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Metabolomics of Cancers of the Upper Aerodigestive Tract

Centre Antoine Lacassagne · 2020
ClinicalTrials.gov · Datasets · License: Public Domain · 2020
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Metabolomics, thanks to advances in mass spectrometry, allows for the analysis of cellular metabolites to better understand biological processes. In oncology, it provides a global view of metabolic alterations in tumors and enables the classification of cancers based on various medical parameters using advanced statistical methods (machine learning). Its low cost and speed make it a promising approach in personalized medicine. Cancers of the upper aerodigestive tract (UADT), the fifth most common cancer in France, are often diagnosed late, reducing survival chances (35-50% at five years). Identifying a specific metabolomic signature for these cancers could facilitate early detection, assess treatment response, and rapidly detect recurrences. Additionally, HPV-induced tumors may exhibit a distinct metabolic profile compared to those caused by tobacco and alcohol. Currently, no published studies have explored this topic for UADT cancers, highlighting the need for such research. The aim of this study is to identify a metabolomic signature associated with the presence of UADT cancer at initial diagnosis and during post-therapeutic follow-up (three months after treatment completion). Hypothesis is that a specific metabolomic signature will be observed in the biological samples of patients diagnosed with UADT cancer, that the type of observed signature could be correlated with tumor site, stage, HPV status, and prognosis, and that the persistence or disappearance of this metabolomic signature three months after treatment may be associated with the risk of recurrence. The search for this potential metabolomic signature will be conducted using tumor biopsies, plasma, and urine samples at the initial diagnostic phase and plasma and urine samples at three and six months post-treatment follow-up. Ultimately, the benefits of this study lie in improving early diagnosis, treatment (adjusting treatment based on the prognostic value of specific metabolomic signatures), and follo
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