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对接受新辅助化疗的乳腺癌患者进行代谢组学分析以预测无病生存和总生存。

Metabolomic Profiling of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy for Predicting Disease-Free and Overall Survival.

机构信息

Department of Obstetrics and Gynecology, Division of Gynecologic and Breast Oncology, School of Medical Sciences, University of Campinas (UNICAMP-Universidade Estadual de Campinas), Campinas 13083-881, SP, Brazil.

Department of Pathology, Harvard Medical School, Boston, MA 02115, USA.

出版信息

Int J Mol Sci. 2024 Aug 8;25(16):8639. doi: 10.3390/ijms25168639.

Abstract

Breast cancer (BC) remains a significant global health concern, with neoadjuvant chemotherapy (NACT) offering preoperative benefits like tumor downstaging and treatment response assessment. However, identifying factors influencing post-NACT treatment response and survival outcomes is challenging. Metabolomic approaches offer promising insights into understanding these outcomes. This study analyzed the serum of 80 BC patients before and after NACT, followed for up to five years, correlating with disease-free survival (DFS) and overall survival (OS). Using untargeted nuclear magnetic resonance (NMR) spectroscopy and a novel statistical model that avoids collinearity issues, we identified metabolic changes associated with survival outcomes. Four metabolites (histidine, lactate, serine, and taurine) were significantly associated with DFS. We developed a metabolite-related survival score (MRSS) from these metabolites, stratifying patients into low- and high-risk relapse groups, independent of classical prognostic factors. High-risk patients had a hazard ratio (HR) for DFS of 3.42 (95% CI 1.51-7.74; = 0.003) after adjustment for disease stage and age. A similar trend was observed for OS (HR of 3.34, 95% CI 1.64-6.80; < 0.001). Multivariate Cox proportional hazards analysis confirmed the independent prognostic value of the MRSS. Our findings suggest the potential of metabolomic data, alongside traditional markers, in guiding personalized treatment decisions and risk stratification in BC patients undergoing NACT. This study provides a methodological framework for leveraging metabolomics in survival analyses.

摘要

乳腺癌(BC)仍然是一个重大的全球健康问题,新辅助化疗(NACT)提供了术前益处,如肿瘤降期和治疗反应评估。然而,确定影响 post-NACT 治疗反应和生存结果的因素具有挑战性。代谢组学方法为理解这些结果提供了有希望的见解。本研究分析了 80 例接受 NACT 前后的 BC 患者的血清,随访时间长达五年,与无病生存(DFS)和总生存(OS)相关。使用非靶向核磁共振(NMR)光谱和一种避免共线性问题的新型统计模型,我们确定了与生存结果相关的代谢变化。四种代谢物(组氨酸、乳酸盐、丝氨酸和牛磺酸)与 DFS 显著相关。我们从这些代谢物中开发了一个与代谢物相关的生存评分(MRSS),将患者分为低风险和高风险复发组,独立于经典预后因素。高风险患者的 DFS 风险比(HR)为 3.42(95%CI 1.51-7.74; = 0.003),在调整疾病分期和年龄后。OS 也观察到类似的趋势(HR 为 3.34,95%CI 1.64-6.80; < 0.001)。多变量 Cox 比例风险分析证实了 MRSS 的独立预后价值。我们的研究结果表明,代谢组学数据与传统标志物一起,有可能在指导接受 NACT 的 BC 患者的个性化治疗决策和风险分层方面发挥作用。本研究提供了一种利用代谢组学进行生存分析的方法框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed66/11354796/db4ebc996cf8/ijms-25-08639-g001.jpg

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