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放射转录组学鉴定了新的 mRNA 和 miRNA 标志物,可用于区分前列腺癌和良性前列腺增生。

Radiotranscriptomics identified new mRNAs and miRNA markers for distinguishing prostate cancer from benign prostatic hyperplasia.

机构信息

Department of Ultrasound, Air Force Medical Center, PLA, Air Force Military Medical University, Beijing, China.

Department of Ultrasound, First Medical Center, Chinese PLA General Hospital, Beijing, China.

出版信息

Cancer Med. 2023 Dec;12(24):21694-21708. doi: 10.1002/cam4.6728. Epub 2023 Nov 21.

DOI:10.1002/cam4.6728
PMID:37987209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10757143/
Abstract

The present study investigated ultrasound (US) phenotypes reflecting prostate cancer (PCa)-related genetic mutations. Herein, integration of radiotranscriptomic data, US and contrast-enhanced ultrasound (CEUS) radiomic images, and RNA sequencing was performed with the aim of significantly improving the accuracy of PCa prognosis. We performed radiotranscriptomic analysis of clinical, imaging, and two genomic (mRNA and microRNA expression) datasets from 48 and 22 men with PCa and benign prostatic hyperplasia (BPH), respectively. Twenty-three US texture features and four microvascular perfusion features were associated with various patterns of 52 differentially expressed genes related to PCa (p < 0.05); 17 overexpressed genes were associated with two key texture features. Twelve overexpressed genes were identified using microvascular perfusion features. Furthermore, mRNA and miRNA biomarkers could be used to distinguish between PCa and BPH. Compared with RNA sequencing, B-mode and CEUS features reflected genomic alterations associated with hormone receptor status, angiogenesis, and prognosis in patients with PCa. These findings indicate the potential of US to assess biomarker levels in patients with PCa.

摘要

本研究调查了反映前列腺癌(PCa)相关基因突变的超声(US)表型。在此,通过整合放射转录组数据、US 和对比增强超声(CEUS)放射组图像以及 RNA 测序,旨在显著提高 PCa 预后的准确性。我们对来自 48 名 PCa 患者和 22 名良性前列腺增生(BPH)患者的临床、影像学以及两个基因组(mRNA 和 microRNA 表达)数据集进行了放射转录组分析。与 52 个与 PCa 相关的差异表达基因(p<0.05)的各种模式相关的 23 个 US 纹理特征和 4 个微血管灌注特征;17 个过表达基因与两个关键纹理特征相关。使用微血管灌注特征鉴定出 12 个过表达基因。此外,mRNA 和 miRNA 生物标志物可用于区分 PCa 和 BPH。与 RNA 测序相比,B 模式和 CEUS 特征反映了与 PCa 患者激素受体状态、血管生成和预后相关的基因组改变。这些发现表明 US 有潜力评估 PCa 患者的生物标志物水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/b1ab72fc7383/CAM4-12-21694-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/7e6bb7a4e200/CAM4-12-21694-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/16e43e5eb551/CAM4-12-21694-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/24eaf8822329/CAM4-12-21694-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/63c901baed27/CAM4-12-21694-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/25f218c0687b/CAM4-12-21694-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/b1ab72fc7383/CAM4-12-21694-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/7e6bb7a4e200/CAM4-12-21694-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/16e43e5eb551/CAM4-12-21694-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/24eaf8822329/CAM4-12-21694-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/63c901baed27/CAM4-12-21694-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/25f218c0687b/CAM4-12-21694-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae67/10757143/b1ab72fc7383/CAM4-12-21694-g004.jpg

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本文引用的文献

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Identification of candidate hub genes correlated with the pathogenesis, diagnosis, and prognosis of prostate cancer by integrated bioinformatics analysis.通过综合生物信息学分析鉴定与前列腺癌发病机制、诊断和预后相关的候选枢纽基因。
Transl Cancer Res. 2022 Oct;11(10):3548-3571. doi: 10.21037/tcr-22-703.
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Ultrasound-based radiomics score for pre-biopsy prediction of prostate cancer to reduce unnecessary biopsies.
基于超声的放射组学评分用于前列腺癌的活检前预测,以减少不必要的活检。
Prostate. 2023 Jan;83(1):109-118. doi: 10.1002/pros.24442. Epub 2022 Oct 7.
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Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI.新兴的磁共振方法通过多参数 MRI 提高前列腺癌的诊断准确性。
MAGMA. 2022 Aug;35(4):587-608. doi: 10.1007/s10334-022-01031-5. Epub 2022 Jul 22.
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Dynamic expression of SNAI2 in prostate cancer predicts tumor progression and drug sensitivity.SNAI2 在前列腺癌中的动态表达预测肿瘤进展和药物敏感性。
Mol Oncol. 2022 Jul;16(13):2451-2469. doi: 10.1002/1878-0261.13140. Epub 2022 Feb 11.
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A New Approach for Prostate Cancer Diagnosis by miRNA Profiling of Prostate-Derived Plasma Small Extracellular Vesicles.基于前列腺来源的血浆小细胞外囊泡 miRNA 谱分析进行前列腺癌诊断的新方法。
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