Rasmussen Martin, Fredsøe Jacob, Salachan Paul Vinu, Blanke Marcus Pii Lunau, Larsen Stine Hesselby, Ulhøi Benedicte Parm, Jensen Jørgen Bjerggaard, Borre Michael, Sørensen Karina Dalsgaard
Department of Molecular Medicine, Aarhus University Hospital (AUH), Aarhus, Denmark.
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
NPJ Precis Oncol. 2024 Feb 23;8(1):48. doi: 10.1038/s41698-024-00540-x.
Current prognostic tools cannot clearly distinguish indolent and aggressive prostate cancer (PC). We hypothesized that analyzing individual contributions of epithelial and stromal components in localized PC (LPC) could improve risk stratification, as stromal subtypes may have been overlooked due to the emphasis on malignant epithelial cells. Hence, we derived molecular subtypes of PC using gene expression analysis of LPC samples from prostatectomy patients (cohort 1, n = 127) and validated these subtypes in two independent prostatectomy cohorts (cohort 2, n = 406, cohort 3, n = 126). Stroma and epithelium-specific signatures were established from laser-capture microdissection data and non-negative matrix factorization was used to identify subtypes based on these signatures. Subtypes were functionally characterized by gene set and cell type enrichment analyses, and survival analysis was conducted. Three epithelial (E1-E3) and three stromal (S1-S3) PC subtypes were identified. While subtyping based on epithelial signatures showed inconsistent associations to biochemical recurrence (BCR), subtyping by stromal signatures was significantly associated with BCR in all three cohorts, with subtype S3 indicating high BCR risk. Subtype S3 exhibited distinct features, including significantly decreased cell-polarity and myogenesis, significantly increased infiltration of M2-polarized macrophages and CD8 + T-cells compared to subtype S1. For patients clinically classified as CAPRA-S intermediate risk, S3 improved prediction of BCR. This study demonstrates the potential of stromal signatures in identification of clinically relevant PC subtypes, and further indicated that stromal characterization may enhance risk stratification in LPC and may be particularly promising in cases with high prognostic ambiguity based on clinical parameters.
当前的预后工具无法清晰区分惰性和侵袭性前列腺癌（PC）。我们推测，分析局限性前列腺癌（LPC）中上皮和基质成分的个体贡献可以改善风险分层，因为由于对恶性上皮细胞的重视，基质亚型可能被忽视了。因此，我们使用前列腺切除患者的LPC样本（队列1，n = 127）的基因表达分析得出PC的分子亚型，并在两个独立的前列腺切除队列（队列2，n = 406，队列3，n = 126）中验证了这些亚型。从激光捕获显微切割数据中建立了基质和上皮特异性特征，并使用非负矩阵分解基于这些特征识别亚型。通过基因集和细胞类型富集分析对亚型进行功能表征，并进行生存分析。确定了三种上皮（E1-E3）和三种基质（S1-S3）PC亚型。虽然基于上皮特征的亚型分类与生化复发（BCR）的关联不一致，但在所有三个队列中，基于基质特征的亚型分类与BCR显著相关，亚型S3表明BCR风险高。与亚型S1相比，亚型S3表现出不同的特征，包括细胞极性和肌生成显著降低，M2极化巨噬细胞和CD8 + T细胞浸润显著增加。对于临床分类为CAPRA-S中度风险的患者，S3改善了BCR的预测。这项研究证明了基质特征在识别临床相关PC亚型中的潜力，并进一步表明基质特征可能增强LPC的风险分层，并且在基于临床参数具有高预后不确定性的病例中可能特别有前景。
