Breast Cancer Research最新文献

{"title":"Cellular senescence predicts breast cancer risk from benign breast disease biopsy images.","authors":"Indra Heckenbach, Rita Peila, Christopher Benz, Sheila Weinmann, Yihong Wang, Mark Powell, Morten Scheibye-Knudsen, Thomas Rohan","doi":"10.1186/s13058-025-01993-z","DOIUrl":"10.1186/s13058-025-01993-z","url":null,"abstract":"<p><strong>Background: </strong>Each year, millions of women undergo breast biopsies. Of these, 80% are negative for malignancy but some may be at elevated risk of invasive breast cancer (IBC) due to the presence of benign breast disease (BBD). Cellular senescence plays a complex but poorly understood role in breast cancer development and the presence or absence of these cells may have prognostic value.</p><p><strong>Methods: </strong>We conducted a case-control study, nested within a cohort of 15,395 women biopsied for BBD at Kaiser Permanente Northwest between 1971 and 2006. Cases (n = 512) were women who developed a subsequent invasive breast cancer (IBC) at least one year after the BBD biopsy; controls (n = 491) did not develop IBC during the same follow-up period. Using H&E-stained biopsy images, we predicted senescence based on deep learning models trained on replicative senescence (RS), ionizing radiation (IR), and various drug treatments. Age-adjusted and multivariable odds ratios (ORs) and 95% confidence intervals (CI) were estimated using unconditional logistic regression.</p><p><strong>Results: </strong>The RS- and IR-derived senescence scores for adipose tissue and the RS-derived score for epithelial tissue were positively associated with the risk of IBC (adipose tissue - RS model: OR_{q4 vs. q1}=1.69, 95% CI 1.03-2.77, and IR model: OR_{q4 vs. q1}=1.73, 95%CI 1.06-2.82; epithelial tissue- RS model: OR_{q4 vs. q1}=1.53, 95% CI 1.05-2.22). The results were stronger among postmenopausal women and women with epithelial hyperplasia with/without atypia, and postmenopausal women also showed a positive association for stromal tissue with the RS model (OR_{q4 vs. q1}=1.84, 95%CI 1.12-3.04). There was an elevated risk of IBC in those with higher senescence scores in both epithelial and adipose tissue compared with those with low senescence scores in both (IR epithelium-IR fat: OR_{q2-4 vs. q1}=2.14, 95% CI 1.30-3.51; and IR epithelium-RS fat: OR_{q2-4 vs. q1}= 2.24, 95% CI 1.15-4.35).</p><p><strong>Conclusions: </strong>This study suggests that nuclear senescence scores predicted by deep learning models in breast epithelial and adipose tissue can predict the risk of breast cancer development among women with BBD.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"37"},"PeriodicalIF":7.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11900263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143606961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a deep learning-based model for guiding a dissection during robotic breast surgery.","authors":"Jeea Lee, Sungwon Ham, Namkug Kim, Hyung Seok Park","doi":"10.1186/s13058-025-01981-3","DOIUrl":"10.1186/s13058-025-01981-3","url":null,"abstract":"<p><strong>Background: </strong>Traditional surgical education is based on observation and assistance in surgical practice. Recently introduced deep learning (DL) techniques enable the recognition of the surgical view and automatic identification of surgical landmarks. However, there was no previous studies have conducted to develop surgical guide for robotic breast surgery. To develop a DL model for guiding the dissection plane during robotic mastectomy for beginners and trainees.</p><p><strong>Methods: </strong>Ten surgical videos of robotic mastectomy procedures were recorded. Video frames taken at 1-s intervals were converted to PNG format. The ground truth was manually delineated by two experienced surgeons using ImageJ software. The evaluation metrics were the Dice similarity coefficient (DSC) and Hausdorff distance (HD).</p><p><strong>Results: </strong>A total of 8,834 images were extracted from ten surgical videos of robotic mastectomies performed between 2016 and 2020. Skin flap dissection during the robotic mastectomy console time was recorded. The median age and body mass index of the patients was 47.5 (38-52) years and 22.00 (19.30-29.52) kg/m², respectively, and the median console time was 32 (21-48) min. Among the 8,834 images, 428 were selected and divided into training, validation, and testing datasets at a ratio of 7:1:2. Two experts determined that the DSC of our model was 0.828[Formula: see text]5.28 and 0.818[Formula: see text]6.96, while the HDs were 9.80[Formula: see text]2.57 and 10.32[Formula: see text]1.09.</p><p><strong>Conclusion: </strong>DL can serve as a surgical guide for beginners and trainees, and can be used as a training tool to enhance surgeons' surgical skills.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"34"},"PeriodicalIF":7.4,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11895239/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143598309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lipid metabolic reprogramming drives triglyceride storage and variable sensitivity to FASN inhibition in endocrine-resistant breast cancer cells.","authors":"Ashley V Ward, Duncan Riley, Kirsten E Cosper, Jessica Finlay-Schultz, Heather M Brechbuhl, Andrew E Libby, Kaitlyn B Hill, Rohan R Varshney, Peter Kabos, Michael C Rudolph, Carol A Sartorius","doi":"10.1186/s13058-025-01991-1","DOIUrl":"10.1186/s13058-025-01991-1","url":null,"abstract":"<p><strong>Background: </strong>Lipid metabolic reprogramming is increasingly recognized as a hallmark of endocrine resistance in estrogen receptor-positive (ER+) breast cancer. In this study, we investigated alterations in lipid metabolism in ER + breast cancer cell lines with acquired resistance to common endocrine therapies and evaluated the efficacy of a clinically relevant fatty acid synthase (FASN) inhibitor.</p><p><strong>Methods: </strong>ER + breast cancer cell lines resistant to Tamoxifen (TamR), Fulvestrant (FulvR), and long-term estrogen withdrawal (EWD) were derived. Global gene expression and lipidomic profiling were performed to compare parental and endocrine resistant cells. Lipid storage was assessed using Oil Red O (ORO) staining. The FASN inhibitor TVB-2640 was tested for its impact on lipid storage and cell growth. ¹³C₂-acetate tracing was used to evaluate FASN activity and the efficacy of TVB-2640.</p><p><strong>Results: </strong>Endocrine resistant cells showed significant enrichment in lipid metabolism pathways and distinct lipidomic profiles, characterized by elevated triglyceride levels and enhanced cytoplasmic lipid droplets. ¹³C₂-acetate tracing revealed increased FASN activity in endocrine resistant cells, which was effectively reduced by TVB-2640. While TVB-2640 reduced lipid storage in most but not all cell lines, this did not correlate with decreased cell growth. Polyunsaturated fatty acids (PUFAs) containing 6 or more double bonds were elevated in endocrine resistant cells and remained unaffected or increased with TVB-2640.</p><p><strong>Conclusion: </strong>Endocrine resistant breast cancer cells undergo a metabolic shift toward increased triglyceride storage and PUFAs with high degrees of desaturation. While TVB-2640 reduced lipid storage in most conditions, it had limited effects on the growth of endocrine resistant breast cancer cells. Targeting specific lipid metabolic dependencies, particularly pathways that produce PUFAs, represents a potential therapeutic strategy in endocrine resistant breast cancer.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"32"},"PeriodicalIF":7.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11889759/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preclinical evaluation of ⁶⁴Cu-labeled cetuximab in immuno-PET for detecting sentinel lymph node metastasis in epidermal growth factor receptor-positive breast cancer.","authors":"Takeshi Usui, Tomohiro Miyake, Tadashi Watabe, Hiroki Kato, Yukie Yoshii, Sadahiro Naka, Kaori Abe, Misato Masuyama, Nanae Masunaga, Tetsuhiro Yoshinami, Masami Tsukabe, Yoshiaki Sota, Tomonori Tanei, Masafumi Shimoda, Kenzo Shimazu","doi":"10.1186/s13058-025-01972-4","DOIUrl":"10.1186/s13058-025-01972-4","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Despite advances in breast cancer imaging, reliable detection of sentinel lymph node (SLN) metastasis remains challenging. This study aimed to determine the ability of immuno-positron emission tomography (PET) using &lt;sup&gt;64&lt;/sup&gt;Cu-labeled cetuximab to detect SLN metastasis in a model of epidermal growth factor receptor (EGFR)-positive breast cancer.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The SLN metastasis model was established using the EGFR-strongly-expressing MDA-MB-468 breast cancer cell line. In this xenograft model, [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab was administered intravenously (5.8 ± 0.9 MBq; n = 12) or both intradermally and subdermally into the parapapillary region of the tumor-containing mammary gland (4.3 ± 0.4 MBq; n = 11), after which PET was performed. &lt;sup&gt;18&lt;/sup&gt;F-FDG PET was also performed intravenously (9.1 ± 1.4 MBq; n = 4) or intradermally/subdermally (5.4 ± 2.2 MBq; n = 3) in the same cohort before [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab PET. PET/computed tomography was performed 60 min after administration of &lt;sup&gt;18&lt;/sup&gt;F-FDG and 24 h after administration of [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab. Delayed PET/CT scans were conducted 48 h after administration for all mice in the intradermally/subdermally administered [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab group and for four of the 12 mice in the intravenously administered [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab group. SLNs were identified using blue dye, and PET and pathological evaluations of the resected SLN were performed to confirm metastases.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;After intravenous administration of [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab (n = 12), accumulation was detected in the primary tumor in all mice and in the axilla of eight mice (67%, SUV&lt;sub&gt;max&lt;/sub&gt; 1.24 ± 0.51), all of which were found to have SLNs with histologically confirmed metastasis. The sensitivity, specificity, accuracy, and negative and positive predictive values for PET with intravenously administered [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab were 89%, 100%, 92%, 75%, and 100%, respectively. In contrast, all mice with intradermal/subdermal administration (n = 11) showed high accumulation in both the primary tumor and axillary lymph nodes (SUV&lt;sub&gt;max&lt;/sub&gt; 4.28 ± 1.19), with six mice (55%, SUV&lt;sub&gt;max&lt;/sub&gt; 5.01 ± 1.12) having histologically confirmed metastasis. The sensitivity, specificity, accuracy, and positive predictive values for PET with intradermally/subdermally administered [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab were 100%, 0%, 55% and 55%, respectively. SLN metastasis was not detectable by intravenous or intradermal/subdermal &lt;sup&gt;18&lt;/sup&gt;F-FDG PET.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;PET with intravenously administered [&lt;sup&gt;64&lt;/sup&gt;Cu]Cu-PCTA-cetuximab demonstrated high precision for diagnosis of SLN metastasis in a xenograft model of EGFR-positive human breast cancer. Although further evaluation is necessary, intradermal/subdermal administration could be a useful therapeutic ap","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"33"},"PeriodicalIF":7.4,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11889786/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143587829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the key mechanisms of FOLR2+ macrophage-mediated antitumor immunity in breast cancer using integrated single-cell RNA sequencing and bulk RNA sequencing.","authors":"Sixuan Wu, Baohong Jiang, Zhimin Li, Yuanbin Tang, Lunqi Luo, Wenjie Feng, Yiling Jiang, Yeru Tan, Yuehua Li","doi":"10.1186/s13058-025-01980-4","DOIUrl":"10.1186/s13058-025-01980-4","url":null,"abstract":"<p><p>Breast cancer (BRCA) is a common malignant tumor, and its immune microenvironment plays a crucial role in disease progression. In this research, we utilized single-cell RNA sequencing and bulk RNA sequencing technologies, combined with in vivo and in vitro experiments, to thoroughly investigate the immunological functions and mechanisms of FOLR2+ macrophages in BRCA. Our findings demonstrate a significant enhancement in the interaction between FOLR2+ macrophages and CD8⁺ T cells within the tumor tissues of BRCA patients. FOLR2 is closely associated with T cell infiltration in the tumor microenvironment of BRCA patients, particularly with CD8⁺ T cells. By secreting CXCL9 and engaging with CXCR3, FOLR2+ macrophages can activate the functionality of CD8⁺ T cells, thereby promoting cancer cell apoptosis. Further animal experiments confirm that FOLR2+ macrophages activate CD8⁺ T cells through the CXCL9-CXCR3 axis, exhibiting an antitumor immunity effect in BRCA. FOLR2+ macrophages play a crucial role in antitumor immunity in BRCA through the CXCL9-CXCR3 axis.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"31"},"PeriodicalIF":7.4,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11881325/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143568633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients based on ultrasound longitudinal temporal depth network fusion model.","authors":"Xiaodan Feng, Yan Shi, Meng Wu, Guanghe Cui, Yao Du, Jie Yang, Yuyuan Xu, Wenjuan Wang, Feifei Liu","doi":"10.1186/s13058-025-01971-5","DOIUrl":"10.1186/s13058-025-01971-5","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The aim of this study was to develop and validate a deep learning radiomics (DLR) model based on longitudinal ultrasound data and clinical features to predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Between January 2018 and June 2023, 312 patients with histologically confirmed breast cancer were enrolled and randomly assigned to a training cohort (n = 219) and a test cohort (n = 93) in a 7:3 ratio. Next, pre-NAC and post-treatment 2-cycle ultrasound images were collected, and radiomics and deep learning features were extracted from NAC pre-treatment (Pre), post-treatment 2 cycle (Post), and Delta (pre-NAC-NAC 2 cycle) images. In the training cohort, to filter features, the intraclass correlation coefficient test, the Boruta algorithm, and the least absolute shrinkage and selection operator (LASSO) logistic regression were used. Single-modality models (Pre, Post, and Delta) were constructed based on five machine-learning classifiers. Finally, based on the classifier with the optimal predictive performance, the DLR model was constructed by combining Pre, Post, and Delta ultrasound features and was subsequently combined with clinical features to develop a combined model (Integrated). The discriminative power, predictive performance, and clinical utility of the models were further evaluated in the test cohort. Furthermore, patients were assigned into three subgroups, including the HR+/HER2-, HER2+, and TNBC subgroups, according to molecular typing to validate the predictability of the model across the different subgroups.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;After feature screening, 16, 13, and 10 features were selected to construct the Pre model, Post model, and Delta model based on the five machine learning classifiers, respectively. The three single-modality models based on the XGBoost classifier displayed optimal predictive performance. Meanwhile, the DLR model (AUC of 0.827) was superior to the single-modality model (Pre, Post, and Delta AUCs of 0.726, 0.776, and 0.710, respectively) in terms of prediction performance. Moreover, multivariate logistic regression analysis identified Her-2 status and histological grade as independent risk factors for NAC response in breast cancer. In both the training and test cohorts, the Integrated model, which included Pre, Post, and Delta ultrasound features and clinical features, exhibited the highest predictive ability, with AUC values of 0.924 and 0.875, respectively. Likewise, the Integrated model displayed the highest predictive performance across the different subgroups.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;The Integrated model, which incorporated pre-NAC treatment and early treatment ultrasound data and clinical features, accurately predicted pCR after NAC in breast cancer patients and provided valuable insights for personalized treatment strategies, allowing for timely adjustment of chemoth","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"30"},"PeriodicalIF":7.4,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11869678/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: CXCR4 promotes tumor stemness maintenance and CDK4/6 inhibitors resistance in ER-positive breast cancer.","authors":"Qianfeng Shi, Wang Yang, Yiye Ouyang, Yujie Liu, Zijie Cai","doi":"10.1186/s13058-025-01977-z","DOIUrl":"10.1186/s13058-025-01977-z","url":null,"abstract":"","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"28"},"PeriodicalIF":7.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11853288/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143505001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding breast cancer imaging trends: the role of AI and radiomics through bibliometric insights.","authors":"Xinyu Wu, Yufei Xia, Xinjing Lou, Keling Huang, Linyu Wu, Chen Gao","doi":"10.1186/s13058-025-01983-1","DOIUrl":"10.1186/s13058-025-01983-1","url":null,"abstract":"<p><strong>Background: </strong>Radiomics and AI have been widely used in breast cancer imaging, but a comprehensive systematic analysis is lacking. Therefore, this study aims to conduct a bibliometrics analysis in this field to discuss its research status and frontier hotspots and provide a reference for subsequent research.</p><p><strong>Methods: </strong>Publications related to AI, radiomics, and breast cancer imaging were searched in the Web of Science Core Collection. CiteSpace plotted the relevant co-occurrence network according to authors and keywords. VOSviewer and Pajek were used to draw relevant co-occurrence maps according to country and institution. In addition, R was used to conduct bibliometric analysis of relevant authors, countries/regions, journals, keywords, and annual publications and citations based on the collected information.</p><p><strong>Results: </strong>A total of 2,701 Web of Science Core Collection publications were retrieved, including 2,486 articles (92.04%) and 215 reviews (7.96%). The number of publications increased rapidly after 2018. The United States of America (n = 17,762) leads in citations, while China (n = 902) leads in the number of publications. Sun Yat-sen University (n = 75) had the largest number of publications. Bin Zheng (n = 28) was the most published author. Nico Karssemeijer (n = 72.1429) was the author with the highest average citations. \"Frontiers in Oncology\" was the journal with the most publications, and \"Radiology\" had the highest IF. The keywords with the most frequent occurrence were \"breast cancer\", \"deep learning\", and \"classification\". The topic trends in recent years were \"explainable AI\", \"neoadjuvant chemotherapy\", and \"lymphovascular invasion\".</p><p><strong>Conclusion: </strong>The application of radiomics and AI in breast cancer imaging has received extensive attention. Future research hotspots may mainly focus on the progress of explainable AI in the technical field and the prediction of lymphovascular invasion and neoadjuvant chemotherapy efficacy in clinical application.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"29"},"PeriodicalIF":7.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11863798/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143505004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genomic alterations are associated with response to aromatase inhibitor therapy for ER-positive postmenopausal ductal carcinoma in situ: (CALGB 40903, Alliance).","authors":"Jeffrey R Marks, Dadong Zhang, Timothy Hardman, Yunn-Yi Chen, Allison Hall, Lunden Simpson, Tina Hieken, Isabelle Bedrosian, Elissa Price, Jeff Sheng, Yanwan Dai, Marissa Lee, Alexander B Sibley, Kouros Owzar, E Shelley Hwang","doi":"10.1186/s13058-025-01963-5","DOIUrl":"10.1186/s13058-025-01963-5","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Purpose: &lt;/strong&gt;CALGB 40903 (Alliance) was a phase II single arm multicenter trial conducted in postmenopausal patients diagnosed with estrogen-receptor (ER) positive breast ductal carcinoma in situ (DCIS) without invasion. Patients were treated with the aromatase inhibitor (AI) letrozole for 6 months prior to surgery with change in magnetic resonance imaging (MRI) enhancement volume compared to baseline as the primary endpoint. In the current study, we performed sequence analysis of pre- and post-treatment specimens to determine gene expression and DNA copy number parameters associated with treatment and response.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Experimental design: &lt;/strong&gt;Paraffin sections from pretreatment biopsies and post-treatment surgical specimens were evaluated for presence of DCIS. Proliferation based on KI67 staining was quantified by a study pathologist. Macrodissection of the DCIS components from thin sections was the source of RNA and DNA. Whole-transcriptome RNA and shallow whole-genome DNA sequencing were performed. PAM50 analysis to assign intrinsic subtypes with associated probability of class membership was performed. Differential gene expression comparing responders versus non-responders and pre- versus post-treatment specimens was performed using a two-tiered approach based on candidate genes and a whole genome survey with appropriate multiple testing corrections.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Based on availability of specimens and presence of DCIS component, 29 patients (from the 70 who completed the treatment trial) were included in the final data set, including five who had a pathologic complete response (pCR). Response to treatment was qualified categorically based on a threshold of 10% KI67 in the post-treatment surgical specimen or pCR. Based on this criterion, six of the 29 DCIS were considered non-responders (&gt; 10% KI67) and five subjects with pCR were assigned to the responder group. No standard clinical variables were associated with response. On the basis of gene expression analysis, 19 of the pre-treatment samples were classified as luminal A, all of which were classified as responders. PAM50 classification of the other ten pre-treatment samples included luminal B, HER2, basal, and normal-like, six of which were non-responders. PAM50 class membership shifted from baseline to post-treatment in eight cases, most often from luminal A to normal-like (five cases). Selected genes associated with estrogen receptor levels in invasive breast cancer were higher in AI responsive tumors. AI treatment resulted in reductions in estrogen and proliferation related genes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Letrozole treatment produced an effective growth response, particularly in DCIS initially classified as luminal A. Study inclusion criteria of DCIS with at least 1% ER positive cells resulted in the inclusion of other subtypes that failed to respond. Treatment also induced both minor and major changes in intrinsic subtype based ","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"26"},"PeriodicalIF":7.4,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11843815/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143469220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interaction between APOE Ɛ4 status, chemotherapy and endocrine therapy on cognitive functioning among breast cancer survivors: the CANTO-Cog longitudinal study.","authors":"Mylène Duivon, François Christy, Emilie Thomas, Justine Lequesne, Hélène Castel, Catherine Gaudin, Dominique Delmas, Sandrine Boyault, Olivier Rigal, Chayma Bousrih, Christelle Lévy, Florence Lerebours, Antonio Di Meglio, Patricia A Ganz, Kathleen Van Dyk, Ines Vaz Luis, Marie Lange, Florence Joly","doi":"10.1186/s13058-025-01974-2","DOIUrl":"10.1186/s13058-025-01974-2","url":null,"abstract":"<p><strong>Background: </strong>Apolipoprotein Ɛ4 genotype (APOE4) has been associated with cancer-related cognitive impairment, but its interaction with treatments remains unclear. This longitudinal study aims to evaluate the association between APOE4 and cognitive impairment in women with breast cancer (BC) undergoing chemotherapy (CT) or endocrine therapy (ET).</p><p><strong>Findings: </strong>Patients with stage I-III breast cancer completed cognitive tests at diagnosis (before surgery), then at year-1, year-2, and year-4 post-diagnosis. APOE4 status (APOE4+ [carriers] vs. APOE4- [non-carriers]) was genotyped from blood sample. Cognitive outcomes included episodic memory, working memory, attention, processing speed, and executive functions. Patients were defined as having overall cognitive impairment if ≥ 2 domains were impaired. We fitted logistic and linear mixed models to assess associations of APOE4 status with cognitive impairment over time and interactions of APOE4 with CT and ET. Among 334 patients, 64 (19%) were APOE4+, 117 (35%) patients were treated with CT, 41 (12%) with ET, and 162 (49%) with CT+ET. There were no significant association between overall cognitive impairment and APOE4, nor interactions with CT or ET. At year-4, APOE4+ patients treated with ET had lower attention performance than APOE4- patients not treated with ET, and APOE4+ patients not treated with ET had lower episodic memory performance than APOE4- patients not treated with ET.</p><p><strong>Conclusions: </strong>This study suggests APOE4 genotyping is ineffective for detecting cognitive impairment in BC. New genotypes should be identified to predict cognitive decline in BC.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"27 1","pages":"25"},"PeriodicalIF":7.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11841345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}