BACKGROUND: It is urgent to explore the potential biomarkers for pancreatic cancer (PC) prognosis and treatment to improve patients' outcomes. METHODS: Firstly, we performed an integrated bioinformatics analysis based on extensive transcriptome data from 615 PC tumors and 329 adjacent tissues, screening for genes with prognostic value. We then validated the prognostic value of OCIAD2, DCBLD2, and SAMD9 in different datasets and analyzed their expression levels in single-cell sequencing datasets of normal, paracancer, primary, and metastatic tissues. Next, we further explored the carcinogenic effect after knocking down the expression of OCIAD2 in PC cancer cell line. Finally, a drug sensitivity analysis was conducted. RESULTS: Differentially expressed genes (DEGs) analysis identified 22 DEGs: ACSL5, ANTXR1, AP1S3, ATP2C2, B3GNT5, C15orf48, CAPG, CTSK, DAPP1, DCBLD2, GPX8, HEPH, IFI44, KRT23, NCF2, OCIAD2, SAMD9, SLC39A10, ST6GALNAC1, TBC1D2, TMSB10 and TSPAN5 with prognostic value in PC, though the related function and mechanism are still unclear. Single-cell sequencing results indicated that OCIAD2 was prominently expressed in ductal cells of primary and metastatic tumors. The expression levels of OCIAD2 mRNA and protein were the highest in pancreatic tumor tissues. Mechanism studies revealed that STAT1 and STAT2 in the JAK-STAT pathway and CCND1, CDK1, and CDK2 in the cell cycle pathway were significantly down-regulated after OCIAD2 knockdown. Drug sensitivity analysis identified 25 compounds significantly associated with OCIAD2. CONCLUSIONS: These results indicate that OCIAD2 is a potential prognostic biomarker and therapeutic target for PC patients.