Breast Cancer Research

PurposePAM50 profiling assigns each breast cancer to a single intrinsic subtype based on a bulk tissue sample. However, individual cancers may show evidence of admixture with an alternate subtype that could affect prognosis and treatment response. We developed a method to model subtype admixture using semi-supervised non-negative matrix factorization (ssNMF) of whole transcriptome data and associated it with tumor, molecular, and survival characteristics for Luminal A (LumA) samples. MethodsWe combined TCGA and METABRIC cohorts and obtained transcriptome, molecular, and clinical data, which yielded 11,379 gene transcripts in common, and 1,179 cases assigned to LumA. We used ssNMF to compute the subtype admixture proportions of the four major subtypes - pLumA, pLumB, pHER2 and pBasal - for each case and measured associations with tumor characteristics, molecular features, and survival. ResultsLuminal A cases with low pLumA transcriptomic proportion were likelier to have non-luminal pathology, higher clinical and genomic risk factors, and lower overall survival (log rank P < 10-5), independent of age, stage, and tumor size. We found positive associations between pHER2 and HER2-positivity by IHC or FISH; between pLumB and PR negativity; and between pBasal and younger age, node positivity, TP53 mutation, and EGFR expression. Predominant basal admixture, in contrast to predominant LumB or HER2 admixture, was not associated with shorter survival. ConclusionsBulk sampling for genomic analyses provides an opportunity to expose intratumor heterogeneity, as reflected by subtype admixture. Our results elucidate the striking extent of diversity among LumA cancers and suggest that determining the extent and type of admixture holds promise for refining individualized therapy. LumA cancers with a high degree of basal admixture appear to have distinct biological characterstics that warrant further study.

ABSTRACT/SUMMARYDuctal carcinoma in situ (DCIS) constitutes an array of morphologically recognized intraductal neoplasms in the mammary ductal tree defined by an increased risk for subsequent invasive carcinomas at or near the site of biopsy detection. However, only 15-45% of untreated DCIS cases progress to invasive cancer, so understanding mechanisms that prevent progression is key to avoid overtreatment and provides a basis for alternative therapies and prevention. This study was designed to characterize the tumor microenvironment and molecular profile of high-risk DCIS that grew to a large size but remained as DCIS. All patients had DCIS lesions >5cm in size with at least one additional high-risk feature: young age (<45 years), high nuclear grade, hormone receptor negativity, HER2 positivity, the presence of comedonecrosis, or a palpable mass. The tumor immune microenvironment was characterized using multiplex immunofluorescence to identify immune cells and their spatial relationships within the ducts and stroma. Gene copy number analysis and whole exome DNA sequencing identified the mutational burden and driver mutations, and quantitative whole-transcriptome/gene expression analyses were performed. There was no association between the percent of the DCIS genome characterized by copy number variants (CNAs) and recurrence events (DCIS or invasive). Mutations, especially missense mutations, in the breast cancer driver genes PIK3CA and TP53 were common in this high-risk DCIS cohort (47% of evaluated lesions). Tumor infiltrating lymphocyte (TIL) density was higher in DCIS lesions with TP53 mutations (p=0.0079) compared to wildtype lesions, but not in lesions with PIK3CA mutations (p=0.44). Immune infiltrates were negatively associated with hormone receptor status and positively associated with HER2 expression. High levels of CD3+CD8-T cells were associated with good outcomes with respect to any subsequent recurrence (DCIS or invasive cancer), whereas high levels of CD3+Foxp3+ Treg cells were associated with poor outcomes. Spatial proximity analyses of immune cells and tumor cells demonstrated that close proximity of T cells with tumor cells was associated with good outcomes with respect to any recurrence as well as invasive recurrences. Interestingly, we found that myoepithelial continuity (distance between myoepithelial cells surrounding the involved ducts) was significantly lower in DCIS lesions compared to normal tissue (p=0.0002) or to atypical ductal hyperplasia (p=0.011). Gene set enrichment analysis identified several immune pathways associated with low myoepithelial continuity and a low myoepithelial continuity score was associated with better outcomes, suggesting that gaps in the myoepithelial layer may allow access/interactions between immune infiltrates and tumor cells. Our study demonstrates the immune microenvironment of DCIS, in particular the spatial proximity of tumor cells and T cells, and myoepithelial continuity are important determinants for progression of disease.

BackgroundThe breast tumor microenvironment (TME) is a complex milieu composed of many factors contributing to breast cancer (BC) heterogeneity and therapeutic resistance. Aberrant tumor vasculature in the TME limits nutrient and drug delivery, inhibits anti-tumor immunity, and contributes to a lack of cancer therapy efficacy. Utilizing publicly available scRNA-seq datasets, this study characterizes differences between normal breast and breast tumor endothelial cells (EC), provides insights into tumor endothelial cell subtypes, endothelial anergy, and identifies novel, tumor-specific vascular therapeutic targets. MethodsGene expression data from normal and breast tumor tissue samples were integrated, and the EC subset was extracted via canonical gene marker expression. The EC subset was clustered and evaluated for cell subtypes and differentially expressed genes (DEG). Normal EC (NEC) and tumor EC (TEC) markers were further assessed for correlation to bulk gene expression and patient survival outcomes in cBioPortal and Kaplan-Meier Plotter. Cell type gene expression specificity was evaluated in the 3CA single-cell RNA-seq datasets across multiple cancers. ResultsThis analysis revealed differences in NEC and TEC subtype populations. Breast NEC contained similar proportions of venule and capillary populations, while breast TEC demonstrated a majority of the venule subtype. Further, TEC venules were phenotypically distinct from the NEC venules. Consistent with endothelial anergy, suppression of the key adhesion protein SELE was noted, as well as several pro-inflammatory cytokines including IL6, CCL2, and CXCL8, likely downstream of aberrant NF-kB signaling. Differential gene expression analysis identified several TEC specific up-regulated genes compared to NEC, including CLEC14a, IGFBP4, EMCN, and ADM5. CLEC14a, EMCN, and ADM5 were further validated in the single-cell Curated Cancer Cell Atlas (3CA) to be highly specific to the endothelial cell clusters across multiple tumor types, while IGFBP4 was diversely expressed in endothelial, fibroblast, and some malignant cell types. ADM5, a novel tumor vascular marker, was enhanced in TEC venules and less so in arteriole or capillaries. High expression of ADM5 was associated with poor breast cancer patient survival in the basal PAM50 cancer subtype compared to normal and luminal subtypes. Further, across multiple cancer types, high ADM5 expression was associated with reduced patient survival in anti-PD1- and anti-CTLA4-treated patients but not in anti-PDL-treated patients. ConclusionsIntegration of single-cell RNA-seq data identified an anergic-like response in breast TEC and multiple, highly specific markers to TEC not found in normal breast tissue. CLEC14a and EMCN were validated as TEC markers, extending their annotation in breast TEC, and ADM5 identified as a novel TEC marker in breast and other cancers. Moreover, as ADM5 is associated with reduced patient overall survival, this data suggests that a better understanding of ADM5 and other TEC-specific response pathways may provide novel approaches to reactivate anergic TECs and lead to effective therapeutic interventions for cancer patients. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC="FIGDIR/small/661087v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@a81bf2org.highwire.dtl.DTLVardef@c2b983org.highwire.dtl.DTLVardef@216ab9org.highwire.dtl.DTLVardef@1e5bebb_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG

PurposeThe development of endocrine resistance remains a significant challenge in the clinical management of estrogen receptor-positive (ER+) breast cancer. Metabolic reprogramming is a prominent component of endocrine resistance and a potential therapeutic intervention point. However, a limited understanding of which metabolic changes are conserved across the heterogeneous landscape of ER+ breast cancer or how metabolic changes factor into ER DNA binding patterns hinder our ability to target metabolic adaptation as a treatment strategy. This study uses dimethyl fumarate (DMF) to restore tamoxifen (Tam) and fulvestrant (Fulv) sensitivity in endocrine-resistant cell lines and investigates how metabolic changes influence ER DNA-binding patterns. Experimental DesignTo address the challenge of metabolic adaptation in anti-endocrine resistance, we generated Tam and Fulv resistance in six ER+ breast cancer (BC) cell lines, representing ductal (MCF7, T47D, ZR75-1, and UCD12), lobular (MDA-MB-134--VI), and HER2 amplified (BT474) BC molecular phenotypes. Metabolomic profiling, RNA sequencing, proteomics, and CUT&RUN assays were completed to characterize metabolic shifts, transcriptional and protein changes, and ER DNA-binding patterns in resistant cells. Dimethyl fumarate was assessed for its ability to reverse Tam and Fulv resistance, restore tricarboxylic acid cycle (TCA) cycle function, and restore parental cell (endocrine sensitive) ER DNA binding patterns. ResultsTamoxifen-resistant (TamR) and fulvestrant-resistant (FulvR) cells exhibited disrupted TCA cycle activity, reduced glutathione levels, and altered nucleotide and amino acid metabolism. DMF treatment replenished TCA cycle intermediates and reversed resistance in both TamR and FulvR cells. DMF also increased mevalonate pathway enzyme expression in both TamR and FulvR cells, with TamR cells upregulating enzymes in the cholesterol synthesis phase and FulvR enhancing enzymes in the early part of the pathway. DMF restored ER DNA-binding patterns in TamR cells to resemble parental cells, re-sensitizing them to Tam. In FulvR cells, DMF reversed resistance by modulating ER-cofactor interactions but did not restore parental ER DNA-binding signatures. ConclusionsOur findings provide new insights into how metabolic reprogramming affects ER DNA-binding activity in endocrine-resistant breast cancer. We demonstrate how altering metabolism can reprogram ER signaling and influence resistance mechanisms by targeting metabolic vulnerabilities, such as TCA cycle disruptions. Additionally, our data provide a comprehensive metabolomic, RNA-seq, and CUT&RUN data set relevant to tumor metabolic adaptation leading to acquired endocrine resistance in highly utilized ER+ breast cancer cell lines. This study improves our understanding of how metabolic states alter ER function in endocrine-resistant breast cancer.

BackgroundPrimary luminal breast cancer cells lose their identity rapidly in standard tissue culture, which is problematic for testing hormone interventions and molecular pathways specific to the luminal subtype. Breast cancer organoids are thought to retain tumor characteristics better, but long-term viability of luminal-subtype cases is a persistent challenge. Our goal was to adapt short-term organoids of luminal breast cancer for parallel testing of genetic and pharmacologic perturbations. MethodsWe freshly isolated patient-derived cells from luminal tumor scrapes, miniaturized the organoid format into 5 {micro}l replicates for increased throughput, and set an endpoint of 14 days to minimize drift. Therapeutic hormone targeting was mimicked in these "zero-passage" organoids by withdrawing {beta}-estradiol and adding 4-hydroxytamoxifen. We also examined sulforaphane as an electrophilic stress and commercial neutraceutical with reported anti-cancer properties. Downstream mechanisms were tested genetically by lentiviral transduction of two complementary sgRNAs and Cas9 stabilization for the first week of organoid culture. Transcriptional changes were measured by RT-qPCR or RNA sequencing, and organoid phenotypes were quantified by serial brightfield imaging, digital image segmentation, and regression modeling of cellular doubling times. ResultsWe achieved >50% success in initiating luminal breast cancer organoids from tumor scrapes and maintaining them to the 14-day zero-passage endpoint. Success was mostly independent of clinical parameters, supporting general applicability of the approach. Abundance of ESR1 and PGR in zero-passage organoids consistently remained within the range of patient variability at the endpoint. However, responsiveness to hormone withdrawal and blockade was highly variable among luminal breast cancer cases tested. Combining sulforaphane with knockout of NQO1 (a phase II antioxidant response gene and downstream effector of sulforaphane) also yielded a breadth of organoid growth phenotypes, including growth inhibition with sulforaphane, growth promotion with NQO1 knockout, and growth antagonism when combined. ConclusionsZero-passage organoids are a rapid and scalable way to interrogate properties of luminal breast cancer cells from patient-derived material. This includes testing drug mechanisms of action in different clinical cohorts. A future goal is to relate inter-patient variability of zero-passage organoids to long-term outcomes.

BackgroundIntratumor heterogeneity is a hallmark of most solid tumors, including breast cancers. We applied spatial transcriptomics and single-cell RNA-sequencing technologies to profile spatially resolved cell populations within estrogen receptor-positive (ER+) metastatic breast cancers and elucidate their importance in estrogen-dependent tumor growth. MethodsSpatial transcriptomics and single-cell RNA-sequencing were performed on two patient-derived xenografts (PDXs) of "ER-high" metastatic breast cancers with opposite estrogen-mediated growth responses: estrogen-suppressed GS3 (80-100% ER) and estrogen-stimulated SC31 (30-75% ER) models. The analyses included samples treated with and without 17{beta}-estradiol. The findings were validated via scRNA-seq analyses on "ER-low" estrogen-accelerating PDX, GS1 (5% ER). The results from our spatial and single-cell analyses were further supported by the analysis of a publicly available single cell dataset and a protein-based dual immunohistochemical (IHC) evaluation using three important clinical markers [i.e., ER, progesterone receptor (PR), and Ki67]. The translational implication of these results was assessed by clinical outcome analyses on public breast cancer cohorts. ResultsOur novel space-gene-function study revealed a "proliferative" cell population in addition to three major spatially distinct compartments within ER+ metastatic breast cancers. These compartments showed functional diversity (i.e., estrogen-responsive, proliferative, hypoxia-induced, and inflammation-related). The "proliferative (MKI67+)" population, not "estrogen-responsive" compartment, was crucial for estrogen-dependent tumor growth, leading to the acquisition of luminal B features. The cells with induction of typical estrogen-responsive genes such as PGR were not directly linked to estrogen-dependent proliferation. Additionally, the dual IHC analyses demonstrated the distinct contribution of the Ki67+ proliferative cells toward estrogen-mediated growth and their response to palbociclib, a CDK4/6 inhibitor. The gene signatures developed from the proliferative, hypoxia-induced, and inflammation-related compartments were significantly correlated with worse clinical outcomes, while patients with the high estrogen-responsive scores showed better prognosis, confirming that the estrogen-responsive compartment would not be directly associated with estrogen-dependent tumor progression. ConclusionsFor the first time, our study elucidated a "proliferative" cell population distinctly distributed in ER+ metastatic breast cancers. They contribute differently toward progression of these cancers, and the gene signature in the "proliferative" compartment is an important determinant of luminal cancer subtypes.

PurposeEndocrine therapy in combination with CDK4/6 inhibition doubles the progression-free survival of patients with advanced ER+ breast cancer, but resistance is inevitable, leaving patients with limited treatment options. Experimental DesignWe performed unbiased genome-wide CRISPR/Cas9 knockout screens using ER+ breast cancer cells to identify novel drivers of resistance to combination endocrine therapy (tamoxifen) and CDK4/6 inhibitor (palbociclib) treatment. Screen hits were validated by CRISPR/Cas9 knockout models, mechanistic analyses and evaluation of patient samples. ResultsOur screens identified the inactivation of JNK signalling, including loss of the kinase MAP2K7, as a key driver of combination resistance. We developed multiple CRISPR/Cas9 knockout ER+ breast cancer cell lines (MCF-7 and T-47D) to investigate the effects of MAP2K7, MAPK8 and MAPK9 loss. MAP2K7 knockout increased metastatic burden in vivo and led to impaired JNK-mediated stress responses, as well as promoting cell survival and reducing senescence entry following endocrine therapy and CDK4/6 inhibitor treatment. Mechanistically, this occurred via loss of the AP-1 transcription factor c-JUN, leading to an attenuated response to combination endocrine therapy plus CDK4/6 inhibition. Furthermore, we analysed ER+ advanced breast cancer patient cohorts and found that inactivation of the JNK pathway was associated with increased metastatic burden, and low pJNKT183/Y185 activity correlated with a poorer response to systemic endocrine and CDK4/6 inhibitor therapies. ConclusionsOverall, we demonstrate that suppression of JNK signalling enables persistent growth during combined endocrine therapy and CDK4/6 inhibition. Furthermore, our data provide a pre-clinical rationale to screen patients tumours for JNK signalling deficiency prior to receiving combined endocrine therapy and CDK4/6 inhibition. STATEMENT OF TRANSLATIONAL RELEVANCEResistance to CDK4/6 inhibitors in the context of endocrine therapy resistance presents an urgent clinical challenge for the management of estrogen receptor positive (ER+) breast cancer. However, the mechanisms driving resistance to this therapeutic combination remain poorly understood. Here, we have identified inactivation of JNK signalling, specifically loss of the JNK kinase MAP2K7, as a major determinant of resistance to combined endocrine therapy and CDK4/6 inhibition in ER+ breast cancer. We uncovered that MAP2K7 loss augments tumour survival in vitro and in vivo. This occurs via disruption of activator protein-1 (AP-1) transcription factors, and thus prevents the induction of therapy-induced senescence and JNK-induced stress response. These findings reveal a critical tumour suppressor role for the JNK pathway in ER+ breast cancer, highlighting the importance of identifying patients with deficient JNK signalling and cautioning against the development of JNK inhibitors for this setting.

Breast cancer is a leading cause of female mortality and despite advancements in diagnostics and personalized therapeutics, metastatic disease largely remains incurable due to drug resistance. Fortunately, identification of mechanisms of therapeutic resistance have rapidly transformed our understanding of cancer evasion and is enabling targeted treatment regimens. When the druggable estrogen receptor (ER, ESR1), expressed in two-thirds of all breast cancer, is exposed to endocrine therapy, there is risk of somatic mutation development in approximately 30% of cases and subsequent treatment resistance. A more recently discovered mechanism of ER mediated endocrine resistance is the expression of ER fusion proteins. ER fusions, which retain the proteins DNA binding domain, harbor ESR1 exons 1-6 fused to an in-frame gene partner resulting in loss of the 3 ER ligand binding domain (LBD). In this report we demonstrate that in no-special type (NST) and invasive lobular carcinoma (ILC) cell line models, ER fusion proteins exhibit robust hyperactivation of canonical ER signaling pathways independent of the ligand estradiol or anti-endocrine therapies such as Fulvestrant and Tamoxifen. We employ cell line models stably overexpressing ER fusion proteins with concurrent endogenous ER knockdown to minimize the influence of endogenous wildtype ER. Cell lines exhibited shared transcriptomic enrichment in pathways known to be drivers of metastatic disease, notably the MYC pathway. The heterogeneous 3 fusion partners, particularly transcription factors SOX9 and YAP1, evoked varying degrees of transcriptomic and cistromic activity that translated into unique phenotypic readouts. Herein we report that cell line activity is subtype-, fusion-, and assay-specific suggesting that the loss of the LBD, the 3 fusion partner, and the cellular landscape all influence fusion activity. Therefore, it will be critical to generate additional data on frequency of the ER fusions, in the context of the clinicopathological features of the tumor. SignificanceER fusion proteins exhibit diverse mechanisms of endocrine resistance in breast cancer cell lines representing the no special type (NST) and invasive lobular cancer (ILC) subtypes. Our emphasize upon both the shared and unique cellular adaptations imparted by ER fusions offers the foundation for further translational research and clinical decision making.

BackgroundEpigenetic regulator genes play critical roles in controlling cell identity and are frequently disrupted in breast cancers, suggesting a key driver role in this disease and its associated phenotypes. However, specific epigenetic drivers (epidrivers) of mammary cell plasticity and their mechanistic contributions to this phenotype are poorly characterized. MethodsTo identify potential epidrivers of the emergence of mesenchymal breast cancer stem cell-like phenotypes in non-tumorigenic mammary cells, we employed a CRISPR/Cas9 loss-of-function screening strategy targeting epigenetic regulator genes. This approach was followed by an in-depth validation and characterization of epigenomic, transcriptomic, proteomic and phenotypic changes resulting from the disruption of the putative epidriver gene BAP1. ResultsOur investigation revealed that loss of the histone deubiquitinase BAP1 impacts cellular processes associated with breast cancer cell plasticity such as epithelial-to-mesenchymal transition (EMT) and actin cytoskeleton organization. In addition, we unveiled that BAP1 loss resulted in an overall less permissive chromatin and downregulated gene expression, impacting programs that control cellular glycosylation and leading to decreased glycan abundance and complexity. BAP1 rescue restored the expression of several deregulated genes in a catalytic activity-dependent manner, suggesting that BAP1-mediated cell identity and glycosylation regulation are largely dependent on its histone deubiquitinase activity. ConclusionsOverall, our results point to BAP1 disruption as a driver of mammary cell plasticity and reveal a novel role of BAP1 as an epigenetic regulator of cellular glycosylation.

Breast cancer (BC) is the most common cancer affecting women in the United States. Ductal carcinoma in situ (DCIS) is the earliest identifiable pre-invasive BC lesion. Estimates show that 14 to 50% of DCIS cases progress to invasive BC. Our objective was to identify nuclear matrix proteins (NMP) with specifically altered expression in DCIS and later stages of BC compared to non-diseased breast reduction mammoplasty and a contralateral breast explant using mass spectrometry and RNA sequencing to accurately identify aggressive DCIS. Sixty NMPs were significantly differentially expressed between the DCIS and non-diseased breast epithelium in an isogenic contralateral pair of patient-derived extended explants. Ten of the sixty showed significant mRNA expression level differences that matched the protein expression. These 10 proteins were similarly expressed in non-diseased breast reduction cells. Three NMPs (RPL7A, RPL11, RPL31) were significantly upregulated in DCIS and all other BC stages compared to the matching contralateral breast culture and an unrelated non-diseased breast reduction culture. RNA sequencing analyses showed that these three genes were upregulated increasingly with BC progression. Finally, we identified three NMPs (AHNAK, CDC37 and DNAJB1) that were significantly downregulated in DCIS and all other BC stages compared to the isogenically matched contralateral culture and the non-diseased breast reduction culture using both proteomics and RNA sequencing techniques.

BackgroundThe tumour microenvironment (TME) influences breast cancer progression and treatment response. We investigated whether TME composition predicts tamoxifen benefit in postmenopausal women with oestrogen receptor-positive, HER2-negative (ER+HER2-) breast cancer. MethodsThis study included 513 patients from the Stockholm Tamoxifen (STO-3) trial, which randomised postmenopausal, lymph node-negative women to tamoxifen or no endocrine therapy. Bulk tumour transcriptomes were deconvoluted with the ConsensusTME algorithm to estimate the relative abundance of 18 immune and stromal cell types. A summary score of combined immune cells was created on a per patient basis and evaluated alongside fibroblast and endothelial stromal compartments. Patients were categorised into immune and stromal tertiles on the basis of these scores. Associations between TME composition and tumour characteristics were evaluated using Spearman correlations and Fishers exact test. Tamoxifen benefit was analysed by univariable Kaplan-Meier (log-rank) and multivariable Cox proportional hazards adjusting for age, tumour size, grade, progesterone receptor, Ki-67, and radiotherapy. Differential expression was assessed with limma and pathway enrichment with fgsea using Hallmark gene sets from MSigDB. ResultsLow immune abundance was significantly associated with higher ER expression (Fishers exact test p < 0.001). Among tamoxifen-treated patients, those with low immune scores showed improved distant recurrence-free interval (DRFI) relative to untreated patients (log-rank p < 0.001). Similarly, intermediate endothelial (p < 0.001) and low/intermediate fibroblast abundances (p = 0.042, p = 0.009) were associated with favourable DRFI. In multivariable models, low immune (aHR = 0.17, 95% CI 0.08-0.40), intermediate endothelial (aHR = 0.21, 95% CI 0.09-0.51), and low/intermediate fibroblast tertiles (aHR = 0.50, 95% CI 0.27-0.93; aHR = 0.36, 95% CI 0.17-0.77) retained significance. Transcriptomic analysis revealed enrichment of oestrogen-response, MYC-target, and oxidative-phosphorylation pathways in low-immune and low-fibroblast tumours, while interferon-{gamma} response and allograft rejection pathways were downregulated. ConclusionsTME composition modulates tamoxifen benefit in postmenopausal ER+HER2-breast cancer. Low immune, intermediate endothelial, and low/intermediate fibroblast abundances are associated with improved benefit from tamoxifen, suggesting that both immune and stromal compartments influence endocrine treatment efficacy.

BackgroundBreast cancer risk is shaped by the vast heterogeneity of mammary epithelial cells, comprising basal, luminal progenitor, and mature luminal populations. While transcriptional variation among these lineages has been extensively studied, protein-level features - particularly in high-risk women - remain underexplored, limiting insight into early cellular and molecular determinants of susceptibility. Moreover, little is known about how clinical covariates influence clonogenic capacity, proteomic states, and epithelial proportions, complicating the design of properly controlled human studies of early breast cancer risk. ResultsWe combined low-input proteomics with functional clonogenic assays to profile mammary epithelial cell subpopulations from a cohort of 21 breast tissues encompassing different germline mutation backgrounds, parity status and age. We quantified over 5,555 proteins and observed marked inter-donor variation in epithelial composition, proteomic programs, and colony-forming capacity. Multivariable modeling revealed that clinical covariates - including age, parity, and germline mutation status - modulate both global proteomic architecture and lineage-specific pathway activity. Parity was associated with reduced basal cell abundance, altered luminal progenitor and mature luminal proteomes, and changes in clonogenicity. Pathway analyses identified both conserved and lineage-restricted responses to shared risk factors. Projection of clonogenic signatures onto METABRIC and TCGA tumors further linked functional programs to tumor subtypes and clinical outcomes. ConclusionsThis study provides the most comprehensive proteomic atlas of cell-type resolved diversity in the high-risk breast to date. By defining how clinical covariates remodel epithelial composition and molecular state, it clarifies key sources of biological variability that challenge controlled study design and offers a resource for improving mechanistic insight, risk assessment, and prevention strategies.

This hypothesis-generating study aims to examine the extent to which computed tomography-assessed body composition phenotypes are associated with immune and PI3K/AKT signaling pathways in breast tumors. A total of 52 patients with newly diagnosed breast cancer were classified into four body composition types: adequate (lowest two tertiles of total adipose tissue [TAT]) and highest two tertiles of total skeletal muscle [TSM] areas); high adiposity (highest tertile of TAT and highest two tertiles of TSM); low muscle (lowest tertile of TSM and lowest two tertiles of TAT); and high adiposity with low muscle (highest tertile of TAT and lowest tertile of TSM). Immune and PI3K/AKT pathway proteins were profiled in tumor epithelium and the leukocyte-enriched stromal microenvironment using GeoMx (NanoString). Linear mixed models were used to compare log2-transformed protein levels. Compared with the normal type, the low muscle type was associated with higher expression of INPP4B (log2-fold change = 1.14, p = 0.0003, false discovery rate = 0.028). Other significant associations included low muscle type with increased CTLA4 and decreased pan-AKT expression in tumor epithelium, and high adiposity with increased CD3, CD8, CD20, and CD45RO expression in stroma (P<0.05; false discovery rate >0.2). With confirmation, body composition can be associated with signaling pathways in distinct components of breast tumors, highlighting the potential utility of body composition in informing tumor biology and therapy efficacies.

BackgroundThe tumor microenvironment influences treatment response in ER-positive breast cancer, but what distinguishes responders from non-responders and how it changes during treatment is poorly understood. MethodsER-positive breast tumors treated with neoadjuvant chemotherapy with or without bevacizumab were profiled with bulk proteomics pre-(n = 95), on-(n = 84) and post-treatment (n = 100). A subset of tumors was profiled with spatial single-cell proteomics pre-(n = 13) and on-treatment (n = 11). Cell phenotypes, spatial location and activation states were determined, and cellular colocalization assessed with spatial metrics. Bulk and spatial features were evaluated against treatment response defined by residual cancer burden. ResultsTreatment with bevacizumab amplified chemotherapy effects on proteomic signaling. The immune contexture shifted from suppressive to supportive during treatment through decreased macrophage, regulatory and anergic T-cell density and increased colocalization between epithelial cells and CD8+, CD4+ T-cells and dendritic cells. At baseline, responders had high density of effector memory T-cells, while non-responders had more naive T-cells. In addition, responders had increased colocalization of epithelial cells with macrophages, and effector memory T-cells with M1-like macrophages compared to non-responders. ConclusionsSpatially distinct tumor-immune microenvironments influence response to neoadjuvant treatment, offering valuable insights for guiding treatment decisions.

PurposeAromatase Inhibitors (AI) are standard therapy for hormone receptor positive breast cancers in post-menopausal patients. Disease recurrence is common and previous studies suggest that the altered steroid environment may be a driver of resistance. Using label-free mass-spectrometry we explored the unique androgen receptor (AR) interactome that supervenes in AI resistant breast cancer and the associated hyperandrogenic environment. Experimental DesignAR expression was evaluated in a primary breast cancer tissue-microarray (n=875) with nuclear and cytoplasmic localization quantified. Liquid-chromatography tandem mass-spectrometry (LC-MS/MS) analysis was utilized to identify proteins interacting with the AR in models of AI-resistance. Validation was carried out by co-immunoprecipitation and co-localisation studies. Live-cell imaging, Seahorse MitoStress Assays and flow cytometry were used to quantify changes in mitochondria and cell metabolism arising in models of AI-resistance. ResultsUtilising digital pathology we detected that abundant cytoplasmic AR protein was associated with poor survival only in the post-menopausal cohort, and most significantly, in the therapy-refractory Luminal B subtype (p=0.0085). Models of AI-resistance and androgen excess highlight diffuse AR localisation throughout the cytoplasm and nucleus accompanied by increased mitochondrial mass and membrane potential, and increased oxidative phosphorylation and glycolysis. Exploration of the AR protein interactome identified G3BP1, SLIRP, and IGFBP5 as AR protein partners which are associated with stress, adaptive metabolic response and estrogen receptor repression. ConclusionsThe findings of this study highlight the prognostic potential of cytoplasmic AR immunoreactivity in specific breast cancer subtypes and uncover novel extra-nuclear AR protein interactions that may mediate metabolic adaptations during the development of endocrine-resistance.

BackgroundThe immune response in breast tumors has an important role in prognosis, but the role of spatial localization of immune cells and of interaction between subtypes is not well-characterized. We evaluated the association between spatially-resolved tissue infiltrating immune cells (TIICs) and breast cancer-specific survival (BCSS) in a large multi-center study. Patients and methodsTissue micro-arrays with tumor cores from 17,265 breast cancer patients of European descent were stained for CD8, FOXP3, CD20, and CD163. We developed a machine learning-based tissue-segmentation and immune cell detection algorithm using Halo to score each image for the percentage of marker-positive cells by compartment (overall, stroma, or tumor). We assessed the association between log transformed TIIC scores and BCSS using Cox regression. ResultsTotal CD8+ and CD20+ TIICs (stromal and intra-tumoral) were associated with better BCSS in women with ER-negative (HR per standard deviation = 0.91 [95% CI 0.85 - 0.98] and 0.89 [0.84 - 0.94] respectively) and ER-positive disease (HR = 0.92 [95% CI 0.87 - 0.98] and 0.93 [0.86 - 0.99] respectively) in multi-marker models. In contrast, CD163+ macrophages were associated with better BCSS in ER-negative disease (0.94 [0.87 - 1.00]) and a poorer BCSS in ER-positive disease 1.04 [0.99 - 1.10]. There was no association between FOXP3 and BCSS. The observed associations tended to be stronger for intra-tumoral than stromal compartments for all markers. However, the TIIC markers account for only 7.6 percent of the variation in BCSS explained by the multi-marker fully-adjusted model for ER-negative cases and 3.0 percent for ER-positive cases. ConclusionsThe presence of intra-tumoral and stromal TIICs is associated with better BCSS in both ER-negative and ER-positive breast cancer. This may have implications for the use of immunotherapy. However, the addition of TIICs to existing prognostic models would only result in a small improvement in model performance. HighlightsStromal and intra-tumoral CD8+ and CD20+ TIICs are associated with better survival in ER+ and ER-breast cancers. Stromal and intra-tumoral CD163+ TIICs are associated with better survival in ER- and poorer survival in ER+ breast cancers. The presence of FOXP3+ tissue infiltrating lymphocytes in breast tumors was not associated with survival in breast cancer.

Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a novel PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2,363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 10-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRSs association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.05-1.21, p=0.001). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used a novel approach based on integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.

Purpose: To test whether histology-derived gene-expression signatures from routine hematoxylin and eosin slides are prognostic for recurrence and predictive of chemotherapy benefit in early breast cancer. Methods: We conducted a multi-cohort study including CALGB 9344 (anthracycline +/- paclitaxel), CALGB 9741 (standard vs dose-dense chemotherapy), a pooled Chicago real-world cohort, and the American Cancer Society (ACS) Cancer Prevention Studies-II and -3. Whole-slide images were processed with a previously described pipeline to generate 61 histology-derived signatures per patient. The primary endpoint was distant recurrence-free interval (DRFI), except in ACS, where breast cancer-specific survival was used. Secondary endpoints include distant recurrence-free survival (DRFS) and overall survival. The most prognostic signature in CALGB 9344, selected by Harrell's C-index, was evaluated in additional cohorts. Signature-treatment interaction was assessed by likelihood-ratio tests. Multivariable Cox models incorporating age, tumor size, nodal status, estrogen/progesterone receptor status, and signature were fit in CALGB 9344 to improve risk stratification. Results: A total of 7,170 patients were included across four cohorts. The top histology-derived signature in CALGB 9344 showed strong prognostic performance for 5-year DRFI (C-index 0.63) and performed well across validation cohorts (C-index 0.60, 0.70, and 0.62 in CALGB 9741, Chicago, and ACS, respectively). The strongest predictive signal for treatment benefit was observed for DRFS. High-risk cases identified by the signature demonstrated greater benefit from taxane in CALGB 9344 (adjusted hazard ratio [aHR] 0.76 for DRFS, 95% CI 0.66-0.88; interaction p=0.028), from dose-dense chemotherapy in CALGB 9741 (aHR 0.69, 95% CI 0.56-0.85; interaction p=0.039), and differential chemotherapy benefit in the Chicago cohort (aHR 0.84, 95% CI 0.59-1.21; interaction p=0.009). Combined clinical-histology models improved risk stratification and identified low-risk groups with a 2%-10% risk of distant recurrence or breast cancer death. Conclusion: Histology-derived signatures from H&E images are broadly prognostic and, unlike clinical factors, may predict chemotherapy benefit.

BackgroundThe cell cycle of mammary stem cells must be tightly regulated to ensure normal homeostasis of the mammary gland to prevent abnormal proliferation and susceptibility to tumorigenesis. The atypical cell cycle regulator, Spy1 can override cell cycle checkpoints, including those activated by the tumour suppressor p53 which mediates mammary stem cell homeostasis. Spy1 has also been shown to promote expansion of select stem cell populations in other developmental systems. Spy1 protein is elevated during proliferative stages of mammary gland development, is found at higher levels in human breast cancers, and promotes susceptibility to mammary tumourigenesis when combined with loss of p53. We hypothesized that Spy1 cooperates with loss of p53 to increase susceptibility to tumour initiation due to changes in susceptible mammary stem cell populations during development and drives the formation of more aggressive stem like tumours. MethodsUsing a transgenic mouse model driving expression of Spy1 within the mammary gland, mammary development and stemness were assessed. These mice were intercrossed with p53 null mice to study the tumourigenic properties of Spy1 driven p53 null tumours, as well as global changes in signaling via RNA sequencing analysis. ResultsWe show that elevated levels of Spy1 leads to expansion of mammary stem cells, even in the presence of p53, and an increase in mammary tumour formation. Spy1-driven tumours have an increased cancer stem cell population, decreased checkpoint signaling, and demonstrate an increase in therapy resistance. Loss of Spy1 decreases tumor onset and reduces the cancer stem cell population. ConclusionsThis data demonstrates the potential of Spy1 to expand mammary stem cell populations and contribute to the initiation and progression of aggressive, drug resistant breast cancers with increased cancer stem cell populations.

Assessing the signalling pathway dependencies of tumours that arise autochthonously in genetically engineered mouse models (GEMMs) of breast cancer is particularly challenging due to the high degree of intra- and inter-tumour heterogeneity, as well as the long latency of tumour development in such models. Use of transplantable tumour lines derived from autochthonous tumours ( Mouse Derived Xenografts or MDXs) is one possible solution and has been used successfully in models of BRCA1-associated triple negative breast cancer. However, their potential in ER+ breast cancer models has not been addressed. Here, we assess the utility of orthotopic transplantable tumour lines derived from an autochthonous ER+ Blg-cre Ptenfl/fl p53fl/fl breast cancer model. We show that initial tumour implantation and early passage results in the development of lines of progeny with heterogeneous histopathological phenotypes which is coincident with an accumulation of, or selection for, de novo mutations. Importantly, these lines also display different dependencies on the key pathways that drive tumourigenesis, which can lead to inherent resistance to treatment with pharmacological agents targeting these pathways and makes them important models to test strategies to overcome such resistance.