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March 4, 2026Journal of Clinical Oncology0 citations

Insulin pathway changes in localized prostate cancer: A multi-institutional analysis.

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EAEvan AdlerAMAnwaruddin MohammadPKPratyush Kumar

Key Points

  • This research aims to analyze insulin pathway gene expression in localized prostate cancer to better understand progression mechanisms and survival outcomes.
  • Utilized the ORIEN database to analyze gene expression data from localized prostate cancer tumors.
  • Normalized raw count data and identified 176 insulin receptor-related genes for clustering.
  • Applied non-negative matrix factorization (NMF) to classify gene expression into two distinct groups.
  • Conducted Gene Set Enrichment Analysis (GSEA) to compare biological pathways between the groups.
  • Employed Kaplan-Meier curves to assess overall survival for each cluster.
  • Cluster analysis identified two groups: Cluster 1 had decreased PTEN and PIK3R1, and increased AKT1, IRS1/2, FASN, IGFBP2, and MTOR.
  • GSEA showed Cluster 1 exhibited heightened MYC targets, PTEN regulatory signaling, and AKT signaling via MTOR.
  • Median overall survival was 117 months for Cluster 1 and 232 months for Cluster 2, demonstrating a significant difference.

Abstract

380 Background: Prostate cancer is a heterogeneous disease with variable clinical outcomes. If localized, the patient may be cured. However, prostate cancer is lethal if recurrence/progression to metastatic castrate resistant disease occurs. Thus, there is an unmet need to further understand the molecular underpinnings of this progression. Epidemiologic studies show that increased risk of developing and dying from prostate cancer has been associated with elevated serum IGF-1 levels, hyperinsulinemia and metabolic syndrome. Alterations in insulin pathway genes, such as PTEN , FOXO , and PIK3CA , are mutated in up to 32%, 15%, and 11% of localized prostate tumors, respectively. We aimed to further characterize expression of insulin pathway genes in localized prostate cancers in an effort to (1) provide insights into potential mechanisms of progression to metastatic disease and (2) try to further enrich for those prostate tumors that portend worse survival outcomes. Methods: Using the multi-institutional Oncology Research Information Exchange Network (ORIEN) database, gene expression data was analyzed from localized prostate cancer tumors. The raw counts were first normalized, and 176 genes related to the insulin receptor and its downstream pathways were then subset and used for clustering using the non-negative matrix factorization (NMF). The NMF Cluster analysis was performed in an attempt to separate gene expression into two groups. Gene Set Enrichment Analysis (GSEA) was then performed between the two groups that had been separated by cluster analysis to determine homology between other GSEA sets. Kaplan-Meier curves were used to assess median overall survival. Results: Cluster analysis revealed two distinct groups of insulin gene expression, Cluster 1 (n=96) and Cluster 2 (n=337). Compared with Cluster 2, Cluster 1 consisted of decreased expression of PTEN (P<0.001) and PIK3R1 (P<0.001) along with increases in the expression of AKT1 (P<0.001), IRS1/2 (P<0.001), FASN (P<0.001), IGFBP2 (P<0.001), and MTOR (P<0.001). GSEA analysis revealed increased expression of the following pathways in Cluster 1 relative to Cluster 2: MYC targets, PTEN regulatory signaling, and AKT signaling via MTOR . Median overall survival was estimated at 117 months and 232 months for Cluster 1 and Cluster 2, respectively (P<0.05). Conclusions: A subset of localized prostate cancer patients demonstrated linked insulin pathway changes that were associated with worse survival outcomes. This finding suggests that early insulin pathway dysregulation may contribute to risk of metastasis and poor outcomes. These findings support larger studies to determine if insulin pathway changes represent prognostic biomarkers at the localized stage.

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Cite This Study

Adler et al. (2026) studied this question.

synapsesocial.com/papers/69a7cd5ed48f933b5eed9a71https://doi.org/10.1200/jco.2026.44.7_suppl.380
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