如何诊断纤维板层癌?

IF 7.1 1区 医学 Q1 PATHOLOGY Modern Pathology Pub Date : 2025-01-13 DOI:10.1016/j.modpat.2025.100711
Haukur Einarsson, Rondell P Graham
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引用次数: 0

摘要

纤维板层癌(FLC)是一种独特的原发性肝癌,其特征是不同的形态学发现和复发性DNAJB1::PRKACA基因融合。它通常出现在年轻人没有潜在的肝功能障碍。仅根据形态学诊断FLC是一种困难的诊断,误诊并不罕见。常见的鉴别诊断包括常规肝细胞癌和肝内胆管癌,两者均表现出相似的形态学和免疫组织化学特征。如果仅仅基于分子分析,其他的鉴别诊断最近也出现了,如DNAJB1::PRKACA融合在导管内嗜瘤细胞乳头状瘤和导管内乳头状粘液瘤的病例中已被报道。在本文中,我们回顾了FLC的诊断方法,它依赖于形态学和免疫组织化学特征,以及分子分析。
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How Do I Diagnose Fibrolamellar Carcinoma?

Fibrolamellar carcinoma (FLC) is a unique primary carcinoma of liver that is characterized by distinct morphologic findings and a recurrent DNAJB1::PRKACA gene fusion. It typically presents in young individuals without underlying liver dysfunction. FLC is a difficult diagnosis when based only on morphology and misdiagnosis is not uncommon. Frequent differential diagnoses include conventional hepatocellular carcinoma and intrahepatic cholangiocarcinoma, both of which can show similar morphologic and immunohistochemical features. If based only on molecular analysis other differential diagnoses have recently emerged, as the DNAJB1::PRKACA fusion has now been reported in cases of intraductal oncocytic papillary neoplasm and intraductal papillary mucinous neoplasm. In this article we review our diagnostic approach to FLC, which relies on both morphologic and immunohistochemical features, as well as molecular analysis.

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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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