Abstract 4758: Identifying metabolic dark matter (unknown) with therapeutic potential in tumor suppressor deficient colorectal cancer cells
Abstract
Numerous unknown features than identified metabolites are detected in untargeted metabolomics experiments. Surprisingly, over 80% of the metabolic features are currently unknown, representing a ‘black hole (dark matter)9 of the metabolic output that is necessary to explore. Unfortunately, research specific to unknown identification and its role in tumor and therapeutics are largely understated. In recent studies, the chemical formula acquired from the high-resolution Mass Spectrometry (MS) detection and further targeted analysis by the Liquid Chromatography-Mass Spectrometry (LC-MS) have been proven useful in confirming the presence and functions of unknown metabolites or their isomers. Emerging evidence indicates that cancer is a metabolic disease and altered metabolism is a cancer hallmark. Genetic alterations including gene loss or gain of function mutations lead to altered metabolic regulation. Tumors frequently mutate genes in order for satisfy growth and survival. For example, tumor suppressor genes such as TP53 and APC are genes with the highest frequency of somatically acquired mutations in diverse cancers. In TCGA colorectal cancer (CRCs), p53 and APC genes show 58% and 81% loss of function mutations, respectively. Tumor suppressor genes with loss of function mutation involve in tumorigenicity of multiple cancers. Therefore, exploring unknown metabolites associated with tumor suppressors has excellent prospect for the discovery of cancer biomarker(s) and therapy. In…
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