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. 2025 Jan 15;26(2):679.
doi: 10.3390/ijms26020679.

Clinical and Genomic Features of Androgen Indifferent Prostate Cancer

Jack Masur  1 , Aakrosh Ratan  2 , Krzysztof Wierbilowicz  3 , Adanma Ayanambakkam  4 , Michelle L Churchman  5 , Laura S Graham  6 , George Daniel Grass  7 , Sumati Gupta  8 , Sean Q Kern  9 , Jennifer King  10 , Zin Myint  11 , Robert J Rounbehler  5 , Bodour Salhia  12 , Eric A Singer  13 , Yousef Zakharia  14 , Bryce M Paschal  3 , Paul V Viscuse  1
Affiliations

Clinical and Genomic Features of Androgen Indifferent Prostate Cancer

Jack Masur et al. Int J Mol Sci. .

Abstract

Androgen-indifferent prostate cancer (AIPC) is increasingly common and particularly lethal. Data describing these tumors are sparse, and AIPC remains a poorly understood malignancy. Utilizing the Oncology Research Information Exchange Network (ORIEN) database, we enriched for tumors with features of AIPC using previously described characteristics. Our AIPC cohort included three subgroups: aggressive variant prostate cancer (AVPC), neuroendocrine PC (NEPC), and double-negative PC (DNPC). Of 1496 total PC patients available for analysis, we identified 323 (22%) as MCRPC. Of those, 39 (12%) met AIPC criteria (17 AVPC, 13 NEPC, 9 DNPC) and 284 (88%) were non-AIPC. Forty-three percent of AIPC patients had de novo metastatic disease vs. 15% for non-AIPC (p = 0.003). Homologous recombination deficiency (HRD) and tumor mutational burden (TMB) did not differ between cohorts, but microsatellite instability scores (MSI) were significantly higher in AIPC (p = 0.019). Using Gene Set Enrichment Analysis (GSEA), we found that genes defining response to androgens and genes involved in oxidative phosphorylation were the most downregulated, whereas genes involved in epithelial-mesenchymal transition (EMT) and immune signaling were significantly upregulated in AIPC vs. non-AIPC. Our study demonstrates the potential for predefined criteria that aim to enrich for AIPC and suggests opportunities for therapeutic investigation.

Keywords: androgen-indifferent prostate cancer; biomarkers; genomics; molecular biology; prostate cancer; therapeutic targets.

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Conflict of interest statement

A.R. reports a consulting or advisory role with MedGenome and research funding from AstraZeneca/MedImmune. A.A. reports a consulting or advisory role with AVEO and Pfizer/Astellas. L.S.G. reports research funding from Merck, Pfizer, Seattle Genetics, and Johnson and Johnson. G.D.G. reports a consulting or advisory role with MyCareGorithm and stock/other ownership interests in Lantheus Medical Imaging, Editas Medicine, Intellia Therapeutics, G1 Therapeutics, Halozyme, and GlycoMimetics. S.G. reports stock/other ownership interests with Salarius Pharmaceuticals and research funding from Mirati Therapeutics, Novartis, Pfizer, Viralytics, Hoosier Cancer Research Network, Rexahn Pharmaceuticals, Five Prime Therapeutics, Incyte, MedImmune, Merck, Bristol-Myers Squibb, Clovis Oncology, LSK BioPharma, QED Therapeutics, Daiichi Sankyo/Lilly, Immunocore, Seagen, AstraZeneca, Acrotech Biopharma, and EMD Serono. Z.M. reports research funding from Merck. B.S. reports a consulting or advisory role with AstraZeneca and stock/other ownership interests with CpG Diagnostics Inc. A.S. reports a consulting or advisory role with Aura Biosciences and research funding from Astellas Medivation. Y.Z. reports a consulting or advisory role with Roche/Genentech, Eisai, Amgen, Castle Biosciences, Novartis, Exelixis, Pfizer, Cardinal Health, Bayer, Janssen, TTC Oncology, Clovis Oncology, EMD Serono, Seagen, Bristol-Myers Squibb/Medarex, Myovant Sciences, Genzyme, Gilead Sciences, AstraZeneca, and Array BioPharma and research funding from Pfizer, Exelixis, and Eisai. All the other authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Results of AIPC enrichment query among all patients with prostate cancer in ORIEN database.
Figure 2
Figure 2
Differentially expressed genes in AIPC vs. non-AIPC: (A) Gene expression (mRNA) in AIPC vs. non-AIPC. (B) GSEA of hallmark performed on differentially expressed genes (AIPC vs. non-AIPC) detected by the Wilcoxon test (padj < 0.05). (C) Selected results of GSEA of Pathway Interaction Database (PID) performed on differentially expressed genes (AIPC vs. non-AIPC) detected by the Wilcoxon test (padj < 0.05).
Figure 3
Figure 3
AR-associated gene expression (mRNA) in AIPC vs. Non-AIPC.
Figure 4
Figure 4
TMPRSS2-ERG gene fusions in AIPC vs. Non-AIPC.
Figure 5
Figure 5
The cumulative distribution of MSI scores reported by ORIEN using MSIsensor2. The dotted line is the tool’s threshold to call a tumor MSI-positive.
See this image and copyright information in PMC

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