Gene signature and connectivity mapping to assist with drug prediction for pancreatic ductal adenocarcinoma

Introduction

The prognosis of patients with pancreatic ductal adenocarcinoma (PDAC) is highly variable and there is a paucity of effective treatment options for patients with PDAC. Genome-wide analyses may allow for potential drugs to be identified using differentially expressed genes, as well as constructing protein interaction networks and molecule-gene connectivity mapping.

Methods

Microarray data of RNA expression profiling of PDAC and normal pancreas tissues were downloaded from the Gene Expression Omnibus (GEO). Functional and pathway enrichment information of the DEGs was obtained using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Corresponding homologous proteins were analyzed by protein-protein interaction analysis. Survival-related hub genes were screened and potential therapeutic drugs for PDAC were identified using the connectivity mapping (cMap).

Results

Of 18,229 PDAC genes assessed using RNA expression profiling from 118 PDAC tumor samples and 13 normal pancreatic tissue samples, 1502 and 744 genes were upregulated and downregulated, respectively, versus normal pancreas tissue. Protein-protein interaction analysis revealed 10 upregulated hub genes (ITGB1, ITGAV, SDC1, KRAS, CCNB2, COL1A2, AURKA, CDC20, COL1A1, COL3A1) and 10 downregulated hub genes (CPB1, CPA1, CPA2, CTRB2, CTRC, CELA3A, CELA2B, PRSS3, CELA2A, REG1A). The connectivity mapping score related to this hub gene list was used to generate the candidate drugs for PDAC treatment, which includes tyrosine kinase inhibitors (lucitanib, lapatinib, ceritinib and CYT-387), serine/threonine protein kinase inhibitors (roscovitine, BS-181, purvalanol-a, MK-2206 and palomid-529) and other small molecules.

Conclusion

Using available genetic atlas data, potential drug candidates for treatment of PDAC were identified based on differentially expressed genes, protein interaction analysis and connectivity mapping. These results may help focus efforts on identifying targeted agents with potential therapeutic efficacy for evaluation in prospective clinical trials of patients with PDAC.

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