ArticleFrontiers in oncology2023
Metabolic classification of non-small cell lung cancer patient-derived xenografts by a digital pathology approach: A pilot study.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 2 citations in OpenAlex.
- Clinical Trials and Translational Advances in Metabolic Targeting.Cancer treatment and research · 2026Review
- CIP2A induces PKM2 tetramer formation and oxidative phosphorylation in non-small cell lung cancer.Cell discovery · 2024Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
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Abstract
Introduction: Genetically characterized patient-derived tumor xenografts (PDX) are a valuable resource to understand the biological complexity of cancer and to investigate new therapeutic approaches. Previous studies, however, lack information about metabolic features of PDXs, which may limit testing of metabolism targeting drugs. Methods: In this pilot study, we investigated by immunohistochemistry (IHC) expression of five essential metabolism-associated markers in a set of lung adenocarcinoma PDX samples previously established and characterized. We exploited digital pathology to quantify expression of the markers and correlated results with tumor cell proliferation, angiogenesis and time of PDX growth in mice. Results: Our results indicate that the majority of the analyzed PDX models rely on oxidative phosphorylation (OXPHOS) metabolism, either alone or in combination with glucose metabolism. Double IHC enabled us to describe spatial expression of the glycolysis-associated monocarboxylate transporter 4 (MCT4) marker and the OXPHOS-associated glutaminase (GLS) marker. GLS expression was associated with cell proliferation and with expression of liver-kinase B1 (LKB1), a tumor suppressor involved in the regulation of multiple metabolic pathways. Acetyl CoA carboxylase (ACC) was associated with the kinetics of PDX growth. Conclusion: Albeit limited by the small number of samples and markers analyzed, metabolic classification of existing collections of PDX by this mini panel will be useful to inform pre-clinical testing of metabolism-targeting drugs.
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