Suppr超能文献

一种确定转移性神经内分泌肿瘤未知原发部位的实用方法。

A practical method to determine the site of unknown primary in metastatic neuroendocrine tumors.

作者信息

Maxwell Jessica E, Sherman Scott K, Stashek Kristen M, O'Dorisio Thomas M, Bellizzi Andrew M, Howe James R

机构信息

Department of General Surgery, University of Iowa Carver College of Medicine, Iowa City, IA.

Department of Pathology, University of Pennsylvania, Philadelphia, PA.

出版信息

Surgery. 2014 Dec;156(6):1359-65; discussion 1365-6. doi: 10.1016/j.surg.2014.08.008. Epub 2014 Nov 11.

Abstract

INTRODUCTION

The site of a primary neuroendocrine tumor (NET) tumor is unknown before treatment in approximately 20% of small bowel (SBNET) and pancreatic (PNET) cases despite extensive workup. It can be difficult to discern a PNET from an SBNET on hematoxylin and eosin stains, and thus, more focused diagnostic tests are required. Immunohistochemistry (IHC) and gene expression profiling are two methods used to identify the tissue of origin from biopsied metastases.

METHODS

Tissue microarrays were created from operative specimens and stained with up to seven antibodies used in the NET-specific IHC algorithm. Expression of four genes for differentiating between PNETs and SBNETs was determined by quantitative polymerase chain reaction and then used in a previously validated gene expression classifier (GEC) algorithm designed to determine the primary site from gastrointestinal NET metastases.

RESULTS

The accuracy of the IHC algorithm in identifying the primary tumor site from a set of 37 metastases was 89%, with only one incorrect call. Three other samples were indeterminate as the result of pan-negative staining. The GEC's accuracy in a set of 136 metastases was 94%. The algorithm identified the primary tumor site in all cases in which IHC failed.

CONCLUSION

Performing IHC, followed by GEC for indeterminate cases, identifies accurately the primary site in SBNET and PNET metastases in virtually all patients.

摘要

引言

尽管进行了广泛的检查,但在大约20%的小肠神经内分泌肿瘤(SBNET)和胰腺神经内分泌肿瘤(PNET)病例中,原发性神经内分泌肿瘤(NET)的肿瘤部位在治疗前仍不明确。在苏木精和伊红染色上,很难将PNET与SBNET区分开来,因此,需要更有针对性的诊断测试。免疫组织化学(IHC)和基因表达谱分析是用于从活检转移灶中识别组织起源的两种方法。

方法

从手术标本中制作组织微阵列,并用NET特异性IHC算法中使用的多达七种抗体进行染色。通过定量聚合酶链反应确定用于区分PNET和SBNET的四个基因的表达,然后将其用于先前验证的基因表达分类器(GEC)算法中,该算法旨在从胃肠道NET转移灶中确定原发部位。

结果

IHC算法从一组37个转移灶中识别原发肿瘤部位的准确率为89%,只有一次错误判断。另外三个样本因全阴性染色而无法确定。GEC在一组136个转移灶中的准确率为94%。该算法在所有IHC失败的病例中都识别出了原发肿瘤部位。

结论

先进行IHC,然后对不确定的病例进行GEC,几乎可以准确识别所有患者SBNET和PNET转移灶的原发部位。

相似文献

引用本文的文献

1
The University of Iowa Neuroendocrine Tumor Clinic.爱荷华大学神经内分泌肿瘤诊所。
Endocr Pract. 2025 Jan;31(1):4-18. doi: 10.1016/j.eprac.2024.09.018. Epub 2024 Sep 28.
9
Small Bowel Neuroendocrine Tumors.小肠神经内分泌肿瘤
Curr Probl Surg. 2020 Dec;57(12):100823. doi: 10.1016/j.cpsurg.2020.100823. Epub 2020 May 15.
10
Surgical Management of Neuroendocrine Tumor Liver Metastases.神经内分泌肿瘤肝转移的外科治疗。
Surg Oncol Clin N Am. 2021 Jan;30(1):39-55. doi: 10.1016/j.soc.2020.08.001. Epub 2020 Oct 20.

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验