Colorectal cancer is the 2nd leading cause of death in humans because of cancer. This rank of death could be due to the high rate of incidence from one hand, and the lack of sufficient diagnostic and therapeutic approaches from the other hand. Thus, molecular tools have been emerging as the potential biomarker to improve the early diagnosis and therapeutic management that subsequently could lead to the heightened survival rate of colorectal cancer patients. Long non-coding RNA (lncRNAs) have shown promising capabilities to be used in clinics. The profiling methods could identify novel aberrantly expressed lncRNAs in colorectal cancer. We, thus, performed a comprehensive and unbiased approach to shortlist the dysregulated lncRNAs based on the colon adenocarcinoma TCGA data. An unbiased in silico method was used to rank the yet to profiled lncRNAs in colorectal cancer. qPCR was used to measure the expression level of selected lncRNAs. Our results nominated ESRG, LINC00518, PWRN1, and TTTY14 lncRNAs as the top-hit novel lncRNAs with aberrant expression in colon cancer. The qPCR method was used to profile these lncRNAs that showed the up-regulation of ESRG and LINC00518, and down-regulation of TTTY14 in thirty paired colorectal cancer specimens. The statistical analyses demonstrated that ESRG, LINC00518 and PWRN1 could distinguish the tumor from normal samples. Moreover, ESRG showed a negative correlation with the overall survival of patients. These diagnostic and prognostic results suggest that profiling ESRG, LINC00518 and PWRN1 s may have implications in clinics.
Keywords: Colorectal cancer; Diagnosis; ESRG; LINC00518; Long non-coding RNA; PWRN1; TTTY14.
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