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<p>Head and neck squamous cell carcinoma (HNSCC) is a complex multivariable disease posing a significant challenge in therapeutics. OXPHOS and PPP are centrally implicated in metabolic heterogeneity influencing tumor behavior, treatment response, and patient outcomes. This study aims to stratify HNSCC based on OXPHOS and PPP gene expression to construct a clinical outcome risk predictive model. HNSCC patients were stratified into four metabolic subtypes including mixed, OXPHOS-leaning, PPP-leaning, and quiescent. The quiescent metabolic subtype showed longest survival with lower proliferation scores, whereas mixed subtype showed the worst survival with higher proliferation scores. Metabolic proteins of the CPTAC and ICPC cohorts affirmed the existence of metabolic heterogeneity among tumor samples. A prognostic risk predictive model was developed based on thirteen genes, which performed better than the OXPHOS-PPP-glycolysis model and other predictive forty-seven metabolic gene’s model. Existence of metabolic heterogeneity was successfully determined in HNSCC. OXPHOS and PPP genes enriched in mixed metabolic subtype having the worst clinical outcome are suggestive of higher metastatic potential, which might offer advisement in personalized therapeutics.</p><p></p>

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Metabolic gene expression-based stratification and prognostic risk predictive model of head and neck squamous cell carcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月25日

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  • Soumya Sau,
  • Anjali Gupta,
  • Swastik Sinha,
  • S. M. Azeem Mohiyuddin,
  • Arvind M. Korwar

摘要

Head and neck squamous cell carcinoma (HNSCC) is a complex multivariable disease posing a significant challenge in therapeutics. OXPHOS and PPP are centrally implicated in metabolic heterogeneity influencing tumor behavior, treatment response, and patient outcomes. This study aims to stratify HNSCC based on OXPHOS and PPP gene expression to construct a clinical outcome risk predictive model. HNSCC patients were stratified into four metabolic subtypes including mixed, OXPHOS-leaning, PPP-leaning, and quiescent. The quiescent metabolic subtype showed longest survival with lower proliferation scores, whereas mixed subtype showed the worst survival with higher proliferation scores. Metabolic proteins of the CPTAC and ICPC cohorts affirmed the existence of metabolic heterogeneity among tumor samples. A prognostic risk predictive model was developed based on thirteen genes, which performed better than the OXPHOS-PPP-glycolysis model and other predictive forty-seven metabolic gene’s model. Existence of metabolic heterogeneity was successfully determined in HNSCC. OXPHOS and PPP genes enriched in mixed metabolic subtype having the worst clinical outcome are suggestive of higher metastatic potential, which might offer advisement in personalized therapeutics.