Breast Cancer : Targets and Therapy最新文献

{"title":"LINC00917 Promotes Bone Metastasis of Breast Cancer by Targeting the miR-491-5p/FOXP4 Axis.","authors":"Xin Qu, Cao Wang, Ying Xu, Xin Yang, An-Bing Sun, Xiao-Yu Liu, Jin-Ze Li, Jian-Yun Nie","doi":"10.2147/BCTT.S545046","DOIUrl":"https://doi.org/10.2147/BCTT.S545046","url":null,"abstract":"<p><strong>Purpose: </strong>Breast cancer is one of the most common malignant tumors in women. Advanced patients often experience distant metastasis, among which bone metastasis has a relatively high incidence rate, seriously affecting the quality of life and prognosis of patients. LINC00917 may be related to the prognosis of breast cancer patients. This study aims to explore whether LINC00917 plays a significant role in breast cancer bone metastasis by targeting and regulating the expression of miR-491-5p.</p><p><strong>Patients and methods: </strong>254 breast cancer patients were recruited. The levels of LINC00917 were examined by RT-qPCR. Furthermore, the association between LINC00917 expression and patient prognosis was evaluated using Kaplan-Meier curves and Cox regression analysis. An in vitro cell model was established, and CCK-8 and Transwell assays were conducted to explore the role of LINC00917 in breast cancer bone metastasis. Additionally, the interaction among LINC00917, miR-491-5p, and FOXP4 were examined using dual-luciferase reporter assays.</p><p><strong>Results: </strong>LINC00917 was upregulated in breast cancer bone metastasis and was associated with bad prognosis. Additionally, the knockdown of LINC00917 inhibited the function of breast cancer cells, and suppressed osteoclastogenesis while promoting osteoblast differentiation. Moreover, miR-491-5p inhibition counteracted the effects of LINC00917 knockdown on cell models. Furthermore, FOXP4 may be a target gene of miR-491-5p.</p><p><strong>Conclusion: </strong>LINC00917 is a potential prognostic indicator for breast cancer bone metastasis. It is proposed that LINC00917 may facilitate the bone metastasis process in breast cancer by modulating the miR-491-5p/FOXP4 axis.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"913-925"},"PeriodicalIF":3.4,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12541200/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145353709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>Ki-67</i> Prediction in Breast Cancer: Integrating Radiomics From Automated Breast Volume Scanner and 2D Ultrasound Images via Machine Learning.","authors":"Wei Wei, Fei Xia, Wang Zhou, Wenwu Lu, Di Zhang, Qianqing Ma, Xiangyi Xu, Chaoxue Zhang","doi":"10.2147/BCTT.S540595","DOIUrl":"10.2147/BCTT.S540595","url":null,"abstract":"<p><strong>Purpose: </strong>This study aimed to develop and validate a predictive model using radiomics features from automatic breast volume scanner (ABVS) and 2D ultrasound images to preoperatively assess Ki-67 expression in breast cancer (BC), thereby supporting personalized clinical treatment planning.</p><p><strong>Methods: </strong>Data from 426 BC patients who met the inclusion criteria were retrospectively analyzed. Univariate and multivariate logistic regression analyses were performed on the clinical ultrasound characteristics to construct a clinical model. Radiomics features were extracted from both the tumor and the sub-regions based on ABVS and 2D images. The silhouette coefficient was used to evaluate clustering performance and determine the optimal number of clusters. Radiomics-based prediction models were developed using four machine learning classifiers: Logistic Regression, ExtraTree, XGBoost, and LightGBM. A combined model was further constructed by integrating radiomics and habitat radiomics features from ABVS and 2D images with relevant clinical factors. Model performance was evaluated using the Receiver Operating Characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).</p><p><strong>Results: </strong>In the validation set, the area under the ROC curve (AUC) values of the radiomics model (Rad <i>_{ABVS + 2D}</i> ), the habitat radiomics model (Hab <i>_{ABVS + 2D}</i> ), and the combined radiomics model (Rad-Hab <i>_{ABVS + 2D}</i> ) were 0.603, 0.664, and 0.850, respectively. By integrating independent clinical factors (US-ALNs, T-stage) with the Rad-Hab <i>_{ABVS + 2D}</i> model, a comprehensive model (CM <i>_{Clinical + Rad-Hab}</i> ) was constructed using LightGBM. According to the DeLong test, this model significantly outperformed others in terms of AUC (<i>P</i> < 0.05). The AUC values for the training and validation sets were 0.951 (95% CI: 0.928-0.973) and 0.884 (95% CI: 0.832-0.949), respectively. The calibration curves and DCA of CM <i>_{Clinical + Rad-Hab}</i> demonstrated excellent model calibration and clinical utility.</p><p><strong>Conclusion: </strong>The CM <i>_{Clinical + Rad-Hab}</i> model developed in this study enables accurate preoperative prediction of <i>Ki-67</i> expression in BC patients, facilitating personalized and precise treatment strategies.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"897-912"},"PeriodicalIF":3.4,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12523655/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145306729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Validation of Machine Learning Models in Predicting Prognosis of Breast Cancer Patients with Lymph Nodes Metastasis Following Neoadjuvant Chemotherapy.","authors":"Yanjia Fan, Yudi Jin, Cheng Tian, Yu Zhang, Chi Zhang, Haochen Yu, Shengchun Liu","doi":"10.2147/BCTT.S534964","DOIUrl":"10.2147/BCTT.S534964","url":null,"abstract":"<p><strong>Background: </strong>Lymph node (LN) status is a critical prognostic factor for breast cancer patients undergoing neoadjuvant chemotherapy (NAC). This study aims to develop and validate machine learning models to predict LN response in breast cancer patients with LN metastases.</p><p><strong>Methods: </strong>Breast cancer patients who received NAC in our hospital were retrospectively analyzed. Clinicopathological data, and MRI imaging were collected. Patients were randomly divided into a training set and a testing set in 7:3 ratio. Radiomic features were extracted from pre-treatment imaging. Random forests and logistic regression were employed alongside Clinical, Clinical-Radiomics and Clinical-Deep-learning-radiomics (Clinical-DLR) in training set. Model performance was evaluated using metrics including sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), accuracy and F1-score. Finally, patients were divided into high-risk and low-risk groups according to the model with the best performance.</p><p><strong>Results: </strong>Overall, 447 patients were enrolled. In the Clinical, Clinical-Radiomics, and Clinical-DLR logistic regression models, the AUC values in the testing set were 0.738, 0.798, and 0.911, respectively. For the random forest models, the AUC values in the testing set were 0.754, 0.801, and 0.921, respectively. Based on the predictions from the Clinical-DLR model, patients can be stratified into high-risk and low-risk groups. The survival outcomes for high-risk patients were significantly worse compared to those of low-risk patients.</p><p><strong>Conclusion: </strong>The deep learning radiomics offers a promising approach to predict LN status and survival outcome in breast cancer patients undergoing NAC. This could facilitate personalized treatment strategies and improve clinical decision-making.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"883-896"},"PeriodicalIF":3.4,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12495929/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145231478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Triple-Negative Breast Cancer on the Rise: Breakthroughs and Beyond [Response to Letter].","authors":"Alex Agelidis, Anna Ter-Zakarian, Mohammed Jaloudi","doi":"10.2147/BCTT.S566423","DOIUrl":"https://doi.org/10.2147/BCTT.S566423","url":null,"abstract":"","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"877-881"},"PeriodicalIF":3.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12493102/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145231473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Triple-Negative Breast Cancer on the Rise or…? [Letter].","authors":"Per Eystein Lønning, Oleksii Nikolaienko, Stian Knappskog","doi":"10.2147/BCTT.S560499","DOIUrl":"10.2147/BCTT.S560499","url":null,"abstract":"","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"875-876"},"PeriodicalIF":3.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12478219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145198138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of Trastuzumab Deruxtecan in HER2-Positive and HER2-Low Metastatic Breast Cancer: A Real-World Retrospective Cohort Study in China.","authors":"Yuxin Yan, Yizi Jin, Mingxi Lin, Ceng Zeng, Qing Guo, Teng Zhou, Dou Dou Li, Jian Zhang","doi":"10.2147/BCTT.S545308","DOIUrl":"10.2147/BCTT.S545308","url":null,"abstract":"<p><strong>Background: </strong>Limited real-world data are available on the effectiveness and safety of trastuzumab deruxtecan (T-DXd, DS8201a) in patients with HER2-positive and HER2-low metastatic breast cancer (MBC), particularly within the Chinese population.</p><p><strong>Methods: </strong>Between 2022 and 2025, 98 patients with MBC treated with T-DXd were retrospectively enrolled at Fudan University Shanghai Cancer Center. Patients were categorized as HER2-positive and HER2-low cohort. Clinical outcomes including objective response rate (ORR), progression-free survival (PFS), disease control rate (DCR), and clinical benefit rate (CBR), were assessed and compared between cohorts. The primary endpoint of the study was PFS, which was estimated using the Kaplan-Meier method and compared using the Log rank test.</p><p><strong>Results: </strong>Among the 98 patients, the median PFS was 15.0 months. The ORR, DCR, and CBR were 48.0%, 69.4%, and 41.8%, respectively. HER2-positive patients experienced longer PFS compared to HER2-low patients (not reached vs 9.0 months). Among HER2-low patients, liver metastases were associated with poorer outcomes. Patients with brain metastases achieved a median PFS of 15.5 months and a 1-year PFS rate of 65.3%. Grade ≥3 adverse events included neutropenia (20.4%), nausea (5.1%), anemia (4.1%), and interstitial lung disease in 6.1% of patients, leading to discontinuation in 2.0%.</p><p><strong>Conclusion: </strong>In this real-world analysis, T-DXd demonstrated robust clinical activity in both HER2-positive and HER2-low MBC, consistent with the findings from the DESTINY-Breast clinical trials. Notably, we identified several clinically relevant prognostic factors, including HER2 status, metastatic site, treatment line, and prior therapies. These findings support the broader clinical application of T-DXd and offer insights into individualized treatment selection.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"863-873"},"PeriodicalIF":3.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479221/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Management of Circulating Tumor DNA in Breast Cancer: Detection, Prediction, and Monitoring.","authors":"Yongqu Lu, Lehao Ren, Meng Yang, Jun Liu","doi":"10.2147/BCTT.S542704","DOIUrl":"10.2147/BCTT.S542704","url":null,"abstract":"<p><p>Despite substantial progress in the diagnosis and treatment of breast cancer, current therapeutic regimens exhibit limitations, necessitating the identification of more robust biomarkers to optimize personalized strategies. Circulating tumor DNA (ctDNA), as a non-invasive liquid biopsy modality, overcomes the inherent constraints of biopsies in capturing tumor heterogeneity. Accumulating evidence from prospective cohort studies demonstrates the clinical utility of ctDNA in risk stratification, guidance of therapeutic decision-making, recurrence surveillance and other clinical applications. Furthermore, ctDNA profiling enhances real-time pharmacodynamic monitoring and accelerates drug development by identifying molecular responders. The methodical requirements and challenges inherent in implementing liquid biopsy assessments in the clinic are examined. These encompass critical pre-analytical variables, the need for highly sensitive and specific analytical techniques, standardization of assays and bioinformatics pipelines across laboratories and the complexities of interpreting results. This review synthesizes current evidence supporting ctDNA integration into breast cancer management frameworks and systematically addresses its methodological challenges and clinical limitations.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"851-861"},"PeriodicalIF":3.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479222/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ANXA2 Regulates RANKL-Induced Osteoclast Differentiation Through STAT3 Signaling in Breast Cancer.","authors":"Jie Yuan, Fei Xin, Ruliang Wang","doi":"10.2147/BCTT.S542181","DOIUrl":"10.2147/BCTT.S542181","url":null,"abstract":"<p><strong>Background: </strong>Bone metastasis affects nearly 70% of patients with advanced breast cancer, significantly influencing patient survival. Osteoclasts play a crucial role in osteolysis and the proliferation of bone tumor cell metastasis. Although previous studies have established Anxa2 as a critical factor in the invasion and metastasis of breast cancer, its involvement in bone metastasis remains poorly understood.</p><p><strong>Methods: </strong>The correlation between ANXA2 expression and survival was analyzed in breast cancer cohorts. Enrichment analysis was performed to explore ANXA2-associated signaling pathways. RAW264.7 cells were induced to differentiate into osteoclasts using conditioned media from breast cancer cells, and osteoclastogenesis was quantified using the TRAP assay. Breast cancer cell lines with either Anxa2 overexpression or knockdown were established to assess the impact on osteoclastogenesis. The mRNA and protein expression levels were analyzed by RT-PCR and Western blot. The role of STAT3 in regulating RANKL expression was evaluated using a dual luciferase reporter assay.</p><p><strong>Results: </strong>ANXA2 was significantly upregulated in breast cancer patients and associated with poor survival. GO and KEGG analyses revealed that ANXA2 substantially modulated signaling pathways involved in bone metastasis. Furthermore, ANXA2 notably enhanced the differentiation of RAW264.7 cells into osteoclasts and upregulated genes associated with osteoclast differentiation. Additional investigation showed that ANXA2 markedly activated the STAT3 signaling pathway and increased RANKL expression. The dual luciferase reporter assay demonstrated that STAT3 directly bound to the -1804 region of the RANKL promoter, thereby regulating RANKL expression.</p><p><strong>Conclusion: </strong>This study identifies ANXA2 as a key regulator of osteoclast differentiation through STAT3-mediated upregulation of RANKL, driving bone metastasis in breast cancer. These results highlight the potential of targeting the ANXA2/STAT3/RANKL axis as a therapeutic strategy to combat bone metastasis.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"837-849"},"PeriodicalIF":3.4,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12452988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145130031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of <i>Clinacanthus nutans</i> Extracts on Cell Proliferation and Apoptosis in Triple-Negative Breast Cancer: Mechanistic Insights.","authors":"Jiafang Xu, Jincha Long, Zhen Ying Li, Chaoqun Wang, Yonggang Zhang, Huifang He, Qingjie Hu, Siqi Yin, Hai Li, Naizhen Wang, Qiang Gao, Shuaining Tang, Yongkang Zhu, Peng Wang, Renjun Feng, Yu Liu","doi":"10.2147/BCTT.S528242","DOIUrl":"10.2147/BCTT.S528242","url":null,"abstract":"<p><strong>Objective: </strong>To explore the effects of <i>Clinacanthus nutans</i> extract (CnE) on triple-negative breast cancer (TNBC) and mechanism of action.</p><p><strong>Methods: </strong>In vitro, the human TNBC cell lines were treated with the extract at various concentrations. Cell viability was assessed using the CCK8 assay. In vivo, establishing a subcutaneous xenograft tumor model of TNBC, Hematoxylin-eosin staining and TUNEL assay were used to evaluate the effect of CnE on tumor proliferation. Tumor proteins were extracted, Quantitative proteomics and subsequently analyzed using bioinformatics approaches. Finally, immunohistochemistry evaluates the protein expression differences of ATP2A3, PLA2G4A, and ITPK1.</p><p><strong>Results: </strong>In vitro, CnE inhibited TNBC cell proliferation in a concentration-dependent manner, with IC50 values of 420 ± 35 μg/mL (MDA-MB-231) and 380 ± 28 μg/mL (MDA-MB-468), showing maximal 68.5% inhibition at 800 μg/mL (p < 0.001). The TNBC xenograft model was successfully established, and tumours in the extract-treated group were markedly smaller than those in the saline group. On day 28, the tumour inhibition rate was 28.66%, significantly higher than that in the saline group (P < 0.05). Haematoxylin-eosin staining staining and TUNEL assay showed increased tumor necrosis and apoptosis induction.(P < 0.001). Proteomic analysis showed that among the 4,908 identified proteins, 80 were upregulated, and 7 were downregulated. Bioinformatics analysis indicated involvement in the extracellular matrix, fatty acid metabolism, cell apoptosis, ferroptosis, immune response, choline metabolism, and amino acid metabolism. Immunohistochemistry revealed increased expression of ATP2A3 (1.3-fold, p < 0.05), PLA2G4A (1.6-fold, p < 0.05) and ITPK1 (3.2-fold, p < 0.01) proteins in the extract group compared to the control group.</p><p><strong>Conclusion: </strong>CnE inhibits TNBC cell proliferation, suppresses tumor growth, The mechanism likely involves multiple biological processes and pathways, Key pathways included apoptosis, ferroptosis, and necroptosis signaling.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"819-835"},"PeriodicalIF":3.4,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12448096/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145111747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utility of Volatile Organic Compounds and Electronic Nose Technology for Breast Cancer Detection: A Systematic Review.","authors":"Fernanda M Orduña-Medina, Lorena Díaz de León-Martinez, Grecia D D Alarcón-Rivera, Nancy Angélica Prieto-Gómez, Boris Mizaikoff, Luz E Alcántara-Quintana","doi":"10.2147/BCTT.S525265","DOIUrl":"10.2147/BCTT.S525265","url":null,"abstract":"<p><p>Breast cancer is a leading cause of mortality in women worldwide, primarily due to challenges in early detection and limited access to timely treatment. While mammography is widely used, it may produce false positives and lead to overdiagnosis. Recent advancements suggest that electronic nose technology, based on the detection of volatile organic compounds (VOCs), may offer a complementary non-invasive approach to breast cancer screening. This systematic review evaluates current detection methods and explores the feasibility and diagnostic value of the electronic nose, assessing its integration into existing clinical strategies.</p><p><strong>Methods: </strong></p><p><strong>Study design: </strong>A systematic review was conducted following PRISMA guidelines.</p><p><strong>Eligibility criteria: </strong>Seventy-six original articles were included, alongside data from eight additional studies. Eligible studies were published in English or Spanish, evaluated VOCs as a breast cancer screening method, and reported identified VOCs. Systematic reviews, duplicates, editorials, and articles without full-text access were excluded. Information sources and search strategy: Searches were conducted in PubMed, Web of Science, Wiley Online Library, and Science Direct between September and October 2024. Keywords included: volatile organic compounds, breath biomarkers, volatolomics, breast cancer, breast carcinoma, screening, detection, and electronic nose. A total of 581 articles were retrieved: 64 from PubMed, 44 from Web of Science, 152 from Wiley, and 321 from Science Direct.</p><p><strong>Study selection: </strong>Zotero was used for reference management and duplicate removal. Two reviewers independently screened titles and abstracts; eligible full texts were reviewed, and discrepancies resolved by consensus.</p><p><strong>Data extraction: </strong>A standardized form was used to collect author, publication year, population, intervention, comparator, main results, and analysis-relevant data. Three reviewers performed the extraction independently.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"805-817"},"PeriodicalIF":3.4,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12435362/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}