Abstract
Colorectal cancer (CRC) is mostly diagnosed at late stages leading to high mortality rates due to the scarcity of efficient screening approaches exhibiting high diagnostic utility. The current study employed a small‑RNA deep‑sequencing approach for screening microRNA (miRNA) differentially expressed genes (DEGs), and evaluating their potential as early diagnostic circulating biomarkers for CRC in clinical plasma and tissue samples from a Saudi patient population. The cohort followed a paired‑study design composed of 20 CRC patients, providing plasma (P) and tissue (T) samples of CRC, and adjacent normal mucosa (CT). Also, control plasma (CP) samples were obtained from neoplasm‑free healthy individuals to compare its miRNA levels with those in P samples. Illumina high‑throughput (HiSeq 2000) sequencing was performed for the identification of known and novel miRNA genes that were differentially expressed in the plasma and tissues of CRC patients compared with CT and CP controls. While we identified only one known (hsa‑miR‑182‑5p, significantly upregulated) and no novel DEGs at the most stringent significance level (P<0.001) in the P‑CP comparison, we found 3 and none at P<0.01, 7 and 9 at P<0.05 level, respectively. In the T‑CT comparison, the results revealed 24 known and 196 novel miRNA DEGs (P<0.001), 31 and 204 (P<0.01), 41 and 213 (P<0.05), respectively. Sequencing data were then analyzed by bioinformatics for potential diagnostic miRNAs. Network functional analysis for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway implicated two pathways rooted to signal transduction [Wnt and mitogen‑activated protein kinase (MAPK)] that were enriched in CRC patients. Our results suggest that characterizing plasma and tissue profiles of CRC by deep sequencing may be a good strategy for identifying known and novel miRNAs and that the validated miRNAs described here may serve as potential CRC‑associated biomarkers. Further research is necessary for determining their screen index values and diagnostic utility for the diagnosis of CRC.