Breast Cancer : Targets and Therapy最新文献

{"title":"Radiomics Integration of Mammography and DCE-MRI for Predicting Molecular Subtypes in Breast Cancer Patients.","authors":"Xianwei Yang, Jing Li, Hang Sun, Jing Chen, Jin Xie, Yonghui Peng, Tao Shang, Tongyong Pan","doi":"10.2147/BCTT.S488200","DOIUrl":"10.2147/BCTT.S488200","url":null,"abstract":"<p><strong>Background: </strong>Accurate identification of the molecular subtypes of breast cancer is essential for effective treatment selection and prognosis prediction.</p><p><strong>Aim: </strong>This study aimed to evaluate the diagnostic performance of a radiomics model, which integrates breast mammography and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the molecular subtypes of breast cancer.</p><p><strong>Methods: </strong>We retrospectively included 462 female patients with pathologically confirmed breast cancer, including 53 cases of triple-negative, 94 cases of HER2 overexpression, 95 cases of luminal A, and 215 cases of luminal B breast cancer. Radiomics analysis was performed using FAE software, wherein the radiomic features were examined about the hormone receptor status. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC) and accuracy.</p><p><strong>Results: </strong>In multivariate analysis, radiomic features were the only independent predictive factors for molecular subtypes. The model that incorporates multimodal fusion features from breast mammography and DCE-MRI images exhibited superior overall performance compared to using either modality independently. The AUC values (or accuracies) for six pairings were as follows: 0.648 (0.627) for luminal A vs luminal B, 0.819 (0.793) for luminal A vs HER2 overexpression, 0.725 (0.696) for luminal A vs triple-negative subtype, 0.644 (0.560) for luminal B vs HER2 overexpression, 0.625 (0.636) for luminal B vs triple-negative subtype, and 0.598 (0.500) for triple-negative subtype vs HER2 overexpression.</p><p><strong>Conclusion: </strong>The radionics model utilizing multimodal fusion features from breast mammography combined with DCE-MRI images showed high performance in distinguishing molecular subtypes of breast cancer. It is of significance to accurately predict prognosis and determine treatment strategy of breast cancer by molecular classification.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"187-200"},"PeriodicalIF":3.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11846489/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482052","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":"Lactate Dehydrogenase-A-Forming LDH5 Promotes Breast Cancer Progression.","authors":"Tianxing Fang, Liyu Hu, Tianshun Chen, Fei Li, Liu Yang, Bin Liang, Wenjun Wang, Fancai Zeng","doi":"10.2147/BCTT.S502670","DOIUrl":"10.2147/BCTT.S502670","url":null,"abstract":"<p><strong>Background: </strong>Breast cancer (BC) has become the main malignant tumor threatening the health of women worldwide. Previous studies have reported that Lactate dehydrogenase-A (LDHA) has critical roles in cancer development and progression. We aimed to explore the roles of LDHA and LDH5 isoenzyme activity in BC, which provides a new insight into LDHA for the treatment of BC.</p><p><strong>Methods: </strong>The expression of LDHA in BC and its relationship with clinicopathological features were obtained from various databases including The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Breast Cancer-Gene Expression Miner (bc-GenExMiner), TNMplot, UALCAN. The Kaplan‒Meier Plotter was used to evaluate the prognostic value of LDHA. Western blot was performed to detect LDHA expression. Agarose gel electrophoresis was performed to detect the activities of LDH isoenzymes. The in vitro proliferation, migration and invasion potentials of BC cells were evaluated using MTT assays, colony formation, wound-healing assay, matrix metalloproteinase assays and transwell assays, respectively. The activities of LDH isoenzymes in serum and tissues were measured in patients with BC and healthy controls.</p><p><strong>Results: </strong>Compared to normal tissues, LDHA expression was significantly higher in BC tissues. Patients' nodal status, histological types, <i>TP53</i> mutation status and PAM50 subtypes were significant factors influencing the <i>LDHA</i> expression. By overexpressing or silencing <i>LDHA</i> gene in BT549 cells, it was confirmed that LDHA promoted cell proliferation, migration and invasion. LDH5 isoenzyme activity in patients with BC was higher than healthy controls. The increased activity of LDH5 isoenzymes was induced by overexpression of LDHA in BC. High expression of LDHA was found to be associated with poor prognosis in BC.</p><p><strong>Conclusion: </strong>LDHA plays a critical role in the progression of BC through the regulation of the activity of LDH5 isoenzyme, indicating that LDHA may serve as a valuable target for BC treatment.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"157-170"},"PeriodicalIF":3.3,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11831019/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143439881","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":"The Prediction Model of High-Frequency Ultrasound Combined with Artificial Intelligence-Assisted Scoring System Improved the Diagnosis of Sclerosing Adenosis and Early Breast Cancer.","authors":"Bingxin Ma, Gang Wu, Haohui Zhu, Yifei Liu, Wenjia Hu, Jing Zhao, Yinlong Liu, Qiuyu Liu","doi":"10.2147/BCTT.S483496","DOIUrl":"10.2147/BCTT.S483496","url":null,"abstract":"<p><strong>Objective: </strong>The study aimed to apply an artificial intelligence (AI)-assisted scoring system, and improve the diagnostic efficiency of Sclerosing adenosis and early breast cancer.</p><p><strong>Methods: </strong>This study retrospectively collected adenopathy patients (156 cases) and early breast cancer patients (150 cases) in Henan Provincial People's Hospital from August 2020 to April 2023.</p><p><strong>Results: </strong>The area under the curve of the model constructed by clinical ultrasound features and combined AI features to predict and identify the two in the training group was 0.89 and 0.94, respectively. The combined AI model with the best performance (training AUC, 0.94, 95% CI, 0.91-0.97 and validation AUC, 0.95, 95% CI, 0.90-0.99) was superior to the clinical ultrasound feature model, and the decision curve also showed that the clinical ultrasound combined with AI Nomogram had good clinical practicability. In the training group, the AUC of the sonographer and AI in differential diagnosis was 0.67(95% CI, 0.62-0.71) and 0.89(95% CI, 0.84-0.93), respectively, and the sonographer's assessment showed better sensitivity (1.00 VS 0.73), but AI showed a higher accuracy rate (0.66 VS 0.80).</p><p><strong>Conclusion: </strong>Age, lesion size, burr, blood flow, and AI risk score are independent predictors of sclerosing adenosis and early breast cancer. The combined clinical ultrasound feature and AI model are correlated with AI risk score, US routine features, and clinical data, superior to the clinical ultrasound model and BI-RADS grading, and have good diagnostic performance, which can provide clinicians with a more effective diagnostic tool.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"145-155"},"PeriodicalIF":3.3,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11812439/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143398108","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":"Programmed Cell Death Ligand 1 (PD-L1) and Major Histocompatibility Complex Class I (MHC Class I) Expression Patterns and Their Pathologic Associations in Triple-Negative Breast Cancer.","authors":"Ponkrit Kaewkedsri, Piyapharom Intarawichian, Sirawich Jessadapattarakul, Waritta Kunprom, Supinda Koonmee, Malinee Thanee, Ongart Somintara, Anongporn Wongbuddha, Payia Chadbunchachai, Supajit Nawapun, Chaiwat Aphivatanasiri","doi":"10.2147/BCTT.S506833","DOIUrl":"10.2147/BCTT.S506833","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to investigate the clinicopathological characteristics of triple-negative breast cancer (TNBC) in relation to programmed cell death ligand 1 (PD-L1) and major histocompatibility complex class I (MHC class I) expression, with a focus on their prognostic significance.</p><p><strong>Patients and methods: </strong>A retrospective analysis was conducted on formalin-fixed paraffin-embedded (FFPE) tissue samples from 148 TNBC patients diagnosed between 2008 and 2021. Immunohistochemical analysis evaluated PD-L1 and MHC class I expression. PD-L1 was assessed using Combine Positive Scores (CPS), with the threshold set at CPS ≥ 1 and CPS ≥ 10. MHC class I expression was categorized into low and high levels. Associations between these markers, clinicopathological features, overall survival (OS), and disease-free survival (DFS) were analyzed. PD-L1 expression was also compared between older FFPE blocks (2008-2018) versus newer blocks (2019-2021).</p><p><strong>Results: </strong>PD-L1 expression was observed in 29.1% of cases with a Combined Positive Score (CPS) ≥1 and 8.8% of CPS ≥10 cases. MHC class I expression was evenly split between low and high levels. Older FFPE blocks (2008-2018) showed lower PD-L1 expression than newer blocks (2019-2021). There was no significant association between PD-L1 expression and overall survival (OS) or disease-free survival (DFS). However, high MHC class I expression was strongly associated with improved OS (HR = 0.469, 95% CI: 0.282-0.780, p=0.004). Patients with negative PD-L1 and high MHC class I expression had the most favorable prognosis, with significant OS for CPS ≥1 (HR = 0.447, 95% CI: 0.236-0.846, p=0.013) and CPS ≥10 (HR = 0.516, 95% CI: 0.307-0.869, p=0.013).</p><p><strong>Conclusion: </strong>These findings support the potential of PD-L1 and MHC class I expression as prognostic markers for TNBC, offering insights to guide treatment decisions and improve patient outcomes.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"123-143"},"PeriodicalIF":3.3,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11812676/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143398103","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":"Analysis of Mammography BI-RADS Distribution and Follow-up Ultrasound Assessment: A Single-Center Study.","authors":"Burak Kankaya, Suleyman Buyukasik, Yusuf Emre Altundal, Feyza Sonmez Topcu, Paria Rahmanbakhsh, Ayden Etemad, Selin Kapan, Halil Alis","doi":"10.2147/BCTT.S481201","DOIUrl":"10.2147/BCTT.S481201","url":null,"abstract":"<p><strong>Purpose: </strong>Our study has three main aims: 1) to assess the distribution of Breast Imaging Reporting and Data System (BI-RADS) classifications in a cohort of Turkish women undergoing screening mammography, 2) to analyze the frequency and non-completion rates of recommended follow-up ultrasound (US) examinations, and 3) to examine the outcomes of completed follow-up US examinations. Our goal was to evaluate potential gaps in the current breast cancer screening process by analyzing BI-RADS classifications, follow-up completion rates, and outcomes of completed ultrasound examinations.</p><p><strong>Patients and methods: </strong>This retrospective study analyzed 1761 Turkish women who underwent screening mammography from 2020-2022 at the Istanbul Aydin University General Surgery Clinic, Istanbul, Turkey. We assessed the distribution of BI-RADS classifications, analyzed the frequency and non-completion rates of recommended follow-up US, and examined the outcomes of completed follow-up US examinations. Chi-square tests of independence and Spearman's rank correlation test were used to analyze the data.</p><p><strong>Results: </strong>Our study revealed three key findings: 1) Over half of mammograms (55.9%) were classified as BI-RADS 0, requiring further imaging. 2) Nearly one-third of patients who recommended US examinations (31.91%) did not complete recommended follow-up ultrasound appointments. 3) Among those who completed follow-up ultrasonography, almost one-third (29.7%) were reclassified as BI-RADS 3 or higher. Notably, 2.3% (n=18) were classified as BI-RADS 4 or 5, suggesting findings suspicious for malignancy.</p><p><strong>Conclusion: </strong>Our findings highlight the crucial role of follow-up US in breast cancer screening. The high rate of initial BI-RADS 0 classifications using mammography, coupled with the significant non-completion rate for follow-up US examinations, particularly among older age groups, highlights potential gaps in the current screening process.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"115-122"},"PeriodicalIF":3.3,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11809216/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143390008","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":"Predicting Axillary Lymph Node Metastasis in Young Onset Breast Cancer: A Clinical-Radiomics Nomogram Based on DCE-MRI.","authors":"Xia Dong, Jingwen Meng, Jun Xing, Shuni Jia, Xueting Li, Shan Wu","doi":"10.2147/BCTT.S495246","DOIUrl":"10.2147/BCTT.S495246","url":null,"abstract":"<p><strong>Background: </strong>Young onset breast cancer, diagnosed in women under 50, is known for its aggressive nature and challenging prognosis. Precisely forecasting axillary lymph node metastasis (ALNM) is essential for customizing treatment plans and enhancing patient results.</p><p><strong>Objective: </strong>This research sought to create and verify a clinical-radiomics nomogram that combines radiomic features from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) with standard clinical predictors to improve the accuracy of predicting ALNM in young breast cancer patients.</p><p><strong>Methods: </strong>We performed a retrospective analysis at one facility, involving the creation and validation of a nomogram in two stages.At first, a medical model was developed utilizing conventional indicators like tumor dimensions, molecular classifications, multifocal presence, and MRI-determined ALN status.A more detailed clinical-radiomics model was subsequently developed by integrating radiomic characteristics derived from DCE-MRI images.These models were created using logistic regression analyses on a training dataset, and their effectiveness was assessed by measuring the area under the receiver operating characteristic curve (AUC) in a separate validation dataset.</p><p><strong>Results: </strong>The clinical-radiomics nomogram surpassed the clinical-only model, recording an AUC of 0.892 in the training dataset and 0.877 in the validation dataset.Significant predictors included MRI-reported ALN status and select radiomic features, which markedly enhanced the model's predictive capacity.</p><p><strong>Conclusion: </strong>Integrating radiomic features with clinical predictors in a nomogram significantly improves ALNM prediction in young onset breast cancer, providing a valuable tool for personalized treatment planning. This study underscores the potential of merging advanced imaging data with clinical insights to refine oncological predictive models. Future research should expand to multicentric studies and include genomic data to boost the nomogram's generalizability and precision.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"103-113"},"PeriodicalIF":3.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11784255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143078119","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":"Adipokines in Breast Cancer: Decoding Genetic and Proteomic Mechanisms Underlying Migration, Invasion, and Proliferation.","authors":"Anne Ließem, Uwe Leimer, Günter K Germann, Eva Köllensperger","doi":"10.2147/BCTT.S491277","DOIUrl":"10.2147/BCTT.S491277","url":null,"abstract":"<p><strong>Background: </strong>Adipokines, bioactive peptides secreted by adipose tissue, appear to contribute to breast cancer development and progression. While numerous studies suggest their role in promoting tumor growth, the exact mechanisms of their involvement are not yet completely understood.</p><p><strong>Methods: </strong>In this project, varying concentrations of recombinant human adipokines (Leptin, Lipocalin-2, PAI-1, and Resistin) were used to study their effects on four selected breast cancer cell lines (EVSA-T, MCF-7, MDA-MB-231, and SK-Br-3). Over a five-day proliferation phase, linear growth was assessed by calculating doubling times and malignancy-associated changes in gene and protein expression were identified using quantitative TaqMan real-time PCR and multiplex protein analysis. Migration and invasion behaviors were quantified using specialized Boyden chamber assays.</p><p><strong>Results: </strong>We found significant, adipokine-mediated genetic and proteomic alterations, with PCR showing an up to 6-fold increase of numerous malignancy-associated genes after adipokine-supplementation. Adipokines further altered protein secretion, such as raising the concentrations of different tumor-associated proteins up to 13-fold. Effects on proliferation varied, however, with most approaches showing significant enhancement in growth kinetics. A concentration-dependent increase in migration and invasion was generally observed, with no significant reductions in any approaches.</p><p><strong>Conclusion: </strong>We could show a robust promoting effect of several adipokines on different breast cancer cells in vitro. Understanding the interaction between adipose tissue and breast cancer cells opens potential avenues for innovative breast cancer prevention and therapy strategies. Our findings indicate that antibodies against specific adipokines could become a beneficial component of clinical breast cancer treatment in the future.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"79-102"},"PeriodicalIF":3.3,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11776935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063669","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":"Non-Luminal Disease Score for Everolimus in Patients with Hormone Receptor‑positive and Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer: A Multicenter and Retrospective Study.","authors":"Yujing Tan, Hanfang Jiang, Xinzhu Tian, Fei Ma, Jiayu Wang, Pin Zhang, Binghe Xu, Ying Fan, Weihong Zhao","doi":"10.2147/BCTT.S493053","DOIUrl":"10.2147/BCTT.S493053","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to explore the role of the non-luminal disease score (NOLUS) for everolimus in patients with hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+/HER2-) advanced breast cancer (ABC).</p><p><strong>Methods: </strong>NOLUS has previously been established as an algorithm: NOLUS (0-100) = - 0.45 × ER(%) - 0.28 × PR(%) + 0.27 × Ki67(%) + 73. Information of cancer patients was retrospectively collected from three cancer centers in China.</p><p><strong>Results: </strong>Totally, 198 HR+/HER2- ABC patients with complete records in expression rates (%) of ER, PR and Ki67 were enrolled in the study. The expression rates (%) of ER, PR, and Ki67 were 38.8 ± 27.9 <i>versus</i> 80.9 ± 14.2 (p < 0.001), 13.9 ± 14.3 <i>versus</i> 50.2 ± 30.4 (p < 0.001), and 37.8 ± 23.6 <i>versus</i> 28.7 ± 19.9 (p = 0.04), respectively, for NOLUS-positive patients and NOLUS-negative patients. For the overall population, the median PFS was 5.8 months <i>versus</i> 5.1 months in NOLUS-positive and NOLUS-negative patients (p = 0.16, HR = 0.75, 95% CI = 0.50, 1.12). The median 1L-, 2L, and 3L-PFS was 13.9 months <i>versus</i> 11.8 months (p = 0.22, HR = 1.63, 95% CI = 0.74, 3.62), 6.7 months <i>versus</i> 3.6 months (p = 0.08, HR = 0.34, 95% CI = 0.10, 1.18), and 4.6 months <i>versus</i> 4.0 months (p = 0.81, HR = 1.07, 95% CI = 0.63, 1.79) respectively, for NOLUS-positive patients and NOLUS-negative patients.</p><p><strong>Conclusion: </strong>NOLUS-positive patients have a lower percentage of ER and PR, but a higher percentage of Ki67 index. The correlation between the benefits of everolimus and NOLUS failed to develop significance, suggesting that NOLUS may not be applicable in predicting everolimus efficacy in patients with HR+/HER2- ABC. Further research is expected.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"67-78"},"PeriodicalIF":3.3,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774108/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143057937","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":"Update on Pulmonary Toxicity Induced by New Breast Cancer Treatments.","authors":"Lorenzo Belluzzi, Giulio Martinelli, Bianca Medici, Alessandro Farina, Enrica Martinelli, Fabio Canino, Federica Caggia, Alessia Molinaro, Monica Barbolini, Fabio Tamburrano, Luca Moscetti, Federico Piacentini, Massimo Dominici, Claudia Omarini","doi":"10.2147/BCTT.S489419","DOIUrl":"10.2147/BCTT.S489419","url":null,"abstract":"<p><p>In recent years, new anticancer drugs have been investigated and approved for the treatment of breast cancer based on improved survival outcomes. However, these new treatments have specific class-related side effects. Pulmonary toxicity has been identified as an adverse event of special interest with everolimus, and is becoming an increasingly significant clinical challenge with the recent approval of trastuzumab deruxtecan. Overall, the risk of pulmonary toxicity is quite low but in some cases lung damage can be fatal. We conducted an update including the available published data regarding the incidence, mechanisms of pathogenesis, clinical presentations, and treatment of lung toxicity induced by new anticancer drugs. A literature search was performed between January and June 2024, considering papers, clinical trials, case reports, case series, meta-analyses, and systematic reviews published from January 2014 to June 2024. We also provide an algorithm for diagnosis and treatment, along with real-life cases managed at the Modena Cancer Center. Data provided here show that pulmonary toxicity is a quite frequent side effect and underline that early recognition and prompt treatment are crucial for the best outcome of patients, whose overall prognosis is being improved by the availability of these new anticancer agents.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"53-66"},"PeriodicalIF":3.3,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11762262/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045536","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":"From Pioneering Discoveries to Innovative Therapies: A Journey Through the History and Advancements of Nanoparticles in Breast Cancer Treatment.","authors":"Fatemah S Basingab, Omniah A Alshahrani, Ibtehal H Alansari, Nada A Almarghalani, Nada H Alshelali, Abeer Hamad Alsaiary, Najwa Alharbi, Kawther A Zaher","doi":"10.2147/BCTT.S501448","DOIUrl":"10.2147/BCTT.S501448","url":null,"abstract":"<p><p>Nanoparticle technology has revolutionized breast cancer treatment by offering innovative solutions addressing the gaps in traditional treatment methods. This paper aimed to comprehensively explore the historical journey and advancements of nanoparticles in breast cancer treatment, highlighting their transformative impact on modern medicine. The discussion traces the evolution of nanoparticle-based therapies from their early conceptualization to their current applications and future potential. We initially explored the historical context of breast cancer treatment, highlighting the limitations of conventional therapies, such as surgery, radiation, and chemotherapy. The advent of nanotechnology has introduced a new era characterized by the development of various nanoparticles, including liposomes, dendrimers, and gold nanoparticles, designed to target cancer cells with remarkable precision. We further described the mechanisms of action for nanoparticles, including passive and active targeting, and reviewed significant breakthroughs and clinical trials that have validated their efficacy. Current applications of nanoparticles in breast cancer treatment have been examined, showcasing clinically approved therapies and comparing their effectiveness with traditional methods. This article also discusses the latest advancements in nanoparticle research, including drug delivery systems and combination therapy innovations, while addressing the current technical, biological, and regulatory challenges. The technical challenges include efficient and targeted delivery to tumor sites without affecting healthy tissue; biological, such as potential toxicity, immune system activation, or resistance mechanisms; economic, involving high production and scaling costs; and regulatory, requiring rigorous testing for safety, efficacy, and long-term effects to meet stringent approval standards. Finally, we have explored emerging trends, the potential for personalized medicine, and the ethical and social implications of this transformative technology. In conclusion, through comprehensive analysis and case studies, this paper underscores the profound impact of nanoparticles on breast cancer treatment and their future potential.</p>","PeriodicalId":9106,"journal":{"name":"Breast Cancer : Targets and Therapy","volume":"17 ","pages":"27-51"},"PeriodicalIF":3.3,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11761866/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045535","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}