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Article Abstract

Background: Slow transit constipation (STC) is a potential risk of the onset of colorectal cancer (CRC). Thus, the purpose of this work is to focus on the co-pathogenic targets between STC and CRC, meanwhile evaluating their prognostic value for CRC.

Methods: The miRNA and mRNA data of STC and CRC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The prognostic signature was constructed based on hub genes, which identified using differential expression analysis and LASSO Cox regression analysis. The hub genes were validated employing multiple public databases. Enrichment analysis was employed to elucidate their functions. Survival analysis was performed using Kaplan-Meier method. Transcription factor binding sites were predicted and verified using FIMO and ChIP-seq database, respectively.

Results: We identified four common key differentially expressed miRNAs of STC and CRC, including hsa-miR-340, hsa-miR-30b, hsa-miR-20b, and hsa-miR-29c (p-value <0.05), and their targets were involved in the CRC's metabolic processes (all p-values <0.05). We developed a prognostic signature based on nine hub genes, and patient prognosis could be predicted employing Risk score = 0.099063054*  + 0.074815408*  + 0.003499667*  + 0.051762032* + 0.050495722*  + 0.045057094*  + 0.097209257* + (-0.246941474)*  + 0.039294168* . High-risk patients exhibited significantly poorer prognosis (p-value <0.05). The hub genes , , , and were significantly down-regulated targets of hsa-miR-340 in the CRC samples (p-value <0.05). Functional analyses suggested their involvement in immune-related processes (all p-values <0.05). Our exploration of upstream regulators revealed six and one reliable transcription factors for and , respectively.

Conclusion: This study delved into common biomarkers between STC and CRC, and developed a reliable prognostic signature for CRC.

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http://dx.doi.org/10.1080/07357907.2025.2506102DOI Listing

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Methods: The miRNA and mRNA data of STC and CRC were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases.

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