Construction of a prediction model for postoperative prognosis in patients with resectable cholangiocarcinoma based on SIRT2 expression.
10.3724/zdxbyxb-2023-0413
- Author:
Wei WANG
1
;
Wenbin JI
2
;
Zhenyu LYU
2
;
Wanliang SUN
3
;
Yu SHAO
4
,
5
;
Jing LIU
2
;
Yan YANG
6
Author Information
1. Department of Medical Oncology, The First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, Anhui Province, China. 18255249512@163.com.
2. Department of Medical Oncology, The First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, Anhui Province, China.
3. Department of Hepatobiliary Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, Anhui Province, China.
4. National Drug Clinical Trial Center, The First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, Anhui Province, China)
5. *Now works in The Third People's Hospital of Bengbu Affiliated to Bengbu Medical College.
6. Department of Medical Oncology, The First Affiliated Hospital of Bengbu Medical College, Bengbu 233004, Anhui Province, China. qiannianhupo@163.com.
- Publication Type:Journal Article
- Keywords:
Bioinformatics analysis;
Cholangiocarcinoma (CCA);
Clinical significance;
Prognostic model;
Silence information regulator 2 (SIRT2)
- From:
Journal of Zhejiang University. Medical sciences
2023;():1-10
- CountryChina
- Language:English
-
Abstract:
OBJECTIVES:To develop a prediction model for postoperative prognosis in patients with cholangiocarcinoma (CCA) based on the expression of silence information regulator 2 (SIRT2).
METHODS:The differential expression of SIRT2 between CCA and normal tissues was analyzed using TCGA and GEO databases. Gene set enrichment analysis (GSEA) was used to explore potential mechanisms of SIRT2 in CCA. The expression of SIRT2 protein in CCA tissues and normal tissues (including 44 pairs of specimens) was also detected by immunohistochemistry (IHC) staining in 89 resectable CCA patients who underwent surgical treatment in The First Affiliated Hospital of Bengbu Medical College between January 2016 and December 2021. The relationship between SIRT2 expression and clinicopathological characteristics and prognosis of CCA patients was analyzed. A survival prediction model for patients with resectable CCA was constructed with COX regression results, the calibration curve and the time-dependent receiver operating characteristic curve (ROC) were used to evaluate the performance of the constructed model, and the predictive power between this model and the AJCC/TNM staging system (8th Edition) was compared.
RESULTS:SIRT2 mRNA was overexpressed in CCA tissues as shown in TCGA and GEO databases. IHC staining showed that SIRT2 protein expression in CCA tissues was significantly higher than that in adjacent non-tumor tissues. GSEA results showed that elevated SIRT2 expression may be involved in multiple metabolism-related signaling pathway, such as fatty acid metabolism, oxidative phosphorylation, amino acid metabolism, etc. SIRT2 expression level was related to serum triglycerides level, tumor size and lymph node metastasis (all P<0.05). The survival analysis results showed that the patients with higher SIRT2 expression had a significant lower overall survival (OS) than patients with lower SIRT2 expression (P<0.05). Univariate COX regression analysis suggested that pathological differentiation, clinical stage, postoperative treatment and SIRT2 expression level were associated with the prognosis of CCA patients (all P<0.05). Multivariate regression analysis confirmed that clinical stage and SIRT2 expression level were independent predictors of OS in postoperative CCA patients (both P<0.05). A nomogram based on SIRT2 for prediction of survival in postoperative CCA patients was constructed. The C-index of the model was 0.675, and the area under the time-dependent ROC curve (AUC) for predicting survival in the first, second, and third years was 0.879, 0.778, and 0.953, respectively, which were superior to those of AJCC/TNM staging system (8th Edition).
CONCLUSIONS:SIRT2 is highly expressed in CCA tissues, which is associated with poor prognosis in patients with resectable CCA. The nomogram developed based on SIRT2 may have better predictive power than the AJCC/TNM staging system (8th Edition) in prediction of survival of postoperative CCA patients.
