# A systematic characterization of amino acid metabolism–related genes reveals molecular subtypes and a prognostic signature in bladder cancer

**Authors:** Junrui He, Xu Liu, Shirui Li, Zhongyou Xia, Xiaojun Tan, Lijuan Peng, Qiongxian Long, Ji Wu

PMC · DOI: 10.3389/fonc.2026.1754912 · 2026-02-27

## TL;DR

This study identifies key amino acid metabolism genes in bladder cancer, revealing distinct subtypes and a 16-gene prognostic signature that could guide treatment decisions.

## Contribution

The study introduces a novel 16-gene metabolic signature for bladder cancer prognosis and identifies PSPH as a key driver of tumor progression.

## Key findings

- Two distinct metabolic subtypes were identified, with one linked to poor survival and immune dysfunction.
- A 16-gene signature showed strong prognostic performance across multiple datasets and predicted response to therapies.
- PSPH was validated as overexpressed in tumors and shown to promote cancer cell proliferation and survival.

## Abstract

Amino acid metabolism is integral to tumor proliferation, redox control, and immune regulation. Yet, studies in bladder cancer have largely centered on single amino acids, leaving the broader metabolic gene network insufficiently characterized.

Transcriptomic and clinical data from TCGA-BLCA, GSE13507, and GSE32894 were integrated with 32 MSigDB amino acid metabolism gene sets. Differential analysis, enrichment profiling, and consensus clustering defined metabolic subtypes. WGCNA and survival filtering identified candidates for a prognostic model, which was optimized using the MIME platform. Immune features and drug sensitivities were evaluated through multiple deconvolutions and pharmacogenomic resources. Single-cell data (GSE222315) were used to trace the cellular origin of model genes. PSPH expression and function were validated in tissues and bladder cancer cell lines.

A total of 144 dysregulated amino acid metabolism–related genes were identified and used to define two distinct metabolic subtypes. One subtype was marked by coordinated upregulation of glutamine, branched-chain amino acid, tryptophan, and serine metabolic programs, accompanied by higher grade and stage, significantly worse survival, and dense but functionally impaired immune infiltration. From 24 candidate genes, a 16-gene metabolic signature was constructed and consistently validated across TCGA, GSE13507, and GSE32894, showing strong and stable prognostic performance superior to several published models. High-risk group displayed activation of cell-cycle, DNA-replication, mTORC1, and inflammatory-stress pathways, together with predicted sensitivity to PI3K/mTOR inhibitors, DNA-damaging agents, and selected epigenetic or cytoskeletal drugs. In the IMvigor210 cohort, the high-risk group showed a greater likelihood of responding to PD-1/PD-L1 blockade. Single-cell profiling localized signature expression predominantly to malignant epithelial cells. PSPH, a core model gene, was overexpressed in tumor tissues and cell lines, and functional assays demonstrated its role in promoting proliferation, migration, invasion, and survival of bladder cancer cells.

This study highlights the central role of amino acid metabolic networks in shaping bladder cancer heterogeneity and provides a metabolically grounded framework for risk stratification and therapeutic development.

## Linked entities

- **Genes:** PSPH (phosphoserine phosphatase) [NCBI Gene 5723]
- **Diseases:** bladder cancer (MONDO:0004986)

## Full-text entities

- **Genes:** MTOR (mechanistic target of rapamycin kinase) [NCBI Gene 100127359] {aka FRAP1}, CD274 (CD274 molecule) [NCBI Gene 574058] {aka PDL1}, PSPH (phosphoserine phosphatase) [NCBI Gene 100316854]
- **Diseases:** tumor (MESH:D009369), bladder cancer (MESH:D001749), inflammatory (MESH:D007249)
- **Chemicals:** serine (MESH:D012694), amino (-), branched-chain amino acid (MESH:D000597), glutamine (MESH:D005973), Amino acid (MESH:D000596), tryptophan (MESH:D014364)

## Figures

10 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12982074/full.md

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Source: https://tomesphere.com/paper/PMC12982074