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

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.

Chromatin Accessibility Landscape of Human Triple-negative Breast Cancer Cell Lines Reveals Variation by Patient Donor Ancestry

African American (AA) women have an excessive risk of developing triple-negative breast cancer (TNBC). We employed Assay for Transposase-Accessible Chromatin using sequencing to characterize differences in chromatin accessibility between nine commonly used TNBC cell lines derived from patients of European and African ancestry. Principal component and chromosome mapping analyses of accessibility peaks with the most variance revealed separation of chromatin profiles by patient group. Motif enrichment and footprinting analyses of disparate open chromatin regions revealed differences in transcription factor activity, identifying 79 with ancestry-associated binding patterns (FDR < 0.01). AA TNBC cell lines exhibited increased accessibility for 62 transcription factors associated with epithelial-to-mesenchymal transition, cancer stemness/chemotherapeutic resistance, proliferation, and aberrant p53 regulation, as well as KAISO, which has been previously linked to aggressive tumor characteristics in AA patients with cancer. Differential Assay for Transposase-Accessible Chromatin signal analysis identified 1,596 genes located within promoters of differentially open chromatin regions in AA-derived TNBC, identifying DNA methyltransferase 1 as the top upregulated gene associated with African ancestry. Pathway analyses with these genes revealed enrichment in several pathways, including hypoxia. Culturing cells under hypoxia showed ancestry-specific stress responses that led to the identification of a core set of AA-associated transcription factors, which included members of the Kruppel-like factor and Sp subfamilies, as well as KAISO, and identified ZDHHC1, a gene previously implicated in immunity and STING activation, as the top upregulated AA-specific gene under hypoxia. Together, these data reveal a differential chromatin landscape in TNBC associated with donor ancestry. The open chromatin structure of AA TNBC may contribute to a more lethal disease.

SIGNIFICANCE

We identify an ancestry-associated open chromatin landscape and related transcription factors that may contribute to aggressive TNBC in AA women. Furthermore, this study advocates for the inclusion of diversely sourced cell lines in experimental in vitro studies to advance health equity at all levels of scientific research.

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.

Demographic confounders distort inference of gene regulatory and gene co-expression networks in cancer

Gene regulatory networks (GRNs) and gene co-expression networks (GCNs) allow genome-wide exploration of molecular regulation patterns in health and disease. The standard approach for obtaining GRNs and GCNs is to infer them from gene expression data, using computational network inference methods. However, since network inference methods are usually applied on aggregate data, distortion of the networks by demographic confounders might remain undetected, especially because gene expression patterns are known to vary between different demographic groups. In this paper, we present a computational framework to systematically evaluate the influence of demographic confounders on network inference from gene expression data. Our framework compares similarities between networks inferred for different demographic groups with similarity distributions obtained for random splits of the expression data. Moreover, it allows to quantify to which extent demographic groups are represented by networks inferred from the aggregate data in a confounder-agnostic way. We apply our framework to test four widely used GRN and GCN inference methods as to their robustness w. r. t. confounding by age, ethnicity and sex in cancer. Our findings based on more than $ {44000}$ inferred networks indicate that age and sex confounders play an important role in network inference for certain cancer types, emphasizing the importance of incorporating an assessment of the effect of demographic confounders into network inference workflows. Our framework is available as a Python package on GitHub: https://github.com/bionetslab/grn-confounders.

Transcriptome profiling and network enrichment analyses identify subtype-specific therapeutic gene targets for breast cancer and their microRNA regulatory networks

Previous studies have suggested that breast cancer (BC) from the Middle East and North Africa (MENA) is presented at younger age with advanced tumor stage, indicating underlying biological differences. Given the scant transcriptomic data on BC from the MENA region and to better understand the biology of this disease, we performed mRNA and microRNA (miRNA) transcriptomic profiling on a local cohort of BC (n = 96) from Qatar. Our data revealed the differentially expressed genes and miRNAs as function of BC molecular subtypes (HR⁺, HER2⁺, HER2⁺HR⁺, and TNBC), tumor grade (GIII vs GI-II), patients' age (young (≤40) vs old (>40)), and ethnicity (MENA vs non-MENA). Our profiling data revealed close similarity between TNBC and HER2⁺, while the transcriptome of HER2⁺HR⁺ tumor was resemblant of that from HR⁺ tumors. Network analysis identified complex miRNA-mRNA regulatory networks in each BC molecular subtype, in high vs low grade tumors, in tumors from young vs old patients, and in tumors from MENA vs non-MENA, thus implicating miRNA-mediated gene regulation as an essential mechanism in shaping the transcriptome of BC. Integration of our transcriptomic data with CRISPR-Cas9 functional screen data and the OncoKB database identified numerous dependencies and therapeutic vulnerabilities in each BC molecular subtype, while CDC123 was functionally validated as potential therapeutic target for TNBC. Cox regression survival analyses identified mRNA and miRNA-based signatures predicative of worse and better relapse free survival (RFS), which were validated in larger BC cohorts. Our data provides comprehensive transcriptomic profiling and unraveled the miRNA-mRNA regulatory networks in BC patients from the region and identified novel actionable gene targets, employing integrated approach. Findings from the current study have potential implications to improve the current standard-of-care for BC from the MENA as well as patients from other ethnicities.

The immune landscape of solid pediatric tumors

Background

Large immunogenomic analyses have demonstrated the prognostic role of the functional orientation of the tumor microenvironment in adult solid tumors, this variable has been poorly explored in the pediatric counterpart.

Methods

We performed a systematic analysis of public RNAseq data (TARGET) for five pediatric tumor types (408 patients): Wilms tumor (WLM), neuroblastoma (NBL), osteosarcoma (OS), clear cell sarcoma of the kidney (CCSK) and rhabdoid tumor of the kidney (RT). We assessed the performance of the Immunologic Constant of Rejection (ICR), which captures an active Th1/cytotoxic response. We also performed gene set enrichment analysis (ssGSEA) and clustered more than 100 well characterized immune traits to define immune subtypes and compared their outcome.

Results

A higher ICR score was associated with better survival in OS and high risk NBL without MYCN amplification but with poorer survival in WLM. Clustering of immune traits revealed the same five principal modules previously described in adult tumors (TCGA). These modules divided pediatric patients into six immune subtypes (S1-S6) with distinct survival outcomes. The S2 cluster showed the best overall survival, characterized by low enrichment of the wound healing signature, high Th1, and low Th2 infiltration, while the reverse was observed in S4. Upregulation of the WNT/Beta-catenin pathway was associated with unfavorable outcomes and decreased T-cell infiltration in OS.

Conclusions

We demonstrated that extracranial pediatric tumors could be classified according to their immune disposition, unveiling similarities with adults’ tumors. Immunological parameters might be explored to refine diagnostic and prognostic biomarkers and to identify potential immune-responsive tumors.

Immune-related 3-lncRNA signature with prognostic connotation in a multi-cancer setting

Background

Advances in our understanding of the tumor microenvironment have radically changed the cancer field, highlighting the emerging need for biomarkers of an active, favorable tumor immune phenotype to aid treatment stratification and clinical prognostication. Numerous immune-related gene signatures have been defined; however, their prognostic value is often limited to one or few cancer types. Moreover, the area of non-coding RNA as biomarkers remains largely unexplored although their number and biological roles are rapidly expanding.

Methods

We developed a multi-step process to identify immune-related long non-coding RNA signatures with prognostic connotation in multiple TCGA solid cancer datasets.

Results

Using the breast cancer dataset as a discovery cohort we found 2988 differentially expressed lncRNAs between immune favorable and unfavorable tumors, as defined by the immunologic constant of rejection (ICR) gene signature. Mapping of the lncRNAs to a coding-non-coding network identified 127 proxy protein-coding genes that are enriched in immune-related diseases and functions. Next, we defined two distinct 20-lncRNA prognostic signatures that show a stronger effect on overall survival than the ICR signature in multiple solid cancers. Furthermore, we found a 3 lncRNA signature that demonstrated prognostic significance across 5 solid cancer types with a stronger association with clinical outcome than ICR. Moreover, this 3 lncRNA signature showed additional prognostic significance in uterine corpus endometrial carcinoma and cervical squamous cell carcinoma and endocervical adenocarcinoma as compared to ICR.

Conclusion

We identified an immune-related 3-lncRNA signature with prognostic connotation in multiple solid cancer types which performed equally well and in some cases better than the 20-gene ICR signature, indicating that it could be used as a minimal informative signature for clinical implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03654-7.

Characteristic MicroRNAs Linked to Dysregulated Metabolic Pathways in Qatari Adult Subjects With Obesity and Metabolic Syndrome

BACKGROUND

Obesity-associated dysglycemia is associated with metabolic disorders. MicroRNAs (miRNAs) are known regulators of metabolic homeostasis. We aimed to assess the relationship of circulating miRNAs with clinical features in obese Qatari individuals.

METHODS

We analyzed a dataset of 39 age-matched patients that includes 18 subjects with obesity only (OBO) and 21 subjects with obesity and metabolic syndrome (OBM). We measured 754 well-characterized human microRNAs (miRNAs) and identified differentially expressed miRNAs along with their significant associations with clinical markers in these patients.

RESULTS

A total of 64 miRNAs were differentially expressed between metabolically healthy obese (OBO) versus metabolically unhealthy obese (OBM) patients. Thirteen out of 64 miRNAs significantly correlated with at least one clinical trait of the metabolic syndrome. Six out of the thirteen demonstrated significant association with HbA1c levels; miR-331-3p, miR-452-3p, and miR-485-5p were over-expressed, whereas miR-153-3p, miR-182-5p, and miR-433-3p were under-expressed in the OBM patients with elevated HbA1c levels. We also identified, miR-106b-3p, miR-652-3p, and miR-93-5p that showed a significant association with creatinine; miR-130b-5p, miR-363-3p, and miR-636 were significantly associated with cholesterol, whereas miR-130a-3p was significantly associated with LDL. Additionally, miR-652-3p's differential expression correlated significantly with HDL and creatinine.

CONCLUSIONS

MicroRNAs associated with metabolic syndrome in obese subjects may have a pathophysiologic role and can serve as markers for obese individuals predisposed to various metabolic diseases like diabetes.

Immune response and inflammation in cancer health disparities

Cancer death rates vary among population groups. Underserved populations continue to experience an excessive burden of lethal cancers that is largely explained by health-care disparities. However, the prominent role of advanced-stage disease as a driver of cancer survival disparities may indicate that some cancers are more aggressive in certain population groups than others. The tumor mutational burden can show large differences among patients with similar-stage disease but differences in race/ethnicity or residence. These dissimilarities may result from environmental or chronic inflammatory exposures, altering tumor biology and the immune response. We discuss the evidence that inflammation and immune response dissimilarities among population groups contribute to cancer disparities and how they can be targeted to reduce these disparities.

Bidirectional Regulatory Cross-Talk between Cell Context and Genomic Aberrations Shapes Breast Tumorigenesis

Breast cancers are classified into five intrinsic subtypes and 10 integrative clusters based on gene expression patterns and genomic aberrations, respectively. Although the cell-of-origin, adaptive plasticity, and genomic aberrations shape dynamic transcriptomic landscape during cancer progression, how interplay between these three core elements governs obligatory steps for a productive cancer progression is unknown. Here, we used genetic ancestry-mapped immortalized breast epithelial cell lines generated from breast biopsies of healthy women that share gene expression profiles of luminal A, normal-like, and basal-like intrinsic subtypes of breast cancers and breast cancer relevant oncogenes to develop breast cancer progression model. Using flow cytometry, mammosphere growth, signaling pathway, DNA damage response, and in vivo tumorigenicity assays, we provide evidence that establishes cell context-dependent effects of oncogenes in conferring plasticity, self-renewal/differentiation, intratumor heterogeneity, and metastatic properties. In contrast, oncogenic aberrations, independent of cell context, shaped response to DNA damage-inducing agents. Collectively, this study reveals how the same set of genomic aberration can have distinct effects on tumor characteristics based on cell-of-origin of tumor and highlights the need to utilize multiple "normal" epithelial cell types to decipher oncogenic properties of a gene of interest. In addition, by creating multiple isogenic cell lines ranging from primary cells to metastatic variants, we provide resources to elucidate cell-intrinsic properties and cell-oncogene interactions at various stages of cancer progression. IMPLICATIONS: Our findings demonstrate that how an interplay between the normal cell type that encountered genomic aberrations and type of genomic aberration influences heterogeneity, self-renewal/differentiation, and tumor properties including propensity for metastasis.

Cancer testis antigen PRAME: An anti-cancer target with immunomodulatory potential

PReferentially expressed Antigen in Melanoma (PRAME) is a cancer testis antigen with restricted expression in somatic tissues and re‐expression in poor prognostic solid tumours. PRAME has been extensively investigated as a target for immunotherapy, however, its role in modulating the anti‐tumour immune response remains largely unknown. Here, we show that PRAME tumour expression is associated with worse survival in the TCGA breast cancer cohort, particularly in immune‐unfavourable tumours. Using direct and indirect co‐culture models, we found that PRAME overexpressing MDA‐MB‐468 breast cancer cells inhibit T cell activation and cytolytic potential, which could be partly restored by silencing of PRAME. Furthermore, silencing of PRAME reduced expression of several immune checkpoints and their ligands, including PD‐1, LAG3, PD‐L1, CD86, Gal‐9 and VISTA. Interestingly, silencing of PRAME induced cancer cell killing to levels similar to anti‐PD‐L1 atezolizumab treatment. Comprehensive analysis of soluble inflammatory mediators and cancer cell expression of immune‐related genes showed that PRAME tumour expression can suppress the expression and secretion of multiple pro‐inflammatory cytokines, and mediators of T cell activation, differentiation and cytolysis. Together, our data indicate that targeting of PRAME offers a potential, novel dual therapeutic approach to specifically target tumour cells and regulate immune activation in the tumour microenvironment.

Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases

Admixed populations arise when two or more ancestral populations interbreed. As a result of this admixture, the genome of admixed populations is defined by tracts of variable size inherited from these parental groups and has particular genetic features that provide valuable information about their demographic history. Diverse methods can be used to derive the ancestry apportionment of admixed individuals, and such inferences can be leveraged for the discovery of genetic loci associated with diseases and traits, therefore having important biomedical implications. In this review article, we summarize the most common methods of global and local genetic ancestry estimation and discuss the use of admixture mapping studies in human diseases.