Fuzzy multiobjective hierarchical optimization with application to identify antienzymes of colon cancer cells

Wang, Feng‐Sheng; Wang, Tsun-Yu; Wu, Wu‐Hsiung

doi:10.1016/j.jtice.2021.10.021

Cited by 10 publications

(29 citation statements)

References 42 publications

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“…This study presents an anti-cancer target discovery (ACTD) platform for identifying potential candidate targets with few side effects. The platform integrates RNA-seq expressions for cancer cells and their healthy counterparts into the IACT framework [ 39 , 40 ] to yield uniform flux patterns for treated and perturbed cells. We formulated this extended platform as a fuzzy hierarchical optimization problem.…”

Section: Methodsmentioning

confidence: 99%

“…

and

denote the LB and UB of the regulated forward–backward fluxes depended on gene- or metabolite-centric approach for activation. The regulation bounds for the gene-centric approach can be expressed as follows:

where

and

are the basal value of the i th forward–backward flux obtained from XA and HT templates; Ω IZ is the set of reactions regulated by isozymes determined using the GPR associations, and δ is the modulation parameter determined by a nested hybrid differential evolution (NHDE) algorithm [ 39 , 40 , 46 – 48 ]. A reaction catalysed by isozymes remains around its basal level; thus, we set the flux ratio ε to 0.03 in this study to restrict the flux value.…”

Section: Methodsmentioning

confidence: 99%

“…The optimality and limitation of the transformation have been proved in Wang et al . [ 40 ]. The MDM problem is expressed as follows:

where the decision objective η D is a hierarchical criterion.…”

Section: Methodsmentioning

confidence: 99%

“…A study introduced a fuzzy multi-objective optimization framework for identifying anti-cancer targets (IACT) in order to identify targets that not only increase the mortality of cancer cells but also minimize side effects due to treatment [ 39 ]. In addition, the existence and limitations of the IACT framework were theoretically verified [ 40 ]. The IACT framework uses RNA-seq expressions of colon cancer cells and their normal counterparts to reconstruct context-specific genome-scale metabolic networks.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy optimization for identifying anti-cancer targets with few side effects in constraint-based models of head and neck cancer

Wang

Chen

et al. 2022

R. Soc. open sci.

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Computer-aided methods can be used to screen potential candidate targets and to reduce the time and cost of drug development. In most of these methods, synthetic lethality is used as a therapeutic criterion to identify drug targets. However, these methods do not consider the side effects during the identification stage. This study developed a fuzzy multi-objective optimization for identifying anti-cancer targets that not only evaluated cancer cell mortality, but also minimized side effects due to treatment. We identified potential anti-cancer enzymes and antimetabolites for the treatment of head and neck cancer (HNC). The identified one- and two-target enzymes were primarily involved in six major pathways, namely, purine and pyrimidine metabolism and the pentose phosphate pathway. Most of the identified targets can be regulated by approved drugs; thus, these drugs are potential candidates for drug repurposing as a treatment for HNC. Furthermore, we identified antimetabolites involved in pathways similar to those identified using a gene-centric approach. Moreover, HMGCR knockdown could not block the growth of HNC cells. However, the two-target combinations of ( UMPS , HMGCR ) and ( CAD , HMGCR ) could achieve cell mortality and improve metabolic deviation grades over 22% without reducing the cell viability grade.

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Section: Methodsmentioning

confidence: 99%

“…

and

where

and

Section: Methodsmentioning

confidence: 99%

“…The optimality and limitation of the transformation have been proved in Wang et al . [ 40 ]. The MDM problem is expressed as follows:

where the decision objective η D is a hierarchical criterion.…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fuzzy optimization for identifying anti-cancer targets with few side effects in constraint-based models of head and neck cancer

Wang

Chen

et al. 2022

R. Soc. open sci.

Self Cite

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“…We developed a systems biology program that automatically builds stoichiometric and reduced GPR models in the files of the General Algebraic Modeling System (GAMS, https://www.gams.com/) for computation. The detailed procedures are discussed in another study [25].…”

Section: Tissue-specific Genome-scale Metabolic Modelsmentioning

confidence: 99%

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

Cheng

Lai

Chang

et al. 2022

Preprint

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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.

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Cell‐specific genome‐scale metabolic modeling of SARS‐CoV‐2‐infected lung to identify antiviral enzymes

Chen,

Wang

2023

FEBS Open Bio

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Computational systems biology plays a key role in the discovery of suitable antiviral targets. We designed a cell‐specific, constraint‐based modeling technique for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2)‐infected lungs. We used the gene sequence of the alpha variant of SARS‐CoV‐2 to build a viral biomass reaction. We also used the mass proportion of lipids between the viral biomass and its host cell to estimate the stoichiometric coefficients of viral lipids in the reaction. We then integrated the viral biomass reaction, the gene expression of the alpha variant of SARS‐CoV‐2, and the generic human metabolic network Recon3D to reconstruct a cell‐specific genome‐scale metabolic model. An antiviral target discovery (AVTD) platform was introduced using this model to identify therapeutic drug targets for combating COVID‐19. The AVTD platform not only identified antiviral genes for eliminating viral replication but also predicted side effects of treatments. Our computational results revealed that knocking out dihydroorotate dehydrogenase (DHODH) might reduce the synthesis rate of cytidine‐5’‐triphosphate and uridine‐5’‐triphosphate, which terminate the viral building blocks of DNA and RNA for SARS‐CoV‐2 replication. Our results also indicated that DHODH is a promising antiviral target that causes minor side effects, which is consistent with the results of recent reports. Moreover, we discovered that the genes that participate in the de novo biosynthesis of glycerophospholipids and ceramides become unidentifiable if the viral biomass reaction does not involve the stoichiometry of lipids.

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Fuzzy multiobjective hierarchical optimization with application to identify antienzymes of colon cancer cells

Cited by 10 publications

References 42 publications

Fuzzy optimization for identifying anti-cancer targets with few side effects in constraint-based models of head and neck cancer

Fuzzy optimization for identifying anti-cancer targets with few side effects in constraint-based models of head and neck cancer

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

Cell‐specific genome‐scale metabolic modeling of SARS‐CoV‐2‐infected lung to identify antiviral enzymes

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