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基于代谢组学的乳腺癌预后和诊断生物标志物发现

Metabolomics-Driven Biomarker Discovery for Breast Cancer Prognosis and Diagnosis.

作者信息

Kaur Rasanpreet, Gupta Saurabh, Kulshrestha Sunanda, Khandelwal Vishal, Pandey Swadha, Kumar Anil, Sharma Gaurav, Kumar Umesh, Parashar Deepak, Das Kaushik

机构信息

Department of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Chaumuhan, Mathura 281406, Uttar Pradesh, India.

Division of Hematology & Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI 53226, USA.

出版信息

Cells. 2024 Dec 25;14(1):5. doi: 10.3390/cells14010005.

Abstract

Breast cancer is a cancer with global prevalence and a surge in the number of cases with each passing year. With the advancement in science and technology, significant progress has been achieved in the prevention and treatment of breast cancer to make ends meet. The scientific intradisciplinary subject of "metabolomics" examines every metabolite found in a cell, tissue, system, or organism from different sources of samples. In the case of breast cancer, little is known about the regulatory pathways that could be resolved through metabolic reprogramming. Evidence related to the significant changes taking place during the onset and prognosis of breast cancer can be obtained using metabolomics. Innovative metabolomics approaches identify metabolites that lead to the discovery of biomarkers for breast cancer therapy, diagnosis, and early detection. The use of diverse analytical methods and instruments for metabolomics includes Magnetic Resonance Spectroscopy, LC/MS, UPLC/MS, etc., which, along with their high-throughput analysis, give insights into the metabolites and the molecular pathways involved. For instance, metabolome research has led to the discovery of the glutamate-to-glutamate ratio and aerobic glycolysis as biomarkers in breast cancer. The present review comprehends the updates in metabolomic research and its processes that contribute to breast cancer prognosis and metastasis. The metabolome holds a future, and this review is an attempt to amalgamate the present relevant literature that might yield crucial insights for creating innovative therapeutic strategies aimed at addressing metastatic breast cancer.

摘要

乳腺癌是一种全球普遍存在且病例数逐年激增的癌症。随着科技的进步,乳腺癌的预防和治疗已取得显著进展以应对需求。“代谢组学”这一科学跨学科主题研究从不同样本来源的细胞、组织、系统或生物体中发现的每一种代谢物。就乳腺癌而言,对于可通过代谢重编程解决的调控途径知之甚少。利用代谢组学能够获得与乳腺癌发生和预后期间发生的显著变化相关的证据。创新的代谢组学方法可识别代谢物,从而发现用于乳腺癌治疗、诊断和早期检测的生物标志物。用于代谢组学的多种分析方法和仪器包括磁共振波谱、液相色谱/质谱联用、超高效液相色谱/质谱联用等,这些方法连同其高通量分析,可深入了解所涉及的代谢物和分子途径。例如,代谢组研究已发现谷氨酰胺与谷氨酸的比率以及有氧糖酵解可作为乳腺癌的生物标志物。本综述涵盖了代谢组学研究及其对乳腺癌预后和转移有贡献的过程的最新进展。代谢组学前景广阔,本综述试图整合当前相关文献,这些文献可能为制定针对转移性乳腺癌的创新治疗策略提供关键见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/421c/11720085/8847c11748cf/cells-14-00005-g001.jpg

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