Detection of the BRAF V600E Mutation in Colorectal Cancer by NIR Spectroscopy in Conjunction with Counter Propagation Artificial Neural Network.

Xue Zhang,Yalan Wang,Yang Yang,Qi Fan

doi:10.3390/molecules24122238

Xue Zhang, Yalan Wang + Show 2 more

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https://doi.org/10.3390/molecules24122238

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Journal: Molecules	Publication Date: Jun 15, 2019
Citations: 21	License type: CC BY 4.0

Affiliation: Chongqing Medical University

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This paper proposes a sensitive, sample preparation-free, rapid, and low-cost method for the detection of the B-rapidly accelerated fibrosarcoma (BRAF) gene mutation involving a substitution of valine to glutamic acid at codon 600 (V600E) in colorectal cancer (CRC) by near-infrared (NIR) spectroscopy in conjunction with counter propagation artificial neural network (CP-ANN). The NIR spectral data from 104 paraffin-embedded CRC tissue samples consisting of an equal number of the BRAF V600E mutant and wild-type ones calibrated and validated the CP-ANN model. As a result, the CP-ANN model had the classification accuracy of calibration (CAC) 98.0%, cross-validation (CACV) 95.0% and validation (CAV) 94.4%. When used to detect the BRAF V600E mutation in CRC, the model showed a diagnostic sensitivity of 100.0%, a diagnostic specificity of 87.5%, and a diagnostic accuracy of 93.8%. Moreover, this method was proven to distinguish the BRAF V600E mutant from the wild type based on intrinsic differences by using a total of 312 CRC tissue samples paraffin-embedded, deparaffinized, and stained. The novel method can be used for the auxiliary diagnosis of the BRAF V600E mutation in CRC. This work can expand the application of NIR spectroscopy in the auxiliary diagnosis of gene mutation in human cancer.

Highlights

Colorectal cancer (CRC) is one of the human malignant tumors with high incidence and mortality rates [1]
There are two kinds of differences in the calibration samples used in Model 4, as shown in. These findings suggest that the counter propagation artificial neural network (CP-artificial neural network (ANN)) models built by the NIR data can detect the B-rapidly accelerated fibrosarcoma (BRAF) V600E
The NIR strategy on the basis of the principle different from the clinical diagnostic methods can be used for the auxiliary diagnosis of the BRAF V600E mutation in colorectal cancer (CRC)

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Introduction

Colorectal cancer (CRC) is one of the human malignant tumors with high incidence and mortality rates [1]. The mutations in CRC often make the treatment more difficult [2,3,4]. One of the most common mutations in CRC is the B-rapidly accelerated fibrosarcoma (BRAF) gene mutation, which involves a substitution of valine to glutamic acid at codon 600 (V600E) [5]. The BRAF V600E mutation in CRC significantly reduces the efficacy of the drugs that are used in the treatment of patients with BRAF V600E wild type in CRC. The drug treatment regimen for patients with BRAF V600E mutant in CRC needs to be redesigned [6,7]. It is crucial to detect the BRAF V600E mutation for the targeted therapy in CRC

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