A multi-tissue, splicing-based joint transcriptome-wide association study identifies susceptibility genes for breast cancer.

Splicing-based transcriptome-wide association studies (splicing-TWASs) of breast cancer have the potential to identify susceptibility genes. However, existing splicing-TWASs test the association of individual excised introns in breast tissue only and thus have limited power to detect susceptibility genes. In this study, we performed a multi-tissue joint splicing-TWAS that integrated splicing-TWAS signals of multiple excised introns in each gene across 11 tissues that are potentially relevant to breast cancer risk. We utilized summary statistics from a meta-analysis that combined genome-wide association study (GWAS) results of 424,650 women of European ancestry. Splicing-level prediction models were trained in GTEx (v.8) data. We identified 240 genes by the multi-tissue joint splicing-TWAS at the Bonferroni-corrected significance level; in the tissue-specific splicing-TWAS that combined TWAS signals of excised introns in genes in breast tissue only, we identified nine additional significant genes. Of these 249 genes, 88 genes in 62 loci have not been reported by previous TWASs, and 17 genes in seven loci are at least 1 Mb away from published GWAS index variants. By comparing the results of our splicing-TWASs with previous gene-expression-based TWASs that used the same summary statistics and expression prediction models trained in the same reference panel, we found that 110 genes in 70 loci that are identified only by the splicing-TWASs. Our results showed that for many genes, expression quantitative trait loci (eQTL) did not show a significant impact on breast cancer risk, whereas splicing quantitative trait loci (sQTL) showed a strong impact through intron excision events.

A joint transcriptome-wide association study across multiple tissues identifies candidate breast cancer susceptibility genes.

Genome-wide association studies (GWASs) have identified more than 200 genomic loci for breast cancer risk, but specific causal genes in most of these loci have not been identified. In fact, transcriptome-wide association studies (TWASs) of breast cancer performed using gene expression prediction models trained in breast tissue have yet to clearly identify most target genes. To identify candidate genes, we performed a GWAS analysis in a breast cancer dataset from UK Biobank (UKB) and combined the results with the GWAS results of the Breast Cancer Association Consortium (BCAC) by a meta-analysis. Using the summary statistics from the meta-analysis, we performed a joint TWAS analysis that combined TWAS signals from multiple tissues. We used expression prediction models trained in 11 tissues that are potentially relevant to breast cancer from the Genotype-Tissue Expression (GTEx) data. In the GWAS analysis, we identified eight loci distinct from those reported previously. In the TWAS analysis, we identified 309 genes at 108 genomic loci to be significantly associated with breast cancer at the Bonferroni threshold. Of these, 17 genes were located in eight regions that were at least 1 Mb away from published GWAS hits. The remaining TWAS-significant genes were located in 100 known genomic loci from previous GWASs of breast cancer. We found that 21 genes located in known GWAS loci remained statistically significant after conditioning on previous GWAS index variants. Our study provides insights into breast cancer genetics through mapping candidate target genes in a large proportion of known GWAS loci and discovering multiple new loci.

An enhancer variant associated with breast cancer susceptibility in Black women regulates TNFSF10 expression and antitumor immunity in triple-negative breast cancer.

Women of African ancestry have the highest mortality from triple-negative breast cancer (TNBC) of all racial groups. To understand the genomic basis of breast cancer in the populations, we previously conducted genome-wide association studies and identified single nucleotide polymorphisms (SNPs) associated with breast cancer in Black women. In this study, we investigated the functional significance of the top associated SNP rs13074711. We found the SNP served as an enhancer variant and regulated TNFSF10 (TRAIL) expression in TNBC cells, with a significant association between the SNP genotype and TNFSF10 expression in breast tumors. Mechanistically, rs13074711 modulated the binding activity of c-MYB at the motif and thereby controlled TNFSF10 expression. Interestingly, TNFSF10 expression in many cancers was consistently lower in African Americans compared with European Americans. Furthermore, TNFSF10 expression in TNBC was significantly correlated with the expression of antiviral immune genes and was regulated by type I interferons (IFNs). Accordingly, loss of TNFSF10 resulted in a profound decrease in apoptosis of TNBC cells in response to type I IFNs and poly(I:C), a synthetic analogue of double stranded virus. Lastly, in a syngeneic mouse model of breast cancer, TNFSF10-deficiency in breast tumors decreased tumor-infiltrated CD4+ and CD8+ T cell quantities. Collectively, our results suggested that TNFSF10 plays an important role in the regulation of antiviral immune responses in TNBC, and the expression is in part regulated by a genetic variant associated with breast cancer in Black women. Our results underscore the important contributions of genetic variants to immune defense mechanisms.

Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach.

BACKGROUND: For patients with breast cancer undergoing neoadjuvant chemotherapy (NACT), most of the existing prediction models of pathologic complete response (pCR) using clinicopathological features were based on standard statistical models like logistic regression, while models based on machine learning mostly utilized imaging data and/or gene expression data. This study aims to develop a robust and accessible machine learning model to predict pCR using clinicopathological features alone, which can be used to facilitate clinical decision-making in diverse settings. METHODS: The model was developed and validated within the National Cancer Data Base (NCDB, 2018-2020) and an external cohort at the University of Chicago (2010-2020). We compared logistic regression and machine learning models, and examined whether incorporating quantitative clinicopathological features improved model performance. Decision curve analysis was conducted to assess the model's clinical utility. RESULTS: We identified 56,209 NCDB patients receiving NACT (pCR rate: 34.0%). The machine learning model incorporating quantitative clinicopathological features showed the best discrimination performance among all the fitted models [area under the receiver operating characteristic curve (AUC): 0.785, 95% confidence interval (CI): 0.778-0.792], along with outstanding calibration performance. The model performed best among patients with hormone receptor positive/human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer (AUC: 0.817, 95% CI: 0.802-0.832); and by adopting a 7% prediction threshold, the model achieved 90.5% sensitivity and 48.8% specificity, with decision curve analysis finding a 23.1% net reduction in chemotherapy use. In the external testing set of 584 patients (pCR rate: 33.4%), the model maintained robust performance both overall (AUC: 0.711, 95% CI: 0.668-0.753) and in the HR+/HER2- subgroup (AUC: 0.810, 95% CI: 0.742-0.878). CONCLUSIONS: The study developed a machine learning model ( https://huolab.cri.uchicago.edu/sample-apps/pcrmodel ) to predict pCR in breast cancer patients undergoing NACT that demonstrated robust discrimination and calibration performance. The model performed particularly well among patients with HR+/HER2- breast cancer, having the potential to identify patients who are less likely to achieve pCR and can consider alternative treatment strategies over chemotherapy. The model can also serve as a robust baseline model that can be integrated with smaller datasets containing additional granular features in future research.

Validation of the RSClin risk calculator in the National Cancer Data Base.

BACKGROUND: Guidelines recommend the use of genomic assays such as OncotypeDx to aid in decisions regarding the use of chemotherapy for hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. The RSClin prognostic tool integrates OncotypeDx and clinicopathologic features to predict distant recurrence and chemotherapy benefit, but further validation is needed before broad clinical adoption. METHODS: This study included patients from the National Cancer Data Base (NCDB) who were diagnosed with stage I-III HR+/HER2- breast cancer from 2010 to 2020 and received adjuvant endocrine therapy with or without chemotherapy. RSClin-predicted chemotherapy benefit was stratified into low (<3% reduction in distant recurrence), intermediate (3%-5%), and high (>5%). Cox models were used to model mortality adjusted for age, comorbidity index, insurance, and race/ethnicity. RESULTS: A total of 285,441 patients were identified for inclusion from the NCDB, with an average age of 60 years and a median follow-up of 58 months. Chemotherapy was associated with improved overall survival only for those predicted to have intermediate (adjusted hazard ratio [aHR], 0.68; 95% confidence interval [CI], 0.60-0.79) and high benefit per RSClin (aHR, 0.66; 95% CI, 0.61-0.72). Consistent benefit was seen in the subset with a low OncotypeDx score (<26) and intermediate (aHR, 0.66; 95% CI, 0.53-0.82) or high (aHR, 0.71; 95% CI, 0.58-0.86) RSClin-predicted benefit. No survival benefit with chemotherapy was seen in patients with a high OncotypeDx score (≥26) and low benefit per RSClin (aHR, 1.70; 95% CI, 0.41-6.99). CONCLUSIONS: RSClin may identify high-risk patients who benefit from treatment intensification more accurately than OncotypeDx, and further prospective study is needed.

Racial differences in familiarity, interest, and use of integrative medicine among patients with breast cancer.

PURPOSE: Integrative medicine (IM) has received the American Society of Clinical Oncology's endorsement for managing cancer treatment-related side effects. Little is known about racial differences in familiarity, interest, and use of IM among patients with breast cancer. METHODS: Patients with breast cancer enrolled in the Chicago Multiethnic Epidemiologic Breast Cancer Cohort were surveyed regarding familiarity, interest, and use of acupuncture, massage, meditation, music therapy, and yoga. Familiarity and interest, measured by a 5-point Likert scale, was modeled using proportional odds. Use was self-reported, and modeled using binary logistic regression. RESULTS: Of 1,300 respondents (71.4% White and 21.9% Black), Black patients were less likely than White patients to be familiar with acupuncture (aOR 0.60, 95% CI 0.41-0.87); there were no racial differences in familiarity with massage, meditation, music therapy, and yoga. While there were no differences in interest in acupuncture between Black and White patients (aOR 1.12, 95% CI 0.76-1.65), Black patients were more interested in massage (aOR 1.86, 95% CI 1.25-2.77), meditation (aOR 2.03, 95% CI 1.37-3.00), music therapy (aOR 2.68, 95% CI 1.80-3.99), and yoga (aOR 2.10, 95% CI 1.41-3.12). Black patients were less likely than White patients to have used acupuncture (aOR 0.49, 95% CI 0.29-0.84); but there were no racial differences in use of massage, meditation, music therapy, and yoga. CONCLUSION: Black patients expressed more interest in IM than their White counterparts; there were no racial differences in IM use, except lower acupuncture use among Black patients. A breast program focused on equity should provide access to these services for patients with breast cancer.

Benign breast disease and breast cancer risk in African women: a case-control study.

PURPOSE: To examine the association between benign breast disease (BBD) and breast cancer (BC) in a heterogeneous population of African women. METHODS: BC cases and controls were enrolled in three sub-Saharan African countries, Nigeria, Cameroon, and Uganda, between 1998 and 2018. Multivariable logistic regression was used to test the association between BBD and BC. Risk factors dually associated with BBD and BC were selected. Using a parametric mediation analysis model, we assessed if selected BC risk factors were mediated by BBD. RESULTS: Of 6,274 participants, 55.6% (3,478) were breast cancer cases. 360 (5.7%) self-reported BBD. Fibroadenoma (46.8%) was the most commonly reported BBD. Women with a self-reported history of BBD had greater odds of developing BC than those without (adjusted odds ratio [aOR] 1.47, 95% CI 1.13-1.91). Biopsy-confirmed BBD was associated with BC (aOR 2.25, 95% CI 1.26-4.02). BBD did not significantly mediate the effects of any of the selected BC risk factors. CONCLUSIONS: In this study, BBD was associated with BC and did not significantly mediate the effects of selected BC risk factors.

Validation of a clinical breast cancer risk assessment tool combining a polygenic score for all ancestries with traditional risk factors.

PURPOSE: We previously described a combined risk score (CRS) that integrates a multiple-ancestry polygenic risk score (MA-PRS) with the Tyrer-Cuzick (TC) model to assess breast cancer (BC) risk. Here, we present a longitudinal validation of CRS in a real-world cohort. METHODS: This study included 130,058 patients referred for hereditary cancer genetic testing and negative for germline pathogenic variants in BC-associated genes. Data were obtained by linking genetic test results to medical claims (median follow-up 12.1 months). CRS calibration was evaluated by the ratio of observed to expected BCs. RESULTS: Three hundred forty BCs were observed over 148,349 patient-years. CRS was well-calibrated and demonstrated superior calibration compared with TC in high-risk deciles. MA-PRS alone had greater discriminatory accuracy than TC, and CRS had approximately 2-fold greater discriminatory accuracy than MA-PRS or TC. Among those classified as high risk by TC, 32.6% were low risk by CRS, and of those classified as low risk by TC, 4.3% were high risk by CRS. In cases where CRS and TC classifications disagreed, CRS was more accurate in predicting incident BC. CONCLUSION: CRS was well-calibrated and significantly improved BC risk stratification. Short-term follow-up suggests that clinical implementation of CRS should improve outcomes for patients of all ancestries through personalized risk-based screening and prevention.

Racial/Ethnic Disparities in Telemedicine Utilization and Satisfaction Among Breast Cancer Patients During the COVID-19 Pandemic: A Mixed-Methods Analysis.

Background: Telemedicine has expanded rapidly during the COVID-19 pandemic. Data on telemedicine utilization are lacking, and racial/ethnic disparities in utilization and satisfaction are unknown among breast cancer patients. Methods: This was a longitudinal study, with two surveys conducted in 2020 and 2021, among patients enrolled in the Chicago Multiethnic Epidemiologic Breast Cancer Cohort. Telemedicine utilization was modeled using mixed-effects logistic regression. Telemedicine satisfaction, assessed using a 5-point Likert scale, was modeled using mixed-effects proportional odds regression. Qualitative data on satisfaction were coded and analyzed using grounded theory. Results: Of 1,721 respondents, most (70.3%) were White, followed by 23.6% Black, 3.1% Asian, and 3.0% Hispanic. The median duration from breast cancer diagnosis to survey was 5.5 years (interquartile range: 2.7-9.4). In 2020, 59.2% reported telemedicine use; in 2021, 64.9% did, with a statistically significant increase (p < 0.001). Black patients had greater odds of telemedicine use than White patients (adjusted odds ratio [AOR] = 1.55, 95% confidence interval [CI]: 1.17-2.05). In 2020, 90.3% reported somewhat-to-extreme satisfaction; in 2021, 91.2% did, with a statistically significant, although clinically small, increase (p = 0.038). There were no racial/ethnic differences in telemedicine satisfaction between Black (AOR = 1.05, 95% CI: 0.81-1.35), Asian (AOR = 0.63, 95% CI: 0.34-1.16), or Hispanic (AOR = 0.63, 95% CI: 0.33-1.21) and White patients. Major themes emerged from the respondents that explained their levels of satisfaction were convenience, safety, specialty dependence, and technical issues. Conclusions: Telemedicine utilization and satisfaction were high among breast cancer patients over time and across races/ethnicities. Telemedicine could have great potential in reducing barriers to care and promoting health equity for breast cancer patients. However, patients' perceived challenges in accessing high-quality virtual care should be addressed.

Molecular profiling of a real-world breast cancer cohort with genetically inferred ancestries reveals actionable tumor biology differences between European ancestry and African ancestry patient populations.

BACKGROUND: Endocrine-resistant HR+/HER2- breast cancer (BC) and triple-negative BC (TNBC) are of interest for molecularly informed treatment due to their aggressive natures and limited treatment profiles. Patients of African Ancestry (AA) experience higher rates of TNBC and mortality than European Ancestry (EA) patients, despite lower overall BC incidence. Here, we compare the molecular landscapes of AA and EA patients with HR+/HER2- BC and TNBC in a real-world cohort to promote equity in precision oncology by illuminating the heterogeneity of potentially druggable genomic and transcriptomic pathways. METHODS: De-identified records from patients with TNBC or HR+/HER2- BC in the Tempus Database were randomly selected (N = 5000), with most having stage IV disease. Mutations, gene expression, and transcriptional signatures were evaluated from next-generation sequencing data. Genetic ancestry was estimated from DNA-seq. Differences in mutational prevalence, gene expression, and transcriptional signatures between AA and EA were compared. EA patients were used as the reference population for log fold-changes (logFC) in expression. RESULTS: After applying inclusion criteria, 3433 samples were evaluated (n = 623 AA and n = 2810 EA). Observed patterns of dysregulated pathways demonstrated significant heterogeneity among the two groups. Notably, PIK3CA mutations were significantly lower in AA HR+/HER2- tumors (AA = 34% vs. EA = 42%, P < 0.05) and the overall cohort (AA = 28% vs. EA = 37%, P = 2.08e-05). Conversely, KMT2C mutation was significantly more frequent in AA than EA TNBC (23% vs. 12%, P < 0.05) and HR+/HER2- (24% vs. 15%, P = 3e-03) tumors. Across all subtypes and stages, over 8000 genes were differentially expressed between the two ancestral groups including RPL10 (logFC = 2.26, P = 1.70e-162), HSPA1A (logFC = - 2.73, P = 2.43e-49), ATRX (logFC = - 1.93, P = 5.89e-83), and NUTM2F (logFC = 2.28, P = 3.22e-196). Ten differentially expressed gene sets were identified among stage IV HR+/HER2- tumors, of which four were considered relevant to BC treatment and were significantly enriched in EA: ERBB2_UP.V1_UP (P = 3.95e-06), LTE2_UP.V1_UP (P = 2.90e-05), HALLMARK_FATTY_ACID_METABOLISM (P = 0.0073), and HALLMARK_ANDROGEN_RESPONSE (P = 0.0074). CONCLUSIONS: We observed significant differences in mutational spectra, gene expression, and relevant transcriptional signatures between patients with genetically determined African and European ancestries, particularly within the HR+/HER2- BC and TNBC subtypes. These findings could guide future development of treatment strategies by providing opportunities for biomarker-informed research and, ultimately, clinical decisions for precision oncology care in diverse populations.

The risks of cancer in older women with BRCA pathogenic variants: How far have we come?

BACKGROUND: The purpose of this study was to estimate the cumulative risks of all cancers in women from 50 to 75 years of age with a BRCA1 or BRCA2 pathogenic variant. METHODS: Participants were women with BRCA1 or BRCA2 pathogenic variants from 85 centers in 16 countries. Women were eligible if they had no cancer before the age of 50 years. Participants completed a baseline questionnaire and follow-up questionnaires every 2 years. Women were followed from age 50 until a diagnosis of cancer, death, age 75, or last follow-up. The risk of all cancers combined from age 50 to 75 was estimated using the Kaplan-Meier method. RESULTS: There were 2211 women included (1470 BRCA1 and 742 BRCA2). There were 379 cancers diagnosed in the cohort between 50 and 75 years. The actuarial risk of any cancer from age 50 to 75 was 49% for BRCA1 and 43% for BRCA2. Breast (n = 186) and ovarian (n = 45) were the most frequent cancers observed. For women who had both risk-reducing mastectomy and bilateral salpingo-oophorectomy before age 50, the risk of developing any cancer between age 50 and 75 was 9%. CONCLUSION: Women with a BRCA1 or BRCA2 pathogenic variant have a high risk of cancer between the ages of 50 and 75 years and should be counselled appropriately.

A metabolome-wide case-control study of african american breast cancer patients.

BACKGROUND: Breast cancer survivors face long-term sequelae compared to the general population, suggesting altered metabolic profiles after breast cancer. We used metabolomics approaches to investigate the metabolic differences between breast cancer patients and women in the general population, aiming to elaborate metabolic changes among breast cancer patients and identify potential targets for clinical interventions to mitigate long-term sequelae. METHODS: Serum samples were retrieved from 125 breast cancer cases recruited from the Chicago Multiethnic Epidemiologic Breast Cancer Cohort (ChiMEC), and 125 healthy controls selected from Chicago Multiethnic Prevention and Surveillance Study (COMPASS). We used liquid chromatography-high resolution mass spectrometry to obtain untargeted metabolic profiles and partial least squares discriminant analysis (PLS-DA) combined with fold change to select metabolic features associated with breast cancer. Pathway analyses were conducted using Mummichog to identify differentially enriched metabolic pathways among cancer patients. As potential confounders we included age, marital status, tobacco smoking, alcohol drinking, type 2 diabetes, and area deprivation index in our model. Random effects of residence for intercept was also included in the model. We further conducted subgroup analysis by treatment timing (chemotherapy/radiotherapy/surgery), lymph node status, and cancer stages. RESULTS: The entire study participants were African American. The average ages were 57.1 for cases and 58.0 for controls. We extracted 15,829 features in total, among which 507 features were eventually selected by our criteria. Pathway enrichment analysis of these 507 features identified three differentially enriched metabolic pathways related to prostaglandin, leukotriene, and glycerophospholipid. The three pathways demonstrated inconsistent patterns. Metabolic features in the prostaglandin and leukotriene pathways exhibited increased abundances among cancer patients. In contrast, metabolic intensity in the glycerolphospholipid pathway was deregulated among cancer patients. Subgroup analysis yielded consistent results. However, changes in these pathways were strengthened when only using cases with positive lymph nodes, and attenuated when only using cases with stage I disease. CONCLUSION: Breast cancer in African American women is associated with increase in serum metabolites involved in prostaglandin and leukotriene pathways, but with decrease in serum metabolites in glycerolphospholipid pathway. Positive lymph nodes and advanced cancer stage may strengthen changes in these pathways.

Adapting a Medical School Cancer Research Education Program to the Virtual Environment: a Mixed-Methods Study.

With cancer incidence increasing worldwide, physicians with cancer research training are needed. The Scholars in Oncology-Associated Research (SOAR) cancer research education program was developed to train medical students in cancer research while exposing them to the breadth of clinical oncology. Due to the COVID-19 pandemic, SOAR transitioned from in-person in 2019 to virtual in 2020 and hybrid in 2021. This study investigates positive and negative aspects of the varying educational formats. A mixed-methods approach was used to evaluate the educational formats. Pre- and post-surveys were collected from participants to assess their understanding of cancer as a clinical and research discipline. Structured interviews were conducted across all three cohorts, and thematic analysis was used to generate themes. A total of 37 students participated in SOAR and completed surveys (2019 n = 11, 2020 n = 14, and 2021 n = 12), and 18 interviews were conducted. Understanding of oncology as a clinical (p < 0.01 for all) and research discipline (p < 0.01 for all) improved within all three cohorts. There was no difference between each cohort's improvement in research understanding (p = 0.6). There was no difference between each cohort's understanding of oncology-related disciplines as both clinical and research disciplines (p > 0.1 for all). Thematic analysis demonstrated that hybrid and in-person formats were favored over a completely virtual one. Our findings demonstrate that a medical student cancer research education program is effective using in-person or hybrid formats for research education, although virtual experiences may be suboptimal to learning about clinical oncology.

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.

Mutational spectrum of breast cancer susceptibility genes among women ascertained in a cancer risk clinic in Northeast Brazil.

PURPOSE: There is a paucity of data on the spectrum and prevalence of pathogenic variants among women of African ancestry in the Northeast region of Brazil. METHODS: We performed BROCA panel sequencing to identify inherited loss-of-function variants in breast cancer susceptibility genes among 292 Brazilian women referred to a single institution cancer risk assessment program. RESULTS: The study included a convenient cohort of 173 women with invasive breast cancer (cases) and 119 women who were cancer-free at the time of ascertainment. The majority of the women self-reported as African-descended (67% for cases and 90.8% for unaffected volunteers). Thirty-seven pathogenic variants were found in 36 (20.8%) patients. While the spectrum of pathogenic variants was heterogeneous, the majority (70.3%) of the pathogenic variants were detected in high-risk genes BRCA1, BRCA2, PALB2, and TP53. Pathogenic variants were also found in the ATM, BARD1, BRIP1, FAM175A, FANCM, NBN, and SLX4 genes in 6.4% of the affected women. Four recurrent pathogenic variants were detected in 11 patients of African ancestry. Only one unaffected woman had a pathogenic variant in the RAD51C gene. Different risk assessment models examined performed well in predicting risk of carrying germline loss-of-function variants in BRCA1 and/or BRCA2 in breast cancer cases. CONCLUSION: The high prevalence and heterogenous spectrum of pathogenic variants identified among self-reported African descendants in Northeast Brazil is consistent with studies in other African ancestry populations with a high burden of aggressive young onset breast cancer. It underscores the need to integrate comprehensive cancer risk assessment and genomic testing in the management of newly diagnosed Black women with breast cancer across the African Diaspora, enabling improved cancer control in admixed underserved and understudied populations.

Breast cancer among African American and sub-Saharan African women: a tale of global inequities.

Breast Cancer is the most common female cancer worldwide with significant global disparities, particularly disadvantaging women of African Ancestry. Though the United States and Sub-Saharan Africa are seemingly very different settings, there are many important parallels between the experience of getting diagnosed and treated for breast cancer in these two geographic regions for women of African ancestry. This commentary explores the parallels and differences and proposes an agenda to move forward to narrow the disparities gaps for some of the worlds most vulnerable women.

A perfect storm: How tumor biology, genomics, and health care delivery patterns collide to create a racial survival disparity in breast cancer and proposed interventions for change.

It is well known that there is a significant racial divide in breast cancer incidence and mortality rates. African American women are less likely to be diagnosed with breast cancer than white women but are more likely to die from it. This review explores the factors that may contribute to the racial survival disparity. Consideration is paid to what is known about the role of differences in tumor biology, genomics, cancer screening, and quality of cancer care. It is argued that it is the collision of 2 forces, tumor biology and genomics, with patterns of care that leads to the breast cancer mortality gap. The delays, misuse, and underuse of treatment for African American patients are of increased significance when these patients are presenting with more aggressive forms of breast cancer. In the current climate of health care reform ushered in by the Affordable Care Act, this article also evaluates interventions to close the disparity gap. Prior interventions have been too narrowly focused on the patient rather than addressing the system and improving care across the continuum of breast cancer evaluation and treatment. Lastly, areas of future investigation and policy initiatives aimed at reducing the racial survival disparity in breast cancer are discussed.

Impact of post-diagnosis weight change on survival outcomes in Black and White breast cancer patients.

PURPOSE: To evaluate weight change patterns over time following the diagnosis of breast cancer and to examine the association of post-diagnosis weight change and survival outcomes in Black and White patients. METHODS: The study included 2888 women diagnosed with non-metastatic breast cancer in 2000-2017 in Chicago. Longitudinal repeated measures of weight and height were collected, along with a questionnaire survey including questions on body size. Multilevel mixed-effects models were used to examine changes in body mass index (BMI). Delayed entry Cox proportional hazards models were used to investigate the impacts of changing slope of BMI on survival outcomes. RESULTS: At diagnosis, most patients were overweight or obese with a mean BMI of 27.5 kg/m2 and 31.5 kg/m2 for Blacks and Whites, respectively. Notably, about 45% of the patients had cachexia before death and substantial weight loss started about 30 months before death. In multivariable-adjusted analyses, compared to stable weight, BMI loss (> 0.5 kg/m2/year) showed greater than 2-fold increased risk in overall survival (hazard ratio [HR] = 2.60, 95% CI 1.88-3.59), breast cancer-specific survival (HR = 3.05, 95% CI 1.91-4.86), and disease-free survival (HR = 2.12, 95% CI 1.52-2.96). The associations were not modified by race, age at diagnosis, and pre-diagnostic weight. BMI gain (> 0.5 kg/m2/year) was also related to worse survival, but the effect was weak (HR = 1.60, 95% CI 1.10-2.33 for overall survival). CONCLUSION: BMI loss is a strong predictor of worse breast cancer outcomes. Growing prevalence of obesity may hide diagnosis of cancer cachexia, which can occur in a large proportion of breast cancer patients long before death.