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Integrative Analysis Combining Machine Learning and Functional Experiments Uncovers ISG15 As a Key Determinant of
Weiwei Wang1,2, Haiquan Ling3,4, Songhao Hu5
1Jinan University, Guangzhou, P.R. China.
Background/Aim:
Cisplatin resistance remains a major obstacle in advanced gastric cancer (GC). This study aimed to identify key molecular determinants of cisplatin resistance, with a focus on interferon-stimulated genes (ISGs), and to systematically investigate the functional role of interferon-stimulated gene 15 (ISG15) in mediating chemoresistance.
Materials And Methods:
Candidate genes associated with cisplatin resistance were first identified through transcriptomic profiling of gastric cancer tissues. An integrative machine learning framework was applied to prioritize these genes: least absolute shrinkage and selection operator (LASSO) regression extracted genes with the highest predictive potential, support vector machine recursive feature elimination (SVM-RFE) ranked genes by their influence on classification precision, and random forest (RF) analysis evaluated the relative importance of each gene across multiple decision trees. Top candidates from these complementary approaches were further validated both bioinformatically and experimentally in normal gastric epithelial cells (GES-1), cisplatin-sensitive (AGS), and cisplatin-resistant (AGS/DDP) cells. Functional validation was conducted using siRNA-mediated knockdown to assess effects on cell viability, colony formation, migration, and cisplatin sensitivity.
Results:
ISG15, OAS2, IFI44, and IFIT3 were identified as central hub genes. Experimental validation confirmed marked upregulation of these genes at both mRNA and protein levels in AGS/DDP cells, with ISG15 showing the most prominent and dose-dependent induction upon cisplatin exposure. Functional assays demonstrated that ISG15 knockdown significantly reduced cell viability, colony formation, and migration, while enhancing cisplatin sensitivity.
Conclusion:
ISG15 functions as a central regulator of cisplatin resistance and tumor progression in GC. The study highlights the effectiveness of integrating machine learning-driven candidate prioritization with functional validation to identify clinically relevant therapeutic targets.
Insights
Interferon-stimulated gene 15 (ISG15) drives cisplatin resistance in gastric cancer. Targeting ISG15 may overcome chemoresistance and improve treatment outcomes for advanced gastric cancer patients.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Cisplatin resistance is a significant challenge in treating advanced gastric cancer (GC).
- Interferon-stimulated genes (ISGs) are implicated in cellular responses to chemotherapy.
- Identifying key regulators of chemoresistance is crucial for developing effective therapies.
Purpose of the Study:
- To identify molecular determinants of cisplatin resistance in GC, focusing on ISGs.
- To investigate the functional role of interferon-stimulated gene 15 (ISG15) in mediating chemoresistance.
Main Methods:
- Transcriptomic profiling and machine learning (LASSO, SVM-RFE, RF) to identify candidate genes.
- Bioinformatic and experimental validation in GC cell lines (AGS, AGS/DDP).
- siRNA-mediated knockdown to assess ISG15 function in cell viability, colony formation, migration, and cisplatin sensitivity.
Main Results:
- ISG15, OAS2, IFI44, and IFIT3 were identified as central hub genes.
- ISG15 was significantly upregulated in cisplatin-resistant GC cells and induced by cisplatin.
- ISG15 knockdown reduced cell viability, migration, and enhanced cisplatin sensitivity.
Conclusions:
- ISG15 is a key regulator of cisplatin resistance and tumor progression in GC.
- Machine learning combined with functional validation effectively identifies therapeutic targets.
- ISG15 represents a potential therapeutic target for overcoming cisplatin resistance in gastric cancer.
