The research on the molecular pathology of pancreatic cancer (PCC) has not been in-depth enough, and there is a lack of comprehensive analysis of the transcriptomics and clinical characteristics of the disease to determine the biomarkers related to the disease and prognosis. Therefore, finding the new targets is the motivation of this research.
What did the researchers do and find?
Weighted Gene Co-expression Network Analysis (WGCNA) and differential expression gene (DEGs) analysis were used to examine the transcriptional expression data of pancreatic cancer (PCC) related to the patient’s clinical status collected from the cancer genome atlas and Gene Expression Omnibus databases. Then, through protein-protein interaction (PPI) analysis, Maximal Clique Centrality scores from the CytoHubba plugin in Cytoscape, combined with survival analysis and COX regression and, the group of researchers from Graduate School of North China University of Science and Technology and Qilu Hospital of Shandong University further identified the TSPAN1 closely linked to the PCC progression and prognosis. Their research offers good clinical data and transcriptomic evidence to support the view that TSPAN1 is tightly aligned to the PCC prognosis.
What is the contribution of this study to our knowledge?
In conclusion,TSPAN1 may be involved in the occurrence and development of PCC. It is a critical marker for diagnosis and prognosis and a potential target for the treatment of PCC.
Ma C, Cui Z, Wang Y, ZhangL, Wen J, Guo H, Li N, Zhang W. Bioinformatics analysis reveals TSPAN1 as a candidate biomarker of progression and prognosis in pancreatic cancer. Bosn J of Basic Med Sci. 2020
Editor: Edna Skopljak, MD