Abstract:The aim of this study was to successfully establish an orthotopic murine model using two different human pancreatic adenocarcinoma cell lines and to propose a 3.0 tesla MRI protocol for noninvasive characterization of this model. SW1990 and MIAPaca-2 tumor cells were injected into the pancreas of BALB/C nu/nu mice. Tumor growth rate and morphological information were assessed by 3.0 tesla MRI (T1WI, T2WI and DCE-MRI) and immunohistology. Proliferation of SW1990 was significantly faster than that of MIAPaca-2 (P=0.000), but MIAPaca-2 mice had a significantly shorter survival than SW1990 mice (41 days and 44 days respectively, P=0.027). MRI could reliably monitor tumor growth in both cell lines: the tumors exhibiting a spherical growth pattern showed a high-intensity signal, and the SW1990 group developed significantly larger tumors compared with the MIAPaCa-2 group. There were no statistical differences between the two groups in which tumor size was assessed using electronic calipers and an MRI scan (P=0.680). Both tumors showed a slow gradual enhancement pattern. Immunohistochemistry demonstrated tumor tissues showing high expression of Ki-67. This model closely mimics human pancreatic cancer and permits monitoring of tumor growth and morphological information by noninvasive 3.0 tesla MRI studies reducing the number of mice required.

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[Objective] ZEB2 is known to be participated in several cancers, yet there is no comprehensive analysis about its function in pan-cancer. This study aimed to investigate the role ZEB2 plays in pan-cancer. [Methods] The data was downloaded from the University of California Santa Cruz (UCSC) Xena and the Cancer Genome Atlas (TCGA). The mRNA expression status of ZEB2 was studied in the TCGA_GTEx samples, TCGA samples and paired samples in TCGA, respectively, and protein expression status was obtained from the University of Alabama at Birmingham Cancer data analysis Portal (UALCAN). Kaplan-Meier analysis was applied to 33 kinds of tumors in TCGA, then among the cancers that ZEB2 can affect prognosis, clinical correlation analysis and univariate and multivariate Cox regression analysis were performed. Furthermore, to confirm the prognostic value of ZEB2 in cancers, nomogram models were constructed on lung adenocarcinoma (LUAD) and stomach adenocarcinoma (STAD). The relationship between ZEB2 mRNA expression and immune cell infiltrates was determined by tumor immune estimation resource (TIMER2.0). Protein-protein interaction (PPI) networks were constructed by the STRING. Functional enrichment analysis was also performed using the “ClusterProfiler” package. [Results] ZEB2 was expressed in most tumors, either upregulated or downregulated, and correlated with clinical characteristics in a part of tumors. The expression level of ZEB2 was also found to impact the prognosis of tumors. Additionally, ZEB2 expression was significantly related to immune cells infiltration level in tumor microenvironment. [Conclusion] we propose that ZEB2 has the potential to be a prognostic biomarker and a promising target for cancer immunotherapy.