BACKGROUND & AIMS:We aimed to identify long noncoding RNAs (lncRNAs) that are up-regulated in gastric cancer tissues from patients and study their function in gastric tumor metastasis. METHODS: We collected gastric tumor and nontumor tissues from patients in China and analyzed levels of lncRNAs by microarray analysis, proteins by immunohistochemistry, and RNAs by quantitative reverse-transcription polymerase chain reaction; we compared these with survival times of patients and tumor progression. RNA levels were knocked down or knocked out in BGC-823, SGC-7901, and MKN45 cell lines using small interfering or short hairpin RNAs or clustered regularly interspaced short palindromic repeats (ie, CRISPR)/CRISPR associated protein 9 (ie, Cas9) vectors. Genes were overexpressed from transfected plasmids in HGC-27 cells. Cells were analyzed by Northern blot and immunoblot, polysome profiling assay, and cell invasion assay. Cells were injected into the tail veins or spleens of nude mice or SCID mice; lung and liver tissues were collected, and metastases were counted. lncRNAs were cloned by using rapid amplification of complementary DNA ends. Their interactions with other genes were determined by RNA pulldown and mapping assays. RESULTS: In microarray analyses, we identified 151 lncRNAs expressed at significantly higher levels in gastric tumor vs nontumor tissues. Levels of an lncRNA that we called gastric cancer metastasis associated long noncoding RNA (GMAN) were increased in gastric tumor tissues, compared with nontumor tissues; its up-regulation was associated with tumor metastasis and shorter survival times of patients. The GMAN gene overlaps with the ephrin A1 gene (EFNA1) and was highly expressed in BGC-823 and MKN45 cells. Knockdown of GMAN in these cells did not affect proliferation, colony formation, or adhesion but did reduce their invasive activity in Transwell assays. Ectopic expression of GMAN increased the invasive activity of HGC-27 cells. BGC-823 and MKN45 cells with knockdown of GMAN formed fewer metastases after injection into tail veins of nude mice. Knockdown or knockout of GMAN also reduced levels of ephrin A1 protein in cells. We found that GMAN promoted translation of ephrin A1 messenger RNA into protein by binding to the antisense GMAN RNA (GMAN-AS)-this antisense sequence is also complementary to that of ephrin A1 mRNA. Levels of ephrin A1 protein were also increased in gastric tumors from patients with metastases than in those without metastases. Knockout of ephrin A1 in BGC-823 cells reduced their invasive activity in Transwell assays and ability to form metastases after injection into SCID mice. Ectopic expression of ephrin A1 in BGC-823 cells with knockdown or knockout of GMAN restored their invasive activities and ability form metastases in nude or SCID mice. A CRISPR/Cas9-based strategy to disrupt the GMAN gene significantly reduced the numbers of metastases formed from SGC-7901 cells in mice. CONCLUSIONS: We identified an lncRNA, which we call GMAN, that is increased in gastric tumors from p...
Gastric cancer (GC) is among the most lethal human malignancies, and the leading cause of GC mortality is metastasis. However, the precise mechanism of GC metastasis remains unclear. To screen key transcriptional factors (TFs) involved in GC metastasis, we performed bioinformatics analysis of The Cancer Genome Atlas database and found that Krüppel‐like factor 9 (KLF9) is a GC metastasis‐associated TF. KLF9 is significantly decreased in patients with GC with distant metastasis compared with those patients without distant metastasis. Ectopic expression of KLF9 evidently inhibited the migration and invasion capabilities of GC cells. Conversely, knockdown of KLF9 endowed GC cells with stronger invasive capacity. Moreover, tail intravenous injection confirmed that KLF9 strongly inhibits the lung metastasis process of GC in vivo. Mechanistically, chromatin immunoprecipitation coupled with high‐throughput sequencing data from Encyclopedia of DNA Elements revealed that KLF9 specifically binds to the promoter region of matrix metalloproteinase (MMP)28. Further quantitative real‐time PCR and dual‐luciferase assay indicated that KLF9 directly inhibited MMP28 transcription. Importantly, decreased invasion and metastasis capability of GC cells caused by ectopic KLF9 expression could be rescued via reinforcing MMP28 expression in vivo. Collectively, our study indicates that KLF9 significantly suppresses GC cell invasion and metastasis through inhibiting MMP28 transcription.—Li, Y., Sun, Q., Jiang, M., Li, S., Zhang, J., Xu, Z., Guo, D., Gu, T., Wang, B., Xiao, L., Zhou, T., Zhuo, W. KLF9 suppresses gastric cancer cell invasion and metastasis through transcriptional inhibition of MMP28. FASEB J. 33, 7915–7928 (2019). http://www.fasebj.org
Background: The AJCC staging system is considered as the golden standard in clinical practice. However, it remains some pitfalls in assessing the prognosis of gastric cancer (GC) patients with similar clinicopathological characteristics. We aim to develop a new clinic and genetic risk score (CGRS) to improve the prognosis prediction of GC patients. Methods: The gene expression pro les of the training set from the Asian Cancer Research Group (ACRG) cohort were used for developing genetic risk score (GRS) by LASSO-Cox regression algorithms. CGRS was established by integrating GRS with clinical risk score (CRS) derived from Surveillance, Epidemiology, and End Results (SEER) database. GRS and CGRS were validated in ACRG validation set and other four independent GC cohorts with different data types, such as microarray, RNA sequencing, and qRT-PCR. Multivariable Cox regression was adopted to evaluate the independence of GRS and CGRS in prognosis evaluation.Results: We established GRS based on a nine-gene signature including APOD, CCDC92, CYS1, GSDME, ST8SIA5, STARD3NL, TIMEM245, TSPYL5, and VAT1. GRS and CGRS dichotomized GC patients into high and low risk groups with signi cantly different prognosis in four independent cohorts, including our Zhejiang cohort (all HR > 1, all P < 0.001). Both GRS and CGRS were prognostic signatures independent of the AJCC staging system. Receiver operating characteristic (ROC) analysis showed that area under ROC curve of CGRS was larger than that of the AJCC staging system in most cohorts we studied. Nomogram and web tool (http://39.100.117.92/CGRS/) based on CGRS were developed for clinicians to conveniently assess GC prognosis in clinical practice.Conclusions: CGRS integrating genetic signature with clinical features shows strong robustness in predicting GC prognosis, and can be easily applied in clinical practice through the web application.
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