Evaluation and Targeting of the Metabolic Signature of Human Pancreatic Ductal Adenocarcinoma Subtypes

by Teona Midelashvili
Cumulative thesis
Date of Examination:2024-11-06
Date of issue:2025-03-13
Advisor:PD Dr. Dr. Lena-Christin Conradi
Referee:Prof. Dr. Argyris Papantonis
Referee:Prof. Dr. Frauke Alves
Referee:Prof. Dr. Elisabeth Hessmann
Referee:Prof. Dr. Andreas Fischer
Referee:Prof. Dr. Michael Altenbuchinger
Persistent Address: http://dx.doi.org/10.53846/goediss-11153

 

 

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Abstract

English

Pancreatic ductal adenocarcinoma (PDAC) presents significant therapeutic challenges due to its pronounced tumor heterogeneity and complex metabolic reprogramming within the tumor microenvironment. In this study, advanced spatial RNA sequencing was utilized to stratify PDAC into two distinct molecular subtypes: a basal subtype, marked by upregulated glycolytic pathways, and a classical subtype, characterized by enhanced lipid metabolism. An in-depth analysis of the metabolic landscape revealed the roles of various cell types within the tumor microenvironment in promoting tumor progression and influencing treatment response. Spatial transcriptomics identified congruent marker genes across PDAC patients, including novel candidates such as MLPH, offering new avenues for exploration in early detection and therapeutic intervention. Further investigation into the metabolic behaviors of these subtypes was conducted using integrative experimental approaches, including multiplexed immunofluorescence staining and in vitro studies with patient-derived organoids and 2D cell lines. Targeting metabolic pathways emerged as a promising therapeutic strategy, with the inhibition of glycolysis using the small-molecule inhibitor KAN0438757 resulting in a metabolic shift from the aggressive basal subtype to the less aggressive classical phenotype. This shift was accompanied by significant reductions in tumor proliferation and survival, underscoring the potential of metabolic interventions as a therapeutic approach. Overall, this research emphasizes the importance of targeting specific metabolic vulnerabilities in PDAC subtypes, offering a foundation for more personalized and effective treatment strategies. By leveraging advanced spatial technologies and patient-derived models, these findings contribute to a deeper understanding of PDAC heterogeneity and open new possibilities for improving patient outcomes through tailored therapeutic approaches.
Keywords: Pancreatic ductal adenocarcinoma; spatial transcriptomics; classical and basal subtypes; metabolism; glycolysis; PFKFB3; KAN0438757