Abstract

BackgroundVarious diagnostic and prognostic tools exist in colorectal cancer (CRC) due to multiple genetic and epigenetic alterations causing the disease. Today, the expression of RNAs is being used as prognostic markers for cancer.MethodsIn the current study, various dysregulated RNAs in CRC were identified via bioinformatics prediction. Expression of several of these RNAs were measured by RT-qPCR in 48 tissues from CRC patients as well as in colorectal cancer stem cell-enriched spheroids derived from the HT-29 cell line. The relationships between the expression levels of these RNAs and clinicopathological features were analyzed.ResultsOur bioinformatics analysis determined 11 key mRNAs, 9 hub miRNAs, and 18 lncRNAs which among them 2 coding RNA genes including DDIT4 and SULF1 as well as 3 non-coding RNA genes including TPTEP1, miR-181d-5p, and miR-148b-3p were selected for the further investigations. Expression of DDIT4, TPTEP1, and miR-181d-5p showed significantly increased levels while SULF1 and miR-148b-3p showed decreased levels in CRC tissues compared to the adjacent normal tissues. Positive relationships between DDIT4, SULF1, and TPTEP1 expression and metastasis and advanced stages of CRC were observed. Additionally, our results showed significant correlations between expression of TPTEP1 with DDIT4 and SULF1.ConclusionsOur findings demonstrated increased expression levels of DDIT4 and TPTEP1 in CRC were associated with more aggressive tumor behavior and more advanced stages of the disease. The positive correlations between TPTEP1 as non-coding RNA and both DDIT4 and SULF1 suggest a regulatory effect of TPTEP1 on these genes.

Highlights

  • Various diagnostic and prognostic tools exist in colorectal cancer (CRC) due to multiple genetic and epigenetic alterations causing the disease

  • We explored effector networks of mRNAs, miRNAs, and Long non-coding RNAs (lncRNAs) in Colorectal cancer (CRC) based on predicted relationships of these RNAs via bioinformatics tools

  • Bioinformatics analysis and selecting target genes Network analysis and clustering genes Three hundred and seventy up-regulated genes were included in network analysis based on score > 3 which found to be involved in carcinogenesis or colorectal cancer (P < 0.0001) on DisGeNET (Additional file 1: Table S1)

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Summary

Introduction

Various diagnostic and prognostic tools exist in colorectal cancer (CRC) due to multiple genetic and epigenetic alterations causing the disease. The existence of a subset of Fattahi et al Cancer Cell Int (2021) 21:303 cancer cells named cancer stem cells (CSCs) leads to tumor heterogeneity by utilizing self-renewal and multilineage differentiation features in the tumor [3]. These alterations and CSCs play important roles in development and progression of CRC [4, 5]. It is important to find sensitive and specific biomarkers to best guide early and appropriate treatment before disease progression [12]

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