Duan Jiale, Yang Yanping, Yin Lei, Zhang Xue, Tang Yi, Zhang Shuxian, Gong Hanjuan, Xiao Ming, Li Ming, Li Qingshu, Li Xian, Yang Lian, Fan Qi, Wang Yalan
Department of Pathology, Molecular Medicine and Cancer Research Center, Chongqing Medical University, Chongqing 400016, People's Republic of China.
School of Pharmacy, Chongqing Medical University, Chongqing 400016, People's Republic of China.
Onco Targets Ther. 2020 Dec 22;13:13077-13085. doi: 10.2147/OTT.S287814. eCollection 2020.
In metastatic colorectal cancer (mCRC), the B-type Raf kinase (BRAF) mutation is a molecular biomarker of poor prognosis and is of great importance to drug target. Currently, the commonly used methods for detecting BRAF mutation include immunohistochemistry (IHC) and gene sequencing, but both present certain limitations. Near-infrared (NIR) spectroscopy is a spectroscopy technology that takes advantage of the electromagnetic wavelength between visible light and mid-infrared light.
IHC was used to detect the expression of BRAF protein with the BRAF (VE1) antibody in 42 cases of paraffin-embedded (FFPE) mCRC tissue sections. The NIR-discriminant analysis model (NIRS-DA) was established using 6 cases of wild-type and 6 cases of mutant-type BRAF specimens.
IHC detection results revealed 13 cases of weakly positive (+), 1 case of moderately positive (++), and 28 cases of negative (-) CRC. Compared with the next-generation sequencing (NGS) results, the positive rate was 66.7%. The classification accuracy of calibration (CAC) was 100% compared with the results of NGS, demonstrating that the BRAF mutant NIRS-DA model, verified by 2 cases of wild-type and 2 cases of mutant-type CRC samples was established. The NIRS-DA model was used to predict gene mutation in the CRC samples, 7 cases were positive (+), and 35 cases were negative (-), and the classification accuracy of prediction (CAP) was 83.3% (35/42).
The NIRS-DA model-predicted results were in high agreement with the detection results of NGS, and the difference in IHC is not statistically significant (P>0.05). However, this study is a preliminary discussion on a methodology due to its small sample size.
在转移性结直肠癌（mCRC）中，B型 Raf 激酶（BRAF）突变是预后不良的分子生物标志物，对药物靶点具有重要意义。目前，检测 BRAF 突变的常用方法包括免疫组织化学（IHC）和基因测序，但两者都存在一定局限性。近红外（NIR）光谱是一种利用可见光和中红外光之间电磁波长的光谱技术。
使用 BRAF（VE1）抗体通过 IHC 检测 42 例石蜡包埋（FFPE）mCRC 组织切片中 BRAF 蛋白的表达。使用 6 例野生型和 6 例突变型 BRAF 标本建立 NIR 判别分析模型（NIRS-DA）。
IHC 检测结果显示，结直肠癌弱阳性（+）13 例、中度阳性（++）1 例、阴性（-）28 例。与下一代测序（NGS）结果相比，阳性率为 66.7%。与 NGS 结果相比，校准分类准确率（CAC）为 100%，表明建立了经 2 例野生型和 2 例突变型结直肠癌样本验证的 BRAF 突变 NIRS-DA 模型。使用 NIRS-DA 模型预测结直肠癌样本中的基因突变，阳性（+）7 例，阴性（-）35 例，预测分类准确率（CAP）为 83.3%（35/42）。
NIRS-DA 模型预测结果与 NGS 检测结果高度一致，与 IHC 的差异无统计学意义（P>0.05）。然而，由于本研究样本量较小，是对一种方法的初步探讨。
