Identification of critical pathways and potential therapeutic targets in poorly differentiated duodenal papilla adenocarcinoma.

2021 
Background Duodenal papilla carcinoma (DPC) is a rare malignancy of the gastrointestinal tract with high recurrence rate, and the pathogenesis of this highly malignant neoplasm is yet to be fully elucidated. This study aims to identify key genes to further understand the biology and pathogenesis underlying the molecular alterations driving DPC, which could be potential diagnostic or therapeutic targets. Methods Tumor samples of three DPC patients were collected and integrating RNA-seq analysis of tumor tissues and matched normal tissues were performed to discover differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were carried out to understand the potential bio-functions of the DPC differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was constructed for functional modules analysis and identification of hub genes. qRT-PCR of clinical samples was conducted to validate the expression level of the hub genes. Results A total of 110 DEGs were identified from our RNA-seq data, GO and KEGG analyses showed that the DEGs were mainly enriched in multiple cancer-related functions and pathways, such as cell proliferation, IL-17signaling pathway, Jak-STAT signaling pathway, PPAR signaling pathway. The PPI network screened out five hub genes including IL-6, LCN2, FABP4, LEP and MMP1, which were identified as core genes in the network and the expression value were validated by qRT-PCR. The hub genes identified in this work were suggested to be potential therapeutic targets of DPC. Discussion The current study may provide new insight into the exploration of DPC pathogenesis and the screened hub genes may serve as potential diagnostic indicator and novel therapeutic target.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    23
    References
    1
    Citations
    NaN
    KQI
    []