Table 5.
Clinical applications of the bioinformatics analyses
| Application | Method | Number of patients involved | Discovery | Ref. |
|---|---|---|---|---|
| Diagnostic Biomarker | Integrative analysis of data from TCGA and GEO database and identify the differentially expressed genes and validated experimentally. | 103 iCCA and 384 other adenocarcinoma patients | C-reactive protein (CRP) was identified as putative diagnostic biomarker better than N-cadherin for distinguish intra-hepatic cholangiocarcinoma (iCCA) from CRP expression indicates a better overall survival. | 17 |
| Comparative and quantitative proteomics study of the bile fluid of patients | Six CCA patients and two non-CCA patients | Alpha-1-antitrypsin is identified as a potential marker for early diagnosis of cholangiocarcinoma. | 81 | |
| Comparative deep sequencing miRNA expression between tumor and control samples | 25 ICC patients and 7 healthy controls | Circulating plasma miRNA-21 and miRNA-221 are identified as potential diagnostic markers for primary iCCA | 82 | |
| Chemotherapeutic Target | A shotgun proteomic approach Using SDS-PAGE coupled with LC-MS/MS to screen mitochondrial proteins overexerted in CCA. | 25 CCA patients with 11 non-papillary and 14 papillary types | AIFM3 was found as a potential CCA chemotherapeutic target. | 83 |
| Prognostic nomogram | Using data from ICCA patients to develop and evaluate the nomogram by concordance index and testing calibration. | Information from 185 iCCA patients was used for nomogram creation | A nomogram integrated ten clinicopathological variables was developed to predict prognostic overall survival (OS) for iCCA patients after hepatectomy. | 84 |
| Biomarkers to distinguish CCA from benign biliary tract diseases(BBTDs) | Comparative proteomic with SDS-PAGE and LC-MS/MS | 19 CCA and 17 BBTDs patients | FAM19A5, MAGED4B, KIAA0321, RBAK, and UPF3B are screened as putative biomarkers to differentiate BBTDs and CCA. | 85 |
| Identification of biomarker for diagnosis of eCCA | Mass spectrometry | 165 extrahepatic cholangiocarcinoma and 21 non-cancerous patients | S100P, CEAM5, MUC5A, OLFM4, OAT, CAD17, FABPL, AOFA, K1C20 and CPSM were identified associated with eCCA could be acted as biomarker for diagnosis of eCCA. | 86 |
| Classification of iCCA | Copy number alterations and classification | 53 iCCA patients | iCCA can be grouped and targeted based on their copy number alterations areas such as 1p, 3p, 7p, etc. | 87 |