Signal Transduction and Targeted Therapy | Glycolytic Heterogeneity Drives Metabolic-Targeted Therapy in Pancreatic Ductal Adenocarcinoma

This study reveals significant glycolytic heterogeneity in pancreatic ductal adenocarcinoma (PDAC), proposes a patient stratification strategy based on glycolytic phenotype, and demonstrates the selective efficacy of LDHA inhibition in high-glycolytic tumors, offering new insights into precision metabolic therapy.

 

Literature Overview

The article "Glycolytic heterogeneity drives metabolic-targeted therapy in pancreatic ductal adenocarcinoma", published in Signal Transduction and Targeted Therapy, reviews and summarizes the spatial distribution characteristics of glycolytic metabolic heterogeneity in pancreatic ductal adenocarcinoma (PDAC), its clinical relevance, and its impact on response to targeted therapies. The study integrates spatial transcriptomics, single-cell RNA sequencing, and multi-omics analyses to systematically map metabolic features of different cell types within the tumor microenvironment, and validates the anti-tumor effects of LDHA inhibition in high-glycolytic subtypes using patient-derived models. It highlights the potential value of metabolic subtyping in prognosis assessment and therapeutic strategy development for PDAC. The paragraph is coherent and logical, ending with a Chinese period.

Background Knowledge

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely low five-year survival rate, primarily due to asymptomatic early stages, late diagnosis, and strong resistance to conventional treatments. Its complex tumor microenvironment (TME) is characterized by a dense stromal barrier, immunosuppressive conditions, and nutrient deprivation, further limiting drug delivery and immune responses. In recent years, metabolic reprogramming has been recognized as one of the hallmarks of cancer. Although PDAC has traditionally been considered reliant on glycolysis for energy, its metabolic heterogeneity remains poorly understood. While previous studies have identified different metabolic subtypes, the lack of spatial resolution and functional validation has hindered the development of precise therapeutic strategies. LDHA (lactate dehydrogenase A) is a key enzyme in the glycolytic pathway responsible for converting pyruvate to lactate. It is highly expressed in various cancers and associated with poor prognosis. However, its heterogeneous expression pattern and potential as a therapeutic target in PDAC remain unclear. This study fills this gap by integrating spatial multi-omics with functional experiments, revealing not only the clinical significance of glycolytic heterogeneity but also providing experimental evidence for targeted intervention, offering new perspectives for overcoming therapeutic resistance in PDAC.

 

 

Research Methods and Experiments

The study first performed single-cell RNA sequencing (scRNA-seq) on 47 PDAC and 16 normal pancreatic tissue samples to define metabolic differences between tumor cells and stromal or immune cell populations. Subsequently, spatial transcriptomic analysis was applied to six primary PDAC tumors to reveal spatial heterogeneity in glycolytic gene expression and its association with tumor stage and immune infiltration. Based on the TCGA database, researchers developed a glycolytic gene expression signature to stratify PDAC patients into high, medium, and low groups, followed by survival analysis and GSEA enrichment analysis to evaluate associations with clinical outcomes, hypoxia status, and molecular subtypes. At the functional level, multiple PDAC cell lines were screened to establish high- and low-glycolysis models. These were treated with an LDHA inhibitor (oxamate) to assess effects on cell proliferation, colony formation, and metabolic flux. Furthermore, 3D organoid models and chick embryo xenograft models were used to validate the anti-tumor efficacy and safety of LDHA inhibition. Finally, integrated metabolomic, proteomic, and lipidomic analyses were performed to systematically dissect the molecular response network in high-glycolysis cells following LDHA inhibition.

Key Conclusions and Perspectives

• Significant glycolytic heterogeneity exists in PDAC tumors, consistent with cellular identity and spatial architecture, and varies substantially across patients
• The high-glycolysis phenotype is significantly associated with tumor progression, an immunosuppressive microenvironment, and poorer clinical outcomes, serving as an independent prognostic biomarker
• High-glycolysis PDAC cells exhibit high sensitivity to LDHA inhibition, whereas low-glycolysis cells are relatively resistant, indicating a therapeutic window
• LDHA inhibition effectively reduces lactate levels in high-glycolysis cells, suppresses proliferation, and induces metabolic reprogramming, shifting cells toward a low-glycolysis phenotype
• Multi-omics analyses show that LDHA inhibition affects not only glycolysis but also regulates key pathways such as hypoxia, unfolded protein response, and mTORC1 signaling, revealing its systemic mechanism of action
• In 3D organoid and chick embryo models, LDHA inhibition significantly suppresses tumor growth without notable toxicity, supporting its therapeutic potential

Research Significance and Prospects

This study overcomes the limitations of traditional bulk sequencing-based metabolic analyses by systematically dissecting glycolytic heterogeneity in PDAC at spatial and single-cell resolution, establishing a direct link between metabolic phenotypes and clinical outcomes. It proposes a patient stratification strategy based on glycolytic activity, offering a new paradigm for precision therapy in PDAC. The validation of LDHA as a potential therapeutic target provides a solid foundation for developing metabolic-targeted drugs.

Future studies could further explore upstream mechanisms driving glycolytic heterogeneity, such as specific signaling pathways or transcription factors. Additionally, the synergistic effects of combining LDHA inhibition with other therapies (e.g., chemotherapy, immunotherapy) should be evaluated. Moreover, developing more specific and stable LDHA inhibitors and advancing them into clinical trials will be critical steps toward clinical translation. This work opens new avenues for metabolic intervention in PDAC and holds promise for improving the treatment landscape of this recalcitrant cancer.

 

 

Conclusion

This study systematically reveals the widespread glycolytic metabolic heterogeneity in pancreatic ductal adenocarcinoma, which is not only closely associated with tumor progression and poor prognosis but also determines differential sensitivity of tumor cells to LDHA inhibition. By integrating spatial transcriptomics, multi-omics analyses, and functional validation, the study establishes glycolytic phenotype as a potential biomarker for patient stratification in PDAC and demonstrates that targeting LDHA can selectively inhibit the growth of high-glycolysis tumors with favorable safety. These findings underscore the importance of metabolic heterogeneity in PDAC treatment decisions and support future individualized therapeutic strategies based on metabolic profiling. LDHA inhibition represents a promising metabolic intervention, particularly for patients with high-glycolysis subtypes. This study provides new insights into overcoming therapeutic resistance in PDAC, advances the field of precision oncology, and offers valuable references for targeted therapy in other metabolically heterogeneous cancers. Follow-up efforts should focus on the development and translational research of clinical-grade LDHA inhibitors to bridge the gap from bench to bedside.

 

Ugo Chianese, Chiara Papulino, Gerardo Saggese, Lucia Altucci, and Rosaria Benedetti. Glycolytic heterogeneity drives metabolic-targeted therapy in pancreatic ductal adenocarcinoma. Signal Transduction and Targeted Therapy.