Prognostic Values and Clinical Significance of S100 Family Member’s Individualized mRNA Expression in Pancreatic Adenocarcinoma

Objective: Pancreatic adenocarcinoma (PAAD) is a common malignant tumor worldwide. S100 family (S100s) is wildly involved in regulating the occurrence, development, invasion, metastasis, apoptosis, and drug resistance of many malignant tumors. However, the expression pattern, prognostic value, and oncological role of individual S100s members in PAAD need to be elucidated. Methods: The transcriptional expression levels of S100s were analyzed through the Oncomine and GEPIA, respectively. The protein levels of S100s members in PAAD were studied by Human Protein Atlas. The correlation between S100 mRNA expression and overall survival and tumor stage in PAAD patients was studied by GEPIA. The transcriptional expression correlation and gene mutation rate of S100s members in PAAD patients were explored by cBioPortal. The co-expression networks of S100s are identified using STRING and Gene MANIA to predict their potential functions. The correlation of S100s expression and tumor-infiltrating immune cells was tested by TIMER. Pathway activity and drug target analyzed by GSCALite. Results: 13 S100s members were upregulated in PAAD tissues. 15 S100s members were associated with TP53 mutation. Expression levels of S100A3/A5/A6/A10/A11/A14/A16/B/P/Z were significantly correlated with the pathological stage. Prognosis analysis demonstrated that PAAD patients with low mRNA levels of S100A1/B/Z or high levels of S100A2/A3/A5/A10/A11/A14/A16 had a poor prognosis. Immuno-infiltration analysis showed that the mRNA levels of S100A10/A11/A14/A16 were correlated with the infiltration degree of macrophages in PAAD. Drug sensitivity analysis showed that PAAD expressing high levels of S100A2/A6/A10/A11/A13/A14/A16 maybe resistant to small molecule drugs. Conclusion: This study identifies the clinical significance and biological functions of the S100s in PAAD, which may provide novel insights for the selection of prognostic biomarkers.