2023
DOI: 10.1186/s12944-023-01804-4
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Lipid metabolism-related miRNAs with potential diagnostic roles in prostate cancer

Abstract: Background Prostate cancer (PCa), the second most prevalent solid tumor among men worldwide, has caused greatly increasing mortality in PCa patients. The effects of lipid metabolism on tumor growth have been explored, but the mechanistic details of the association of lipid metabolism disorders with PCa remain largely elusive. Methods The RNA sequencing data of the GSE45604 and The Cancer Genome Atlas-Prostate Adenocarcinoma (TCGA-PRAD) datasets wer… Show more

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Cited by 7 publications
(3 citation statements)
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“…To efficiently screen feature variables associated with colorectal cancer postoperative unplanned reoperation, we used three different machine learning methods: support vector machine (SVM)[ 16 ] least absolute shrinkage and selection operator (LASSO) regression[ 17 ], and extreme gradient boosting (XGBoost)[ 18 ].…”
Section: Methodsmentioning
confidence: 99%
“…To efficiently screen feature variables associated with colorectal cancer postoperative unplanned reoperation, we used three different machine learning methods: support vector machine (SVM)[ 16 ] least absolute shrinkage and selection operator (LASSO) regression[ 17 ], and extreme gradient boosting (XGBoost)[ 18 ].…”
Section: Methodsmentioning
confidence: 99%
“…Seven key lipid metabolism-related miRNAs (LMRMs), including miR-148-3p and miR-375-3p, exhibit significant diagnostic potential for prognosis and diagnosis in prostate cancer (PCa). A TF-miRNA-mRNA regulatory network involving SNAI2, GATA3, and target genes like CLIC6 and SCNN1A, is significant in PCa progression and patient prognosis [172]. In HCC, miR-122 promotes lipid accumulation by targeting several genes involved in lipid oxidation, including CPT1A and acyl-CoA oxidase 1 (ACOX1) [173].…”
Section: Non-coding Rnas In Lipid Metabolismmentioning
confidence: 99%
“…A recent computational biology study using machine learning has identified seven key miRNAs associated with mRNAs involved in lipid metabolism that are differentially expressed between prostate cancer and its benign counterpart. The differential expression of this lipid metabolism-related signature was also validated by PCR and in publicly available datasets ( 14 ). In addition to forming a molecular signature, miRNA expression profiles can identify distinct metabolic phenotypes within a disease spectrum.…”
Section: Introductionmentioning
confidence: 99%