Construction of a prognostic model for radical esophagectomy based on immunohistochemical prognostic markers combined with clinicopathological factors. Issue 9 (3rd March 2023)

• Record Type: Journal Article
• Authors: Wang, Bo; Su, Anna; Li, Mengyan; Wang, Xuecheng; Gao, Yongmei; Su, Liping; Li, Wan; Ma, Yuqing
• Is Part Of: Medicine. Volume 102:Issue 9(2023)
• Page Start: e32889
• Publication Date: 2023-03-03
• Subjects: esophageal squamous cell carcinoma (ESCC) -- GPNMB -- immunohistochemical (IHC) -- prognostic; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000032889
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Esophageal squamous cell carcinoma (ESCC) has a poor prognosis and lacks effective biomarkers to evaluate prognosis and treatment. Glycoprotein nonmetastatic melanoma protein B (GPNMB) is a protein highly expressed in ESCC tissues screened by isobaric tags for relative and absolute quantitation proteomics, which has significant prognostic value in a variety of malignant tumors, but its relationship with ESCC remains unclear. By immunohistochemical staining of 266 ESCC samples, we analyzed the relationship between GPNMB and ESCC. To explore how to improve the ability of ESCC prognostic assessment, we established a prognostic model of GPNMB and clinicopathological features. The results suggest that GPNMB expression is generally positive in ESCC tissues and is significantly associated with poorer differentiation, more advanced American Joint Council on Cancer (AJCC) stage, and higher tumor aggressiveness ( P < .05). Multivariate Cox analysis indicated that GPNMB expression was an independent risk factor for ESCC patients. A total of 188 (70%) patients were randomly selected from the training cohort and the four variables were automatically screened by stepwise regression based on the AIC principle: GPNMB expression, nation, AJCC stage and nerve invasion. Through the weighted term, we calculate the risk score of each patient, and by drawing the receiver operating characteristic curve, we show that the model has good prognostic evaluation performance. The stability of the model was verified by test cohort. Conclusion: GPNMB is a prognostic marker consistent with the characteristics of tumor therapeutic targets. For the first time, we constructed a prognostic model combining immunohistochemical prognostic markers and clinicopathological features in ESCC, which showed higher prognostic efficacy than AJCC staging system in predicting the prognosis of ESCC patients in this region.