Multiomics and single-cell sequencings reveal the specific biological characteristics of low Ki-67 triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC) displays high heterogeneity. The majority of TNBC cases are characterized by high Ki-67 expression. TNBC with low Ki-67 expression accounts for only a small fraction of cases and has been relatively less studied. Methods: This study analyzed a large single-center multiomics TNBC data set, combined with a single-cell data set. The clinical, genomic, and metabolic characteristics of patients with low Ki-67 TNBC were analyzed. Results: The clinical and pathological characteristics were analyzed in 2217 TNBC patients. Low Ki-67 TNBC was associated with a higher patient age at diagnosis, a lower proportion of invasive ductal carcinoma, increased alterations in the PI3K-AKT-mTOR pathway, upregulated lipid metabolism pathways, and enhanced infiltration of M2 macrophages. High Ki-67 TNBC exhibited a higher prevalence of TP53 gene mutations, elevated nucleotide metabolism, and increased infiltration of M1 macrophages. Conclusions: We identified specific genomic and metabolic characteristics unique to low Ki-67 TNBC, which have implications for the development of precision therapies and patient stratification strategies.

Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era.

As one of the most common tumors in women, the pathogenesis and tumor heterogeneity of breast cancer have long been the focal point of research, with the emergence of tumor metastasis and drug resistance posing persistent clinical challenges. The emergence of single-cell sequencing (SCS) technology has introduced novel approaches for gaining comprehensive insights into the biological behavior of malignant tumors. SCS is a high-throughput technology that has rapidly developed in the past decade, providing high-throughput molecular insights at the individual cell level. Furthermore, the advent of multitemporal point sampling and spatial omics also greatly enhances our understanding of cellular dynamics at both temporal and spatial levels. The paper provides a comprehensive overview of the historical development of SCS, and highlights the most recent advancements in utilizing SCS and spatial omics for breast cancer research. The findings from these studies will serve as valuable references for future advancements in basic research, clinical diagnosis, and treatment of breast cancer.

Radiomics in breast cancer: Current advances and future directions.

Breast cancer is a common disease that causes great health concerns to women worldwide. During the diagnosis and treatment of breast cancer, medical imaging plays an essential role, but its interpretation relies on radiologists or clinical doctors. Radiomics can extract high-throughput quantitative imaging features from images of various modalities via traditional machine learning or deep learning methods following a series of standard processes. Hopefully, radiomic models may aid various processes in clinical practice. In this review, we summarize the current utilization of radiomics for predicting clinicopathological indices and clinical outcomes. We also focus on radio-multi-omics studies that bridge the gap between phenotypic and microscopic scale information. Acknowledging the deficiencies that currently hinder the clinical adoption of radiomic models, we discuss the underlying causes of this situation and propose future directions for advancing radiomics in breast cancer research.

Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-biological connection.

Radiomics offers a noninvasive avenue for predicting clinicopathological factors. However, thorough investigations into a robust breast cancer outcome-predicting model and its biological significance remain limited. This study develops a robust radiomic model for prognosis prediction, and further excavates its biological foundation and transferring prediction performance. We retrospectively collected preoperative dynamic contrast-enhanced MRI data from three distinct breast cancer patient cohorts. In FUSCC cohort (n = 466), Lasso was used to select features correlated with patient prognosis and multivariate Cox regression was utilized to integrate these features and build the radiomic risk model, while multiomic analysis was conducted to investigate the model's biological implications. DUKE cohort (n = 619) and I-SPY1 cohort (n = 128) were used to test the performance of the radiomic signature in outcome prediction. A thirteen-feature radiomic signature was identified in the FUSCC cohort training set and validated in the FUSCC cohort testing set, DUKE cohort and I-SPY1 cohort for predicting relapse-free survival (RFS) and overall survival (OS) (RFS: p = 0.013, p = 0.024 and p = 0.035; OS: p = 0.036, p = 0.005 and p = 0.027 in the three cohorts). Multiomic analysis uncovered metabolic dysregulation underlying the radiomic signature (ATP metabolic process: NES = 1.84, p-adjust = 0.02; cholesterol biosynthesis: NES = 1.79, p-adjust = 0.01). Regarding the therapeutic implications, the radiomic signature exhibited value when combining clinical factors for predicting the pathological complete response to neoadjuvant chemotherapy (DUKE cohort, AUC = 0.72; I-SPY1 cohort, AUC = 0.73). In conclusion, our study identified a breast cancer outcome-predicting radiomic signature in a multicenter radio-multiomic study, along with its correlations with multiomic features in prognostic risk assessment, laying the groundwork for future prospective clinical trials in personalized risk stratification and precision therapy.

Molecular Characterization and Classification of HER2-Positive Breast Cancer Inform Tailored Therapeutic Strategies.

HER2-positive breast cancer is an aggressive subtype that accounts for 15-20% of all breast cancers. Recent studies have suggested that HER2-positive breast cancer is a group of heterogeneous diseases with different sensitivities to standard treatment regimens. Revealing the molecular heterogeneity of HER2-positive breast cancer could potentially enable more precise treatment strategies. Here, we performed multiomics profiling on a HER2-positive breast cancer cohort and identified four transcriptome-based subtypes. The classical HER2 (HER2-CLA) subtype comprised 28.3% of the samples and displayed high ERBB2 activation and significant benefit from anti-HER2 therapy. The immunomodulatory (HER2-IM) subtype (20%) featured an immune-activated microenvironment, potentially suitable for de-escalated treatment and immunotherapy. The luminal-like (HER2-LUM) subtype (30.6%) possessed similar molecular features of hormone receptor-positive HER2-negative breast cancer, suggesting endocrine therapy and CDK4/6 inhibitors as a potential therapeutic strategy. Lastly, the basal/mesenchymal-like (HER2-BM) subtype (21.1%), had a poor response to current anti-HER2 dual-targeted therapies and could potentially benefit from tyrosine kinase inhibitors. The molecular characteristics and clinical features of the subtypes were further explored across multiple cohorts, and the feasibility of the proposed treatment strategies was validated in patient-derived organoid and patient-derived tumor fragment models. This study elucidates the molecular heterogeneity of HER2-positive breast cancer and paves the way for a more tailored treatment.

Neoadjuvant anthracycline followed by toripalimab combined with nab-paclitaxel in patients with early triple-negative breast cancer (NeoTENNIS): a single-arm, phase II study.

Background: Toripalimab, a novel PD-1 antibody, is approved for treatment of multiple solid tumors; however, its neoadjuvant use with chemotherapy for triple-negative breast cancer (TNBC) remains unevaluated. Additionally, induction chemotherapy followed by de-escalation of neoadjuvant immunotherapy remains underexplored. Therefore, we conducted a phase II trial investigating a novel neoadjuvant chemoimmunotherapy regimen including de-escalation of immunotherapy for early-stage TNBC. Methods: Chemotherapy and anti-PD-1 therapy were sequentially administered in a neoadjuvant setting to female patients with histologically confirmed stage II-III TNBC between June 9, 2020, and March 24, 2022. Patients received neoadjuvant therapy with four cycles of epirubicin-cyclophosphamide every 2 weeks, followed by toripalimab (240 mg) every 3 weeks plus nab-paclitaxel weekly for 12 weeks. The primary endpoint was total pathological complete response (tpCR; ypT0/is ypN0). Key secondary endpoints included breast pCR (bpCR; ypT0/is), event-free survival and biomarker analysis. Safety was also assessed. This study was registered with ClinicalTrials.gov (NCT04418154). Findings: Among 70 enrolled patients (median age, 51 years; 62.9% stage III), 66 completed treatment without progression and subsequently underwent surgery. The percentages of patients with a tpCR and bpCR were 39 of 70 (55.7%, 95% confidence interval [CI]: 43.3-67.6) and 41 of 70 (58.6%, 95% CI 46.2-70.2), respectively. Sixteen (22.9%) patients experienced grade ≥3 adverse events (AEs), frequently neutropenia (12, 17.1%) and leukopenia (11, 15.7%). The most common immune-related AE was hypothyroidism (5, 7.1%, all grade 1-2). Interpretation: Including 12 weeks of toripalimab in neoadjuvant chemotherapy conferred encouraging activity and manageable toxicity in patients with early TNBC, and this regimen warrants further investigation. Funding: National Natural Science Foundation of China, Junshi Biosciences, and Jiangsu Hengrui Pharmaceuticals.

SOSTDC1 Nuclear Translocation Facilitates BTIC Maintenance and CHD1-Mediated HR Repair to Promote Tumor Progression and Olaparib Resistance in TNBC.

Breast tumor-initiating cells (BTICs) of triple-negative breast cancer (TNBC) tissues actively repair DNA and are resistant to treatments including chemotherapy, radiotherapy, and targeted therapy. Herein, it is found that a previously reported secreted protein, sclerostin domain containing 1 (SOSTDC1), is abundantly expressed in BTICs of TNBC cells and positively correlated with a poor patient prognosis. SOSTDC1 knockdown impairs homologous recombination (HR) repair, BTIC maintenance, and sensitized bulk cells and BTICs to Olaparib. Mechanistically, following Olaparib treatment, SOSTDC1 translocates to the nucleus in an importin-α dependent manner. Nuclear SOSTDC1 interacts with the N-terminus of the nucleoprotein, chromatin helicase DNA-binding factor (CHD1), to promote HR repair and BTIC maintenance. Furthermore, nuclear SOSTDC1 bound to ß-transducin repeat-containing protein (ß-TrCP) binding motifs of CHD1 is found, thereby blocking the ß-TrCP-CHD1 interaction and inhibiting ß-TrCP-mediated CHD1 ubiquitination and degradation. Collectively, these findings identify a novel nuclear SOSTDC1 pathway in regulating HR repair and BTIC maintenance, providing insight into the TNBC therapeutic strategies.

DUSP4 enhances therapeutic sensitivity in HER2-positive breast cancer by inhibiting the G6PD pathway and ROS metabolism by interacting with ALDOB.

BACKGROUND: Breast cancer (BC) poses a global threat, with HER2-positive BC being a particularly hazardous subtype. Despite the promise shown by neoadjuvant therapy (NAT) in improving prognosis, resistance in HER2-positive BC persists despite emerging targeted therapies. The objective of this study is to identify markers that promote therapeutic sensitivity and unravel the underlying mechanisms. METHODS: We conducted an analysis of 86 HER2-positive BC biopsy samples pre-NAT using RNA-seq. Validation was carried out using TCGA, Kaplan‒Meier Plotter, and Oncomine databases. Phenotype verification utilized IC50 assays, and prognostic validation involved IHC on tissue microarrays. RNA-seq was performed on wild-type/DUSP4-KO cells, while RT‒qPCR assessed ROS pathway regulation. Mechanistic insights were obtained through IP and MS assays. RESULTS: Our findings reveal that DUSP4 enhances therapeutic efficacy in HER2-positive BC by inhibiting the ROS pathway. Elevated DUSP4 levels correlate with increased sensitivity to HER2-targeted therapies and improved clinical outcomes. DUSP4 independently predicts disease-free survival (DFS) and overall survival (OS) in HER2-positive BC. Moreover, DUSP4 hinders G6PD activity via ALDOB dephosphorylation, with a noteworthy association with heightened ROS levels. CONCLUSIONS: In summary, our study unveils a metabolic reprogramming paradigm in BC, highlighting DUSP4's role in enhancing therapeutic sensitivity in HER2-positive BC cells. DUSP4 interacts with ALDOB, inhibiting G6PD activity and the ROS pathway, establishing it as an independent prognostic predictor for HER2-positive BC patients.

BOLERO-5: a phase II study of everolimus and exemestane combination in Chinese post-menopausal women with ER + /HER2- advanced breast cancer.

BACKGROUND: The global BOLERO-2 trial established the efficacy and safety of combination everolimus (EVE) and exemestane (EXE) in the treatment of estrogen receptor positive (ER +), HER2-, advanced breast cancer (ABC). BOLERO-5 investigated this combination in a Chinese population (NCT03312738). METHODS: BOLERO-5 is a randomized, double-blind, multicenter, placebo controlled, phase II trial comparing EVE (10 mg/day) or placebo (PBO) in combination with EXE (25 mg/day). The primary endpoint was progression-free survival (PFS) per investigator assessment. Secondary endpoints included PFS per blinded independent review committee (BIRC), overall survival (OS), overall response rate (ORR), clinical benefit rate (CBR), pharmacokinetics, and safety. RESULTS: A total of 159 patients were randomized to EVE + EXE (n = 80) or PBO + EXE (n = 79). By investigator assessment, treatment with EVE + EXE prolonged median PFS by 5.4 months (HR 0.52; 90% CI 0.38, 0.71), from 2.0 months (PBO + EXE; 90% CI 1.9, 3.6) to 7.4 months (EVE + EXE; 90% CI 5.5, 9.0). Similar results were observed following assessment by BIRC, with median PFS prolonged by 4.3 months. Treatment with EVE + EXE was also associated with improvements in ORR and CBR. No new safety signals were identified in BOLERO-5, with the incidence of adverse events in Chinese patients consistent with the safety profile of both drugs. CONCLUSION: The efficacy and safety results of BOLERO-5 validate the findings from BOLERO-2, and further support the use of EVE + EXE in Chinese post-menopausal women with ER + , HER2- ABC. NCT03312738, registered 18 October 2017.

Sideroflexin-1 promotes progression and sensitivity to lapatinib in triple-negative breast cancer by inhibiting TOLLIP-mediated autophagic degradation of CIP2A.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and it lacks specific therapeutic targets and effective treatment protocols. By analyzing a proteomic TNBC dataset, we found significant upregulation of sideroflexin 1 (SFXN1) in tumor tissues. However, the precise function of SFXN1 in TNBC remains unclear. Immunoblotting was performed to determine SFXN1 expression levels. Label-free quantitative proteomics and liquid chromatography-tandem mass spectrometry were used to identify the downstream targets of SFXN1. Mechanistic studies of SFXN1 and cellular inhibitor of PP2A (CIP2A) were performed using immunoblotting, immunofluorescence staining, and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Functional experiments were used to investigate the role of SFXN1 in TNBC cells. SFXN1 was significantly overexpressed in TNBC tumor tissues and was associated with unfavorable outcomes in patients with TNBC. Functional experiments demonstrated that SFXN1 promoted TNBC growth and metastasis in vitro and in vivo. Mechanistic studies revealed that SFXN1 promoted TNBC progression by inhibiting the autophagy receptor TOLLIP (toll interacting protein)-mediated autophagic degradation of CIP2A. The pro-tumorigenic effect of SFXN1 overexpression was partially prevented by lapatinib-mediated inhibition of the CIP2A/PP2A/p-AKT pathway. These findings may provide a new targeted therapy for patients with TNBC.

Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (N = 425), a deep learning-based framework was devised and validated for comprehensive predictions of molecular features, subtypes and prognosis from pathological whole slide images. The framework first incorporated a neural network to decompose the tissue on WSIs, followed by a second one which was trained based on certain tissue types for predicting different targets. Multi-omics molecular features were analyzed including somatic mutations, copy number alterations, germline mutations, biological pathway activities, metabolomics features and immunotherapy biomarkers. It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation, germline BRCA2 mutation and PD-L1 protein expression (area under the curve [AUC]: 0.78, 0.79 and 0.74 respectively). The molecular subtypes of TNBC can be identified (AUC: 0.84, 0.85, 0.93 and 0.73 for the basal-like immune-suppressed, immunomodulatory, luminal androgen receptor, and mesenchymal-like subtypes respectively) and their distinctive morphological patterns were revealed, which provided novel insights into the heterogeneity of TNBC. A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes (log-rank P < 0.001). Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA (N = 143) and appeared robust to the changes in patient population. For potential clinical translation, we built a novel online platform, where we modularized and deployed our framework along with the validated models. It can realize real-time one-stop prediction for new cases. In summary, using only pathological WSIs, our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making. It had the potential to be clinically implemented and promote the personalized management of TNBC.

Stability and variability of molecular subtypes: comparative analysis of primary and metastatic triple-negative breast cancer.

OBJECTIVE: Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive cancer. Although our previous study classified primary TNBC into four subtypes, comprehensive longitudinal investigations are lacking. METHODS: We assembled a large-scale, real-world cohort comprised of 880 TNBC patients [465 early-stage TNBC (eTNBC) and 415 metastatic TNBC (mTNBC) patients] who were treated at Fudan University Shanghai Cancer Center. The longitudinal dynamics of TNBC subtypes during disease progression were elucidated in this patient cohort. Comprehensive analysis was performed to compare primary and metastatic lesions within specific TNBC subtypes. RESULTS: The recurrence and metastasis rates within 3 years after initial diagnosis in the eTNBC cohort were 10.1% (47/465). The median overall survival (OS) in the mTNBC cohort was 27.2 months [95% confidence interval (CI), 24.4-30.2 months], which indicated a poor prognosis. The prognostic significance of the original molecular subtypes in both eTNBC and mTNBC patients was confirmed. Consistent molecular subtypes were maintained in 77.5% of the patients throughout disease progression with the mesenchymal-like (MES) subtype demonstrating a tendency for subtype transition and brain metastasis. Additionally, a precision treatment strategy based on the metastatic MES subtype of target lesions resulted in improved progression-free survival in the FUTURE trial. CONCLUSIONS: Our longitudinal study comprehensively revealed the clinical characteristics and survival of patients with the original TNBC subtypes and validated the consistency of most molecular subtypes throughout disease progression. However, we emphasize the major importance of repeat pathologic confirmation of the MES subtype.

The DRAP1/DR1 Repressor Complex Increases mTOR Activity to Promote Progression and Confer Everolimus Sensitivity in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Transcriptional dysregulation is a hallmark of cancer, and several transcriptional regulators have been demonstrated to contribute to cancer progression. In this study, we identified an upregulation of the transcriptional corepressor downregulator of transcription 1-associated protein 1 (DRAP1) in TNBC, which was closely associated with poor recurrence-free survival in patients with TNBC. DRAP1 promoted TNBC proliferation, migration, and invasion in vitro and tumor growth and metastasis in vivo. Mechanistically, the downregulator of transcription 1 (DR1)/DRAP1 heterodimer complex inhibited expression of the cytosolic arginine sensor for mTORC1 subunit 1 (CASTOR1) and thereby increased activation of mTOR, which sensitized TNBC to treatment with the mTOR inhibitor everolimus. DRAP1 and DR1 also formed a positive feedback loop. DRAP1 enhanced the stability of DR1 by recruiting the deubiquitinase USP7 to inhibit its proteasomal degradation; in turn, DR1 directly promoted DRAP1 transcription. Collectively, this study uncovered a DRAP1-DR1 bidirectional regulatory pathway that promotes TNBC progression, suggesting that targeting the DRAP1/DR1 complex might be a potential therapeutic strategy to treat TNBC. Significance: DR1 and DRAP1 form a positive feedback loop and a repressor complex to cooperatively inhibit cytosolic arginine sensor for mTORC1 subunit 1 transcription and stimulate mTOR signaling, leading to progression and increased everolimus sensitivity in triple-negative breast cancer.

Identification of immune-related prognostic biomarkers in triple-negative breast cancer.

Background: Triple-negative breast cancer (TNBC), a type of breast cancer, lacks immune-related markers that can be used for prognosis or prediction. Therefore, we created a predictive framework for TNBC using a risk assessment. Methods: Our previous study group consisted of 360 individuals who were diagnosed with TNBC through pathology using RNA sequencing and had clinical data from Fudan University Shanghai Cancer Center (FUSCC). A risk scoring model was constructed using the Cox regression method with the least absolute shrinkage and selection operator (LASSO). A multivariate Cox regression analysis was utilized to develop the prediction model, which was then assessed using the consistency index and calibration plots. The validation cohort of The Cancer Genome Atlas (TCGA) TNBC confirmed the strength of the signatures' predictive value. Results: The prognostic risk score model included 12 genes: TDO2, CHIT1, CARML2, HLA-C, ADIRF, C19orf33, CA8, AHNAK2, RHOV, OPLAH, THEM6, and NEBL. The receiver operator characteristic (ROC) curves for survivability values at 1, 3, and 5 years in the FUSCC TNBC cohort demonstrated area under the curve (AUC) values of 0.78, 0.83, and 0.75, respectively. These results indicated a high level of accuracy in predicting outcomes, which was further confirmed through validation using TCGA database. The patients in the high-risk group showed worse prognoses and lower levels of immune cell infiltration, specifically CD8+ T cells, than those in the low-risk group. Furthermore, the low-risk group exhibited a significant upregulation of genes that encode immune checkpoints, including CD274 and CTLA4, suggesting that immunotherapy may yield enhanced efficacy within this particular group. Conclusions: In conclusion, the prognostic signature consisting of 12 genes can assist in the choice of immunotherapy for TNBC.

Genetic interactions reveal distinct biological and therapeutic implications in breast cancer.

Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.

SF3A2 promotes progression and cisplatin resistance in triple-negative breast cancer via alternative splicing of MKRN1.

Triple-negative breast cancer (TNBC) is the deadliest subtype of breast cancer owing to the lack of effective therapeutic targets. Splicing factor 3a subunit 2 (SF3A2), a poorly defined splicing factor, was notably elevated in TNBC tissues and promoted TNBC progression, as confirmed by cell proliferation, colony formation, transwell migration, and invasion assays. Mechanistic investigations revealed that E3 ubiquitin-protein ligase UBR5 promoted the ubiquitination-dependent degradation of SF3A2, which in turn regulated UBR5, thus forming a feedback loop to balance these two oncoproteins. Moreover, SF3A2 accelerated TNBC progression by, at least in part, specifically regulating the alternative splicing of makorin ring finger protein 1 (MKRN1) and promoting the expression of the dominant and oncogenic isoform, MKRN1-T1. Furthermore, SF3A2 participated in the regulation of both extrinsic and intrinsic apoptosis, leading to cisplatin resistance in TNBC cells. Collectively, these findings reveal a previously unknown role of SF3A2 in TNBC progression and cisplatin resistance, highlighting SF3A2 as a potential therapeutic target for patients with TNBC.

Enhancing therapeutic efficacy in luminal androgen receptor triple-negative breast cancer: exploring chidamide and enzalutamide as a promising combination strategy.

Extensive exploration of the molecular subtypes of triple-negative breast cancer (TNBC) is critical for advancing precision medicine. Notably, the luminal androgen receptor (LAR) subtype has attracted attention for targeted treatment combining androgen receptor antagonists and CDK4/6 inhibitors. Unfortunately, this strategy has proven to be of limited efficacy, highlighting the need for further optimization. Using our center's comprehensive multiomics dataset (n = 465), we identified novel therapeutic targets and evaluated their efficacy through multiple models, including in vitro LAR cell lines, in vivo cell-derived allograft models and ex vivo patient-derived organoids. Moreover, we conducted flow cytometry and RNA-seq analysis to unveil potential mechanisms underlying the regulation of tumor progression by these therapeutic strategies. LAR breast cancer cells exhibited sensitivity to chidamide and enzalutamide individually, with a drug combination assay revealing their synergistic effect. Crucially, this synergistic effect was verified through in vivo allograft models and patient-derived organoids. Furthermore, transcriptomic analysis demonstrated that the combination therapeutic strategy could inhibit tumor progression by regulating metabolism and autophagy. This study confirmed that the combination of histone deacetylase (HDAC) inhibitors and androgen receptor (AR) antagonists possessed greater therapeutic efficacy than monotherapy in LAR TNBC. This finding significantly bolsters the theoretical basis for the clinical translation of this combination therapy and provides an innovative strategy for the targeted treatment of LAR TNBC.

IL1R2 Blockade Alleviates Immunosuppression and Potentiates Anti-PD-1 Efficacy in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with limited therapeutic options. IL1 receptor type 2 (IL1R2) promotes breast tumor-initiating cell (BTIC) self-renewal and tumor growth in TNBC, indicating that targeting it could improve patient treatment. In this study, we observed that IL1R2 blockade strongly attenuated macrophage recruitment and the polarization of tumor-associated macrophages (TAM) to inhibit BTIC self-renewal and CD8+ T-cell exhaustion, which resulted in reduced tumor burden and prolonged survival in TNBC mouse models. IL1R2 activation by TAM-derived IL1ß increased PD-L1 expression by interacting with the transcription factor Yin Yang 1 (YY1) and inducing YY1 ubiquitination and proteasomal degradation in both TAMs and TNBC cells. Loss of YY1 alleviated the transcriptional repression of c-Fos, which is a transcriptional activator of PDL-1. Combined treatment with an IL1R2-neutralizing antibodies and anti-PD-1 led to enhanced antitumor efficacy and reduced TAMs, BTICs, and exhausted CD8+ T cells. These results suggest that IL1R2 blockade might be a strategy to potentiate immune checkpoint blockade efficacy in TNBC to improve patient outcomes. Significance: IL1R2 in both macrophages and breast cancer cells orchestrates an immunosuppressive tumor microenvironment by upregulating PD-L1 expression and can be targeted to enhance the efficacy of anti-PD-1 in triple-negative breast cancer.