Clinical breast cancer最新文献

{"title":"Trends in Surgical Axillary Staging and Clinical Outcomes Among Breast Cancer Patients With Neoadjuvant Therapy: A Population-Based Cohort Study.","authors":"Xihan Xiang, Xunxi Lu, Mengting He, Zongchao Gou","doi":"10.1016/j.clbc.2025.02.001","DOIUrl":"https://doi.org/10.1016/j.clbc.2025.02.001","url":null,"abstract":"<p><strong>Objectives: </strong>Surgical management of the axilla with neoadjuvant treatment has been a significant research focus over the past decade, resulting in numerous publications. The trends in surgical choices based on lymph node status and survival outcomes in large populations were previously unclear.</p><p><strong>Methods: </strong>Breast cancer patients who underwent neoadjuvant therapy were identified from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2021 and categorized into 2 cohorts: LN- (no lymph node metastasis) and LNm (1-2 sentinel node metastases). We analyzed the trends in surgical axillary staging and compared the 10-year overall survival between sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND).</p><p><strong>Results: </strong>Among 26,320 patients, 18,548 were in the LN- cohort (16,607 with SLNB and 1,941 with ALND) and 7,772 were in the LNm cohort (3,601 with SLNB and 4,171 with ALND). The proportion of patients undergoing SLNB increased from 76.4% in 2010 to 93.8% in 2021 in the LN- cohort and doubled from 25.2% in 2010 to 55.0% in 2021 in the LNm cohort. ALND was identified as a favorable factor over SLNB in the LNm cohort (hazard ratio [HR] 0.84; 95% CI, 0.73-0.96; P = .014).</p><p><strong>Conclusion: </strong>Omission of ALND for patients with 1 to 2 node metastases after neoadjuvant therapy has doubled since 2010. SLNB is an efficient and safe approach of surgical axillary staging for the LN- cohort but not for patients with residual axillary cancer, even with low-volume disease.</p>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143531358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Habitat-Based Radiomics for Revealing Tumor Heterogeneity and Predicting Residual Cancer Burden Classification in Breast Cancer.","authors":"Zhi-Yong Li, Sheng-Nan Wu, Peng Lin, Mei-Chen Jiang, Cong Chen, Wen-Jin Lin, En-Sheng Xue, Rong-Xi Liang, Zhen-Hu Lin","doi":"10.1016/j.clbc.2025.01.014","DOIUrl":"https://doi.org/10.1016/j.clbc.2025.01.014","url":null,"abstract":"<p><strong>Purpose: </strong>To investigate the feasibility of characterizing tumor heterogeneity in breast cancer ultrasound images using habitat analysis technology and establish a radiomics machine learning model for predicting response to neoadjuvant chemotherapy (NAC).</p><p><strong>Methods: </strong>Ultrasound images from patients with pathologically confirmed breast cancer who underwent neoadjuvant therapy at our institution between July 2021 and December 2023 were retrospectively reviewed. Initially, the region of interest was delineated and segmented into multiple habitat areas using local feature delineation and cluster analysis techniques. Subsequently, radiomics features were extracted from each habitat area to construct 3 machine learning models. Finally, the model's efficacy was assessed through operating characteristic (ROC) curve analysis, decision curve analysis (DCA), and calibration curve evaluation.</p><p><strong>Results: </strong>A total of 945 patients were enrolled, with 333 demonstrating a favorable response to NAC and 612 exhibiting an unfavorable response to NAC. Through the application of habitat analysis techniques, 3 distinct habitat regions within the tumor were identified. Subsequently, a predictive model was developed by incorporating 19 radiomics features, and all 3 machine learning models demonstrated excellent performance in predicting treatment outcomes. Notably, extreme gradient boosting (XGBoost) exhibited superior performance with an area under the curve (AUC) of 0.872 in the training cohort and 0.740 in the testing cohort. Additionally, DCA and calibration curves were employed for further evaluation.</p><p><strong>Conclusions: </strong>The habitat analysis technique effectively distinguishes distinct biological subregions of breast cancer, while the established radiomics machine learning model predicts NAC response by forecasting residual cancer burden (RCB) classification.</p>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143499661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Systemic Immune-Inflammation Index is a Predictor of Chemotherapy Sensitivity and Disease-Free Survival in Patients With Hormone Receptor-Positive Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer","authors":"Xuan Liu ,&nbsp;Guoqing Yan ,&nbsp;Jian Pang ,&nbsp;Zhi Xiao ,&nbsp;Haiqing Xie","doi":"10.1016/j.clbc.2024.09.016","DOIUrl":"10.1016/j.clbc.2024.09.016","url":null,"abstract":"<div><h3>Background</h3><div>The relationship between the systemic immune-inflammation index (SII), chemotherapy sensitivity, and prognosis in HR+HER2– breast cancer (BC) has not been extensively studied.</div></div><div><h3>Patients and methods</h3><div>Clinical data from 980 patients diagnosed with HR+HER2– BC between June 2012 and June 2016 were collected. Patients were divided into low- and high-SII groups according to median SII value. Differences among variables were assessed using the chi-squared test. The inverse probability of treatment weighting (IPTW) method was used to control bias. The associations between clinicopathological factors, baseline SII, and disease-free survival (DFS) were analyzed using Kaplan–Meier curves and Cox analyses.</div></div><div><h3>Results</h3><div>The median follow-up period was 37 months (5-77). 480 patients underwent neoadjuvant chemotherapy, and low baseline SII values were associated with higher pathological complete response (pCR) rates than those in the high SII group (16.4% vs. 9.2%; <em>P</em> = .019). Multivariate analyses revealed that larger tumor size, more lymph node involvement, high Ki-67 score, and high baseline SII were independent prognostic factors for worse outcomes in patients with HR+HER2– BC. The risk for metastasis/recurrence was higher in the high SII group compared with that in the low SII group (hazard ratio 2.07 [95% CI, 1.35-3.19]; <em>P</em> = .001). After IPTW, a similar result was obtained, in that a high SII value was significantly associated with worse DFS among patients with HR+HER2– BC.</div></div><div><h3>Conclusion</h3><div>A low baseline SII was associated with higher pCR rates after neoadjuvant chemotherapy and was an independent prognostic factor for better DFS outcomes in patients with HR+HER2– BC.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Pages e190-e195"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142496156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metronomic Chemotherapy in Breast Cancer as a Strategy to Deliver More Sustainable and Less Toxic Treatments: Time to Debunk the Myth?","authors":"Elena Battaiotto ,&nbsp;Simeone d'Ambrosio ,&nbsp;Dario Trapani ,&nbsp;Giuseppe Curigliano","doi":"10.1016/j.clbc.2024.11.003","DOIUrl":"10.1016/j.clbc.2024.11.003","url":null,"abstract":"<div><div>Breast cancer is the most commonly diagnosed cancer in women, worldwide. With the increasing burden of breast cancer, the search for more tolerable and sustainable treatments is required, to result in broader access to cancer treatments. Metronomic chemotherapy defines the use of chemotherapy agents based on low-dose, continuous regimens, as opposed to traditional treatments administered for limited intervals, at higher dose. The use of metronomic chemotherapies has been envisioned often as a way to reduce toxicity while maintaining similar efficacy, and result in reduced health system resource utilization, while tailoring some special populations’ needs, such as the older adults with cancer. In our review, we provide a revision of the data available on the use of metronomic chemotherapy in breast cancer, as stratified per setting of use and subtypes of diseases. Clinical trials evaluating head-to-head metronomic and nonmetronomic schedules of chemotherapies broadly failed to meet their endpoints of noninferiority and/or superiority in term of safety, showing more often similar burden of adverse effect. Efficacy was also usually comparable. Data on financial implications appeared limited, and not conclusive of economic and health system benefits with the use of metronomic schedules. Our review of the evidence suggests that broad implementation of metronomic chemotherapy to enhance sustainability and safety may be not appropriate in all settings, as data for the optimized use are still warranted. The use of metronomic chemotherapy in breast cancer as a mean to improve tolerability, reduce treatment-related complications and associate costs and enhance sustainability of cancer treatments should not be pursued as an ultimate solution, in all settings of breast cancer treatment. Standard treatments having robustly proved to improve patient outcomes are to be prioritised for first, unless data suggest otherwise with these regimens.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Pages 85-95.e18"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142766747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing & Validating a Clinical Decision Support Tool for ER-Targeted PET Imaging With 16α-18F-Fluoro-17β-Fluoroestradiol","authors":"Nicholas DiGregorio ,&nbsp;Regina Munter-Young","doi":"10.1016/j.clbc.2024.10.013","DOIUrl":"10.1016/j.clbc.2024.10.013","url":null,"abstract":"<div><h3>Background</h3><div>Estrogen receptor (ER) status in breast cancer (BC) is routinely determined by immunohistochemistry (IHC); however, this technique is not without limitations, including false results. Imaging of FES-PET (fluoroestradiol F18) injection provides high diagnostic accuracy of ER expression, supplementing information from biopsy. A Clinical Decision Support (CDS) tool was developed to better assess its clinical usefulness in metastatic and recurrent breast cancer management. This study evaluated a conceptual tool that reflects clinical practice variables.</div></div><div><h3>Methods</h3><div>Individual patient characteristics - candidacy for therapeutic treatment and rate of recurrence - determined initial eligibility. The CDS tool uses rules (IF-THEN statements) to produce an output on the diagnostic accuracy of ER status based on tumor burden, anatomical location(s) of metastasis, heterogeneity, and confidence in sample collection &amp; pathology accuracy (CSC &amp; PA). An Excel-based probability decision tree calculates the accuracy of ER expression.</div></div><div><h3>Results</h3><div>360 oncologists in the United States participated in the survey study. 223 respondents identified as medical oncologists (62%), 77 as clinical oncologists (21%), and 60 as hematologic oncologists (17%). 93% of respondents found the CDS tool intuitive and easy to follow with medical and clinical oncologists favoring the tool more than hematologic oncologists. Individual CDS attributes - clinical criteria, diagnostic comparator, true positive and true negative, patient inclusion and exclusion, and clinical patient level inputs - were tested with overall positive feedback.</div></div><div><h3>Conclusions</h3><div>Based on respondent feedback, further development of CDS tools are warranted for potential use in patients’ diagnostic workup.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Pages 133-140.e1"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142754873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adjuvant Trastuzumab Plus Pertuzumab Versus Trastuzumab Alone in Patients Achieving Pathologic Complete Response After Chemotherapy With Trastuzumab and Pertuzumab: A Retrospective Cohort Study","authors":"Yoonwon Kook ,&nbsp;Jee Hung Kim ,&nbsp;Ji Soo Jang ,&nbsp;Soong June Bae ,&nbsp;Seung Ho Baek ,&nbsp;Joon Jeong ,&nbsp;Joon Young Choi ,&nbsp;Dong Seung Shin ,&nbsp;Jai Min Ryu ,&nbsp;Sung Gwe Ahn","doi":"10.1016/j.clbc.2024.11.006","DOIUrl":"10.1016/j.clbc.2024.11.006","url":null,"abstract":"<div><h3>Background</h3><div>For patients who achieve pathologic complete response (pCR) after neoadjuvant chemotherapy with trastuzumab (T) and pertuzumab (P), the benefit of adding P to T remains uncertain. We compared survival outcomes according to the type of adjuvant anti-HER2 therapy in patients with pCR after chemotherapy with TP.</div></div><div><h3>Method</h3><div>Patients who achieved pCR in both the breast and axilla after neoadjuvant chemotherapy with TP were included. Recurrence-free survival (RFS) and distant recurrence-free survival (DRFS) were evaluated. Univariate and multivariate Cox proportional hazards analyses were used to assess the impact of different adjuvant therapies on RFS and DRFS.</div></div><div><h3>Results</h3><div>In total, 386 patients were included, with 69 (17.9%) receiving adjuvant TP and 317 (82.1%) receiving adjuvant T alone. At a median follow-up of 49 months, the 3-year RFS rate was 96.1%. There was no significant difference in the 3-year RFS between groups (94.2% in TP and 95.6% in T), with an adjusted hazard ratio (HR) of 1.15 (95% CI, 0.37-3.55, <em>P</em> = .806). In the clinical node-positive group (<em>n</em> = 294), there was no difference in survival between groups (HR 1.64, 95% CI, 0.58-4.65, <em>P</em> = .35). The multivariate analysis showed no significant predictors of recurrence or distant recurrence, including clinical tumor size, nodal status, ER/PR/HER2 status, and adjuvant radiotherapy receipt. Among 11 patients with brain metastasis after pCR, there was no difference according to the type of adjuvant anti-HER2 therapy.</div></div><div><h3>Conclusions</h3><div>In patients with pCR who responded to chemotherapy and dual HER2 blockade (TP), the 3-year RFS and brain metastasis-free survival did not differ according to the type of adjuvant anti-HER2 therapy.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Pages 164-171"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142766638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deubiquitinase OTUD7B Regulates Cell Proliferation in Breast Cancer","authors":"Xiu Zhang ,&nbsp;Peng Zhang ,&nbsp;Xiang Chen ,&nbsp;Xianyi Liu ,&nbsp;Wenwen Liu ,&nbsp;Xi Hu ,&nbsp;Chengcheng Sun ,&nbsp;Xiaochun Wang ,&nbsp;Jianhong Shi","doi":"10.1016/j.clbc.2024.10.002","DOIUrl":"10.1016/j.clbc.2024.10.002","url":null,"abstract":"<div><h3>Purpose</h3><div>The deubiquitylase OTUD7B plays a facilitates role in lung tumorigenesis through VEGF protein, but its role in breast cancer remains unclear. In the present study, we proposed to explore the role of deubiquitylase OTUD7B in breast cancer.</div></div><div><h3>Methods</h3><div>The expression of OTUD7B in breast cancer and adjacent tissues was detected. The role of OTUD7B in cell proliferation and invasion of breast cancer cell lines such as MCF-7 and MDA-MB-453 was explored.</div></div><div><h3>Results</h3><div>OTUD7B is highly expressed in human breast cancer tissues and its higher expression correlates with better survival of patients. Further mechanistic studies reveal that OTUD7B associates with RASGRF1 and PLCE1 to disrupt RAS signaling pathway. Knockdown of OTUD7B results in decreasing levels of RASGRF1 protein, suppression cell growth and invasion in breast cancer. Collectively, our results reveal a previously unappreciated anti-oncogentic role OTUD7B involved in RAS signaling pathway in breast cancer and indicate that deubiquitylases could induce tumor-suppressing or tumor-promoting activities in a cell- and tissue-dependent context.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Pages 122-132.e2"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142709589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Madarosis Among Breast Cancer Survivors: Correspondence","authors":"Hinpetch Daungsupawong ,&nbsp;Viroj Wiwanitkit","doi":"10.1016/j.clbc.2024.11.004","DOIUrl":"10.1016/j.clbc.2024.11.004","url":null,"abstract":"","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Page e210"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142766717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Microinvasion in Breast Ductal Carcinoma in Situ Using Conventional Ultrasound Combined with Contrast-Enhanced Ultrasound Features: A Two-Center Study","authors":"Tingting Wu ,&nbsp;Jing Chen ,&nbsp;Sihui Shao ,&nbsp;Yu Du ,&nbsp;Fang Li ,&nbsp;Hui Liu ,&nbsp;Liping Sun ,&nbsp;Xuehong Diao ,&nbsp;Rong Wu","doi":"10.1016/j.clbc.2024.09.014","DOIUrl":"10.1016/j.clbc.2024.09.014","url":null,"abstract":"<div><h3>Background</h3><div>To develop and validate a model based on conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) features to preoperatively predict microinvasion in breast ductal carcinoma in situ (DCIS).</div></div><div><h3>Patients and Methods</h3><div>Data from 163 patients with DCIS who underwent CUS and CEUS from the internal hospital was retrospectively collected and randomly apportioned into training and internal validation sets in a ratio of 7:3. External validation set included 56 patients with DCIS from the external hospital. Univariate and multivariate logistic regression analysis were performed to determine the independent risk factors associated with microinvasion. These factors were used to develop predictive models. The performance was evaluated through calibration, discrimination, and clinical utility.</div></div><div><h3>Results</h3><div>Multivariate analysis indicated that centripetal enhancement direction (odds ratio [OR], 13.268; 95% confidence interval [CI], 3.687-47.746) and enhancement range enlarged on CEUS (OR, 4.876; 95% CI, 1.470-16.181), lesion size of ≥20 mm (OR, 3.265; 95% CI, 1.230-8.669) and calcification detected on CUS (OR, 5.174; 95% CI, 1.903-14.066) were independent risk factors associated with microinvasion. The nomogram incorporated the CUS and CEUS features achieved favorable discrimination (AUCs of 0.850, 0.848, and 0.879 for the training, internal and external validation datasets), with good calibration. The nomogram outperformed the CUS model and CEUS model (all <em>P</em> &lt; .05). Decision curve analysis confirmed that the predictive nomogram was clinically useful.</div></div><div><h3>Conclusion</h3><div>The nomogram based on CUS and CEUS features showed promising predictive value for the preoperative identification of microinvasion in patients with DCIS.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Pages e178-e189"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"USP4/CARM1 Axis Promotes the Malignant Transformation of Breast Cancer Cells by Upregulating SLC7A11 Expression","authors":"Xin Li ,&nbsp;Changjiao Yan ,&nbsp;Jun Yun,&nbsp;Xin Xu,&nbsp;Hongliang Wei,&nbsp;Xiaolong Xu,&nbsp;Yike Li,&nbsp;Jun Yi","doi":"10.1016/j.clbc.2024.10.001","DOIUrl":"10.1016/j.clbc.2024.10.001","url":null,"abstract":"<div><h3>Background</h3><div>Coactivator associated arginine methyltransferase 1 (CARM1) has been identified as a regulator of breast cancer (BC) progression, yet the underlying mechanisms remain elusive.</div></div><div><h3>Methods</h3><div>Quantitative real-time polymerase chain reaction (qRT-PCR) was employed to assess the mRNA expression of CARM1 and solute carrier family 7 member 11 (SLC7A11). Western blotting was conducted to detect the protein expressions of CARM1, ubiquitin specific peptidase 4 (USP4), and SLC7A11. Cell viability, apoptosis, invasion, and migration were evaluated using CCK-8 assay, flow cytometry, transwell assay, and wound-healing assay, respectively. Fe²⁺ and GSH levels were determined by colorimetric assay. Fluorescence microscopy and flow cytometry were utilized to quantify reactive oxygen species (ROS) production. Co-immunoprecipitation (Co-IP) assay and cycloheximide (CHX) assay were performed to investigate the relationship between USP4 and CARM1. Xenograft mouse model assay was conducted to validate the effects of USP4 silencing and CARM1 overexpression on the malignant phenotypes of BC cells.</div></div><div><h3>Results</h3><div>CARM1 and SLC7A11 expression was upregulated in BC tissues and cells when compared with normal breast tissues and cells. Silencing of CARM1 inhibited the malignant phenotypes of BC cells, including decreased cell viability, invasion, and migration and increased cell apoptosis, ferroptosis and oxidative stress. In addition, USP4 stabilized CARM1 protein expression through its deubiquitinating activity. Overexpression of CARM1 attenuated the effects of USP4 silencing in both MCF-7 and MDA-MB-231 cells. Furthermore, silencing of CARM1 reduced SLC7A11 expression, and SLC7A11 overexpression relieved the CARM1 silencing-induced effects. Further, overexpression of CARM1 counteracted the inhibitory effects of USP4 silencing on tumor growth <em>in vivo</em>.</div></div><div><h3>Conclusion</h3><div>Our study reveals a novel mechanism by which USP4-dependent CARM1 promotes the malignant growth of BC cells by interacting with SLC7A11. Targeting this axis may provide a potential therapeutic strategy for BC.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 2","pages":"Pages e196-e207"},"PeriodicalIF":2.9,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142582042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}