Identification of the hub genes RUNX2 and FN1 in gastric cancer

Han, Chao; Jin, Lei; Ma, Xuemei; Qin, Hao; Lin, Hui‐Yi; Zhang, Zhongtao

doi:10.1515/med-2020-0405

Cited by 14 publications

(11 citation statements)

References 41 publications

(49 reference statements)

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“…RUNX2 promotes the development of multiple tumors such as prostate cancer and breast cancer and is a negative prognostic indicator of the survival of osteosarcoma. RUNX2, a mesenchymal stem marker [30], was reported by Chao Han et al that the high expression of RUNX2 and low expression of FN1 analyzed using the GEO2R tool could be the poor predictive marker of long survival in diffuse, poorly differentiated, and lymph node-positive GC [31]. Moreover, ZJ Guo et al also found that the levels of RUNX2 expression in gastric cancer tissues were correlated with the differentiation degrees, invasion depth and lymph node metastasis.…”

Section: Discussionmentioning

confidence: 94%

lncRNA-GPAND Promotes Gastric Cancer Progression via RUNX2 and MMP13

Wang¹,

Pei

Wang³

et al. 2021

Preprint

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Background: Gastric cancer (GC) is still one major reason for cancer-related death worldwide and in China, which ranks the second highest common cancer death rate. It is of great importance to study the molecular mechanisms by which gastric cancer develops. Methods: In this study, in situ hybridization histochemistry (ISHH) was used to examine the lncRNA-GPAND expression levels using gastric cancer tissue array. The real-time live-cell imaging system was used to investigate the effect of GPAND on cell proliferation and apoptosis of GC cell lines. Cell cycle of AGS cell line was examined after GPAND was suppressed using the flow cytometry (FCM). Transwell method was used to study the effect of GPAND on the invasion characteristics of GC cell line. Then the next generation sequencing (NGS) was used to study the potential molecular mechanism and the pathway, and the RT-qPCR was performed to verify the potential targets found by NGS method. Results: It was shown that GPAND was significantly over-expressed in the gastric cancer (GC) tissues (n=215) compared with the paired non-cancerous tissues (n=215), the expression levels of GPAND of GC tissues of TNM stage I-II (n=45) were significantly higher than that of stage III-IV (n=147). It has shown that knockdown of GPAND inhibited the AGS and N87 cell proliferation and promoted the cell apoptosis of AGS and N87 cell lines significantly, and the G1 phase percentage was remarkably increased in GPAND knockdown group of AGS cell line compared with control group. Moreover, suppression of GPAND inhibited the AGS cell invasion significantly. It was found via the NGS method that RUNX2 and MMP13 were significantly up-regulated when the GPAND was over-expressed. Conclusions: These observations suggest the lncRNA-GPAND/RUNX2/MMP13 axis to be a viable therapeutic target for gastric cancer.

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Section: Discussionmentioning

confidence: 94%

lncRNA-GPAND Promotes Gastric Cancer Progression via RUNX2 and MMP13

Wang¹,

Pei

Wang³

et al. 2021

Preprint

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“…Semmlinger et al, 2018;Shi et al, 2020;Zhang et al, 2021;. Moreover, these genes play an important role in the progression of several other cancers, for example, FN1 and CLEC5A have been reported to promote proliferation, invasion and metastasis of gastric cancer and glioblastoma (Fan et al, 2019;Han et al, 2020;Wang et al, 2020;Yang et al, 2019a). In line with other findings (Inoue et al, 2019;Milioli et al, 2017;Saatci et al, 2020), we also found a significant positive correlation between low expression of IL18 genes and good prognosis of breast cancer through survival curves, while high expression of FN1 and C3AR1 genes implied poor disease prognosis.…”

Section: Discussionmentioning

confidence: 99%

Prognostic tumor microenvironment gene and the relationship with immune infiltration characteristics in metastatic breast cancer

Yang¹,

LIU²,

ZHANG³

et al. 2022

Biocell

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The aim of this study was to reveal genes associated with breast cancer metastasis, to investigate their intrinsic relationship with immune cell infiltration in the tumor microenvironment, and to screen for prognostic biomarkers. Gene expression data of breast cancer patients and their metastases were downloaded from the GEO, TCGA database. R language package was used to screen for differentially expressed genes, enrichment analysis of genes, PPI network construction, and also to elucidate key genes for diagnostic and prognostic survival. Spearman's r correlation was used to analyze the correlation between key genes and infiltrating immune cells. We screened 25 hub genes, FN1, CLEC5A, ATP8B4, TLR7, LY86, PTGER3 and other genes were differentially expressed in cancer and paraneoplastic tissues.However, patients with higher expression of CD1C, IL-18 breast cancer had a better prognosis in the 10 years survival period, while patients with high expression of FN1, EIF4EBP1 tumors had a worse prognosis. In addition, TP53 and HIF1 genes are closely related to the signaling pathway of breast cancer metastasis. In this study, gene expression of ATP8B4 and CD1C were correlated with cancer tissue infiltration of CD8 + T lymphocytes, while GSE43816, GSE62327 and TCGA databases showed that CD8 + T lymphocytes were closely associated with breast cancer progression. Functional enrichment analysis of genes based on expression differences yielded key genes of prognostic value in the breast cancer microenvironment.

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“…FN1 expression is associated with OS in patients with gastric cancer. FN1 may serve as promising targets for gastric cancer treatment ( Han et al, 2020 ). miR-515-3p directly regulates MMP3 expression by binding to the coding sequence.…”

Section: Discussionmentioning

confidence: 99%

Construction of a Prognostic Immune-Related LncRNA Risk Model for Lung Adenocarcinoma

Shen

Wang

et al. 2021

Front. Cell Dev. Biol.

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BackgroundLung adenocarcinoma (LUAD) originates mainly from the mucous epithelium and glandular epithelium of the bronchi. It is the most common pathologic subtype of non-small cell lung cancer (NSCLC). At present, there is still a lack of clear criteria to predict the efficacy of immunotherapy. The 5-year survival rate for LUAD patients remains low.MethodsAll data were downloaded from The Cancer Genome Atlas (TCGA) database. We used Gene Set Enrichment Analysis (GSEA) database to obtain immune-related mRNAs. Immune-related lncRNAs were acquired by using the correlation test of the immune-related genes with R version 3.6.3 (Pearson correlation coefficient cor = 0.5, P < 0.05). The TCGA-LUAD dataset was divided into the testing set and the training set randomly. Based on the training set to perform univariate and multivariate Cox regression analyses, we screened prognostic immune-related lncRNAs and given a risk score to each sample. Samples were divided into the high-risk group and the low-risk group according to the median risk score. By the combination of Kaplan–Meier (KM) survival curve, the receiver operating characteristic (ROC) (AUC) curve, the independent risk factor analysis, and the clinical data of the samples, we assessed the accuracy of the risk model. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the differentially expressed mRNAs between the high-risk group and the low-risk group. The differentially expressed genes related to immune response between two risk groups were analyzed to evaluate the role of the model in predicting the efficacy and effects of immunotherapy. In order to explain the internal mechanism of the risk model in predicting the efficacy of immunotherapy, we analyzed the differentially expressed genes related to epithelial-mesenchymal transition (EMT) between two risk groups. We extracted RNA from normal bronchial epithelial cell and LUAD cells and verified the expression level of lncRNAs in the risk model by a quantitative real-time polymerase chain reaction (qRT-PCR) test. We compared our risk model with other published prognostic signatures with data from an independent cohort. We transfected LUAD cell with siRNA-LINC0253. Western blot analysis was performed to observed change of EMT-related marker in protein level.ResultsThrough univariate Cox regression analysis, 24 immune-related lncRNAs were found to be strongly associated with the survival of the TCGA-LUAD dataset. Utilizing multivariate Cox regression analysis, 10 lncRNAs were selected to establish the risk model. The K-M survival curves and the ROC (AUC) curves proved that the risk model has a fine predictive effect. The GO enrichment analysis indicated that the effect of the differentially expressed genes between high-risk and low-risk groups is mainly involved in immune response and intercellular interaction. The KEGG enrichment analysis indicated that the differentially expressed genes between high-risk and low-risk groups are mainly involved in endocytosis and the MAPK signaling pathway. The expression of genes related to the efficacy of immunotherapy was significantly different between the two groups. A qRT-PCR test verified the expression level of lncRNAs in LUAD cells in the risk model. The AUC of ROC of 5 years in the independent validation dataset showed that this model had superior accuracy. Western blot analysis verified the change of EMT-related marker in protein level.ConclusionThe immune lncRNA risk model established by us could better predict the prognosis of patients with LUAD.

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Identification of the hub genes RUNX2 and FN1 in gastric cancer

Cited by 14 publications

References 41 publications

lncRNA-GPAND Promotes Gastric Cancer Progression via RUNX2 and MMP13

lncRNA-GPAND Promotes Gastric Cancer Progression via RUNX2 and MMP13

Prognostic tumor microenvironment gene and the relationship with immune infiltration characteristics in metastatic breast cancer

Construction of a Prognostic Immune-Related LncRNA Risk Model for Lung Adenocarcinoma

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