What does this research mean for the field?

A novel five-gene glutamine metabolism-based prognostic signature accurately stratifies prostate cancer risk, and targeting this metabolic vulnerability with a cisplatin and glutaminase inhibitor co-delivery nanoplatform synergistically suppresses tumor growth. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop a prognostic signature based on glutamine metabolism for prostate cancer and translate this into a targeted therapy approach.

April 20, 2026Discover Oncology0 citationsOpen Access

Integration of a glutamine metabolism-based prognostic signature and a synergistic nanotherapeutic strategy targeting metabolic vulnerabilities in prostate cancer

WLWenya LiSecond Hospital of Tianjin Medical University WGWeiying GeSecond Hospital of Tianjin Medical University WNWenjie NiSecond Hospital of Tianjin Medical University

Key Points

To develop a prognostic signature based on glutamine metabolism for prostate cancer and translate this into a targeted therapy approach.
Analyzed transcriptomic data from TCGA for dysregulated genes in glutamine metabolism.
Constructed a prognostic model using univariate Cox, LASSO, and multivariate Cox regression.
Validated the model in an independent cohort and assessed characteristics like tumor microenvironment and mutation burden.
Engineered a CB/CDDP@lipo nanoplatform to co-deliver cisplatin and glutaminase inhibitor CB-839 in prostate cancer models.
Established a five-gene prognostic signature that stratifies patients based on progression-free interval.
Identified high-risk patients with an immunosuppressive tumor microenvironment and higher tumor mutation burden.
Validated ASNS as a key driver of tumor cell proliferation, migration, and invasion.
Demonstrated that the nanoplatform induced significant apoptosis and tumor suppression with a favorable safety profile.

Abstract

Prostate cancer (PCa) clinical management is challenged by tumor heterogeneity, driving the need for robust prognostic biomarkers, with altered glutamine metabolism emerging as a promising target. This investigation aimed to construct a metabolism-based prognostic signature for PCa and translate it into a targeted nanotherapeutic strategy. Transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to identify dysregulated glutamine metabolism genes and construct a prognostic model via univariate Cox, LASSO, and multivariate Cox regression with validation in an independent cohort. The model’s characteristics were assessed through tumor microenvironment (TME), tumor mutation burden (TMB), and consensus clustering analyses. The pivotal gene of the model was selected to functionally validate in vitro through proliferation, clonogenicity, migration, and invasion assays. To exploit this vulnerability, a CB/CDDP@lipo nanoplatform was engineered to co-deliver cisplatin and glutaminase inhibitor CB-839, with evaluation in PCa models in vitro and in vivo. A novel five-gene prognostic signature (ASNS, ATP2B4, GLYATL1, SLC6A20, SLC7A9) was established and stratified PCa patients into high- and low-risk groups based on progression-free interval (PFI). High-risk patients exhibited an immunosuppressive TME, higher TMB and TP53 mutations, and activation of proliferation-related pathways. Functional validation identified ASNS as a key oncogenic driver, enhancing PCa tumor cell proliferation, migration, and invasion. Therapeutically, CB/CDDP@lipo nanoplatform demonstrated potent synergistic cytotoxicity by depleting glutathione (GSH) and amplifying oxidative stress. This dual-action mechanism triggered significant apoptosis and tumor suppression with a favorable safety profile. Our study establishes a glutamine metabolism-based prognostic signature, pinpointing ASNS as a key driver. The resulting CB/CDDP@lipo nanoplatform offers a promising chemo-metabolic strategy for enhanced PCa treatment.

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