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本文引用的文献

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Development of a urine-based metabolomics approach for multi-cancer screening and tumor origin prediction.一种用于多癌筛查和肿瘤起源预测的基于尿液的代谢组学方法的开发。
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Oxidative Stress in Breast Cancer: A Biochemical Map of Reactive Oxygen Species Production.乳腺癌中的氧化应激:活性氧生成的生化图谱
Curr Issues Mol Biol. 2024 May 13;46(5):4646-4687. doi: 10.3390/cimb46050282.
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Multi-omics landscape analysis reveals the pan-cancer association of arginine biosynthesis genes with tumor immune evasion and therapy resistance.多组学景观分析揭示精氨酸生物合成基因与肿瘤免疫逃逸和治疗耐药性的泛癌关联。
Heliyon. 2024 Feb 29;10(5):e26804. doi: 10.1016/j.heliyon.2024.e26804. eCollection 2024 Mar 15.
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Cancer statistics, 2024.2024年癌症统计数据。
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Amino acid metabolism in tumor biology and therapy.肿瘤生物学和治疗中的氨基酸代谢。
Cell Death Dis. 2024 Jan 13;15(1):42. doi: 10.1038/s41419-024-06435-w.
6
Proline metabolism shapes the tumor microenvironment: from collagen deposition to immune evasion.脯氨酸代谢塑造肿瘤微环境:从胶原沉积到免疫逃逸。
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7
Branched-chain amino acids catabolism and cancer progression: focus on therapeutic interventions.支链氨基酸分解代谢与癌症进展:聚焦于治疗干预措施。
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8
Advancing Breast Cancer Heterogeneity Analysis: Insights from Genomics, Transcriptomics and Proteomics at Bulk and Single-Cell Levels.推进乳腺癌异质性分析:来自大量样本和单细胞水平的基因组学、转录组学和蛋白质组学的见解
Cancers (Basel). 2023 Aug 18;15(16):4164. doi: 10.3390/cancers15164164.
9
Unlocking the Potential of Arginine Deprivation Therapy: Recent Breakthroughs and Promising Future for Cancer Treatment.精氨酸剥夺疗法的潜力解锁:癌症治疗的最新突破和广阔前景。
Int J Mol Sci. 2023 Jun 26;24(13):10668. doi: 10.3390/ijms241310668.
10
Role of Glucose Metabolic Reprogramming in Breast Cancer Progression and Drug Resistance.葡萄糖代谢重编程在乳腺癌进展和耐药中的作用
Cancers (Basel). 2023 Jun 28;15(13):3390. doi: 10.3390/cancers15133390.

乳腺癌放疗后疾病进展的代谢组学分析

Metabolomic Profiling of Disease Progression Following Radiotherapy for Breast Cancer.

作者信息

McMahon Alexandra N, Reis Isildinha M, Takita Cristiane, Wright Jean L, Hu Jennifer J

机构信息

Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA.

Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA.

出版信息

Cancers (Basel). 2025 Mar 5;17(5):891. doi: 10.3390/cancers17050891.

DOI:10.3390/cancers17050891
PMID:40075737
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11899340/
Abstract

BACKGROUND

This study aims to explore metabolic biomarkers and pathways in breast cancer prognosis.

METHODS

We performed a global post-radiotherapy (RT) urinary metabolomic analysis of 120 breast cancer patients: 60 progression-free (PF) patients as the reference and 60 with progressive disease (PD: recurrence, second primary, metastasis, or death). UPLC-MS/MS (Metabolon Inc.) identified 1742 biochemicals (1258 known and 484 unknown structures). Following normalization to osmolality, log transformation, and imputation of missing values, a Welch's two-sample -test was used to identify biochemicals and metabolic pathways that differed between PF and PD groups. Data analysis and visualization were performed with MetaboAnalyst.

RESULTS

Metabolic biomarkers and pathways that significantly differed between the PD and PF groups were the following: amino acid metabolism, including phenylalanine, tyrosine, and tryptophan biosynthesis (impact value (IV) = 1.00; = 0.0007); histidine metabolism (IV = 0.60; < 0.0001); and arginine and proline metabolism (IV = 0.70; = 0.0035). Metabolites of carbohydrate metabolism, including glucose ( = 0.0197), sedoheptulose ( = 0.0115), and carboxymethyl lysine ( = 0.0098), were elevated in patients with PD. Gamma-glutamyl amino acids, myo-inositol, and oxidative stress biomarkers, including 7-Hydroxyindole Sulfate and sulfate, were elevated in patients who died ( ≤ 0.05).

CONCLUSIONS

Amino acid metabolism emerged as a key pathway in breast cancer progression, while carbohydrate and oxidative stress metabolites also showed potential utility as biomarkers for breast cancer progression. These findings demonstrate applications of metabolomics in identifying metabolic biomarkers and pathways as potential targets for predicting breast cancer progression.

摘要

背景

本研究旨在探索乳腺癌预后中的代谢生物标志物和代谢途径。

方法

我们对120例乳腺癌患者进行了放疗后尿液代谢组学分析:60例无进展(PF)患者作为参照,60例疾病进展(PD:复发、第二原发性肿瘤、转移或死亡)患者。采用超高效液相色谱-串联质谱法(Metabolon公司)鉴定出1742种生化物质(1258种已知结构和484种未知结构)。在对渗透压进行归一化、对数转换和缺失值插补后,使用韦尔奇两样本t检验来鉴定PF组和PD组之间存在差异的生化物质和代谢途径。数据分析和可视化使用MetaboAnalyst软件完成。

结果

PD组和PF组之间存在显著差异的代谢生物标志物和代谢途径如下:氨基酸代谢,包括苯丙氨酸、酪氨酸和色氨酸生物合成(影响值(IV)=1.00;P=0.0007);组氨酸代谢(IV=0.60;P<0.0001);精氨酸和脯氨酸代谢(IV=0.70;P=0.0035)。糖代谢的代谢产物,包括葡萄糖(P=0.0197)、景天庚酮糖(P=0.0115)和羧甲基赖氨酸(P=0.0098),在PD患者中升高。γ-谷氨酰氨基酸、肌醇以及氧化应激生物标志物,包括7-羟基吲哚硫酸盐和硫酸盐,在死亡患者中升高(P≤0.05)。

结论

氨基酸代谢是乳腺癌进展中的关键途径,而碳水化合物和氧化应激代谢产物也显示出作为乳腺癌进展生物标志物的潜在效用。这些发现证明了代谢组学在识别代谢生物标志物和代谢途径作为预测乳腺癌进展潜在靶点方面的应用。