| Literature DB >> 27323782 |
Pu Xia1, Xiao-Yan Xu2.
Abstract
CD44 is a well-recognized stem cell biomarker expressed in colon and gastric cancer. In order to identify whether CD44 mRNA could be used as a prognostic marker in colon and gastric cancer, bioinformatic analyses were used in this study. cBioPortal analysis and COSMIC analysis were used to explore the CD44 mutation. CD44 mRNA levels were evaluated by using SAGE Genie tools and Oncomine analysis. Kaplan-Meier Plotter was performed to identify the prognostic roles of CD44 mRNA in these two cancers. In this study, first, we found that low alteration frequency of CD44 mRNA in colon and gastric cancer. Second, the high CD44 mRNA level was found in colon and gastric cancer, and it correlated with a benign survival rate in gastric cancer. Third, CD4 and CD74 may be used as markers to predict the prognosis of colon and gastric cancer. However, the deep mechanism(s) of these results remains unclear, further studies have to be performed in the future.Entities:
Keywords: CD44; The Cancer Genome Atlas; bioinformatic analyses; colon cancer; gastric cancer
Mesh:
Substances:
Year: 2016 PMID: 27323782 PMCID: PMC5216740 DOI: 10.18632/oncotarget.9998
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1(A) Ideograph of CD44 protein was generated by using Peptide Atlas. (B) An evolutionary tree of CD44 transcript variant was generated by the maximum likelihood analysis.
Figure 2(A) Pie-chart showed the percentage of the mutation type of CD44 in colon and gastric cancer according to COSMIC database. (B) Alteration frequency of CD44 mutation in colon and gastric cancer was analyzed by using BioPortal.
Figure 3Expression profile for CD44 in human cancers found by the SAGE DGED
Figure 4CD44 mRNA was evaluated in colon and gastric cancer by using Oncomine analysis
Prognostic significance of CD44 enriched in colon and gastric cancer.
Figure 5(A) Interaction genes of CD44 were analyzed by using Oncomine. (B) Relationships of CD44, CD4 and CD74 in colon and gastric cancer were analyzed by using the UCSC Cancer Genomics Browser.