ArticleTranslational cancer research2022
Establishment of a 7-microRNA prognostic signature and identification of hub target genes in colorectal carcinoma.
Article in Translational cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 2 citations in OpenAlex.
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3 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Colorectal cancer (CRC) is a malignant tumor with high morbidity and mortality, but there is still no recognized prognostic prediction model to better predict and intervene its prognosis. Our aim is to establish a novel microRNA (miRNA) signature and identify hub target genes for simply and accurately predicting survival risk for CRC patients and to provide therapeutic targets. Methods: The miRNA expression profiles along with clinical data of 512 CRC patients were downloaded from the Cancer Genome Atlas (TCGA) database and randomly divided into training set and validation set. The signature was generated from the training set after a series of Cox regression analyses, including least absolute shrinkage and selectionator operator (LASSO)-Cox regression, and verified in the test set and the whole set. Furthermore, the signature was compared with clinical risk factors. Interaction network of target genes of the seven micoRNAs was established. Functional enrichment analysis was performed to reveal the biological processes and pathways. GEPIA2 was used for prognostic analysis. Results: A 7-micoRNA prognostic signature was generated from the training set with the areas under the receiver operating characteristic (ROC) curve (AUC) of 5-year survival rate was 0.889. Its performance was well verified both in the test set and the entire set by Kaplan-Meier analysis (P value <0.05). Further analysis demonstrated that the signature was an independent prognostic risk factor for CRC patients and its predictive ability was superior to age and tumor-node-metastasis (TNM) stage. Interaction network found two major gene modules, and they might be involved in the activation of PI3K-Akt-mTOR and p53 signaling pathways, which related to epidermal growth factor receptor (EGFR) resistance. The GEPIA2 revealed that CDKN1A, eIF4E and SNAI1 were associated with CRC prognosis. Conclusions: Our study demonstrated the potential of this novel 7-micoRNA signature to independently predict overall survival in patients with CRC and provided potential therapeutic targets.
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