Breast Cancer Research最新文献

{"title":"Contrast-enhanced ultrasound to predict malignant upgrading of atypical ductal hyperplasia.","authors":"Jun Kang Li, Zhi Ying Jin, Yong Jie Xu, Nai Qin Fu, Ying Jiang, Shi Yu Li, Rui Lan Niu, Gang Liu, Zhi Li Wang","doi":"10.1186/s13058-024-01772-2","DOIUrl":"10.1186/s13058-024-01772-2","url":null,"abstract":"<p><strong>Background: </strong>A malignancy might be found at surgery in cases of atypical ductal hyperplasia (ADH) diagnosed via US-guided core needle biopsy (CNB). The objective of this study was to investigate the diagnostic performance of contrast-enhanced ultrasound (CEUS) in predicting ADH diagnosed by US-guided CNB that was upgraded to malignancy after surgery.</p><p><strong>Methods: </strong>In this retrospective study, 110 CNB-diagnosed ADH lesions in 109 consecutive women who underwent US, CEUS, and surgery between June 2018 and June 2023 were included. CEUS was incorporated into US BI-RADS and yielded a CEUS-adjusted BI-RADS. The diagnostic performance of US BI-RADS and CEUS-adjusted BI-RADS for ADH were analyzed and compared.</p><p><strong>Results: </strong>The mean age of the 109 women was 49.7 years ± 11.6 (SD). The upgrade rate of ADH at CNB was 48.2% (53 of 110). The sensitivity, specificity, positive predictive value, and negative predictive value of CEUS for identification of malignant upgrading were 96.2%, 66.7%,72.9%, and 95.0%, respectively, based on BI-RADS category 4B threshold. The two false-negative cases were low-grade ductal carcinoma in situ. Compared with the US, CEUS-adjusted BI-RADS had better specificity for lesions smaller than 2 cm (76.7% vs. 96.7%, P = 0.031). After CEUS, 16 (10 malignant and 6 nonmalignant) of the 45 original US BI-RADS category 4A lesions were up-classified to BI-RADS 4B, and 3 (1 malignant and 2 nonmalignant) of the 41 original US BI-RADS category 4B lesions were down-classified to BI-RADS 4A.</p><p><strong>Conclusions: </strong>CEUS is helpful in predicting malignant upgrading of ADH, especially for lesions smaller than 2 cm and those classified as BI-RADS 4A and 4B on ultrasound.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10863177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139724618","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":"Prognostic impact of HER2 biomarker levels in trastuzumab-treated early HER2-positive breast cancer.","authors":"Caroline Rönnlund, Emmanouil G Sifakis, Caroline Schagerholm, Qiao Yang, Emelie Karlsson, Xinsong Chen, Theodoros Foukakis, Jodi Weidler, Michael Bates, Irma Fredriksson, Stephanie Robertson, Johan Hartman","doi":"10.1186/s13058-024-01779-9","DOIUrl":"10.1186/s13058-024-01779-9","url":null,"abstract":"<p><strong>Background: </strong>Overexpression of human epidermal growth factor receptor 2 (HER2) caused by HER2 gene amplification is a driver in breast cancer tumorigenesis. We aimed to investigate the prognostic significance of manual scoring and digital image analysis (DIA) algorithm assessment of HER2 copy numbers and HER2/CEP17 ratios, along with ERBB2 mRNA levels among early-stage HER2-positive breast cancer patients treated with trastuzumab.</p><p><strong>Methods: </strong>This retrospective study comprised 371 early HER2-positive breast cancer patients treated with adjuvant trastuzumab, with HER2 re-testing performed on whole tumor sections. Digitized tumor tissue slides were manually scored and assessed with uPath HER2 Dual ISH image analysis, breast algorithm. Targeted ERBB2 mRNA levels were assessed by the Xpert® Breast Cancer STRAT4 Assay. HER2 copy number and HER2/CEP17 ratio from in situ hybridization assessment, along with ERBB2 mRNA levels, were explored in relation to recurrence-free survival (RFS).</p><p><strong>Results: </strong>The analysis showed that patients with tumors with the highest and lowest manually counted HER2 copy number levels had worse RFS than those with intermediate levels (HR = 2.7, CI 1.4-5.3, p = 0.003 and HR = 2.1, CI 1.1-3.9, p = 0.03, respectively). A similar trend was observed for HER2/CEP17 ratio, and the DIA algorithm confirmed the results. Moreover, patients with tumors with the highest and the lowest values of ERBB2 mRNA had a significantly worse prognosis (HR = 2.7, CI 1.4-5.1, p = 0.003 and HR = 2.8, CI 1.4-5.5, p = 0.004, respectively) compared to those with intermediate levels.</p><p><strong>Conclusions: </strong>Our findings suggest that the association between any of the three HER2 biomarkers and RFS was nonlinear. Patients with tumors with the highest levels of HER2 gene amplification or ERBB2 mRNA were associated with a worse prognosis than those with intermediate levels, which is of importance to investigate in future clinical trials studying HER2-targeted therapy.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10848443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139698652","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":"Are better AI algorithms for breast cancer detection also better at predicting risk? A paired case-control study.","authors":"Ruggiero Santeramo, Celeste Damiani, Jiefei Wei, Giovanni Montana, Adam R Brentnall","doi":"10.1186/s13058-024-01775-z","DOIUrl":"10.1186/s13058-024-01775-z","url":null,"abstract":"<p><strong>Background: </strong>There is increasing evidence that artificial intelligence (AI) breast cancer risk evaluation tools using digital mammograms are highly informative for 1-6 years following a negative screening examination. We hypothesized that algorithms that have previously been shown to work well for cancer detection will also work well for risk assessment and that performance of algorithms for detection and risk assessment is correlated.</p><p><strong>Methods: </strong>To evaluate our hypothesis, we designed a case-control study using paired mammograms at diagnosis and at the previous screening visit. The study included n = 3386 women from the OPTIMAM registry, that includes mammograms from women diagnosed with breast cancer in the English breast screening program 2010-2019. Cases were diagnosed with invasive breast cancer or ductal carcinoma in situ at screening and were selected if they had a mammogram available at the screening examination that led to detection, and a paired mammogram at their previous screening visit 3y prior to detection when no cancer was detected. Controls without cancer were matched 1:1 to cases based on age (year), screening site, and mammography machine type. Risk assessment was conducted using a deep-learning model designed for breast cancer risk assessment (Mirai), and three open-source deep-learning algorithms designed for breast cancer detection. Discrimination was assessed using a matched area under the curve (AUC) statistic.</p><p><strong>Results: </strong>Overall performance using the paired mammograms followed the same order by algorithm for risk assessment (AUC range 0.59-0.67) and detection (AUC 0.81-0.89), with Mirai performing best for both. There was also a correlation in performance for risk and detection within algorithms by cancer size, with much greater accuracy for large cancers (30 mm+, detection AUC: 0.88-0.92; risk AUC: 0.64-0.74) than smaller cancers (0 to < 10 mm, detection AUC: 0.73-0.86, risk AUC: 0.54-0.64). Mirai was relatively strong for risk assessment of smaller cancers (0 to < 10 mm, risk, Mirai AUC: 0.64 (95% CI 0.57 to 0.70); other algorithms AUC 0.54-0.56).</p><p><strong>Conclusions: </strong>Improvements in risk assessment could stem from enhancing cancer detection capabilities of smaller cancers. Other state-of-the-art AI detection algorithms with high performance for smaller cancers might achieve relatively high performance for risk assessment.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10848404/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139703804","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":"Low-dose acetylsalicylic acid reduces local inflammation and tissue perfusion in dense breast tissue in postmenopausal women.","authors":"Peter Lundberg, Annelie Abrahamsson, Johan Kihlberg, Jens Tellman, Ieva Tomkeviciene, Anette Karlsson, Maria Kristoffersen Wiberg, Marcel Warntjes, Charlotta Dabrosin","doi":"10.1186/s13058-024-01780-2","DOIUrl":"10.1186/s13058-024-01780-2","url":null,"abstract":"<p><strong>Purpose: </strong>One major risk factor for breast cancer is high mammographic density. It has been estimated that dense breast tissue contributes to ~ 30% of all breast cancer. Prevention targeting dense breast tissue has the potential to improve breast cancer mortality and morbidity. Anti-estrogens, which may be associated with severe side-effects, can be used for prevention of breast cancer in women with high risk of the disease per se. However, no preventive therapy targeting dense breasts is currently available. Inflammation is a hallmark of cancer. Although the biological mechanisms involved in the increased risk of cancer in dense breasts is not yet fully understood, high mammographic density has been associated with increased inflammation. We investigated whether low-dose acetylsalicylic acid (ASA) affects local breast tissue inflammation and/or structural and dynamic changes in dense breasts.</p><p><strong>Methods: </strong>Postmenopausal women with mammographic dense breasts on their regular mammography screen were identified. A total of 53 women were randomized to receive ASA 160 mg/day or no treatment for 6 months. Magnetic resonance imaging (MRI) was performed before and after 6 months for a sophisticated and continuous measure breast density by calculating lean tissue fraction (LTF). Additionally, dynamic quantifications including tissue perfusion were performed. Microdialysis for sampling of proteins in vivo from breasts and abdominal subcutaneous fat, as a measure of systemic effects, before and after 6 months were performed. A panel of 92 inflammatory proteins were quantified in the microdialysates using proximity extension assay.</p><p><strong>Results: </strong>After correction for false discovery rate, 20 of the 92 inflammatory proteins were significantly decreased in breast tissue after ASA treatment, whereas no systemic effects were detected. In the no-treatment group, protein levels were unaffected. Breast density, measured by LTF on MRI, were unaffected in both groups. ASA significantly decreased the perfusion rate. The perfusion rate correlated positively with local breast tissue concentration of VEGF.</p><p><strong>Conclusions: </strong>ASA may shape the local breast tissue microenvironment into an anti-tumorigenic state. Trials investigating the effects of low-dose ASA and risk of primary breast cancer among postmenopausal women with maintained high mammographic density are warranted. Trial registration EudraCT: 2017-000317-22.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10845760/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139693353","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":"The novel phosphatase NUDT5 is a critical regulator of triple-negative breast cancer growth.","authors":"Jing Qian, Yanxia Ma, William M Tahaney, Cassandra L Moyer, Amanda Lanier, Jamal Hill, Darian Coleman, Negar Koupaei, Susan G Hilsenbeck, Michelle I Savage, Brent D G Page, Abhijit Mazumdar, Powel H Brown","doi":"10.1186/s13058-024-01778-w","DOIUrl":"10.1186/s13058-024-01778-w","url":null,"abstract":"<p><strong>Background: </strong>The most aggressive form of breast cancer is triple-negative breast cancer (TNBC), which lacks expression of the estrogen receptor (ER) and progesterone receptor (PR), and does not have overexpression of the human epidermal growth factor receptor 2 (HER2). Treatment options for women with TNBC tumors are limited, unlike those with ER-positive tumors that can be treated with hormone therapy, or those with HER2-positive tumors that can be treated with anti-HER2 therapy. Therefore, we have sought to identify novel targeted therapies for TNBC. In this study, we investigated the potential of a novel phosphatase, NUDT5, as a potential therapeutic target for TNBC.</p><p><strong>Methods: </strong>The mRNA expression levels of NUDT5 in breast cancers were investigated using TCGA and METABRIC (Curtis) datasets. NUDT5 ablation was achieved through siRNA targeting and NUDT5 inhibition with the small molecule inhibitor TH5427. Xenograft TNBC animal models were employed to assess the effect of NUDT5 inhibition on in vivo tumor growth. Proliferation, death, and DNA replication assays were conducted to investigate the cellular biological effects of NUDT5 loss or inhibition. The accumulation of 8-oxo-guanine (8-oxoG) and the induction of γH₂AX after NUDT5 loss was determined by immunofluorescence staining. The impact of NUDT5 loss on replication fork was assessed by measuring DNA fiber length.</p><p><strong>Results: </strong>In this study, we demonstrated the significant role of an overexpressed phosphatase, NUDT5, in regulating oxidative DNA damage in TNBCs. Our findings indicate that loss of NUDT5 results in suppressed growth of TNBC both in vitro and in vivo. This growth inhibition is not attributed to cell death, but rather to the suppression of proliferation. The loss or inhibition of NUDT5 led to an increase in the oxidative DNA lesion 8-oxoG, and triggered the DNA damage response in the nucleus. The interference with DNA replication ultimately inhibited proliferation.</p><p><strong>Conclusions: </strong>NUDT5 plays a crucial role in preventing oxidative DNA damage in TNBC cells. The loss or inhibition of NUDT5 significantly suppresses the growth of TNBCs. These biological and mechanistic studies provide the groundwork for future research and the potential development of NUDT5 inhibitors as a promising therapeutic approach for TNBC patients.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10845800/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139693354","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":"ADAMTS18 deficiency associates extracellular matrix dysfunction with a higher risk of HER2-positive mammary tumorigenesis and metastasis.","authors":"Jiahui Nie, Suying Dang, Rui Zhu, Tiantian Lu, Wei Zhang","doi":"10.1186/s13058-024-01771-3","DOIUrl":"10.1186/s13058-024-01771-3","url":null,"abstract":"<p><strong>Background: </strong>Human epidermal growth factor receptor 2 (HER2)-positive breast cancer accounts for about 20% of all breast cancer cases and is correlated with a high relapse rate and poor prognosis. ADAMTS18 is proposed as an important functional tumor suppressor gene involved in multiple malignancies, including breast cancer. It functions as an extracellular matrix (ECM) modifier. However, it remains unclear whether ADAMTS18 affects mammary tumorigenesis and malignant progression through its essential ECM regulatory function.</p><p><strong>Methods: </strong>To elucidate the role of ADAMTS18 in HER2-positive mammary tumorigenesis and metastasis in vivo, we compared the incidence of mammary tumor and metastasis between Adamts18-knockout (MMTV)-Her2/ErbB2/Neu⁺ transgenic mice (i.e., Her2^t/w/Adamts18^-/-) and Adamts18-wildtype (MMTV)-Her2/ErbB2/Neu⁺ transgenic mice (i.e., Her2^t/w/Adamts18^+/+). The underlying mechanisms by which ADAMTS18 regulates HER2-positive tumorigenesis and metastasis were investigated by pathology, cell culture, Western blot and immunochemistry.</p><p><strong>Results: </strong>Adamts18 mRNA is mainly expressed in myoepithelial cells of the mammary duct. ADAMTS18 deficiency leads to a significantly increased incidence of mammary tumors and metastasis, as well as mammary hyperplasia in mice, over 30 months of observation. The proliferation, migration and invasion capacities of primary Her2^t/w/Adamts18^-/- mammary tumor cells are significantly higher than those of primary Her2^t/w/Adamts18^+/+ mammary tumor cells in vitro. At 30 months of age, the expression levels of laminin (LNα5), fibronectin (FN) and type I collagen (ColI) in the mammary glands of Her2^t/w/Adamts18^-/- mice are significantly increased, and the activities of integrin-mediated PI3K/AKT, ERK and JNK signaling pathways are enhanced.</p><p><strong>Conclusions: </strong>ADAMTS18 deficiency leads to alterations in mammary ECM components (e.g., LNα5, FN, ColI), which are associated with a higher risk of HER2-positive mammary tumorigenesis and metastasis.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10826190/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139575700","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 and prognostic validation of a three-level NHG-like deep learning-based model for histological grading of breast cancer.","authors":"Abhinav Sharma, Philippe Weitz, Yinxi Wang, Bojing Liu, Johan Vallon-Christersson, Johan Hartman, Mattias Rantalainen","doi":"10.1186/s13058-024-01770-4","DOIUrl":"10.1186/s13058-024-01770-4","url":null,"abstract":"<p><strong>Background: </strong>Histological grade is a well-known prognostic factor that is routinely assessed in breast tumours. However, manual assessment of Nottingham Histological Grade (NHG) has high inter-assessor and inter-laboratory variability, causing uncertainty in grade assignments. To address this challenge, we developed and validated a three-level NHG-like deep learning-based histological grade model (predGrade). The primary performance evaluation focuses on prognostic performance.</p><p><strong>Methods: </strong>This observational study is based on two patient cohorts (SöS-BC-4, N = 2421 (training and internal test); SCAN-B-Lund, N = 1262 (test)) that include routine histological whole-slide images (WSIs) together with patient outcomes. A deep convolutional neural network (CNN) model with an attention mechanism was optimised for the classification of the three-level histological grading (NHG) from haematoxylin and eosin-stained WSIs. The prognostic performance was evaluated by time-to-event analysis of recurrence-free survival and compared to clinical NHG grade assignments in the internal test set as well as in the fully independent external test cohort.</p><p><strong>Results: </strong>We observed effect sizes (hazard ratio) for grade 3 versus 1, for the conventional NHG method (HR = 2.60 (1.18-5.70 95%CI, p-value = 0.017)) and the deep learning model (HR = 2.27, 95%CI 1.07-4.82, p-value = 0.033) on the internal test set after adjusting for established clinicopathological risk factors. In the external test set, the unadjusted HR for clinical NHG 2 versus 1 was estimated to be 2.59 (p-value = 0.004) and clinical NHG 3 versus 1 was estimated to be 3.58 (p-value < 0.001). For predGrade, the unadjusted HR for predGrade 2 versus 1 HR = 2.52 (p-value = 0.030), and 4.07 (p-value = 0.001) for preGrade 3 versus 1 was observed in the independent external test set. In multivariable analysis, HR estimates for neither clinical NHG nor predGrade were found to be significant (p-value > 0.05). We tested for differences in HR estimates between NHG and predGrade in the independent test set and found no significant difference between the two classification models (p-value > 0.05), confirming similar prognostic performance between conventional NHG and predGrade.</p><p><strong>Conclusion: </strong>Routine histopathology assessment of NHG has a high degree of inter-assessor variability, motivating the development of model-based decision support to improve reproducibility in histological grading. We found that the proposed model (predGrade) provides a similar prognostic performance as clinical NHG. The results indicate that deep CNN-based models can be applied for breast cancer histological grading.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10823657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139575743","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 machine learning-based radiomics signature for estimating breast cancer TME phenotypes and predicting anti-PD-1/PD-L1 immunotherapy response.","authors":"Xiaorui Han, Yuan Guo, Huifen Ye, Zhihong Chen, Qingru Hu, Xinhua Wei, Zaiyi Liu, Changhong Liang","doi":"10.1186/s13058-024-01776-y","DOIUrl":"10.1186/s13058-024-01776-y","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Backgrounds: &lt;/strong&gt;Since breast cancer patients respond diversely to immunotherapy, there is an urgent need to explore novel biomarkers to precisely predict clinical responses and enhance therapeutic efficacy. The purpose of our present research was to construct and independently validate a biomarker of tumor microenvironment (TME) phenotypes via a machine learning-based radiomics way. The interrelationship between the biomarker, TME phenotypes and recipients' clinical response was also revealed.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In this retrospective multi-cohort investigation, five separate cohorts of breast cancer patients were recruited to measure breast cancer TME phenotypes via a radiomics signature, which was constructed and validated by integrating RNA-seq data with DCE-MRI images for predicting immunotherapy response. Initially, we constructed TME phenotypes using RNA-seq of 1089 breast cancer patients in the TCGA database. Then, parallel DCE-MRI images and RNA-seq of 94 breast cancer patients obtained from TCIA were applied to develop a radiomics-based TME phenotypes signature using random forest in machine learning. The repeatability of the radiomics signature was then validated in an internal validation set. Two additional independent external validation sets were analyzed to reassess this signature. The Immune phenotype cohort (n = 158) was divided based on CD8 cell infiltration into immune-inflamed and immune-desert phenotypes; these data were utilized to examine the relationship between the immune phenotypes and this signature. Finally, we utilized an Immunotherapy-treated cohort with 77 cases who received anti-PD-1/PD-L1 treatment to evaluate the predictive efficiency of this signature in terms of clinical outcomes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The TME phenotypes of breast cancer were separated into two heterogeneous clusters: Cluster A, an \"immune-inflamed\" cluster, containing substantial innate and adaptive immune cell infiltration, and Cluster B, an \"immune-desert\" cluster, with modest TME cell infiltration. We constructed a radiomics signature for the TME phenotypes ([AUC] = 0.855; 95% CI 0.777-0.932; p &lt; 0.05) and verified it in an internal validation set (0.844; 0.606-1; p &lt; 0.05). In the known immune phenotypes cohort, the signature can identify either immune-inflamed or immune-desert tumor (0.814; 0.717-0.911; p &lt; 0.05). In the Immunotherapy-treated cohort, patients with objective response had higher baseline radiomics scores than those with stable or progressing disease (p &lt; 0.05); moreover, the radiomics signature achieved an AUC of 0.784 (0.643-0.926; p &lt; 0.05) for predicting immunotherapy response.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our imaging biomarker, a practicable radiomics signature, is beneficial for predicting the TME phenotypes and clinical response in anti-PD-1/PD-L1-treated breast cancer patients. It is particularly effective in identifying the \"immune-desert\" phenotype and may aid in its tra","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10823720/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139575847","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":"A genome-wide association study of contralateral breast cancer in the Women's Environmental Cancer and Radiation Epidemiology Study.","authors":"Xiaohui Sun, Anne S Reiner, Anh Phong Tran, Gordon P Watt, Jung Hun Oh, Lene Mellemkjær, Charles F Lynch, Julia A Knight, Esther M John, Kathleen E Malone, Xiaolin Liang, Meghan Woods, Andriy Derkach, Patrick Concannon, Jonine L Bernstein, Xiang Shu","doi":"10.1186/s13058-024-01765-1","DOIUrl":"10.1186/s13058-024-01765-1","url":null,"abstract":"<p><strong>Background: </strong>Contralateral breast cancer (CBC) is the most common second primary cancer diagnosed in breast cancer survivors, yet the understanding of the genetic susceptibility of CBC, particularly with respect to common variants, remains incomplete. This study aimed to investigate the genetic basis of CBC to better understand this malignancy.</p><p><strong>Findings: </strong>We performed a genome-wide association analysis in the Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study of women with first breast cancer diagnosed at age < 55 years including 1161 with CBC who served as cases and 1668 with unilateral breast cancer (UBC) who served as controls. We observed two loci (rs59657211, 9q32, SLC31A2/FAM225A and rs3815096, 6p22.1, TRIM31) with suggestive genome-wide significant associations (P < 1 × 10^-6). We also found an increased risk of CBC associated with a breast cancer-specific polygenic risk score (PRS) comprised of 239 known breast cancer susceptibility single nucleotide polymorphisms (SNPs) (rate ratio per 1-SD change: 1.25; 95% confidence interval 1.14-1.36, P < 0.0001). The protective effect of chemotherapy on CBC risk was statistically significant only among patients with an elevated PRS (P_{heterogeneity} = 0.04). The AUC that included the PRS and known breast cancer risk factors was significantly elevated.</p><p><strong>Conclusions: </strong>The present GWAS identified two previously unreported loci with suggestive genome-wide significance. We also confirm that an elevated risk of CBC is associated with a comprehensive breast cancer susceptibility PRS that is independent of known breast cancer risk factors. These findings advance our understanding of genetic risk factors involved in CBC etiology.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10807183/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139541814","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":"c-MET-positive circulating tumor cells and cell-free DNA as independent prognostic factors in hormone receptor-positive/HER2-negative metastatic breast cancer.","authors":"Jieun Park, Eun Sol Chang, Ji-Yeon Kim, Chaithanya Chelakkot, Minjung Sung, Ji-Young Song, Kyungsoo Jung, Ji Hye Lee, Jun Young Choi, Na Young Kim, Hyegyeong Lee, Mi-Ran Kang, Mi Jeong Kwon, Young Kee Shin, Yeon Hee Park, Yoon-La Choi","doi":"10.1186/s13058-024-01768-y","DOIUrl":"10.1186/s13058-024-01768-y","url":null,"abstract":"<p><strong>Background: </strong>Endocrine therapy resistance in hormone receptor-positive/HER2-negative (HR+/HER2-) breast cancer (BC) is a significant clinical challenge that poses several unmet needs in the management of the disease. This study aimed to investigate the prognostic value of c-MET-positive circulating tumor cells (cMET+ CTCs), ESR1/PIK3CA mutations, and cell-free DNA (cfDNA) concentrations in patients with hormone receptor-positive (HR+) metastatic breast cancer (mBC).</p><p><strong>Methods: </strong>Ninety-seven patients with HR+ mBC were prospectively enrolled during standard treatment at Samsung Medical Center. CTCs were isolated from blood using GenoCTC^® and EpCAM or c-MET CTC isolation kits. PIK3CA and ESR1 hotspot mutations were analyzed using droplet digital PCR. CfDNA concentrations were calculated using internal control copies from the ESR1 mutation test. Immunocytochemistry was performed to compare c-MET overexpression between primary and metastatic sites.</p><p><strong>Results: </strong>The proportion of c-MET overexpression was significantly higher in metastatic sites than in primary sites (p = 0.00002). Survival analysis showed that c-MET+ CTC, cfDNA concentration, and ESR1 mutations were significantly associated with poor prognosis (p = 0.0026, 0.0021, and 0.0064, respectively) in HR+/HER2- mBC. By contrast, EpCAM-positive CTC (EpCAM+ CTC) and PIK3CA mutations were not associated with progression-free survival (PFS) in HR+/HER2- mBC. Multivariate analyses revealed that c-MET+ CTCs and cfDNA concentration were independent predictors of PFS in HR+/HER2- mBC.</p><p><strong>Conclusions: </strong>Monitoring c-MET+ CTC, rather than assessing c-MET expression in the primary BC site, could provide valuable information for predicting disease progression, as c-MET expression can change during treatment. The c-MET+ CTC count and cfDNA concentration could provide complementary information on disease progression in HR+ /HER2- mBC, highlighting the importance of integrated liquid biopsy.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":null,"pages":null},"PeriodicalIF":7.4,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10797795/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139492577","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}