Breast Cancer Research

The normal adult male breast has not been characterized at single-cell resolution, leaving the cellular basis of male breast cancer (MBC) biology undefined. Here we present an integrated single-cell RNA sequencing atlas of the adult human breast comprising 174,471 cells from 17 donors (3 male, 14 female), including 18,117 male-derived cells. This revealed that the male breast retains all three epithelial populations, basal (BC), luminal progenitor (LP), and luminal committed cells (LC), but with an increase in LC at the expense of BC and LP across all three male donors. Male LC were distinguished from female by elevated ESR1 and PGR mRNA, enrichment of RNA processing and ribosome biogenesis programs, reduced inflammatory cytokine and growth factor signaling, elevated estradiol gene set enrichment scores, and higher inferred activity of developmental patterning transcription factors. This pattern was observed across differential expression, gene ontology, ligand profiling, and regulon-based analyses, and was not restricted to sex chromosome-linked gene expression. This is consistent with the near-universal estrogen receptor (ER) positivity that characterizes MBC clinically. This atlas provides the first cellular and transcriptional reference for the normal male breast and a resource for investigating sex differences in mammary biology, germline susceptibility variant interpretation, and modeling breast malignancies.

Advances in spatial transcriptomics enable high-throughput quantitation of both established and novel biomarkers at single cell resolution, offering the potential to transform diagnostics. Using Xenium in situ technology in FFPE human breast samples, we address two challenges in the cancer field: 1. achieving reliable normalization of gene expression across heterogeneous sample populations; 2. identifying biomarkers that predict invasion or metastasis. We describe a scalable approach to identify low-variation housekeeping (HK) genes within any given sample set, then use those HK genes for cross- and intra-sample normalization of biomarkers. Analyzing 12 FFPE human breast samples-primarily ductal carcinoma in situ (DCIS)-with a custom 280-gene panel, we identified four HK genes (EEF1G, EEF2, MALAT1, and RPLP0) that exhibited minimal variability in tumor cells, four tumor cell biomarkers (LDHA, SDC1, PIGR, SFRP1) that increased or decreased with tumor grade, and one tumor-associated myoepithelial biomarker (LAMC2). Normalizing biomarkers to the four HK genes preserved the dynamic range of expression necessary for distinguishing tumor grades, outperforming HKs from legacy RT-PCR diagnostic panels. Lastly, we employed a cell-agnostic approach in the tumor periphery to quantify MMP11, a biomarker correlated with proliferative and potentially pre-invasive ducts. Our results establish a single cell normalization method for spatial in situ transcriptomics and reveal and quantitate biomarkers relevant to DCIS risk and progression.

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.

BackgroundTriple-negative breast cancers (TNBC) occur more frequently in African Americans and are associated with worse outcomes when compared to other subtypes of breast cancer. These cancers lack expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) and have limited treatment options. To shed light on mechanisms behind these differences and suggest novel treatments, we used a meta-analytic approach to identify gene expression differences in breast tumors for people with self-reported African or European ancestry; additionally, we compared gene expression levels based on ER, PR, HER2 and TNBC status. MethodsAfter gathering and standardizing gene expression data and metadata from 106 datasets (representing 27,000 samples), we identified genes that were expressed differently between these groups via random-effects meta-analyses. To evaluate the robustness of these gene lists, we devised a novel computational methodology that uses cross validation and classification. We also computed overlaps between the most significant genes and known signaling pathways. ResultsUsing a false discovery rate threshold of 0.05, we identified genes that are known to play a significant role in their respective breast cancer subtypes (e.g., ESR1 for ER status and ERBB2 for HER2 status), thus confirming the validity of our findings. We also discovered genes that have not been reported previously and may be new targets for breast cancer therapy. GATA3, CA12, TBC1D9, XBP1 and FOXA1 were among the most significant genes for ER, PR, and TNBC. However, none of these genes overlapped with HER2 status, supporting prior research that HER2 tumors are mechanistically different from endocrine breast cancers. The genes identified from the race meta-analysis--including DNAJC15, HLA-DPA1, STAP2, CEP68, MOGS--have not been associated previously with race-specific breast-cancer outcomes, highlighting a potential area of further research. ConclusionsWe have carried out a large meta-analysis of breast cancer gene expression data, identifying novel genes that may serve as potential biomarkers for breast cancer in diverse populations. We have also developed a computational method that identifies gene sets small enough to be analyzed and explored in future studies. This method has the potential to be applied to other cancers.

Background Background breast features are frequently noted in pathology reports alongside invasive breast cancer but rarely factor into prognosis or treatment decisions. Their relationship to tumor characteristics and patient outcomes remains incompletely characterised. Methods We conducted a retrospective cohort study of 7,603 patients with Stage I-III invasive breast cancer (diagnosed 1991-2022, age <80 years) from the Joint Breast Cancer Registry in Singapore. Natural language processing (NLP) was applied to 9,754 free-text pathology reports to extract co-existing background breast features, with accuracy validated by dual-reviewer assessment of 200 reports. Unsupervised hierarchical clustering grouped extracted features into three categories. Associations with tumor characteristics were assessed by multinomial logistic regression, and ten-year overall survival by Cox proportional hazards models (median follow-up 9.6 years; 620 deaths). Results Here we show that NLP-based extraction of background breast features from routine pathology reports achieves an accuracy of over 90% across features. Lobular neoplasia and benign proliferative changes are associated with less aggressive tumor characteristics, whereas early neoplastic and papillary lesions are more prevalent in HER2-enriched and luminal B tumor subtypes. Benign proliferative changes are associated with better survival in age- and year-adjusted models (hazard ratio 0.91, 95% CI 0.86-0.97), but this association is attenuated after adjustment for stage and subtype. Conclusions NLP-enabled extraction of background breast features from pathology text is feasible at scale. These features reflect tumor biology but do not independently add prognostic information beyond established clinical variables.

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.

BackgroundWe investigated the impact of gender-affirming testosterone therapy (TT) on breast cancer (BC) risk and tumor progression. Materials and methodsWe leveraged a large human breast tissue dataset (n=417) to assess TT and terminal duct lobular unit (TDLU) involution, complemented with tissue markers (ER, PR, AR, and Ki67; n=24) and transcriptome profiling (n=8). Preclinical models assessed the effect of TT on BC incidence (MMTV-Cre Pik3caf/wt n=149 and K14-Cre Brcaf/fTp53f/f n=153), murine mammary gland architecture (n=60), and tumor transcriptome (n=10). Lastly, we discuss trans masculine invasive BC cases and summarize tumor characteristics in this population (n=24). ResultsTT promotes TDLU involution by reducing epithelial proliferation via altered estrogen signaling and increases ER+, PR+, and Ki67+ extralobular stromal cells. In mice, TT similarly reduced mammary gland ductal branching and terminal end buds. TT decreased Pik3ca-related ER+ BC incidence by 81% compared to female controls (adj RR 0.19, 95% CI 0.08-0.45), but did not affect Brca1-related triple negative BC incidence. TT did not influence tumor progression in either model but shaped the Pik3ca-related ER+ tumor microenvironment toward a pro-tumor phenotype. Most trans masculine BC cases were ER+ (83.3%), small and node-negative, but were also moderately to poorly differentiated (70.8%). ConclusionTT reduces ER+ BC risk but does not eliminate risk, and has a negligible impact on BRCA1-related triple-negative BC risk. TT does not affect tumor growth once tumors are established but modulates the tumor microenvironment. Our work supports the need for breast cancer screening in TT users. HighlightsO_LITT reduces but does not completely ablate the breast epithelium. C_LIO_LITT decreases PIK3CA-related ER+ breast cancer incidence by 81% compared to female control mice (adj RR 0.19, 95% CI 0.08-0.45), but does not affect BRCA1-related triple negative breast cancer incidence. C_LIO_LITT does not affect tumor progression once the tumor is established. C_LIO_LITrans masculine breast tumors are mostly ER+ (83.3%), small and node-negative, but are also moderately to poorly differentiated (70.8%). C_LIO_LITailored risk assessment and ongoing surveillance strategies are key for the care of transmasculine individuals who use TT. C_LI

Pathogenic germline TP53 alterations cause Li-Fraumeni Syndrome (LFS), and breast cancer is the most common cancer in LFS females. We performed first of its kind multimodal analysis of LFS breast cancer (LFS-BC) compared to sporadic premenopausal BC. Nearly all LFS-BC underwent biallelic loss of TP53 with no recurrent oncogenic variants except ERBB2 (HER2) amplification. Compared to sporadic BC, in situ and invasive LFS-BC exhibited a high burden of short amplified aneuploid segments (SAAS). Pro-apoptotic p53 target genes BAX and TP53I3 failed to be up-regulated in LFS-BC as was seen in sporadic BC compared to normal breast tissue. LFS-BC had lower CD8+ T-cell infiltration compared to sporadic BC yet higher levels of proliferating cytotoxic T-cells. Within LFS-BC, progression from in situ to invasive BC was marked by an increase in chromosomal instability with a decrease in proliferating cytotoxic T-cells. Our study uncovers critical events in mutant p53-driven tumorigenesis in breast tissue.

Tumor Infiltrating Lymphocytes (TILs) have been shown to be prognostic in Triple-Negative Breast Cancer (TNBC), but are rarely considered in other subtypes, particularly estrogen receptor (ER) positive cancers (70-80% of breast cancers), due to lower TIL counts. However, the spatial proximity of lower abundance TILs has not been evaluated in relation to breast cancer prognosis. In this study, multiplex immunofluorescent-stained images were used to identify cell types based on cytokeratin (Ck), CD8, and FoxP3 expression. Using distance-based visual morphometry between epithelial and immune cells, we computed new metrics, proximity and consistency, which capture spatial relationships between Ck+ tumor cells and CD8+ T-cells. Prognostic significance of proximity and consistency were compared to lymphocyte counts using log-rank tests. Worse relapse-free survival (RFS) was observed for both ER+ and ER-breast cancers with low proximity and consistency of CD8+ cells. Among ER negative breast cancers, proximity had the highest RFS hazard ratio (HR 1.84, 95% CI [1.18,2.87]). Among ER positive participants, RFS hazard ratios for proximity and consistency were 2.04 (95% CI [1.39, 2.98]) and 1.82 (95% CI [1.23, 2.69]) respectively. These associations were stronger than those observed for lymphocyte count (HR 1.35, 95% CI [0.92,1.98], log-rank p-value = 0.13). These IF-derived spatial metrics were also associated with established TILs metrics and RNA-based expression-based measures of tumor adaptive immune response. The prognostic significance of proximity in ER+ breast cancer implies that spatial parameters may identify individuals who would benefit from immune therapy; up to 75% of breast cancers experience T-cell proximity suggestive of immune susceptibility.

Hormone therapies are frequently used to reduce breast cancer risk in individuals at increased risk for primary or subsequent disease; however, tissue-level responses to these therapies are heterogeneous and incompletely understood. Background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) provides a non-invasive radiologic readout of breast tissue features associated with endocrine responsiveness and cancer risk. Although BPE is associated with hormonal exposure, a subset of patients with BPE do not show a response to preventive endocrine therapy and therefore may remain at increased breast cancer risk. In this study, we integrated single-nucleus RNA sequencing and spatial transcriptomics to define the determinants of endocrine responsiveness in the setting of BPE. We identify hormone-driven epithelial cells with high levels of estrogen signaling and endocrine responsiveness, together with immune-associated epithelial programs characterized by diminished luminal identity and increased expression of immune-modulatory pathways, including major histocompatibility complex (MHC) class II and CD74. Functional organoid assays validate that these epithelial states exhibit differential sensitivity to tamoxifen and demonstrate that inflammatory signals can induce immune-modulatory epithelial programs. Together, our findings identify hormone signaling and immune programs as key determinants of endocrine responsiveness in breast tissue and provide a biological basis for interpreting radiologic markers relevant to cancer prevention.

The development of breast cancer has been observed due to altered regulation of mammary gland developmental processes. Thus, a better understand of the normal mammary gland development can reveal possible mechanism in how normal cells are re-programmed to become malignant cells. E2F1-4 are part of the E2F transcription factor family with varied roles in mammary development. However, little is known about the role of E2F5 in mammary gland development. A combination of scRNAseq and predictive signature tools demonstrate the presence of E2F5 in the mammary gland and showed altered activity during the various phases of mammary gland development and function. Testing the hypothesis that E2F5 regulates mammary function, we generated a mammary-specific E2F5 knockout mouse model, resulting in modest mammary gland development changes. However, after a prolonged latency the E2F5 conditional knockout mice developed highly metastatic mammary tumors with metastases in both the lung and liver. Transplantation of the tumors revealed metastases to lymph nodes that was enriched through serial transplantation. Through whole genome sequencing and RNAseq analysis we identified, and then confirmed in vivo, that Cyclin D1 was dysregulated in E2F5 conditional knockout mammary glands and tumors. Based on these findings, we propose that loss of E2F5 leads altered regulation of Cyclin D1, which facilitates the development of mammary tumors.

Profiling of cell-free DNA (cfDNA) has been well demonstrated to be a potential non-invasive screening tool for early cancer detection. However, limited studies have investigated the detectability of cfDNA methylation markers that are predictive of cancers in asymptomatic individuals. We performed cfDNA methylation profiling using cell-free DNA methylation immunoprecipitation sequencing (cfMeDIP-Seq) in blood collected from individuals up to seven years before a breast cancer diagnosis in addition to matched cancer-free controls. We identified differentially methylated cfDNA signatures that discriminated cancer-free controls from pre-diagnosis breast cancer cases in a discovery cohort that is used to build a classification model. We show that predictive models built from pre-diagnosis cfDNA hypermethylated regions can accurately predict early breast cancers in an independent test set (AUC=0.930) and are generalizable to late-stage breast cancers cases at the time of diagnosis (AUC=0.912). Characterizing the top hypermethylated cfDNA regions revealed significant enrichment for hypermethylation in external bulk breast cancer tissues compared to peripheral blood leukocytes and breast normal tissues. Our findings demonstrate that cfDNA methylation markers predictive of breast cancers can be detected in blood among asymptomatic individuals up to six years prior to clinical detection.

Single nuclei analysis is allowing robust classification of cell types in an organ that helps to establish relationships between cell-type specific gene expression and chromatin accessibility status of gene regulatory regions. Using breast tissues of 92 healthy donors of various genetic ancestry, we have developed a comprehensive chromatin accessibility and gene expression atlas of human breast tissues. Integrated analysis revealed 10 distinct cell types in the healthy breast, which included three major epithelial cell subtypes (luminal hormone sensing, luminal adaptive secretory precursor, and basal-myoepithelial cells), two endothelial subtypes, two adipocyte subtypes, fibroblasts, T-cells, and macrophages. By integrating gene expression signatures derived from epithelial cell subtypes with spatial transcriptomics, we identify specific gene expression differences between lobular and ductal epithelial cells and age-associated changes in epithelial cell gene expression patterns and signaling networks. Among various cell types, luminal adaptive secretory cells and fibroblasts showed genetic ancestry dependent variability. A subpopulation of luminal adaptive secretory cells with alveolar progenitor (AP) cell state were enriched in Indigenous American (IA) ancestry and fibroblast populations were distinct in African ancestry. ESR1 expression pattern was distinctly different in cells from IA compared to the rest, with a high level of ESR1 expression extending to AP cells and crosstalk between growth factors and Estrogen Receptor signaling being evident in these AP cells. In general, cell subtype-specific gene expression did not uniformly correlate with cell-specific chromatin accessibility, suggesting that transcriptional regulation independent of chromatin accessibility governs cell type-specific gene expression in the breast.

Breast cancer remains the leading cause of cancer related mortality among women globally, yet South Asian populations are critically underrepresented in genomic studies. Here, we present whole-genome and transcriptome analyses of over 500 treatment naive, clinically annotated breast tumors from India, representing the first large scale integrative omics characterization of this population. In addition to established drivers, we identify novel significantly mutated genes, including ISM2, TERF2, and DHRSX, under positive selection, along with previously unreported potentially pathogenic somatic variants. Notably, the distribution of key hotspot mutations appears shaped by immune escape pressures. We uncover recurrent copy number alterations driving lipid metabolic reprogramming (e.g., NCEH1 and PLD1 amplifications) and complex structural events, including IKZF3 promoter hijacking leading to ERBB2 overexpression and TTC28 associated genomic instability findings not previously described in breast cancer. Mutational processes are dominated by DNA repair deficiency, APOBEC activity, and genome instability. We identify three genomic features significantly associated with poor post surgical recurrence free survival. Transcriptomic profiling reveals distinct intrinsic subtypes with divergent immune landscapes, including a high risk HER2 androgenic cluster with the worst outcomes. Additionally, we find a novel transcriptomic signature that robustly captures a HER2 like transcriptional state within triple-negative breast cancer patients with major implications for TNBC treatment. Finally, clinically actionable germline and somatic alterations are revealed with high significance, highlighting opportunities for therapeutic repurposing. Together, the study establishes a comprehensive molecular atlas of breast cancer in an underrepresented population, providing critical insights into tumour biology and advancing precision oncology.

PurposegBRCA1/2 pathogenic variant (PV) carriers have elevated young-onset breast cancer risk. Understanding the distinct genomic landscapes of gBRCA1- and gBRCA2-associated breast cancer, including presence of PARP and CDK4/6 inhibitor (PARPi; CDK4/6i) response-associated alterations, may inform treatment selection for these patients. Patients and methodsWe evaluated 136 treatment-naive primary tumors from POSH study participants diagnosed with breast cancer before age 50 years (92.6% diagnosed [&le;]40): gBRCA1 86(63.2%), gBRCA2 50(36.8%). We evaluated somatic mutational and copy number variations (CNV), allele-specific loss of heterozygosity (asLOH), homologous recombination deficiency (HRD), and single-base substitution signatures (SBS) from whole exome sequencing. ResultsBoth gBRCA1 (93%) and gBRCA2 (96%) breast cancers had high rates of asLOH. We found significant differences between gBRCA1 and gBRCA2 tumors in average HRD scores (57.4{+/-}1.3 vs 43.7{+/-}1.5, p<0.0001) and SBS composition: SBS1 (aging-associated) 12.9 vs 7.3, p=0.013; SBS18 (reactive oxygen species [ROS]-associated) 1.4 vs 0, p=0.007; SBS3 (HRD-associated) 27.3 vs 42.6, p=0.002; and SBS26 (mismatch repair-associated) 5.9 vs 9.4, p=0.049. Compared to gBRCA2 tumors, gBRCA1 tumors with asLOH were significantly enriched for gains of chr6q, and alterations in Hallmark ROS, DNA repair, and epithelial-mesenchymal transition pathways. In ER-positive, HER2-negative tumors from POSH gBRCA1/2 carriers compared to noncarriers from the TCGA, we found significant enrichment of RB1 (OR:6.3, 95%CI:2.8-15.4, padj=0.001), TP53 (OR:4.6, 95%CI:1.9-12.1, padj=0.017), FAT1 (OR:3.9, 95%CI:1.84-8.7, padj=0.013), and MYC (OR:4.0, 95%CI:1.8-9.1, padj=0.017) SNV/indels/CNVs, which are associated with CDK4/6i resistance. ConclusionOur data suggest that PARPi may be preferable over CDK4/6i to treat ER-positive, HER2-negative breast cancer in young-onset gBRCA1/2-associated breast cancer when both therapies are considered in adjuvant and metastatic settings. Additionally, we identified significant differences between gBRCA1- and gBRCA2-associated tumors, which may inform therapeutic development.

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.

In diploid cells, allelic imbalance occurs when gene alleles are expressed at different levels. To investigate the allelic imbalance landscape in tumor samples, we developed Interval-Based Allelic Imbalance Detection (IB-Aid), a quantitative framework that uses interval arithmetic to robustly distinguish monoallelic from biallelic gene expression by computing confidence intervals based on sequencing measurement uncertainty. We applied this approach to The Cancer Genome Atlas Breast Invasive Carcinoma tumor samples and through unsupervised gene enrichment analyses, identified a group of patients with a distinct monoallelic gene expression signature. Notably, these patients were enriched in Black/African American patients and had tumors which had not been previously classified into any established molecular subtype. Clinically, these tumors were associated with poor overall survival, with survival outcomes comparable to the aggressive basal subtype. These findings suggest a potential link between allelic imbalance and breast cancer development and point to genetic and epigenetic mechanisms that drive allelic imbalance as novel biomarkers for prognosis and design of targeted treatment strategies.

The tumor suppressor NF1 is a critical driver of sporadic breast cancer and NF-related breast cancers. We utilized distinct Nf1-deficient immunocompetent rat models to investigate Nf1 function in mammary development and homeostasis. Here we demonstrate that Nf1 deficiency dramatically accelerates mammary morphogenesis, alters TEB cell organization, and proliferation. Notably, we observed a shift in luminal-basal epithelial lineage commitment within Nf1-deficient lines with early tumor onset. In addition, we detected subpopulations of hybrid EMT cells (Ecad+/CK14+) within the invasive edge and stroma of Nf1-deficient tumors. Nf1 deficiency restricted luminal progenitor potential and resulted in gene expression changes associated with decreased cell adhesion and increased EMT signatures. Together our findings support a model in which Nf1 loss of function results in lineage plasticity throughout mammary morphogenesis and promotes EMT-mediated invasion. This study reveals a previously unknown role for the tumor suppressor neurofibromin in mammary homeostasis and phenotypic plasticity during breast cancer progression.

BackgroundBreast cancer is comprised of distinct molecular subtypes. Studies have reported differences in risk factor associations with breast cancer subtypes, especially by tumor estrogen receptor (ER) status, but their consistency across racial and ethnic populations has not been comprehensively evaluated. MethodsWe conducted a qualitative, scoping literature review using the Preferred Reporting Items for Systematic Reviews and Meta-analysis, extension for Scoping Reviews to investigate consistencies in associations between 18 breast cancer risk factors (reproductive, anthropometric, lifestyle, and medical history) and risk of ER-defined subtypes in women who self-identify as Asian, Black or African American, Hispanic or Latina, or White. We reviewed publications between January 1, 1990 and July 1, 2022. Etiologic heterogeneity evidence (convincing, suggestive, none, or inconclusive) was determined by expert consensus. ResultsPublications per risk factor ranged from 14 (benign breast disease history) to 66 (parity). Publications were most abundant for White women, followed by Asian, Black or African American, and Hispanic or Latina women. Etiologic heterogeneity evidence was strongest for parity, followed by age at first birth, post-menopausal BMI, oral contraceptive use, and estrogen-only and combined menopausal hormone therapy. Evidence was limited for other risk factors. Findings were consistent across racial and ethnic groups, although the strength of evidence varied. ConclusionThe literature supports etiologic heterogeneity by ER for some established risk factors that are consistent across race and ethnicity groups. However, in non-White populations evidence is limited. Larger, more comparable data in diverse populations is needed to better characterize breast cancer etiologic heterogeneity.

Collagen breast stroma is the basis of increased breast density and a well-established breast cancer risk factor, yet proteomic regulation of normal breast stroma remains poorly defined. This study reports spatial regulation of the collagen proteome in normal breast tissue sections annotated by clinical characteristics. Normal breast samples from the Susan G. Komen tissue bank included data on genetic ancestry (n=40 total; n=20 African ancestry; n=20 European ancestry), body-mass-index (BMI), age, and mammogram density by the Breast Imaging Reporting and Data System (BI-RADS). Multiplexed cell marker staining showed CD44 and COL1A1 markers modulated with BMI. Collagen fiber widths by second harmonic generation (SHG) showed potential contrasts in BMI categories by genetic ancestry. Targeted extracellular matrix proteomics mass spectrometry imaging showed collagen alpha-1(I) chain domain proteome was spatially heterogenous across the normal breast microenvironment with site specific post-translational modification of proline hydroxylation. Signatures computationally extracted from breast stroma reported that 47 collagen peptides distinguished BI-RADS categories (area under the receiver operating curve>0.7; p-value>0.05). Proteomic alterations were found between overweight to obese categories with strong positive associations to BMI by multivariate analysis. This study provides the first spatial analysis of the collagen proteome in normal breast within contexts of cellular markers and clinical characteristics.