| Timetable |
| Download Conference Program |
| Download All Abstracts |
| Zoom Access |
| Corporate Program |
Poster Presentations
Day 4, June 25（Wed.）
Room P (Maesato East, Foyer, Ocean Wing)
- 4P-PM-24
Development of Phosphoproteomics Prediction Model for Next-line Therapy in TKI-Resistant Non-Small Cell Lung Cancer
(1NTU Chem, 2IoC, 3NTNU, 4NTU CliLab)
oIrene-Ya Tai1,2, Chiao-Chun Chang2, Shen-Shian Chan1,2, Yu-Hsuan Lin2,3, Yi-Ju Chen2, Sung-Liang Yu4, Yu-Ju Chen1,2
This study employed a library-enhanced DIA pipeline, integrating DDA to construct a spectral library of 74,763 phosphopeptides from 23 EGFR-TKI-resistant NSCLC cell lines. Pervanadate-treated PC9 cells enhanced tyrosine phosphopeptide detection by 85.8%. Differential phosphoproteomic signatures were identified for five FDA-approved drugs (Afatinib, Osimertinib, Neratinib, Trametinib, Dasatinib) and systematically correlated with drug response datasets. Spearman correlation coefficients (-0.54 to 0.59) indicated predictive potential, further supported by deep learning models. Validation with nine additional resistant cell lines confirmed the approach's robustness. Notably, Dasatinib's limited efficacy was reflected in correlation patterns, highlighting the relevance of phosphoproteomics for personalized treatment strategies in TKI-resistant NSCLC.