Abstract A067: Precision medicine-oriented analysis of RTK-RAS signaling in gemcitabine-treated pancreatic cancer using conversational artificial intelligence
Camila Cosme, Brigette Waldrup, Francisco G. Carranza, Sophia Manjarrez, Vincent Chung, Laleh Melstrom, Steven Rosen, Enrique Velazquez-VillarrealAbstract
Background:
Although KRAS mutations represent the hallmark genomic alteration in pancreatic ductal adenocarcinoma (PDAC), the broader receptor tyrosine kinase RTK-RAS signaling landscapes underlying differential responses to gemcitabine remain poorly defined.
Methods:
We performed an integrative clinical-genomic analysis of 150 PDAC patients stratified by age at diagnosis and gemcitabine exposure to characterize pathway- and gene-level alterations associated with treatment response. Cohort construction, pathway interrogation, and multidimensional analyses were performed using our AI-HOPE-Pancreas, a conversational artificial intelligence agent developed for precision oncology, with all principal findings independently validated using conventional statistical methods.
Results:
Pathway-level alteration frequencies of RTK-RAS signaling were comparable across age- and treatment-defined subgroups, indicating that global pathway prevalence remained largely stable despite clinical stratification. In contrast, gene-level analyses uncovered distinct molecular architectures associated with both age and gemcitabine exposure. Late-onset gemcitabine-treated tumors demonstrated significant enrichment of ERBB2 and RET alterations. Conversely, TP53 mutations were more prevalent in gemcitabine-treated early-onset disease. Survival analyses further demonstrated that late-onset patients who did not receive gemcitabine and whose tumors lacked RTK-RAS pathway alterations experienced significantly improved overall survival. AI-HOPE-Pancreas enabled rapid clinical cohort generation, pathway-centric interrogation, survival modeling, and multidimensional genomic analyses while producing results consistent with conventional statistical validation.
Conclusions:
RTK-RAS signaling in PDAC extends beyond canonical KRAS mutations and exhibits distinct age- and treatment-dependent molecular architectures with potential prognostic and therapeutic relevance. These findings support pathway-informed patient stratification for precision oncology and demonstrate the utility of conversational artificial intelligence as a scalable platform for integrating multidimensional clinical and genomic data to accelerate hypothesis generation and biomarker discovery in pancreatic cancer.
Citation Format:
Camila Cosme, Brigette Waldrup, Francisco G. Carranza, Sophia Manjarrez, Vincent Chung, Laleh Melstrom, Steven Rosen, Enrique Velazquez-Villarreal. Precision medicine-oriented analysis of RTK-RAS signaling in gemcitabine-treated pancreatic cancer using conversational artificial intelligence [abstract]. In: Proceedings of the AACR Conference on Pancreatic Cancer: New Frontiers in Biology and Therapeutic Development; 2026 Sep 25-28; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(18_Suppl_2):Abstract nr A067.