Nov 25, 2019

Identification of miRNA signatures for kidney renal clear cell carcinoma using the tensor-decomposition method

BioRxiv : the Preprint Server for Biology
Ka-Lok Ng, Y-h. Taguchi

Abstract

Purpose: Cancer is a highly complex disease caused by multiple genetic factors. MicroRNA (miRNA) and mRNA expression profiles are useful for identifying prognostic biomarkers for cancer. The kidney renal clear cell carcinoma (KIRC) was selected for our analysis, because KIRC accounts for more than 70% of all renal malignant tumor cases. Methods: Traditional methods of identifying cancer prognostic markers may not be accurate. Tensor decomposition (TD) is a useful method uncovering the underlying low-dimensional structures in the tensor. TD-based unsupervised feature extraction method was applied to analyze mRNA and miRNA expression profiles. Biological annotations of the prognostic miRNAs and mRNAs were examined by utilizing pathway and oncogenic signature databases, i.e. DIANA-miRPath and MSigDB. Results: TD identified the miRNA signatures and the associated genes. These genes were found to be involved in cancer-related pathways and 23 genes were significantly correlated with the survival of KIRC patients. We demonstrated that the results are robust and not highly dependent upon the database we selected. Compare to the t-test, we shown that TD achieves a much better performance in selecting prognostic miRNAs and mRNAs. Conclus...Continue Reading

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Mentioned in this Paper

Biological Markers
Study
Biochemical Pathway
Genes
Diagnostic Techniques, Surgical
Cancer Diagnosis
Fibrous Capsule of Left Kidney
Analysis
Adenocarcinoma, Clear Cell
Urea Catabolic Process

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