2023
DOI: 10.1200/jco.2023.41.4_suppl.tps758
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A phase I study of a mutant KRAS-targeted long peptide vaccine in patients at high risk of developing pancreatic cancer.

Abstract: TPS758 Background: KRAS mutations are identified in the majority of premalignant lesions that precede pancreatic ductal adenocarcinoma (PDAC). Arising during tumorigenesis, mutant KRAS (mKRAS) neoantigens are less susceptible to central tolerance mechanisms and serve as ideal vaccine targets. Indeed, targeting mKRAS neoantigens with vaccines has shown promising anti-tumor activity in the preclinical setting. For instance, our group previously demonstrated that a Listeria-based vaccine targeting mKRAS G12D com… Show more

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“…As our understanding of the complex interplay between the immune system and pancreatic cancer continues to evolve, the field of pancreatic cancer immunotherapy is positioned at the forefront of cutting-edge research. These groundbreaking domains of research, such as machine learning and artificial intelligence [ 547 ], mutant KRAS peptide-driven vaccines and personalized RNA neo-antigen vaccines [ 401 , 548 ], single-cell multi-omics-oriented approaches [ 546 , 549 ], and CRISPR/Cas-based RNA editing [ 550 ], are of utmost importance as they define the active research areas of the future, paving the way for gaining better clinical outcomes. Given the role of artificial intelligence in cancer research, researchers used machine learning to analyze complex tumor molecular data from pancreatic cancer patients and found that anti-CD40 therapy reduced T-cell exhaustion in the TME.…”
Section: Discussionmentioning
confidence: 99%
“…As our understanding of the complex interplay between the immune system and pancreatic cancer continues to evolve, the field of pancreatic cancer immunotherapy is positioned at the forefront of cutting-edge research. These groundbreaking domains of research, such as machine learning and artificial intelligence [ 547 ], mutant KRAS peptide-driven vaccines and personalized RNA neo-antigen vaccines [ 401 , 548 ], single-cell multi-omics-oriented approaches [ 546 , 549 ], and CRISPR/Cas-based RNA editing [ 550 ], are of utmost importance as they define the active research areas of the future, paving the way for gaining better clinical outcomes. Given the role of artificial intelligence in cancer research, researchers used machine learning to analyze complex tumor molecular data from pancreatic cancer patients and found that anti-CD40 therapy reduced T-cell exhaustion in the TME.…”
Section: Discussionmentioning
confidence: 99%