Bustos Matias A, Chong Kelly K, Koh Yoko, Kim SooMin, Ziarnik Eleanor, Ramos Romela I, Jimenez Gianna, Krasne David L, Allen Warren M, Wilson Timothy G, Hoon Dave S B
Department of Translational Molecular Medicine, Saint John's Cancer Institute (SJCI) at Providence Saint John's Health Center (SJHC), Santa Monica, California, USA.
Department of Urology and Urologic Oncology, SJCI at Providence SJHC, Santa Monica, California, USA.
Clin Transl Med. 2025 Apr;15(4):e70288. doi: 10.1002/ctm2.70288.
Nomograms or comparable techniques can be used to determine which patients with prostate cancer (PCa) will benefit from extended pelvic lymph node dissection (ePLND). While nomograms help guide clinical decisions, ∼80% of the patients undergo unnecessary ePLND. This pilot study aims to identify both transcriptomic mRNA and microRNA (miR) signatures in primary PCa tumours that are associated with the presence of lymph node metastasis (LNM).
Primary PCa tumours obtained from 88 patients (pathologically diagnosed as N0 [pN0, n = 44] or as N1 [pN1, n = 44]) were profiled using two different probe-based captured direct assays based on next-generation sequencing and targeting 19398 mRNA transcripts (human transcriptome panel [HTP] dataset) and 2083 miRs (miRs whole-transcriptome assay [WTA] dataset). The TCGA-PRAD (pN0 [n = 382] and pN1 [n = 70]) and GSE220095 (pN0 [n = 138] and pN1 [n = 17]) datasets were used for validation using bioinformatic analyses.
A four-mRNA signature (CHRNA2, NPR3, VGLL3 and PAH) was found in primary tumour tissue samples from pN1 PCa patients, and then it was validated using the TCGA-PRAD and GSE220095 datasets. Adding serum prostate-specific antigen (PSA) values to the four-gene signature increased the performance to identify pN1 (HTP [AUC = .8487, p = 2.18e-09], TCGA-PRAD [AUC = .7150, p = 8.66e-08] and GSE220095 datasets [AUC = .8772, p = 4.09e-07]). Paired miR analyses showed that eight miRs were significantly upregulated in primary PCa that were pN1 (p < .01). The eight-miR signature performance increased when adding PSA (WTA dataset [AUC = .8626, p = 4.66e-10]) or Grade group (WTA dataset [AUC = .8689, p = 2e-10]). When combining the miR/mRNA signatures (miR-663b, CHRNA2 and PAH) with PSA levels, it showed the best performance to distinguish pN1 from pN0 PCa patients.
This study found miR/mRNA signatures in primary PCa tumours that in combination with serum PSA levels may complement nomograms for better detection of PCa patients with LNM and triage patients into better surgical decision-making.
Primary prostate cancer (PCa) tumours from patients pathologically diagnosed as N0 (pN0) or N1 (pN1) were dually assessed for microRNA (miRs) and mRNA levels using an NGS-based assay. A four-mRNA and an eight-miRNA signature were found. The mRNA signatures were further validated using two datasets. The combination of serum prostate-specific antigen (PSA) levels or Grade Group with the miR/mRNA signatures separates pN1 from pN0 PCa patients.
列线图或类似技术可用于确定哪些前列腺癌（PCa）患者将从扩大盆腔淋巴结清扫术（ePLND）中获益。虽然列线图有助于指导临床决策，但约80%的患者接受了不必要的ePLND。这项初步研究旨在确定原发性PCa肿瘤中与淋巴结转移（LNM）存在相关的转录组mRNA和微小RNA（miR）特征。
使用基于下一代测序的两种不同的基于探针捕获的直接检测方法，对从88例患者（病理诊断为N0 [pN0，n = 44] 或N1 [pN1，n = 44]）获得的原发性PCa肿瘤进行分析，靶向19398个mRNA转录本（人类转录组面板 [HTP] 数据集）和2083个miR（miR全转录组分析 [WTA] 数据集）。使用生物信息学分析，将TCGA-PRAD（pN0 [n = 382] 和pN1 [n = 70]）和GSE220095（pN0 [n = 138] 和pN1 [n = 17]）数据集用于验证。
在pN1 PCa患者的原发性肿瘤组织样本中发现了一个四mRNA特征（CHRNA2、NPR3、VGLL3和PAH），然后使用TCGA-PRAD和GSE220095数据集进行了验证。将血清前列腺特异性抗原（PSA）值添加到四基因特征中，提高了识别pN1的性能（HTP [AUC = 0.8487，p = 2.18e-09]，TCGA-PRAD [AUC = 0.7150，p = 8.66e-08] 和GSE220095数据集 [AUC = 0.8772 p = 4.09e-07]）。配对miR分析表明，在pN1的原发性PCa中，有8个miR显著上调（p < 0.01）。添加PSA（WTA数据集 [AUC = 0.8626，p = 4.66e-10]）或分级组（WTA数据集 [AUC = 0.8689，p = 2e-10]）时，八miR特征性能提高。当将miR/mRNA特征（miR-663b、CHRNA2和PAH）与PSA水平相结合时，它在区分pN1和pN0 PCa患者方面表现出最佳性能。
本研究在原发性PCa肿瘤中发现了miR/mRNA特征，其与血清PSA水平相结合可能补充列线图，以便更好地检测有LNM的PCa患者，并将患者分类以做出更好的手术决策。
使用基于NGS的检测方法对病理诊断为N0（pN0）或N1（pN1）的患者的原发性前列腺癌（PCa）肿瘤进行miR和mRNA水平的双重评估。发现了一个四mRNA和一个八miRNA特征。使用两个数据集对mRNA特征进行了进一步验证。血清前列腺特异性抗原（PSA）水平或分级组与miR/mRNA特征的组合将pN1与pN0 PCa患者区分开来。
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