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pmid:32336950

Bioinformatics combined with quantitative proteomics analyses and identification of potential biomarkers in cholangiocarcinoma.

Zijian Da · Long Gao · Gang Su · Jia Yao · Wenkang Fu · Jinduo Zhang · Xu Zhang · Zhaoji Pei · Ping Yue · Bing Bai · Yanyan Lin · Wenbo Meng · Xun Li

Cancer cell international · 2020 doi:10.1186/s12935-020-01212-z

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pmid:32336950
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2026-11-01T15:41:00Z
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2026-11-01T22:44:47Z
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title
Bioinformatics combined with quantitative proteomics analyses and identification of potential biomarkers in cholangiocarcinoma.
doi
10.1186/s12935-020-01212-z
pmid
32336950
authors array · 13 items
[0]
Zijian Da
[1]
Long Gao
[2]
Gang Su
[3]
Jia Yao
[4]
Wenkang Fu
[5]
Jinduo Zhang
[6]
Xu Zhang
[7]
Zhaoji Pei
[8]
Ping Yue
[9]
Bing Bai
[10]
Yanyan Lin
[11]
Wenbo Meng
[12]
Xun Li
journal
Cancer cell international
year
2020
abstract
BACKGROUND: Cholangiocarcinoma (CCA) is an invasive malignancy arising from biliary epithelial cells; it is the most common primary tumour of the bile tract and has a poor prognosis. The aim of this study was to screen prognostic biomarkers for CCA by integrated multiomics analysis. METHODS: The GSE32225 dataset was derived from the Gene Expression Omnibus (GEO) database and comprehensively analysed by using R software and The Cancer Genome Atlas (TCGA) database to obtain the differentially expressed RNAs (DERNAs) associated with CCA prognosis. Quantitative isobaric tags for relative and absolute quantification (iTRAQ) proteomics was used to screen differentially expressed proteins (DEPs) between CCA and nontumour tissues. Through integrated analysis of DERNA and DEP data, we obtained candidate proteins APOF, ITGAV and CASK, and immunohistochemistry was used to detect the expression of these proteins in CCA. The relationship between CASK expression and CCA prognosis was further analysed. RESULTS: Through bioinformatics analysis, 875 DERNAs were identified, of which 10 were associated with the prognosis of the CCA patients. A total of 487 DEPs were obtained by using the iTRAQ technique. Comprehensive analysis of multiomics data showed that CASK, ITGAV and APOF expression at both the mRNA and protein levels were different in CCA compared with nontumour tissues. CASK was found to be expressed in the cytoplasm and nucleus of CCA cells in 38 (45%) of 84 patients with CCA. Our results suggested that patients with positive CASK expression had significantly better overall survival (OS) and recurrence-free survival (RFS) than those with negative CASK expression. Univariate and multivariate analyses demonstrated that negative expression of CASK was a significantly independent risk factor for OS and RFS in CCA patients. CONCLUSIONS: CASK may be a tumour suppressor; its low expression is an independent risk factor for a poor prognosis in CCA patients, and so it could be used as a clinically valuable prognostic marker.
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Matrix files from the GSE32225 dataset were obtained from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. We used the “limma” package to identify DERNAs between CCA tissues and nontumour tissues [16].
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Matrix files from the GSE32225 dataset were obtained from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database.
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sections[4] "Identification of differentially expressed RNAs" paragraph 2
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We used the “limma” package to identify DERNAs between CCA tissues and nontumour tissues [16].
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The data used to sustain the results of this work are included in the article and its supplementary information files.
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The data used to sustain the results of this work are included in the article and its supplementary information files.
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Summary of clinic parameters of CCA patients collected for iTRAQ
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Selection of patients and collection of clinical samples
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Summary of clinic parameters of CCA patients collected for iTRAQ
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Summary of clinical characteristic of CCA patients collected for TMAs
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The Basic Properties of candidate protein
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The summary of relationship between CASK expression and clinicopathological features of CCA patients
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12
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3
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17
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33
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Univariate analysis and multivariate analysis of the relationship of CASK expression with OS among CCA patients
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Relationship between positive CASK expression and overall survival rate
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Univariate analysis and multivariate analysis of the relationship of CASK expression with OS among CCA patients
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0.085
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1.262
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[3]
0.246
[4]
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[6]
[7] array · 7 items
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1.659
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[5]
[6]
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0.001
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1.236
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0.523–2.918
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0.629
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[3]
0.012
[4]
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Univariate analysis and multivariate analysis of the relationship of CASK expression with RFS among CCA patients
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Relationship between positive CASK expression and recurrence-free survival rate
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Univariate analysis and multivariate analysis of the relationship of CASK expression with RFS among CCA patients
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[3]
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0.001
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1.612
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0.035
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[1]
1.377
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[3]
0.095
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[6]
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1.591
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0.103
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[5]
[6]
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1.325
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0.472
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Matrix files from the GSE32225 dataset were obtained from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. We used the “limma” package to identify DERNAs between CCA tissues and nontumour tissues [16].
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candidate proteins APOF, ITGAV and CASK, and immunohistochemistry was used to detect the expression of these p
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Matrix files from the GSE32225 dataset were obtained from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. We used the “limma” package to identify DERNAs between CCA tissues and nontumour tissues [16].
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32336950", "kind": "science-record", "revision": 8, "content_hash": "sha256:0ed1beceff789ed9c070240e19cb1664bc9ea941a6b47e8bc3958c7bfb4dbd8a", "created_at": "2026-11-01T15:41:00Z", "updated_at": "2026-11-01T22:44:47Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics combined with quantitative proteomics analyses and identification of potential biomarkers in cholangiocarcinoma.", "doi": "10.1186/s12935-020-01212-z", "pmid": "32336950", "authors": ["Zijian Da", "Long Gao", "Gang Su", "Jia Yao", "Wenkang Fu", "Jinduo Zhang", "Xu Zhang", "Zhaoji Pei", "Ping Yue", "Bing Bai", "Yanyan Lin", "Wenbo Meng", "Xun Li"], "journal": "Cancer cell international", "year": 2020, "abstract": "BACKGROUND: Cholangiocarcinoma (CCA) is an invasive malignancy arising from biliary epithelial cells; it is the most common primary tumour of the bile tract and has a poor prognosis. The aim of this study was to screen prognostic biomarkers for CCA by integrated multiomics analysis.\nMETHODS: The GSE32225 dataset was derived from the Gene Expression Omnibus (GEO) database and comprehensively analysed by using R software and The Cancer Genome Atlas (TCGA) database to obtain the differentially expressed RNAs (DERNAs) associated with CCA prognosis. Quantitative isobaric tags for relative and absolute quantification (iTRAQ) proteomics was used to screen differentially expressed proteins (DEPs) between CCA and nontumour tissues. Through integrated analysis of DERNA and DEP data, we obtained candidate proteins APOF, ITGAV and CASK, and immunohistochemistry was used to detect the expression of these proteins in CCA. The relationship between CASK expression and CCA prognosis was further analysed.\nRESULTS: Through bioinformatics analysis, 875 DERNAs were identified, of which 10 were associated with the prognosis of the CCA patients. A total of 487 DEPs were obtained by using the iTRAQ technique. Comprehensive analysis of multiomics data showed that CASK, ITGAV and APOF expression at both the mRNA and protein levels were different in CCA compared with nontumour tissues. CASK was found to be expressed in the cytoplasm and nucleus of CCA cells in 38 (45%) of 84 patients with CCA. Our results suggested that patients with positive CASK expression had significantly better overall survival (OS) and recurrence-free survival (RFS) than those with negative CASK expression. Univariate and multivariate analyses demonstrated that negative expression of CASK was a significantly independent risk factor for OS and RFS in CCA patients.\nCONCLUSIONS: CASK may be a tumour suppressor; its low expression is an independent risk factor for a poor prognosis in CCA patients, and so it could be used as a clinically valuable prognostic marker.", "claims": [{"id": "claim-method", "statement": "Matrix files from the GSE32225 dataset were obtained from the GEO (https://www.ncbi.nlm.nih.gov/geo/) database. 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