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Prediction of cell migration potential on human breast cancer cells treated with Albizia lebbeck ethanolic extract
Huzaifa Umar1, Maryam Rabiu Aliyu2, Abdullahi Garba Usman3,4
1Near East University, Operational Research Centre in Healthcare, TRNC Mersin 10, 99138, Nicosia, Turkey. Huzaifa.umar@neu.edu.tr.
Abstract:
Cancer is one of the major causes of death in the modern world, and the incidence varies considerably based on race, ethnicity, and region. Novel cancer treatments, such as surgery and immunotherapy, are ineffective and expensive. In this situation, ion channels responsible for cell migration have appeared to be the most promising targets for cancer treatment. This research presents findings on the organic compounds present in Albizia lebbeck ethanolic extracts (ALEE), as well as their impact on the anti-migratory, anti-proliferative and cytotoxic potentials on MDA-MB 231 and MCF-7 human breast cancer cell lines. In addition, artificial intelligence (AI) based models, multilayer perceptron (MLP), extreme gradient boosting (XGB), and extreme learning machine (ELM) were performed to predict in vitro cancer cell migration on both cell lines, based on our experimental data. The organic compounds composition of the ALEE was studied using gas chromatography-mass spectrometry (GC-MS) analysis. Cytotoxicity, anti-proliferations, and anti-migratory activity of the extract using Tryphan Blue, MTT, and Wound Heal assay, respectively. Among the various concentrations (2.5-200 μg/mL) of the ALEE that were used in our study, 2.5-10 μg/mL revealed anti-migratory potential with increased concentrations, and they did not show any effect on the proliferation of the cells (P < 0.05; n ≥ 3). Furthermore, the three data-driven models, Multi-layer perceptron (MLP), Extreme gradient boosting (XGB), and Extreme learning machine (ELM), predict the potential migration ability of the extract on the treated cells based on our experimental data. Overall, the concentrations of the plant extract that do not affect the proliferation of the type cells used demonstrated promising effects in reducing cell migration. XGB outperformed the MLP and ELM models and increased their performance efficiency by up to 3% and 1% for MCF and 1% and 2% for MDA-MB231, respectively, in the testing phase.
Insights
Albizia lebbeck ethanolic extract (ALEE) shows anti-migratory effects on breast cancer cells without impacting proliferation. Artificial intelligence models, particularly XGBoost, accurately predict this anti-migratory potential, offering a promising avenue for novel cancer therapies.
Area of Science:
- Phytochemistry and Cancer Biology
- Computational Biology and Bioinformatics
Background:
- Cancer remains a leading cause of death, with current treatments facing limitations in efficacy and cost.
- Ion channels regulating cell migration are emerging as critical therapeutic targets for cancer intervention.
- Albizia lebbeck ethanolic extract (ALEE) is investigated for its potential anti-cancer properties.
Purpose of the Study:
- To analyze the organic compounds in ALEE and evaluate its anti-migratory, anti-proliferative, and cytotoxic effects on human breast cancer cell lines (MDA-MB-231 and MCF-7).
- To develop and assess artificial intelligence (AI) models (MLP, XGB, ELM) for predicting the in vitro cancer cell migration based on experimental data.
Main Methods:
- Gas chromatography-mass spectrometry (GC-MS) was used to determine the chemical composition of ALEE.
- In vitro assays including Trypan Blue, MTT, and Wound Heal assays were performed to assess cytotoxicity, proliferation, and migration, respectively.
- AI models (MLP, XGBoost, ELM) were trained and tested using experimental data to predict cell migration.
Main Results:
- ALEE demonstrated significant anti-migratory potential at concentrations of 2.5-10 μg/mL without affecting cell proliferation (P < 0.05).
- The XGBoost model exhibited superior performance in predicting cell migration compared to MLP and ELM, improving accuracy by 1-3% in the testing phase.
- The study identified specific concentrations of ALEE that reduce cancer cell migration while preserving normal cell proliferation.
Conclusions:
- ALEE possesses promising anti-migratory properties against breast cancer cells, offering a potential natural-based therapeutic strategy.
- AI-driven predictive models, especially XGBoost, can effectively forecast the anti-migratory activity of plant extracts.
- Targeting cell migration with compounds like those found in ALEE presents a viable approach for developing novel, less toxic cancer treatments.
