Identification of Differentially Expressed Genes in Human Colorectal Cancer Using RNASeq Data Validated on the Molecular Level with Real-Time PCR

Abstract

Colorectal cancer (CRC) is a prevalent cancer with high morbidity and mortality rates worldwide. Late diagnosis is a significant contributor to low survival rates in a minority of cases. The study aimed to perform a robust pipeline using integrated bioinformatics tools that will enable us to identify potential diagnostic and prognostic biomarkers for early detection of CRC by exploring differentially expressed genes (DEGs). In addition to, testing the capability of replacing chemotherapy with plant extract in CRC treatment by validating it using real-time PCR. RNA-seq data from cancerous and adjacent normal tissues were pre-processed and analyzed using various tools such as FastQC, Kallisto, DESeq@ R package, g:Profiler, GNEMANIA-CytoScape and CytoHubba, resulting in the identification of 1641 DEGs enriched in various signaling routes. MMP7, TCF21, and VEGFD were found to be promising diagnostic biomarkers for CRC. An in vitro experiment was conducted to examine the potential anticancer properties of 5-fluorouracile, Withania somnifera extract, and their combination. The extract was found to exhibit a positive trend in gene expression and potential therapeutic value by targeting the three genes; however, further trials are required to regulate the methylation promoter. Molecular docking tests supported the findings by revealing a stable ligand-receptor complex. In conclusion, the study’s analysis workflow is precise and robust in identifying DEGs in CRC that may serve as biomarkers for diagnosis and treatment. Additionally, the identified DEGs can be used in future research with larger sample sizes to analyze CRC survival.

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