<p>FKBP10 Acts as a New Biomarker for Prognosis and Lymph Node Metastasis of Gastric Cancer by Bioinformatics Analysis and in Vitro Experiments</p>

Abstract

To explore the role of FKBP prolyl isomerase 10 (FKBP10) protein in the progression of gastric cancer. Methods: Four independent gastric cancer databases (GSE27342, GSE29272, GSE54129 and TCGA-STAD) were used to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to identify the abnormally active pathways in patients with gastric cancer. Univariate Cox regression analysis was used to identify genes with stable prognostic value in gastric cancer patients based on three independent gastric cancer databases (GSE15459, GSE62254, TCGA-STAD). Gene set enrichment analysis (GSEA) was used to explore the possible pathways related to FKBP10. The reverse transcription-polymerase chain reaction (RT-PCR) was employed to determine the expression of FKBP10 mRNA in the HGC-27 and MKN-7 cell lines. Adhesion assay was used to detect changes in cell adhesion ability. FKBP10, ITGA1, ITGA2, ITGA5, ITGAV, ITGA6, P-AKT 473 , P-AKT 308 , AKT, and β-actin were evaluated by Western blot (WB). Results: We first performed differential expression genes (DEGs) screening of four independent GC databases (GSE27342, GSE29272, GSE54129 and TCGA-STAD). Eighty-nine genes showed consistent up-regulation in GC, the results of pathway analysis showed that they were related to "Focal adhesion". The prognostic value of these 89 genes was tested in three independent GC databases GSE15459, GSE62254 and TCGA-STAD cohort. Finally, 12 genes, in which the expression of FKBP10 was prominently increased in patients with lymph node metastasis (LNM), showed stable prognostic value. The following gene set enrichment analysis (GSEA) also showed that FKBP10 is mainly involved in cell adhesion process, while adhesion experiments confirmed that cell adhesion was down-regulated after silencing FKBP10 in GC cells, and adhesion-related molecules integrin αV and α6 were down-regulated. Conclusion: FKBP10 may be used as a marker for lymph node metastasis of GC and could be used as a potential target for future treatment of GC.

circREEP3 Drives Colorectal Cancer Progression via Activation of FKBP10 Transcription and Restriction of Antitumor Immunity

“…[ 38 ] Additionally, FKBP10 is a biomarker for gastric cancer progression and metastasis. [ 39 ] In our study, we found that FKBP10 was upregulated in CRC tissues and may be a potential marker for prognosis. Our results demonstrated that FKBP10 knockout suppressed CRC growth and metastasis.…”

A Novel Biomarker, FKBP10, for Poor Prognosis Prediction in Patients with Clear Cell Renal Cell Carcinoma

“…In addition, in the endoplasmic reticulum of fibroblasts, the FKBP10 protein binds to Hsp47 (heat shock protein 47) to promote the synthesis of procollagen and formation of mature collagen molecules, thereby forming a more stable complex to construct extracellular matrix [15,16]. FKBP10 expression is aberrant in a variety of malignancies and is often associated with poor prognosis in patients [17,18]. It has been reported that FKBP10 expression is negatively correlated with the survival rate of lung cancer patients, and the regulative effect of FKBP10 on protein translation sustains the growth of lung cancer [12].…”

Annotation of pituitary neuroendocrine tumors with genome-wide expression analysis

“…A prognostic role has also been reported for some of these genes, both negative ( ERRFI1 ) [ 25 ], and positive ( SLC44A3 ) [ 29 ]. Additionally, several of the differentially expressed genes are proposed to be potential therapeutic targets, such as FAIM2 in small cell lung carcinoma [ 18 ], ERRFI1 in pancreatic carcinoma [ 25 ], RASA4 in triple-negative breast carcinoma [ 53 ], FKBP10 in gliomas [ 7 , 18 ], metastatic gastric carcinoma [ 16 ] and lung carcinoma [ 38 ], and CACNA2D in prostate carcinoma [ 18 ]. Overview of the most interesting genes differentially expressed between the cell-lineage based groups of PitNETs has been presented in Table 2 .…”