Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-03-19
S. Majumder, K. G. Gray, N. Shinde, R. Mawalkar, A. Zhang, M. Basree, K. Ormiston, X. Zhang, R. Ganju, G. Sizemore, B. Ramaswamy, D. G. Stover
Background: Epidemiological studies link lack of or short-term breast feeding to increased risk of breast cancer (BC), including triple negative breast cancer (TNBC). However, few models allow interrogation of the underlying biology. To decipher this link, we developed a model of short-term breastfeeding (BF) leading to abrupt involution (AI) versus long-term BF leading to gradual involution (GI) in mice. In our prior work, we showed that AI led to significant increase in estrogen signaling and precancerous changes (hyperplasia, squamous metaplasia) in mammary glands (MG) (Basree, et al Br Can Res 2019). Further, AI glands are characterized by a notable increase in alveolar progenitor (AP) population, the cells of origin of TNBC. In this study, we addressed the hypothesis that the anti-estrogen tamoxifen (TAM) could revert the adverse effects of abrupt involution/lack of breast feeding by deep interrogation of shifts in cellular phenotypes through CyTOF single cell proteomics. Methods: FVB/N female mice (∼8 week old) were bred and allowed to nurse six pups/dam at partum. All pups were removed on postpartum (PP) day 7 to induce AI. On PP day 8, 5mg-60day sustained release tamoxifen pellet or placebo pellet (PLAC) was implanted in the subscapular region of the AI mice. MGs were harvested on PP day 28 and 120 from three groups: 1) TAM-treated AI; 2) PLAC-treated AI; 3) age matched nulliparous mice. FFPE sections were used for histology and immunohistochemistry. Immune cell composition and epithelial subpopulations from PP day 28 and day 120 MGs were evaluated by FACS and subjected to CyTOF using an established 40-antibody murine mammary targeted proteome panel (Gray, et al Cell Rep 2024). The Ingest algorithm was used to integrate and analyze mass cytometry datasets. Results: Overall, TAM treatment for 60 days completely abrogated the hyperplastic changes induced by AI in MGs, including reduction in proliferation index, collagen deposition, macrophages, and alveolar AP cells in the AI glands. As seen in our prior work, at day 120, abrupt involution-placebo glands (relative to nulliparous MGs) demonstrated marked enrichment of AP (1.5-fold) and basal (BA 1.6-fold) cells at the expense of hormone sensing (HS) cells. Analyses of MGs from the abrupt involution-tamoxifen group at day 120 revealed a significant increase (3-fold) in hormone sensing (HS) epithelial cells and an attendant decrease in AP cells compared to placebo. Further, abrupt involution-placebo glands show upregulation of AP markers (CD61, TSPAN8, SSEA1, CD14) and basal markers (CD54, CD47, CD104, CD49F) in the AP cells and higher expression of BA markers and reduced expression of HS markers in the HS cells. TAM treatment reversed these aberrant changes in abrupt involution-placebo glands in fact inducing a shift in HS cells to an involution-like state. Integration of the AI-PLAC/TAM data with lineage trajectory of these three cell types across the gestation-lactation-involution cycle rev
背景：流行病学研究将缺乏或短期母乳喂养与乳腺癌（BC）风险增加联系起来，包括三阴性乳腺癌（TNBC）。然而，很少有模型允许询问潜在的生物学。为了解释这种联系，我们在小鼠中建立了一个短期母乳喂养（BF）导致突然退化（AI）与长期母乳喂养（GI）导致逐渐退化（GI）的模型。在我们之前的工作中，我们发现AI导致乳腺（MG）中雌激素信号和癌前病变（增生，鳞状皮化生）的显著增加（Basree等Br Can Res 2019）。此外，AI腺体的特征是肺泡祖细胞（AP）数量显著增加，这是TNBC的起源细胞。在这项研究中，我们提出了一种假设，即抗雌激素的他莫昔芬（TAM）可以通过CyTOF单细胞蛋白质组学深入研究细胞表型的变化，从而逆转突然复发/缺乏母乳喂养的不良影响。方法：饲养FVB/N雌性小鼠（~ 8周龄），在分娩时每只喂养6只。所有幼犬于产后第7天取出，以诱导人工智能。PP第8天，在AI小鼠肩胛下区植入5mg-60d缓释他莫昔芬微丸或安慰剂微丸（placc）。在PP第28天和第120天，从3组中收获mg: 1)经tam处理的AI；2)经place处理的AI；3)年龄匹配的未生育小鼠。FFPE切片用于组织学和免疫组织化学。通过FACS评估PP第28天和第120 mg的免疫细胞组成和上皮亚群，并使用已建立的40抗体小鼠乳腺靶向蛋白质组小组进行CyTOF （Gray等cell Rep 2024）。Ingest算法用于整合和分析细胞计数数据集。结果：总体而言，TAM治疗60天完全消除了AI诱导的mg细胞增生性变化，包括AI腺体的增殖指数、胶原沉积、巨噬细胞和肺泡AP细胞的减少。正如我们之前的工作所见，在第120天，突然消退的安慰剂腺体（相对于未分娩的mg）显示出AP（1.5倍）和基础（BA 1.6倍）细胞的显著富集，而激素感知（HS）细胞的富集则为损失。他莫昔芬突然消退组在第120天的mg分析显示，与安慰剂相比，激素感应（HS）上皮细胞显著增加（3倍），AP细胞随之减少。此外，突然消退的安慰剂腺体显示AP细胞中AP标记物（CD61、TSPAN8、SSEA1、CD14）和基础标记物（CD54、CD47、CD104、CD49F）上调，BA标记物在HS细胞中表达升高，HS标记物表达降低。TAM治疗逆转了突然复合体的这些异常变化——安慰剂腺体实际上诱导了HS细胞向复合体样状态的转变。ai - placc /TAM数据与这三种细胞类型在妊娠-哺乳-复合体周期中的谱系轨迹的整合显示，AI-AP细胞在第120天表现出复合体后和妊娠状态。在第120天，TAM导致排卵期后样AP细胞比例增加4.1倍，异常妊娠样细胞比例减少10.2倍。TAM处理后，BA细胞有类似变化，HS细胞无。结论：进一步了解短/不母乳喂养的生物学影响是至关重要的，这项工作表明TAM治疗对小鼠模型中ai诱导的癌前病变有显著的保护作用。TAM恢复AI后的长期谱系平衡，改变AP分化为典型的退化后状态，而不是AI诱导的增生。TAM的矫正效果为不能BF的女性短期TAM治疗降低BC风险提供了理论依据。引文格式：S. Majumder， K. G. Gray， N. Shinde， R. Mawalkar， A. Zhang， M. Basree， K. Ormiston， X. Zhang， R. Ganju， G. Sizemore， B. Ramaswamy， D. G. Stover。单细胞蛋白质组学表型揭示了他莫昔芬治疗后乳腺上皮突变引起的改变的缓解[摘要]。摘自：《2025年圣安东尼奥乳腺癌研讨会论文集》；2025年12月9-12日；费城（PA）： AACR；临床癌症杂志2026；32（4增刊）：nr PS3-03-19。
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Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-07-21
J. A. Mouabbi, A. S. Raghavendra, S. Pasyar, B. L. Roland, R. A. Mukhtar, M. Giancarlo, M. D. Wright, A. K. Bisen, A. N. Iheme, C. H. Barcenas, V. Valero, A. Nasrazadani, B. Lim, D. L. Ramirez, A. Hassan, H. M. Kuerer, T. Adesoye, P. R. Paula, F. Meric-Bernstam, S. H. Giordano, J. K. Litton, R. M. Layman
Background: ILC is a distinct subtype of breast cancer characterized by unique histopathological features and a higher risk of late distant recurrence (DR) compared to invasive ductal carcinoma (IDC). Accurate risk stratification is critical for optimizing adjuvant management. While CTS5 is a widely used and readily available tool for predicting late DR (after 5 years) in HR+/HER2- breast cancer, it has not been evaluated and validated in ILC. We report the first validation of CTS5 in ILC and compare its performance to the recently developed ILC-specific prognostic model (MDA-iLobulaRX). Methods: We retrospectively analyzed data from patients with stage I-III HR+/HER2- ILC treated at MD Anderson Cancer Center, between 1980-2020, using a prospectively curated database. Two models were evaluated for predicting late DR: (1) MDA-iLobulaRX, incorporating age, ER%, tumor grade, presence of LCIS, ILC histology, lymph node status, tumor size, and adjuvant endocrine therapy (tamoxifen or aromatase inhibitor [AI]); and (2) CTS5, including age, tumor size and grade, and nodal status. Patients with less than five years of follow-up were excluded to ensure adequate time at risk for late DR. Additionally, patients who did not receive endocrine therapy were excluded. Model performance was assessed using: (1) Akaike Information Criterion (AIC) to compare model fit; (2) Harrell’s concordance index (c-index) to assess discrimination; and (3) Receiver operating characteristic (ROC) curves with area under the curve (AUC), based on a binary classification of recurrence (yes/no) after 5 years for clinical interpretability. Results: The cohort included 2,253 women with a median follow up time of 10.3 years with a range of 5 to 40 years. The median age was 57 years, median tumor size was 23 mm, 52% were node-positive and 67% were postmenopausal. Classical ILC was the predominant subtype (90%) compared to 10% non-classical subtypes. Endocrine therapy included tamoxifen (43%), non-steroidal AIs (55%) and steroidal AI (2%). Model 1 (MDA-iLobulaRX) had a slightly better fit (AIC: 9115 vs 9157) while both models demonstrated comparable discrimination (c-index 0.698 for model 1 vs 0.704 for model 2) and AUC (0.74 for model 1 and 0.75 for model 2). Conclusion: CTS5 is a valid, readily accessible tool for predicting late DR in HR+/HER2- ILC, with performance comparable to ILC-specific models. While CTS5 does not guide treatment or surveillance decisions, it may support risk stratification discussions in clinical practice and offers a pragmatic tool for estimating late recurrence risk in this population. Citation Format: J. A. Mouabbi, A. S. Raghavendra, S. Pasyar, B. L. Roland, R. A. Mukhtar, M. Giancarlo, M. D. Wright, A. K. Bisen, A. N. Iheme, C. H. Barcenas, V. Valero, A. Nasrazadani, B. Lim, D. L. Ramirez, A. Hassan, H. M. Kuerer, T. Adesoye, P. R. Paula, F. Meric-Bernstam, S. H. Giordano, J. K. Litton, R. M. Layman. Validation of the CTS5 as a predictor of late distant rec
背景：ILC是一种独特的乳腺癌亚型，具有独特的组织病理学特征，与浸润性导管癌（IDC）相比，其晚期远处复发（DR）的风险更高。准确的风险分层是优化辅助治疗的关键。虽然CTS5是一种广泛使用且易于获得的工具，用于预测HR+/HER2-乳腺癌的晚期DR（5年后），但尚未在ILC中进行评估和验证。我们报告了CTS5在ILC中的首次验证，并将其性能与最近开发的ILC特异性预后模型（MDA-iLobulaRX）进行了比较。方法：我们回顾性分析1980-2020年间在MD安德森癌症中心接受治疗的I-III期HR+/HER2- ILC患者的数据，使用前瞻性整理的数据库。评估两种预测晚期DR的模型：(1)mda - ilobullarx，包括年龄、ER%、肿瘤分级、LCIS的存在、ILC组织学、淋巴结状态、肿瘤大小和辅助内分泌治疗（他莫昔芬或芳香酶抑制剂[AI]）；(2) CTS5，包括年龄、肿瘤大小、分级和淋巴结状态。随访时间少于5年的患者被排除在外，以确保有足够的时间存在晚期dr的风险。此外，未接受内分泌治疗的患者也被排除在外。采用(1)赤池信息准则（Akaike Information Criterion， AIC）比较模型拟合；(2)采用Harrell’s concordance index （c-index）评价歧视；(3)受试者工作特征（ROC）曲线，曲线下面积（AUC），基于5年后复发的二元分类（是/否），以获得临床可解释性。结果：该队列包括2253名女性，中位随访时间为10.3年，范围为5至40年。中位年龄为57岁，中位肿瘤大小为23 mm， 52%为淋巴结阳性，67%为绝经后。经典ILC是主要亚型（90%），而非经典亚型占10%。内分泌治疗包括他莫昔芬（43%）、非甾体AI（55%）和甾体AI（2%）。模型1 （MDA-iLobulaRX）的拟合稍微好一些（AIC: 9115 vs 9157），而两个模型都表现出可比性（模型1的c指数为0.698 vs模型2的0.704）和AUC（模型1为0.74，模型2为0.75）。结论：CTS5是预测HR+/HER2- ILC晚期DR的有效且易于获得的工具，其性能与ILC特异性模型相当。虽然CTS5不能指导治疗或监测决策，但它可以支持临床实践中的风险分层讨论，并为估计该人群的晚期复发风险提供实用工具。引文格式：J. A. Mouabbi， A. S. Raghavendra， S. Pasyar， B. L. Roland， R. A. Mukhtar， M. Giancarlo， M. D. Wright， A. K. Bisen， A. N. Iheme， C. H. Barcenas， V. Valero， A. Nasrazadani， B. Lim， D. L. Ramirez， A. Hassan， H. M. Kuerer， T. Adesoye， P. R. Paula， F. Meric-Bernstam， S. H. Giordano， J. K. Litton， R. M. Layman。验证CTS5作为HR+ her2阴性侵袭性小叶癌（ILC）晚期远处复发（DR）的预测因子[摘要]。摘自：《2025年圣安东尼奥乳腺癌研讨会论文集》；2025年12月9-12日；费城（PA）： AACR；临床癌症杂志2026；32（4增刊）：nr PS3-07-21。
{"title":"Abstract PS3-07-21: Validation of the CTS5 as a predictor of late distant recurrence (DR) for HR+ HER2-negative Invasive Lobular Carcinoma (ILC)","authors":"J. A. Mouabbi, A. S. Raghavendra, S. Pasyar, B. L. Roland, R. A. Mukhtar, M. Giancarlo, M. D. Wright, A. K. Bisen, A. N. Iheme, C. H. Barcenas, V. Valero, A. Nasrazadani, B. Lim, D. L. Ramirez, A. Hassan, H. M. Kuerer, T. Adesoye, P. R. Paula, F. Meric-Bernstam, S. H. Giordano, J. K. Litton, R. M. Layman","doi":"10.1158/1557-3265.sabcs25-ps3-07-21","DOIUrl":"https://doi.org/10.1158/1557-3265.sabcs25-ps3-07-21","url":null,"abstract":"Background: ILC is a distinct subtype of breast cancer characterized by unique histopathological features and a higher risk of late distant recurrence (DR) compared to invasive ductal carcinoma (IDC). Accurate risk stratification is critical for optimizing adjuvant management. While CTS5 is a widely used and readily available tool for predicting late DR (after 5 years) in HR+/HER2- breast cancer, it has not been evaluated and validated in ILC. We report the first validation of CTS5 in ILC and compare its performance to the recently developed ILC-specific prognostic model (MDA-iLobulaRX). Methods: We retrospectively analyzed data from patients with stage I-III HR+/HER2- ILC treated at MD Anderson Cancer Center, between 1980-2020, using a prospectively curated database. Two models were evaluated for predicting late DR: (1) MDA-iLobulaRX, incorporating age, ER%, tumor grade, presence of LCIS, ILC histology, lymph node status, tumor size, and adjuvant endocrine therapy (tamoxifen or aromatase inhibitor [AI]); and (2) CTS5, including age, tumor size and grade, and nodal status. Patients with less than five years of follow-up were excluded to ensure adequate time at risk for late DR. Additionally, patients who did not receive endocrine therapy were excluded. Model performance was assessed using: (1) Akaike Information Criterion (AIC) to compare model fit; (2) Harrell’s concordance index (c-index) to assess discrimination; and (3) Receiver operating characteristic (ROC) curves with area under the curve (AUC), based on a binary classification of recurrence (yes/no) after 5 years for clinical interpretability. Results: The cohort included 2,253 women with a median follow up time of 10.3 years with a range of 5 to 40 years. The median age was 57 years, median tumor size was 23 mm, 52% were node-positive and 67% were postmenopausal. Classical ILC was the predominant subtype (90%) compared to 10% non-classical subtypes. Endocrine therapy included tamoxifen (43%), non-steroidal AIs (55%) and steroidal AI (2%). Model 1 (MDA-iLobulaRX) had a slightly better fit (AIC: 9115 vs 9157) while both models demonstrated comparable discrimination (c-index 0.698 for model 1 vs 0.704 for model 2) and AUC (0.74 for model 1 and 0.75 for model 2). Conclusion: CTS5 is a valid, readily accessible tool for predicting late DR in HR+/HER2- ILC, with performance comparable to ILC-specific models. While CTS5 does not guide treatment or surveillance decisions, it may support risk stratification discussions in clinical practice and offers a pragmatic tool for estimating late recurrence risk in this population. Citation Format: J. A. Mouabbi, A. S. Raghavendra, S. Pasyar, B. L. Roland, R. A. Mukhtar, M. Giancarlo, M. D. Wright, A. K. Bisen, A. N. Iheme, C. H. Barcenas, V. Valero, A. Nasrazadani, B. Lim, D. L. Ramirez, A. Hassan, H. M. Kuerer, T. Adesoye, P. R. Paula, F. Meric-Bernstam, S. H. Giordano, J. K. Litton, R. M. Layman. Validation of the CTS5 as a predictor of late distant rec","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":"820 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146230794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps1-04-07
L. Yang, T. Tayyab, R. Kokts-Porietis, Q. Wang, J. McNeil, M. Matthews, L. Dickau, J. Vallance, M. McNeely, N. Culos-Reed, K. Kopciuk, K. Courneya, C. Friedenreich
Background: Sleep problems are common among breast cancer survivors and are associated with poor quality of life. Yet, few studies have accounted for depression. This study examines whether depressive symptoms attenuate the association between sleep and quality of life in newly diagnosed breast cancer survivors. Methods: Women with newly diagnosed early-stage breast cancer were recruited between 2012-2019 in Alberta, Canada, and completed the Pittsburgh Sleep Quality Index (PSQI) to assess global sleep quality. Quality of life was measured using the Short Form Survey (SF-36 version-2) to assess physical and mental well-being. Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-9). Multivariable linear regressions were used to estimate the association of sleep measures with physical and mental well-being. Depressive symptoms were evaluated as a potential confounder and effect modifier. Results: Among 1454 breast cancer survivors with available data, 43% reported poor global sleep quality and 10.5% reported clinically meaningful depressive symptoms. Poor sleep quality was associated with lower physical (β=-3.0, 95%CI: -3.8 to -2.3) and mental well-being (β=-5.7, 95%CI: -6.7 to -4.7). These associations were attenuated to (β=-2.3, 95%CI: -3.1 to 1.5) and (β=-1.2, 95%CI: -2.1 to -0.3) after further adjusting for depression symptoms. Stratified analyses showed a slightly stronger association in women with non-minimal symptoms, though this association was not clinically meaningful. Conclusion: The association between sleep and quality of life was substantially attenuated after accounting for depressive symptoms. Longitudinal data are needed to clarify the temporal relationship and determine whether sleep can serve as an early indicator of emerging depression. Next steps: Based on these findings, we are currently investigating depressive symptoms as a mediator for the association between sleep health and quality of life, using longitudinal data collected from time of diagnosis to five-years follow-up. We will be able to complete the analyses and report findings from the mediation analyses at the time of conference. Citation Format: L. Yang, T. Tayyab, R. Kokts-Porietis, Q. Wang, J. McNeil, M. Matthews, L. Dickau, J. Vallance, M. McNeely, N. Culos-Reed, K. Kopciuk, K. Courneya, C. Friedenreich. Sleep, depressive symptoms and quality of life among women with newly diagnosed breast cancer: findings from the AMBER cohort study [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl): nr PS1-04-07.
背景：睡眠问题在乳腺癌幸存者中很常见，并且与生活质量差有关。然而，很少有研究能解释抑郁症。本研究探讨抑郁症状是否会减弱新诊断乳腺癌幸存者的睡眠和生活质量之间的联系。方法：招募2012-2019年加拿大艾伯塔省新诊断的早期乳腺癌女性，完成匹兹堡睡眠质量指数（PSQI），评估全球睡眠质量。生活质量采用短表调查（SF-36 version-2）来评估身心健康。使用患者健康问卷（PHQ-9）测量抑郁症状。使用多变量线性回归来估计睡眠测量与身心健康的关系。抑郁症状被评估为潜在的混杂因素和效果调节因素。结果：在1454名乳腺癌幸存者中，43%的人报告整体睡眠质量差，10.5%的人报告有临床意义的抑郁症状。睡眠质量差与较低的身体（β=-3.0, 95%CI: -3.8至-2.3）和精神健康（β=-5.7, 95%CI: -6.7至-4.7）有关。在进一步调整抑郁症状后，这些关联减弱为（β=-2.3, 95%CI: -3.1至1.5）和（β=-1.2, 95%CI: -2.1至-0.3）。分层分析显示，在有非轻微症状的妇女中，这种关联略强，尽管这种关联没有临床意义。结论：在考虑抑郁症状后，睡眠与生活质量之间的关联明显减弱。需要纵向数据来澄清时间关系，并确定睡眠是否可以作为出现抑郁症的早期指标。下一步：基于这些发现，我们目前正在研究抑郁症状作为睡眠健康和生活质量之间关系的中介，使用从诊断到5年随访期间收集的纵向数据。我们将能够在会议召开时完成分析并报告调解分析的结果。引用格式：L. Yang， T. Tayyab， R. Kokts-Porietis， Q. Wang， J. McNeil， M. Matthews， L. Dickau， J. valance， M. McNeely， N. cullos - reed， K. Kopciuk， K. Courneya， C. Friedenreich。新诊断乳腺癌女性的睡眠、抑郁症状和生活质量：来自AMBER队列研究的发现[摘要]。摘自：《2025年圣安东尼奥乳腺癌研讨会论文集》；2025年12月9-12日；费城（PA）： AACR；临床癌症杂志2026；32（4增刊）：nr PS1-04-07。
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Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps1-02-30
M. C. Carvalho, I. d. Oliveira, B. C. Figueroa, T. C. Lima, R. P. Souza, S. M. Sanches, V. C. Lima, M. G. Cesca
Background: Endocrine therapy (ET) is the cornerstone of hormone-receptor positive (HR+) breast cancer treatment. However, it is potentially associated with several adverse events, which can impact patients' quality of life (QoL). Depicting different spheres of QoL affected by ET is essential to improve supportive care strategies. This study aimed to evaluate QoL among breast cancer patients on mid/long-term ET, exploring its diverse domains. Methods: Single-center, observational cohort study. Female patients with HR+ breast cancer undergoing systemic ET for at least 6 months were included. Participants fulfilled a unique online questionnaire, including the validated European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) + Breast Cancer-specific Module (BR23). QoL was assessed across several functioning and symptom domains. Each score domain was transformed into a score ranging 0 to 100, according to EORTC guidelines. Higher scores indicated a better quality of life for functioning domains/general health status, and a greater symptom burden. Descriptive statistics were used to characterize the domains (mean scores) and the population characteristics. Correlations between the patient’s characteristics and the scores were evaluated with Student’s T test. Results: 200 patients, with a median age of 44 years-old (range: 27-92), were included. The majority had at least higher education (87%), were self-declared as white (69%; brown/black: 24.5%), heterosexual (95.5%), were premenopausal (74.5%), overweight (68%) and had children (69.5%). 14% were under ET for metastatic disease (86% adjuvant ET), 94.5% had primary breast cancer surgery (50.5% conservative) and 49% breast reconstructive surgery. Chemotherapy was used in 62.5% and the ongoing ETs were: SERMs (22.5%), aromatase inhibitors (70.5%) and SERDs (7%); 58.5% associated with ovarian function suppression. Global health status (71.4) and physical and role functioning (76.9 and 71.8) were relatively well preserved in this cohort. Financial difficulties (25.7), and symptoms related to surgery, such as breast (23.3) and arm (31.9) pain were also not impactful. However, patients had significant impairment in sexual functioning (27.4), future perspective (27.5), body image (56.6) and in emotional (51.3) and cognitive (52.9) functioning. Insomnia (52.0) and fatigue (40.1) were the most impactful symptoms. Premenopausal status was correlated to worse body image (52.9 vs 67.1; p=0.014) and emotional functioning (49.4 vs 56.9; p=0.006). There was a trend for worse body image in patients who underwent breast reconstructive surgery (46.9 vs 66.5; p=0.055), worse sexual functioning for aromatase inhibitors versus SERMs (25.9 vs 32.6; p=0.059) and worse global health status in premenopausal women (70.1 vs 75.2; p=0.058). Conclusion: This study highlights the impact of ET and breast cancer diagnosis in the sexual, cognitive and emotional functioning, as
背景：内分泌治疗（ET）是激素受体阳性（HR+）乳腺癌治疗的基石。然而，它可能与一些不良事件相关，这些不良事件可能影响患者的生活质量（QoL）。描述受ET影响的生活质量的不同领域对于改善支持性护理策略至关重要。本研究旨在评估乳腺癌患者中长期ET治疗的生活质量，探讨其在不同领域的影响。方法：单中心、观察队列研究。女性HR+乳腺癌患者接受全身ET治疗至少6个月。参与者完成了一份独特的在线问卷，包括经过验证的欧洲癌症研究和治疗组织生活质量问卷核心30 (EORTC QLQ-C30) +乳腺癌特异性模块（BR23）。生活质量通过几个功能和症状领域进行评估。根据EORTC的指导方针，每个分数域被转换成0到100分的分数。得分越高，表明功能域/一般健康状况的生活质量越好，症状负担越重。描述性统计用于描述域（平均得分）和总体特征。采用学生T检验评估患者特征与得分之间的相关性。结果：纳入200例患者，中位年龄44岁（范围27-92岁）。大多数人至少受过高等教育（87%），自称为白人（69%；棕色/黑色：24.5%），异性恋（95.5%），绝经前（74.5%），超重（68%），有孩子（69.5%）。14%的患者因转移性疾病接受ET治疗（86%为辅助ET治疗），94.5%的患者接受了原发性乳腺癌手术（50.5%为保守手术），49%的患者接受了乳房重建手术。化疗占62.5%，正在进行的et为：serm(22.5%)，芳香化酶抑制剂（70.5%）和serd (7%)；58.5%与卵巢功能抑制有关。在该队列中，总体健康状况（71.4）和身体和角色功能（76.9和71.8）相对保存较好。经济困难（25.7）和与手术相关的症状，如乳房（23.3）和手臂（31.9）疼痛也没有影响。然而，患者在性功能（27.4）、未来展望（27.5）、身体形象（56.6）、情感（51.3）和认知（52.9）功能方面存在显著障碍。失眠（52.0）和疲劳（40.1）是影响最大的症状。绝经前状态与较差的身体形象（52.9比67.1,p=0.014）和情绪功能（49.4比56.9,p=0.006）相关。接受乳房重建手术的患者有更差的身体形象的趋势（46.9 vs 66.5; p=0.055），芳香酶抑制剂与SERMs的性功能更差（25.9 vs 32.6; p=0.059），绝经前妇女的整体健康状况更差（70.1 vs 75.2; p=0.058）。结论：本研究突出了ET与乳腺癌诊断在HR+乳腺癌患者的性功能、认知功能、情绪功能、未来观和身体形象等方面的影响。绝经前妇女似乎受影响最大。这些发现强调了常规生活质量评估在临床实践中的重要性，以及改善乳腺癌患者生存护理的迫切需要。引用格式：M. C. Carvalho， I. d. Oliveira， B. C. Figueroa， T. C. Lima， R. P. Souza， S. M. Sanches， V. C. Lima， M. G. Cesca乳腺癌生存之外：接受内分泌治疗的女性生活质量方面[摘要]。摘自：《2025年圣安东尼奥乳腺癌研讨会论文集》；2025年12月9-12日；费城（PA）： AACR；临床癌症杂志2026；32（4增刊）：nr PS1-02-30。
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Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-02-26
S. J. Friedman, D. B. Rose, J. D. Rogers, K. N. Owens, P. L. Welcsh, M. Dean, R. H. Pugh Yi
Background: Only 7% of adult cancer patients enroll in treatment-related clinical trials, with even lower rates for genetics and quality-of-life studies.1 People with germline mutations are interested in participating in hereditary cancer research, but few are being offered the opportunity by their healthcare team. In a FORCE survey, only 14% of people at high risk for breast cancer reported hearing about clinical research opportunities from their healthcare providers, while 75% expressed interest.2 Dedicated efforts are needed to ensure that the hereditary cancer community is aware of clinical research opportunities. In 2020 FORCE surveys, 46% of oncology nurses and 55% of certified genetic counselors identified research jargon and health literacy as major barriers to clinical trial referral.3,4 FORCE and other members of the "Consistent Testing Terminology Working Group" found large gaps in patient understanding of commonly-used cancer research terms.5 In focus groups, FORCE asked women with or at high risk for hereditary breast cancer to review a cancer study listing on ClinicalTrials.gov. All agreed that the study description was difficult to understand due to complexity and jargon and that Clinicaltrials.gov required a lot of practice to use.6 Methods: In 2014, FORCE built a tool to help hereditary cancer patients find, understand, and enroll in relevant studies. The tool consists of a custom database with plain-language summaries of research studies relevant for people with inherited cancer risk. Users can search for studies listed in the FORCE database as well as on ClinicalTrials.gov by study type, cancer type, gene or biomarker, study location and key word. FORCE evaluated the tool through focus groups and a user survey. Focus group participants were asked to compare the ClinicalTrials.gov listing with the FORCE plain-language version of the same study. Results: Focus group participants all agreed that the FORCE listing was clearer and easier to understand than ClinicalTrials.gov.6 Key user survey results are included in Table 1. Of the respondents, 79% found the tool easy to use, 84% would use it again, 79% would refer others to the tool. Of respondents, 36% enrolled, and 43% planned to enroll in a research study. Conclusions: People with inherited cancer risk are highly motivated to participate in clinical research—but most are never informed about studies by their healthcare team. ClinicalTrials.gov is not patient friendly, and hereditary cancer patients find the site difficult to use and understand. FORCE’s “Search and Enroll Tool” bridges this gap by offering accessible, accurate, and easy-to-understand listings of studies enrolling hereditary cancer patients. Results from our focus groups and survey demonstrate that the tool meets a critical need. Participants reported high user satisfaction, comprehension, and intention to utilize the tool to enroll in future studies. Citation Format: S. J. Friedman, D. B. Rose, J. D. Rogers, K. N
背景：只有7%的成年癌症患者参加了与治疗相关的临床试验，而遗传学和生活质量研究的比例更低有生殖系突变的人有兴趣参与遗传性癌症的研究，但很少有人被他们的医疗团队提供机会。在FORCE的一项调查中，只有14%的乳腺癌高危人群报告从他们的医疗保健提供者那里听到了临床研究机会，而75%的人表示感兴趣需要做出专门的努力，以确保遗传性癌症社区意识到临床研究的机会。在2020年FORCE调查中，46%的肿瘤护士和55%的注册遗传咨询师认为，研究术语和健康素养是临床试验转诊的主要障碍FORCE和“一致检测术语工作组”的其他成员发现，患者对常用癌症研究术语的理解存在很大差距在焦点小组中，FORCE要求患有或处于遗传性乳腺癌高风险的妇女回顾ClinicalTrials.gov网站上列出的一份癌症研究清单。所有人都同意，由于研究描述的复杂性和术语，很难理解，而且Clinicaltrials.gov网站需要大量的练习才能使用方法：FORCE于2014年构建了一个帮助遗传性癌症患者发现、了解和参与相关研究的工具。该工具由一个定制数据库组成，其中包含与遗传癌症风险相关的研究的简单语言摘要。用户可以根据研究类型、癌症类型、基因或生物标志物、研究地点和关键词搜索FORCE数据库和ClinicalTrials.gov上列出的研究。FORCE通过焦点小组和用户调查来评估该工具。焦点小组参与者被要求将ClinicalTrials.gov列表与FORCE的同一研究的简单语言版本进行比较。结果：焦点小组参与者一致认为FORCE列表比ClinicalTrials.gov.6更清晰易懂。关键用户调查结果见表1。在受访者中，79%的人认为该工具易于使用，84%的人会再次使用，79%的人会推荐其他人使用该工具。在受访者中，36%的人参加了研究，43%的人计划参加研究。结论：有遗传性癌症风险的人参与临床研究的积极性很高，但大多数人从来没有被他们的医疗团队告知过这些研究。ClinicalTrials.gov对患者并不友好，遗传性癌症患者发现该网站难以使用和理解。FORCE的“搜索和注册工具”通过提供可访问的，准确的，易于理解的研究纳入遗传性癌症患者的列表，弥合了这一差距。我们的焦点小组和调查结果表明，该工具满足了关键需求。参与者报告了较高的用户满意度、理解力和利用该工具参加未来研究的意愿。引用格式：S. J. Friedman， D. B. Rose， J. D. Rogers， K. N. Owens， P. L. welsh， M. Dean， R. H. Pugh Yi。使用一个简单的语言工具来克服遗传癌症风险人群参与研究的障碍[摘要]。摘自：《2025年圣安东尼奥乳腺癌研讨会论文集》；2025年12月9-12日；费城（PA）： AACR；临床癌症杂志2026；32（4增刊）：nr PS3-02-26。
{"title":"Abstract PS3-02-26: Using a plain language tool to overcome barriers to research participation by people with inherited cancer risk","authors":"S. J. Friedman, D. B. Rose, J. D. Rogers, K. N. Owens, P. L. Welcsh, M. Dean, R. H. Pugh Yi","doi":"10.1158/1557-3265.sabcs25-ps3-02-26","DOIUrl":"https://doi.org/10.1158/1557-3265.sabcs25-ps3-02-26","url":null,"abstract":"Background: Only 7% of adult cancer patients enroll in treatment-related clinical trials, with even lower rates for genetics and quality-of-life studies.1 People with germline mutations are interested in participating in hereditary cancer research, but few are being offered the opportunity by their healthcare team. In a FORCE survey, only 14% of people at high risk for breast cancer reported hearing about clinical research opportunities from their healthcare providers, while 75% expressed interest.2 Dedicated efforts are needed to ensure that the hereditary cancer community is aware of clinical research opportunities. In 2020 FORCE surveys, 46% of oncology nurses and 55% of certified genetic counselors identified research jargon and health literacy as major barriers to clinical trial referral.3,4 FORCE and other members of the \"Consistent Testing Terminology Working Group\" found large gaps in patient understanding of commonly-used cancer research terms.5 In focus groups, FORCE asked women with or at high risk for hereditary breast cancer to review a cancer study listing on ClinicalTrials.gov. All agreed that the study description was difficult to understand due to complexity and jargon and that Clinicaltrials.gov required a lot of practice to use.6 Methods: In 2014, FORCE built a tool to help hereditary cancer patients find, understand, and enroll in relevant studies. The tool consists of a custom database with plain-language summaries of research studies relevant for people with inherited cancer risk. Users can search for studies listed in the FORCE database as well as on ClinicalTrials.gov by study type, cancer type, gene or biomarker, study location and key word. FORCE evaluated the tool through focus groups and a user survey. Focus group participants were asked to compare the ClinicalTrials.gov listing with the FORCE plain-language version of the same study. Results: Focus group participants all agreed that the FORCE listing was clearer and easier to understand than ClinicalTrials.gov.6 Key user survey results are included in Table 1. Of the respondents, 79% found the tool easy to use, 84% would use it again, 79% would refer others to the tool. Of respondents, 36% enrolled, and 43% planned to enroll in a research study. Conclusions: People with inherited cancer risk are highly motivated to participate in clinical research—but most are never informed about studies by their healthcare team. ClinicalTrials.gov is not patient friendly, and hereditary cancer patients find the site difficult to use and understand. FORCE’s “Search and Enroll Tool” bridges this gap by offering accessible, accurate, and easy-to-understand listings of studies enrolling hereditary cancer patients. Results from our focus groups and survey demonstrate that the tool meets a critical need. Participants reported high user satisfaction, comprehension, and intention to utilize the tool to enroll in future studies. Citation Format: S. J. Friedman, D. B. Rose, J. D. Rogers, K. N","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":"15 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146230844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-03-27
M. Hou, F. Chen, C. Li, C. Chiang
Background Most breast cancer-related death is caused by recurrence and metastasis. Approximately 30% to 40% of patients will experience recurrence during their lifetime. Although the promising effect of endocrine therapy in ER-positive breast cancer, there are still about 30% of patients who ultimately die due to recurrence. In contrast to ER-negative, more than 50% of recurrences occur beyond five years (late recurrence, LR) in ER-positive breast cancer, which represents the proportion of early (ER, recurrence occur within five years) or even very early recurrence (VER, recurrence occur within one year in our preliminary results) are rare. In comparison with LR, the prognosis of ER and VER is poor and more aggressive; however, most studies focused on LR, including mechanisms, treatment, and genetic/immune profiles, few studies focused on ER, and even No studies concerned what we named VER. On the other hand, the introduction of a multigene prognostic test (MPT) can provide the dual role of prognostic and predictive to fulfill and strengthen the information in treatment decisions. However, there still existed some defects in the current MPT, including high cost, ethnic difference, and specificity for different time points of recurrence type. Thus, there is a huge gap in ER or even VER, and a critical unmet need to identify who is prone to recurrence for Asia breast cancer. Methods Fifty ER-positive patients with disease-free (DF, average follow-up 48 months), and 14 ER-positive patients with recurrence were enrolled in this study. Initially, three patients from 50 patients with DF and nine patients from 14 patients with recurrence were selected. In total of 12 patients (three patients for each group, including DF, VER, ER, and LR) were selected, and residual RNA samples from EndoPredict (EP) were analyzed by using the NanoString technique. Finally, raw data processing, normalization, and analysis were performed in the nSolver analysis software. Appropriate statistical analyses were performed using GraphPad Prism 9. Results In our preliminary results, we collected the data with EndoPredict and long-term follow-up records. By using the NanoString technique, we found some novel and unique target genes in different groups of recurrence. The expression of SERPINA1 was specific to disease-free (DF, average follow-up 48 months), CEACAM6 was overexpressed in LR group (average PFS 45 months), TGFB2 was only observed in VER group (average PFS 8 months), and AREG was co-existed in the group of ER (average PFS 23 months) and VER. Moreover, we compared the scores from a low-cost platform of immunohistochemical 4 (IHC4) and EndoPredict within 64 patients (average follow-up 48 months) and found a positive correlation between the IHC4 risk score and EPClin score in prognosis prediction. Conclusion To our knowledge, we provide the first preliminary results of novel gene targets at different time points of recurrence, especially for VER. We also found a positive
{"title":"Abstract PS3-03-27: Potential genetic targets of recurrence at different time points in Asia breast cancer with NanoString and multigene prognostic test","authors":"M. Hou, F. Chen, C. Li, C. Chiang","doi":"10.1158/1557-3265.sabcs25-ps3-03-27","DOIUrl":"https://doi.org/10.1158/1557-3265.sabcs25-ps3-03-27","url":null,"abstract":"Background Most breast cancer-related death is caused by recurrence and metastasis. Approximately 30% to 40% of patients will experience recurrence during their lifetime. Although the promising effect of endocrine therapy in ER-positive breast cancer, there are still about 30% of patients who ultimately die due to recurrence. In contrast to ER-negative, more than 50% of recurrences occur beyond five years (late recurrence, LR) in ER-positive breast cancer, which represents the proportion of early (ER, recurrence occur within five years) or even very early recurrence (VER, recurrence occur within one year in our preliminary results) are rare. In comparison with LR, the prognosis of ER and VER is poor and more aggressive; however, most studies focused on LR, including mechanisms, treatment, and genetic/immune profiles, few studies focused on ER, and even No studies concerned what we named VER. On the other hand, the introduction of a multigene prognostic test (MPT) can provide the dual role of prognostic and predictive to fulfill and strengthen the information in treatment decisions. However, there still existed some defects in the current MPT, including high cost, ethnic difference, and specificity for different time points of recurrence type. Thus, there is a huge gap in ER or even VER, and a critical unmet need to identify who is prone to recurrence for Asia breast cancer. Methods Fifty ER-positive patients with disease-free (DF, average follow-up 48 months), and 14 ER-positive patients with recurrence were enrolled in this study. Initially, three patients from 50 patients with DF and nine patients from 14 patients with recurrence were selected. In total of 12 patients (three patients for each group, including DF, VER, ER, and LR) were selected, and residual RNA samples from EndoPredict (EP) were analyzed by using the NanoString technique. Finally, raw data processing, normalization, and analysis were performed in the nSolver analysis software. Appropriate statistical analyses were performed using GraphPad Prism 9. Results In our preliminary results, we collected the data with EndoPredict and long-term follow-up records. By using the NanoString technique, we found some novel and unique target genes in different groups of recurrence. The expression of SERPINA1 was specific to disease-free (DF, average follow-up 48 months), CEACAM6 was overexpressed in LR group (average PFS 45 months), TGFB2 was only observed in VER group (average PFS 8 months), and AREG was co-existed in the group of ER (average PFS 23 months) and VER. Moreover, we compared the scores from a low-cost platform of immunohistochemical 4 (IHC4) and EndoPredict within 64 patients (average follow-up 48 months) and found a positive correlation between the IHC4 risk score and EPClin score in prognosis prediction. Conclusion To our knowledge, we provide the first preliminary results of novel gene targets at different time points of recurrence, especially for VER. We also found a positive ","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":"8 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146230880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-08-03
S. M. Doss, P. Raval
Background: The existence of estrogen receptor-negative (ER-), progesterone receptor-positive (PR+) breast cancer is rare, biologically confusing, and often attributed to technical artifact. Previous national analyses found no benefit from endocrine therapy (ET) in ER-/PR+ tumors, but more recent data suggest a survival benefit. To explore this inconsistency, we analyzed the association between receiving ET and survival in ER-/PR+ early-stage breast cancer treated with chemotherapy over time. Methods: We used the National Cancer Database (NCDB) to identify women age 40 and older diagnosed with stage I-III, ER-/PR+ breast cancer from 2010 to 2020 who received chemotherapy. Multivariate logistic regression evaluated factors associated with ET omission. Multivariate Cox regression analyzed the association between ET receipt and three-year overall survival (OS), stratified by diagnosis period (2010-2017 vs. 2018-2020) based on 2018 changes for prognostic staging and NCDB site-specific factors. Analyses adjusted for stage at diagnosis, age, comorbidity, HER2 status, race/ethnicity, grade, facility type, and zip code income. Robustness was tested using propensity score matching (PSM), landmark analysis, and HER2-negative subgroup analysis. Results: We identified 24,198 (0.94%) cases of ER-/PR+ breast cancer, of which 18,788 (77.6%) were stage I-III at diagnosis. Of these, 13,957 (74.3%) received chemotherapy, and 11,558 with complete covariate data were analyzed. Most cases were HER2-negative (60.2%) and high grade (75.1%). Stage distribution was 38.5% stage I, 43.5% stage II, and 18.0% stage III. Two-year overall survival was 93.3% for patients diagnosed from 2010-2017 and 92.9% for 2018-2020. ET was omitted in 33.8% of patients (median age 58 vs. 57 among ET recipients). In multivariate logistic regression, factors associated with omission of ET were diagnosis from 2018-2020 (adjusted odds ratio [aOR] 1.95, 95% CI 1.75-2.17, p<0.001), increasing age (age 70-80 vs. 40-50: aOR 1.34, 95% CI 1.16-1.55, p<0.001), and high grade (aOR 1.15, 95% CI 1.03-1.28, p=0.02). In multivariate Cox regression, receiving ET was associated with improved three-year OS for patients diagnosed from 2010-2017 (n=7,517; adjusted hazard ratio [aHR] 0.54, 95% CI 0.47-0.62, p<0.001) and 2018-2020 (n=4,041; aHR 0.60, 95% CI 0.48-0.77, p<0.001). Interaction testing for diagnosis period and ET benefit was not significant (p=0.59). After PSM by all covariates, OS benefit remained for both 2010-2017 (n=5,696; aHR 0.55, 95% CI 0.47-0.65, p<0.001) and 2018-2020 (n=2,344; aHR 0.64, 95% CI 0.48-0.86, p=0.003). Conclusions: Omission of ET in ER-/PR+ early-stage breast cancer treated with chemotherapy was associated with worse overall survival, both before and after 2018. The biological and technical uncertainty of this subtype remains unresolved, but these findings warrant further investigation. Citation Format: S. M. Doss, P. Raval. The mystery of ER-neg
背景：雌激素受体阴性（ER-），孕激素受体阳性（PR+）乳腺癌的存在是罕见的，生物学上令人困惑，通常归因于技术人为因素。先前的国家分析发现，内分泌治疗（ET）对ER-/PR+肿瘤没有益处，但最近的数据表明，内分泌治疗对生存有好处。为了探究这种不一致性，我们分析了接受ET治疗与接受化疗的ER-/PR+早期乳腺癌患者生存率之间的关系。方法：我们使用国家癌症数据库（NCDB）来识别2010年至2020年期间诊断为I-III期，ER-/PR+乳腺癌的40岁及以上接受化疗的女性。多元逻辑回归评估与ET遗漏相关的因素。多变量Cox回归分析了ET治疗与三年总生存期（OS）之间的关系，根据2018年预后分期和NCDB部位特异性因素的变化，按诊断期（2010-2017 vs. 2018-2020）分层。分析调整了诊断阶段、年龄、合并症、HER2状态、种族/民族、年级、设施类型和邮政编码收入。采用倾向评分匹配（PSM）、里程碑分析和her2阴性亚组分析来检验稳健性。结果：我们发现24,198例（0.94%）ER-/PR+乳腺癌，其中18,788例（77.6%）在诊断时为I-III期。其中，13957例（74.3%）接受了化疗，11558例有完整的协变量数据分析。大多数病例为her2阴性（60.2%）和高分级（75.1%）。分期分布为：一期38.5%，二期43.5%，三期18.0%。2010-2017年诊断的患者两年总生存率为93.3%，2018-2020年为92.9%。33.8%的患者未接受ET治疗（接受ET治疗的患者中位年龄为58岁对57岁）。在多因素logistic回归中，与ET遗漏相关的因素是2018-2020年的诊断（校正优势比[aOR] 1.95, 95% CI 1.75-2.17, p= 0.001）、年龄增加（70-80岁vs. 40-50岁：aOR 1.34, 95% CI 1.16-1.55, p= 0.001）和高分级（aOR 1.15, 95% CI 1.03-1.28, p=0.02）。在多变量Cox回归中，2010-2017年（n=7,517；校正风险比[aHR] 0.54, 95% CI 0.47-0.62, p<0.001）和2018-2020年（n=4,041; aHR 0.60, 95% CI 0.48-0.77, p<0.001）诊断的患者接受ET治疗与改善三年OS相关。诊断期与ET获益的交互作用测试无显著性意义（p=0.59）。在所有协变量的PSM后，2010-2017年（n=5,696; aHR 0.55, 95% CI 0.47-0.65, p<0.001）和2018-2020年（n=2,344; aHR 0.64, 95% CI 0.48-0.86, p=0.003）的OS获益仍然存在。结论：2018年前后，接受化疗的ER-/PR+早期乳腺癌患者遗漏ET与总生存率降低相关。该亚型的生物学和技术不确定性仍未得到解决，但这些发现值得进一步调查。引文格式：S. M. Doss， P. Raval。er阴性/ pr阳性乳腺癌的奥秘：利用国家数据重新审视内分泌治疗争议[摘要]。摘自：《2025年圣安东尼奥乳腺癌研讨会论文集》；2025年12月9-12日；费城（PA）： AACR；临床癌症杂志2026；32（4增刊）：nr PS3-08-03。
{"title":"Abstract PS3-08-03: The mystery of ER-negative/PR-positive breast cancer: revisiting the endocrine therapy controversy using national data","authors":"S. M. Doss, P. Raval","doi":"10.1158/1557-3265.sabcs25-ps3-08-03","DOIUrl":"https://doi.org/10.1158/1557-3265.sabcs25-ps3-08-03","url":null,"abstract":"Background: The existence of estrogen receptor-negative (ER-), progesterone receptor-positive (PR+) breast cancer is rare, biologically confusing, and often attributed to technical artifact. Previous national analyses found no benefit from endocrine therapy (ET) in ER-/PR+ tumors, but more recent data suggest a survival benefit. To explore this inconsistency, we analyzed the association between receiving ET and survival in ER-/PR+ early-stage breast cancer treated with chemotherapy over time. Methods: We used the National Cancer Database (NCDB) to identify women age 40 and older diagnosed with stage I-III, ER-/PR+ breast cancer from 2010 to 2020 who received chemotherapy. Multivariate logistic regression evaluated factors associated with ET omission. Multivariate Cox regression analyzed the association between ET receipt and three-year overall survival (OS), stratified by diagnosis period (2010-2017 vs. 2018-2020) based on 2018 changes for prognostic staging and NCDB site-specific factors. Analyses adjusted for stage at diagnosis, age, comorbidity, HER2 status, race/ethnicity, grade, facility type, and zip code income. Robustness was tested using propensity score matching (PSM), landmark analysis, and HER2-negative subgroup analysis. Results: We identified 24,198 (0.94%) cases of ER-/PR+ breast cancer, of which 18,788 (77.6%) were stage I-III at diagnosis. Of these, 13,957 (74.3%) received chemotherapy, and 11,558 with complete covariate data were analyzed. Most cases were HER2-negative (60.2%) and high grade (75.1%). Stage distribution was 38.5% stage I, 43.5% stage II, and 18.0% stage III. Two-year overall survival was 93.3% for patients diagnosed from 2010-2017 and 92.9% for 2018-2020. ET was omitted in 33.8% of patients (median age 58 vs. 57 among ET recipients). In multivariate logistic regression, factors associated with omission of ET were diagnosis from 2018-2020 (adjusted odds ratio [aOR] 1.95, 95% CI 1.75-2.17, p&lt;0.001), increasing age (age 70-80 vs. 40-50: aOR 1.34, 95% CI 1.16-1.55, p&lt;0.001), and high grade (aOR 1.15, 95% CI 1.03-1.28, p=0.02). In multivariate Cox regression, receiving ET was associated with improved three-year OS for patients diagnosed from 2010-2017 (n=7,517; adjusted hazard ratio [aHR] 0.54, 95% CI 0.47-0.62, p&lt;0.001) and 2018-2020 (n=4,041; aHR 0.60, 95% CI 0.48-0.77, p&lt;0.001). Interaction testing for diagnosis period and ET benefit was not significant (p=0.59). After PSM by all covariates, OS benefit remained for both 2010-2017 (n=5,696; aHR 0.55, 95% CI 0.47-0.65, p&lt;0.001) and 2018-2020 (n=2,344; aHR 0.64, 95% CI 0.48-0.86, p=0.003). Conclusions: Omission of ET in ER-/PR+ early-stage breast cancer treated with chemotherapy was associated with worse overall survival, both before and after 2018. The biological and technical uncertainty of this subtype remains unresolved, but these findings warrant further investigation. Citation Format: S. M. Doss, P. Raval. The mystery of ER-neg","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":"66 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146231084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-01-09
G. Pourali, L. Lyu, X. Guo, A. Toriola
Background: Genome-wide association studies (GWAS) have identified genetic loci associated with mammographic breast density (MBD) and breast cancer risk, but the mechanisms underlying these associations remain unclear. Metabolite quantitative trait loci (mQTL) analyses can map genetic loci associated with metabolites, potentially offering insight into mechanisms involved in risk, but there is limited data on how genetically predicted metabolites are associated with MBD and breast cancer risk in premenopausal women. To address this, we performed mQTL analyses in non-Hispanic White (NHW) and non-Hispanic Black (NHB) women and examined their overlap with established GWAS loci for MBD and breast cancer. Methods: Our analysis included 494 NHW and 163 NHB women who had screening mammograms at Washington University in St. Louis. Plasma metabolomic profiling (Metabolon®) identified 1,074 metabolites, and genotyping (Infinium microarray, Illumina) covered 2,028,571 loci. Metabolite data were batch-normalized, metabolites with >10% missingness were excluded, and remaining missing values were imputed. We conducted mQTL mapping using linear regression in PLINK 2.0, stratified by race and adjusted for age, body mass index, alcohol use, oral contraceptive use, and first five genotype principal components. Significant mQTLs (FDR-p<0.05) were compared to GWAS loci for breast cancer, two fine mapping studies, and GWAS of MBD. Results: In NHW women, 30 mQTLs were associated with 54 metabolites overlapping breast cancer GWAS loci. Key pathways included xenobiotics (anti-inflammatory/immunosuppressant drugs, chemicals, tobacco metabolites), lipid (fatty acid, corticosteroid, bile acid metabolism), and amino acid (tryptophan, methionine/cysteine, tyrosine metabolism). In NHB women, 2 mQTLs were associated with 3 metabolites overlapping breast cancer GWAS loci: rs16866849 (diltiazem, ß =0.2, FDR-p=1.6×10-6, cardiovascular drug), and rs9397068 with two metabolites (2-hydroxyibuprofen, ß=5.3, FDR-p=9.6×10-3, analgesics; and 2,2'-methylenebis(6-tert-butyl-p-cresol), ß=14.6, FDR-p=9.6×10-3, chemical). Additionally, in NHW women, 5 mQTLs were associated with 5 metabolites overlapping GWAS loci of MBD. For dense area, these included rs150249911 (levulinate (4-oxovalerate), ß=6.5, FDR-p=2.3×10-7, food component/plant), rs150249911 (N-acetyltyrosine, ß=5.0, FDR-p=3.3×10-4, tyrosine metabolism), rs2042239 (5-acetylamino-6-formylamino-3-methyluracil, ß=1.3, FDR-p=3.3×10-2, xanthine metabolism), and rs833472 (3-hydroxystachydrine, ß=11.0, FDR-p=2.5×10-3, food component/plant). For percent mammographic density, rs61941038 (3-hydroxystachydrine, ß=10.4, FDR-p=7.4×10-3, food component/plant) was associated. For non-dense area, rs78395856 (taurochenodeoxycholic acid 3-sulfate, ß=3.7, FDR-p=3.3×10-2, bile acid metabolism) was associated. Conclusions: Our novel study identified genetic loci associated with metabolites that overlap with established MBD and breast cancer r
{"title":"Abstract PS3-01-09: Associations of genetically predicted metabolites with mammographic breast density and breast cancer risk in premenopausal women","authors":"G. Pourali, L. Lyu, X. Guo, A. Toriola","doi":"10.1158/1557-3265.sabcs25-ps3-01-09","DOIUrl":"https://doi.org/10.1158/1557-3265.sabcs25-ps3-01-09","url":null,"abstract":"Background: Genome-wide association studies (GWAS) have identified genetic loci associated with mammographic breast density (MBD) and breast cancer risk, but the mechanisms underlying these associations remain unclear. Metabolite quantitative trait loci (mQTL) analyses can map genetic loci associated with metabolites, potentially offering insight into mechanisms involved in risk, but there is limited data on how genetically predicted metabolites are associated with MBD and breast cancer risk in premenopausal women. To address this, we performed mQTL analyses in non-Hispanic White (NHW) and non-Hispanic Black (NHB) women and examined their overlap with established GWAS loci for MBD and breast cancer. Methods: Our analysis included 494 NHW and 163 NHB women who had screening mammograms at Washington University in St. Louis. Plasma metabolomic profiling (Metabolon®) identified 1,074 metabolites, and genotyping (Infinium microarray, Illumina) covered 2,028,571 loci. Metabolite data were batch-normalized, metabolites with &gt;10% missingness were excluded, and remaining missing values were imputed. We conducted mQTL mapping using linear regression in PLINK 2.0, stratified by race and adjusted for age, body mass index, alcohol use, oral contraceptive use, and first five genotype principal components. Significant mQTLs (FDR-p&lt;0.05) were compared to GWAS loci for breast cancer, two fine mapping studies, and GWAS of MBD. Results: In NHW women, 30 mQTLs were associated with 54 metabolites overlapping breast cancer GWAS loci. Key pathways included xenobiotics (anti-inflammatory/immunosuppressant drugs, chemicals, tobacco metabolites), lipid (fatty acid, corticosteroid, bile acid metabolism), and amino acid (tryptophan, methionine/cysteine, tyrosine metabolism). In NHB women, 2 mQTLs were associated with 3 metabolites overlapping breast cancer GWAS loci: rs16866849 (diltiazem, ß =0.2, FDR-p=1.6×10-6, cardiovascular drug), and rs9397068 with two metabolites (2-hydroxyibuprofen, ß=5.3, FDR-p=9.6×10-3, analgesics; and 2,2'-methylenebis(6-tert-butyl-p-cresol), ß=14.6, FDR-p=9.6×10-3, chemical). Additionally, in NHW women, 5 mQTLs were associated with 5 metabolites overlapping GWAS loci of MBD. For dense area, these included rs150249911 (levulinate (4-oxovalerate), ß=6.5, FDR-p=2.3×10-7, food component/plant), rs150249911 (N-acetyltyrosine, ß=5.0, FDR-p=3.3×10-4, tyrosine metabolism), rs2042239 (5-acetylamino-6-formylamino-3-methyluracil, ß=1.3, FDR-p=3.3×10-2, xanthine metabolism), and rs833472 (3-hydroxystachydrine, ß=11.0, FDR-p=2.5×10-3, food component/plant). For percent mammographic density, rs61941038 (3-hydroxystachydrine, ß=10.4, FDR-p=7.4×10-3, food component/plant) was associated. For non-dense area, rs78395856 (taurochenodeoxycholic acid 3-sulfate, ß=3.7, FDR-p=3.3×10-2, bile acid metabolism) was associated. Conclusions: Our novel study identified genetic loci associated with metabolites that overlap with established MBD and breast cancer r","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":"8 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146231086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-06-16
Y. Xu, D. Ma, X. Wu, Z. Qiu, L. Dai, H. Zhang, S. Zhao, Y. Xiao, Y. Jiang, Z. Shao
Background: Neutrophils are increasingly recognized as a key component of the tumor microenvironment. However, their spatial organization and interactions with other cells remain poorly characterized. The clinical and biological significance of these spatial patterns requires further exploration. Our study aims to identify clinically relevant neutrophil spatial architectures in breast cancer and elucidate their biological underpinnings. Methods: We established a large-scale breast cancer cohort covering all standard therapeutic regimens (adjuvant setting, n = 629; neoadjuvant setting, n = 381), with matched hematoxylin and eosin (H&E)-stained whole slide images (WSIs). We refined an artificial intelligence-based computational pathology framework we had proposed1 to identify neutrophils in WSIs and characterize their spatial patterns (i.e., their spatial relationships with neighboring cell types). Then we studied the correlation between these patterns and patient outcomes. To investigate the biology basis of distinct neutrophil spatial patterns, we performed single-cell spatial transcriptomics profiling (n = 104) and integrative analysis, with functional validation using patient-derived organoids (PDOs). Results: We found neutrophil spatial architectures demonstrated significant prognostic and predictive value, particularly in triple-negative breast cancer (TNBC). Specifically, we identified two clinically relevant patterns in TNBC: (1) Neutrophils in closer proximity to tumor cells predicted improved prognosis, which was validated in independent cohorts. Mechanistically, neutrophils upregulated MHC class I on tumor cells via secreted factors (e.g., TNFα), thereby enhancing CD8+ T cell-mediated recognition and cytotoxicity. This process was further corroborated by evidence from a neutrophil-PDO-CD8+ T cell co-culture system. (2) Neutrophils neighboring immune cells correlated with superior response to neoadjuvant immunotherapy. These neutrophils developed potent antigen-presenting capabilities through concurrent upregulation of MHC class I and II molecules. They primed CD4+ naive T cells and expanded CD8+ effector/memory T cells, thus fostering an immunotherapy-responsive microenvironment. Conclusion: Our study delineates the spatial heterogeneity of neutrophils, mapping their functional plasticity to spatial patterns with clinical relevance. These findings may inform the development of clinically actionable biomarkers for prognosis stratification and treatment response prediction in breast cancer patients. References 1Zhao, S. et al. Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer. Nat Commun 14, 6796, doi:10.1038/s41467-023-42504-y (2023). Citation Format: Y. Xu, D. Ma, X. Wu, Z. Qiu, L. Dai, H. Zhang, S. Zhao, Y. Xiao, Y. Jiang, Z. Shao. Mapping neutrophil architecture with integrative spatial analysis to reveal clinically relevant functional heterogeneity [abstract]. In: Proceedings of
{"title":"Abstract PS3-06-16: Mapping neutrophil architecture with integrative spatial analysis to reveal clinically relevant functional heterogeneity","authors":"Y. Xu, D. Ma, X. Wu, Z. Qiu, L. Dai, H. Zhang, S. Zhao, Y. Xiao, Y. Jiang, Z. Shao","doi":"10.1158/1557-3265.sabcs25-ps3-06-16","DOIUrl":"https://doi.org/10.1158/1557-3265.sabcs25-ps3-06-16","url":null,"abstract":"Background: Neutrophils are increasingly recognized as a key component of the tumor microenvironment. However, their spatial organization and interactions with other cells remain poorly characterized. The clinical and biological significance of these spatial patterns requires further exploration. Our study aims to identify clinically relevant neutrophil spatial architectures in breast cancer and elucidate their biological underpinnings. Methods: We established a large-scale breast cancer cohort covering all standard therapeutic regimens (adjuvant setting, n = 629; neoadjuvant setting, n = 381), with matched hematoxylin and eosin (H&E)-stained whole slide images (WSIs). We refined an artificial intelligence-based computational pathology framework we had proposed1 to identify neutrophils in WSIs and characterize their spatial patterns (i.e., their spatial relationships with neighboring cell types). Then we studied the correlation between these patterns and patient outcomes. To investigate the biology basis of distinct neutrophil spatial patterns, we performed single-cell spatial transcriptomics profiling (n = 104) and integrative analysis, with functional validation using patient-derived organoids (PDOs). Results: We found neutrophil spatial architectures demonstrated significant prognostic and predictive value, particularly in triple-negative breast cancer (TNBC). Specifically, we identified two clinically relevant patterns in TNBC: (1) Neutrophils in closer proximity to tumor cells predicted improved prognosis, which was validated in independent cohorts. Mechanistically, neutrophils upregulated MHC class I on tumor cells via secreted factors (e.g., TNFα), thereby enhancing CD8+ T cell-mediated recognition and cytotoxicity. This process was further corroborated by evidence from a neutrophil-PDO-CD8+ T cell co-culture system. (2) Neutrophils neighboring immune cells correlated with superior response to neoadjuvant immunotherapy. These neutrophils developed potent antigen-presenting capabilities through concurrent upregulation of MHC class I and II molecules. They primed CD4+ naive T cells and expanded CD8+ effector/memory T cells, thus fostering an immunotherapy-responsive microenvironment. Conclusion: Our study delineates the spatial heterogeneity of neutrophils, mapping their functional plasticity to spatial patterns with clinical relevance. These findings may inform the development of clinically actionable biomarkers for prognosis stratification and treatment response prediction in breast cancer patients. References 1Zhao, S. et al. Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer. Nat Commun 14, 6796, doi:10.1038/s41467-023-42504-y (2023). Citation Format: Y. Xu, D. Ma, X. Wu, Z. Qiu, L. Dai, H. Zhang, S. Zhao, Y. Xiao, Y. Jiang, Z. Shao. Mapping neutrophil architecture with integrative spatial analysis to reveal clinically relevant functional heterogeneity [abstract]. In: Proceedings of","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":"5 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146230760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-20DOI: 10.1158/1557-3265.sabcs25-ps3-06-15
Y. Yuan, A. Yuan, W. Wang, Z. Hu, C. Zheng, Z. Zheng, W. Liang, Y. Zhang, Y. Pan, C. Zhang
Background: In survival analysis tasks, DeepSurv, DeepHit, etc., are deep learning-based models designed to handle one-dimensional time series data. Their primary objective is to predict an individual's survival probability and its relationship with time. However, traditional one-dimensional data processing methods may overlook certain spatial structural information inherent in the data—a limitation that is particularly significant for specific types of biomedical or clinical data. Therefore, we propose an innovative approach: converting one-dimensional data into grayscale images. This conversion introduces additional spatial features, enabling the model to better capture complex patterns in the data. Our aim is to develop a predictive analysis model for the impact of atmospheric environment on breast cancer prognosis. Methods: This study is a multi-center retrospective cohort study on breast cancer, involving 17,438 breast cancer patients. The endpoint outcome is disease-free survival (DFS). The features include age, gender, HDI, history of malignant tumors, family history of breast cancer, ki67, pathological type, molecular subtype, TNM staging, O3, PM2.5, monthly average precipitation, monthly average wind speed, and monthly average temperature. Firstly, we expand the dimensionality of one-dimensional survival data by mapping it to grayscale images, making it compatible with the input format of convolutional neural networks (CNNs) for processing image data. Through this conversion, we can effectively extract spatial features using convolutional operations, thereby enhancing the model's predictive capability. Subsequently, we develop a CNN-based deep neural network model that incorporates convolutional layers to process these grayscale image data while retaining the core concepts of survival analysis. This model aims to predict an individual's relative risk value by learning deep patterns in the data and can handle prognostic data with high complexity and non-linear relationships. Citation Format: Y. Yuan, A. Yuan, W. Wang, Z. Hu, C. Zheng, Z. Zheng, W. Liang, Y. Zhang, Y. Pan, C. Zhang. A Retrospective Study on a Predictive Model to Probe the Impact of Atmospheric Environment on Breast Cancer Prognosis: A Cohort of 17,438 Patients [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl): nr PS3-06-15.
{"title":"Abstract PS3-06-15: A Retrospective Study on a Predictive Model to Probe the Impact of Atmospheric Environment on Breast Cancer Prognosis: A Cohort of 17,438 Patients","authors":"Y. Yuan, A. Yuan, W. Wang, Z. Hu, C. Zheng, Z. Zheng, W. Liang, Y. Zhang, Y. Pan, C. Zhang","doi":"10.1158/1557-3265.sabcs25-ps3-06-15","DOIUrl":"https://doi.org/10.1158/1557-3265.sabcs25-ps3-06-15","url":null,"abstract":"Background: In survival analysis tasks, DeepSurv, DeepHit, etc., are deep learning-based models designed to handle one-dimensional time series data. Their primary objective is to predict an individual's survival probability and its relationship with time. However, traditional one-dimensional data processing methods may overlook certain spatial structural information inherent in the data—a limitation that is particularly significant for specific types of biomedical or clinical data. Therefore, we propose an innovative approach: converting one-dimensional data into grayscale images. This conversion introduces additional spatial features, enabling the model to better capture complex patterns in the data. Our aim is to develop a predictive analysis model for the impact of atmospheric environment on breast cancer prognosis. Methods: This study is a multi-center retrospective cohort study on breast cancer, involving 17,438 breast cancer patients. The endpoint outcome is disease-free survival (DFS). The features include age, gender, HDI, history of malignant tumors, family history of breast cancer, ki67, pathological type, molecular subtype, TNM staging, O3, PM2.5, monthly average precipitation, monthly average wind speed, and monthly average temperature. Firstly, we expand the dimensionality of one-dimensional survival data by mapping it to grayscale images, making it compatible with the input format of convolutional neural networks (CNNs) for processing image data. Through this conversion, we can effectively extract spatial features using convolutional operations, thereby enhancing the model's predictive capability. Subsequently, we develop a CNN-based deep neural network model that incorporates convolutional layers to process these grayscale image data while retaining the core concepts of survival analysis. This model aims to predict an individual's relative risk value by learning deep patterns in the data and can handle prognostic data with high complexity and non-linear relationships. Citation Format: Y. Yuan, A. Yuan, W. Wang, Z. Hu, C. Zheng, Z. Zheng, W. Liang, Y. Zhang, Y. Pan, C. Zhang. A Retrospective Study on a Predictive Model to Probe the Impact of Atmospheric Environment on Breast Cancer Prognosis: A Cohort of 17,438 Patients [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl): nr PS3-06-15.","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":"5 1","pages":""},"PeriodicalIF":11.5,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146230769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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