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

doi:10.1186/s12935-020-01212-z

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

Cancer Cell Int. 2020 Apr 22:20:130. doi: 10.1186/s12935-020-01212-z. eCollection 2020.

Authors

Zijian Da¹, Long Gao¹, Gang Su², Jia Yao^{1

3}, Wenkang Fu¹, Jinduo Zhang^{4

5

6}, Xu Zhang¹, Zhaoji Pei¹, Ping Yue^{4

5

6}, Bing Bai^{4

5

6}, Yanyan Lin^#^{4

5

6}, Wenbo Meng^#^{1

4

3

2

5

6}, Xun Li^{1

5

6

7}

Affiliations

¹ 1The First Clinical Medical College, Lanzhou University, Lanzhou, 730000 China.
² 4Institute of Genetics, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000 China.
³ 3Division of Scientific Research and Development Planning, The First Hospital of Lanzhou University, Lanzhou, 730000 China.
⁴ 2Department of Special Minimally Invasive Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000 China.
⁵ Gansu Province Institute of Hepatopancreatobiliary, Lanzhou, 730000 China.
⁶ Gansu Province Key Laboratory Biotherapy and Regenerative Medicine, Lanzhou, 730000 China.
⁷ 7The Second Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou, 730000 China.

^# Contributed equally.

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.

Keywords: Bioinformatics; CASK; Cholangiocarcinoma; Multiomics; Prognosis; iTRAQ.