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Metabolism‐Based Molecular Subtyping Endows Effective Ketogenic Therapy in p53‐Mutant Colon Cancer

Authors: Meng Tang; Hui Xu; Hongyan Huang; Hao Kuang; Chenxi Wang; Qinqin Li; Xin Zhang; +17 Authors

Metabolism‐Based Molecular Subtyping Endows Effective Ketogenic Therapy in p53‐Mutant Colon Cancer

Abstract

AbstractAlthough targeting cancer metabolism is a promising therapeutic strategy, clinical success depends on accurate molecular and metabolic subtyping. Here, this study reports two metabolism‐based molecular subtypes associated with the ketogenic treatment of colon cancer: glycolytic (glycolysis+/ketolysis−) and ketolytic (glycolysis+/ketolysis+), which are manifested by distinct profiles of metabolic enzymes and mitochondrial dysfunction, and by different responses to ketone‐containing interventions in vitro and in vivo. Notably, the glycolytic subtype is able to be transformed into the ketolytic subtype in p53‐mutated tumors upon glucose limitation, rendering resistance to ketogenic therapy associated with upregulation of ketolytic enzymes, such as OXCT1 by mutant p53. The allosteric activator of mutant p53 effectively blocks the rewired molecular expression and the reprogrammed metabolism, leading to the suppression of tumor growth. The findings highlight the utility of metabolic subtyping to guide ketogenic therapy in colon cancer and identify mutant p53 as a synthetic lethality target for ketogenic treatment.

Keywords

p53, ketogenic therapy, Science, Q, Ketone Bodies, Ketones, Glucose, colon cancer, Colonic Neoplasms, Humans, Tumor Suppressor Protein p53, OXCT1, Research Articles, metabolic subtype

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    11
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Average
Top 10%
Green
gold