Related Experiment Video

Updated: Jan 15, 2026

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
13:34

A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds

Published on: April 6, 2016

10.6K

Constraint based modeling of drug induced metabolic changes in a cancer cell line

Xavier Benedicto1, Åsmund Flobak2,3,4, Miguel Ponce-de-Leon5

  • 1Barcelona Supercomputing Center (BSC), Barcelona, Spain.

NPJ Systems Biology and Applications
|October 6, 2025
PubMed

Insights

This study reveals how cancer cells alter metabolism to survive. Combining kinase inhibitors affects specific metabolic pathways, offering new therapeutic strategies for gastric cancer and highlighting drug synergy mechanisms.

Area of Science:

  • Metabolic reprogramming in cancer
  • Cancer cell metabolism and therapy

Background:

  • Cancer cells exhibit altered metabolism to fuel growth and survival.
  • Metabolic pathways are promising therapeutic targets in oncology.
  • Gastric cancer presents a significant clinical challenge.

Purpose of the Study:

  • To investigate the metabolic effects of kinase inhibitors and their combinations in gastric cancer cells.
  • To identify synergistic drug combinations targeting cancer metabolism.
  • To explore metabolic pathway activity using computational methods.

Main Methods:

  • Utilized genome-scale metabolic models and transcriptomic profiling of the AGS gastric cancer cell line.
  • Applied the Tasks Inferrred from Differential Expression (TIDE) algorithm and a variant using task-essential genes.
  • Analyzed metabolic pathway activity changes under various drug treatment conditions.

Main Results:

  • Observed widespread down-regulation of biosynthetic pathways, especially in amino acid and nucleotide metabolism.
  • Identified condition-specific metabolic alterations induced by combinatorial treatments.
  • Found synergistic effects in the PI3K inhibitor-MEK inhibitor (PI3Ki-MEKi) condition impacting ornithine and polyamine biosynthesis.

Conclusions:

  • Metabolic shifts provide insights into mechanisms of drug synergy in gastric cancer.
  • Identified potential therapeutic vulnerabilities related to metabolic pathways.
  • Developed MTEApy, an open-source Python package for TIDE analysis, to enhance reproducibility.

More Related Videos

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo09:19

Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo

Published on: February 6, 2015

9.1K
Mass Spectrometry and Luminogenic-based Approaches to Characterize Phase I Metabolic Competency of In Vitro Cell Cultures10:44

Mass Spectrometry and Luminogenic-based Approaches to Characterize Phase I Metabolic Competency of In Vitro Cell Cultures

Published on: March 28, 2017

10.3K

Related Concept Videos

Treatment Resistant Cancers02:56

Treatment Resistant Cancers

Cancer is the second leading cause of death in the United States. A cancer cell is genetically unstable and hence can mutate faster. They can also modify their microenvironment and escape immune surveillance. The difficulties in treating cancer are further compounded by the emergence of rapid resistance to anticancer drugs. The most common ways to attain resistance in cancer cells include alteration in drug transport and metabolism, modification of drug target, elevated DNA damage response, or...
3.7K
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
5.9K
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
334
Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
6.9K
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
1.9K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
242