The diagnostic and prognostic value of in colorectal cancer.

INTRODUCTION

Colorectal cancer (CRC) is among the lethal cancers, indicating the need for the identification of novel biomarkers for the detection of patients in earlier stages. RNA and microRNA sequencing were analyzed using bioinformatics and machine learning algorithms to identify differentially expressed genes (DEGs), followed by validation in CRC patients.

METHODS

The genome-wide RNA sequencing of 631 samples, comprising 398 patients and 233 normal cases was extracted from the Cancer Genome Atlas (TCGA). The DEGs were identified using DESeq package in R. Survival analysis was evaluated using Kaplan-Meier analysis to identify prognostic biomarkers. Predictive biomarkers were determined by machine learning algorithms such as Deep learning, Decision Tree, and Support Vector Machine. The biological pathways, protein-protein interaction (PPI), the co-expression of DEGs, and the correlation between DEGs and clinical data were evaluated. Additionally, the diagnostic markers were assessed with a combioROC package. Finally, the candidate tope score gene was validated by Real-time PCR in CRC patients.

RESULTS

The survival analysis revealed five novel prognostic genes, including , , , , and . Thirty-nine upregulated, 40 downregulated genes, and 20 miRNAs were detected by SVM with high accuracy and AUC. The upregulation of and genes and the downregulation of and genes had the highest coefficient in the advanced stage. Furthermore, our findings showed that three miRNAs (, and ) upregulated in the advanced stage. , as a novel gene, was validated using RT-PCR in CRC patients. The combineROC curve analysis indicated that the combination of can be considered as diagnostic markers with sensitivity, specificity, and AUC values of 0.90, 0.94, and 0.92, respectively.

CONCLUSION

Machine learning algorithms can be used to Identify key dysregulated genes/miRNAs involved in the pathogenesis of diseases, leading to the detection of patients in earlier stages. Our data also demonstrated the prognostic value of in colorectal cancer.