DPC4 gene expression in primary pancreatic ductal adenocarcinoma: relationship with CT characteristics

Abstract

Objective: To investigate the relationship between CT imaging findings and DPC4 gene expression and to determine the prognostic value of DPC4 gene expression to predict overall survival in patients with pancreatic ductal adenocarcinoma. Methods: Between January and December 2011, we retrospectively analyzed 163 pancreatic ductal adenocarcinomas in 163 patients who had undergone surgical resection (mean age 5 61.8 years; range 5 35-81 years). We divided the study patients into two groups according to DPC4 gene expression: DPC4-expression or DPC4-non-expression group. The CT findings were analyzed by two reviewers. The associations between the CT imaging findings and DPC4 gene expression were evaluated using univariate analysis and multivariate logistic regression analysis. Overall survival was compared according to the DPC4 gene expression (DPC4-expression vs DPC4-nonexpression) using Kaplan-Meier analysis and log-rank testing. To avoid bias, subgroup analyses of CT findings in T3 tumour and overall survival in patients with T3 tumour and R0 resection were performed. Results: Between DPC4-expression group (n 5 75) and DPC4-non-expression group (n 5 88), three CT findings (i.e., tumour margin, peripancreatic infiltration, and the presence of background intraductal pancreatic mucinous neoplasm) were significantly different in univariate analysis. Of these, a well-defined tumour margin was significantly associated with DPC4-expression tumour (adjusted odds ratio 5 2.06; p 5 0.032) in multivariate analysis. Of the total 163 patients, the mean overall survival of the DPC4-expression group was significantly longer than that of the DPC4-non-expression group (30.0 vs 22.0 months; p 5 0.049). Of the 150 T3 tumours, the presence of well-defined tumour margins was also a significant CT finding (adjusted odd ratio 5 2.00; p 5 0.044) in multivariate analysis. However, of 131 patients with T3 tumour and R0 resection, the overall survival period of the DPC4-expression group was not significantly different from that of the DPC4-nonexpression group (24.0 vs 22.0 months; p 5 0.240). Conclusion: The presence of well-defined tumour margins on CT was significantly linked with DPC4-expression tumour. Advances in knowledge: A well-defined tumour margin is an independent CT finding associated with DPC4-expression pancreatic ductal adenocarcinoma.

CT Simplified Radiomic Approach to Assess the Metastatic Ductal Adenocarcinoma of the Pancreas

“…Six of these parameters supported the hypothesis. Regarding the qualitative analysis, we found that tumors with ill-defined margins were significantly more common among metastatic patients: this finding is in line with the study by Choi et al, which observed that PDACs with well-defined margins were significantly associated with DPC4 expression, a tumor-suppressor gene known to have a pivotal role in widespread metastases [ 15 ]. Moreover, hypodense tumors on portal-phase images were significantly more frequent among patients with metastatic spread; this finding was corroborated by the analysis of the density values, that showed lower attenuation values in metastatic patients.…”

“…Previous reports have shown that a radiomic approach to PDAC may show promising results [ 12 , 13 , 14 ], but the application of such analysis to clinical practice is still very limited, due to its complexity. However, a simplified approach to radiomics may be feasible: for example, Choi et al [ 15 ] reported a correlation between non-complex features, as tumor margins, and DPC4 expression in PDAC patients. Since metastases are the most relevant negative prognostic factor in pancreatic ductal adenocarcinoma, the availability of biomarkers that could identify patients that will likely develop metastases would be useful to stratify patients’ prognosis and to optimize their therapeutic management [ 16 ].…”

Prediction of Early Distant Recurrence in Upfront Resectable Pancreatic Adenocarcinoma: A Multidisciplinary, Machine Learning-Based Approach

“…With regard to this last point, the selection of few, simple (that means, easily to be interpreted) features is a relevant approach [ 17 , 18 ] when compared to more complex radiomic signatures relying on several features of doubtful clinical significance, frequently weakening validation for clinical use [ 19 , 20 ]. As an example of interpretable features in the setting of pancreatic adenocarcinoma, Choi and colleagues, for instance, reported a correlation between non-complex shape features like irregular margins and DPC4 expression [ 21 ].…”