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高分化G1胰腺神经内分泌肿瘤的mRNA谱与免疫组化谱相关:病例报告

mRNA profiling of a well-differentiated G1 pancreatic NET correlates with immunohistochemistry profile: a case report.

作者信息

Venugopal Abhirami, Gillick-Walker Jessie, Michalczyk Agnes, Khasraw Mustafa, Ackland M Leigh

机构信息

Centre for Cellular and Molecular Biology, School of Life and Environmental Sciences, Deakin University, Burwood, VIC, 3125, Australia.

Duke University Medical Center, Durham, NC, 27710, USA.

出版信息

BMC Gastroenterol. 2021 Apr 27;21(1):194. doi: 10.1186/s12876-021-01705-9.

DOI:10.1186/s12876-021-01705-9
PMID:33906633
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8080317/
Abstract

BACKGROUND

Neuroendocrine neoplasms (NENs) are a complex group of tumours that occur in many organs. Routinely used IHC markers for NEN diagnosis include CgA, synaptophysin, Ki67 and CD56. These have limitations including lack of correlation to clinical outcomes and their presence in non-tumour tissue. Identification of additional markers and more quantitative analyses of tumour tissue has the potential to contribute to improved clinical outcomes. We used qRT-PCR to profile the expression levels of a panel of markers in tumour and matched non-tumour tissue from a patient with a G1 pancreatic neuroendocrine tumour. Differences in mRNA levels between tumour and non-tumour tissue were compared with IHC analyses of the same sample.

CASE PRESENTATION

An elderly man presented with lower abdominal pain for 6 months. Histological analysis identified a low grade, well differentiated pancreatic endocrine neoplasm. Twenty-seven tumour markers for neuroendocrine status, proliferation, stem cell phenotype, angiogenesis, epithelial to mesenchymal transition, cell adhesion, differentiation and tumour suppression were selected from previous studies and mRNA levels of these markers were measured in tumour and adjacent non-tumour tissue sample using qRT-PCR. IHC was carried out on the same tissue to detect the corresponding marker proteins. Of the markers analysed, seven showed higher mRNA levels in tumour relative to non-tumour tissue while thirteen had lower expression in tumour relative to non-tumour tissue. Substantial differences in mRNA levels were a gain of CgA, CD56, β-catenin, CK20, PDX1 and p53 and loss of Ki67, PCAD, CK7, CD31, MENA, ECAD, EPCAM, CDX2 and CK6. Comparison of qRT-PCR data with IHC showed correlation between fifteen markers.

CONCLUSION

Our study is unique as it included matched controls that provided a comparative assessment for tumour tissue analysis, whereas many previous studies report tumour data only. Additionally, we utilised qRT-PCR, a relatively quantitative diagnostic tool for differential marker profiling, having the advantage of being reproducible, fast, cheap and accurate. qRT-PCR has the potential to improve the defining of tumour phenotypes and, in combination with IHC may have clinical utility towards improving tumour stratification or distinguishing tumour grades. The results need to be validated with different grades of NENs and related to clinical outcomes.

摘要

背景

神经内分泌肿瘤(NENs)是一组发生于多个器官的复杂肿瘤。常用于NEN诊断的免疫组化(IHC)标志物包括嗜铬粒蛋白A(CgA)、突触素、Ki67和CD56。这些标志物存在局限性,包括与临床结局缺乏相关性以及在非肿瘤组织中也有表达。鉴定额外的标志物并对肿瘤组织进行更定量的分析可能有助于改善临床结局。我们使用定量逆转录聚合酶链反应(qRT-PCR)分析了一名G1级胰腺神经内分泌肿瘤患者的肿瘤组织及配对的非肿瘤组织中一组标志物的表达水平。将肿瘤组织和非肿瘤组织之间mRNA水平的差异与同一样本的IHC分析结果进行比较。

病例介绍

一名老年男性因下腹部疼痛6个月就诊。组织学分析确定为低级别、高分化的胰腺内分泌肿瘤。从先前的研究中选取了27种用于评估神经内分泌状态、增殖、干细胞表型、血管生成、上皮-间质转化、细胞黏附、分化和肿瘤抑制的肿瘤标志物,使用qRT-PCR测定这些标志物在肿瘤组织和相邻非肿瘤组织样本中的mRNA水平。对同一组织进行IHC检测以检测相应的标志物蛋白。在所分析的标志物中,7种在肿瘤组织中的mRNA水平相对于非肿瘤组织更高,而13种在肿瘤组织中的表达相对于非肿瘤组织更低。mRNA水平存在显著差异的有CgA、CD56、β-连环蛋白、细胞角蛋白20(CK20)、胰腺十二指肠同源盒1(PDX1)和p53升高,以及Ki67、前列腺癌相关抗原(PCAD)、细胞角蛋白7(CK7)、CD31、膜突蛋白(MENA)、上皮钙黏蛋白(ECAD)、上皮细胞黏附分子(EPCAM)、尾型同源盒转录因子2(CDX2)和细胞角蛋白6(CK6)降低。qRT-PCR数据与IHC结果的比较显示15种标志物之间存在相关性。

结论

我们的研究具有独特性,因为它纳入了配对对照,为肿瘤组织分析提供了对比评估,而许多先前的研究仅报告肿瘤数据。此外,我们使用了qRT-PCR,这是一种用于差异标志物分析的相对定量诊断工具,具有可重复、快速、廉价和准确的优点。qRT-PCR有潜力改善肿瘤表型的界定,并且与IHC相结合可能在改善肿瘤分层或区分肿瘤分级方面具有临床应用价值。这些结果需要在不同级别的NENs中进行验证并与临床结局相关联。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/8080317/b245c9abe022/12876_2021_1705_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/8080317/e631eb2022a3/12876_2021_1705_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/8080317/40b7f15e8296/12876_2021_1705_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/8080317/b245c9abe022/12876_2021_1705_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/8080317/e631eb2022a3/12876_2021_1705_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/8080317/40b7f15e8296/12876_2021_1705_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8871/8080317/b245c9abe022/12876_2021_1705_Fig3_HTML.jpg

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