Lu-Lu Zhai1, Pei-Pei Qiao2, Yue-Shen Sun3, Zhi-Gang Tang1, Tong-Fa Ju4. 1. Department of General Surgery, Renmin Hospital of Wuhan University, Wuhan, China. 2. Ningxia Medical University, Yinchuan, China. 3. Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 4. Department of General Surgery, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Abstract
BACKGROUND: Heat shock protein A2 (HSPA2) is known to relate to the pathogenesis and progress of cancer. This study aimed to investigate the connection between HSPA2 and early postsurgical relapse of pancreatic cancer (PC). METHODS: Expression of HSPA2 in 85 pairs of cancerous and matched noncancerous samples was determined by immunostaining method. The relationship between HSPA2 expression and early postsurgical recurrence was assessed using logistic regression. The performance and potential application of HSPA2 expression to predict early postsurgical recurrence was evaluated by receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). RESULTS: HSPA2 expression in tumor specimens was markedly elevated compared with non-tumor specimens. Logistic regression analysis indicated that HSPA2 upregulation was an independent risk marker for early postsurgical recurrence of PC. ROC curve analysis and DCA demonstrated that both the area under the curve (AUC) and the net benefit of HSPA2 expression were higher than those of other clinicopathologic features in predicting early postsurgical relapse of PC. The combination of HSPA2 expression with other malignant clinicopathologic characteristics had greater AUC and net benefit relative to them alone in predicting early postsurgical recurrence. CONCLUSIONS: Upregulated HSPA2 independently predicts early postsurgical recurrence of PC and has superior predictive performance and potential application value when combined with malignant clinicopathologic features. Our findings reveal that HSPA2 is a promising predictor for early postoperative relapse of PC. 2021 Gland Surgery. All rights reserved.
BACKGROUND: Heat shock protein A2 (HSPA2) is known to relate to the pathogenesis and progress of cancer. This study aimed to investigate the connection between HSPA2 and early postsurgical relapse of pancreatic cancer (PC). METHODS: Expression of HSPA2 in 85 pairs of cancerous and matched noncancerous samples was determined by immunostaining method. The relationship between HSPA2 expression and early postsurgical recurrence was assessed using logistic regression. The performance and potential application of HSPA2 expression to predict early postsurgical recurrence was evaluated by receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). RESULTS: HSPA2 expression in tumor specimens was markedly elevated compared with non-tumor specimens. Logistic regression analysis indicated that HSPA2 upregulation was an independent risk marker for early postsurgical recurrence of PC. ROC curve analysis and DCA demonstrated that both the area under the curve (AUC) and the net benefit of HSPA2 expression were higher than those of other clinicopathologic features in predicting early postsurgical relapse of PC. The combination of HSPA2 expression with other malignant clinicopathologic characteristics had greater AUC and net benefit relative to them alone in predicting early postsurgical recurrence. CONCLUSIONS: Upregulated HSPA2 independently predicts early postsurgical recurrence of PC and has superior predictive performance and potential application value when combined with malignant clinicopathologic features. Our findings reveal that HSPA2 is a promising predictor for early postoperative relapse of PC. 2021 Gland Surgery. All rights reserved.
Entities:
Keywords:
Heat shock protein A2 (HSPA2); pancreatic cancer (PC); recurrence; risk factor; surgery
Authors: L L Bonnycastle; C E Yu; C R Hunt; B J Trask; K P Clancy; J L Weber; D Patterson; G D Schellenberg Journal: Genomics Date: 1994-09-01 Impact factor: 5.736
Authors: D J Dix; J W Allen; B W Collins; P Poorman-Allen; C Mori; D R Blizard; P R Brown; E H Goulding; B D Strong; E M Eddy Journal: Development Date: 1997-11 Impact factor: 6.868