Heterogeneity Of Breast Cancer Research Articles

Abstract C047: Multiomics approaches to identify African-ancestry specific phenotypes of triple negative breast cancer

Abstract Despite recent convergence of breast cancer (BC) incidence among African American (AA) and European American (EA) women, BC mortality remains 40% higher among AA women. This disparity is driven partly by BC heterogeneity, where distinct subtypes have differing prognosis and treatment modalities, defined by presence of estrogen and/or progesterone receptor (HR+), overexpression of HER2, or lack of all three biomarkers (triple negative BC (TNBC)). TNBC is the most aggressive subtype, diagnosed as late-stage disease and lacking targeted therapeutic options. TNBC represents ~10% of annual diagnoses, however prevalence is significantly higher among AA women. Our work in the International Center for the Study of Breast Cancer Subtypes (ICSBCS) revealed significant association of west African (AFR) ancestry and TNBC, where we report that Ghanaian and AA women have increased frequency of TNBC, compared to Ethiopian and EA women, and that TNBC patients have higher percentages of quantified AFR ancestry. To characterize AFR ancestry-specific TNBC phenotypes, we have employed transcriptomics and whole genome sequencing (WGS) methods. Our recent publication from an AFR ancestry enriched TNBC transcriptomics cohort (n = 26) leveraged genetic ancestry to identify 600+ AFR and 2000+ AFR sub-continental ancestry associated genes. Pathway analysis showed enrichment of immune cell trafficking and indicates distinct AFR ancestry phenotypes that can be leveraged for future therapeutic opportunities. Recently, we have completed WGS on 80+ AFR ancestry patients with TNBC disease (n = 59) and HR+ disease (n = 23); representing AA (n = 71), Ethiopian (n = 8) and Ghanaian patients (n = 3). TP53 was the most mutated gene, more commonly mutated among TNBC cases (83%) compared to HR+ cases (35%) (p < 0.0001). HR+ had significantly more GATA3 (26%) and PIK3CA (30%) mutations compared to TNBC (0% and 9%, p < 0.05). Prevalence of COSMIC mutational signatures shows higher Signature 1 among HR+ cases, and higher Signature 3 among TNBC cases (both p < 0.05). Signature 3 is associated with DNA double-strand break repair and germline BRCA1/2 mutation status, where 9 TNBC cases have elevated homologous repair deficiency status. Our genomic work utilizes the reference genome, which is primarily sequenced from a single individual. With the African Pan Genome (APG), a set of 125,000+ contigs distinct from the reference genome, we have aligned RNAseq reads to the APG that failed to map to the reference genome. Successful APG alignment of a subset of reads indicates that genes are expressed from these distinct AFR sequences. We also identified CpG sites in contigs with gene expression, showing AFR ancestry specific regulatory regions in the previously unmapped genome. We are working to determine the significance of these in the tumor microenvironment. This work represents a comprehensive, AFR ancestry enriched cohort with multiple genomic data approaches that will allow us to further characterize TNBC disease and define actionable biomarkers and targets for women of African ancestry. Citation Format: Rachel Martini, Max Chao, Timothy Chu, Brian Stonaker, Ishmael Kyei, Ernest Adjei, Mahteme Bekele, Kofi Gyan, Olivier Elemento, Nicolas Robine, John Carpten, Lisa Newman, Melissa Davis. Multiomics approaches to identify African-ancestry specific phenotypes of triple negative breast cancer [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C047.

Single-cell Analysis Reveals Inter- and Intratumour Heterogeneity in Metastatic Breast Cancer

Metastasis is the leading cause of cancer-related deaths of breast cancer patients. Some cancer cells in a tumour go through successive steps, referred to as the metastatic cascade, and give rise to metastases at a distant site. We know that the plasticity and heterogeneity of cancer cells play critical roles in metastasis but the precise underlying molecular mechanisms remain elusive. Here we aimed to identify molecular mechanisms of metastasis during colonization, one of the most important yet poorly understood steps of the cascade. We performed single-cell RNA-Seq (scRNA-Seq) on tumours and matched lung macrometastases of patient-derived xenografts of breast cancer. After correcting for confounding factors such as the cell cycle and the percentage of detected genes (PDG), we identified cells in three states in both tumours and metastases. Gene-set enrichment analysis revealed biological processes specific to proliferation and invasion in two states. Our findings suggest that these states are a balance between epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial transitions (MET) traits that results in so-called partial EMT phenotypes. Analysis of the top differentially expressed genes (DEGs) between these cell states revealed a common set of partial EMT transcription factors (TFs) controlling gene expression, including ZNF750, OVOL2, TP63, TFAP2C and HEY2. Our data suggest that the TFs related to EMT delineate different cell states in tumours and metastases. The results highlight the marked interpatient heterogeneity of breast cancer but identify common features of single cells from five models of metastatic breast cancer.

Heterogeneity and transcriptional drivers of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous disease with limited treatment options. To characterize TNBC heterogeneity, we defined transcriptional, epigenetic, and metabolic subtypes and subtype-driving super-enhancers and transcription factors by combining functional and molecular profiling with computational analyses. Single-cell RNA sequencing revealed relative homogeneity of the major transcriptional subtypes (luminal, basal, and mesenchymal) within samples. We found that mesenchymal TNBCs share features with mesenchymal neuroblastoma and rhabdoid tumors and that the PRRX1 transcription factor is a key driver of these tumors. PRRX1 is sufficient for inducing mesenchymal features in basal but not in luminal TNBC cells via reprogramming super-enhancer landscapes, but it is not required for mesenchymal state maintenance or for cellular viability. Our comprehensive, large-scale, multiplatform, multiomics study of both experimental and clinical TNBC is an important resource for the scientific and clinical research communities and opens venues for future investigation.

Abstract A020: Reversing triple negative breast cancer stem cells by disrupting the Notch signaling pathway via BCL6 targeting

Abstract Triple negative breast cancer (TNBC) is a heterogeneous molecular breast cancer (BC) subtype that still has a very poor prognosis. Genetic, molecular and clinical tumor heterogeneity represent major pathobiological factors involved in poor clinical outcome. The sequence specific transcriptional repressor and proto-oncogene B cell lymphoma protein 6 (BCL6) has emerged as a suitable therapeutic target as it plays broad and critical roles in many hematological and solid cancers. BCL6 exerts control over cellular proliferation and survival by binding to specific responsive elements located within the regulatory regions of target genes and recruiting of chromatin modifying co-repressor complexes such as silencing mediator for retinoid and thyroid receptors (SMRT), BCL6 corepressor (BCoR) and histone deacetylases (HDACs). Moreover, in hematological malignancies, BCL6 transcriptional activity is also associated to the recruitment of the chromatin remodeling factor, Enhancer of Zeste 2 (EZH2). The role of BCL6 in BC is still not well defined; however emerging studies report its involvement in tumorigenesis, disease progression and poor survival. We recently showed that BCL6 is expressed at significantly higher levels in TNBC mammospheres, 3D multicellular structures enriched in cancer stem cells (CSCs), than in their differentiated bulk cell counterparts. Additionally, we found that the functional role of BCL6 is crucial for mammosphere formation, as its loss of function decreased this process. Intriguingly, we uncovered a functional interplay occurring between BCL6 and EZH2, which triggers the BCL6/Notch stemness signaling axis by inhibiting Numb transcription in both SUM149 and SUM159 TNBC cell lines. We exploited the molecular mechanisms responsible for this specific interplay, taking advantage of two molecules, FX1, a small molecule inhibitor able to block BCL6 recruiting activity and EED226, a potent Polycomb Repressive Complex 2 (PRC2) inhibitor. In order to define the role of both BCL6, as epigenetic regulator, and NUMB, as inhibitor of NOTCH stemness pathway in TNBC, SUM149 and SUM159 cell lines were stably transduced with lentiviral shRNA to derive stable NUMB-silenced matched cells. The expression of Notch downstream target genes, such as HES1/2 and HEY1/2, was assessed by qRT PCR analysis in the engineered TNBC cell models and resulted only slightly increased following NUMB downmodulation. Upon FX1 or EED226 administration, a strongest effect was observed, indicating that NUMB is not the only player in regulating the Notch pathway. Further experiments are currently ongoing aiming at identify additional players and molecular pathway(s). Collectively, our preliminary results provide additional preclinical evidences on the role exerted by BCL6 as epigenetic regulator of TNBC and underlie its interplay with EZH2thus paving the way for a novel potential therapeutic strategy targeting BCL6/Notch signaling axis. Citation Format: Francesca De Santis, Francesca Putti, Giorgia Bravin, Carla Portulano, Federica Zonca, Lorenzo Castagnoli, Michele Magni, Filippo de Braud, Serenella M Pupa, Massimo Di Nicola. Reversing triple negative breast cancer stem cells by disrupting the Notch signaling pathway via BCL6 targeting [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A020.

Comprehensive analysis of mitophagy-related subtypes of breast cancer and the association with immune related characteristics

Breast cancer (BRCA) is a common neoplasm characterized by high levels of molecular heterogeneity. Previous studies have noted the importance of mitophagy for the progression and prognosis of BRCA. However, little was found in the similarity and difference of mitophagy-related gene expression patterns of BRCA. This study intended to investigate the differences in functional activation, somatic mutation, and immune-related characteristics among different subtypes of BRCA associated with mitophagy. Based on bioinformatics analysis, we systematically examined the heterogeneity of breast cancer concerning mitophagy and observed two distinct subtypes with different tumor microenvironments and prognoses. BRCA samples from TCGA database were divided into two subtypes based on the expression of 29 mitophagy-related genes by ConsensusClusterPlus algorithm. Two mitophagy-related subtypes with marked prognostic discrepancies were significantly correlated with race, intrinsic subtype grouped based on PAM50 subtype purity and BRCA Pathology. The results of GSVA and immune microenvironment analysis showed significant differences in cancer-related and immune-related features between the two subtypes. METABRIC datasets were extracted to validate the immune characteristics scoring and the expression of immune checkpoints between different subtypes based on the medium value of TCGA-Mitophagy score. It is noteworthy that the present study is the first to demonstrate a new classification based on the mitophagy of breast cancer, which comes up with a new perspective for the assessment and prognoses of BRCA.

Tumor Heterogeneity of Breast Cancer Assessed with Computed Tomography Texture Analysis: Association with Disease-Free Survival and Clinicopathological Prognostic Factor

Breast cancer is a heterogeneous disease, and computed tomography texture analysis (CTTA), which reflects the tumor heterogeneity, may predict the prognosis. We investigated the usefulness of CTTA for the prediction of disease-free survival (DFS) and prognostic factors in patients with invasive breast cancer. A total of 256 consecutive women who underwent preoperative chest CT and surgery in our institution were included. The Cox proportional hazards model was used to determine the relationship between textural features and DFS. Logistic regression analysis was used to reveal the relationship between textural features and prognostic factors. Of 256 patients, 21 (8.2%) had disease recurrence over a median follow-up of 60 months. For the prediction of shorter DFS, higher histological grade (hazard ratio [HR], 6.12; p < 0.001) and lymphovascular invasion (HR, 2.93; p = 0.029) showed significance, as well as textural features such as lower mean attenuation (HR, 4.71; p = 0.003) and higher entropy (HR, 2.77; p = 0.036). Lower mean attenuation showed a correlation with higher tumor size, and higher entropy showed correlations with higher tumor size and Ki-67. In conclusion, CTTA-derived textural features can be used as a noninvasive imaging biomarker to predict shorter DFS and prognostic factors in patients with invasive breast cancer.

AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer

Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an objective Haematoxylin & Eosin (H&E) image-based prognostic marker for early-stage luminal/Her2-negative BReAst CancEr that we term as the BRACE marker. The proposed BRACE marker is derived from AI based assessment of heterogeneity in BC at a detailed level using the power of deep learning. The prognostic ability of the marker is validated in two well-annotated cohorts (Cohort-A/Nottingham: n = 2122 and Cohort-B/Coventry: n = 311) on early-stage luminal/HER2-negative BC patients treated with endocrine therapy and with long-term follow-up. The BRACE marker is able to stratify patients for both distant metastasis free survival (p = 0.001, C-index: 0.73) and BC specific survival (p < 0.0001, C-index: 0.84) showing comparable prediction accuracy to Nottingham Prognostic Index and Magee scores, which are both derived from manual histopathological assessment, to identify luminal BC patients that may be likely to benefit from adjuvant chemotherapy.

Recent Advances in Drug Discovery for Triple-Negative Breast Cancer Treatment.

Triple-negative breast cancer (TNBC) is one of the most heterogeneous and aggressive breast cancer subtypes with a high risk of death on recurrence. To date, TNBC is very difficult to treat due to the lack of an effective targeted therapy. However, recent advances in the molecular characterization of TNBC are encouraging the development of novel drugs and therapeutic combinations for its therapeutic management. In the present review, we will provide an overview of the currently available standard therapies and new emerging therapeutic strategies against TNBC, highlighting the promises that newly developed small molecules, repositioned drugs, and combination therapies have of improving treatment efficacy against these tumors.

Multi-omics analyses unravel DNA damage repair-related clusters in breast cancer with experimental validation.

As one of the most common malignancies worldwide, breast cancer (BC) exhibits high heterogeneity of molecular phenotypes. The evolving view regarding DNA damage repair (DDR) is that it is context-specific and heterogeneous, but its role in BC remains unclear. Multi-dimensional data of transcriptomics, genomics, and single-cell transcriptome profiling were obtained to characterize the DDR-related features of BC. We collected 276 DDR-related genes based on the Molecular Signature Database (MSigDB) database and previous studies. We acquired public datasets included the SCAN-B dataset (GEO: GSE96058), METABRIC database, and TCGA-BRCA database. Corresponding repositories such as transcriptomics, genomics, and clinical information were also downloaded. We selected scRNA-seq data from GEO: GSE176078, GSE114727, GSE161529, and GSE158724. Bulk RNA-seq data from GEO: GSE176078, GSE18728, GSE5462, GSE20181, and GSE130788 were extracted for independent analyses. The DDR classification was constructed in the SCAN-B dataset (GEO: GSE96058) and METABRIC database, Among BC patients, there were two clusters with distinct clinical and molecular characteristics: the DDR-suppressed cluster and the DDR-active cluster. A superior survival rate is found for tumors in the DDR-suppressed cluster, while those with the DDR-activated cluster tend to have inferior prognoses and clinically aggressive behavior. The DDR classification was validated in the TCGA-BRCA cohort and shown similar results. We also found that two clusters have different pathway activities at the genomic level. Based on the intersection of the different expressed genes among these cohorts, we found that PRAME might play a vital role in DDR. The DDR classification was then enabled by establishing a DDR score, which was verified through multilayer cohort analysis. Furthermore, our results revealed that malignant cells contributed more to the DDR score at the single-cell level than nonmalignant cells. Particularly, immune cells with immunosuppressive properties (such as FOXP3+ CD4+ T cells) displayed higher DDR scores among those with distinguishable characteristics. Collectively, this study performs general analyses of DDR heterogeneity in BC and provides insight into the understanding of individualized molecular and clinicopathological mechanisms underlying unique DDR profiles.

Organ-Specificity of Breast Cancer Metastasis.

Breast cancer (BC) remains one of the most common malignancies among women worldwide. Breast cancer shows metastatic heterogeneity with priority to different organs, which leads to differences in prognosis and response to therapy among patients. The main targets for metastasis in BC are the bone, lung, liver and brain. The molecular mechanism of BC organ-specificity is still under investigation. In recent years, the appearance of new genomic approaches has led to unprecedented changes in the understanding of breast cancer metastasis organ-specificity and has provided a new platform for the development of more effective therapeutic agents. This review summarises recent data on molecular organ-specific markers of metastasis as the basis of a possible therapeutic approach in order to improve the diagnosis and prognosis of patients with metastatically heterogeneous breast cancer.

‘Inner world’ of luminal HER 2-negative metastatic breast cancer: Efficacy of ribociclib in different intrinsic subtypes

The heterogeneity of breast cancer (BC), which determines various clinical scenarios of the disease, is still inaccessible to our understanding. Heterogeneity is based primarily on intrinsic subtypes of breast cancer, determined using genomic tests. Currently, four intrinsic subtypes are generally recognized: luminal A and B, HER-enriched (HER2-E) and basal-like. HER2-E subtype in luminal HER-negative (ER+HER–) breast cancer accounts for 11–22 per cent of cases. The efficacy of a combination of hormone therapy (HT) and the CDK4/6 inhibitor ribociclib in the HER2-E subtype was evaluated in a large exploratory analysis of MONALEESA-2, -3, and -7 trials. The gain in progression-free survival (PFS) and overall survival (OS) from the addition of ribociclib to HT was observed in all intrinsic subtypes, except for basal-like, and reached maximum in HER2-E subtype: Ribociclib increased the median PFS to 16.4 months from 5.5 months on HT (HR = 0.389; p &lt; 0.0001) and median OS to 40.3 months from 29.4 months (HR = 0.600; p = 0.0180). The significant frequency of occurrence of the HER2-E subtype in ER+HER-BC, the low efficiency of monoHT in this subtype is another argument in favor of prescribing combination therapy in early lines. Information about the intrinsic subtype not only brings us closer to understanding tumor heterogeneity, but may also become a significant factor in determining treatment tactics in the future.

Multi-omics integration analysis unveils heterogeneity in breast cancer at the individual level

ABSTRACT Identifying robust breast cancer subtypes will help to reveal the cancer heterogeneity. However, previous breast cancer subtypes were based on population-level quantitative gene expression, which is affected by batch effects and cannot be applied to individuals. We detected differential gene expression, genomic, and epigenomic alterations to identify driver differential expression at the individual level. The individual driver differential expression reflected the breast cancer patients’ heterogeneity and revealed four subtypes. Mesenchymal subtype as the most aggressive subtype harbored deletion and downregulated expression of genes in chromosome 11q23 region. Specifically, silencing of the SDHD gene in 11q23 promoted the invasion and migration of breast cancer cells in vitro by the epithelial–mesenchymal transition. The immunologically hot subtype displayed an immune-hot microenvironment, including high T-cell infiltration and upregulated PD-1 and CTLA4. Luminal and genomic-unstable subtypes showed opposite macrophage polarization, which may be regulated by the ligand–receptor pairs of CD99. The integration of multi-omics data at the individual level provides a powerful framework for elucidating the heterogeneity of breast cancer.

KLHL29-mediated DDX3X degradation promotes chemosensitivity by abrogating cell cycle checkpoint in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a heterogeneous breast cancer subtype and accounts for approximately 15–20% of breast cancer cases. In this study, we identified KLHL29, which is an understudied member of the Kelch-like gene family, as a crucial tumor suppressor that regulates chemosensitivity in TNBC. KLHL29 expression was significantly downregulated in breast cancer tissues compared with adjacent normal tissues, and low levels of KLHL29 were associated with unfavorable prognoses. Ectopic KLHL29 suppressed, while depleting KLHL29 promoted, the growth, proliferation, migration, and invasion of TNBC. Mechanistically, KLHL29 recruited the CUL3 E3-ligase to the RNA-binding protein DDX3X, leading to the proteasomal degradation of the latter. This downregulation of DDX3X resulted in the destabilization of CCND1 mRNA and the consequent cell cycle arrest at G0/G1 phase. Remarkably, the DDX3X inhibitor RK33 combined with platinum-based chemotherapy can synergistically suppress TNBC that usually expresses low levels of KLHL29 and high levels of DDX3X using cancer cell-derived xenograft and patient-derived organoids models. Altogether, we uncovered the potential role for the KLHL29-DDX3X signaling cascade in the regulation of TNBC progression, thus providing a promising combination strategy for overcoming TNBC chemoresistance.

BGSSN: Breast Cancer-Associated Genes Prediction Based on Weighted Sample-Specific Networks of Cancer Subtypes

Breast cancer exhibits a notable degree of heterogeneity in its occurrence and progression, encompassing diverse clinical patterns and outcomes among patients even with identical clinical pathological stages. Genetic mutations in different subtypes of breast cancer may lead to different types of disease and have different clinical implications. Therefore, molecular typing based on the characteristics of breast cancer heterogeneity and the screening of associated genes for different subtypes of breast cancer may be able to more accurately determine the pathogenic genes of breast cancer. In this paper, we propose a weighted sample-specific network based on breast cancer subtypes to predict associated genes, named BGSSN. To better reflect the individual characteristics of patients and the importance of patient samples in different subtypes, the weight of samples is added when constructing the sample-specific network. The random walk with restart method is then utilized to predict new breast cancer-associated genes within the constructed network. By leveraging this method, the network structure can be effectively explored to identify potential gene candidates.

Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

BackgroundBreast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.MethodsTumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman’s rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan–Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.ResultsHerein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.ConclusionsWe conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

OR33-01 Live Cell Imaging Of Enhancer Transcriptional States

Abstract Disclosure: F. Chapus: None. C. Day: None. P. Yasar: None. C. Bregio: None. A. Palia: None. E. Scappini: None. C. Tucker: None. J. Rodriguez: None. Intra-tumoral gene expression heterogeneity of estrogen receptor positive breast cancers is a roadblock toward effective treatment due to subpopulations acquiring resistance and metastatic ability. This expression heterogeneity can be explained by the stochastic nature of transcription. Transcriptional initiation is coordinated through distal elements known as enhancers. These elements aid in the recruitment of cofactors and chromatin remodelers to promoters. During transcriptional activation, genes are transcribed during short periods of nascent RNA synthesis known as transcriptional bursts. Furthermore, estrogen responsive genes can transition between transcriptional bursting and variably long periods of inactivity lasting from minutes to days. Here, we investigated whether estrogen responsive enhancers of variably expressed genes also exhibited transcriptional states which reflect promoter states. To observe live cell transcription dynamics, we integrated MS2 stem loops into several endogenous enhancers using CRISPR. After transcription initiation, these stem loops are transcribed and subsequently bound by the RNA binding protein, MS2-GFP. This enrichment in MS2-GFP at the transcription site is visible as a bright punctate spot. We observed that the estrogen responsive TFF1 enhancer exhibited short periods of transcriptional activity and long periods of inactivity. Moreover, the TFF1 enhancer RNA (eRNA) sporadically formed dynamic, but rare and long-lived condensates. To correlate enhancer and promoter transcription we used single molecule fluorescence in situ hybridization of several eRNA. We observed that eRNA aggregates were correlated with an increase of mRNA content and occasionally localized to different nuclear bodies. Lastly, we enriched for chromatin bound RNA and observed long enhancer RNA transcripts. Taken together, our work highlights the dynamic coupling of enhancer and promoter regulation and the importance of understanding the regulators of enhancer transcriptional states in cancer. Presentation: Sunday, June 18, 2023

NKG2A Is a Therapeutic Vulnerability in Immunotherapy Resistant MHC-I Heterogeneous Triple-Negative Breast Cancer.

Clinical resistance to immunotherapy is common in breast cancer, and many patients will likely require combination therapy to maximize immunotherapeutic benefit. This study demonstrates that heterogeneous MHC-I expression drives resistance to anti-PD-L1 therapy and exposes NKG2A on NK cells as a target to overcome resistance. This article is featured in Selected Articles from This Issue, p. 201.

Identifying the effectiveness of 3D culture systems to recapitulate breast tumor tissue in situ.

Breast cancer heterogeneity contributes to chemotherapy resistance and decreased patient survival. To improve patient outcomes it is essential to develop a technology that is able to rapidly select the most efficacious therapy that targets the diverse phenotypes present within the tumor. Breast cancer organoid technologies are proposed as an attractive approach for evaluating drug responses prior to patient therapy. However, there remain challenges in evaluating the effectiveness of organoid cultures to recapitulate the heterogeneity present in the patient tumor in situ. Organoids were generated from seven normal breast and nineteen breast cancer tissues diagnosed as estrogen receptor positive or triple negative. The Jensen-Shannon divergence index, a measure of the similarity between distributions, was used to compare and evaluate heterogeneity in starting tissue and their resultant organoids. Heterogeneity was analyzed using cytokeratin 8 and cytokeratin 14, which provided an easily scored readout. In the in vitro culture system HER1 and FGFR were able to drive intra-tumor heterogeneity to generate divergent phenotypes that have different sensitivities to chemotherapies. Our methodology, which focuses on quantifiable cellular phenotypes, provides a tractable system that complements omics approaches to provide an unprecedented view of heterogeneity and will enhance the identification of novel therapies and facilitate personalized medicine.

Phenotypic heterogeneity drives differential disease outcome in a mouse model of triple negative breast cancer.

The triple negative breast cancer (TNBC) subtype is one of the most aggressive forms of breast cancer that has poor clinical outcome and is an unmet clinical challenge. Accumulating evidence suggests that intratumoral heterogeneity or the presence of phenotypically distinct cell populations within a tumor play a crucial role in chemoresistance, tumor progression and metastasis. An increased understanding of the molecular regulators of intratumoral heterogeneity is crucial to the development of effective therapeutic strategies in TNBC. To this end, we used an unbiased approach to identify a molecular mediator of intratumoral heterogeneity in breast cancer by isolating two tumor cell populations (T1 and T2) from the 4T1 TNBC model. Phenotypic characterization revealed that the cells are different in terms of their morphology, proliferation and self-renewal ability in vitro as well as primary tumor formation and metastatic potential in vivo. Bioinformatic analysis followed by Kaplan Meier survival analysis in TNBC patients identified Metastasis associated colon cancer 1 (Macc1) as one of the top candidate genes mediating the aggressive phenotype in the T1 tumor cells. The role of Macc1 in regulating the proliferative phenotype was validated and taken forward in a therapeutic context with Lovastatin, a small molecule transcriptional inhibitor of Macc1 to target the T1 cell population. This study increases our understanding of the molecular underpinnings of intratumoral heterogeneity in breast cancer that is critical to improve the treatment of women currently living with the highly aggressive TNBC subtype.

Metabolic stratification of human breast tumors reveal subtypes of clinical and therapeutic relevance

Extensive metabolic heterogeneity in breast cancers has limited the deployment of metabolic therapies. To enable patient stratification, we studied the metabolic landscape in breast cancers (∼3000 patients combined) and identified three subtypes with increasing degrees of metabolic deregulation. Subtype M1 was found to be dependent on bile-acid biosynthesis, whereas M2 showed reliance on methionine pathway, and M3 engaged fatty-acid, nucleotide, and glucose metabolism. The extent of metabolic alterations correlated strongly with tumor aggressiveness and patient outcome. This pattern was reproducible in independent datasets and using invivo tumor metabolite data. Using machine-learning, we identified robust and generalizable signatures of metabolic subtypes in tumors and cell lines. Experimental inhibition of metabolic pathways in cell lines representing metabolic subtypes revealed subtype-specific sensitivity, therapeutically relevant drugs, and promising combination therapies. Taken together, metabolic stratification of breast cancers can thus aid in predicting patient outcome and designing precision therapies.