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Optimized p53 immunohistochemistry is an accurate predictor of

机译:优化的p53免疫组织化学可以准确预测

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Abstract TP53 mutations are ubiquitous in high-grade serous ovarian carcinomas (HGSOC), and the presence of TP53 mutation discriminates between high and low-grade serous carcinomas and is now an important biomarker for clinical trials targeting mutant p53. p53 immunohistochemistry (IHC) is widely used as a surrogate for TP53 mutation but its accuracy has not been established. The objective of this study was to test whether improved methods for p53 IHC could reliably predict TP53 mutations independently identified by next generation sequencing (NGS). Four clinical p53 IHC assays and tagged-amplicon NGS for TP53 were performed on 171 HGSOC and 80 endometrioid carcinomas (EC). p53 expression was scored as overexpression (OE), complete absence (CA), cytoplasmic (CY) or wild type (WT). p53 IHC was evaluated as a binary classifier where any abnormal staining predicted deleterious TP53 mutation and as a ternary classifier where OE, CA or WT staining predicted gain-of-function (GOF or nonsynonymous), loss-of-function (LOF including stopgain, indel, splicing) or no detectable TP53 mutations (NDM), respectively. Deleterious TP53 mutations were detected in 169/171 (99%) HGSOC and 7/80 (8.8%) EC. The overall accuracy for the best performing IHC assay for binary and ternary prediction was 0.94 and 0.91 respectively, which improved to 0.97 (sensitivity 0.96, specificity 1.00) and 0.95 after secondary analysis of discordant cases. The sensitivity for predicting LOF mutations was lower at 0.76 because p53 IHC detected mutant p53 protein in 13 HGSOC with LOF mutations. CY staining associated with LOF was seen in 4 (2.3%) of HGSOC. Optimized p53 IHC can approach 100% specificity for the presence of TP53 mutation and its high negative predictive value is clinically useful as it can exclude the possibility of a low-grade serous tumour. 4.1% of HGSOC cases have detectable WT staining while harboring a TP53 LOF mutation, which limits sensitivity for binary prediction of mutation to 96%.
机译:摘要TP53突变在高度浆液性卵巢癌(HGSOC)中无处不在,并且TP53突变的存在可区分高危和低度浆液性癌,目前已成为针对突变p53的临床试验的重要生物标志物。 p53免疫组化(IHC)被广泛用作TP53突变的替代物,但尚未确定其准确性。这项研究的目的是测试改进的p53 IHC方法是否可以可靠地预测由下一代测序(NGS)独立鉴定的TP53突变。对171例HGSOC和80例子宫内膜样癌(EC)进行了四种临床的p53 IHC测定和标记的TP53的NGS。将p53表达记为过表达(OE),完全不存在(CA),细胞质(CY)或野生型(WT)。 p53 IHC被评估为二元分类器,其中任何异常染色均预测有害的TP53突变,而三元分类器被评估为OE,CA或WT染色预测功能获得(GOF或非同义),功能丧失(LOF包括停顿,插入缺失,剪接)或没有可检测的TP53突变(NDM)。在169/171(99%)HGSOC和7/80(8.8%)EC中检测到有害的TP53突变。对于二元和三元预测而言,性能最佳的IHC分析的总体准确度分别为0.94和0.91,经过对不和谐病例进行二次分析后,总准确度提高至0.97(敏感性0.96,特异性1.00)和0.95。预测LOF突变的敏感性较低,为0.76,因为p53 IHC在13个HGSOC中检测到LOF突变的突变p53蛋白。在4个(2.3%)HGSOC中观察到与LOF相关的CY染色。优化的p53 IHC对TP53突变的存在可以达到100%的特异性,其高阴性预测值在临床上是有用的,因为它可以排除低度浆液性肿瘤的可能性。 4.1%的HGSOC病例具有可检测的WT染色,但带有TP53 LOF突变,因此将二进制预测突变的敏感性限制为96%。

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