Biomarker ID | 1917 |
PMID | 22654636 |
Year | 2011 |
Biomarker | CAV1; TP53; MAGEA11; CALM1; EGFR; UBE2I; CALR; SMAD3; FHL2; HDAC1; APP; MYC; JUN; ESR1; GNB2L1; HIPK3; SMAD2; APPBP2; CDC2; BRCA1; RB1; SMAD1;PXN; XRCC6; IL6ST; STAT3; DLG1; AES; TRAF6; FLNA; TRIM29; PCAF; REPS2; AKT1; PRKCA; RAF1; HLA-B; TRAF2; SMARCA4; MAPK1; CHGB; RANBP9; CCND1; GSK3B; HSPA1A; BCL2; VCL; RAI17; TGFBR1; SELENBP1; |
Biomarker Basis | Expression Based |
Biomolecule | Protein |
Source | Tissue |
Subjects | Humans |
Regulation | Upregulated in Metastatic PCa: [HSP27 (2.01 fold); prohibitin (1.88 fold); GSTP1 (1.18 fold); fibrinogen β chain (2.68 fold); ALDH6A1 (2.89 fold);]Downregulated in Metastatic PCa [A1AT (0.84 fold) ; HSP60 (0.19 fold);] |
Odds Ratio/Hazard Ratio/Relative Risk | NA |
Effect on Pathways | NA |
Experiment | Prostate Cancer Vs Normal Prostate |
Type of Biomarker | Diagnostic |
Cohort | Microarray data that consists of 62 primary tumors, 9 lymph nodes metastasis and 41 normal control samples was chosen |
Senstivity | NA |
Specificity | NA |
AUC | NA |
Accuracy | NA |
Level Of Significance | NA |
Method Used | Microarray |
Clinical | No |
Remarks | Top 50 ranking genes were selected by using public biological network datasets. 41 genes overlapped in prognostic and diagnostic performance. The paper Integrates protein interaction network with normal and disease microarray data, using this integration they apply all-pairs shortest paths to find the significant networks and calculate the score for the genes. Additionally the method filters interactions, in such way the most relevant interactions are left for analysis |
Clinical Trial Number | NA |
Degree Of Validity | Not validated on independent patient dataset |
Technical Name | NA |