npj Breast Cancer

Purpose: Beyond estrogen receptor (ER) positivity, no genomic biomarker reliably identifies ER+ breast cancer patients who derive differential benefit from endocrine therapy (ET). We performed an unbiased genomic screen to discover genes predicting ET response and characterized the top candidate across clinical settings, treatment modalities, and an independent validation cohort. Experimental Design: We screened 240 genes in 1,197 metastatic ET-treated patients from the MSK-CHORD clinical genomics database using Cox proportional hazards regression with false discovery rate (FDR) correction. The top candidate, core-binding factor subunit beta (CBFB), was characterized across four cohorts defined by disease setting (metastatic/adjuvant) and treatment (ET/chemotherapy), with multivariable adjustment, gene-by-treatment interaction testing, left-truncation sensitivity analysis for guarantee-time bias, and external validation in METABRIC (N = 1,499 ER+). Results: CBFB mutations (prevalence, ~5%) were the only gene associated with improved time to progression (TTP). In metastatic ET patients, CBFB-mutated tumors (n = 80) demonstrated significantly longer TTP (hazard ratio [HR], 0.44; 95% CI, 0.29-0.67; P = .0002, FDR q = .010) with no chemotherapy benefit (HR, 1.16; P = .65). The gene-by-treatment interaction was significant (HR, 0.37; P = .009). Effects were robust to multivariable adjustment (HR, 0.46-0.50), independent of histology, and preserved under left-truncated Cox regression (HR, 0.38). In the adjuvant setting, CBFB mutations predicted improved recurrence-free survival (HR, 0.52; 95% CI, 0.31-0.85; P = .010), with no effect under chemotherapy. In METABRIC, CBFB mutations predicted improved ER+ overall survival (HR, 0.52; P = 9.3e-5). Conclusions: CBFB mutations identify ~5% of ER+ breast cancers with exceptional ET benefit. As CBFB is included on all major cancer gene panels, this biomarker requires no additional testing infrastructure for clinical implementation.

Assessment of pathologic complete response (pCR) following neoadjuvant chemotherapy (NAC) remains an unmet clinical need in breast cancer. Fibroblast activation protein inhibitor (FAPI) PET targets the tumor microenvironment and may therefore enhance response evaluation after NAC. This study aimed to compare the performance of [68Ga]Ga-FAPI-04 PET, [18F]FDG PET, and contrast-enhanced MRI for predicting pathologic response after NAC in breast cancer, with separate analyses for primary breast lesions and axillary lymph nodes. MethodsIn this prospective single-center diagnostic accuracy study, women with biopsy-confirmed stage II-III breast cancer underwent baseline and post-therapy [68Ga]Ga-FAPI-04 PET/MRI, [18F]FDG PET/CT, and contrast-enhanced MRI before surgery. Quantitative PET parameters were evaluated for primary tumors and axillary lymph nodes. pCR was defined as ypT0/isN0. Significant variables identified in univariable analyses were further explored using least absolute shrinkage and selection operator (LASSO) analysis, and receiver-operating-characteristic (ROC) analysis was performed to assess diagnostic performance. Fibroblast activation protein expression was also assessed by immunohistochemistry in paired pre- and post-therapy tumor specimens from a subset of patients. ResultsTwenty-four patients completed the study protocol, yielding 25 primary lesions and 44 metastatic lymph nodes across 27 axillary compartments. Overall patient-level pCR was achieved in 13 of 24 patients (54.17%). The lesion-level pCR rate was 60.00% (15/25) for primary breast lesions, and the node-level pCR rate was 72.73% (32/44) for axillary lymph nodes. For primary tumor response, post-therapy [68Ga]Ga-FAPI-04 SUVmax showed the highest diagnostic performance (AUC, 0.84; sensitivity, 80.00%; specificity, 80.00%; accuracy, 80.00%), whereas the optimal [18F]FDG parameter was {Delta} TBR% (AUC, 0.747). For nodal response, post-therapy [68Ga]Ga-FAPI-04 SULmean showed the highest diagnostic performance (AUC, 0.89; sensitivity, 91.67%; specificity, 81.25%; accuracy, 84.09%) and was significantly different from the best [18F]FDG parameter ({Delta} SULmax%, AUC, 0.669) on DeLong testing (P < 0.05). MRI achieved AUCs of 0.733 for primary lesions and 0.770 for lymph nodes. Stromal FAP expression positively correlated with [68Ga]Ga-FAPI-04 SUVmax and was markedly reduced in lesions achieving pCR. ConclusionPost-therapy [68Ga]Ga-FAPI-04 PET may serve as a promising adjunctive imaging biomarker for predicting pathologic response after NAC in breast cancer, particularly for axillary nodal assessment. These findings suggest that FAPI PET may provide clinically relevant information for preoperative evaluation of residual disease burden, potentially contributing to more individualized surgical planning and treatment decision-making.

Metabolic dysfunction is increasingly recognized as a risk factor for poor outcomes in breast cancer, but whether incretin-based therapies confer survival benefit beyond weight loss remains unresolved. Using a federated electronic health record platform spanning nearly 29 million patients, we evaluated breast cancer survival after semaglutide and tirzepatide initiation in routine care. In 1:1 propensity-matched pooled-comparator analyses, semaglutide was associated with improved overall survival versus metformin, sodium-glucose cotransporter 2 (SGLT2) inhibitor, and dipeptidyl peptidase 4 (DPP4) inhibitor users, with 54 deaths among 2,433 semaglutide users (2.2%) versus 395 deaths among 2,433 comparators (16.2%) over 24 months (log-rank P < 0.001). Tirzepatide showed a favorable survival association relative to pooled anti-diabetic comparators that did not meet statistical significance (P = 0.24), with 3 deaths among 220 users (1.4%) versus 64 deaths among 220 comparators (29.1%). In a head-to-head propensity-score-matched comparison, overall survival did not differ significantly between semaglutide- and tirzepatide-treated patients with pre-existing breast cancer (2,117 per arm; P = 0.12). In semaglutide-treated patients alive and observable at the 1-year landmark, higher maximum dose achieved was significantly associated with lower post-landmark mortality (P = 0.034), with an event rate of approximately 1.0% in the high-dose group ([&ge;]1.7 mg) versus approximately 4.5% in the low-dose group (0.25-1.0 mg). Despite a linear dose-weight loss relationship for semaglutide, however, weight-loss strata did not separate survival outcomes (global P = 0.22). In tirzepatide-treated patients alive and observable at the same landmark, neither maximum dose achieved nor weight-loss strata separated post-landmark survival (P = 0.98 and P = 0.50, respectively). Structured EHR and AI-based clinical-note analyses further showed significantly lower frequency of documented metastatic disease in semaglutide-treated patients relative to pooled anti-diabetic comparators, including any metastasis (7.0% versus 15.0%, rate ratio 0.5, P < 0.001), bone metastasis (1.0% versus 5.2%, rate ratio 0.2, P < 0.001), and liver, lung, or brain metastases (all P < 0.001). LLM-derived cause-of-death extraction further showed a 60% lower relative proportion of cancer-associated deaths in semaglutide-treated patients (19% of ascertainable deaths) than in matched pooled anti-diabetic comparators (47% of ascertainable deaths), with comparator deaths more often attributed to cancer progression involving metastatic breast cancer, leptomeningeal carcinomatosis, and cancer-driven organ failure. Overall, this study demonstrates that semaglutide use in patients with pre-existing breast cancer is associated with a dose-correlated but weight-loss independent improvement in overall survival. These findings motivate prospective trials of GLP-1 receptor agonists in breast cancer across various stages and treatment settings.

PurposeTo 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. MethodsWe 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 Harrells 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. ResultsA 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. ConclusionHistology-derived signatures from H&E images are broadly prognostic and, unlike clinical factors, may predict chemotherapy benefit. HighlightsO_LIHistology-derived H&E signatures consistently predicted recurrence risk across randomized trials and real-world cohorts. C_LIO_LIA single cutoff of a low-risk histology signature predicted taxane benefit and dose-dense chemotherapy benefit. C_LIO_LICombined clinical-histology models identified low-risk groups with 2%-10% risk of distant recurrence. C_LI

Purpose: The prognostic role of tumor-infiltrating lymphocytes in luminal breast cancer remains uncertain, partly because density-based metrics do not capture spatial interactions between immune cell subsets. We developed a density-independent spatial metric quantifying macrophage-T cell proximity and assessed its prognostic value. Experimental Design: Using multiplex immunohistochemistry across three breast cancer cohorts (exploratory, n = 17; discovery, n = 687; validation, n = 305), we measured nearest-neighbor distances from T cells to M1-like and M2-like macrophages, benchmarked against a randomly subsampled total macrophage pool. We defined the Macrophage Spatial Polarity Index (MSPI) as the difference between M2-to-T cell and M1-to-T cell affinity scores, where higher values reflect an M2-dominated spatial phenotype. Cox regression was used to assess associations with distant disease-free survival (discovery) and overall survival (validation). Results: M2-like macrophages preferentially localized near T cells, independent of cell density. Higher MSPI was associated with shorter survival in luminal cancers (discovery: HR = 1.45, p < 0.001), with the strongest effect in young women with early-stage disease (HR = 2.16, p < 0.0001). MSPI remained independently prognostic after adjustment for stage, systemic treatment, and diagnosis period (HR = 2.31, 95% CI 1.73-3.09, p < 0.0001) and was non-significant in HER2-positive and triple-negative subtypes. Validation in an independent ER-positive cohort confirmed the finding (HR = 1.30, p = 0.004). Pooled analysis yielded HR = 2.13 (95% CI 1.68-2.70, p = 3.45 x 10-10). Conclusions: MSPI is a robust prognostic biomarker in luminal breast cancer, particularly in young women with early-stage disease, warranting further validation for risk stratification and therapeutic guidance.

PurposeTo develop and validate a multimodal recurrence-risk model integrating histology, genomic testing, and clinical variables. MethodsWe developed AI-Path, a whole-slide image biomarker for recurrence prediction trained in CALGB 9344, and validated it in three independent cohorts: TAILORx, a multi-site Chicago cohort, and the MDX-BRCA cohort. We then integrated AI-Path with Oncotype DX Recurrence Score (RS), tumor size, and nodal status into a Cox model, PathClinRS, fit using 60% of cases from TAILORx, with the remaining 40% held out for validation. The primary end point was distant recurrence-free interval. Performance was assessed using Harrells concordance index (C-index) and Kaplan-Meier analyses. ResultsA total of 12,418 patients were included. In TAILORx, AI-Path outperformed RS for distant recurrence (C-index, 0.682 vs 0.647; P = .038), driven by superior prediction of late recurrence (0.656 vs 0.567; P < .001). In node-negative disease, PathClinRS outperformed RSClin in the TAILORx fitting (0.72 vs 0.70; P = .016) and validation sets (0.74 vs 0.70; P = .004). In node-positive disease, PathClinRS outperformed RSClinN+ in Chicago (0.94 vs 0.74; P < .001) and MDX-BRCA (0.71 vs 0.66; P = .004) cohorts. Compared with NATALEE eligibility, PathClinRS identified nearly twice as many high-risk node-negative patients while maintaining a comparable 10-year distant recurrence risk (16.7% vs 16.6% per NATALEE eligibility in TAILORx fitting; 21.0% vs 19.4% in TAILORx validation). PathClinRS identified 68% of intermediate risk premenopausal patients as low-risk with no evidence of chemotherapy benefit, compared to only 36% identified as low risk by standard clinicopathologic criteria. ConclusionDigital histopathology provides prognostic information complementary to genomic assays and has the potential to personalize therapy beyond existing clinicogenomic tools.

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.

Cancer-related fatigue is the most common and persistent symptom in breast cancer, with fatigue reported up to 10 years post-diagnosis. Unlike many cancers, fatigue in breast cancer often arises during early-stage disease in the absence of cachexia. While many factors contribute to fatigue, the direct contribution of cancer-associated skeletal muscle pathology remains poorly understood. Here we analyzed pectoralis major muscle biopsies from individuals with non-metastatic breast cancer and non-cancer controls. Using single-fiber morphometry and spatial transcriptomics, we identified fiber-type-specific structural alterations and spatially localized transcriptional reprogramming within the muscle microenvironment. Single-fiber morphometry revealed selective atrophy of oxidative type I and type IIa muscle fibers, while glycolytic type IIx fibers were relatively preserved. Concordant spatial transcriptomic profiling revealed suppression of oxidative metabolic programs, evidence of mitochondrial dysfunction, and spatially localized catabolic signaling originating from intramuscular adipocytes. This study introduces an integrated framework for profiling skeletal muscle architecture and spatially localized gene expression in surgically obtained muscle biopsies and represents the first application of spatial transcriptomics to human skeletal muscle from individuals with cancer. These findings demonstrate structural and metabolic remodeling of skeletal muscle in non-metastatic breast cancer and suggest targeting muscle metabolism represents a promising therapeutic strategy for cancer-related fatigue.

Objective Accurate prognostication of recurrence risk in HR+/HER2- early breast cancer is central for therapeutic decision-making, including identifying patients who may safely avoid adjuvant systemic therapy. However, the performance of existing prognostic tools remains insufficient for effective clinical stratification, motivating the development of artificial intelligence (AI)-based methods to improve risk stratification. Methods Ataraxis Breast CTX (ATX) is a multi-modal AI test that integrates H&E-stained whole-slide images with clinicopathologic features to predict risk of recurrence for individual patients. This study aims to validate ATX in an external dataset enriched for clinically low-risk patients from Dordrecht, the Netherlands. ATX scores were generated for 892 women diagnosed with early HR+/HER2- breast cancer. Of the 892 patients, 299 did not receive adjuvant systemic therapy. The discriminative performance of ATX was assessed using C-index and its stratification ability was evaluated by log-rank tests comparing Kaplan-Meier survival curves across risk groups. Results ATX achieved a C-index of 0.71 and a 5-year time-dependent AUC of 0.71, demonstrating strong discrimination in predicting recurrence-free survival (RFS). Among 299 patients who received no adjuvant therapy, ATX achieved a C-index and time-dependent AUC of 0.78 and 0.81 respectively, suggesting ATX retains prognostic information in the absence of systemic therapy. ATX scores were used to stratify patients into risk groups using a pre-specified threshold, where 656 (74%) were classified as ATX low-risk and 236 (26%) were classified as high-risk. Notably, untreated and treated ATX low-risk patients had comparable 5-year RFS (untreated: 5-year RFS = 96%, 95% CI = 92-97%; treated: 5-year RFS = 96%, 95% CI = 93-97%) with near identical 10-year RFS (86%, 95% CI = 83-92% for both), suggesting ATX low-risk status may identify a subgroup with favorable prognosis independent of treatment exposure. Conclusion ATX provides robust prognostic stratification in an external cohort of clinically low-risk HR+/HER2- early breast cancer and identifies a subgroup of patients who did not receive systemic therapy with favorable observed outcomes. These results support prospective validation of ATX as a decision-support tool for adjuvant therapy de-escalation in HR+/HER2- early breast cancer.

Abstract Background Immune-related adverse events (irAEs) involving the breast remain rarely reported. Purpose To characterize clinical and imaging features of camrelizumab-associated breast lesions (CABLs). Materials and Methods This retrospective dual cohort study (October 2019 to February 2026) included 196 female patients. Cohort A comprised 180 non-breast cancer patients; Cohort B comprised 16 breast cancer patients receiving neoadjuvant camrelizumab. Baseline characteristics, treatment response, and CT/MRI features were compared between CABL-positive and CABL-negative groups using Mann-Whitney U and chi-square tests. Results CABLs developed in 34.4% (62/180) of Cohort A and 93.8% (15/16) of Cohort B. CABL-positive patients were younger (median 50.5 vs 54.5 years; P = 0.006) and more often premenopausal (46.8% vs 26.3%; P = 0.009). The objective response rate was relatively high among patients with positive lesions; in Group A, the disease progression rate was lower in the CABL-positive group than in the CABL-negative group (3.2% vs 17.8%), whilst in Group B, the pathological complete response rate was as high as 53.3% (8/15). On CT/MRI, CABLs were predominantly multiple (62.5%), with well-defined margins and unrestricted diffusion. The predominant time-intensity curve (TIC) pattern was washout (46.7%). Median time to onset was 2-3 cycles (the second MRI scan); most lesions disappeared (40.3%) and shrank (46.8%) during follow-up. ADC values of lesions were significantly higher than those of primary tumors (1.847+/-0.284 vs 0.976+/-0.055 x10[-3] mm[2]/s; P < 0.001). Histopathology of four lesions revealed lymphocytic infiltration and fibrosis without malignancy. Conclusion CABLs are benign reactive changes driven by multiple factors. Their recognition prevents misinterpretation as disease progression, thereby avoiding unnecessary treatment discontinuation or biopsy.

PurposeTriple-negative breast cancer (TNBC) exhibits substantial clinical heterogeneity, with some patients experiencing early recurrence and poor survival despite similar clinicopathologic features. We sought to determine whether quantitative measures of intratumoral collagen architecture and composition derived from standard histopathologic specimens can identify patients at risk of recurrence and adverse survival outcomes. Experimental DesignWe analyzed a retrospective cohort of 79 TNBC tumors assembled into a tissue microarray using a multimodal computational pathology framework integrating Massons Trichrome staining with COL1 and COL3 immunohistochemistry. Collagen architecture was quantified using fiber-based image analysis and unsupervised clustering, while collagen composition was assessed using a normalized COL3:COL1 ratio. Associations with recurrence-free interval (RFI) and overall survival (OS) were evaluated using Kaplan-Meier analysis, restricted mean survival time (RMST), and Cox proportional hazards modeling. ResultsUnsupervised analysis identified four distinct collagen architectural states, which were consolidated into low-risk and high-risk groups based on recurrence patterns. High-risk collagen architecture was associated with significantly worse long-term RFI (log-rank p=0.025; RMST difference 10.1 months). Independently, a higher COL3:COL1 ratio was associated with improved OS (log-rank p=0.042; RMST difference 9.4 months). Integration of architectural and compositional biomarkers further refined risk stratification, identifying a subgroup with high-risk architecture and low COL3:COL1 ratio that exhibited the poorest survival outcomes. Notably, collagen-based stratification identified patients with divergent outcomes not readily predicted from tumor stage alone. ConclusionsQuantitative assessment of intratumoral collagen architecture and composition provides clinically meaningful prognostic information in TNBC and enables stratification of recurrence and survival risk. These findings support extracellular matrix phenotyping as a practical and scalable computational pathology approach for refining risk assessment in TNBC. Translational RelevanceTriple-negative breast cancer (TNBC) remains clinically challenging due to heterogeneous outcomes that are not fully captured by standard clinicopathologic variables. In this study, we demonstrate that quantitative features of intratumoral collagen architecture and composition, derived from routine pathology specimens, provide clinically meaningful prognostic information. Collagen-based biomarkers, including distinct collagen architectural phenotypes and the COL3:COL1 ratio, identify patient subgroups with distinct recurrence and survival outcomes, particularly among individuals whose risk is not adequately predicted by conventional staging. Importantly, these features can be extracted from widely available histological stains and immunohistochemistry, supporting the potential integration into existing pathology workflows. These findings support the tumor microenvironment as an underutilized source of biomarkers and suggest that extracellular matrix-based phenotyping may improve risk stratification and inform clinical decision-making in TNBC.

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.

Introduction: With recent approvals of multiple targeted therapies for triple-negative breast cancer (TNBC), including antibody-drug conjugates and immunotherapy in biomarker-selected populations, it is critical to define the temporal evolution of cell-surface target expression from early-stage to metastatic disease, the co-expression patterns across these markers, and optimal quantification methodologies. Here we report biomarker expression profiles measured by multi-omics and pathology-based platforms in patients with TNBC using a large cohort of matched longitudinal tumor samples. Methods: Patients who underwent neoadjuvant chemotherapy (NAC) for stage I-III TNBC or were diagnosed with any stage TNBC and developed metastatic recurrence were retrospectively identified from an institutional database and prospective research metastatic biopsy protocol. Tumor samples from diagnosis (DX), residual disease (RD) post-NAC (if applicable), and metastasis/recurrence (MR) were collected. Quantification of HER2, TROP2, and PD-L1 expression was performed by immunohistochemistry (IHC), whole-exome sequencing, transcriptome sequencing, and targeted mass spectrometry (MS). For HER2, TROP2, and stromal tumor-infiltrating lymphocytes (sTILs), both manual pathologist assessment and computational pathology quantification were obtained. HER2 status was categorized as HER2-0 or HER2-low by local (L-IHC) and central (C-IHC) review, TROP2 status was defined as low (H-score <100), medium (H-score 100-200) or high (H-score >200), and PD-L1 as low (tumor area positivity, TAP <5%) or high (TAP [&ge;]5%). Pathologist-assessed sTILs were classified as low (<10%), medium ([&ge;]10% and <40%) or high ([&ge;]40%). Biomarkers were compared between primary (DX/RD) and MR, and between pre- vs post-NAC (DX-RD) samples. Correlations between markers, quantification methods, inferred PAM50 subtype, and clinical variables of interest were evaluated. Results: A total of 359 samples from 110 patients with TNBC with data available from at least one platform were included in the analysis. HER2-low prevalence at DX, RD, and MR was: 51% (50/98), 40% (21/53), and 27% (16/60); TROP2 high/medium was 90% (47/52), 91% (42/46), and 88% (28/32); PD-L1-high was 51%, 50%, and 38% (9/24); and sTILs-high/medium was 88% (59/67), 80% (40/50), and 49% (17/35), respectively. While TROP2-high/medium vs low remained stable over time, HER2 IHC and sTILs significantly decreased from DX/RD to MR samples, both at the cohort-level (HER2, p=0.0081; sTILs, p=4.6x10e-5) and longitudinal patient-level (HER2, p=0.030; sTILs, p=0.0077), with a similar decreasing trend for PD-L1 that did not reach statistical significance. HER2 concordance (0 vs low) between L-IHC and C-IHC was 78% (91/116). ERBB2, TACSTD2 and CD274 mRNA expression were significantly correlated with IHC protein levels, though only TACSTD2 had limited overlap in distribution of gene expression between high/medium vs low groups. Strong correlation between protein membrane staining intensity from computational pathology, protein expression measured by MS, and pathologist-assed IHC was observed across all biomarkers tested by each method. In comparisons between biomarkers, pathologist-assessed PD-L1 IHC and sTILs were significantly correlated (p=0.0001); 94% (51/54) of PD-L1-high tumors were classified as sTILs high/medium. PAM50 subtype was not significantly correlated with time point or biomarker status, although there was a trend toward more HER2-enriched tumors in HER2-low (20%, 5/25) vs HER2-0 (6%, 3/52) (p=0.086). Across biomarkers and clinical variables, an association between age and sTILs was observed (p=0.038, FDR=0.42) due to a decrease in sTILs high/medium tumors with age, primarily driven by post-treatment (RD/MR) but not DX samples. Conclusions: Multi-platform and multi-omics profiling in this large unique cohort of longitudinal TNBC samples revealed distinct patterns of expression and dynamic changes of key biomarkers of interest for targeted therapies. Given variability with manual IHC scoring, improved methods for quantification of expression may help optimize treatment selection in an individualized manner.

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.

BackgroundTriple-negative breast cancer (TNBC) is a clinically aggressive breast cancer subtype. It is a heterogeneous disease that remains difficult to stratify and that still lacks durable and biomarker-guided therapeutic options. Low expression of the tumour suppressor MTUS1 is associated with aggressive breast cancer features, but the biological properties of MTUS1-low TNBC remain insufficiently defined. Our goal was to determine whether low MTUS1 expression defines shared proliferative and stress-adaptation mechanisms that could guide candidate therapeutic strategies and corresponding target/drug pairs in MTUS1-low TNBC. MethodsWe labelled tumours from seven public TNBC RNA-seq cohorts based on the lowest and highest MTUS1 expression tertiles. Differential gene expression was analysed using gene set enrichment analysis (GSEA) on the Hallmark pathway database to identify deregulated biological pathways between MTUS1-low TNBC tumours and their MTUS1-high counterparts. Reproducibility was examined across independent TNBC cohorts and secondarily in broader breast cancer and selected TCGA tumour cohorts. Gene essentiality scores from CRISPR-Cas9 experiments in TNBC cell-line models were correlated to MTUS1 expression in these cell lines, to propose therapeutic strategies and their corresponding candidate target/drug pairs. ResultsMTUS1-low tumours showed a reproducible pathway-level proliferation mechanism driven by the MYC oncogene and sustained by up-regulated oxidative phosphorylation, combined with stress adaptation mechanisms involving unfolded protein response (UPR), and DNA repair Hallmark gene sets. Based on CRISPR data, we propose 3 therapeutic strategies: (1) targeting MYC to reduce its transcriptional activity, (2) targeting proteins from UPR, (3) targeting DNA-repair. We also propose corresponding candidate target/drug pairs to allow experimental validation of these strategies. ConclusionsProliferation in low MTUS1 TNBC is driven by MYC and stress-adaptation mechanisms. By linking this tumour profile to CRISPR-derived dependency signals, our analysis prioritises experimentally testable target-pathway hypotheses centred on MYC, UPR/proteostasis, and DNA-repair or checkpoint control. Although the proposed therapeutic strategies and candidate targets remain to be experimentally tested, the latter finding is consistent with published work showing that ATIP3-deficient TNBC cell line models are sensitive to inhibition of the WEE1 PKMYT1 G2/M checkpoint kinases.

BackgroundBreast cancer exhibits extensive molecular heterogeneity across intrinsic subtypes, yet convergent metabolic reprogramming may represent an obligate feature of tumour initiation. We hypothesised that suppression of nuclear-encoded mitochondrial fatty acid oxidation (FAO) constitutes such a convergence point, defining a shared metabolic phenotype independent of subtype. MethodsRNA-seq data from 1,106 primary breast tumours and 113 normal-adjacent tissues (TCGA-BRCA) were intersected with 1,079 nuclear-encoded mitochondrial genes from MitoCarta 3.0. Differential expression was assessed using Welch t-test with Benjamini-Hochberg correction at all tumour stages, at Stage I specifically, and stratified across PAM50 subtypes. A 55-gene core FAO signature was derived by three-way intersection. Ten candidate genes were selected by pre-specified objective scoring, locked before any clinical testing. Gene set enrichment analysis (GSEA) was performed using MitoCarta 3.0 pathway annotations. Diagnostic performance, clinical associations, survival, and mutation independence were characterised. External validation used two independent GEO cohorts (GSE42568, n = 121; GSE109169, n = 50); prognostic validation used METABRIC (Molecular Taxonomy of Breast Cancer International Consortium; n = 1,980). DESeq2 was applied as methodological cross-validation. ResultsAmong 126 differentially expressed mitochondrial genes, fatty acid oxidation was the most significantly depleted pathway (normalised enrichment score -2.130; false discovery rate 0.001). The 55-gene core signature replicated in both external cohorts with 100% directional concordance (hypergeometric p < 10-{superscript 1}). All 10 candidate genes discriminated tumour from normal tissue (area under the curve 0.915-0.979) and demonstrated broad clinical associations. The composite FAO suppression score predicted overall survival in METABRIC (log-rank p = 7.82 x 10-) and MAOA achieved independent prognostic significance in multivariable Cox regression (hazard ratio 0.890; adjusted p = 0.009). DESeq2 cross-validation confirmed Spearman {rho} = 0.980 concordance. ConclusionsNuclear-encoded FAO suppression is a robust, pan-subtype feature of breast cancer detectable at Stage I and validated across independent platforms and cohorts. These 10 candidate genes constitute a consistent initiation-phase mitochondrial signature, implicating FAO suppression as a potential convergence point in breast cancer oncogenesis and motivating targeted functional investigation.

BackgroundThe ketogenic diet is being explored as an adjuvant intervention in breast cancer because it lowers circulating glucose and elevates ketone bodies such as {beta}-hydroxybutyrate (BHB), but how individual ER+ breast cancer subtypes adapt to these conditions remains poorly characterized. We examined metabolic responses to BHB supplementation under glucose restriction in two ER+ breast cancer cell lines, asking whether metabolic adaptation patterns differ between models. MethodsMCF-7 and T47D cells were cultured under high glucose, glucose-restricted (5% of standard), or glucose-restricted with 10 mM BHB conditions and profiled by comprehensive two-dimensional gas chromatography-mass spectrometry (GCxGC-MS). Pairwise Welchs t-tests with Benjamini-Hochberg false discovery rate (FDR) correction were applied to identify treatment-responsive metabolites. Targeted assays quantified intracellular glycine, SHMT1 protein, and total branched-chain amino acid (BCAA) concentrations across a BHB dose range (2.5-15 mM). Patient tumor transcriptomic data from TCGA (n=1,084) and paired tumor-normal samples from GSE58135 (n=20) were analyzed for genes involved in one-carbon, ketone body, and BCAA metabolism. ResultsMCF-7 and T47D cells exhibited markedly divergent metabolic responses to BHB. In MCF-7 cells, BHB supplementation produced a broad pattern-level metabolic shift: 75% of detected metabolites trended upward when BHB was added to glucose-restricted cultures (C vs. B comparison), with 1,4-butanediol reaching nominal significance (FC=2.35, p=0.016) and a 4.1-fold trend increase in lactic acid (p=0.11), although no individual metabolite survived FDR correction. T47D cells showed essentially no metabolic response to BHB at the global level. Targeted assays detected an elevation in glycine at 5 mM BHB in both cell lines that did not follow a monotonic dose response and was not accompanied by changes in SHMT1 protein expression. Total BCAA levels were elevated by BHB in T47D cells but remained unchanged in MCF-7 cells. In paired patient samples, OXCT1 (log2FC = -1.41), SHMT1 (log2FC = -1.31), and ACAT1 (log2FC = -1.07) were significantly downregulated in ER+ tumors relative to matched normal tissue (adjusted p < 0.001 for all three). ConclusionsER+ breast cancer cell lines show heterogeneous metabolic responses to BHB supplementation under glucose restriction. The broad pattern of metabolite elevation in MCF-7 but not T47D cells suggests that capacity to utilize ketone bodies as metabolic substrate varies between ER+ models. The downregulation of OXCT1, ACAT1, and SHMT1 in ER+ tumors compared to normal tissue identifies these enzymes as candidate biomarkers that may help stratify which patients are likely to benefit from ketogenic interventions. Findings related to individual metabolites should be regarded as exploratory and require validation in larger, adequately powered cohorts.