Expression profile of SYNE3 and bioinformatic analysis of its prognostic value and functions in tumors

Abstract Background Spectrin repeat containing nuclear envelope family member 3 (SYNE3) encodes an essential component of the linker of the cytoskeleton and nucleoskeleton (LINC) complex, namely nesprin-3. In a tumor, invasiveness and metastasis rely on the integrity of the LINC complex, while the role of SYNE3/nesprin-3 in cancer is rarely studied. Methods Here, we explored the expression pattern, prognostic value, and related mechanisms of SYNE3 through both experimental and bioinformatic methods. We first detected SYNE3 in BALB/c mice, normal human tissues, and the paired tumor tissues, then used bioinformatics databases to verify our results. We further analyzed the prognostic value of SYNE3. Next, we predicted miRNA targeting SYNE3 and built a competing endogenous RNA (ceRNA) network and a transcriptional network by analyzing data from the cancer genome atlas (TCGA) database. Interacting genes of SYNE3 were predicted, and we further performed GO and KEGG enrichment analysis on these genes. Besides, the relationship between SYNE3 and immune infiltration was also investigated. Results SYNE3 exhibited various expressions in different tissues, mainly located on nuclear and in cytoplasm sometimes. SYNE3 expression level had prognostic value in tumors, possibly by stabilizing nucleus, promoting tumor cells apoptosis, and altering tumor microenvironment. Additionally, we constructed a RP11-2B6.2-miR-149-5p-/RP11-67L2.2-miR-330-3p-SYNE3 ceRNA network and a SATB1-miR-149-5p-SYNE3 transcriptional network in lung adenocarcinoma to support the tumor-suppressing role of SYNE3. Conclusions Our study explored novel anti-tumor functions and mechanisms of SYNE3, which might be useful for future cancer therapy.

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Expression profile of SYNE3 and bioinformatic analysis of its prognostic value and functions in tumors

10.21203/rs.3.rs-17159/v1 ◽

2020 ◽

Author(s):

Liwei Liao ◽

Longshan Zhang ◽

Mi Yang ◽

Xiaoqing Wang ◽

Weiqiang Huang ◽

...

Keyword(s):

Prognostic Value ◽

Lung Squamous Cell Carcinoma ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Transcriptional Network ◽

The Cancer Genome Atlas ◽

Linc Complex ◽

Spectrin Repeat ◽

Cerna Network

Abstract Background: Spectrin repeat containing nuclear envelope family member 3 (SYNE3) encodes an important component of linker of cytoskeleton and nucleoskeleton (LINC) complex, namely nesprin-3. In tumor, invasiveness and metastasis rely on the integrity of LINC complex, while the role of SYNE3/nesprin-3 in cancer is rarely studied. Methods: Here, we explored the expression pattern, prognostic value and related mechanisms of SYNE3 through both experimental and bioinformatic methods. We first detected SYNE3 in BALB/c mice, normal human tissues and the paired tumor tissues, then used bioinformatic databases to verify our results. We further analyzed the prognostic value of SYNE3. Next, we predicted miRNA targeting SYNE3 and built a competing endogenous RNA (ceRNA) network and a transcriptional network by analyzing data from the cancer genome atlas (TCGA) database. Interacting genes of SYNE3 were predicted, and we further performed GO and KEGG enrichment analysis on these genes. Besides, the relationship of SYNE3 and immune infiltration was also investigated. Results: SYNE3 exhibited various expressions in different tissues, mainly located on nuclear and in cytoplasm sometimes. SYNE3 expression level had prognostic value in tumors, possibly by stablizing nucleus, promoting tumor cells apoptosis and altering tumor microenvironment. Additionally, we constructed a RP11-2B6.2-miR-149-5p-/LINC01094-miR-330-3p-SYNE3 ceRNA network and a SATB1-miR-149-5p-SYNE3 transcriptional network in lung squamous cell carcinoma to support the tumor-suppressing role of SYNE3. Conclusions: Our study explored novel anti-tumor functions and mechanisms of SYNE3, which might be useful for future cancer therapy.

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Integrative and Comprehensive Pancancer Analysis of Regulator of Chromatin Condensation 1 (RCC1)

International Journal of Molecular Sciences ◽

10.3390/ijms22147374 ◽

2021 ◽

Vol 22 (14) ◽

pp. 7374

Author(s):

Changwu Wu ◽

Yingjuan Duan ◽

Siming Gong ◽

Sonja Kallendrusch ◽

Nikolas Schopow ◽

...

Keyword(s):

Cell Cycle ◽

Chromatin Condensation ◽

Treatment Strategies ◽

Enrichment Analysis ◽

Tissue Expression ◽

The Cancer Genome Atlas ◽

Malignant Neoplasms ◽

Nucleotide Exchange ◽

Genome Database

Regulator of Chromatin Condensation 1 (RCC1) is the only known guanine nucleotide exchange factor that acts on the Ras-like G protein Ran and plays a key role in cell cycle regulation. Although there is growing evidence to support the relationship between RCC1 and cancer, detailed pancancer analyses have not yet been performed. In this genome database study, based on The Cancer Genome Atlas, Genotype-Tissue Expression and Gene Expression Omnibus databases, the potential role of RCC1 in 33 tumors’ entities was explored. The results show that RCC1 is highly expressed in most human malignant neoplasms in contrast to healthy tissues. RCC1 expression is closely related to the prognosis of a broad variety of tumor patients. Enrichment analysis showed that some tumor-related pathways such as “cell cycle” and “RNA transport” were involved in the functional mechanism of RCC1. In particular, the conducted analysis reveals the relation of RCC1 to multiple immune checkpoint genes and suggests that the regulation of RCC1 is closely related to tumor infiltration of cancer-associated fibroblasts and CD8+ T cells. Coherent data demonstrate the association of RCC1 with the tumor mutation burden and microsatellite instability in various tumors. These findings provide new insights into the role of RCC1 in oncogenesis and tumor immunology in various tumors and indicate its potential as marker for therapy prognosis and targeted treatment strategies.

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Knockdown of PGM1 Synergistically Enhances Anticancer Effects of Orlistat in Gastric Cancer Under Glucose Deprivation

10.21203/rs.3.rs-650761/v1 ◽

2021 ◽

Author(s):

Bo Cao ◽

Huan Deng ◽

Hao Cui ◽

Ruiyang Zhao ◽

Hanghang Li ◽

...

Keyword(s):

Gastric Cancer ◽

Cell Proliferation ◽

Lipid Metabolism ◽

Fatty Acid Synthase ◽

Enrichment Analysis ◽

Glucose Deprivation ◽

Metabolic Reprogramming ◽

The Cancer Genome Atlas

Abstract Background Phosphoglucomutase 1 (PGM1) acts as an important regulator in glucose metabolism. However, the role of PGM1 in gastric cancer (GC) remains unclear. This study aims to investigate the role of PGM1 and develop novel regimens based on metabolic reprogramming in GC. MethodsCorrelation and enrichment analysis of PGM1 was conducted based on The Cancer Genome Atlas database. Data derived from the Kaplan-Meier Plotter database were analyzed for correlations between PGM1 expression and survival time of GC patients. CCK-8, EdU, flow cytometry assays, generation of subcutaneous tumor and lung metastasis mouse models were used to determine growth and metastasis in vitro and in vivo. Cell glycolysis was detected by a battery of glycolytic indicators, including lactate, pyruvic acid, ATP production and glucose uptake. Fatty Acid Synthase (FASN) activity and detection of lipid regulators levels by western blot were used to reflect on the cell lipid metabolism. ResultsCorrelation and enrichment analysis suggested that PGM1 was closely associated with cell proliferation and metabolism. PGM1 was overexpressed in GC tissues and cell lines. High PGM1 expression served as an indicator of shorter survival for specific subpopulation of GC patients, which was also correlated with some clinicopathological features, including T stage and TNM stage. Under low glucose conditions, knockdown of PGM1 significantly suppressed cell proliferation and glycolysis levels, whereas lipid metabolism was enhanced. Orlistat, as a drug that was designed to inhibit FASN activity for obesity treatment, effectively induced apoptosis, suppressed FASN activity. However, orlistat conversely increased glycolytic levels in GC cells. Orlistat exhibited more significant inhibitive effects on GC progression after knockdown of PGM1 under glucose deprivation due to combination of glycolysis and lipid metabolism. ConclusionsDownregulation of PGM1 expression under glucose deprivation synergistically enhanced anti-cancer effects of orlistat. This combination application may serve as a novel strategy for GC treatment.

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Identification of Core Genes and Screening of Potential Targets in Glioblastoma Multiforme by Integrated Bioinformatic Analysis

Frontiers in Oncology ◽

10.3389/fonc.2020.615976 ◽

2021 ◽

Vol 10 ◽

Author(s):

Ji’an Yang ◽

Qian Yang

Keyword(s):

Glioblastoma Multiforme ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Low Grade ◽

Hypergeometric Test ◽

Ppi Network ◽

Neuropsychiatric Diseases ◽

Core Genes

Glioblastoma multiforme is the most common primary intracranial malignancy, but its etiology and pathogenesis are still unclear. With the deepening of human genome research, the research of glioma subtype screening based on core molecules has become more in-depth. In the present study, we screened out differentially expressed genes (DEGs) through reanalyzing the glioblastoma multiforme (GBM) datasets GSE90598 from the Gene Expression Omnibus (GEO), the GBM dataset TCGA-GBM and the low-grade glioma (LGG) dataset TCGA-LGG from the Cancer Genome Atlas (TCGA). A total of 150 intersecting DEGs were found, of which 48 were upregulated and 102 were downregulated. These DEGs from GSE90598 dataset were enriched using the overrepresentation method, and multiple enriched gene ontology (GO) function terms were significantly correlated with neural cell signal transduction. DEGs between GBM and LGG were analyzed by gene set enrichment analysis (GSEA), and the significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways involved in synapse signaling and oxytocin signaling pathways. Then, a protein-protein interaction (PPI) network was constructed to assess the interaction of proteins encoded by the DEGs. MCODE identified 2 modules from the PPI network. The 11 genes with the highest degrees in module 1 were designated as core molecules, namely, GABRD, KCNC1, KCNA1, SYT1, CACNG3, OPALIN, CD163, HPCAL4, ANK3, KIF5A, and MS4A6A, which were mainly enriched in ionic signaling-related pathways. Survival analysis of the GSE83300 dataset verified the significant relationship between expression levels of the 11 core genes and survival. Finally, the core molecules of GBM and the DrugBank database were assessed by a hypergeometric test to identify 10 drugs included tetrachlorodecaoxide related to cancer and neuropsychiatric diseases. Further studies are required to explore these core genes for their potentiality in diagnosis, prognosis, and targeted therapy and explain the relationship among ionic signaling-related pathways, neuropsychiatric diseases and neurological tumors.

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The Role of Early Growth Response 1 in the Prognostic Value and Cell Migration of Breast Cancer

10.21203/rs.3.rs-136417/v1 ◽

2021 ◽

Author(s):

Leiyu Hao ◽

Fengru Huang ◽

Xinqian Yu ◽

Bujie Xu ◽

Yan Liu ◽

...

Keyword(s):

Breast Cancer ◽

Cell Migration ◽

Protein Expression ◽

Prognostic Value ◽

Growth Response ◽

Expression Patterns ◽

Early Growth ◽

The Cancer Genome Atlas ◽

Early Growth Response

Abstract Background: Early growth response family members (EGRs), EGR1-4, have increasingly attracted attention in multiple cancers. However, the exact expression patterns and prognostic values of EGRs in the progress of breast cancer (BRCA) remain largely unknown. Methods: The mRNA expression and prognostic characteristics of EGRs were examined by the Cancer Genome Atlas (TCGA), Oncomine and Kaplan-Meier plotter. Enrichment analyses were conducted based on protein-protein interaction (PPI) network. The Tumor Immune Estimation Resource (TIMER) database and MethSurv were further explored. The protein expression level of EGR1 and cell migration were measured by Western blotting, immunohistochemistry, wound-healing assay and Boyden chamber assay in BRCA. Results: The transcriptional levels of EGR1/2/3 displayed significantly low expression in BRCA compared to that in normal tissues, while EGR4 was shown adverse expression pattern. Survival analysis revealed up-regulated EGR1-4 were remarkably associated with favorable relapse-free survival (RFS). A close correlation with specific tumor-infiltrating immune cells (TIICs) and several CpG sites of EGRs were exhibited. Immunohistochemistry assays showed that the protein expression of EGR1 was remarkably downregulated in BRCA compared to that in paracancerous tissues. Cell migration of MCF10A cells was increased after the silence of EGR1 by siRNA transfection.Conclusions: This study provides a novel insight to the role of EGR1 in the prognostic value and cell migration of BRCA.

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Integrative Analysis of Three Novel Competing Endogenous RNA Biomarkers with a Prognostic Value in Lung Adenocarcinoma

BioMed Research International ◽

10.1155/2020/2837906 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Juan Tan ◽

Weimin Wang ◽

Bin Song ◽

Yingjian Song ◽

Zili Meng

Keyword(s):

High Risk ◽

Lung Adenocarcinoma ◽

Prognostic Value ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Cerna Network ◽

Kaplan Meier ◽

Function Enrichment Analysis ◽

Pathway Function ◽

Function Enrichment

Increasing evidence has shown competitive endogenous RNAs (ceRNAs) play key roles in numerous cancers. Nevertheless, the ceRNA network that can predict the prognosis of lung adenocarcinoma (LUAD) is still lacking. The aim of the present study was to identify the prognostic value of key ceRNAs in lung tumorigenesis. Differentially expressed (DE) RNAs were identified between LUAD and adjacent normal samples by limma package in R using The Cancer Genome Atlas database (TCGA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway function enrichment analysis was performed using the clusterProfiler package in R. Subsequently, the LUAD ceRNA network was established in three steps based on ceRNA hypothesis. Hub RNAs were identified using degree analysis methods based on Cytoscape plugin cytoHubba. Multivariate Cox regression analysis was implemented to calculate the risk score using the candidate ceRNAs and overall survival information. The survival differences between the high-risk and low-risk ceRNA groups were determined by the Kaplan-Meier and log-rank test using survival and survminer package in R. A total of 2,989 mRNAs, 185 lncRNAs, and 153 miRNAs were identified. GO and KEGG pathway function enrichment analysis showed that DE mRNAs were mainly associated with “sister chromatid segregation,” “regulation of angiogenesis,” “cell adhesion molecules (CAMs),” “cell cycle,” and “ECM-receptor interaction.” LUAD-related ceRNA network was constructed, which comprised of 54 nodes and 78 edges. Top ten hub RNAs (hsa-miR-374a-5p, hsa-miR-374b-5p, hsa-miR-340-5p, hsa-miR-377-3p, hsa-miR-21-5p, hsa-miR-326, SNHG1, RALGPS2, and PITX2) were identified according to their degree. Kaplan-Meier survival analyses demonstrated that hsa-miR-21-5p and RALGPS2 had a significant prognostic value. Finally, we found that a high risk of three novel ceRNA interactions (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) was positively associated with worse prognosis. Three novel ceRNAs (SNHG1-hsa-miR-21-5p-RALGPS2, SNHG1-hsa-miR-326-RALGPS2, and SNHG1-hsa-miR-377-3p-RALGPS2) might be potential biomarkers for the prognosis and treatment of LUAD.

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Construction and analysis of the lncRNA-miRNA-mRNA network based on competitive endogenous RNA reveal functional lncRNAs in oral cancer

10.21203/rs.3.rs-18709/v2 ◽

2020 ◽

Author(s):

Junhao Yin ◽

Xiaoli Zeng ◽

Zexin Ai ◽

Miao Yu ◽

Yang’ou Wu ◽

...

Keyword(s):

Oral Cancer ◽

Expression Profiles ◽

Topological Analysis ◽

Enrichment Analysis ◽

Clinical Information ◽

R Package ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Cerna Network ◽

Competitive Endogenous Rna

Abstract Background: A growing evidence suggests that long non-coding RNAs (lncRNAs) can function as a microRNA (miRNA) sponge in various diseases including oral cancer. However, the pathophysiological function of lncRNAs remains unclear. Methods: Based on the competitive endogenous RNA (ceRNA) theory, we constructed a lncRNA-miRNA-mRNA network in oral cancer with the human expression profiles GSE74530 from the Gene Expression Omnibus (GEO) database. We used topological analysis to determine the hub lncRNAs in the regulatory ceRNA network. Then, function enrichment analysis was performed using the clusterProfiler R package. Clinical information was downloaded from The Cancer Genome Atlas (TCGA) database and survival analysis was performed with Kaplan-Meier analysis. Results: A total of 238 potential co-dysregulated competing triples were obtained in the lncRNA-associated ceRNA network in oral cancer, which consisted of 10 lncRNA nodes, 41 miRNA nodes and 122 mRNA nodes. Additionally, we found lncRNA HCG22 exhibiting superior potential as a diagnostic and prognostic marker of oral cancer. Conclusions: Our findings provide novel insights to understand the ceRNA regulation in oral cancer and identify a novel lncRNA as a potential molecular biomarker.

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Long Noncoding RNA RP11-357H14.17 Plays an Oncogene Role in Gastric Cancer by Activating ATF2 Signaling and Enhancing Treg Cells

BioMed Research International ◽

10.1155/2021/6635936 ◽

2021 ◽

Vol 2021 ◽

pp. 1-19

Author(s):

Tang Xiaoli ◽

Wang Wenting ◽

Zhang Meixiang ◽

Zuo Chunlei ◽

Hu Chengxia

Keyword(s):

Gastric Cancer ◽

Noncoding Rna ◽

Prognostic Value ◽

Malignant Tumors ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Treg Cells ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Biological Behavior

Background. Gastric cancer (GC) is one of the most common malignant tumors in the world. The potential functions and mechanisms of long noncoding RNAs (lncRNAs) in GC development are still unclear. It is of great significance to explore the prognostic value of LncRNA signatures for GC. Methods. LncRNAs differently expressed in GC and their prognostic value were studied based on The Cancer Genome Atlas (TCGA) database. The functional regulatory network and immune infiltration of RP11-357H14.17 were further studied using a variety of bioinformatics tools and databases. Results. We found that the high expression of RP11-357H14.17 was closely associated with shortened overall survival (OS) and poor prognosis in gastric cancer patients. We also found that its expression was related to clinical features including tumor volume, metastasis, and differentiation. Functional enrichment analysis revealed that RP11-357H14.17 is closely related to enhanced DNA replication and metabolism; ssGSEA analysis implied the oncogenic roles of RP11-357H14.17 was related to ATF2 signaling and Treg cell differentiation. Furthermore, we verified such link by using real-time PCR and IHC staining in human GC samples. Conclusion. We demonstrate that RP11-357H14.17 may play a crucial role in the occurrence, development, and malignant biological behavior of gastric cancer as a potential prognostic marker for gastric cancer.

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The Prognostic Value of m6A-related LncRNAs in Patients with HNSCC

10.21203/rs.3.rs-778502/v1 ◽

2021 ◽

Author(s):

Liu-qing Zhou ◽

Jie-yu Zhou ◽

Yao Hu

Keyword(s):

Prognostic Value ◽

Risk Model ◽

Cox Regression ◽

Predictive Ability ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Cox Regression Analysis ◽

Kaplan Meier ◽

Cancer Genome Atlas

Abstract Background: N6-methyladenosine (m6A) modifications play an essential role in tumorigenesis. m6A modifications are known to modulate RNAs, including mRNAs and lncRNAs. However, the prognostic role of m6A-related lncRNAs in head and neck squamous cell carcinoma (HNSCC) is poorly understood.Methods: Based on LASSO Cox regression, enrichment analysis, univariate and multivariate Cox regression analysis, a risk prognostic model, and consensus clustering analysis, we analyzed the 12 m6A-related lncRNAs in HNSCC samples data using the data from The Cancer Genome Atlas (TCGA) database.Results: We found twelve m6A-related lncRNAs in the training cohort and validated in all cohorts by Kaplan-Meier and Cox regression analyses, and revealing their independent prognostic value in HNSCC. Moreover, ROC analysis was conducted, confirming the strong predictive ability of this signature for HNSCC prognosis. GSEA and detailed immune infiltration analyses revealed specific pathways associated with m6A-related lncRNAs.Conclusions: In this study, a novel risk model including twelve genes (SAP30L-AS1, AC022098.1, LINC01475, AC090587.2, AC008115.3, AC015911.3, AL122035.2, AC010226.1, AL513190.1, ZNF32-AS1, AL035587.1 and AL031716.1) was built. It could accurately predict HNSCC prognosis and provide potential prediction outcome and new therapeutic target for HNSCC patients.

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