Integrin β (ITGB) superfamily members have been reported to play important roles in multiple biological functions in various cancers. However, the prognostic and oncologic values of ITGB superfamily members have not been systematically investigated in pancreatic cancer (PC). In this study, the mRNA expression and biological functions of ITGB superfamily members in PC were evaluated by bioinformatic analysis. Our results demonstrated that ITGB1, ITGB4, ITGB5 and ITGB6 overexpressions were significantly associated with advanced AJCC stage and histologic grade, and worse prognosis in PC. A prognostic signature based on ITGB1, ITGB4, ITGB5 and ITGB6 showed a reliable predictive performance. Furthermore, one CpGs (cg20545410) in promoter region of ITGB1, four (cg18709893, cg15700850, cg20667796 and cg18326022) of ITGB4, two (cg10977398 and cg03518058) of ITGB5 and one (cg23008083) of ITGB6 were negatively associated with their corresponding mRNA expression, and positively associated with prognosis in PC. We also identified TFAP2A as the potential transcription factor for ITGB4, SP1 for ITGB1 and ITGB6, and FHL2 for ITGB5 and ITGB6. ITGB1, ITGB4, ITGB5 and ITGB6 overexpressions were all significantly involved in focal adhesion signalling pathway. ITGB1 and ITGB5 overexpressions also associated with up‐regulation of TGF‐β and WNT signalling pathway, whereas ITGB4 and ITGB6 overexpressions associated with up‐regulation of Notch signalling pathway. Besides, ITGB1, ITGB5 and ITGB6 overexpressions significantly correlated with immunosuppression in PC. In summary, our study investigated the multilevel prognostic and biological values of ITGB superfamily members in PC.

S100 calcium‐binding protein A (S100A) family members regulate multiple biological functions related to pancreatic cancer (PC) progression and metastasis. However, the prognostic and oncologic values of S100A family have not been systematically investigated in PC. In the present study, the mRNA expression and potential functions of S100A family were investigated by bioinformatic analysis. Our results demonstrated that overexpression of S100A2, S100A6, S100A10, S100A11, S100A14 and S100A16 was significantly associated with higher T stage, advanced histologic grade and worse prognosis in PC. Besides, one CpG of S100A2, three CpG of S100A6, four CpG of S100A10, four CpG of S100A11, two CpG of S100A14 and five CpG of S100A16 were negatively associated with corresponding S100A family members expression and positively associated with overall survival (OS). The signature based on four CpGs showed good prediction ability of OS. Besides, S100A2 overexpression took part in the regulation of mitotic cell cycle, ECM‐receptor interaction and HIF‐1α transcription factor network. Overexpression of S100A6, S100A10, S100A11, S100A14 and S100A16 may impair the infiltration and cytolytic activity of CD8⁺ T cells through focal adhesion‐Ras‐stimulating signalling pathway in PC. Overall, this study explores the multiple prognostic values and oncologic functions of the S100A family in PC.

Pancreatic ductal adenocarcinoma (PDAC) has a hypoxic and desmoplastic tumor microenvironment (TME), leading to treatment failure. We aimed to develop a prognostic classifier to evaluate hypoxia status and hypoxia-related molecular characteristics of PDAC. In this study, we classified PDAC into three clusters based on 16 known hypoxia-inducible factor 1 (HIF-1)-related genes. Nine differentially expressed genes were identified to construct an HIF-1 score system, whose predictive efficacy was evaluated. Furthermore, we investigated oncogenic pathways and immune-cell infiltration status of PDAC with different scores. The C-index of the HIF-1score system for OS prediction in the meta-PDAC cohort and the other two validation cohorts were 0.67, 0.63, and 0.65, respectively, indicating that it had a good predictive value for patient survival. Furthermore, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the HIF-1α score system for predicting 1-, 3-, and 4-year OS indicated the HIF-1α score system had an optimal discrimination of prognostic prediction for PDAC. Importantly, our model showed superior predictive ability compared to previous hypoxia signatures. We also classified PDAC into HIF-1 scores of low, medium, and high groups. Then, we found high enrichment of glycolysis, mTORC1 signaling, and MYC signaling in the HIF-1 score high group, whereas the cGMP metabolic process was activated in the low score group. Of note, analysis of public datasets and our own dataset showed a high HIF-1 score was associated with high immunosuppressive TME, evidenced by fewer infiltrated CD8⁺ T cells, B cells, and type 1 T-helper cells and reduced cytolytic activity of CD8⁺ T cells. In summary, we established a specific HIF-1 score system to discriminate PDAC with various hypoxia statuses and immune microenvironments. For highly hypoxic and immunosuppressive tumors, a combination treatment strategy should be considered in the future.