Decoding and targeting of metabolic heterogeneity in pancreatic neuroendocrine tumors (PanNETs): MCT1 and MCT4 in the crosshair for precision therapy (B01)
Category: Basic Science
Special category: B - Basic Science - In-vitro Models, Tumor Growth, CTCs
Presenting author: Dr Martin Sadowski
Introduction: Mechanisms driving progression from indolent to aggressive and metastatic disease in PanNET are largely unknown. Recent transcriptome and epigenome analyses suggest a stepwise progression model leading to enhanced proliferation, de-differentiation, and metabolic reprogramming. However, the metabolic landscape at different stages and the therapeutic potential of targeting metabolic proteins remain largely uncharacterized.
Aim(s): –
Materials and methods: –
Results: Immunohistochemical analyses of two independent PanNET cohorts (109 and 102 cases) revealed distinctive metabolic subtypes based on the expression of MCT1, MCT4, and CA9—proteins involved in monocarboxylate transport and pH homeostasis. 52% of tumors co-expressed MCT1 and MCT4. Similarly, HIF-1A-regulated MCT4 and CA9 expression strongly correlated with each other and, along with microvessel density assessment, classified PanNET into three subtypes: MCT4-negative tumors (MCT4neg), tumors with hypoxia-induced, intratumoral metabolic heterogeneity (MCT4het+), and tumors with evident pseudohypoxia where MCT4 expression is homogeneously positive (MCT4hom+). Despite their divergent underlying mechanisms, MCT4hom+ and MCT4het+ tumors were significantly associated with features of aggressive disease (T, N, M stage, and early relapse). 2D and 3D cell culture studies, including patient-derived tumoroids, functionally assessed the role of MCT1 and MCT4 and evaluated their potential as therapeutic targets under various oxygen and nutrient conditions and in the context of metabolic heterogeneity.
Conclusion: We discovered that both MCT1 and MCT4 support a glycolytic phenotype through lactate efflux and that co-targeting both transporters is particularly effective in the context of metabolic heterogeneity in PanNET.
Keywords: metabolic heterogeneity, 3d model, precision medicine, metabolic subtype, pannet, hypoxia, lactate efflux, microvessel density, mct1/mct4