Differentially expressed transcripts and dysregulated signaling pathways and networks in African American breast cancer

Gene expression associated with endocrine therapy resistance in estrogen receptor-positive breast cancer

Despite endocrine therapy (ET), approximately 20-40% of Stage I-III estrogen receptor-positive breast cancer (ER + BC) patients experience recurrence. Recurrence while on ET is indicative of ET resistance. This study aimed to identify differentially expressed genes (DEGs) associated with recurrence during ET (ET resistance) and to explore gene expression differences across PAM50 molecular subtypes. Eighty tumor specimens from 79 patients treated at the City of Hope Comprehensive Cancer Center (2012-2016) were analyzed using NanoString technology. Fourteen patients (17.7%) experienced recurrence over a median follow-up of 68 months (range 35-104 months). Key upregulated DEGs in the recurrence group included EZH2 (log2 fold change[log2FC]: 0.67, p = 0.0017), WNT11 (log2FC: 1.08, p = 0.0088), ITGB6 (log2FC: 0.80, p = 0.0312), and TOP2A (log2FC: 0.79, p = 0.0381). Downregulated DEGs included SNAI2 (log2FC: - 0.63, p = 0.0055), ITPR1 (log2FC: - 0.75, p = 0.0083), CD10 (log2FC: - 0.70, p = 0.0092), PTEN (log2FC: - 0.29, p = 0.0163), VRD (log2FC: - 0.46, p = 0.0184), and WNT5A (log2FC: - 0.76, p = 0.0272). EZH2 and TOP2A were positively correlated with proliferation scores, while WNT11 and ITGB6 emerged as potential biomarkers independently associated with recurrence. These findings suggest novel biomarker candidates that could help overcome ET resistance, reduce recurrence, and improve outcomes in ER + BC.

The pertinence of resistin gene single nucleotide polymorphism G > A and its expression in oral cancer

BACKGROUND/AIM

Oral cancer (OC) is the leading cause of fatalities in Pakistan among males due to inadequate oral hygiene and chewing habits. However, genetic susceptibility patterns also play a critical role in disease progression. Since the frequency of Resistin (RETN) SNP (Single nucleotide polymorphism) rs3219175 is unknown; there is a requirement for early diagnosis of the OC. Therefore, the current study aims to determine the frequency of targeted SNP and develop a safe, simple, and fast alternative technique for better treatment using a real-time PCR assay with HRM (high-resolution melting curve) analysis.

MATERIALS AND METHODS

A case-control study was conducted on 35 Oral squamous cell carcinomas (OSCC) diagnosed patients and 35 healthy individuals. HRM and RT-PCR results were analysed by the bioinformatics analyses.

RESULTS

The frequency of RETN SNP rs3219175 genotypes GG and GA in male patients was 16 (46 %) and 5 (14 %) respectively and in females 8 (23 %) and 6 (17 %) respectively. The chi-square test of independence consummated the assessment between males and females in both control and patients. The relation between these variables was significant (p < 0.05). The interaction network of String 8.3 demonstrates strong interactions at a high confidence score, which helps to characterize functional disorders that may be a causative factor for oral pathology. Reactome and KEGG data were acquired to rule out the pathway involvement of the targeted gene. MuPIT software was used to identify the 3D structure or RETN and their expected mutation effect.

CONCLUSION

This study provides baseline data regarding the frequency of RETN SNP rs3219175 among the Pakistani population. For further clarification of their stage in cancer emergence and growth, large-scale studies must be conducted. This study might be helpful in the precision medicine approach and provide better therapeutic for OSCC patients.

Impact of Structural Racism and Social Determinants of Health on Disparities in Breast Cancer Mortality

The striking ethnic and racial disparities in breast cancer mortality are not explained fully by pathologic or clinical features. Structural racism contributes to adverse conditions that promote cancer inequities, but the pathways by which this occurs are not fully understood. Social determinants of health, such as economic status and access to care, account for a portion of this variability, yet interventions designed to mitigate these barriers have not consistently led to improved outcomes. Based on the current evidence from multiple disciplines, we describe a conceptual model in which structural racism and racial discrimination contribute to increased mortality risk in diverse groups of patients by promoting adverse social determinants of health that elevate exposure to environmental hazards and stress; these exposures in turn contribute to epigenetic and immune dysregulation, thereby altering breast cancer outcomes. Based on this model, opportunities and challenges arise for interventions to reduce racial and ethnic disparities in breast cancer mortality.

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.

The interrelationship between obesity and race in breast cancer prognosis: a prospective cohort study

BACKGROUND

Obesity is associated with an increased breast cancer risk in postmenopausal women and may contribute to worse outcomes. Black women experience higher obesity and breast cancer mortality rates than non-Black women. We examined associations between race, obesity, and clinical tumor stage with breast cancer prognosis.

METHODS

We conducted a prospective cohort study in 1,110 breast cancer patients, using univariable and multivariable Cox regression analyses to evaluate the effects of obesity, race/ethnicity, and clinical tumor stage on progression-free and overall survival (PFS and OS).

RESULTS

22% of participants were Black, 64% were Hispanic White, and 14% were non-Hispanic White or another race. 39% of participants were obese (body mass index [BMI] ≥ 30 kg/m2). In univariable analyses, tumor stage III-IV was associated with worse PFS and OS compared to tumor stage 0-II (hazard ratio [HR] = 4.68, 95% confidence interval [CI] = 3.52-6.22 for PFS and HR = 5.92, 95% CI = 4.00-8.77 for OS). Multivariable analysis revealed an association between Black race and worse PFS in obese (HR = 2.19, 95% CI = 1.06-4.51) and non-obese (HR = 2.11, 95% CI = 1.05-4.21) women with tumors staged 0-II. Obesity alone was not associated with worse PFS or OS.

CONCLUSIONS

Results suggest a complex interrelationship between obesity and race in breast cancer prognosis. The association between the Black race and worse PFS in tumor stages 0-II underscores the importance of early intervention in this group. Future studies are warranted to evaluate whether alternative measures of body composition and biomarkers are better prognostic indicators than BMI among Black breast cancer survivors.

Disparities in care of older adults of color with cancer: A narrative review

This review describes the barriers and challenges faced by older adults of color with cancer and highlights methods to improve their overall care. In the next decade, cancer incidence rates are expected to increase in the United States for people aged ≥65 years. A large proportion will be older adults of color who often have worse outcomes than older White patients. Many issues contribute to racial disparities in older adults, including biological factors and social determinants of health (SDOH) related to healthcare access, socioeconomic concerns, systemic racism, mistrust, and the neighborhood where a person lives. These disparities are exacerbated by age-related challenges often experienced by older adults, such as decreased functional status, impaired cognition, high rates of comorbidities and polypharmacy, poor nutrition, and limited social support. Additionally, underrepresentation of both patients of color and older adults in cancer clinical research results in a lack of adequate data to guide the management of these patients. Use of geriatric assessments (GA) can aid providers in uncovering age-related concerns and personalizing interventions for older patients. Research demonstrates the ability of GA-directed care to result in fewer treatment-related toxicities and improved quality of life, thus supporting the routine incorporation of validated GA into these patients' care. GA can be enhanced by including evaluation of SDOH, which can help healthcare providers understand and address the needs of older adults of color with cancer who face disparities related to their age and race.

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.

The Interrelationship between Obesity and Race in Breast Cancer Prognosis: A Prospective Cohort Study

Purpose

Obesity is associated with an increased breast cancer risk in postmenopausal women and may contribute to worse outcomes. Black women experience higher obesity and breast cancer mortality rates than non-Black women. We examined associations between race, obesity, and clinical tumor stage with breast cancer prognosis.

Methods

We conducted a prospective cohort study in 1,110 breast cancer patients, using univariable and multivariable Cox regression analyses to evaluate the effects of obesity, race/ethnicity, and clinical tumor stage on progression-free and overall survival (PFS and OS).

Results

22% of participants were Black, 64% were Hispanic White, and 14% were non-Hispanic White or another race. 39% of participants were obese (body mass index [BMI] ≥ 30 kg/m2). In univariable analyses, tumor stage III-IV was associated with worse PFS and OS compared to tumor stage 0-II (hazard ratio [HR] = 4.68, 95% confidence interval [CI] = 3.52-6.22 for PFS and HR = 5.92, 95% CI = 4.00-8.77 for OS). Multivariable analysis revealed an association between Black race and worse PFS in obese (HR = 2.19, 95% CI = 1.06-4.51) and non-obese (HR = 2.11, 95% CI = 1.05-4.21) women with tumors staged 0-II. Obesity alone was not associated with worse PFS or OS.

Conclusion

Results suggest a complex interrelationship between obesity and race in breast cancer prognosis. The association between Black race and worse PFS in tumor stages 0-II underscores the importance of early intervention in this group. Future studies are warranted to evaluate whether alternative measures of body composition and biomarkers are better prognostic indicators than BMI among Black breast cancer survivors.

Anticancer Effects of Fucoxanthin through Cell Cycle Arrest, Apoptosis Induction, and Angiogenesis Inhibition in Triple-Negative Breast Cancer Cells

The absence of progesterone receptors, estrogen receptors, and human epidermal growth factor receptor-2 restricts the therapy choices for treating triple-negative breast cancer (TNBC). Moreover, conventional medication is not highly effective in treating TNBC, and developing effective therapeutic agents from natural bioactive compounds is a viable option. In this study, the anticancer effects of the natural compound fucoxanthin were investigated in two genetically different models of TNBC cells: MDA-MB-231 and MDA-MB-468 cells. Fucoxanthin had a significant anticancer effect in both cell lines at a concentration range of 1.56-300 µM. The compound decreased cell viability in both cell lines with higher potency in MDA-MB-468 cells. Meanwhile, proliferation assays showed similar antiproliferative effects in both cell lines after 48 h and 72 h treatment periods. Flow cytometry and Annexin V-FITC apoptosis assay revealed the ability of fucoxanthin to induce apoptosis in MDA-MB-231 only. Cell cycle arrest analysis showed that the compound also induced cell cycle arrest at the G1 phase in both cell lines, accompanied by more cell cycle arrest in MDA-MB-231 cells at S-phase and a higher cell cycle arrest in the MDA-MB-468 cells at G2-phase. Wound healing and migration assay showed that in both cell lines, fucoxanthin prevented migration, but was more effective in MDA-MB-231 cells in a shorter time. In both angiogenic cytokine array and RT-PCR studies, fucoxanthin (6.25 µM) downregulated VEGF-A and -C expression in TNF-α-stimulated (50 ng/mL) MDA-MB-231, but not in MDA-MB-468 cells on the transcription and protein levels. In conclusion, this study shows that fucoxanthin was more effective in MDA-MB-231 TNBC cells, where it can target VEGF-A and VEGF-C, inhibit cell proliferation and cell migration, and induce cell cycle arrest and apoptosis-the most crucial cellular processes involved in breast cancer development and progression.

Ethnic disparities in the immune microenvironment of triple negative breast cancer and its role in therapeutic outcomes

In 2020, newly diagnosed breast cancer (BC) cases surpassed that of lung cancer among women, making it the most common female cancer globally. In spite of recent increases in incidence rates, mortality due to BC has declined since 1989. These declines have been attributed to advancements in treatment modalities as well as increased mammography surveillance. Despite these advances, African American (AA) women are 40% more likely to die from BC than Caucasian women. Multifactorial etiology has been implicated in the disparity of BC mortality rates among AA women. As an example, AA women have a disproportionate incidence of triple negative breast cancer (TNBC), which has a poor prognosis and marginal treatment options. Increasingly, the tumor microenvironment (TME) has gained relevance as it relates to primary tumor progression, metastasis and treatment possibilities. The treatment outcomes or pathological complete response (pCR) in TNBC among AA women are affected by differences in TME. The TME of AA women exhibit several variances in acellular and cellular components associated with pro-tumorigenic effects. For example, increased levels of the adipocyte-related hormone, resistin, the pro-inflammatory cytokine, IL-6, and the CC chemokine, CCL2, within the TME of AA women gives rise to an increased density of M2 macrophages, also known as tumor-associated macrophages. Elevated levels of vascular endothelial growth factor in the TME of AA women increase the vascular density or vascularity, which facilitate aggressive tumor growth and metastasis. Furthermore, a pro-tumorigenic TME is supported by increased levels of the CXC chemokine, CXCL12 that results in the recruitment of regulatory T lymphocytes (Tregs ). Due to these and other differences in the TME of AA women, precision oncology can target specific aspects of the TME that may contribute to a poorer prognosis. In addition to the discrepancies in the TME, AA women face socio-economic barriers that limit their ability to access state-of-the-art, novel therapies against metastatic TNBC. In this review, we will provide a brief overview of the tumor immune microenvironment, immune-based treatment options for TNBC and their potential to decrease health disparities due to ethnicity.

Evaluation of breast tumor morphologies from African American and Caucasian patients

The primary aim of this research was to investigate potential differences of breast tumor morphologies across African American and Caucasian racial groups by utilizing machine learning (ML) and artificial intelligence (AI) methods. While breast cancer disparities can partially be attributed to social determinants of health, tumor biology also contributes to survival outcomes. The rate of breast tumor growth is largely dependent on the extracellular matrix (ECM). Current research suggests the cellular components of the ECM may vary among racial and ethnic populations, and this may contribute to the incidence of cancer in African Americans. We utilized a supervised AI method to evaluate morphological differences between African American and Caucasian breast cancer tumors. Images used for analysis were downloaded from the Cancer Genome Atlas (TCGA) biorepository stored in the NIH Genomic Data Commons (GDC) data portal. We designed an ML classifier using the AlexNet model provided in PyTorch's torchvision package. The model was pre-trained and adapted via transfer learning resulting in a classification accuracy of 92.1% when using our breast cancer tumor image database split into 80% of training set and 20% of testing set. We interpreted the results of the AlexNet and ResNet50 models using LIME and saliency mapping as the explainers. Based on the images from our bi-racial testing set, this study confirmed significant variations of tumor and ECM regions in the different racial groups evaluated. Based on these findings, further analysis and characterization may provide new insight into disparities associated with the incidence of breast cancer.

Outcomes in breast cancer-does ethnicity matter?

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

Identifying Biomarkers Using Support Vector Machine to Understand the Racial Disparity in Triple-Negative Breast Cancer

With the properties of aggressive cancer and heterogeneous tumor biology, triple-negative breast cancer (TNBC) is a type of breast cancer known for its poor clinical outcome. The lack of estrogen, progesterone, and human epidermal growth factor receptor in the tumors of TNBC leads to fewer treatment options in clinics. The incidence of TNBC is higher in African American (AA) women compared with European American (EA) women with worse clinical outcomes. The significant factors responsible for the racial disparity in TNBC are socioeconomic lifestyle and tumor biology. The current study considered the open-source gene expression data of triple-negative breast cancer samples' racial information. We implemented a state-of-the-art classification Support Vector Machine (SVM) method with a recurrent feature elimination approach to the gene expression data to identify significant biomarkers deregulated in AA women and EA women. We also included Spearman's rho and Ward's linkage method in our feature selection workflow. Our proposed method generates 24 features/genes that can classify the AA and EA samples 98% accurately. We also performed the Kaplan-Meier analysis and log-rank test on the 24 features/genes. We only discussed the correlation between deregulated expression and cancer progression with a poor survival rate of 2 genes, KLK10 and LRRC37A2, out of 24 genes. We believe that further improvement of our method with a higher number of RNA-seq gene expression data will more accurately provide insight into racial disparity in TNBC.

Genetic ancestry, differential gene expression, and survival in pediatric B-cell acute lymphoblastic leukemia

BACKGROUND

Black children have lower incidence yet worse survival than White and Latinx children with B-cell acute lymphoblastic leukemia (B-ALL). It is unclear how reported race/ethnicity (RRE) is associated with death in B-ALL after accounting for differentially expressed genes associated with genetic ancestry.

METHODS

Using Phase 1 and 2 NCI TARGET B-ALL cases (N = 273; RRE-Black = 21, RRE-White = 162, RRE-Latinx = 69, RRE-Other = 9, RRE-Unknown = 12), we estimated proportions of African (AFR), European (EUR), and Amerindian (AMR) genetic ancestry. We estimated hazard ratios (HR) and 95% confidence intervals (95% CI) between ancestry and death while adjusting for RRE and clinical measures. We identified genes associated with genetic ancestry and adjusted for them in RRE and death associations.

RESULTS

Genetic ancestry varied within RRE (RRE-Black, AFR proportion: Mean: 78.5%, Range: 38.2%-93.6%; RRE-White, EUR proportion: Mean: 94%, Range: 1.6%-99.9%; RRE-Latinx, AMR proportion: Mean: 52.0%, Range: 1.2%-98.7%). We identified 10, 1, and 6 differentially expressed genes (p_adjusted  <0.05) associated with AFR, AMR, and EUR ancestry proportion, respectively. We found AMR and AFR ancestry were statistically significantly associated with death (AMR each 10% HR: 1.05, 95% CI: 1.03-1.17, AFR each 10% increase HR: 1.03, 95% CI:1.01-1.19). RRE differences in the risk of death were larger in magnitude upon adjustment for genes associated with genetic ancestry for RRE-Black, but not RRE-Latinx children (RRE-Black HR: 3.35, 95% CI: 1.31, 8.53; RRE-Latinx HR: 1.47, 0.88-2.45).

CONCLUSIONS

Our work highlights B-ALL survival differences by RRE after adjusting for ancestry differentially expressed genes suggesting other factors impacting survival are important.

Altered Adipokine Expression in Tumor Microenvironment Promotes Development of Triple Negative Breast Cancer

Obesity is a remarkably important factor for breast carcinogenesis and aggressiveness. The implication of increased BMI in triple negative breast cancer (TNBC) development is also well established. A malignancy-promoting role of the adipose tissue has been supposed, where the adipocytes that constitute the majority of stromal cells release pro-inflammatory cytokines and growth factors. Alterations in adipokines and their receptors play significant roles in breast cancer initiation, progression, metastasis, and drug response. Classic adipokines, such as leptin, adiponectin, and resistin, have been extensively studied in breast cancer and connected with breast cancer risk and progression. Notably, new molecules are constantly being discovered and the list is continuously growing. Additionally, substantial progress has been made concerning their differential expression in association with clinical and pathological parameters of tumors and the prognostic and predictive value of their dysregulation in breast cancer carcinogenesis. However, evidence regarding the mechanisms by which adipose tissue is involved in the development of TNBC is lacking. In the present article we comment on current data on the suggested involvement of these mediators in breast cancer development and progression, with particular emphasis on TNBC, to draw attention to the design of novel targeted therapies and biomarkers.

Chemokine receptors differentially expressed by race category and molecular subtype in the breast cancer TCGA cohort

Racial disparities in mortality due to metastasis remain significant among breast cancer patients. Chemokine receptors contribute to breast tumors and metastatic outcome. We explored for significant differences in chemokine receptor expression in breast tumors from Black, Asian, and White patients in The Cancer Genome Atlas. We show that despite sharing the same molecular subtype, expression of the chemokine receptors ACKR1, CCR3, CCR6, CCRL1, CCRL2, CXCR1, CXCR2, CXCR4, CXCR6, and CXC3CR1 was significantly different depending on racial group. For patients with triple negative breast cancer, CCR3 was higher in Black versus White and CCRL2 was higher in Asian versus White. In luminal A tumors, ACKR1 was lower in Asian versus White, CCR3 was higher in Black versus White, and CCR6 and CXC3CR1 were lower in Black versus White. In luminal B tumors, CCRL2 was lower in Black versus White, CXCR1 and CXC3CR1 were lower in Asian versus White, and CXCR2 was lower in Black and Asian versus White. In HER2 enriched tumors, CCR3 was higher in Black versus White and CXCR4 lower in Asian versus White. CCR3, CCR6, and CXCR6 associated with worse patient survival. These findings can inform improved treatment strategies to decrease racial disparities in breast cancer burden.

Interface between obesity with dysfunctional metabolism and inflammation, and the triple-negative breast cancer in African American women

Obesity has dramatically increased over the past fifty years. In the last decade, it has been noted that augmented body mass, metabolic abnormalities, and the relevant "obese" tumor microenvironment (TME) are connected with signaling molecular networks, which in turn, may contribute to aggressive tumor biology in some patients with breast malignancies. This article presents the associations between obesity, metabolic derangements, inflammatory processes in the adipose tissue or TME, and aggressive behavior of triple-negative breast cancer (TNBC) in African American (AA) women. It also describes some abnormal molecular signaling patterns in the "obese" TME with relevance to TNBC biology. Ethnic disparities in TNBC can be due to a variety of biological features (e.g., genetic mutations and tumor heterogeneity), comorbidities (e.g., cardio-metabolic diseases, including diabetes mellitus), and reproductive factors (e.g., multiparty or short breastfeeding period). Such a constellation of biological variables potentially leads to the association between obesity, metabolic derangements, inflammatory processes in the adipose tissue or TME, and aggressive behavior of TNBC in AA women. Since the TNBC and its TME can display very aggressive behavior, it is crucial that the afflicted AA women make efforts to maintain healthy body weight, "flexible" metabolism, and a well-functioning immune system. Further studies are merited to explore the multi-disciplinary factors that can affect TNBC prevention, management, and outcomes to optimize treatment strategies and survival among AA women.

Biological Network Inference With GRASP: A Bayesian Network Structure Learning Method Using Adaptive Sequential Monte Carlo

Bayesian networks (BNs) provide a probabilistic, graphical framework for modeling high-dimensional joint distributions with complex correlation structures. BNs have wide applications in many disciplines, including biology, social science, finance and biomedical science. Despite extensive studies in the past, network structure learning from data is still a challenging open question in BN research. In this study, we present a sequential Monte Carlo (SMC)-based three-stage approach, GRowth-based Approach with Staged Pruning (GRASP). A double filtering strategy was first used for discovering the overall skeleton of the target BN. To search for the optimal network structures we designed an adaptive SMC (adSMC) algorithm to increase the quality and diversity of sampled networks which were further improved by a third stage to reclaim edges missed in the skeleton discovery step. GRASP gave very satisfactory results when tested on benchmark networks. Finally, BN structure learning using multiple types of genomics data illustrates GRASP’s potential in discovering novel biological relationships in integrative genomic studies.

Quantitative assessment of the immune microenvironment in African American Triple Negative Breast Cancer: a case-control study

PURPOSE

Triple negative breast cancer (TNBC) is more common in African American (AA) than Non-AA (NAA) population. We hypothesize that tumor microenvironment (TME) contributes to this disparity. Here, we use multiplex quantitative immunofluorescence to characterize the expression of immunologic biomarkers in the TME in both populations.

PATIENTS AND METHODS

TNBC tumor resection specimen tissues from a 100-patient case: control cohort including 49 AA and 51 NAA were collected. TME markers including CD45, CD14, CD68, CD206, CD4, CD8, CD20, CD3, Ki67, GzB, Thy1, FAP, aSMA, CD34, Col4, VWF and PD-L1 we quantitatively assessed in every field of view. Mean expression levels were compared between cases and controls.

RESULTS

Although no significant differences were detected in individual lymphoid and myeloid markers, we found that infiltration with CD45+ immune cells (p = 0.0102) was higher in TNBC in AA population. AA TNBC tumors also had significantly higher level of lymphocytic infiltration defined as CD45+ CD14- cells (p = 0.0081). CD3+ T-cells in AA tumors expressed significantly higher levels of Ki67 (0.0066) compared to NAAs, indicating that a higher percentage of AA tumors contained activated T-cells. All other biomarkers showed no significant differences between the AA and NAA group.

CONCLUSIONS

While the TME in TNBC is rich in immune cells in both racial groups, there is a numerical increase in lymphoid infiltration in AA compared to NAA TNBC. Significantly, higher activated T cells seen in AA patients raises the possibility that there may be a subset of AA patients with improved response to immunotherapy.

Concomitant activation of GLI1 and Notch1 contributes to racial disparity of human triple negative breast cancer progression

Mortality from triple negative breast cancer (TNBC) is significantly higher in African American (AA) women compared to White American (WA) women emphasizing ethnicity as a major risk factor; however, the molecular determinants that drive aggressive progression of AA-TNBC remain elusive. Here, we demonstrate for the first time that AA-TNBC cells are inherently aggressive, exhibiting elevated growth, migration, and cancer stem-like phenotype compared to WA-TNBC cells. Meta-analysis of RNA-sequencing data of multiple AA- and WA-TNBC cell lines shows enrichment of GLI1 and Notch1 pathways in AA-TNBC cells. Enrichment of GLI1 and Notch1 pathway genes was observed in AA-TNBC. In line with this observation, analysis of TCGA dataset reveals a positive correlation between GLI1 and Notch1 in AA-TNBC and a negative correlation in WA-TNBC. Increased nuclear localization and interaction between GLI1 and Notch1 is observed in AA-TNBC cells. Of importance, inhibition of GLI1 and Notch1 synergistically improves the efficacy of chemotherapy in AA-TNBC cells. Combined treatment of AA-TNBC-derived tumors with GANT61, DAPT, and doxorubicin/carboplatin results in significant tumor regression, and tumor-dissociated cells show mitigated migration, invasion, mammosphere formation, and CD44⁺/CD24^- population. Indeed, secondary tumors derived from triple-therapy-treated AA-TNBC tumors show diminished stem-like phenotype. Finally, we show that TNBC tumors from AA women express significantly higher level of GLI1 and Notch1 expression in comparison to TNBC tumors from WA women. This work sheds light on the racial disparity in TNBC, implicates the GLI1 and Notch1 axis as its functional mediators, and proposes a triple-combination therapy that can prove beneficial for AA-TNBC.

A panel of miRNAs as prognostic markers for African-American patients with triple negative breast cancer

BACKGROUND

To investigate the global expression profile of miRNAs, their impact on cellular signaling pathways, and their association with poor prognostic parameters in African-American (AA) patients with triple negative breast cancer (TNBC).

METHODS

Twenty-five samples of AA TNBC patients were profiled for global miRNA expression and stratified considering three clinical-pathological parameters: tumor size, lymph node (LN), and recurrence (REC) status. Differential miRNA expression analysis was performed for each parameter, and their discriminatory power was determined by Receiver Operating Characteristic (ROC) curve analysis. KMplotter was assessed to determine the association of the miRNAs with survival, and functional enrichment analysis to determine the main affected pathways and miRNA/mRNA target interactions.

RESULTS

A panel of eight, 23 and 27 miRNAs were associated with tumor size, LN, and REC status, respectively. Combined ROC analysis of two (miR-2117, and miR-378c), seven (let-7f-5p, miR-1255b-5p, miR-1268b, miR-200c-3p, miR-520d, miR-527, and miR-518a-5p), and three (miR-1200, miR-1249-3p, and miR-1271-3p) miRNAs showed a robust discriminatory power based on tumor size (AUC = 0.917), LN (AUC = 0.945) and REC (AUC = 0.981) status, respectively. Enrichment pathway analysis revealed their involvement in proteoglycans and glycan and cancer-associated pathways. Eight miRNAs with deregulated expressions in patients with large tumor size, positive LN metastasis, and recurrence were significantly associated with lower survival rates. Finally, the construction of miRNA/mRNA networks based in experimentally validated mRNA targets, revealed nodes of critical cancer genes, such as AKT1, BCL2, CDKN1A, EZR and PTEN.

CONCLUSIONS

Altogether, our data indicate that miRNA deregulated expression is a relevant biological factor that can be associated with the poor prognosis in TNBC of AA patients, by conferring to their TNBC cells aggressive phenotypes that are reflected in the clinical characteristics evaluated in this study.

Disparities in Breast Cancer Associated With African American Identity

Persistent disparities in the burden of breast cancer between African Americans and White Americans have been documented over many decades. Features characterizing breast cancer in the African American community include a 40% higher mortality rate, younger age distribution, greater advanced-stage distribution, increased risk of biologically aggressive disease such as the triple-negative phenotype, and increased incidence of male breast cancer. Public health experts, genetics researchers, clinical trialists, multidisciplinary oncology teams, and advocates must collaborate to comprehensively address the multifactorial etiology of and remedies for breast cancer disparities. Efforts to achieve breast health equity through improved access to affordable, high-quality care are especially imperative in the context of the COVID-19 pandemic and its disproportionately high economic toll on African Americans.

Long non-coding RNAs and their targets as potential biomarkers in breast cancer

Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease-specific biomarkers. Recently, long non-coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post-transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co-expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co-expressed lncRNAs and their cis- and trans-regulating mRNA targets which include RP11-108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future.

Therapeutic Strategies for Metastatic Triple-Negative Breast Cancers: From Negative to Positive

Metastatic triple-negative breast cancer (TNBC) is a distinct and immensely complex form of breast cancer. Among all subtypes of breast cancers, TNBC has a comparatively high rate of relapse, a high rate of distant metastasis, and poor overall survival after standard chemotherapy. Chemotherapy regimens are an essential component of the management of this estrogen receptor-negative, progesterone receptor-negative, and epidermal growth factor receptor2 negative subtype of breast cancers. Chemotherapy is critical for preventing the recurrence of the disease and for achieving long-term survival. Currently, a couple of agents are approved for the management of this disease, including chemotherapy like eribulin, targeted therapy like PARP inhibitor, as well as an antibody-drug conjugate (ADC) to target TROP2. Like many other metastatic cancers, immune checkpoint inhibitors (ICIs) have also been approved for TNBC patients with PD-L1 positive tumors and high tumor mutational burden. In this review article, we discuss these newly approved and promising novel agents that may change the therapeutic landscape for advanced/metastatic TNBC patients.

Ancestry-associated transcriptomic profiles of breast cancer in patients of African, Arab, and European ancestry

Breast cancer largely dominates the global cancer burden statistics; however, there are striking disparities in mortality rates across countries. While socioeconomic factors contribute to population-based differences in mortality, they do not fully explain disparity among women of African ancestry (AA) and Arab ancestry (ArA) compared to women of European ancestry (EA). In this study, we sought to identify molecular differences that could provide insight into the biology of ancestry-associated disparities in clinical outcomes. We applied a unique approach that combines the use of curated survival data from The Cancer Genome Atlas (TCGA) Pan-Cancer clinical data resource, improved single-nucleotide polymorphism-based inferred ancestry assignment, and a novel breast cancer subtype classification to interrogate the TCGA and a local Arab breast cancer dataset. We observed an enrichment of BasalMyo tumors in AA patients (38 vs 16.5% in EA, p = 1.30E - 10), associated with a significant worse overall (hazard ratio (HR) = 2.39, p = 0.02) and disease-specific survival (HR = 2.57, p = 0.03). Gene set enrichment analysis of BasalMyo AA and EA samples revealed differences in the abundance of T-regulatory and T-helper type 2 cells, and enrichment of cancer-related pathways with prognostic implications (AA: PI3K-Akt-mTOR and ErbB signaling; EA: EGF, estrogen-dependent and DNA repair signaling). Strikingly, AMPK signaling was associated with opposing prognostic connotation (AA: 10-year HR = 2.79, EA: 10-year HR = 0.34). Analysis of ArA patients suggests enrichment of BasalMyo tumors with a trend for differential enrichment of T-regulatory cells and AMPK signaling. Together, our findings suggest that the disparity in the clinical outcome of AA breast cancer patients is likely related to differences in cancer-related and microenvironmental features.

Transcriptomic Profiling of Buffalo Spermatozoa Reveals Dysregulation of Functionally Relevant mRNAs in Low-Fertile Bulls

Although, it is known that spermatozoa harbor a variety of RNAs that may influence embryonic development, little is understood about sperm transcriptomic differences in relation to fertility, especially in buffaloes. In the present study, we compared the differences in sperm functional attributes and transcriptomic profile between high- and low-fertile buffalo bulls. Sperm membrane and acrosomal integrity were lower (P < 0.05), while protamine deficiency and lipid peroxidation were higher (P < 0.05) in low- compared to high-fertile bulls. Transcriptomic analysis using mRNA microarray technology detected a total of 51,282 transcripts in buffalo spermatozoa, of which 4,050 transcripts were differentially expressed, and 709 transcripts were found to be significantly dysregulated (P < 0.05 and fold change >1) between high- and low-fertile bulls. Majority of the dysregulated transcripts were related to binding activity, transcription, translation, and metabolic processes with primary localization in the cell nucleus, nucleoplasm, and in cytosol. Pathways related to MAPK signaling, ribosome pathway, and oxidative phosphorylation were dysregulated in low-fertile bull spermatozoa. Using bioinformatics analysis, we observed that several genes related to sperm functional attributes were significantly downregulated in low-fertile bull spermatozoa. Validation of the results of microarray analysis was carried out using real-time qPCR expression analysis of selected genes (YBX1, ORAI3, and TFAP2C). The relative expression of these genes followed the same trend in both the techniques. Collectively, this is the first study to report the transcriptomic profile of buffalo spermatozoa and to demonstrate the dysregulation of functionally relevant transcripts in low-fertile bull spermatozoa. The results of the present study open up new avenues for understanding the etiology for poor fertility in buffalo bulls and to identify fertility biomarkers.

Racial Disparities in Triple Negative Breast Cancer: A Review of the Role of Biologic and Non-biologic Factors

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer that lacks expression of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2). TNBC constitutes about 15–30 percent of all diagnosed invasive breast cancer cases in the United States. African-American (AA) women have high prevalence of TNBC with worse clinical outcomes than European-American (EA) women. The contributing factors underlying racial disparities have been divided into two major categories based on whether they are related to lifestyle (non-biologic) or unrelated to lifestyle (biologic). Our objective in the present review article was to understand the potential interactions by which these risk factors intersect to drive the initiation and development of the disparities resulting in the aggressive TNBC subtypes in AA women more likely than in EA women. To reach our goal, we conducted literature searches using MEDLINE/PubMed to identify relevant articles published from 2005 to 2019 addressing breast cancer disparities primarily among AA and EA women in the United States. We found that disparities in TNBC may be attributed to racial differences in biological factors, such as tumor heterogeneity, population genetics, somatic genomic mutations, and increased expression of genes in AA breast tumors which have direct link to breast cancer. In addition, a large number of non-biologic factors, including socioeconomic deprivation adversities associated with poverty, social stress, unsafe neighborhoods, lack of healthcare access and pattern of reproductive factors, can promote comorbid diseases such as obesity and diabetes which may adversely contribute to the aggression of TNBC biology in AA women. Further, the biological risk factors directly linked to TNBC in AA women may potentially interact with non-biologic factors to promote a higher prevalence of TNBC, more aggressive biology, and poor survival. The relative contributions of the biologic and non-biologic factors and their potential interactions is essential to our understanding of disproportionately high burden and poor survival rates of AA women with TNBC.

Cancer stem cells: Culprits in endocrine resistance and racial disparities in breast cancer outcomes

Breast cancer stem cells (BCSCs) promote endocrine therapy (ET) resistance, also known as endocrine resistance in hormone receptor (HR) positive breast cancer. Endocrine resistance occurs via mechanisms that are not yet fully understood. In vitro, in vivo and clinical data suggest that signaling cascades such as Notch, hypoxia inducible factor (HIF), and integrin/Akt promote BCSC-mediated endocrine resistance. Once HR positive breast cancer patients relapse on ET, targeted therapy agents such as cyclin dependent kinase inhibitors are frequently implemented, though secondary resistance remains a threat. Here, we discuss Notch, HIF, and integrin/Akt pathway regulation of BCSC activity and potential strategies to target these pathways to counteract endocrine resistance. We also discuss a plausible link between elevated BCSC-regulatory gene levels and reduced survival observed among African American women with basal-like breast cancer which lacks HR expression. Should future studies reveal a similar link for patients with luminal breast cancer, then the use of agents that impede BCSC activity could prove highly effective in improving clinical outcomes among African American breast cancer patients.

Triage of documents containing protein interactions affected by mutations using an NLP based machine learning approach

BACKGROUND

Information on protein-protein interactions affected by mutations is very useful for understanding the biological effect of mutations and for developing treatments targeting the interactions. In this study, we developed a natural language processing (NLP) based machine learning approach for extracting such information from literature. Our aim is to identify journal abstracts or paragraphs in full-text articles that contain at least one occurrence of a protein-protein interaction (PPI) affected by a mutation.

RESULTS

Our system makes use of latest NLP methods with a large number of engineered features including some based on pre-trained word embedding. Our final model achieved satisfactory performance in the Document Triage Task of the BioCreative VI Precision Medicine Track with highest recall and comparable F1-score.

CONCLUSIONS

The performance of our method indicates that it is ideally suited for being combined with manual annotations. Our machine learning framework and engineered features will also be very helpful for other researchers to further improve this and other related biological text mining tasks using either traditional machine learning or deep learning based methods.

Maximizing the reusability of gene expression data by predicting missing metadata

Reusability is part of the FAIR data principle, which aims to make data Findable, Accessible, Interoperable, and Reusable. One of the current efforts to increase the reusability of public genomics data has been to focus on the inclusion of quality metadata associated with the data. When necessary metadata are missing, most researchers will consider the data useless. In this study, we developed a framework to predict the missing metadata of gene expression datasets to maximize their reusability. We found that when using predicted data to conduct other analyses, it is not optimal to use all the predicted data. Instead, one should only use the subset of data, which can be predicted accurately. We proposed a new metric called Proportion of Cases Accurately Predicted (PCAP), which is optimized in our specifically-designed machine learning pipeline. The new approach performed better than pipelines using commonly used metrics such as F1-score in terms of maximizing the reusability of data with missing values. We also found that different variables might need to be predicted using different machine learning methods and/or different data processing protocols. Using differential gene expression analysis as an example, we showed that when missing variables are accurately predicted, the corresponding gene expression data can be reliably used in downstream analyses.

Genetic factors associated with cancer racial disparity - an integrative study across twenty-one cancer types

It is well known that different racial groups have significantly different incidence and mortality rates for certain cancers. It has been suggested that biological factors play a major role in these cancer racial disparities. Previous studies on the biological factors contributing to cancer racial disparity have generated a very large number of candidate factors, although there is modest agreement among the results of the different studies. Here, we performed an integrative analysis using genomic data of 21 cancer types from TCGA, GTEx, and the 1000 Genomes Project to identify biological factors contributing to racial disparity in cancer. We also built a companion website with additional results for cancer researchers to freely mine. Our study identified genes, gene families, and pathways displaying similar differential expression patterns between different racial groups across multiple cancer types. Among them, XKR9 gene expression was found to be significantly associated with overall survival for all cancers combined as well as for several individual cancers. Our results point to the interesting hypothesis that XKR9 could be a novel drug target for cancer immunotherapy. Bayesian network modeling showed that XKR9 is linked to important cancer-related genes, including FOXM1, cyclin B1, and RB1CC1 (RB1 regulator). In addition, metabolic pathways, neural signaling pathways, and several cancer-related gene families were found to be significantly associated with cancer racial disparities for multiple cancer types. Single nucleotide polymorphisms (SNPs) discovered through integrating data from the TCGA, GTEx, and 1000 Genomes databases provide biologists the opportunity to test highly promising, targeted hypotheses to gain a deeper understanding of the genetic drivers of cancer racial disparity and cancer biology in general.

miR-452 Reverses Abnormal Glycosylation Modification of ERα and Estrogen Resistance in TNBC (Triple-Negative Breast Cancer) Through Targeting UGT1A1

Background: The breast epithelial cells in patients with triple-negative breast cancer (TNBC) actually have specific estrogen receptor (ER) expression, and the abnormal glycosylation of UGT1A1 in TNBC cells resulted in abnormal expression and function of ERα through regulating the modification of ERα. Therefore, our study targets the role of UGT1A1 expression, then glycosylation modification of ERα (estrogen receptor α) and estrogen resistance in development of TNBC.

Methods: The differential expression of mRNA and miRNA in TNBC tissues was tested. Luciferase activity was analyzed in TNBC cells treated with miR-452. Moreover, the human mammary gland and TNBC cell lines were dealt with estrogen and miR-452 or its inhibitors, then proliferation ability was further determined. Moreover, the role of interaction between UGT1A1 and ERα in the glycosylation modification of ERα and UGT activity, and metabolism of estrogen were assessed. The effects of miR-452 on TNBC by improving abnormal glycosylation modification of ERα by targeting UGT1A1 and estrogen resistance were studied in vitro and in vivo.

Results: The expression level of UGT1A1 in TNBC tumor tissues was higher than its matched para-tumorous tissues, but the miR-452 expression was opposite. The glycosylation modification site of ERα expressed in TNBC cells was different from that of normal mammary epithelial cells. The estrogen 17β-estradiol (E2) significantly promoted mitotic entry of TNBC cells. The interaction between UGT1A1 and ERα affected the expression level of each other, as well as the UGT enzyme activity and proliferation of TNBC cells. UGT1A1 induced production of intracellular estrogens and TNBC proliferation, but it could be reversed by overexpression of ERα. Upregulation of ERα caused the downregulation of UGT1A1 and marked decrease of intracellular estrogen products, and then suppressed TNBC proliferation. Moreover, UGT1A1 was the target gene of miR-452; miR-452 antagomir restrained TNBC xenograft.

Conclusion: Our results demonstrated that estrogen was a positive factor in the proliferation of TNBC cells at onset of mitosis through accentuating the expression and enzyme activity of UGT1A1. However, miR-452 targeted to UGT1A1, then regulated glycosylation modification of ERα, estrogen metabolism, and TNBC development associated with estrogen resistance.

Resistin: An inflammatory cytokine with multi-faceted roles in cancer

Systemic and organ-confined inflammation has been associated with cancer development and progression. Resistin, initially described as an adipocyte-derived cytokine in mice, is mostly expressed by the macrophages in humans. It has potent pro-inflammatory properties, and its elevated serum levels are detected in cancer patients. Aberrant expression of resistin receptors is also reported in several malignancies and associated with aggressive clinicopathological features. Several lines of evidence demonstrate that resistin, acting through its different receptors, promotes tumor growth, metastasis, and chemoresistance by influencing a variety of cellular phenotypes as well as by modulating the tumor microenvironment. Racially disparate expression of resistin has also attracted much interest, considering prevalent cancer health disparities. This review discusses the aberrant expression of resistin and its receptors, its diverse downstream signaling and impact on tumor growth, metastasis, angiogenesis, and therapy resistance to support its clinical exploitation in biomarker and therapeutic development.

Molecular and Cellular Factors Associated with Racial Disparity in Breast Cancer

Recent studies have demonstrated that racial differences can influence breast cancer incidence and survival rate. African American (AA) women are at two to three fold higher risk for breast cancer than other ethnic groups. AA women with aggressive breast cancers show worse prognoses and higher mortality rates relative to Caucasian (CA) women. Over the last few years, effective treatment strategies have reduced mortality from breast cancer. Unfortunately, the breast cancer mortality rate among AA women remains higher compared to their CA counterparts. The focus of this review is to underscore the racial differences and differential regulation/expression of genetic signatures in CA and AA women with breast cancer. Moreover, immune cell infiltration significantly affects the clinical outcome of breast cancer. Here, we have reviewed recent findings on immune cell recruitment in the tumor microenvironment (TME) and documented its association with breast cancer racial disparity. In addition, we have extensively discussed the role of cytokines, chemokines, and other cell signaling molecules among AA and CA breast cancer patients. Furthermore, we have also reviewed the distinct genetic and epigenetic changes in AA and CA patients. Overall, this review article encompasses various molecular and cellular factors associated with breast cancer disparity that affects mortality and clinical outcome.

The Contribution of Race to Breast Tumor Microenvironment Composition and Disease Progression

Breast cancer is the second most commonly diagnosed cancer in American women following skin cancer. Despite overall decrease in breast cancer mortality due to advances in treatment and earlier screening, black patients continue to have 40% higher risk of breast cancer related death compared to white patients. This disparity in outcome persists even when controlled for access to care and stage at presentation and has been attributed to differences in tumor subtypes or gene expression profiles. There is emerging evidence that the tumor microenvironment (TME) may contribute to the racial disparities in outcome as well. Here, we provide a comprehensive review of current literature available regarding race-dependent differences in the TME. Notably, black patients tend to have a higher density of pro-tumorigenic immune cells (e.g., M2 macrophages, regulatory T cells) and microvasculature. Although immune cells are classically thought to be anti-tumorigenic, increase in M2 macrophages and angiogenesis may lead to a paradoxical increase in metastasis by forming doorways of tumor cell intravasation called tumor microenvironment of metastasis (TMEM). Furthermore, black patients also have higher serum levels of inflammatory cytokines, which provide a positive feedback loop in creating a pro-metastatic TME. Lastly, we propose that the higher density of immune cells and angiogenesis observed in the TME of black patients may be a result of evolutionary selection for a more robust immune response in patients of African geographic ancestry. Better understanding of race-dependent differences in the TME will aid in overcoming the racial disparity in breast cancer mortality.

Somatic mutations of triple-negative breast cancer: a comparison between Black and White women

PURPOSE

Understanding the contribution of tumor genome biology to racial disparities of triple-negative breast cancer (TNBC) is important for narrowing the cancer mortality gap between Black and White women.

METHODS

We evaluated tumor somatic mutations using targeted sequencing of a customized panel of 151 genes and 15 copy number variations (CNVs) within a population of 133 TNBC patients, including 71 Black and 62 White women.

RESULTS

The overall mutational burden between Black and White women with TNBC was not significantly different, with a median of 5 somatic changes per patient (point mutations and CNVs combined) for the customized panel (range 1-31 for Blacks vs. 1-26 for Whites; p = 0.76). Of the 151 genes examined, none were mutated at a significantly higher frequency in Black than in White cases, whereas two genes were mutated at a higher frequency in White cases-PIK3CA and NCOR1. No significant difference in the frequency of CNVs was observed between Black and White women with TNBC in our study population.

CONCLUSION

Of gene mutations and CNVs in TNBC tumors from Black and White women, only PIK3CA and NCOR1 had significantly different, although slight, frequencies by race. These results indicate that overall differences observed in the mutation spectra between Black and White women with breast cancer are likely due to the differential distributions of breast cancer subtypes by race.

Integrated copy number and miRNA expression analysis in triple negative breast cancer of Latin American patients

Triple negative breast cancer (TNBC), a clinically aggressive breast cancer subtype, affects 15-35% of women from Latin America. Using an approach of direct integration of copy number and global miRNA profiling data, performed simultaneously in the same tumor specimens, we identified a panel of 17 miRNAs specifically associated with TNBC of ancestrally characterized patients from Latin America, Brazil. This panel was differentially expressed between the TNBC and non-TNBC subtypes studied (p ≤ 0.05, FDR ≤ 0.25), with their expression levels concordant with the patterns of copy number alterations (CNAs), present mostly frequent at 8q21.3-q24.3, 3q24-29, 6p25.3-p12.2, 1q21.1-q44, 5q11.1-q22.1, 11p13-p11.2, 13q12.11-q14.3, 17q24.2-q25.3 and Xp22.33-p11.21. The combined 17 miRNAs presented a high power (AUC = 0.953 (0.78-0.99);95% CI) in discriminating between the TNBC and non-TNBC subtypes of the patients studied. In addition, the expression of 14 and 15 of the 17miRNAs was significantly associated with tumor subtype when adjusted for tumor stage and grade, respectively. In conclusion, the panel of miRNAs identified demonstrated the impact of CNAs in miRNA expression levels and identified miRNA target genes potentially affected by both CNAs and miRNA deregulation. These targets, involved in critical signaling pathways and biological functions associated specifically with the TNBC transcriptome of Latina patients, can provide biological insights into the observed differences in the TNBC clinical outcome among racial/ethnic groups, taking into consideration their genetic ancestry.

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

Importance

African Americans have the highest breast cancer mortality rate. Although racial difference in the distribution of intrinsic subtypes of breast cancer is known, it is unclear if there are other inherent genomic differences that contribute to the survival disparities.

Objectives

To investigate racial differences in breast cancer molecular features and survival and to estimate the heritability of breast cancer subtypes.

Design, Setting, and Participants

Among a convenience cohort of patients with invasive breast cancer, breast tumor and matched normal tissue sample data (as of September 18, 2015) were obtained from The Cancer Genome Atlas.

Main Outcomes and Measures

Breast cancer–free interval, tumor molecular features, and genetic variants.

Results

Participants were 930 patients with breast cancer, including 154 black patients of African ancestry (mean [SD] age at diagnosis, 55.66 [13.01] years; 98.1% [n = 151] female) and 776 white patients of European ancestry (mean [SD] age at diagnosis, 59.51 [13.11] years; 99.0% [n = 768] female). Compared with white patients, black patients had a worse breast cancer-free interval (hazard ratio, HR=1.67; 95% CI, 1.02-2.74; P = .043). They had a higher likelihood of basal-like (odds ratio, 3.80; 95% CI, 2.46-5.87; P < .001) and human epidermal growth factor receptor 2 (ERBB2 [formerly HER2])–enriched (odds ratio, 2.22; 95% CI, 1.10-4.47; P = .027) breast cancer subtypes, with the Luminal A subtype as the reference. Blacks had more TP53 mutations and fewer PIK3CA mutations than whites. While most molecular differences were eliminated after adjusting for intrinsic subtype, the study found 16 DNA methylation probes, 4 DNA copy number segments, 1 protein, and 142 genes that were differentially expressed, with the gene-based signature having an excellent capacity for distinguishing breast tumors from black vs white patients (cross-validation C index, 0.878). Using germline genotypes, the heritability of breast cancer subtypes (basal vs nonbasal) was estimated to be 0.436 (P = 1.5 × 10−14). The estrogen receptor–positive polygenic risk score built from 89 known susceptibility variants was higher in blacks than in whites (difference, 0.24; P = 2.3 × 10−5), while the estrogen receptor–negative polygenic risk score was much higher in blacks than in whites (difference, 0.48; P = 2.8 × 10−11).

Conclusions and Relevance

On the molecular level, after adjusting for intrinsic subtype frequency differences, this study found a modest number of genomic differences but a significant clinical survival outcome difference between blacks and whites in The Cancer Genome Atlas data set. Moreover, more than 40% of breast cancer subtype frequency differences could be explained by genetic variants. These data could form the basis for the development of molecular targeted therapies to improve clinical outcomes for the specific subtypes of breast cancers that disproportionately affect black women. Findings also indicate that personalized risk assessment and optimal treatment could reduce deaths from aggressive breast cancers for black women.

Triple Negative Breast Cancer Profile, from Gene to microRNA, in Relation to Ethnicity

Breast cancer is the most frequent cause of cancer-related deaths among women worldwide. It is classified into four major molecular subtypes. Triple-negative breast cancers (TNBCs), a subgroup of breast cancer, are defined by the absence of estrogen and progesterone receptors and the lack of HER-2 expression; this subgroup accounts for ~15% of all breast cancers and exhibits the most aggressive metastatic behavior. Currently, very limited targeted therapies exist for the treatment of patients with TNBCs. On the other hand, it is important to highlight that knowledge of the molecular biology of breast cancer has recently changed the decision-making process regarding the course of cancer therapies. Thus, a number of new techniques, such as gene profiling and sequencing, proteomics, and microRNA analysis have been used to explore human breast carcinogenesis and metastasis including TNBC, which consequently could lead to new therapies. Nevertheless, based on evidence thus far, genomics profiles (gene and miRNA) can differ from one geographic location to another as well as in different ethnic groups. This review provides a comprehensive and updated information on the genomics profile alterations associated with TNBC pathogenesis associated with different ethnic backgrounds.

Extracting chemical-protein interactions from literature using sentence structure analysis and feature engineering

Information about the interactions between chemical compounds and proteins is indispensable for understanding the regulation of biological processes and the development of therapeutic drugs. Manually extracting such information from biomedical literature is very time and resource consuming. In this study, we propose a computational method to automatically extract chemical-protein interactions (CPIs) from a given text. Our method extracts CPI pairs and CPI triplets from sentences, where a CPI pair consists of a chemical compound and a protein name, and a CPI triplet consists of a CPI pair along with an interaction word describing their relationship. We extracted a diverse set of features from sentences that were used to build multiple machine learning models. Our models contain both simple features, which can be directly computed from sentences, and more sophisticated features derived using sentence structure analysis techniques. For example, one set of features was extracted based on the shortest paths between the CPI pairs or among the CPI triplets in the dependency graphs obtained from sentence parsing. We designed a three-stage approach to predict the multiple categories of CPIs. Our method performed the best among systems that use non-deep learning methods and outperformed several deep-learning-based systems in the track 5 of the BioCreative VI challenge. The features we designed in this study are informative and can be applied to other machine learning methods including deep learning.

Racial Disparity and Triple-Negative Breast Cancer in African-American Women: A Multifaceted Affair between Obesity, Biology, and Socioeconomic Determinants

Triple negative breast cancer (TNBC) is a molecularly heterogeneous disease whose incidence is disproportionately higher in African American (AA) women compared to European American (EA) women. Earlier onset, more advanced stage at diagnosis, and aggressive tumor phenotype are some of the characteristic features of TNBC in women with African ethnicity in comparison to EA women, denoting one of the most significant examples of racial disparity in oncology. It is still contentious whether health disparities result in aggressive behavior of TNBC in AA women or it is indeed a molecularly distinct disease. Given the “gaps-in-knowledge” surrounding racial disparity in TNBC, this review discusses various socioeconomic factors and the genetic predispositions contributing to poor prognosis of TNBC in AA women. While socioeconomic factors may contribute to poorer survival, multiple preclinical and clinical studies suggest inherent genetic risk factors and aberrant activation of oncogenic pathways in AA TNBC. Additionally, AA women are more likely to be obese and obesity is known to drive a molecular circuitry resulting in aggressive tumor progression indicating a potential obesity-TNBC axis at work in AA women. Given the multifactorial nature of AA TNBC, a transdisciplinary approach may help bridge the disparity that exists between AA and EA TNBC.

Genomic analysis of racial differences in triple negative breast cancer

Triple negative breast cancer (TNBC) is more prevalent in African Americans (AAs), has a more aggressive clinical course including a higher mortality rate and an increased occurrence of metastases. This study was designed to determine if racial differences at the molecular level might explain the more aggressive phenotype in AAs. Mutation profiling, was performed on 51 AA and 77 CA tumor/ normal pairs. Transcript expression analysis was performed on 35AA and 37CA. Genes with high frequency mutation rates such as MUC4 and TP53 were common to both racial populations, however genes that were less frequently mutated differed between the races suggesting that those cause the more aggressive nature of TNBC in AA women. JAK-Stat and HER2 signaling were unique to the AA and PTEN and mTOR were unique to the CA profiles. Many pathways identified by the mutational profiles were predicted to be down-regulated by the transcript expression profiles.

Breast Cancer Disparities: How Can We Leverage Genomics to Improve Outcomes?

Breast cancer mortality rates are higher in African American compared with white American women. Disproportionately rising incidence rates, coupled with higher rates of biologically aggressive disease among African Americans is resulting in a widening of the mortality disparity. Higher rates of triple-negative breast cancer among African American women, as well as women from western sub-Saharan Africa, has prompted questions regarding the role of African ancestry as a marker of hereditary susceptibility for specific disease phenotypes. Advances in germline genetics, as well as somatic tumor genomic research, hold great promise in the effort to understand the biology of breast cancer variations between different population subsets.

Intra-individual Gene Expression Variability of Histologically Normal Breast Tissue

Several studies have sought to identify novel transcriptional biomarkers in normal breast or breast microenvironment to predict tumor risk and prognosis. However, systematic efforts to evaluate intra-individual variability of gene expression within normal breast have not been reported. This study analyzed the microarray gene expression data of 288 samples from 170 women in the Normal Breast Study (NBS), wherein multiple histologically normal breast samples were collected from different block regions and different sections at a given region. Intra-individual differences in global gene expression and selected gene expression signatures were quantified and evaluated in association with other patient-level factors. We found that intra-individual reliability was relatively high in global gene expression, but differed by signatures, with composition-related signatures (i.e., stroma) having higher intra-individual variability and tumorigenesis-related signatures (i.e., proliferation) having lower intra-individual variability. Histological stroma composition was the only factor significantly associated with heterogeneous breast tissue (defined as > median intra-individual variation; high nuclear density, odds ratio [OR] = 3.42, 95% confidence interval [CI] = 1.15–10.15; low area, OR = 0.29, 95% CI = 0.10–0.86). Other factors suggestively influencing the variability included age, BMI, and adipose nuclear density. Our results underscore the importance of considering intra-individual variability in tissue-based biomarker development, and have important implications for normal breast research.

Pre-diagnostic biomarkers of metabolic dysregulation and cancer mortality

INTRODUCTION

The obesogenic milieu is a pro-tumorigenic environment that promotes tumor initiation, angiogenesis and metastasis. In this prospective cohort, we examined the association between pre-diagnostic metabolic biomarkers, plasma adiponectin, resistin, leptin and lipoprotein (a), and the risk of cancer mortality.

METHODS

Prospective data was obtained from the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort of Blacks and Whites followed from 2003 through 2012 for cancer mortality. We determined the association between metabolism biomarkers (log-transformed and tertiles) and risk of cancer mortality using Cox Proportional Hazards models with robust sandwich estimators to calculate the 95% confidence intervals (CIs), and adjusted for baseline covariates, including age, gender, income, education, physical activity, BMI, smoking status, alcohol use, and comorbidity score.

RESULTS

Among 1764 participants with available biomarker data, each SD higher log-leptin was associated with a 54% reduced risk of total cancer mortality (HR: 0.46, 95% CI: 0.23 – 0.92) and obesity-related cancer mortality (HR: 0.55, 95% CI: 0.39-0.79). Among Blacks only, each SD higher log-resistin was associated with a nearly 7-fold increased risk of cancer mortality (adjusted HR: 6.68, 95% CI: 2.10 – 21.21). There were no significant associations of adiponectin or Lp(a) and cancer mortality.

CONCLUSIONS

Leptin is involved in long-term regulation of energy balance, while resistin is involved in chronic inflammation and LDL production. These findings highlight the biological mechanisms linking metabolic dysregulation with cancer mortality, and the influence of resistin on cancer mortality only among Blacks suggests that this hormone may be a useful biomarker of racial differences in cancer mortality that deserves further study.

IMPACT

Our observed increased risk of cancer mortality associated with higher serum resistin levels among Blacks suggests that if validated in larger cohorts, clinical strategies focused on resistin control may be a promising cancer prevention strategy.

Differentially expressed miRNAs in triple negative breast cancer between African-American and non-Hispanic white women

Triple Negative Breast Cancer (TNBC), a clinically aggressive subtype of breast cancer, disproportionately affects African American (AA) women when compared to non-Hispanic Whites (NHW). MiRNAs(miRNAs) play a critical role in these tumors, through the regulation of cancer driver genes. In this study, our goal was to characterize and compare the patterns of miRNA expression in TNBC of AA (n = 27) and NHW women (n = 30). A total of 256 miRNAs were differentially expressed between these groups, and distinct from the ones observed in their respective non-TNBC subtypes. Fifty-five of these miRNAs were mapped in cytobands carrying copy number alterations (CNAs); 26 of them presented expression levels concordant with the observed CNAs. Receiving operating characteristic (ROC) analysis showed a good power (AUC ≥ 0.80; 95% CI) for over 65% of the individual miRNAs and a high combined power with superior sensitivity and specificity (AUC = 0.88 (0.78−0.99); 95% CI) of the 26 miRNA panel in discriminating TNBC between these populations. Subsequent miRNA target analysis revealed their involvement in the interconnected PI3K/AKT, MAPK and insulin signaling pathways. Additionally, three miRNAs of this panel were associated with early age at diagnosis. Altogether, these findings indicated that there are different patterns of miRNA expression between TNBC of AA and NHW women and that their mapping in genomic regions with high levels of CNAs is not merely physical, but biologically relevant to the TNBC phenotype. Once validated in distinct cohorts of AA women, this panel can potentially represent their intrinsic TNBC genome signature.

Race-associated biological differences among luminal A and basal-like breast cancers in the Carolina Breast Cancer Study

BACKGROUND

We examined racial differences in the expression of eight genes and their associations with risk of recurrence among 478 white and 495 black women who participated in the Carolina Breast Cancer Study Phase 3.

METHODS

Breast tumor samples were analyzed for PAM50 subtype and for eight genes previously found to be differentially expressed by race and associated with breast cancer survival: ACOX2, MUC1, FAM177A1, GSTT2, PSPH, PSPHL, SQLE, and TYMS. The expression of these genes according to race was assessed using linear regression and each gene was evaluated in association with recurrence using Cox regression.

RESULTS

Compared to white women, black women had lower expression of MUC1, a suspected good prognosis gene, and higher expression of GSTT2, PSPHL, SQLE, and TYMS, suspected poor prognosis genes, after adjustment for age and PAM50 subtype. High expression (greater than median versus less than or equal to median) of FAM177A1 and PSPH was associated with a 63% increase (hazard ratio (HR) = 1.63, 95% confidence interval (CI) = 1.09-2.46) and 76% increase (HR = 1.76, 95% CI = 1.15-2.68), respectively, in risk of recurrence after adjustment for age, race, PAM50 subtype, and ROR-PT score. Log₂-transformed SQLE expression was associated with a 20% increase (HR = 1.20, 95% CI = 1.03-1.41) in recurrence risk after adjustment. A continuous multi-gene score comprised of eight genes was also associated with increased risk of recurrence among all women (HR = 1.11, 95% CI = 1.04-1.19) and among white (HR = 1.14, 95% CI = 1.03-1.27) and black (HR = 1.11, 95% CI = 1.02-1.20) women.

CONCLUSIONS

Racial differences in gene expression may contribute to the survival disparity observed between black and white women diagnosed with breast cancer.