Agaimy Abbas, Otto Claudia, Braun Alexander, Geddert Helene, Schaefer Inga-Marie, Haller Florian
Institute of Pathology, Friedrich Alexander University Erlangen, Germany.
Int J Clin Exp Pathol. 2013 Aug 15;6(9):1839-46. eCollection 2013.
Genotyping is a prerequisite for tyrosine kinase inhibitor therapy in high risk and malignant GIST. About 10% of GISTs are wild-type for KIT but carry PDGFRA mutations. Applying the traditional approach, mutation analysis of these cases is associated with higher costs if all hotspots regions in KIT (exon 9, 11, 13, 17) are performed at first. Our aim was to evaluate the predictive value of a combined histomorphological-immunohistochemical pattern analysis of PDGFRA-mutated GISTs to efficiently direct KIT and PDGFRA mutation analysis.
The histomorphology and PDGFRA immunostaining pattern was studied in a test cohort of 26 PDGFRA mutants. This was then validated on a cohort of 94 surgically resected GISTs with mutations in KIT (n=72), PDGFRA (n=15) or with wild-type status (n=7) on a tissue microarray. The histological subtype (spindled, epithelioid, mixed), PDGFRA staining pattern (paranuclear dot-like/Golgi, cytoplasmic and/or membranous), and extent of staining were determined without knowledge of the genotype. The combination of histomorphology and immunophenotype were used to classify tumors either as PDGFRA- or non-PDGFRA phenotype.
PDGFRA-mutated GISTs were significantly more often epithelioid (p<0.001) and had a higher PDGFRA expression, compared to KIT-mutants (p<0.001). Paranuclear PDGFRA immunostaining was almost exclusively observed in PDGFRA mutants (p<0.001). The sensitivity and specificity of this combined histological-immunohistochemical approach to predict the PDGFRA-genotype was 100% and 99%, respectively (p=6x10(-16)).
A combination of histomorphology and PDGFRA immunostaining is a reliable predictor of PDGFRA genotype in GIST. This approach allows direct selection of the "gene/exons of relevance" to be analyzed and may help to reduce costs and work load and shorten processing time of GIST genotyping by mutation analysis.
基因分型是高危和恶性胃肠道间质瘤（GIST）酪氨酸激酶抑制剂治疗的前提条件。约10%的GIST为KIT野生型，但携带血小板衍生生长因子受体α（PDGFRA）突变。采用传统方法，如果首先对KIT的所有热点区域（外显子9、11、13、17）进行检测，这些病例的突变分析成本较高。我们的目的是评估PDGFRA突变型GIST的组织形态学-免疫组织化学联合模式分析对有效指导KIT和PDGFRA突变分析的预测价值。
在一个包含26例PDGFRA突变体的测试队列中研究组织形态学和PDGFRA免疫染色模式。然后在一个组织芯片上，对94例手术切除的GIST进行验证，这些GIST在KIT（n = 72）、PDGFRA（n = 15）或野生型状态（n = 7）方面存在突变。在不知道基因型的情况下，确定组织学亚型（梭形、上皮样、混合型）、PDGFRA染色模式（核旁点状/高尔基体、细胞质和/或膜性）以及染色程度。组织形态学和免疫表型的组合用于将肿瘤分类为PDGFRA或非PDGFRA表型。
与KIT突变体相比，PDGFRA突变型GIST更常为上皮样（p < 0.001）且PDGFRA表达更高（p < 0.001）。核旁PDGFRA免疫染色几乎仅在PDGFRA突变体中观察到（p < 0.001）。这种组织学-免疫组织化学联合方法预测PDGFRA基因型的敏感性和特异性分别为100%和99%（p = 6×10⁻¹⁶）。
组织形态学和PDGFRA免疫染色的组合是GIST中PDGFRA基因型的可靠预测指标。这种方法允许直接选择要分析的“相关基因/外显子”，并可能有助于降低成本、减轻工作量以及缩短GIST基因分型突变分析的处理时间。
