PO.CL12.04 · 临床研究

影像不可见前列腺肿瘤的多组学表征揭示PET可视性的微环境驱动因素

Multi-omic characterization of imaging invisible prostate tumors reveals microenvironmental drivers of PET visibility

海报缩略图:影像不可见前列腺肿瘤的多组学表征揭示PET可视性的微环境驱动因素
编号 2613 展板 4 时间 4/20 09:00–12:00 区域 Section 47 主讲 Jiyoun Seo, MS;PhD
分会场 Molecular Imaging, Radiomics, and Theranostics
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作者与单位 Authors & Affiliations

Jiyoun Seo1, Raag Agrawal2, Pranav Movva1, Camille Motchoffo Simo1, Paul C. Boutros3

1Cedars-Sinai Medical Center, Los Angeles, CA,2University of California, Los Angeles, Los Angeles, CA,3Sanford Burnham Prebys, La Jolla, CA

摘要 Abstract

中文摘要
背景:高达20%的侵袭性局限性前列腺肿瘤在PSMA PET或MRI上不可见,限制了诊断准确性和治疗选择。由于这两种影像模态在新诊断患者中被常规使用,明确影像可视性的分子基础对于影像驱动的精准医学至关重要。尽管既往有证据提示间质和代谢通路的参与,但影像可视性的生物学机制尚未通过直接关联的多组学数据得以阐明。为此,我们分析了具有配对影像和多组学谱的前列腺肿瘤,以界定PET和MRI可视性背后的分子程序。 方法:从59名前列腺切除术前接受配对PSMA PET和MRI检查的患者中获取了共71个2-3级组(grade group 2-3)前列腺肿瘤。宏观解剖的肿瘤区域接受了bulk RNA测序、靶向DNA测序和蛋白质组学分析。使用多变量模型检验与PET SUVmax和MRI可视性(PIRADS≥4)的关联,并对临床病理特征进行校正(FDR>0.05)。使用预排序GSEA结合MSigDB Hallmark、KEGG和Reactome注释,对排序后的检验统计量进行基因集富集分析。将一致的分子特征在DNA和蛋白数据集之间交叉参照,以识别与影像可视性一致相关的通路。 结果:MRI不可见的肿瘤表现出增殖和代谢通路的下调,包括DNA修复和糖酵解,与静息表型一致。PET可视性与转录和代谢活跃状态相关。此外,RNA、DNA和蛋白质组学的整合分析共同指向细胞外基质重塑和免疫调节过程为PSMA PET信号强度的主要相关因素,表明间质和免疫结构决定了影像可检测性。表面组(surfaceome)分析进一步凸显了参与基质和免疫相互作用的细胞表面蛋白,可作为PSMA低表达肿瘤中PET成像的候选替代生物标志物。 结论:这些数据表明,PSMA PET可视性反映了以DNA损伤反应和细胞外基质重塑为特征的生物学活跃肿瘤状态,而MRI不可见则对应于一种更静息且代谢受抑的表型。整合的分子与表面组分析表明,间质和免疫改变促成PSMA摄取和影像可检测性。总之,这些发现支持将影像可视性作为一种由生物学驱动的标志物,具有优化风险评估和指导前列腺癌精准管理的潜力。
查看英文原文 English abstract
Background: Up to 20% of aggressive localized prostate tumors are invisible on PSMA PET or MRI, limiting diagnostic accuracy and treatment selection. As both imaging modalities are routinely used in newly diagnosed patients, defining the molecular basis of imaging visibility is critical for imaging-driven precision medicine. Despite prior evidence implicating stromal and metabolic pathways, the biology of imaging visibility has not been resolved using directly linked multi-omic data. To address this, we analyzed prostate tumors with matched imaging and multi-omic profiles to define molecular programs underlying PET and MRI visibility. Methods: A total 71 grade group 2-3 prostate tumors were obtained from 59 patients who underwent paired PSMA PET and MRI before prostatectomy. Macrodissected tumor regions underwent bulk RNA sequencing, targeted DNA sequencing, and proteomics. Associations with PET SUVmax and MRI visibility (PIRADS≥4) were tested using multivariable models adjusting for clinico-pathologic features (FDR>0.05). Gene set enrichment was performed on ranked test statistics using preranked GSEA with MSigDB Hallmark, KEGG, and Reactome annotations. Concordant molecular features were cross-referenced across DNA and protein datasets to identify pathways consistently associated with imaging visibility. Results: MRI-invisible tumors showed downregulation of proliferative and metabolic pathways, including DNA repair and glycolysis, consistent with a quiescent phenotype. PET visibility was associated with transcriptionally and metabolically active states. Furthermore, integrative RNA, DNA, and proteomic analyses converged on extracellular matrix remodeling and immune-regulatory processes as major correlates of PSMA PET signal intensity, indicating that stromal and immune architecture shape imaging detectability. Surfaceome profiling further highlighted cell-surface proteins involved in matrix and immune interactions as candidate alternative biomarkers for PET imaging in PSMA low tumors. Conclusions: These data suggest PSMA PET visibility reflects biologically active tumor states characterized by DNA damage response and extracellular matrix remodeling, while MRI invisibility corresponds to a more quiescent and metabolically repressed phenotype. Integrated molecular and surfaceome analyses indicate that stromal and immune alterations contribute to PSMA uptake and imaging detectability. Together, these findings support imaging visibility as a biologically driven marker with potential to refine risk assessment and guide precision management in prostate cancer.
利益披露 Disclosure
J. Seo, None.. R. Agrawal, None.. P. Movva, None.. C. M. Simo, None.. P. C. Boutros, None.

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