast cancer mortality rate compared with women of other racial/ethnic groups. To gain a deeper understanding of breast cancer heterogeneity across diverse populations, we examined a VEGF-hypoxia gene expression signature in breast tumors from women of diverse ancestry.

EXPERIMENTAL DESIGN

We developed a NanoString nCounter gene expression panel and applied it to breast tumors from Nigeria (n = 182) and the University of Chicago (Chicago, IL; n = 161). We also analyzed RNA sequencing data from Nigeria (n = 84) and The Cancer Genome Atlas (TCGA) datasets (n = 863). Patient prognosis was analyzed using multiple datasets.

RESULTS

The VEGF-hypoxia signature was highest in the basal-like subtype compared with other subtypes, with greater expression in Black women compared with White women. In TCGA dataset, necrotic breast tumors had higher scores for the VEGF-hypoxia signature compared with non-necrosis tumors (P < 0.001), with the highest proportion in the basal-like subtype. Furthermore, necrotic breast tumors have higher scores for the proliferation signature, suggesting an interaction between the VEGF-hypoxia signature, proliferation, and necrosis. T-cell gene expression signatures also correlated with the VEGF-hypoxia signature when testing all tumors in TCGA dataset. Finally, we found a significant association of the VEGF-hypoxia profile with poor outcomes when using all patients in the METABRIC (P < 0.0001) and SCAN-B datasets (P = 0.002).

CONCLUSIONS

These data provide further evidence for breast cancer heterogeneity across diverse populations and molecular subtypes. Interventions selectively targeting VEGF-hypoxia and the immune microenvironment have the potential to improve overall survival in aggressive breast cancers that disproportionately impact Black women in the African Diaspora.

Temporal Association Rule Mining: Race-Based Patterns of Treatment-Adverse Events in Breast Cancer Patients Using SEER-Medicare Dataset

PURPOSE

Disparities in the screening, treatment, and survival of African American (AA) patients with breast cancer extend to adverse events experienced with systemic therapy. However, data are limited and difficult to obtain. We addressed this challenge by applying temporal association rule (TAR) mining using the SEER-Medicare dataset for differences in the association of specific adverse events (AEs) and treatments (TRs) for breast cancer between AA and White women. We considered two categories of cancer care providers and settings: practitioners providing care in the outpatient units of hospitals and institutions and private practitioners providing care in their offices.

PATIENTS AN METHODS

We considered women enrolled in the Medicare fee-for-service option at age 65 who qualified by age and not disability, who were diagnosed with breast cancer with attributed patient factors of age and race, marital status, comorbidities, prior malignancies, prior therapy, disease factors of stage, grade, and ER/PR and Her2 status and laterality. We included 141 HCPCS drug J codes for chemotherapy, biotherapy, and hormone therapy drugs, which we consolidated into 46 mechanistic categories and generated AE data. We consolidated AEs from ICD9 codes into 18 categories associated with breast cancer therapy. We applied TAR mining to determine associations between the 46 TR and 18 AE categories in the context of the patient categories outlined. We applied the spark.mllib implementation of the FPGrowth algorithm, a parallel version called PFP. We considered differences of at least one unit of lift as significant between groups. The model's results demonstrated a high overlap between the model's identified TR-AEs associated set and the actual set.

RESULTS

Our results demonstrate that specific TR/AE associations are highly dependent on race, stage, and venue of care administration.

CONCLUSIONS

Our data demonstrate the usefulness of this approach in identifying differences in the associations between TRs and AEs in different populations and serve as a reference for predicting the likelihood of AEs in different patient populations treated for breast cancer. Our novel approach using unsupervised learning enables the discovery of association rules while paying special attention to temporal information, resulting in greater predictive and descriptive power as a patient's health and life status change over time.

Association Between Polymorphisms in DNA Damage Repair Pathway Genes and Female Breast Cancer Risk

Breast cancer risk have been discussed to be associated with polymorphisms in genes as well as abnormal DNA damage repair function. This study aims to assess the relationship between genes single nucleotide polymorphisms (SNPs) related to DNA damage repair and female breast cancer risk in Chinese population. A case-control study containing 400 patients and 400 healthy controls was conducted. Genotype was identified using the sequence MassARRAY method and expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2) in tumor tissues was analyzed by immunohistochemistry assay. The results revealed that ATR rs13091637 decreased breast cancer risk influenced by ER, PR (CT/TT vs. CC: adjusted odds ratio [OR] = 1.54, 95% confidence interval [CI]: 1.04-2.27, p = 0.032; CT/TT vs. CC: adjusted OR = 1.63, 95%CI: 1.14-2.35, p = 0.008) expression. Stratified analysis revealed that PALB2 rs16940342 increased breast cancer risk in response to menstrual status (AG/GG vs. AA: adjusted OR = 1.72, 95%CI: 1.13-2.62, p = 0.011) and age of menarche (AG/GG vs. AA: adjusted OR = 1.54, 95%CI: 1.03-2.31, p = 0.037), whereas ATM rs611646 and Ku70 rs132793 were associated with reduced breast cancer risk influenced by menarche (GA/AA vs. GG: adjusted OR = 0.50, 95%CI: 0.30-0.95, p = 0.033). In a summary, PALB2 rs16940342, ATR rs13091637, ATM rs611646, and Ku70 rs132793 were associated with breast cancer risk.

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field.

SIGNIFICANCE

AI is increasingly being applied to all aspects of oncology, where several applications are maturing beyond research and development to direct clinical integration. This review summarizes the current state of the field through the lens of clinical translation along the clinical care continuum. Emerging areas are also highlighted, along with common challenges, evolving solutions, and potential future directions for the field.

Germline testing of BRCA1, BRCA2, PALB2 and CHEK2 c.1100delC in 1514 triple negative familial and isolated breast cancers from a single centre, with extended testing of ATM, RAD51C and RAD51D in over 400

BACKGROUND

The identification of germline pathogenic gene variants (PGVs) in triple negative breast cancer (TNBC) is important to inform further primary cancer risk reduction and TNBC treatment strategies. We therefore investigated the contribution of breast cancer associated PGVs to familial and isolated invasive TNBC.

METHODS

Outcomes of germline BRCA1, BRCA2 and CHEK2_c.1100delC testing were recorded in 1514 women (743-isolated, 771-familial), and for PALB2 in 846 women (541-isolated, 305-familial), with TNBC and smaller numbers for additional genes. Breast cancer free controls were identified from Predicting Risk Of Cancer At Screening and BRIDGES (Breast cancer RIsk after Diagnostic GEne Sequencing) studies.

RESULTS

BRCA1_PGVs were detected in 52 isolated (7.0%) and 195 (25.3%) familial cases (isolated-OR=58.9, 95% CI: 16.6 to 247.0), BRCA2_PGVs in 21 (2.8%) isolated and 67 (8.7%) familial cases (isolated-OR=5.0, 95% CI: 2.3 to 11.2), PALB2_PGVs in 9 (1.7%) isolated and 12 (3.9%) familial cases (isolated-OR=8.8, 95% CI: 2.5 to 30.4) and CHEK2_c.1100delC in 0 isolated and 3 (0.45%) familial cases (isolated-OR=0.0, 95% CI: 0.00 to 2.11). BRCA1_PGV detection rate was >10% for all familial TNBC age groups and significantly higher for younger diagnoses (familial: <50 years, n=165/538 (30.7%); ≥50 years, n=30/233 (12.9%); p<0.0001). Women with a G3_TNBC were more likely to have a BRCA1_PGV as compared with a BRCA2 or PALB2_PGV (p<0.0001). 0/743 isolated TNBC had the CHEK2_c.1100delC PGV and 0/305 any ATM_PGV, but 2/240 (0.83%) had a RAD51D_PGV.

CONCLUSION

PGVs in BRCA1 are associated with G3_TNBCs. Familial TNBCs and isolated TNBCs <30 years have a >10% likelihood of a PGV in BRCA1. BRCA1_PGVs are associated with younger age of familial TNBC. There was no evidence for any increased risk of TNBC with CHEK2 or ATM PGVs.

The Genetic Paradigm of Hereditary Breast and Ovarian Cancer (HBOC) in the Afro-Caribbean Population

Differences in tumor biology and genetic predisposition have been suggested as factors influencing overall survival and increased mortality in Black breast and ovarian cancer patients. Therefore, it is key to evaluate genetic susceptibilities in Afro-Caribbean patients because the black population in the US is not homogeneous. Identifying a high incidence of hereditary breast and ovarian cancer (HBOC) in Afro-Caribbean countries can lead to understanding the pattern of inherited traits in US-Caribbean immigrants and their subsequent generations. The paucity of projects studying the genetic landscape in these populations makes it difficult to design studies aimed at optimizing screening and prophylaxis strategies, which in turn, improve survival and mortality rates. This scoping review identifies and categorizes current research on the genetic paradigm of HBOC in the Afro-Caribbean population. We performed an evaluation of the evidence and generated a summary of findings according to preferred reporting items for systematic review and meta-analysis (PRISMA) Extension for Scoping Reviews guidelines. We included articles that assessed the incidence and prevalence of pathologic germline mutations and experience/barriers for genetic testing in Afro-Caribbean Countries and US-Caribbean patients. Our results highlight countries where genetic landscapes remain severely understudied and support recommending multigene testing in Caribbean-born patients. They highlight a need for further research on the genetic paradigm of HBOC in the Afro-Caribbean population to improve genetic testing/counseling and the subsequent adoption of early detection and risk reduction strategies.

Population-specific Mutation Patterns in Breast Tumors from African American, European American, and Kenyan Patients

Women of African descent have the highest breast cancer mortality in the United States and are more likely than women from other population groups to develop an aggressive disease. It remains uncertain to what extent breast cancer in Africa is reminiscent of breast cancer in African American or European American patients. Here, we performed whole-exome sequencing of genomic DNA from 191 breast tumor and non-cancerous adjacent tissue pairs obtained from 97 African American, 69 European American, 2 Asian American, and 23 Kenyan patients. Our analysis of the sequencing data revealed an elevated tumor mutational burden in both Kenyan and African American patients, when compared with European American patients. TP53 mutations were most prevalent, particularly in African American patients, followed by PIK3CA mutations, which showed similar frequencies in European American, African American, and the Kenyan patients. Mutations targeting TBX3 were confined to European Americans and those targeting the FBXW7 tumor suppressor to African American patients whereas mutations in the ARID1A gene that are known to confer resistance to endocrine therapy were distinctively enriched among Kenyan patients. A Kyoto Encyclopedia of Genes and Genomes pathway analysis could link FBXW7 mutations to an increased mitochondrial oxidative phosphorylation capacity in tumors carrying these mutations. Finally, Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures in tumors correlated with the occurrence of driver mutations, immune cell profiles, and neighborhood deprivation with associations ranging from being mostly modest to occasionally robust. To conclude, we found mutational profiles that were different between these patient groups. The differences concentrated among genes with low mutation frequencies in breast cancer.

SIGNIFICANCE

The study describes differences in tumor mutational profiles between African American, European American, and Kenyan breast cancer patients. It also investigates how these profiles may relate to the tumor immune environment and the neighborhood environment in which the patients had residence. Finally, it describes an overrepresentation of ARID1A gene mutations in breast tumors of the Kenyan patients.

Neighborhood Disadvantage, African Genetic Ancestry, Cancer Subtype, and Mortality Among Breast Cancer Survivors

Importance

Racial disparities in breast cancer (BC) survival arise from multilevel causes, which may exert influence at different stages of BC progression. Clarifying the importance of genetic and social factors could help prioritize interventions.

Objective

To jointly examine associations between African genetic ancestry, social environment, and mortality from any cause and BC in Black BC survivors.

Design, Setting, and Participants

This population-based cohort study enrolled self-identified Black women aged 20 to 75 years with histologically confirmed BC from June 2005 to May 2019 and followed them up until death or censoring in September 2021. Participants lived in 10 New Jersey counties. Data were analyzed between December 2022 and April 2023.

Exposures

A neighborhood socioeconomic status (nSES) index composed of census tract measures (education, income, wealth, employment status, and occupation) was linked to residential addresses at diagnosis. Percentage African ancestry was estimated using the ADMIXTURE program.

Main Outcomes and Measures

Sequentially adjusted (age adjusted: age and interview year; fully adjusted: age adjusted with individual SES, lifestyle factors, and comorbidities) logistic regression models were fit to estimate associations with tumor subtypes (estrogen receptor-negative [ER-] vs estrogen receptor-positive [ER+]; triple-negative breast cancer [TNBC] vs luminal A), and Cox models were fit for associations with all-cause mortality (ACM) and breast cancer-specific mortality (BCSM). Models for BCSM were fit using Fine-Gray competing risks models, and robust standard errors were used to account for census tract-level clustering.

Results

Among 1575 participants, median (IQR) African ancestry was 85% (76%-90%), and median (IQR) age was 55 (46-63) years. A 10-percentage point increase in African ancestry was associated with higher odds of ER- vs ER+ (adjusted odds ratio [aOR], 1.08; 95% CI, 0.98-1.18) and TNBC vs luminal (aOR, 1.15; 95% CI, 1.02-1.31) tumors, but not with ACM or BCSM. A 1-IQR increase in nSES was associated with lower ACM (adjusted hazard ratio [aHR], 0.76; 95% CI, 0.63-0.93), and the HR for BCSM was less than 1 but not statistically significant (aHR, 0.81; 95% CI, 0.62-1.04) in age-adjusted models, but associations attenuated following further adjustment for potential mediators (individual SES, lifestyles, comorbidities).

Conclusions and Relevance

In this cohort study of Black female BC survivors, higher African ancestry was associated with aggressive tumor subtypes. Compared with genetic ancestry, mediating pathways related to social environments may be more important for survival in these patients.

Algorithmic fairness in artificial intelligence for medicine and healthcare

In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspective, we outline fairness in machine learning through the lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation and intra-observer labelling variability, in particular) arise in clinical workflows and the resulting healthcare disparities. We also review emerging technology for mitigating biases via disentanglement, federated learning and model explainability, and their role in the development of AI-based software as a medical device.

A Focus on the Synergy of Radiomics and RNA Sequencing in Breast Cancer

Radiological imaging is currently employed as the most effective technique for screening, diagnosis, and follow up of patients with breast cancer (BC), the most common type of tumor in women worldwide. However, the introduction of the omics sciences such as metabolomics, proteomics, and molecular genomics, have optimized the therapeutic path for patients and implementing novel information parallel to the mutational asset targetable by specific clinical treatments. Parallel to the "omics" clusters, radiological imaging has been gradually employed to generate a specific omics cluster termed "radiomics". Radiomics is a novel advanced approach to imaging, extracting quantitative, and ideally, reproducible data from radiological images using sophisticated mathematical analysis, including disease-specific patterns, that could not be detected by the human eye. Along with radiomics, radiogenomics, defined as the integration of "radiology" and "genomics", is an emerging field exploring the relationship between specific features extracted from radiological images and genetic or molecular traits of a particular disease to construct adequate predictive models. Accordingly, radiological characteristics of the tissue are supposed to mimic a defined genotype and phenotype and to better explore the heterogeneity and the dynamic evolution of the tumor over the time. Despite such improvements, we are still far from achieving approved and standardized protocols in clinical practice. Nevertheless, what can we learn by this emerging multidisciplinary clinical approach? This minireview provides a focused overview on the significance of radiomics integrated by RNA sequencing in BC. We will also discuss advances and future challenges of such radiomics-based approach.

Neighborhood factors and triple negative breast cancer: The role of cumulative exposure to area-level risk factors

BACKGROUND

Despite similar incidence rates among Black and White women, breast cancer mortality rates are 40% higher among Black women. More than half of the racial difference in breast cancer mortality can be attributed to triple negative breast cancer (TNBC), an aggressive subtype of invasive breast cancer that disproportionately affects Black women. Recent research has implicated neighborhood conditions in the etiology of TNBC. This study investigated the relationship between cumulative neighborhood-level exposures and TNBC risk.

METHODS

This single-institution retrospective study was conducted on a cohort of 3316 breast cancer cases from New Castle County, Delaware (from 2012 to 2020), an area of the country with elevated TNBC rates. Cases were stratified into TNBC and "Non-TNBC" diagnosis and geocoded by residential address. Neighborhood exposures included census tract-level measures of unhealthy alcohol use, metabolic dysfunction, breastfeeding, and environmental hazards. An overall cumulative risk score was calculated based on tract-level exposures.

RESULTS

Univariate analyses showed each tract-level exposure was associated with greater TNBC odds. In multivariate analyses that controlled for patient-level race and age, tract-level exposures were not associated with TNBC odds. However, in a second multivariate model that included patient-level variables and considered tract-level risk factors as a cumulative exposure risk score, each one unit increase in cumulative exposure was significantly associated with a 10% increase in TNBC odds. Higher cumulative exposure risk scores were found in census tracts with relatively high proportions of Black residents.

CONCLUSIONS

Cumulative exposure to neighborhood-level risk factors that disproportionately affect Black communities was associated with greater TNBC risk.

African Ancestry-Associated Gene Expression Profiles in Triple-Negative Breast Cancer Underlie Altered Tumor Biology and Clinical Outcome in Women of African Descent

Women of sub-Saharan African descent have disproportionately higher incidence of triple-negative breast cancer (TNBC) and TNBC-specific mortality across all populations. Population studies show racial differences in TNBC biology, including higher prevalence of basal-like and quadruple-negative subtypes in African Americans (AA). However, previous investigations relied on self-reported race (SRR) of primarily U.S. populations. Due to heterogeneous genetic admixture and biological consequences of social determinants, the true association of African ancestry with TNBC biology is unclear. To address this, we conducted RNA sequencing on an international cohort of AAs, as well as West and East Africans with TNBC. Using comprehensive genetic ancestry estimation in this African-enriched cohort, we found expression of 613 genes associated with African ancestry and 2,000+ associated with regional African ancestry. A subset of African-associated genes also showed differences in normal breast tissue. Pathway enrichment and deconvolution of tumor cellular composition revealed that tumor-associated immunologic profiles are distinct in patients of African descent.

SIGNIFICANCE

Our comprehensive ancestry quantification process revealed that ancestry-associated gene expression profiles in TNBC include population-level distinctions in immunologic landscapes. These differences may explain some differences in race-group clinical outcomes. This study shows the first definitive link between African ancestry and the TNBC immunologic landscape, from an African-enriched international multiethnic cohort. See related commentary by Hamilton et al., p. 2496. This article is highlighted in the In This Issue feature, p. 2483.

Risk of Presenting with Poor-Prognosis Metastatic Cancer in Adolescents and Young Adults: A Population-Based Study

Having metastatic disease at diagnosis poses the great risk of death among AYAs with cancer from all sociodemographic subgroups. This “landscape” study utilized United States Surveillance, Epidemiology, and End Results Program data from 2000−2016 to identify subgroups of AYAs at highest risk for presenting with metastases across twelve cancer sites having a poor-prognosis (5-year survival <50% with metastases). Adjusted odds ratios for risk of metastatic disease presentation were compared for AYAs in aggregate and by sociodemographic subgroup (race/ethnicity, sex, socioeconomic status [SES]). In general, AYAs who were male, racial/ethnic minorities, or low SES were at consistently greatest risk of metastases. Strikingly, having metastatic melanoma was independently associated with multiple AYA sociodemographic subgroups, including males (aOR 3.11 [95% CI 2.64−3.66]), non-Hispanic Blacks (4.04 [2.32−7.04]), Asian Pacific Islanders (2.99 [1.75−5.12]), Hispanics (2.37 [1.85−3.04]), and low SES (2.30 [1.89−2.80]). Non-Hispanic Blacks were more likely to present with metastatic cancer in all sites, except for bone, rhabdomyosarcoma, and stomach. Low SES AYAs are more likely to present with metastatic melanoma, bone tumors, soft tissue sarcomas, breast, cervical, lung, and stomach carcinomas. Building on these results, future cancer-specific studies should investigate the connection between sociodemographic risk factors and biological drivers of metastases. This line of research has potential to inform targeted public health and screening efforts to facilitate risk reduction and earlier detection of these deadly diseases.

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.