Mining cancer genomes for change-of-metabolic-function mutations

Area of Science:

• Biochemistry
• Computational Biology
• Medicinal Chemistry

Background:

• Novel enzymes are crucial for advancing organic synthesis techniques.
• Cancer mutations can alter protein function and cellular metabolism, offering a source of new enzymatic capabilities.
• Current methods for producing valuable chemicals like xanthosine are often unsustainable.

Purpose of the Study:

• To develop a computational tool, METIS (Mutated Enzymes from Tumors In silico Screen), for identifying metabolism-altering cancer mutations.
• To discover novel enzymes with potential applications in green chemistry and therapeutics.
• To catalog potentially useful cancer mutations for broader scientific use.

Main Methods:

• Developed METIS, a computational screen utilizing mutation recurrence rates and protein structure to identify functional alterations.
• Screened 298,517 cancer mutations to identify 48 candidate mutations.
• Performed unbiased metabolomic profiling of cells expressing a candidate mutant (OGDHLp.A400T).
• Expanded the METIS screen to 49 million cancer mutations for a refined candidate list.

Main Results:

• Identified 48 candidate cancer mutations with potential to alter enzymatic function.
• Demonstrated that the OGDHLp.A400T mutant enhances in vitro production of xanthosine.
• Validated METIS's capability to identify functionally significant mutations from large cancer genomic datasets.

Conclusions:

• METIS is an effective tool for discovering novel enzymes from cancer mutations.
• Identified mutations can be leveraged for sustainable chemical production (green chemistry) and therapeutic development.
• The METIS approach provides a valuable resource for both biotechnological innovation and cancer research.