Identifying Essential Genes in Genome-Scale Metabolic Models of Consensus Molecular Subtypes of Colorectal Cancer

This source program is used to identify essential genes, metabolites and reactions for tissue-specific metabolic networks of consensus molecular subtypes of colorectal cancer.  These files are coded by the GAMS software language. The folders are storeed as follows:

/A0-ModelData: A user provides the problem model
/A0-ReportData: Computational results
/Solver: Solver for identifying essential targets

Abstract of the manuscript as follows:

Identifying essential targets in genome-scale metabolic networks of cancer cells is a time-consuming process. This study proposed a fuzzy hierarchical optimization framework for identifying essential genes, metabolites and reactions. On the basis of four objectives, the framework can identify essential targets that lead to cancer cell death, and evaluate metabolic flux perturbations of normal cells due to treatment. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. We applied nested hybrid differential evolution to solve the trilevel MDM problem to identify essential targets in the genome-scale metabolic models of five consensus molecular subtypes (CMSs) of colorectal cancers. We used various media to identify essential targets for each CMS, and discovered that most targets affected all five CMSs and that some genes belonged to a CMS-specific model. We used the experimental data for the lethality of cancer cell lines from the DepMap database to validate the identified essential genes. The results reveal that most of the identified essential genes were compatible to colorectal cancer cell lines from DepMap and that these genes could engender a high percentage of cell death when knocked out, except for EBP, LSS and SLC7A6. The identified essential genes were mostly involved in cholesterol biosynthesis, nucleotide metabolisms, and the glycerophospholipid biosynthetic pathway. The genes in the cholesterol biosynthetic pathway were also revealed to be determinable, if the medium used excluded a cholesterol uptake reaction. By contrast, the genes in the cholesterol biosynthetic pathway were non-essential, if a cholesterol uptake reaction was involved in the medium used. Furthermore, the essential gene CRLS1 was revealed as a medium-independent target for all CMSs irrespective of whether a medium involves a cholesterol uptake reaction.