Identifying genetics biomarkers in correlation with pathological and PSMA PET/CT characteristics in prostate cancer

EJNMMI Research

卷:16

Original Research

Lili Qu¹  Kaiyue Li¹  Muwen Wang²  Yadi Xiao³  Xin Jin⁴  Hang Zhou¹  Lujie Yuan¹  Yuekai Li¹  Shiwei Wang⁵  Rui Li⁵  Marcus Hacker⁶  Xin Li¹  Xiang Li^7,6,8 

[1] Chengwu County People’s Hospital, Heze, China

[2] Evomics Medical Technology Co., Ltd, Shanghai, China

[3] Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Vienna General Hospital, Medical University of Vienna, Vienna, Austria

[4] Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria

[5] Imaging center of Jinan Third People’s Hospital, Jinan, China

[6] Department of Nuclear Medicine, Beijing Chest Hospital, Capital Medical University & Beijing Tuberculosis and Tumor Research Institute, Beijing, China

[7] Department of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China

[8] Department of Nuclear Medicine, Qilu Hospital of Shandong University, #107 Wenhua West Road, 250012, Jinan, Shandong Province, China

关键词: Prostate cancer;    PSMA PET/CT;    Radiogenomics;    mRNA;    Gleason score;   

DOI  :  10.1186/s13550-026-01471-3

 received in 2025-07-25, accepted in 2026-06-09,  发布年份 2026

来源: Springer

【 摘 要 】

BackgroundProstate cancer is a prevalent disease with diverse tumor characteristics that complicate treatment. The integration of spatial patterns from prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT), pathology and expanding genomic data represents a groundbreaking advancement in histo-imaging genomics. The aim of this study was to elucidate the internetwork mapping between genetic biomarkers and PSMA PET/CT imaging in prostate cancer patients.ResultsmRNA sequencing and clinical data from 433 prostate cancer patients were retrieved from The Cancer Genome Atlas (TCGA) database. Differential gene expression between the Gleason score (GS) > 7 and GS ≤ 7 groups was analyzed. Feature selection was performed following the univariate and multivariate logistic regression analyses. A GS predictive model was developed using multivariate logistic regression. Additionally, local samples and images from 27 patients were collected. PSMA PET/CT imaging was performed before radical prostatectomy, and mRNA sequencing of prostate cancer lesions was conducted using next-generation sequencing. Differentially expressed genes identified from the TCGA dataset were subsequently analyzed for correlations with PET-related metrics in the local dataset by utilizing Pearson correlation analysis.Out of the TCGA dataset, 174 genes exhibited differential expression. After feature selection, 53 genes remained. In the local dataset, ten genes (EFNA2, CACNA1I, CA1, MYBPC3, CYP1A1, TLCD3B, LRTM2, GBX2, SPSB4, and GDF3) demonstrated significant associations with PET-related metrics. When comparing the differential expression of genes between the GS>7 and GS≤7 groups, six genes (STMN2, CYP1A1, THRSP, LIPC, GBX2, and SPSB4) in the GS>7 group and eight genes (FBXL16, KLK14, DIRAS2, TERB2, PRAME, UTS2B, UGT2B15, and LINC02798) in the GS≤7 group were significantly correlated with PET-related parameters.ConclusionsThis study identified genetic markers significantly correlated with PSMA PET/CT imaging features in prostate cancer patients. These findings may provide a valuable foundation for optimizing prostate cancer diagnostic procedures and tailoring therapeutic approaches based on genetic and imaging biomarkers.

【 授权许可】

CC BY-NC-ND   
© The Author(s) 2026

【 图 表 】

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