Identification of Novel Pathways in Plant Lectin-Induced Cancer Cell Apoptosis

Area of Science:

• Biochemistry
• Computational Biology
• Oncology

Background:

• Plant lectins exhibit significant anticancer activities, necessitating further investigation into their molecular mechanisms.
• Understanding these mechanisms is crucial for advancing plant lectins as potential anticancer agents in preclinical and clinical settings.

Purpose of the Study:

• To develop a computational model for predicting protein-protein interactions (PPI) to construct a human PPI network.
• To identify novel plant lectin-induced apoptotic pathways in cancer cells, specifically mesothelioma.
• To discover potential therapeutic targets for plant lectin-based cancer drug discovery.

Main Methods:

• A Naïve Bayesian model was employed to predict protein-protein interactions (PPI) and build a global human PPI network.
• Integration of diverse biological data (SSBP, DDI, gene co-expression, interolog mapping) to construct an apoptotic PPI network.
• Modification of the network for plant lectin-induced apoptotic cell death and identification of 22 apoptotic hub proteins in mesothelioma cells using microarray data.

Main Results:

• A Naïve Bayesian model successfully predicted PPI and constructed a comprehensive human PPI network.
• An integrated apoptotic PPI network was built, specifically adapted to the context of plant lectin-induced apoptosis.
• Twenty-two apoptotic hub proteins were identified in mesothelioma cells, and potential regulatory microRNAs (miRNAs) were predicted.

Conclusions:

• The developed Naïve Bayesian model-based network effectively identifies novel plant lectin-treated cancer cell apoptotic pathways.
• These findings offer valuable insights into plant lectins as potential apoptotic inducers for future cancer drug development.
• The study highlights the utility of computational approaches in uncovering molecular mechanisms of plant-derived anticancer agents.