Related Experiment Video
Updated: Jul 29, 2025
Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
Published on: July 22, 2020
Identifying essential genes in genome-scale metabolic models of consensus molecular subtypes of colorectal cancer
Chao-Ting Cheng1, Jin-Mei Lai2, Peter Mu-Hsin Chang3,4
1Department of Chemical Engineering, National Chung Cheng University, Chiayi, Taiwan.
Abstract:
Identifying essential targets in the genome-scale metabolic networks of cancer cells is a time-consuming process. The present study proposed a fuzzy hierarchical optimization framework for identifying essential genes, metabolites and reactions. On the basis of four objectives, the present study developed a framework for identifying essential targets that lead to cancer cell death and evaluating metabolic flux perturbations in normal cells that have been caused by cancer 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 genome-scale metabolic models for five consensus molecular subtypes (CMSs) of colorectal cancer. We used various media to identify essential targets for each CMS and discovered that most targets affected all five CMSs and that some genes were CMS-specific. We obtained experimental data on 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 with the colorectal cancer cell lines obtained from DepMap and that these genes, with the exception of EBP, LSS, and SLC7A6, could generate a high level of cell death when knocked out. The identified essential genes were mostly involved in cholesterol biosynthesis, nucleotide metabolisms, and the glycerophospholipid biosynthetic pathway. The genes involved in the cholesterol biosynthetic pathway were also revealed to be determinable, if a cholesterol uptake reaction was not induced when the cells were in the culture medium. However, the genes involved in the cholesterol biosynthetic pathway became non-essential if such a reaction was induced. Furthermore, the essential gene CRLS1 was revealed as a medium-independent target for all CMSs.
Insights
This study introduces a fuzzy optimization framework to identify essential genes in colorectal cancer, pinpointing targets crucial for cell death and validating them with experimental data. The findings highlight key metabolic pathways and medium-dependent targets for personalized cancer therapy.
Area of Science:
- Computational Biology
- Systems Biology
- Cancer Metabolism
Background:
- Identifying essential targets in cancer's genome-scale metabolic networks is challenging and time-consuming.
- Existing methods require significant computational resources and time for accurate target identification.
Purpose of the Study:
- To develop a fuzzy hierarchical optimization framework for identifying essential genes, metabolites, and reactions in cancer.
- To identify targets leading to cancer cell death and evaluate metabolic perturbations in normal cells during treatment.
- To analyze essential targets across five consensus molecular subtypes (CMSs) of colorectal cancer.
Main Methods:
- A fuzzy hierarchical optimization framework was developed based on four objectives.
- A multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem using fuzzy set theory.
- Nested hybrid differential evolution was employed to solve the MDM problem for genome-scale metabolic models of colorectal cancer CMSs.
Main Results:
- Most identified essential targets affected all five colorectal cancer CMSs, with some being CMS-specific.
- Experimental validation using DepMap data confirmed the lethality of most identified essential genes upon knockout.
- Essential genes were primarily involved in cholesterol biosynthesis, nucleotide metabolism, and glycerophospholipid biosynthesis, with CRLS1 identified as a medium-independent target.
Conclusions:
- The fuzzy hierarchical optimization framework effectively identifies essential targets in colorectal cancer metabolism.
- Metabolic pathway essentiality can be medium-dependent, particularly for cholesterol biosynthesis genes.
- The study provides a valuable resource for developing targeted cancer therapies by identifying CMS-specific and general essential genes.
Related Concept Videos
01:05Cancer-Critical Genes II: Tumor Suppressor Genes
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...
01:33Cancer-Critical Genes I: Proto-oncogenes
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...