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Utilizing Functional Genomics Screening to Identify Potentially Novel Drug Targets in Cancer Cell Spheroid Cultures

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Computer-Aided Design for Identifying Anticancer Targets in Genome-Scale Metabolic Models of Colon Cancer.

Chao-Ting Cheng¹, Tsun-Yu Wang¹, Pei-Rong Chen¹

¹Department of Chemical Engineering, National Chung Cheng University, Chiayi 62102, Taiwan.

|November 27, 2021

Summary

This study introduces a fuzzy optimization framework to identify anticancer targets, aiming to improve cancer treatment efficacy while minimizing side effects. Combining specific gene targets with metabolic interventions shows greater effectiveness than single-target approaches.

Keywords:

fuzzy optimization metabolite-centric target reaction-centric target two-target combination

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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization

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Published on: October 3, 2025

Area of Science:

Computational Biology
Systems Biology
Drug Discovery

Background:

Efficient discovery of anticancer targets with minimal side effects is crucial for drug development.
Early prediction of drug side effects reduces costs and enhances safety and efficacy.

Purpose of the Study:

To develop a fuzzy optimization framework for Identifying AntiCancer Targets (IACT) using constraint-based models.
To evaluate and minimize cancer cell mortality, normal cell toxicity, and metabolic perturbations.

Main Methods:

Applied fuzzy set theory to assess potential side effects and metabolic deviations.
Utilized a nested hybrid differential evolution algorithm to solve multilevel IACT problems.
Identified gene regulator, metabolite, and reaction-centric targets.

Main Results:

Combined carbon metabolism targets with specific gene targets (sphingolipid, glycerophospholipid, nucleotide, cholesterol biosynthesis, or pentose phosphate pathways) are more effective than single-target inhibition.
A two-target combination of 5-fluorouracil (5-FU) and a folate supplement improved cell viability and reduced side effects in computational models.

Conclusions:

The IACT framework effectively identifies multi-centric targets for improved cancer therapy.
Combined therapeutic strategies, like 5-FU and folate, offer a promising approach to enhance treatment outcomes and patient safety.