Comparison of Breast Cancer Molecular Features and Survival by African and European Ancestry in The Cancer Genome Atlas

Automatic Segmentation and Molecular Subtype Classification of Breast Cancer Using an MRI-based Deep Learning Framework

Purpose To build a deep learning framework using contrast-enhanced MRI for lesion segmentation and automatic molecular subtype classification in breast cancer. Materials and Methods This retrospective multicenter study included patients with biopsy-proven invasive breast cancer between January 2015 and January 2021. An automatic breast lesion segmentation model was developed using three-dimensional (3D) ResU-Net as the backbone, and its accuracy was evaluated in an internal and two external testing datasets using the Dice score. An ensemble model for classification of breast cancer into four molecular subtypes (Ensemble ResNet) was then developed by combining both two-dimensional and 3D lesion features. The performance of Ensemble ResNet was evaluated in the three testing datasets using the area under the receiver operating characteristic curve (AUC). Results A total of 687 female patients (mean age ± SD, 48.70 years ± 8.97) were included, with 289, 61, 73, and 264 patients included in the training, internal testing, and two external testing datasets, respectively. The proposed segmentation model achieved high accuracy in internal testing dataset 1, external testing dataset 2, and external testing dataset 3 (Dice scores: 0.86, 0.82, 0.85) and luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, and triple-negative breast cancer (TNBC) subtypes (Dice scores: 0.8571, 0.8323, 0.8199, 0.8481). Ensemble ResNet demonstrated high performance for the prediction of luminal A subtypes (AUC range, 0.74-0.84), luminal B subtypes (AUC range, 0.68-0.72), HER2-enriched subtypes (AUC range, 0.73-0.82), and TNBC (AUC range, 0.80-0.81) in the three testing datasets. Conclusion The proposed novel deep learning framework based on MRI achieved high, robust performance in fully automatic classification of breast cancer molecular subtypes. Keywords: MR-Imaging, Breast, Oncology, Breast Cancer, Molecular Subtype, Deep Learning Framework Supplemental material is available for this article. © RSNA, 2025.

Genomic Analysis Reveals Racial and Age-Related Differences in the Somatic Landscape of Breast Cancer and the Association with Socioeconomic Factors

Cancer genomics consortia have identified somatic drivers of breast cancer subtypes. However, these studies have predominantly included older, non-Black women, and the related socioeconomic status (SES) data are limited. Increased representation and depth of social data are crucial for understanding how health inequity is intertwined with somatic landscapes. Here, we conducted targeted sequencing on primary tumors from the Carolina Breast Cancer Study (N = 357; 52% Black; 47% <50) and compared the results with The Cancer Genome Atlas (N = 948; 18% Black; 27% <50). Race (Black vs. non-Black), age, and SES were evaluated in association with mutations, copy number alterations, and aneuploidy using generalized linear models. Pathway dysfunction was also assessed by aggregating mutation and copy number alterations. Adjusting for age, Black participants (N = 350) were significantly more likely to have TP53 and FAT1 mutations and less likely to have PIK3CA, CDH1, DDR2, and GATA3 mutations than non-Black participants. Younger participants had more GATA3 alterations and fewer KMT2C, PTEN, MAP3K1, and CDH1 alterations. Black participants had significant enrichment for MYC (8q) and PIK3CA (3q26) amplifications and higher total aneuploidy, but age was not associated with copy number variation. SES was associated with different patterns of alteration in Black versus non-Black women. Overall, Black participants showed modest differences in TP53, PIK3CA, and other alterations that further varied by SES. Race is a social construct, and varying distributions of etiologic factors across social strata may predispose Black, young, and low SES women to cancer subtypes characterized by these alterations. Significance: The collection and analysis of DNA sequencing with comprehensive socioeconomic factor associations in a large Black breast cancer patient cohort could help uncover mechanisms by which social conditions contribute to tumor biology.

Inference of genetic ancestry from a multi-gene cancer panel in Colombian women with cancer

INTRODUCTION

Cancer health disparities among racial and ethnic populations significantly burden health systems due to unequal access to early detection, treatment, and healthcare resources. These disparities lead to worse outcomes and increased costs from delayed diagnoses, advanced treatments, and prolonged care. Genetic differences can also influence cancer susceptibility and treatment response, thus analyzing genetic ancestry is essential for uncovering genetic factors that may contribute to these disparities. Utilizing data from clinical multigene cancer panels to infer genetic ancestry offers a valuable approach to understand population structure and the impact of individual ancestries in development of complex diseases.

AIM

To evaluate the accuracy of global ancestry inference using genetic markers from the TruSight™ Hereditary Cancer Panel, which was used to investigate hereditary cancer syndromes in a cohort of 116 female cancer patients at the Colombian National Cancer Institute. Additionally, to compare these results with genetic ancestry estimations from traditional genome-wide markers.

RESULTS

Our results demonstrate a strong correlation between global genetic ancestry inferred with markers captured from TruSightTM panel (4785 markers) and Whole Genome Sequencing (WGS, 8 million markers in admixed populations. The correlation values were 0.96 (p < 0.0001) for the Native American and European ancestry components, and 0.99 (p < 0.0001) for the African ancestry fraction. Genetic ancestry mean proportions in the Colombian cohort were 45.7%, 46.2%, and 8.11% for the European, the Native American, and the African components, respectively.

CONCLUSION

This study demonstrates the accuracy of ancestry inference from clinical panel data offering a promising approach for understanding cancer health disparities in admixed populations.

Understanding Susceptibility to Breast Cancer: From Risk Factors to Prevention Strategies

Breast cancer is the most common malignancy among women globally, with incidence rates continuing to rise. A comprehensive understanding of its risk factors and the underlying biological mechanisms that drive tumor initiation is essential for developing effective prevention strategies. This review examines key non-modifiable risk factors, such as genetic predisposition, demographic characteristics, family history, mammographic density, and reproductive milestones, as well as modifiable risk factors like exogenous hormone exposure, obesity, diet, and physical inactivity. Importantly, reproductive history plays a dual role, providing long-term protection while temporarily increasing breast cancer risk shortly after pregnancy. Current chemoprevention strategies primarily depend on selective estrogen receptor modulators (SERMs), including tamoxifen and raloxifene, which have demonstrated efficacy in reducing the incidence of estrogen receptor-positive breast cancer but remain underutilized due to adverse effects. Emerging approaches such as aromatase inhibitors, RANKL inhibitors, progesterone antagonists, PI3K inhibitors, and immunoprevention strategies show promise for expanding preventive options. Understanding the interactions between risk factors, hormonal influences, and tumorigenesis is critical for optimizing breast cancer prevention and advancing safer, more targeted chemopreventive interventions.

A Portrait of Breast Cancer in Portugal: The Impact of Racial Disparities

Background Breast cancer is the most common malignancy among women, with racial disparities in diagnosis, tumor characteristics and outcomes. Black women are disproportionately affected by aggressive subtypes and advanced stage disease, influenced by biological, socioeconomic, and healthcare access factors. While these disparities are well-documented globally, their impact in Portugal remains unknown. The Portuguese healthcare system ensures equal access, including for patients from African Portuguese-speaking countries (PALOPs), who face additional challenges due to the medical evacuation process. This study aims to evaluate differences in breast cancer characteristics and treatment delays between black and white women treated at a Portuguese center. Materials and methods A unicentric, retrospective observational study was conducted at a Portuguese center, including 208 women with breast cancer treated between 2022 and 2023. Patients were categorized as black or white, and data were collected on demographic variables, tumor characteristics, stage at diagnosis, and time from symptom onset to treatment initiation. Logistic regression was used to assess the association between the race and breast cancer characteristics. Statistical analyses included Kaplan-Meier survival estimates and Cox proportional hazards models to evaluate survival differences. Results Of the 208 patients, 60 were black and 148 were white. The median age at diagnosis was lower for black women (50 years) compared to white women (64 years). Black women were more likely to be diagnosed at stage III or IV (55% vs. 16.2%, p<0.001). Regarding tumor characteristics, black women had a significantly higher prevalence of grade 3 tumors (30% vs. 12.8%, p=0.005), triple-negative breast cancer (TNBC) (31.7% vs. 11.5%, p<0.001) and lower rates of hormone receptor-positive tumors (58.3% vs. 82.4%, p<0.001). No statistically significant difference was found in HER2 expression between groups. The time from symptom onset to treatment initiation was longer for black women (8.5 months vs. 5 months, p<0.001). However, multiple linear regression indicated that being from a PALOP country, was the main predictor of treatment delays (p=0.013), while race alone was not significant (p=0.341). Overall survival analysis was not feasible. Discussion The findings of this study showed significant disparities in breast cancer between black and white women. Black women were younger at diagnosis, more frequently presented with advanced stage and aggressive subtypes, and experienced longer treatment delays. The longer time from symptom onset to treatment initiation in black women suggests potential barriers to timely healthcare access, including socioeconomic factors and healthcare system navigation challenges. Further analysis suggests that these delays are primarily driven by patients from PALOPs rather than race itself. These patients face additional systemic barriers, including delays in the medical evacuation process and socioeconomic challenges. Conclusion This study highlights the need to address racial disparities in breast cancer care in Portugal. Targeted interventions, policy changes, and improved access to timely care are essential to reducing disparities and improving outcomes.

Genetic Ancestry and 21-Gene Oncotype DX Breast Cancer Recurrence Scores

BACKGROUND

Racial and ethnic breast cancer disparities persist. This may be reflected by differences in Oncotype DX recurrence scores (RS), which are higher for Black women. This study assesses the association between ancestry and RS.

METHODS

Stage I-III hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients with ancestry and RS data were prospectively identified from 2017 to 2021. RS were grouped into low, intermediate, and high categories. Multinomial regression determined the association between ancestry and RS controlling for ancestry and estrogen receptor (ER), progesterone receptor (PR), and HER2 expression.

RESULTS

Of 174 patients, 28 (16.1%) self-identified as non-Hispanic White, 107 (61.5%) self-identified as Hispanic White, 19 (10.9%) self-identified as non-Hispanic Black, and 9 (5.2%) self-identified as Hispanic Black. Ninety-four (54.0%) patients had low RS, 51 (29.3%) had intermediate RS, and 29 (16.7%) had high RS. On multivariable analyses, West African ancestry was associated with increased odds of intermediate (odds ratio [OR] 1.02, 95% confidence interval [CI] 1.00-1.04, p = 0.039) and high (OR 1.03, 95% CI 1.00-1.06, p = 0.022) RS. East Asian ancestry was associated with decreased odds of intermediate RS (OR 0.78, 95% CI 0.60-1.00, p = 0.048). Increasing ER (OR 0.43, 95% CI 0.23-0.82, p = 0.011), PR (OR 0.20, 95% CI 0.11-0.34, p < 0.001), and HER2 (OR 0.24, 95% CI 0.09-0.63, p = 0.004) expression were associated with lower odds of high RS.

CONCLUSION

Increasing West African ancestry is associated with increased odds of high and intermediate RS, while increasing East Asian ancestry is associated with lower odds of intermediate RS. These findings require validation but suggest ancestry may represent a biological biomarker and that assays guiding adjuvant therapy may require ancestry-based calibration in HR+/HER2- tumors.

Defining hypoxia in cancer: A landmark evaluation of hypoxia gene expression signatures

Tumor hypoxia drives metabolic shifts, cancer progression, and therapeutic resistance. Challenges in quantifying hypoxia have hindered the exploitation of this potential "Achilles' heel." While gene expression signatures have shown promise as surrogate measures of hypoxia, signature usage is heterogeneous and debated. Here, we present a systematic pan-cancer evaluation of 70 hypoxia signatures and 14 summary scores in 104 cell lines and 5,407 tumor samples using 472 million length-matched random gene signatures. Signature and score choice strongly influenced the prediction of hypoxia in vitro and in vivo. In cell lines, the Tardon signature was highly accurate in both bulk and single-cell data (94% accuracy, interquartile mean). In tumors, the Buffa and Ragnum signatures demonstrated superior performance, with Buffa/mean and Ragnum/interquartile mean emerging as the most promising for prospective clinical trials. This work delivers recommendations for experimental hypoxia detection and patient stratification for hypoxia-targeting therapies, alongside a generalizable framework for signature evaluation.

A qualitative study of Black breast cancer previvors' and survivors' experiences after positive genetic testing

Black women have a disproportionately high mortality rate from breast cancer, which is likely influenced by an intersection of environmental, cultural, economic, and social factors. Few published studies capture the experiences of Black women after a genetic diagnosis associated with increased risk for breast cancer. This study aims to explore the perspectives and experiences of Black women who carry a pathogenic variant associated with increased breast cancer risk and identify barriers to care for this population. We conducted semi-structured interviews with 16 participants with and without histories of breast cancer. The sample included representation across a range of demographic groups (e.g., income level, employment status, insurance status, and education level). Reflexive thematic analysis was the methodology used to analyze data. Five major themes emerged from participants' descriptions of their experiences during and after genetic testing: (1) searching for representation; (2) information enabling agency; (3) healthcare providers as facilitators or barriers to care; (4) self-identity impacting disclosure; and (5) evolving mental health and coping strategies. Participants identified barriers to care including challenging or misinformed healthcare providers, medical racism, and a lack of Black representation in the cancer community. This work deepens our understanding of the nuanced experiences of Black women across the continuum of cancer care, illustrates unmet needs, and provides a foundation for future research that includes the perspectives of Black women.

CRYβB2 alters cell adhesion to promote invasion in a triple-negative breast cancer cell line

OBJECTIVE

African American women with breast cancer experience disproportionately poor survival outcomes, primarily due to the high prevalence of the deadliest subtype; triple-negative breast cancer (TNBC). The CRYβB2 gene is upregulated in tumors from African American patients across all breast cancer subtypes, including TNBC, and is associated with worse survival rates. This study investigated the effect of CRYβB2 on the invasion of TNBC cells and the underlying mechanisms contributing to this phenotype.

RESULTS

We utilized the SUM159 cells with stable CRYβB2 overexpression in a 3D-culture tumor spheroids model in our investigation. A quantitative 3D invasion assay demonstrated that CRYβB2 overexpression significantly enhanced invasion (median invasion %; SUM159 = 0.14 and SUM159 + CRYβB2 = 0.33). RNA sequencing analysis indicated that CRYβB2 overexpression modulated cell-cell adhesion and extracellular matrix organization pathways, which are critical to invasion of cancer cells. Specifically, CRYβB2 suppressed the expression of key cell-cell adhesion genes known as clustered protocadherins and promoted the expression of PCDH7, a nonclustered protocadherin with known oncogenic roles in various cancers. Notably, the knockout of PCDH7 diminished the invasive capacity induced by CRYβB2 (median invasion %; SUM159 = 0.093, SUM159 + CRYβB2 = 0.184 and SUM159 + CRYβB2/PCDH7-/-=0.082). These findings provide a novel link between a previously identified differentially expressed gene, CRYβB2, in driving breast cancer phenotypes by modulating a class of adhesion proteins.

The TRIM37 variant rs57141087 contributes to triple-negative breast cancer outcomes in Black women

Triple-negative breast cancer (TNBC) disproportionately affects younger Black women, who show more aggressive phenotypes and poorer outcomes than women of other racial identities. While the impact of socioenvironmental inequities within and beyond health systems is well documented, the genetic influence in TNBC-associated racial disparities remains elusive. Here, we report that cancer-free breast tissue from Black women expresses TRIM37 at a significantly higher level relative to White women. A reporter-based screen for regulatory variants identifies a non-coding risk variant rs57141087 in the 5' gene upstream region of the TRIM37 locus with enhancer activity. Mechanistically, rs57141087 increases enhancer-promoter interactions through NRF1, resulting in stronger TRIM37 promoter activity. Phenotypically, high TRIM37 levels drive neoplastic transformations in immortalized breast epithelial cells. Finally, context-dependent TRIM37 expression reveals that early-stage TRIM37 levels affect the initiation and trajectory of breast cancer progression. Together, our results indicate a genotype-informed association of oncogenic TRIM37 with TNBC risk in Black women and implicate TRIM37 as a predictive biomarker to better identify patients at risk of aggressive TNBC.

Low Hospital Volume Is Associated with Higher All-Cause Mortality in Black Women with Triple Negative Breast Cancer

INTRODUCTION

This study examines the association between hospital volume and all-cause mortality in Black women with triple negative breast cancer (TNBC) who received surgery and chemotherapy.

METHODS

Black women ages 18+ with stage I-III TNBC who received both surgery and chemotherapy were identified in the National Cancer Database (NCDB). Hospital volume was determined using the number of annual breast cancer cases divided by the number of years the hospital participated in the NCDB. Hospital annual volume quartiles ranged from Q1 (lowest) to Q4 (highest). Univariable analysis and multivariable logistic regression modeling with restricted cubic splines examined the effect of hospital volume on all-cause mortality.

RESULTS

Sixteen thousand five hundred fifty-six patients met the study criteria. All-cause mortality incidence was lower at higher volume compared to lower volume hospitals Q1 24.1% (95% CI: 22.8 to 25.4), Q2 21.8% (95% CI: 20.5 to 23.1), Q3 20.9% (95% CI: 19.6 to 22.1), Q4 19.0% (95% CI: 17.7 to 20.1), p<0.001. On multivariable analysis, treatment at the highest hospital volume quartile was associated with a 21% reduction in the odds of death compared to the lowest quartile [Q4 Vs. Q1, OR=0.79 (95% CI: 0.67 to 0.92)]. For every 100-patient increase in annual volume, all-cause mortality was reduced by 4% [OR=0.96 (95% CI: 0.94 to 0.98)]. There was a significant linear dose-dependent relationship between increasing hospital volume and all-cause mortality.

CONCLUSION

Black women treated at high-volume hospitals have lower all-cause mortality than those at low-volume hospitals. Future studies should examine the characteristics of high-volume hospitals associated with improved outcomes.

Worse Clinical and Survival Outcomes in Breast Cancer Patients Living in Puerto Rico Compared to Hispanics, Non-Hispanic Blacks, and Non-Hispanic Whites from Florida

BACKGROUND

Herein, we report the characterization of four cohorts of breast cancer patients including (1) non-Hispanic Whites in Florida, (2) non-Hispanic Blacks in Florida, (3) Hispanics in Florida, and (4) Hispanics in Puerto Rico.

METHODS

Data from female breast cancer patients were collected from cancer registry (n = 9361) and self-reported patient questionnaires (n = 4324). Several statistical tests were applied to identify significant group differences.

RESULTS

Breast cancer patients from Puerto Rico were least frequently employed and had the lowest rates of college education among the groups. They also reported more live births and less breastfeeding. Both Hispanic groups reported a higher fraction experiencing menstruation at age 11 or younger (Floridian Hispanics [38%] and Puerto Ricans [36%]) compared to non-Hispanic Whites (20%) and non-Hispanic Blacks (22%). Non-Hispanic Black and Puerto Rican women were significantly older at breast cancer diagnosis than their non-Hispanic White and Floridian Hispanic counterparts. The Puerto Rican and non-Hispanic Black groups more frequently had pathology stage T2 or higher primary breast tumors at diagnosis (non-Hispanic Whites [29%], non-Hispanic Blacks [39%], Floridian Hispanics [33%], Puerto Ricans [46%]). The Puerto Rican (73%, 95% CI [66, 82]) and non-Hispanic Black (79%, 95% CI [75, 84]) groups demonstrate reduced 5-year survival compared to non-Hispanic Whites (89%, 95% CI [86, 92]) and Floridian Hispanics (89%, 95% CI [86, 90]).

CONCLUSIONS

These findings demonstrate that Puerto Rican breast cancer patients suffer significant breast cancer health disparities relative to non-Hispanic Whites and Hispanics from Florida similar to the disparities observed for non-Hispanic Blacks. Future work must seek to better understand and address these disparities.

Breast cancer statistics 2024

This is the American Cancer Society's biennial update of statistics on breast cancer among women based on high-quality incidence and mortality data from the National Cancer Institute and the Centers for Disease Control and Prevention. Breast cancer incidence continued an upward trend, rising by 1% annually during 2012-2021, largely confined to localized-stage and hormone receptor-positive disease. A steeper increase in women younger than 50 years (1.4% annually) versus 50 years and older (0.7%) overall was only significant among White women. Asian American/Pacific Islander women had the fastest increase in both age groups (2.7% and 2.5% per year, respectively); consequently, young Asian American/Pacific Islander women had the second lowest rate in 2000 (57.4 per 100,000) but the highest rate in 2021 (86.3 per 100,000) alongside White women (86.4 per 100,000), surpassing Black women (81.5 per 100,000). In contrast, the overall breast cancer death rate continuously declined during 1989-2022 by 44% overall, translating to 517,900 fewer breast cancer deaths during this time. However, not all women have experienced this progress; mortality remained unchanged since 1990 in American Indian/Alaska Native women, and Black women have 38% higher mortality than White women despite 5% lower incidence. Although the Black-White disparity partly reflects more triple-negative cancers, Black women have the lowest survival for every breast cancer subtype and stage except localized disease, with which they are 10% less likely to be diagnosed than White women (58% vs. 68%), highlighting disadvantages in social determinants of health. Progress against breast cancer could be accelerated by mitigating racial, ethnic, and social disparities through improved clinical trial representation and access to high-quality screening and treatment.

Epidemiology of early vs late recurrence among women with early stage estrogen receptor-positive breast cancer in the Pathways Study

BACKGROUND

Relatively little is known about the differences in prognostic factors for early vs late recurrence among women with early stage estrogen receptor-positive breast cancer.

METHODS

We analyzed factors related to early (<5 years) vs late (≥5 years) recurrence in 2992 women with stage I-IIB estrogen receptor-positive breast cancer in the Pathways Study, a prospective cohort of women with breast cancer enrolled between 2006 and 2013, with ascertainment of recurrence and death through December 2021.

RESULTS

After a median follow-up of 13.3 years, 341 (13.8%) women had recurrences, including 181 (53.7%) with late recurrence. Higher stage and grade were associated with recurrence regardless of timing, whereas progesterone receptor negativity was associated with early but not late recurrence. Receipt of endocrine therapy was associated with reduced risk of overall recurrence, but the length of endocrine therapy was not statistically significant in multivariable models. Minoritized racial and ethnic groups, including Asian, Black, and Hispanic women, had higher risk of early but not late recurrence compared to non-Hispanic White women. The trend of higher risk of early recurrence among these groups remained after adjustment for clinical, demographic, and socioeconomic factors but was statistically significant only in Asian women.

CONCLUSIONS

Our study revealed potentially important distinctions for early vs late recurrence, including the associations with progesterone receptor negativity and self-identified race and ethnicity. Possible higher risk of early recurrence among Asian, Black, and Hispanic women provides novel evidence for the existence of disparities in cancer outcomes, even within the breast cancer subtype indicative of generally good prognosis.

Analysis of ductal carcinoma in situ by self-reported race reveals molecular differences related to outcome

BACKGROUND

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated.

METHODS

We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n = 99) and White (n = 191) women in a large DCIS case-control cohort study with longitudinal follow up.

RESULTS

Gene expression and pathway analyses suggested that different genes and pathways are involved in diagnosis and ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups.

CONCLUSIONS

Our results suggest that different molecular mechanisms drive initiation and subsequent ipsilateral breast events in Black versus White women.

Does combining numerous data types in multi-omics data improve or hinder performance in survival prediction? Insights from a large-scale benchmark study

BACKGROUND

Predictive modeling based on multi-omics data, which incorporates several types of omics data for the same patients, has shown potential to outperform single-omics predictive modeling. Most research in this domain focuses on incorporating numerous data types, despite the complexity and cost of acquiring them. The prevailing assumption is that increasing the number of data types necessarily improves predictive performance. However, the integration of less informative or redundant data types could potentially hinder this performance. Therefore, identifying the most effective combinations of omics data types that enhance predictive performance is critical for cost-effective and accurate predictions.

METHODS

In this study, we systematically evaluated the predictive performance of all 31 possible combinations including at least one of five genomic data types (mRNA, miRNA, methylation, DNAseq, and copy number variation) using 14 cancer datasets with right-censored survival outcomes, publicly available from the TCGA database. We employed various prediction methods and up-weighted clinical data in every model to leverage their predictive importance. Harrell's C-index and the integrated Brier Score were used as performance measures. To assess the robustness of our findings, we performed a bootstrap analysis at the level of the included datasets. Statistical testing was conducted for key results, limiting the number of tests to ensure a low risk of false positives.

RESULTS

Contrary to expectations, we found that using only mRNA data or a combination of mRNA and miRNA data was sufficient for most cancer types. For some cancer types, the additional inclusion of methylation data led to improved prediction results. Far from enhancing performance, the introduction of more data types most often resulted in a decline in performance, which varied between the two performance measures.

CONCLUSIONS

Our findings challenge the prevailing notion that combining multiple omics data types in multi-omics survival prediction improves predictive performance. Thus, the widespread approach in multi-omics prediction of incorporating as many data types as possible should be reconsidered to avoid suboptimal prediction results and unnecessary expenditure.

FBXW7 as a Factor of the African American and White Breast Cancer Racial Disparity

INTRODUCTION

African American women have a breast cancer mortality rate 40% higher than Caucasian women. Many contributing factors account for this racial disparity, such as socioeconomic status and the age when women give birth, but even after considering such factors, studies have found that the racial disparity persists, suggesting that genetic factors may play a crucial role in this breast cancer racial inequality.

METHODS

This study utilizes the All of Us database, The Cancer Genome Atlas (TCGA), and an array of bioinformatics tools to integrate differential mutation and gene expression analyses, aiming to identify genes potentially associated with this racial disparity. Although previous studies have identified genes associated with this breast cancer racial disparity through mutation or gene expression analysis, no studies have considered both simultaneously. Ultimately, this study considers both mutation and gene expression to discover novel genes linked to this racial disparity.

RESULTS

After mutation analysis, this study identified FBXW7, a gene involved in the destruction of oncogenic proteins, as being associated with this racial inequality. FBXW7  was the only gene that presented differences in both mutation frequency and gene expression between African Americans and Caucasians. The other four candidate genes, such as COL12A1, whose upregulation plays a critical role in tumor progression, may also be linked to this racial inequality.

CONCLUSION

By combining both mutation and gene expression analysis, this research offers a unique perspective into this issue. Furthermore, the identification of FBXW7 provides insight into this racial disparity, which can contribute to the pursuit of more effective or personalized treatment for both Caucasian and African American breast cancer patients. Finally, the multi-level method presented could possibly apply to other racial disparities, providing a distinctive perspective that cannot be found with other methods.

Molecular characterization analysis of PANoptosis-related genes in colorectal cancer based on bioinformatic analysis

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally and stands as the second principal contributor to cancer-related fatalities. Recently, emerging research has emphasized the role of pan apoptosis (PANoptosis) in tumor development and anti-tumor therapy. In the course of this investigation, we meticulously identified and conducted a correlation analysis between differentially expressed genes associated with PANoptosis in CRC (CPAN_DEGs) and the proportion of immune cells. Subsequently, we formulated a prognostic score based on the CPAN_DEGs. Further our analysis revealed a noteworthy reduction in UNC5D mRNA expression within HCT116, HT29 and SW480 cells, as validated by qRT-PCR assay. Furthermore, scrutinizing the TCGA database unveiled a distinctive trend wherein individuals with the low UNC5D expression exhibited significantly reduced overall survival compared to their counterparts with the high UNC5D levels. The drug susceptibility analysis of UNC5D was further performed, which showed that UNC5D was corassociated with the sensitivity of CRC to 6-Thioguanine. The outcomes of our investigation underscore the mechanisms by which PANoptosis influences immune dysregulation as well as prognostic outcome in CRC.

ECOG-ACRIN EAZ171: Prospective Validation Trial of Germline Predictors of Taxane-Induced Peripheral Neuropathy in Black Women With Early-Stage Breast Cancer

PURPOSE

Black women experience higher rates of taxane-induced peripheral neuropathy (TIPN) compared with White women when receiving adjuvant once weekly paclitaxel for early-stage breast cancer, leading to more dose reductions and higher recurrence rates. EAZ171 aimed to prospectively validate germline predictors of TIPN and compare rates of TIPN and dose reductions in Black women receiving (neo)adjuvant once weekly paclitaxel and once every 3 weeks docetaxel for early-stage breast cancer.

METHODS

Women with early-stage breast cancer who self-identified as Black and had intended to receive (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel were eligible, with planned accrual to 120 patients in each arm. Genotyping was performed to determine germline neuropathy risk. Grade 2-4 TIPN by Common Terminology Criteria for Adverse Events (CTCAE) v5.0 was compared between high- versus low-risk genotypes and between once weekly paclitaxel versus once every 3 weeks docetaxel within 1 year. Patient-rated TIPN and patient-reported outcomes were compared using patient-reported outcome (PRO)-CTCAE and Functional Assessment of Cancer Therapy/Gynecologic Oncology Group-Neurotoxicity.

RESULTS

Two hundred and forty of 249 enrolled patients had genotype data, and 91 of 117 (77.8%) receiving once weekly paclitaxel and 87 of 118 (73.7%) receiving once every 3 weeks docetaxel were classified as high-risk. Physician-reported grade 2-4 TIPN was not significantly different in high- versus low-risk genotype groups with once weekly paclitaxel (47% v 35%; P = .27) or with once every 3 weeks docetaxel (28% v 19%; P = .47). Grade 2-4 TIPN was significantly higher in the once weekly paclitaxel versus once every 3 weeks docetaxel arm by both physician-rated CTCAE (45% v 29%; P = .02) and PRO-CTCAE (40% v 24%; P = .03). Patients receiving once weekly paclitaxel required more dose reductions because of TIPN (28% v 9%; P < .001) or any cause (39% v 25%; P = .02).

CONCLUSION

Germline variation did not predict risk of TIPN in Black women receiving (neo)adjuvant once weekly paclitaxel or once every 3 weeks docetaxel. Once weekly paclitaxel was associated with significantly more grade 2-4 TIPN and required more dose reductions than once every 3 weeks docetaxel.

Bioinformatics analysis of ERCC family in pan-cancer and ERCC2 in bladder cancer

Background

Single nucleotide polymorphisms (SNPs) in DNA repair genes can impair protein function and hinder DNA repair, leading to genetic instability and increased cancer risk. The Excision Repair Cross-Complementation (ERCC) family plays a crucial role in nucleotide excision repair, yet their comprehensive multi-omics characterization and roles in tumor prognosis and immune microenvironment remain unexplored.

Methods and materials

We performed bioinformatics analysis using publicly available data from 33 cancer types to investigate associations between ERCC gene expression, patient prognosis, and clinical features. We also validated the role of ERCC2 in bladder cancer through in vitro assays, including CCK-8, colony formation, wound healing, and Transwell assays.

Results

By utilizing the most recent database, we have conducted an analysis that reveals associations between variations in ERCC expression across multiple cancer types and both patient prognosis and the tumor microenvironment. To ensure the reliability of our findings, we applied the Benjamini-Hochberg procedure to adjust for multiple testing. After correction, we identified that ERCC expression levels remained significantly correlated with patient prognosis in various cancer types (p < 0.05). In addition, according to the results of drug sensitivity studies of anticancer drugs, there is a large correlation between ERCC expression and the sensitivity of different anticancer drugs. Finally, in vitro cell behavioral assays determined that knockdown of ERCC2 gene expression significantly inhibited the proliferation, migration and invasion of bladder cancer cells.

Conclusion

Through in-depth exploration of ERCC differential expression and its correlation with immune-related indicators, the unique microenvironment of tumors, and patient prognosis, we verified the potential role of ERCC2 in the process of bladder cancer genesis and progression. Therefore, we believe that the ERCC family of genes is expected to be a new option for cancer treatment and deserves to be further explored in the future.

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

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

Multi-tissue transcriptome-wide association studies identified 235 genes for intrinsic subtypes of breast cancer

BACKGROUND

Although genome-wide association studies (GWAS) of breast cancer (BC) identified common variants which differ between intrinsic subtypes, genes through which these variants act to impact BC risk have not been fully established. Transcriptome-wide association studies (TWAS) have identified genes associated with overall BC risk, but subtype-specific differences are largely unknown.

METHODS

We performed two multi-tissue TWAS for each BC intrinsic subtype, including an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues and a novel splicing-based approach that collated signals from splicing QTLs (sQTLs) across intron clusters and subsequently across tissues. We used summary statistics for five intrinsic subtypes including Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, and triple-negative BC, generated from 106 278 BC cases and 91 477 controls in the Breast Cancer Association Consortium.

RESULTS

Overall, we identified 235 genes in 88 loci that were associated with at least one of the five intrinsic subtypes. Most genes were subtype-specific, and many have not been reported in previous TWAS. We discovered common variants that modulate expression of CHEK2 confer increased risk to Luminal A-like BC, in contrast to the viewpoint that CHEK2 primarily harbors rare, penetrant mutations. Additionally, our splicing-based TWAS provided population-level support for MDM4 splice variants that increased the risk of triple-negative BC.

CONCLUSION

Our comprehensive, multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation that impacts expression and splicing of genes in multiple tissue types can be used to further elucidate the etiology of BC.

Association of ESR1 Germline Variants with TP53 Somatic Variants in Breast Tumors in a Genome-wide Study

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. A genome-wide association study was conducted in 2,850 women of European ancestry with breast cancer using TP53 and PIK3CA mutation status (positive or negative) as well as specific functional categories [e.g., TP53 gain-of-function (GOF) and loss-of-function, PIK3CA activating] as phenotypes. Germline variants showing evidence of association were selected for validation analyses and tested in multiple independent datasets. Discovery association analyses found five variants associated with TP53 mutation status with P values <1 × 10-6 and 33 variants with P values <1 × 10-5. Forty-four variants were associated with PIK3CA mutation status with P values <1 × 10-5. In validation analyses, only variants at the ESR1 locus were associated with TP53 mutation status after multiple comparisons corrections. Combined analyses in European and Malaysian populations found ESR1 locus variants rs9383938 and rs9479090 associated with the presence of TP53 mutations overall (P values 2 × 10-11 and 4.6 × 10-10, respectively). rs9383938 also showed association with TP53 GOF mutations (P value 6.1 × 10-7). rs9479090 showed suggestive evidence (P value 0.02) for association with TP53 mutation status in African ancestry populations. No other variants were significantly associated with TP53 or PIK3CA mutation status. Larger studies are needed to confirm these findings and determine if additional variants contribute to ancestry-specific differences in mutation frequency.

SIGNIFICANCE

Emerging data show ancestry-specific differences in TP53 and PIK3CA mutation frequency in breast tumors suggesting that germline variants may influence somatic mutational processes. This study identified variants near ESR1 associated with TP53 mutation status and identified additional loci with suggestive association which may provide biological insight into observed differences.

Genetic ancestry is related to potential sources of breast cancer health disparities among Colombian women

Breast cancer health disparities are linked to clinical-pathological determinants, socioeconomic inequities, and biological factors such as genetic ancestry. These factors collectively interact in complex ways, influencing disease behavior, especially among highly admixed populations like Colombians. In this study, we assessed contributing factors to breast cancer health disparities according to genetic ancestry in Colombian patients from a national cancer reference center. We collected non-tumoral paraffin embedded (FFPE) blocks from 361 women diagnosed with breast cancer at the National Cancer Institute (NCI) to estimate genetic ancestry using a 106-ancestry informative marker (AIM) panel. Differences in European, Indigenous American (IA) and African ancestry fractions were analyzed according to potential sources of breast cancer health disparities, like etiology, tumor-biology, treatment administration, and socioeconomic-related factors using a Kruskal-Wallis test. Our analysis revealed a significantly higher IA ancestry among overweight patients with larger tumors and those covered by a subsidized health insurance. Conversely, we found a significantly higher European ancestry among patients with smaller tumors, residing in middle-income households, and affiliated to the contributory health regime, whereas a higher median of African ancestry was observed among patients with either a clinical, pathological, or stable response to neoadjuvant treatment. Altogether, our results suggest that the genetic legacy among Colombian patients, measured as genetic ancestry fractions, may be reflected in many of the clinical-pathological variables and socioeconomic factors that end up contributing to health disparities for this disease.

Genetic Ancestry-specific Molecular and Survival Differences in Admixed Patients With Breast Cancer

OBJECTIVE

We aim to determine whether incremental changes in genetic ancestry percentages influence molecular and clinical outcome characteristics of breast cancer in an admixed population.

BACKGROUND

Patients with breast cancer are predominantly characterized as "Black" or "White" based on self-identified race/ethnicity or arbitrary genetic ancestry cutoffs. This limits scientific discovery in populations that are admixed or of mixed race/ethnicity as they cannot be classified based on historical race/ethnicity boxes or genetic ancestry cutoffs.

METHODS

We used The Cancer Genome Atlas cohort and focused on genetically admixed patients that had less than 90% European, African, Asian, or Native American ancestry.

RESULTS

Genetically admixed patients with breast cancer exhibited improved 10-year overall survival relative to those with >90% European ancestry. Within the luminal A subtype, patients with lower African ancestry had longer 10-year overall survival compared to those with higher African ancestry. The correlation of genetic ancestry with gene expression and DNA methylation in the admixed cohort revealed novel ancestry-specific intrinsic PAM50 subtype patterns. In luminal A tumors, genetic ancestry was correlated with both the expression and methylation of signaling genes, while in basal-like tumors, genetic ancestry was correlated with stemness genes. In addition, we took a machine-learning approach to estimate genetic ancestry from gene expression or DNA methylation and were able to accurately calculate ancestry values from a reduced set of 10 genes or 50 methylation sites that were specific for each molecular subtype.

CONCLUSIONS

Our results suggest that incremental changes in genetic ancestry percentages result in ancestry-specific molecular differences even between well-established PAM50 subtypes which may influence disparities in breast cancer survival outcomes. Accounting for incremental changes in ancestry will be important in future research, prognostication, and risk stratification, particularly in ancestrally diverse populations.

Psychosocial stressors and breast cancer gene expression in the Black Women's Health Study

PURPOSE

Prior studies indicate that the physiologic response to stress can affect gene expression. We evaluated differential gene expression in breast cancers collected from Black women with high versus low exposure to psychosocial stressors.

METHODS

We analyzed tumor RNA sequencing data from 417 Black Women's Health Study breast cancer cases with data on early life trauma and neighborhood disadvantage. We conducted age-adjusted differential gene expression analyses and pathway analyses. We also evaluated Conserved Transcriptional Response to Adversity (CTRA) contrast scores, relative fractions of immune cell types, T cell exhaustion, and adrenergic signaling. Analyses were run separately for estrogen receptor positive (ER+; n = 299) and ER- (n = 118) cases.

RESULTS

Among ER+ cases, the top differentially expressed pathways by stress exposure were related to RNA and protein metabolism. Among ER- cases, they were related to developmental biology, signal transduction, metabolism, and the immune system. Targeted analyses indicated greater immune pathway enrichment with stress exposure for ER- cases, and possible relevance of adrenergic signaling for ER+ cases. CTRA contrast scores did not differ by stress exposure, but in analyses of the CTRA components, ER- breast cancer cases with high neighborhood disadvantage had higher pro-inflammatory gene expression (p = 0.039) and higher antibody gene expression (p = 0.006) compared to those with low neighborhood disadvantage.

CONCLUSION

There are multiple pathways through which psychosocial stress exposure may influence breast tumor biology. Given the present findings on inflammation and immune response in ER- tumors, further research to identify stress-induced changes in the etiology and progression of ER- breast cancer is warranted.

Expression- and splicing-based multi-tissue transcriptome-wide association studies identified multiple genes for breast cancer by estrogen-receptor status

BACKGROUND

Although several transcriptome-wide association studies (TWASs) have been performed to identify genes associated with overall breast cancer (BC) risk, only a few TWAS have explored the differences in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) breast cancer. Additionally, these studies were based on gene expression prediction models trained primarily in breast tissue, and they did not account for alternative splicing of genes.

METHODS

In this study, we utilized two approaches to perform multi-tissue TWASs of breast cancer by ER subtype: (1) an expression-based TWAS that combined TWAS signals for each gene across multiple tissues and (2) a splicing-based TWAS that combined TWAS signals of all excised introns for each gene across tissues. To perform this TWAS, we utilized summary statistics for ER + BC from the Breast Cancer Association Consortium (BCAC) and for ER- BC from a meta-analysis of BCAC and the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA).

RESULTS

In total, we identified 230 genes in 86 loci that were associated with ER + BC and 66 genes in 29 loci that were associated with ER- BC at a Bonferroni threshold of significance. Of these genes, 2 genes associated with ER + BC at the 1q21.1 locus were located at least 1 Mb from published GWAS hits. For several well-studied tumor suppressor genes such as TP53 and CHEK2 which have historically been thought to impact BC risk through rare, penetrant mutations, we discovered that common variants, which modulate gene expression, may additionally contribute to ER + or ER- etiology.

CONCLUSIONS

Our study comprehensively examined how differences in common variation contribute to molecular differences between ER + and ER- BC and introduces a novel, splicing-based framework that can be used in future TWAS studies.

The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics

Despite significant progress in the prevention, screening, diagnosis, prognosis, and therapy of breast cancer (BC), it remains a highly prevalent and life-threatening disease affecting millions worldwide. Molecular subtyping of BC is crucial for predictive and prognostic purposes due to the diverse clinical behaviors observed across various types. The molecular heterogeneity of BC poses uncertainties in its impact on diagnosis, prognosis, and treatment. Numerous studies have highlighted genetic and environmental differences between patients from different geographic regions, emphasizing the need for localized research. International studies have revealed that patients with African heritage are often diagnosed at a more advanced stage and exhibit poorer responses to treatment and lower survival rates. Despite these global findings, there is a dearth of in-depth studies focusing on communities in the African region. Early diagnosis and timely treatment are paramount to improving survival rates. In this context, radiogenomics emerges as a promising field within precision medicine. By associating genetic patterns with image attributes or features, radiogenomics has the potential to significantly improve early detection, prognosis, and diagnosis. It can provide valuable insights into potential treatment options and predict the likelihood of survival, progression, and relapse. Radiogenomics allows for visual features and genetic marker linkage that promises to eliminate the need for biopsy and sequencing. The application of radiogenomics not only contributes to advancing precision oncology and individualized patient treatment but also streamlines clinical workflows. This review aims to delve into the theoretical underpinnings of radiogenomics and explore its practical applications in the diagnosis, management, and treatment of BC and to put radiogenomics on a path towards fully integrated diagnostics.

Efficacy of Single-Agent Chemotherapy in Endocrine Therapy-Refractory Metastatic Invasive Lobular Carcinoma

BACKGROUND

Hormone receptor (HR)-positive, HER2-negative metastatic invasive lobular breast cancer (mILC) is distinct from invasive ductal cancer (IDC) in clinicopathologic and molecular characteristics, impacting its response to systemic therapy. While endocrine therapy (ET) combined with targeted therapies has shown efficacy in ET-sensitive mILC, data on chemotherapy in ET-refractory mILC remain limited. We investigated the efficacy of single-agent capecitabine (CAP) versus taxanes (TAX) in ET-refractory HR+ HER2-negative patients with mILC.

MATERIALS AND METHODS

Using data from the MD Anderson prospectively collected breast cancer database, we identified patients with HR+ HER2-negative mILC who received prior ET and first-time chemotherapy in the metastatic setting. We compared outcomes between 173 CAP-treated and 96 TAX-treated patients.

RESULTS

CAP-treated patients had significantly better median progression-free survival (PFS) than TAX-treated patients (8.8 vs 5.0 months, HR 0.63, P < .001). Overall survival (OS) did not differ significantly between the groups (42.7 vs 36.6 months for CAP vs TAX, respectively, HR 0.84, P = .241). Multivariate analyses for PFS and OS revealed better outcomes in subjects with fewer metastatic sites and those exposed to more lines of ET. Additionally, Black patients showed worse OS outcomes compared to White patients (HR 2.46; P = .001).

CONCLUSION

In ET-refractory HR+ HER2-negative mILC, single-agent CAP demonstrated superior PFS compared to TAX. Our findings highlight the potential benefit of CAP in this patient subset, warranting further investigation through prospective trials.

Comparing extracellular volume fraction with apparent diffusion coefficient for the characterization of breast tumors

PURPOSE

To investigate the feasibility of dual-energy CT (DECT)-derived extracellular volume (ECV) fraction for characterization of breast tumors, compared to apparent diffusion coefficient (ADC) and validated against histopathological findings.

MATERIAL AND METHODS

The ECV fraction and ADC were prospectively assessed in patients with breast tumors using chest DECT and breast MRI. The diagnostic performance of ECV fraction and ADC was accessed in predicting breast histopathological subtypes and pathological complete response (pCR) status. Histopathological sections were analyzed by digital image analysis. Pearson's correlation analysis was used to correlate between DECT and histopathological ECV fractions.

RESULTS

This study included 271 patients, with 314 breast lesions (61 benign and 253 malignant). The ECV fraction and ADC showed comparable area under the curve (AUC) for distinguishing benign from malignant lesions (p = 0.123) and invasive carcinoma from ductal carcinoma in situ (p = 0.115). There were significant differences in ECV fraction between different hormone receptors and Ki67 states (p = 0.001 ∼ 0.014), while ADC values only differed among various Ki67 states (p < 0.001). The ECV fraction was lower (p = 0.007), ADC was higher (p = 0.013) in pCR than in non-pCR group, with an AUC of 0.748 and 0.730 (p = 0.887), respectively. There was a positive correlation between DECT and histopathological ECV fractions (r = 0.615, p < 0.01).

CONCLUSIONS

Routine chest DECT-derived ECV fraction is a viable quantitative imaging biomarker for predicting histopathological subtypes and pCR in patient with breast tumors, and correlated well with histopathology finding.

Gene-Expression Profiling to Decipher Breast Cancer Inter- and Intratumor Heterogeneity

Breast cancer is heterogeneous and differs substantially across different tumors (intertumor heterogeneity) and even within an individual tumor (intratumor heterogeneity). Gene-expression profiling has considerably impacted our understanding of breast cancer biology. Four main "intrinsic subtypes" of breast cancer (i.e., luminal A, luminal B, HER2-enriched, and basal-like) have been consistently identified by gene expression, showing significant prognostic and predictive value in multiple clinical scenarios. Thanks to the molecular profiling of breast tumors, breast cancer is a paradigm of treatment personalization. Several standardized prognostic gene-expression assays are presently being used in the clinic to guide treatment decisions. Moreover, the development of single-cell-level resolution molecular profiling has allowed us to appreciate that breast cancer is also heterogeneous within a single tumor. There is an evident functional heterogeneity within the neoplastic and tumor microenvironment cells. Finally, emerging insights from these studies suggest a substantial cellular organization of neoplastic and tumor microenvironment cells, thus defining breast cancer ecosystems and highlighting the importance of spatial localizations.

Breast cancer: Epidemiology, risk factors and screening

Breast cancer is a global health concern with a significant impact on the well-being of women. Worldwide, the past several decades have witnessed changes in the incidence and mortality of breast cancer. Additionally, epidemiological data reveal distinct geographic and demographic disparities globally. A range of modifiable and non-modifiable risk factors are established as being associated with an increased risk of developing breast cancer. This review discusses genetic, hormonal, behavioral, environmental, and breast-related risk factors. Screening plays a critical role in the effective management of breast cancer. Various screening modalities, including mammography, ultrasound, magnetic resonance imaging (MRI), and physical examination, have different applications, and a combination of these modalities is applied in practice. Current screening recommendations are based on factors including age and risk, with a significant emphasis on minimizing potential harms to achieve an optimal benefits-to-harms ratio. This review provides a comprehensive insight into the epidemiology, risk factors, and screening of breast cancer. Understanding these elements is crucial for improving breast cancer management and reducing its burden on affected individuals and healthcare systems.

Comprehensive genomic profiling of breast cancers characterizes germline-somatic mutation interactions mediating therapeutic vulnerabilities

Germline-somatic mutation interactions are universal and associated with tumorigenesis, but their role in breast cancer, especially in non-Caucasians, remains poorly characterized. We performed large-scale prospective targeted sequencing of matched tumor-blood samples from 4079 Chinese females, coupled with detailed clinical annotation, to map interactions between germline and somatic alterations. We discovered 368 pathogenic germline variants and identified 5 breast cancer DNA repair-associated genes (BCDGs; BRCA1/BRCA2/CHEK2/PALB2/TP53). BCDG mutation carriers, especially those with two-hit inactivation, demonstrated younger onset, higher tumor mutation burden, and greater clinical benefits from platinum drugs, PARP inhibitors, and immune checkpoint inhibitors. Furthermore, we leveraged a multiomics cohort to reveal that clinical benefits derived from two-hit events are associated with increased genome instability and an immune-activated tumor microenvironment. We also established an ethnicity-specific tool to predict BCDG mutation and two-hit status for genetic evaluation and therapeutic decisions. Overall, this study leveraged the large sequencing cohort of Chinese breast cancers, optimizing genomics-guided selection of DNA damaging-targeted therapy and immunotherapy within a broader population.

Association of ESR1 germline variants with TP53 somatic variants in breast tumors in a genome-wide study

Background

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. HER2 positive and triple negative breast cancers (TNBC) have a higher frequency of TP53 somatic mutations than other subtypes. PIK3CA mutations are more frequently observed in hormone receptor positive tumors. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors.

Methods

A genome-wide association study was conducted using breast cancer mutation status of TP53 and PIK3CA and functional mutation categories including TP53 gain of function (GOF) and loss of function mutations and PIK3CA activating/hotspot mutations. The discovery analysis consisted of 2850 European ancestry women from three datasets. Germline variants showing evidence of association with somatic mutations were selected for validation analyses based on predicted function, allele frequency, and proximity to known cancer genes or risk loci. Candidate variants were assessed for association with mutation status in a multi-ancestry validation study, a Malaysian study, and a study of African American/Black women with TNBC.

Results

The discovery Germline x Mutation (GxM) association study found five variants associated with one or more TP53 phenotypes with P values <1×10-6, 33 variants associated with one or more TP53 phenotypes with P values <1×10-5, and 44 variants associated with one or more PIK3CA phenotypes with P values <1×10-5. In the multi-ancestry and Malaysian validation studies, germline ESR1 locus variant, rs9383938, was associated with the presence of TP53 mutations overall (P values 6.8×10-5 and 9.8×10-8, respectively) and TP53 GOF mutations (P value 8.4×10-6). Multiple variants showed suggestive evidence of association with PIK3CA mutation status in the validation studies, but none were significant after correction for multiple comparisons.

Conclusions

We found evidence that germline variants were associated with TP53 and PIK3CA mutation status in breast cancers. Variants near the estrogen receptor alpha gene, ESR1, were significantly associated with overall TP53 mutations and GOF mutations. Larger multi-ancestry studies are needed to confirm these findings and determine if these variants contribute to ancestry-specific differences in mutation frequency.

Race, Gene Expression Signatures, and Clinical Outcomes of Patients With High-Risk Early Breast Cancer

Importance

There has been little consideration of genomic risk of recurrence by breast cancer subtype despite evidence of racial disparities in breast cancer outcomes.

Objective

To evaluate associations between clinical trial end points, namely pathologic complete response (pCR) and distant recurrence-free survival (DRFS), and race and examine whether gene expression signatures are associated with outcomes by race.

Design, Setting, and Participants

This retrospective cohort study used data from the Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2 (I-SPY 2) multicenter clinical trial of neoadjuvant chemotherapy with novel agents and combinations for patients with previously untreated stage II/III breast cancer. Analyses were conducted of associations between race and short- and long-term outcomes, overall and by receptor subtypes, and their association with 28 expression biomarkers. The trial enrolled 990 female patients between March 30, 2010, and November 5, 2016, with a primary tumor size of 2.5 cm or greater and clinical or molecular high risk based on MammaPrint or hormone receptor (HR)-negative/ERBB2 (formerly HER2 or HER2/neu)-positive subtyping across 9 arms. This data analysis was performed between June 10, 2021, and October 20, 2022.

Exposure

Race, tumor receptor subtypes, and genomic biomarker expression of early breast cancer.

Main Outcomes and Measures

The primary outcomes were pCR and DRFS assessed by race, overall, and by tumor subtype using logistic regression and Cox proportional hazards regression models. The interaction between 28 expression biomarkers and race, considering pCR and DRFS overall and within subtypes, was also evaluated.

Results

The analytic sample included 974 participants (excluding 16 self-reporting as American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, or multiple races due to small sample sizes), including 68 Asian (7%), 120 Black (12%), and 786 White (81%) patients. Median (range) age at diagnosis was 47 (25-71) years for Asian, 49 (25-77) for Black, and 49 (23-73) years for White patients. The pCR rates were 32% (n = 22) for Asian, 30% for Black (n = 36), and 32% for White (n = 255) patients (P = .87). Black patients with HR-positive/ERBB2-negative tumors not achieving pCR had significantly worse DRFS than their White counterparts (hazard ratio, 2.28; 95% CI, 1.24-4.21; P = .01), with 5-year DRFS rates of 55% (n = 32) and 77% (n = 247), respectively. Black patients with HR-positive/ERBB2-negative tumors, compared with White patients, had higher expression of an interferon signature (mean [SD], 0.39 [0.87] and -0.10 [0.99]; P = .007) and, compared with Asian patients, had a higher mitotic score (mean [SD], 0.07 [1.08] and -0.69 [1.06]; P = .01) and lower estrogen receptor/progesterone receptor signature (mean [SD], 0.31 [0.90] and 1.08 [0.95]; P = .008). A transforming growth factor β signature had a significant association with race relative to pCR and DRFS, with a higher signature associated with lower pCR and worse DRFS outcomes among Black patients only.

Conclusions and Relevance

The findings show that women with early high-risk breast cancer who achieve pCR have similarly good outcomes regardless of race, but Black women with HR-positive/ERBB2-negative tumors without pCR may have worse DRFS than White women, highlighting the need to develop and test novel biomarker-informed therapies in diverse populations.

Tumor sequencing of African ancestry reveals differences in clinically relevant alterations across common cancers

Cancer genomes from patients with African (AFR) ancestry have been poorly studied in clinical research. We leverage two large genomic cohorts to investigate the relationship between genomic alterations and AFR ancestry in six common cancers. Cross-cancer type associations, such as an enrichment of MYC amplification with AFR ancestry in lung, breast, and prostate cancers, and depletion of BRAF alterations are observed in colorectal and pancreatic cancers. There are differences in actionable alterations, such as depletion of KRAS G12C and EGFR L858R, and enrichment of ROS1 fusion with AFR ancestry in lung cancers. Interestingly, in lung cancer, KRAS mutations are less common in both smokers and non-smokers with AFR ancestry, whereas the association of TP53 mutations with AFR ancestry is only seen in smokers, suggesting an ancestry-environment interaction that modifies driver rates. Our study highlights the need to increase representation of patients with AFR ancestry in drug development and biomarker discovery.

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.

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.

Survival of Filipino women with breast cancer in the United States

BACKGROUND

The survival of women with early-stage breast cancer varies by racial group. Filipino women with breast cancer are an understudied group and are often combined with other Asian groups. We compared clinical presentations and survival rates for Filipino and White women with breast cancer diagnosed in the United States.

METHODS

We conducted a retrospective cohort study of women with breast cancer diagnosed between 2004 and 2015 in the SEER18 registries database. We compared crude survival between Filipino and White women. We then calculated adjusted hazard ratios (HR) in a propensity-matched design using the Cox proportional hazards model.

RESULTS

There were 10,834 Filipino (2.5%) and 414,618 White women (97.5%) with Stage I-IV breast cancer in the SEER database. The mean age at diagnosis was 57.5 years for Filipino women and 60.8 years for White women (p < 0.0001). Filipino women had more high-grade and larger tumors than White women and were more likely to have node-positive disease. Among women with Stage I-IIIC breast cancer, the crude 10-year breast cancer-specific survival rate was 91.0% for Filipino and 88.9% for White women (HR 0.81, 95% CI 0.74-0.88, p < 0.01). In a propensity-matched analysis, the HR was 0.73 (95% CI 0.66-0.81). The survival advantage for Filipino women was present in subgroups defined by age of diagnosis, nodal status, estrogen receptor status, and HER2 receptor status.

CONCLUSION

In the United States, Filipino women often present with more advanced breast cancers than White women, but experience better breast cancer-specific survival.

Landmark Series: The Cancer Genome Atlas and the Study of Breast Cancer Disparities

Race-related variation in breast cancer incidence and mortality are well-documented in the United States. The effect of genetic ancestry on disparities in tumor genomics, risk factors, treatment, and outcomes of breast cancer is less understood. The Cancer Genome Atlas (TCGA) is a publicly available resource that has allowed for the recent emergence of genome analysis research seeking to characterize tumor DNA and protein expression by ancestry as well as the social construction of race and ethnicity. Results from TCGA based studies support previous clinical evidence that demonstrates that American women with African ancestry are more likely to be afflicted with breast cancers featuring aggressive biology and poorer outcomes compared with women with other backgrounds. Data from TCGA based studies suggest that Asian women have tumors with favorable immune microenvironments and may experience better disease-free survival compared with white Americans. TCGA contains limited data on Hispanic/Latinx patients due to small sample size. Overall, TCGA provides important opportunities to define the molecular, biologic, and germline genetic factors that contribute to breast cancer disparities.

Translational Epidemiology: Genetic Ancestry in Breast Cancer: What Is the Role of Genetic Ancestry and Socioeconomic Status in Triple-Negative Breast Cancer?

Racial/ethnic and socioeconomic disparities seen in triple-negative breast cancer (TNBC) have prompted questions regarding the role of genetic ancestry in breast cancer (BC) subtype development, tumor biology, and ultimately prognosis. The causes of disparities in TNBC are influenced greatly by both sociopolitical factors and genetic ancestry, and now, the potential genomic underpinnings of social factors. To comprehensively understand disparities in TNBC, it is critical to take a translational epidemiologic approach that takes into account genomic and non-genomic factors. Understanding the interplay between genetic ancestry and social genomics and their proportional influence on outcomes can guide our priorities for screening, diagnosis, and interventions for this aggressive BC subtype.

Investigating the association between educational attainment and allostatic load with risk of cancer mortality among African American women

BACKGROUND

African American (AA) women navigate the world with multiple intersecting marginalized identities. Accordingly, AA women have higher cumulative stress burden or allostatic load (AL) compared to other women. Studies suggest that AA women with a college degree or higher have lower AL than AA women with less than a high school diploma. We examined the joint effect of educational attainment and AL status with long-term risk of cancer mortality, and whether education moderated the association between AL and cancer mortality.

METHODS

We performed a retrospective analysis among 4,677 AA women within the National Health and Nutrition Examination Survey (NHANES) from 1988 to 2010 with follow-up data through December 31, 2019. We fit weighted Cox proportional hazards models to estimate adjusted hazard ratios (aHRs) of cancer death between educational attainment/AL (adjusted for age, income, and smoking status).

RESULTS

AA women with less than a high school diploma living with high AL had nearly a 3-fold increased risk (unadjusted HR: 2.98; 95%C CI: 1.24-7.15) of cancer death compared to AA college graduates living with low AL. However, after adjusting for age, this effect attenuated (age-adjusted HR: 1.11; 95% CI: 0.45-2.74). AA women with high AL had 2.3-fold increased risk of cancer death (fully adjusted HR: 2.26; 95% CI: 1.10-4.57) when compared to AA with low AL, specifically among women with high school diploma or equivalent and without history of cancer.

CONCLUSIONS

Our findings suggest that high allostatic load is associated with a higher risk of cancer mortality among AA women with lower educational attainment, while no such association was observed among AA women with higher educational attainment. Thus, educational attainment plays a modifying role in the relationship between allostatic load and the risk of cancer death for AA women. Higher education can bring several benefits, including improved access to medical care and enhanced medical literacy, which in turn may help mitigate the adverse impact of AL and the heightened risk of cancer mortality among AA women.

Delineating intra-tumoral heterogeneity and tumor evolution in breast cancer using precision-based approaches

The burden of breast cancer continues to increase worldwide as it remains the most diagnosed tumor in females and the second leading cause of cancer-related deaths. Breast cancer is a heterogeneous disease characterized by different subtypes which are driven by aberrations in key genes such as BRCA1 and BRCA2, and hormone receptors. However, even within each subtype, heterogeneity that is driven by underlying evolutionary mechanisms is suggested to underlie poor response to therapy, variance in disease progression, recurrence, and relapse. Intratumoral heterogeneity highlights that the evolvability of tumor cells depends on interactions with cells of the tumor microenvironment. The complexity of the tumor microenvironment is being unraveled by recent advances in screening technologies such as high throughput sequencing; however, there remain challenges that impede the practical use of these approaches, considering the underlying biology of the tumor microenvironment and the impact of selective pressures on the evolvability of tumor cells. In this review, we will highlight the advances made thus far in defining the molecular heterogeneity in breast cancer and the implications thereof in diagnosis, the design and application of targeted therapies for improved clinical outcomes. We describe the different precision-based approaches to diagnosis and treatment and their prospects. We further propose that effective cancer diagnosis and treatment are dependent on unpacking the tumor microenvironment and its role in driving intratumoral heterogeneity. Underwriting such heterogeneity are Darwinian concepts of natural selection that we suggest need to be taken into account to ensure evolutionarily informed therapeutic decisions.

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.

Profiling the Somatic Mutational Landscape of Breast Tumors from Hispanic/Latina Women Reveals Conserved and Unique Characteristics

Somatic mutational profiling is increasingly being used to identify potential targets for breast cancer. However, limited tumor-sequencing data from Hispanic/Latinas (H/L) are available to guide treatment. To address this gap, we performed whole-exome sequencing (WES) and RNA sequencing on 146 tumors and WES of matched germline DNA from 140 H/L women in California. Tumor intrinsic subtype, somatic mutations, copy-number alterations, and expression profiles of the tumors were characterized and compared with data from tumors of non-Hispanic White (White) women in The Cancer Genome Atlas (TCGA). Eight genes were significantly mutated in the H/L tumors including PIK3CA, TP53, GATA3, MAP3K1, CDH1, CBFB, PTEN, and RUNX1; the prevalence of mutations in these genes was similar to that observed in White women in TCGA. Four previously reported Catalogue of Somatic Mutations in Cancer (COSMIC) mutation signatures (1, 2, 3, 13) were found in the H/L dataset, along with signature 16 that has not been previously reported in other breast cancer datasets. Recurrent amplifications were observed in breast cancer drivers including MYC, FGFR1, CCND1, and ERBB2, as well as a recurrent amplification in 17q11.2 associated with high KIAA0100 gene expression that has been implicated in breast cancer aggressiveness. In conclusion, this study identified a higher prevalence of COSMIC signature 16 and a recurrent copy-number amplification affecting expression of KIAA0100 in breast tumors from H/L compared with White women. These results highlight the necessity of studying underrepresented populations.

SIGNIFICANCE

Comprehensive characterization of genomic and transcriptomic alterations in breast tumors from Hispanic/Latina patients reveals distinct genetic alterations and signatures, demonstrating the importance of inclusive studies to ensure equitable care for patients. See related commentary by Schmit et al., p. 2443.

Equitable machine learning counteracts ancestral bias in precision medicine, improving outcomes for all

Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease [1-8]. Therapeutics and outcomes remain hidden because we lack insights that we could gain from analyzing ancestry-unbiased genomic data. To address this significant gap, we present PhyloFrame, the first-ever machine learning method for equitable genomic precision medicine. PhyloFrame corrects for ancestral bias by integrating big data tissue-specific functional interaction networks, global population variation data, and disease-relevant transcriptomic data. Application of PhyloFrame to breast, thyroid, and uterine cancers shows marked improvements in predictive power across all ancestries, less model overfitting, and a higher likelihood of identifying known cancer-related genes. The ability to provide accurate predictions for underrepresented groups, in particular, is substantially increased. These results demonstrate how AI can mitigate ancestral bias in training data and contribute to equitable representation in medical research.

Involvement of AKT/PI3K Pathway in Sanguinarine's Induced Apoptosis and Cell Cycle Arrest in Triple-negative Breast Cancer Cells

BACKGROUND/AIM

Chemotherapy resistance in triple-negative breast cancer (TNBC) cells is well documented. Therefore, it is necessary to develop safer and more effective therapeutic agents to enhance the outcomes of chemotherapeutic agents. The natural alkaloid sanguinarine (SANG) has demonstrated therapeutic synergy when coupled with chemotherapeutic agents. SANG can also induce cell cycle arrest and trigger apoptosis in various cancer cells.

MATERIALS AND METHODS

In this study, we investigated the molecular mechanism underlying SANG activity in MDA-MB-231 and MDA-MB-468 cells as two genetically different models of TNBC. We employed various assays including Alamar Blue to measure the effect of SANG on cell viability and proliferation rate, flow cytometry analysis to study the potential of the compound to induce apoptosis and cell cycle arrest, quantitative qRT PCR apoptosis array to measure the expression of different genes mediating apoptosis, and the western system was used to analyze the impact of the compound on AKT protein expression.

RESULTS

SANG lowered cell viability and disrupted cell cycle progression in both cell lines. Furthermore, S-phase cell cycle arrest-mediated apoptosis was found to be the primary contributor to cell growth inhibition in MDA-MB-231 cells. SANG-treated TNBC cells showed significantly up-regulated mRNA expression of 18 genes associated with apoptosis, including eight TNF receptor superfamily (TNFRSF), three members of the BCL2 family, and two members of the caspase (CASP) family in MDA-MB-468 cells. In MDA-MB-231 cells, two members of the TNF superfamily and four members of the BCL2 family were affected. The western study data showed the inhibition of AKT protein expression in both cell lines concurrent with up-regulated BCL2L11 gene. Our results point to the AKT/PI3K signaling pathway as one of the key mechanisms behind SANG-induced cell cycle arrest and death.

CONCLUSION

SANG shows anticancer properties and apoptosis-related gene expression changes in the two TNBC cell lines and suggests AKT/PI3K pathway implication in apoptosis induction and cell cycle arrest. Thus, we propose SANG's potential as a solitary or supplementary treatment agent against TNBC.