Dataset Information

Proteomic analysis identifies deregulated metabolic and oxidative-associated proteins in Italian intrahepatic cholangiocarcinoma patients.

ABSTRACT:

Background

Cholangiocarcinoma (CCA) is an aggressive disease with poor prognosis. A molecular classification based on mutational, methylation and transcriptomic features could allow identifying tailored therapies to improve CCA patient outcome. Proteomic remains partially unexplored; here, we analyzed the proteomic profile of five intrahepatic cholangiocarcinoma (ICC) derived from Italian patients undergone surgery and one normal bile duct cell line.

Methods

Proteome profile was investigated by using 2D electrophoresis followed by Mass Spectrometry (MS). To validate proteomic data, the expression of four overexpressed proteins (CAT, SOD, PRDX6, DBI/ACBP) was evaluated by immunohistochemistry in an independent cohort of formalin fixed, paraffin-embedded (FFPE) ICC tissues. We also compared proteomic data with those obtained by transcriptomic profile evaluated by microarray analysis of the same tissues.

Results

We identified 19 differentially expressed protein spots, which were further characterized by MS; 13 of them were up- and 6 were down-regulated in ICC. These proteins are mainly involved in redox processes (CAT, SODM, PRDX2, PRDX6), in metabolism (ACBP, ACY1, UCRI, FTCD, HCMS2), and cell structure and organization (TUB2, ACTB). CAT is overexpressed in 86% of patients, PRDX6 in 73%, SODM in 100%, and DBI/ACBP in 81% compared to normal adjacent tissues. A concordance of 50% between proteomic and transcriptomic data was observed.

Conclusions

This study pointed out that the impairment of the metabolic and antioxidant systems, with a subsequent accumulation of free radicals, might be a key step in CCA development and progression.

SUBMITTER: Cavalloni G

PROVIDER: S-EPMC8317365 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Chemotherapy resistance is a relevant clinical issue in the tumor treatment, in particular in biliary tract carcinoma (BTC), for which there are no effective therapies, neither in the first nor in the second line. The development of chemoresistant cell lines as experimental models to investigate the mechanisms of resistance and identify alternative druggable pathways is mandatory. In BTC, in which genetics and biological behavior depend on the etiology, ethnicity and anatomical site of origin, the creation of models that better recapitulate these characteristics is even more crucial. Here we have established and characterized an intrahepatic cholangiocarcinoma (iCCA) cell line derived from an Italian patient, called 82.3. Cells were isolated from a patient-derived xenograft and, after establishment, immunophenotypic, biological, genetic, molecular characteristics and tumorigenicity in vivo in NOD/SCID mice were investigated. 82.3 cells exhibited epithelial morphology and cell markers (EPCAM, CK7 and 19); they also expressed different cancer stem markers (CD44, CD133, CD49b, CD24, Stro1, PAX6, FOXA2, OCT3 / 4) and under anchorage-independent and serum-free conditions were capable of originating cholangiospheres. The population doubling time was approximately 53 hours. In vitro they demonstrated a poor ability to migrate, but in vivo, 82.3 cells retained their tumorigenicity, with a long latency period (16 weeks). Genetic identity using DNA fingerprinting analysis revealed 16 different loci and the cell line was characterized by a complex hyperdiploid karyotype. Furthermore, 82.3 cells showed cross-resistance to gemcitabine, 5-fluorouracil, carboplatin and oxaliplatin; in fact their genetic profile showed that in a panel of genes (n = 168), specific for drug resistance and related to the epithelial-mesenchymal transition, 60% of them were deregulated in 82.3 cells compared to a control iCCA cell line sensitive to chemotherapeutics. In conclusion, we have created new iCCA cell line of Caucasian origin that could be exploited as a preclinical model to study drug resistance mechanisms and to identify alternative therapies to improve the prognosis of this tumor type.

Project description:Intrahepatic cholangiocarcinoma (ICC) is an aggressive cancer arising from the bile ducts with a need for earlier diagnosis and a greater range of treatment options. KRAS/NRAS mutations are common in ICC tumours and 6-32% of patients also have isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) gene mutations associated with metabolic changes. This feasibility study investigated sequencing circulating tumour DNA (ctDNA) combined with metabolite profiling of plasma as a method for biomarker discovery in ICC patients. Plasma was collected from four ICC patients receiving radio-embolisation and healthy controls at multiple time points. ctDNA was sequenced using Ampliseq cancer hotspot panel-v2 on Ion Torrent PGM for single nucleotide variants (SNV) detection and with Illumina whole genome sequencing for copy number variants (CNV) and further targeted examination for SNVs. Untargeted analysis of metabolites from patient and control plasma was performed using liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-MS/MS). Metabolite identification was performed using multi-parameter comparisons with analysis of authentic standards, and univariate statistical analysis was performed to identify differences in metabolite abundance between patient and control samples. Recurrent somatic SNVs and CNVs were identified in ctDNA from three out of four patients that included both NRAS and IDH1 mutations linked to ICC. Plasma metabolite analysis revealed biomarker metabolites associated with ICC and in particular 2-hydroxyglutarate (2-HG) levels were elevated in both samples from the only patient showing a variant allele in IDH1. A reduction in the number of CNVs was observed with treatment. This study demonstrates that ctDNA and metabolite levels can be identified and correlated in ICC patient blood samples and differentiated from healthy controls. We conclude that combining genomic and metabolic analysis of plasma offers an effective approach to biomarker identification with potential for disease stratification and early detection studies.