Preliminary Study on the Identification of BRAFV600E Mutation in Colorectal Cancer by Near-Infrared Spectroscopy

• Published in: OncoTargets and therapy 2020-01, Vol.13, p.13077-13085
• Main Authors: 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
• Format: Article
• Language: English
• Subjects: Antigens; Cloning; Colorectal cancer; Colorectal carcinoma; Deoxyribonucleic acid; DNA; DNA methylation; Ethanol; I.R. radiation; Immunohistochemistry; Infrared spectroscopy; Kinases; Metastases; Metastasis; Monoclonal antibodies; Mutants; Mutation; Next-generation sequencing; Original Research; Paraffin; Point mutation; Proteins; Software; Statistical analysis; Therapeutic targets; Tumors
• ISSN: 1178-6930; 1178-6930
• DOI: 10.2147/OTT.S287814

Introduction: In metastatic colorectal cancer (mCRC), the B-type Raf kinase (BRAF)V600E mutation is a molecular biomarker of poor prognosis and is of great importance to drug target. Currently, the commonly used methods for detecting BRAFV600E 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. Methods: IHC was used to detect the expression of BRAFV600E protein with the BRAFV600E (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. Results: 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 BRAFV600E 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). Discussion: 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.