ABSTRACT
Profiles of circulating microRNA in the plasma of patients with prostate cancer with pathomorphological stages pT2, pT3, and pT4 are analyzed. The level of circulating microRNA hsa-miR-619-5p is elevated in patients with extracapsular spreading of the tumor, increasing significantly from stage pT2 to stage pT4.
Subject(s)
Biomarkers, Tumor/blood , MicroRNAs/genetics , Prostatic Neoplasms/blood , Cisplatin/pharmacology , Docetaxel , Granulocytes/drug effects , Granulocytes/metabolism , Humans , Male , MicroRNAs/blood , Neutrophils/cytology , Neutrophils/drug effects , Neutrophils/metabolism , Stem Cells/cytology , Stem Cells/metabolism , Taxoids/pharmacologyABSTRACT
We performed diagnostic classification of plasma specimens from patients with non-metastatic and metastatic prostate cancer based on pairs of miRNA that have no individual diagnostic significance. Of 230 miRNA detected in plasma specimens, 3 pairs were diagnostically significant. The miRNA pair hsa-miR-19b-3p and hsa-miR-297 demonstrated highest sensitivity and specificity. Among common target genes of these miRNA, CFL2 gene associated with cell mobility was detected.
Subject(s)
Biomarkers, Tumor/genetics , Cofilin 2/genetics , Gene Expression Regulation, Neoplastic , MicroRNAs/genetics , Prostatic Neoplasms/diagnosis , Aged , Biomarkers, Tumor/blood , Cofilin 2/blood , Humans , Kallikreins/blood , Kallikreins/genetics , Lymphatic Metastasis , Male , MicroRNAs/blood , Middle Aged , Neoplasm Grading , Prostate-Specific Antigen/blood , Prostate-Specific Antigen/genetics , Prostatic Neoplasms/blood , Prostatic Neoplasms/genetics , Prostatic Neoplasms/pathology , Sensitivity and Specificity , Signal TransductionABSTRACT
Genes with significant differential expression are traditionally used to reveal the genetic background underlying phenotypic differences between cancer cells. We hypothesized that informative marker sets can be obtained by combining genes with a relatively low degree of individual differential expression. We developed a method for construction of highly informative gene combinations aimed at the maximization of the cumulative informative power and identified sets of 2-5 genes efficiently predicting recurrence for ER-positive breast cancer patients. The gene combinations constructed on the basis of microarray data were successfully applied to data acquired by RNA-seq. The developed method provides the basis for the generation of highly efficient prognostic and predictive gene signatures for cancer and other diseases. The identified gene sets can potentially reveal novel essential segments of gene interaction networks and pathways implied in cancer progression.
