对胃癌和胃食管交界腺癌中的 Claudin-18.2 进行免疫组化评估以指导靶向治疗:一种实用方法。

IF 7.1 1区 医学 Q1 PATHOLOGY
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引用次数: 0

摘要

通过免疫组化评估克劳迪蛋白-18.2(CLDN18.2)的表达是胃癌和胃食管交界处腺癌的一种新生物标记物,不久将获得市场授权,用于常规临床实践。尽管在临床试验中进行了成功的测试,但尚未提出具体的实用测试指南。一些分析前和分析中的变量可能会干扰对CLDN18.2染色的充分解读,因此本文就胃/胃食管交界处腺癌的CLDN18.2检测和评分提供了实用指南,以确定哪些患者可能会对针对CLDN18.2的单克隆抗体靶向治疗产生反应。根据现有数据,抗CLDN18.2单克隆抗体(zolbetuximab)在≥75%的腺癌细胞中的中度至强膜染色(2+/3+)是临床应用的建议临界值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Claudin-18.2 Immunohistochemical Evaluation in Gastric and Gastroesophageal Junction Adenocarcinomas to Direct Targeted Therapy: A Practical Approach

Claudin-18.2 (CLDN18.2) expression evaluated by immunohistochemistry is a new biomarker for gastric and gastroesophageal junction adenocarcinomas that will soon have market authorization for implementation into routine clinical practice. Despite successful testing in the setting of clinical trials, no specific practical testing guidelines have been proposed. Several preanalytical and analytical variables may interfere with adequate CLDN18.2 staining interpretation; thus, this article provides practical guidance on CLDN18.2 testing and scoring in gastric and gastroesophageal junction adenocarcinomas to identify patients who may respond to targeted therapy with monoclonal antibodies directed against CLDN18.2. Based on available data, moderate to strong (2+/3+) membrane staining in ≥75% of adenocarcinoma cells is the proposed cutoff for clinical use of monoclonal antibody anti-CLDN18.2 (zolbetuximab).

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来源期刊
Modern Pathology
Modern Pathology 医学-病理学
CiteScore
14.30
自引率
2.70%
发文量
174
审稿时长
18 days
期刊介绍: Modern Pathology, an international journal under the ownership of The United States & Canadian Academy of Pathology (USCAP), serves as an authoritative platform for publishing top-tier clinical and translational research studies in pathology. Original manuscripts are the primary focus of Modern Pathology, complemented by impactful editorials, reviews, and practice guidelines covering all facets of precision diagnostics in human pathology. The journal's scope includes advancements in molecular diagnostics and genomic classifications of diseases, breakthroughs in immune-oncology, computational science, applied bioinformatics, and digital pathology.
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