Metabolomics, the systematic investigation of all metabolites present within a biologic system, is used in biomarker development for many human diseases, including cancer. In this review, we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase, and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification, or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including less than 100 patients. Standardization is required especially concerning sample preparation and data analysis. In the second part of this review, we reconstructed a metabolic network of patients with cancer by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane, and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed.
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http://dx.doi.org/10.1158/1055-9965.EPI-13-0584 | DOI Listing |
Int J Surg
January 2025
Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center, Shanghai, China.
Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal diseases. Although several chemotherapy regimens have been developed over the past decades, few targeted therapies have shown a significant improvement in overall survival, partly due to the identification of PDAC as a single disease.
Methods: Combining metabolomic analysis and immunohistochemistry staining with Oil Red O staining, analysis for the oxygen consumption rate and extracellular acidification rate, we stratified pancreatic cancer cells into two subtypes.
Anal Chem
January 2025
State Key Laboratory of Cellular Stress Biology, Institute of Artificial Intelligence, School of Life Sciences, Faculty of Medicine and Life Sciences, National Institute for Data Science in Health and Medicine, XMU-HBN skin biomedical research center, Xiamen University, Xiamen, Fujian 361102, China.
In metabolomic analysis based on liquid chromatography coupled with mass spectrometry, detecting and quantifying intricate objects is a massive job. Current peak picking methods still cause high rates of incorrectly picked peaks to influence the reliability and reproducibility of results. To address these challenges, we developed QuanFormer, a deep learning method based on object detection designed to accurately quantify peak signals.
View Article and Find Full Text PDFInvasive Lobular Carcinoma (ILC), a distinct subtype of breast cancer is hallmarked by E-Cadherin loss, slow proliferation, and strong hormone receptor positivity. ILC faces significant challenges in clinical management due to advanced stage at diagnosis, late recurrence, and development of resistance to endocrine therapy - a cornerstone of ILC treatment. To elucidate the mechanisms underlying endocrine resistance in ILC, ILC cell lines (MDA-MB-134-VI, SUM44PE) were generated to be resistant to tamoxifen, a selective estrogen receptor modulator.
View Article and Find Full Text PDFBackground: For patients with head and neck squamous cell carcinoma (HNSCC), failure of definitive radiation combined with cisplatin nearly universally results in death. Although hyperactivation of the Nrf2 pathway can drive radiation and cisplatin resistance along with suppressed anti-tumor immunity, treatment-refractory HNSCC tumors may retain sensitivity to targeted agents secondary to synergistic lethality with other oncogenic drivers (e.g.
View Article and Find Full Text PDFCurr Pharm Des
January 2025
Centre of Experimental Medicine and Surgery, Institute of Medical Sciences, Banaras Hindu University, Varanasi 221005, India.
Introduction: Fungal endophytes have mutualistic associations with the plant's host, communicating through genetic and metabolic processes. As a result, they gain the ability to generate therapeutically effective metabolites and their derivatives.
Methods: The current study aims to assess antioxidant potential along with the identification of robust metabolites within the crude extract of a potent endophytic fungus Xylaria ellisii isolated from leaf tissues of the Acorus calamus Linn plant.
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