Prognostic gene biomarkers for c-Src inhibitor Si162 sensitivity in melanoma cells

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Turkish Journal of Biology, vol.48, no.1, pp.13-23, 2024 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 48 Issue: 1
  • Publication Date: 2024
  • Doi Number: 10.55730/1300-0152.2678
  • Journal Name: Turkish Journal of Biology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, Veterinary Science Database, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.13-23
  • Keywords: c-Src inhibitor, chemotherapy, gene biomarker, Melanoma, si162
  • Lokman Hekim University Affiliated: Yes


Background/aim: Early detection and treatment are crucial in combating malignant melanoma. Src is an important therapeutic target in melanoma due to its association with cancer progression. However, developing effective Src-targeting drugs remains challenging and personalized medicine relies on biomarkers and targeted therapies for precise and effective treatment. This study focuses on Si162, a newly synthesized c-Src inhibitor, to identify reliable biomarkers for predicting Si162 sensitivity and explore associated biological characteristics and pathways in melanoma cells. Materials and methods: Primary melanoma cells (M1, M21, M24, M84, M133, M307, and M2025) were obtained from patients diagnosed with melanoma. Si162 cytotoxicity tests were performed using luminescent adenosine triphosphate detection and the half-maximal inhibitory concentration (IC50) values were calculated. Gene expression profiles were analyzed using microarray-based gene expression data. Differentially expressed genes between the resistant and sensitive groups were identified using Pearson correlation analysis. Gene coexpression, interactions, and pathways were investigated through clustering, network, and pathway analyses. Biological functions were examined using the Database for Annotation, Visualization, and Integrated Discovery. Molecular pathways associated with different responses to Si162 were identified using gene set enrichment analysis. The gene expressions were validated using reverse transcription-quantitative polymerase chain reaction. Results: The cells revealed significant differences in response to Si162 based on the IC50 values (p < 0.05). A total of 36 differentially expressed genes associated with Si162 susceptibility were identified. Distinct expression patterns between the sensitive and resistant groups were observed in 9 genes (LRBA, MGMT, CAND1, ADD1, SETD2, CNTN6, FGF18, C18orf25, and RPL13). Coexpression among the differentially expressed genes was highlighted, and 9 genes associated with molecular pathways, including EMT, transforming growth factor-beta (TGF-β) signaling, and ribosomal protein synthesis, between groups. Genes involved in dysregulated immune response were observed in the resistant group. The involvement of 5 genes (ADD1, CNTN6, FGF18, C18orf25, and RPL13) in Si162 resistance was confirmed through qRT-PCR validation. Conclusion: These findings contribute to our understanding of the underlying biological differences among melanoma cells and suggest potential biomarkers and pathways associated with Si162 response and resistance.