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Targeting G6PD (Glucose-6-Phosphate Dehydrogenase) as a Biomarker of Therapeutic Vulnerability in Renal Cell Carcinoma.

Created on 17 Sep 2026

Authors

Daniel Pinheiro Ferreira, Ana Carolina Souza Mizael, Julia Victória Bonifácio Cabrieira, Rafaela Viviane Neves Silva, Liliane Silvano Araújo, Crislaine Aparecida Silva, Karen Bento Ribeiro, Adilha Misson Rua Michelleti, Juliana Reis Machado, Régia Caroline Peixoto Lira

Published in

International journal of molecular sciences. Volume 27. Issue 6. Mar 20, 2026. Epub Mar 20, 2026.

Abstract

Renal cell carcinoma (RCC) is the most common kidney cancer, with increasing global incidence. Despite advances with VEGF-targeted tyrosine kinase inhibitors (TKIs) and immunotherapies, therapeutic resistance remains frequent, limiting long-term benefits. This highlights the need for potential biomarkers of tumor aggressiveness and therapeutic candidates, such as glucose-6-phosphate dehydrogenase (G6PD), whose altered expression has been associated with several cancers. We evaluated G6PD gene and protein expression in 121 RCC samples through immunohistochemistry and assessed functional role in vitro approaches. 786-O and ACHN cells were treated with the inhibitor G6PDi-1 and the anti-VEGF cabozantinib/lenvatinib. G6PD mRNA levels were higher in tumors than in non-neoplastic tissues, indicating shorter overall survival in clear cell (ccRCC) and papillary (pRCC) subtypes. Immunolabeling confirmed a higher expression in pRCC and associations with pathological features. CRISPR and RNAi datasets revealed a stronger G6PD dependency in the ccRCC. A high gene expression was observed in lenvatinib non-responder cell lines, and DepMap dose-response curves indicated modest responses to VEGF inhibitors. In vitro, ACHN was more sensitive to VEGF inhibition, particularly cabozantinib, whereas G6PDi-1 had stronger effects in 786-O, impairing viability, migration, and clonogenic capacity. Our findings support G6PD as a biomarker of tumor aggressiveness and G6PDi-1 as a potential therapeutic in RCC models.

PMID:
41898704
Bibliographic data and abstract were imported from PubMed on 17 Sep 2026.

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