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Metabolomics approaches for early cancer diagnosis: a review


Article Information

Title: Metabolomics approaches for early cancer diagnosis: a review

Authors: Ali Zineddine Boumehira, Yasmine Fatima Akchiche, Wissam Cherfi, Oualid Talhi, Reda Djidjik, Daniel Joe Dailin, Ting Ho, Hesham Ali El Enshasy

Journal: Asian Journal of Agriculture and Biology

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
Y 2020-07-01 2021-06-30

Publisher: Asian Journal of Agriculture and Biology

Country: Pakistan

Year: 2022

Volume: 2022

Issue: 4

Language: en

DOI: 10.35495/

Keywords: CancerEarly diagnosisMetabolomicsNMRdna lesions

Categories

Abstract

Cancer remains a major burden on global public health with high mortality rates worldwide. Current diagnosis can detect cancer in late stages when therapy options become limited. Early diagnosis is broadly recognized as the key to a better treatment to save lives. The metabolomics approach provides a better understanding of the different types of cancer. They offer promising and potential interventions in biomarkers discovery which eventually will be better suited for individualized medicine. It elucidates endpoint products for other omic processes while significantly improving the understanding of pathogenesis and mechanisms yet to be discovered. Metabolomics offers a less-invasive, cost-effective for predicting, screening, diagnosis, prognosis, and monitoring therapeutic responses of the disease. There are two methods to study the metabolism and metabolites: targeted and untargeted. The workflow of these approaches requires different analytical platforms, such as Nuclear Magnetic Resonance spectroscopy (NMR), Mass Spectrometry (MS), and different bioinformatic tools. This review provides a systematic summary of metabolomics methods in identifying metabolic biomarkers of cancers (colorectal, prostate, breast, bladder, pancreas, lung, and buccal cancers). In addition, the current review will try to shed light on DNA lesions as a potential metabolic biomarker for cancer.


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