npj Breast Cancer

Purpose: There are no clinically validated biomarkers to assess recurrence risk and guide treatment de-escalation in Basal-like and HER2-enriched breast cancer. Taxane-based chemotherapy remains a cornerstone of treatment despite significant toxicity. We evaluated the prognostic and predictive utility of the MHCII Immune Activation Score (IA Score) in these subtypes. Experimental Design: We retrospectively analyzed Basal-like and HER2-enriched breast cancers from the NCIC CTG MA.21 trial, which randomized patients with node-positive or high-risk node-negative disease to adjuvant chemotherapy with or without taxanes. MA.21 predated immune checkpoint inhibitors and routine HER2-targeted therapy. Subtype was previously assigned by PAM50. The 36-gene MHCII-IA assay used RNA from formalin-fixed, paraffin-embedded tissue. Multivariable Cox and Kaplan-Meier analyses evaluated associations between IA Score, clinicopathologic variables, tumor-infiltrating lymphocytes (TILs), relapse-free survival (RFS), and taxane benefit. Results: Among Basal-like (N=317) and HER2-enriched (N=155) tumors, higher IA Score was associated with improved RFS independent of lymph node status and provided stronger prognostic discrimination than TILs. Node-negative patients with high IA Score had excellent outcomes (8-year RFS >90%) versus those with low IA Score (8-year RFS <76%). In node-positive disease, high IA Score increased 8-year RFS by >10% relative to low IA Score. IA Score stratified taxane benefit: node-positive IA-low patients benefited, whereas IA-high tumors had favorable outcomes regardless of regimen. Conclusions: MHCII Immune Activation Score is a prognostic and predictive biomarker in Basal-like and HER2-enriched breast cancer. High IA Score identified patients with excellent outcomes before pembrolizumab, trastuzumab, and taxane-based treatment escalation, providing a rationale for prospective risk-adapted de-escalation strategies.

Confounding the treatment options available to patients with triple-negative breast cancer (TNBC) are not only its purported lack of hormone receptor and growth factor receptor targets (ER-/ PR-/ HER2-), but its enrichment in plastic and chemoresistant breast cancer stem cells (BCSCs). Although descriptions of non-canonical PR expression in TNBC are rife in the literature, only canonical PR is considered in the definition of TNBC and is used to determine therapeutic strategy, not least because the utility of non-canonical PR modulation in TNBC chemoresistance is largely unexplored and poorly understood. Here we document the expression of three non-canonical PRs and the canonical PR (PGR) phosphorylated at Ser345 (p-PGR S345) in a panel of TNBC and luminal breast cancer cell lines, and employ combined PR agonists and antagonists to investigate the influence of PR activity on TNBC cell viability and PI3K inhibitor cytotoxicity. To examine the contributions of non-canonical membrane-associated PRs mPR{beta} and PGRMC1, we tested the agonist Org OD 02-0, a synthetic progestin targeted to mPRs; the PGRMC1 antagonist Ag-205; and the antagonist SPA70 against the cytosolic/nuclear PXR, in the background of pan-PI3K inhibition with Buparlisib (BUP). We also reveal that combinations of agonists and antagonists targeted to canonical and non-canonical PRs robustly potentiate the cytotoxic effects of PI3K inhibition, and also exhibit significant cytotoxicity on their own. Using functional assays, flow cytometry, immunocytochemistry and protein expression analyses, we found that simultaneously perturbing PRs and inhibiting PI3K function resulted in significantly greater cell death than vehicle control or BUP alone, and reduced the proportion of ALDH1+ BCSCs in two TNBC cell lines. We conclude that four types of PR are tractable targets in TNBC which participate in cell viability and enhance chemotherapy-induced cytotoxicity, and should be re-evaluated in an evolving definition of this challenging disease.

The intensification of neoadjuvant therapy for early triple-negative breast cancer (eTNBC) - through the addition of carboplatin to standard chemotherapy and the incorporation of pembrolizumab - has markedly improved prognosis in recent years. However, this escalation carries a substantial risk of toxicity, and not all patients require the full regimen to achieve benefit. Realizing individualized treatment strategies will therefore depend on prognostic and predictive biomarkers that can forecast treatment response and long-term outcome. In the present study, we interrogated public gene expression datasets to develop transcriptomic signatures predicting response to neoadjuvant treatment and risk of recurrence. To validate these signatures, we used the Multiplex8+ platform for spatially informed comprehensive transcriptomic profiling in a real-world, multicenter, retrospective cohort of 590 patients diagnosed with eTNBC and treated with neoadjuvant chemotherapy with or without immunotherapy. The diagnostic Multiplex8+ test uses H&E and multiplexed RNA-FISH to guide the selection of specific tumor areas for the whole transcriptome sequencing and signature analysis. In the real-world cohort, the Multiplex8+ signatures were associated with both response and prognosis, remaining highly significant in multivariable models that included clinical parameters. The signatures were complementary to established biomarkers such as stromal tumor-infiltrating lymphocytes. These findings warrant prospective integration of the signatures into risk-stratified clinical trials to support future de-escalation and escalation strategies, enabling a better balance of efficacy, toxicity, cost, and drug availability.

Purpose: Exceptional responses are frequent in patients with HER2-positive (HER2+) metastatic breast cancer (MBC), but predictive biomarkers are lacking. We aimed to investigate the association between detection of minimal residual disease (MRD) via circulating tumor DNA (ctDNA) and exceptional response to first-line HER2 targeted therapy for MBC. Patients and Methods: We identified exceptional (real-world progression-free survival [rwPFS] [&ge;]3 years) and conventional (rwPFS <3 years) responders treated with first-line HER2 targeted therapy for HER2+ MBC and plasma collected at landmark timepoints (e.g., baseline, year [Y] 1, Y2, Y3, at progression). We generated personalized, tissue-informed MRD assays using MAESTRO mutation enrichment sequencing in a pooled format. The primary endpoint was the association between MRD status at Y1 and rwPFS. Results: Of 70 patients, 63 (90%) (40 exceptional and 23 conventional responders) had sufficient samples and successful assay design; MAESTRO was run on 149 samples. A median of 1,823 (range 387-5,000) tumor-specific mutations were tracked per patient. MRD was detected in 49 (32%) samples (median tumor fraction [TFx] 936 ppm; range 3.8-164,068 ppm); 15 (31%) samples had TFx <100 ppm. MRD was associated with outcomes: 0/27 [0%] exceptional versus 9/12 [75%] conventional responders (p<0.001) had detectable MRD at Y1. Exceptional responders who remained progression-free were always MRD-negative (n=30) or cleared MRD by Y1 (n=3). Six exceptional responders experienced late progression, and four of them had a Y3 sample: MRD was detected in three patients (lead time range 2.77-13.47 years), one patient had breast-only progression and was MRD-negative. Conclusions: MRD status at key timepoints is associated with exceptional response and late distant progression, supporting prospective clinical trials implementing MRD testing with highly sensitive tumor-informed assays to guide treatment de-escalation.

Inflammatory breast cancer (IBC) is an aggressive breast cancer subtype characterized by tumor emboli, lymphovascular invasion (LVI), and early dissemination. Herein, we establish adaptive stress response (ASR) as a biologic feature linking stress adaptation to tumor emboli survival, lymphatic dissemination, therapeutic response, and disparities. Using a previously defined 226 ASR-related genes, complementary preclinical models of tumor emboli and lymphatic circulating cell clusters, and independent patient cohorts, we identified ASR genes enriched for XIAP-NF{kappa}B, oxidative stress response, inflammatory, and immune pathways. CXCL8 emerged as one of the most highly upregulated transcripts in tumor emboli and was shared across both models; however, CXCL8, IL6, and PTGS2 were downregulated in lymphatic circulating cell clusters and LVI-positive triple-negative IBC patients, suggesting dynamic remodeling of inflammatory signaling during dissemination. CYP4B1 was associated with ER status, LVI, and therapeutic response across multiple cohorts, implicating metabolic stress adaptation in dissemination. IL6 and PTGS2 were elevated in self-reported Black patients with triple-negative IBC compared to White patients. Pharmacologic inhibition of XIAP-NF{kappa}B and oxidative stress pathways suppressed tumor emboli formation. Collectively, these findings identify ASR signaling as a framework linking tumor emboli survival, dissemination, and therapeutic vulnerability in IBC.

Tumor-infiltrating lymphocytes (TILs) are widely used to assess antitumor immunity in breast cancer but may not reflect the functional competence of adaptive immune responses. We show that immune organization, reflected by tertiary lymphoid structures (TLS) and coordinated humoral and cellular immune programs, represents a distinct dimension of tumor immunity beyond lymphocyte abundance. By integrating histologic, transcriptomic, spatial, and immune receptor profiling analyses across multiple breast cancer cohorts, we show that immune organization is associated with greater immune repertoire diversity, evidence of therapy-induced clonal selection, and improved clinical outcomes, independent of immune infiltration. Transcriptomic measures of immune organization retained independent prognostic value across external cohorts, whereas measures of immune infiltration did not. Furthermore, treatment-induced increases in immune organization, but not immune infiltration, were associated with therapeutic response. These findings identify immune organization as a dynamic and clinically measurable state of adaptive antitumor immunity with implications for prognosis, treatment monitoring, and therapeutic development in breast cancer.

Background The NEO-EXCEL trial hypothesised that aromatase inhibitor (AI)-activity as neoadjuvant endocrine therapy for early-stage breast cancer in postmenopausal women may be enhanced in combination with cyclooxygenase-2 (COX-2) inhibition. Methods NEO-EXCEL was a phase III, placebo-controlled, randomised trial in postmenopausal women with oestrogen receptor (ER)-positive resectable breast cancer with tumours [&ge;]2cm. Women were randomised (1:1:1:1): exemestane (25mg od) plus celecoxib (400mg bid), exemestane (25mg od) plus placebo (bid), letrozole (2.5mg od) plus celecoxib (400mg bid), or letrozole (2.5mg od) plus placebo (bid). Primary endpoint was clinical response (complete/partial) measured by callipers at 16 weeks; a standard assessment method at the time of trial inception. Sixteen-week ultrasound-determined response was the main secondary outcome to verify the calliper-based primary. Analysis was intention-to-treat. Results Due to slow accrual the trial design was redesigned from a definitive 2x2, 1000 patient trial to one randomising 269 patients between 20-Nov-2007 and 29-Apr-2014; 34.9% were human epithelial growth factor receptor 2-positive. AI+celecoxib produced a significantly greater objective clinical response than AI+placebo (72.9% vs 55.6%, P=0.003), which remained after adjustment for AI type and stratification factors (odds ratio = 2.3; 95% CI 1.3-3.8, P=0.003). Ultrasound-determined response was however not significantly enhanced (48.7% [AI+celecoxib] vs 41.2% [AI+placebo], P=0.34). Progression free survival and overall survival remained similar (median follow-up = 5.1 years [range 0.1-7.1]). Conclusions NEO-EXCEL is the first completed, phase III double-blind, placebo-controlled trial testing the addition of celecoxib to AI as neoadjuvant endocrine therapy in early breast cancer. Clinical response showed significant improvement but there was no significant ultrasound-determined response improvement nor any surgical or long-term outcome evidence of AI+COX-2 inhibition improving treatment outcomes for ER+ early resectable postmenopausal breast cancers. Use of short-term celecoxib at 400mg bd for 16 weeks was safe with no excess cardiotoxicity observed.

Objective: To develop and evaluate a deep learning model for five-year breast cancer risk prediction from screening breast ultrasound (BUS) examinations. Methods: This retrospective study included 295,298 breast ultrasound examinations from 122,072 women imaged between 2012 and 2020. Patients were split into training, validation, and test sets; the test set included screening examinations only. BUS-Risk-Net aggregated image features using attention-based multiple instance learning and combined them with age and ultrasound-estimated breast density to predict 2- to 5-year risk. Performance was compared with the full Tyrer-Cuzick model in a matched case-control cohort and with a reduced Tyrer-Cuzick model in the held-out test set. Risk stratification was evaluated within BI-RADS density categories. Results: In the matched case-control cohort (n = 240 women), BUS-Risk-Net achieved a 5-year AUC of 0.632 (95% CI, 0.562-0.702), versus 0.514 for the full Tyrer-Cuzick model (95% CI, 0.440-0.588; p = 0.04). Among 19,548 examinations from 9,015 women eligible for 5-year evaluation in the test set, BUS-Risk-Net achieved an AUC of 0.679 (95% CI, 0.653-0.706), versus 0.594 for the reduced Tyrer-Cuzick model (95% CI, 0.564-0.623; P < .001). Observed 5-year cancer incidence increased across AI-defined risk tiers within each BI-RADS density category, ranging from 0.0% to 5.8% after AI stratification, compared with 2.1% to 3.6% across density categories alone. Discussion: Deep learning models applied to screening breast ultrasound could enable long-term breast cancer risk prediction and stratify risk beyond breast density alone. External and prospective validation is needed before clinical use.

Breast cancer is a heterogeneous disease whose clinical management relies heavily on accurate molecular subtyping. The murine E0771 mammary carcinoma cell line is widely used in preclinical studies, yet its molecular identity remains controversial, with reports variably classifying it as luminal B or triple-negative. In this study, we performed an integrated molecular and functional characterization of two independently sourced E0771 cell line stocks to resolve this discrepancy. Both stocks were genetically authenticated and exhibited concordant phenotypes. Immunohistochemical and molecular analyses demonstrated absence of oestrogen and progesterone receptors, classifying E0771 as triple-negative. Functionally, E0771 cells showed no transcriptional response to oestrogen and displayed resistance to endocrine therapy both in vitro and in vivo. Collectively, our results establish E0771 as an oestrogen-independent, basal-like triple-negative breast cancer model, supporting its appropriate use in studies of hormone-resistant breast cancer biology.

Background Lymph node status and molecular subtype are among the most established prognostic factors in breast cancer. However, the extent to which their prognostic effects vary across different tumor size categories and clinical subgroups remains incompletely understood. We investigated the interplay between nodal status, molecular subtype, and tumor size in a large real world breast cancer cohort and developed a prognostic nomogram for individualized survival prediction. Methods A total of 12,225 women with invasive breast cancer from the Shiraz Breast Cancer Registry were analyzed. Patients were stratified according to tumor size, lymph node status, and molecular subtype. Overall survival (OS) and disease free survival (DFS) were evaluated using Kaplan Meier analyses and subgroup comparisons. Logistic regression was performed to identify predictors of lymph node involvement, while Cox regression was used to determine independent prognostic factors. A nomogram was subsequently developed and internally validated for prediction of 3-year and 5-year OS. Results Of 12,225 patients, 41.7% had lymph node positive disease. Across nearly all tumor size categories and molecular subtypes, nodal involvement was associated with significantly worse OS and DFS. Notably, the survival disadvantage associated with nodal positivity was more pronounced among patients with larger tumors and among those with HER2 positive and triple negative breast cancer (TNBC). Although TNBC demonstrated the lowest rate of lymph node involvement among molecular subtypes (adjusted OR 0.54, 95% CI 0.46-0.63), it appeared to show one of the largest survival gaps between node positive and node negative disease. In the overall cohort, survival outcomes generally ranked from best to worst as Luminal A, Luminal B, HER2 positive, and TNBC. However, survival differences among molecular subtypes were not consistently observed across all tumor size and nodal status subgroups. When significant differences were present, Luminal A and Luminal B tumors consistently showed superior outcomes compared with HER2 positive and TNBC tumors. Multivariable analysis identified lymph node status, tumor size, molecular subtype, lymphovascular invasion, tumor necrosis, type of surgery, radiotherapy, hormone therapy, and adjuvant chemotherapy as independent prognostic factors. A nomogram integrating clinicopathological and treatment variables demonstrated good predictive performance, with time dependent AUCs of 0.749 and 0.751 for 3 year and 5 year OS, respectively, and showed good calibration. Conclusions The prognostic impact of lymph node status is not uniform across breast cancer subgroups and appears particularly pronounced in larger tumors and biologically aggressive subtypes. Despite a lower likelihood of nodal involvement, TNBC showed substantial outcome deterioration when nodal metastasis was present. These findings highlight the importance of jointly considering nodal status, molecular subtype, and tumor burden in prognostic assessment.

Spatial transcriptomics can reveal localized tumor-immune relationships, but thousands of spots from one tissue section do not provide thousands of biological replicates. We evaluated the distinction between within-section association and patient-level reproducibility using public breast cancer datasets. In a 10x Genomics Visium discovery section containing 3,798 spots, hypoxia-related transcription was inversely associated with cytotoxic gene activity in neighboring spots (Spearman{rho} = -0.202). High-hypoxia spots also had lower neighborhood cytotoxic scores than low-hypoxia spots (rank-biserial effect = -0.286). We then tested the directional association in an independent HER2-positive cohort comprising 36 sections, 13,619 spots, and eight patients. Only 19 of 36 sections and five of eight patients showed negative associations. The median patient-level correlation was -0.043 and did not differ from zero in a one-sided exact Wilcoxon test (P = 0.473). Sensitivity analyses using alternative cytotoxic and hypoxia signatures, neighborhood sizes, and Kendall correlation did not support a consistent inverse patient-level effect. Thus, a strong single-section association did not consistently reproduce across patients. These results caution against interpreting spot-level spatial associations from one section as patient-level biological effects.

Background: Breast cancer survivors often experience psychological distress that may increase suicide risk. Marital status, a proxy for social support, may influence this risk, but its role within a competing-risk framework is unclear. This study examined the association between marital status and suicide mortality and assessed modification by socioeconomic and geographic factors. Methods: This is a population-based cohort study using SEER data, including adults diagnosed with primary breast cancer from 2000 to 2022. Marital status was classified as married/partnered or unmarried/non-partnered. Baseline characteristics were balanced using subdistribution inverse probability of treatment weighting (sIPTW). Suicide mortality was analyzed using sIPTW-weighted Fine-Gray competing-risk models, treating non-suicide deaths as competing events. Landmark, subgroup, interaction, and sensitivity analyses were performed. Results: Among 825,047 patients, 40.7% were unmarried. Covariates were well balanced after weighting (SMD <0.01). During follow-up, 529 suicide deaths occurred. Unmarried status was associated with higher suicide mortality (sHR = 1.34, 95% CI: 1.12-1.60). Male sex and estrogen receptor-negative tumors increased risk, while older age and non-White race were protective. Findings were consistent in Cox models (HR = 1.45) and sensitivity analyses (sHR = 1.42). Landmark analyses showed persistent associations at 1, 3, and 5 years. The association was attenuated in the highest income quartile but not modified by rural-urban status. Conclusions: Unmarried breast cancer patients had higher suicide mortality. These findings support integrating psychosocial assessment and targeted suicide prevention into survivorship care, especially for socially vulnerable groups.

Triple Negative Breast Cancer (TNBC) is the deadliest and most aggressive subtype of breast cancer, with poor prognosis and high rates of metastasis. Despite knowledge of metabolic rewiring in TNBC, the systems-level coordination of these adaptive pathways remains unmapped. This integrative systems-level analysis reveals key metabolic hub genes and identifies ATP1A2 as a significant prognostic marker. Analysis identified 764 differentially expressed genes, with 89 enriched biological processes predominantly involving metabolic pathways. Co-expression network analysis of 261 genes identified metabolic hub genes including LEP, ADIPOQ, and ATP1A2. To evaluate the prognostic framework, survival analysis of the top 10 hubs was performed on synthetic survival data, revealing ATP1A2 as a significant marker (p = 0.03) under Cox regression, with elevated expression associating with altered survival outcomes. By systematically mapping metabolic rewiring in TNBC, this work identifies ATP1A2 as an actionable therapeutic target and establishes a systems-level framework for rational drug discovery and patient stratification in this aggressive malignancy.

Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) are a mainstay therapy for homologous recombination (HR)-deficient cancers; however, resistance remains a major clinical challenge. Previously, through a genome wide CRISPR screen, we identified ZNF251 haploinsufficiency as a novel driver of PARPi resistance. In BRCA1-mutant (BRCA1mut) cells, ZNF251 deficiency led to HR hyperactivation, conferring PARPi resistance that could be reversed by RAD51 inhibition. In this study, we further show that ZNF251 deficiency induces replication stress and a pseudo-senescence state, in which cells exhibit molecular and phenotypic markers of senescence while retaining proliferative capacity. Because senomorphic and senolytic therapies can target senescent cells, we tested whether these approaches could overcome PARPi resistance in ZNF251-deficient breast cancer cells. Critically, targeting this senescence-like state with either senomorphic agents, such as cytokine inhibitors, or senolytic agents, such as BCL-2 and BCL-XL inhibitors, overcame PARPi resistance ex vivo and in vivo. Importantly, pseudo-senescence was also observed in other PARPi-resistant contexts driven by HR hyperactivation, including 53BP1- and Shieldin-mutant cells, suggesting that it may represent a broader mechanism underlying PARPi resistance in breast cancer. Furthermore, in two olaparib-resistant, BRCA-mutant triple-negative breast cancer organoid models, treatment with DT2216, a BCL-XL-targeting PROTAC, sensitized both models to olaparib. Together, our work defines a novel pathway linking HR hyperactivation, replication stress, and pseudo-senescence, and positions both senomorphic and senolytic therapies as promising strategies to overcome PARPi resistance in BRCA1mut breast cancer. HighlightsO_LIZNF251 deficiency drives PARP inhibitor resistance through HR hyperactivation, replication stress, and pseudo-senescence in BRCA1-mutant breast cancer. C_LIO_LISenomorphic and senolytic therapies overcome PARP inhibitor resistance in vitro, in vivo, and in patient-derived organoid models. C_LIO_LIPseudo-senescence represents a shared vulnerability of HR-hyperactivated PARPi-resistant cancers and can be therapeutically targeted. C_LI

Triple-negative breast cancer (TNBC) exhibits pronounced molecular heterogeneity, yet the majority of published transcriptomic prognostic signatures suffer from limited reproducibility and have not achieved clinical translation. We systematically benchmarked 62 published TNBC prognostic signatures across 6 independent cohorts (n=1,357) using a unified analytical framework spanning multiple scoring algorithms, survival endpoints, and threshold strategies. While 17 signatures demonstrated consistent univariate prognostic associations, only 4 remained independently prognostic after adjustment for clinicopathological variables, and none achieved robustness across all analytical conditions-underscoring the fragility of existing classifiers. Leveraging genes with concordant survival associations across all 6 discovery cohorts, we identified a reproducible 15-gene directionally concordant gene set (DCGS) signature and distilled it into MetaSig-EFS, a 13-gene prognostic model optimized using a cohort-aware DeepSurv framework. MetaSig-EFS demonstrated robust cross-cohort generalizability, achieving validation concordance indices of 0.89 in GSE19615 and 0.69 in JBordet, with corresponding 3- and 5-year time-dependent AUROCs of 0.89 and 0.96 in GSE19615 and 0.80 and 0.71 in JBordet, respectively, while retaining independent prognostic value across established TNBC molecular sub-typing systems. Leveraging the TAHOE-100M transcriptomic perturbation atlas, we systematically prioritized candidate therapeutics through large-scale drug repurposing, identifying Paclitaxel as the top-ranked compound, followed by Venetoclax and Tucatinib. Together, these findings provide biologically informed and clinically actionable therapeutic hypotheses that extend the translational utility of our validated prognostic framework for TNBC risk stratification.

Bone metastasis remains a major clinical challenge in advanced breast cancer. Downregulation of type I interferon signalling, a critical immunomodulatory pathway in anti-cancer immunity and disease progression, is a defining feature of this process. Here, we utilised an IFN-reporter system to perform unbiased epigenetic compound screens to identify agents that could restore type I IFN signalling. This screen identified Decitabine, a DNA hypomethylating agent, that enhanced tumor immunogenicity across a broad range of mouse and human breast cancer cell lines, including bone-derived lines. Mechanistically, suppression of interferon-stimulated genes is highly correlated with elevated DNMT1 expression in bone metastasis compared with primary tumor, in both mouse models and matched human samples. Decitabine treatment was sufficient to reactivate interferon stimulated genes in bone-derived 4T1.2 cell lines via hypomethylation of type I interferon pathway gene promoter regions. Correspondingly, in the syngeneic 4T1.2 metastasis mouse model, Decitabine treatment conferred a survival benefit and reduced metastatic potential, particularly in bone. Our findings reveal DNA methylation as a key regulator of the transcriptional programs underlying bone metastasis, providing mechanistic insight into how Decitabine reactivates type I interferon signalling and reduces metastatic potential, highlighting epigenetic reprogramming as a promising approach for targeting metastatic breast cancer. STATEMENT OF SIGNIFICANCEBone metastasis remains a major clinical challenge and a key mechanism of progression to bone is the suppression of tumor-inherent type I interferon signalling. We identified Decitabine, a DNA hypomethylating agent, as a promising therapeutic agent to enhance tumor immunogenicity across a broad range of breast cancer cell lines, including bone metastasis-derived lines. Our findings support DNA methylation as a key regulator of transcriptional programs associated with bone metastatic progression, and provide mechanistic insight into how Decitabine reactivates type I interferon signalling and reduces metastatic potential in vivo. These results highlight epigenetic reprogramming as a promising approach for targeting metastatic breast cancer.

Recent NCCN guideline highlighted AI-based mammographic risk prediction, but AI-based breast cancer detection remains questionable to translation. One barrier is current models often do not match routine clinical reasoning, which may add decision burden than benefits. In practice, radiologists compare current and prior mammograms while assessing breast density, bilateral symmetry, and lesion laterality. To align AI with this reasoning, we developed MuSTAF, a multi-task spatiotemporal attention fusion model for patient-level breast cancer classification from longitudinal full-field digital mammography. MuSTAF uses up to three recent mammograms, integrates temporal and cross-view information, refines suspicious-region features, and jointly predicts cancer status, breast density, and bilateral symmetry, with a separate laterality classifier for cancer-positive cases. In an internal case-control cohort (n = 351), MuSTAF achieved a cancer classification (AUC=0.84) exceeding all architecture-level baselines and published mammography AI models adapted to the same task (AUC [&le;] 0.81). Simultaneously, it achieved AUCs of 0.83/0.80 for density/laterality assessments, and removing these auxiliary tasks reduced cancer detection performance. On the external CSAW-CC dataset (n = 8,723), model performance improved from 0.72 to 0.88 when restricting cancer cases to those with latest exams within 60 days before diagnosis, showing that temporally distant labels may shift detection evaluation toward risk prediction. Longitudinal analysis further showed that three recent exams outperformed five exams internally (AUC = 0.84 vs 0.80) and externally (0.72 vs 0.66), indicating recent imaging evidence mattered more than remote history. Overall, MuSTAF model improved longitudinal mammographic cancer classification while providing auxiliary outputs, and clarified temporal factors for applying AI to screening detection.

Sentinel lymph node biopsy (SLNB) is increasingly omitted in early-stage breast cancer, often prompting whole-breast irradiation (WBI). We evaluated partial-breast irradiation (PBI) without axillary surgery among 78 clinically node-negative patients (median age 75) treated from 2014 to 2022. After 53-month median follow-up, no ipsilateral, regional, or distant recurrences occurred. These results demonstrate excellent outcomes and suggest PBI is a feasible, safe alternative to WBI when SLNB is omitted.

Hormone receptor-positive, HER2-negative breast cancers are often poorly infiltrated by immune cells and derive limited benefit from current immunotherapy strategies. Here, using paired tumour samples from the randomised window-of-opportunity D-BIOMARK trial (NCT03691311), we investigated the immunomodulatory effects of denosumab in early luminal breast cancer. Short-term preoperative denosumab reduced tumour-cell proliferative transcriptional programs and immunosuppressive features of the local tumour microenvironment, enhancing innate and adaptive immune activation and altering circulating cytokine profiles. High-resolution spatial transcriptomics revealed coordinated remodelling of tumour, immune, fibroblast and endothelial compartments after treatment. Denosumab reduced immune-tumour spatial separation and enhanced T cell activation, accompanied by a shift from matrix-associated tumour programs towards increased tumour-T cell communication. Copy number-informed tumour-state inference further identified a reduced representation of genomically complex, immune-poor tumour subclones after treatment. Together, these findings identify denosumab as a modulator of tumour-microenvironment crosstalk and support RANKL blockade as a strategy to render immune-poor luminal breast tumours more permissive to immune engagement.

Structural AbstractO_ST_ABSBackgroundC_ST_ABSTriple-negative breast cancer (TNBC) represents a major clinical challenge due to its aggressiveness, heterogeneity and limited availability of effective targeted therapy. We investigated whether LRP-1, a multifunctional cell-surface endocytic and signaling receptor, contributes to TNBC progression. MethodsUsing CRISPR-Cas9, LRP-1-deficient murine 4T1 and human HS578-T TNBC cells were used. Functional consequences were assessed through migration, invasion, and 3D spheroid assays, imaging of focal adhesions and actin organization, atomic force microscopy, and plasmin activity assays. Global molecular reprogramming was analyzed by label-free quantitative proteomics and secretomics. LRP-1-deficient or proficient 4T1 cells were implanted orthotopically in immunocompetent mice; tumor progression was monitored longitudinally while peritumoral collagen architecture and immune microenvironment composition were characterized by second harmonic generation imaging and immunohistochemistry. ResultsWe show that LRP-1 loss reduces TNBC aggressiveness, as reflected by decreased migration and invasive capacity, reduced spheroid evasion, and significant morphological changes in focal adhesion and actin structure. LRP-1-deficient cells became stiffer and showed lower LOXL-4 levels, while pericellular proteolytic activity remained unchanged, suggesting other proteases mechanism. Multi-omic analysis revealed alterations in extracellular matrix (ECM), epithelial-mesenchymal transition, and inflammatory pathways. In vivo, LRP-1-deficiency reduced tumor progression and peritumoral collagen deposition, while increasing CD8+ T and Natural Killer cell infiltration, together with a cytokine profiling compatible with a more immune-permissive microenvironment. ConclusionsLRP-1 act as a key contributor in TNBC progression through matrix remodeling, mechano-adaptation, and immune exclusion. Positioning it as a candidate biomarker for TNBC patients who are likely to benefit from stroma-targeting therapies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/732906v2_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@1b595c2org.highwire.dtl.DTLVardef@7b208aorg.highwire.dtl.DTLVardef@1956e54org.highwire.dtl.DTLVardef@17e55d0_HPS_FORMAT_FIGEXP M_FIG C_FIG