scholarly journals Global transcriptomic analysis identifiesSERPINE1as a prognostic biomarker associated with epithelial-to-mesenchymal transition in gastric cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7091 ◽  
Author(s):  
Bodong Xu ◽  
Zhigang Bai ◽  
Jie Yin ◽  
Zhongtao Zhang
Keyword(s):  
Gastric Cancer ◽  
Poor Prognosis ◽  
Epithelial To Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Plasminogen Activation ◽  
Mesenchymal Transition ◽  
Qrt Pcr ◽  
Plasminogen Activator System ◽  
Km Plotter

BackgroundThe plasminogen activation system plays a pivotal role in regulating tumorigenesis. In this work, we aim to identify key regulators of plasminogen activation associated with tumorigenesis and explore potential mechanisms in gastric cancer (GC).MethodsGene profiling datasets were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened for and obtained by the GEO2R tool. The Database for Annotation, Visualization and Integrated Discovery was used for GO and KEGG enrichment analysis. Gene set enrichment analysis (GSEA) was performed to verify molecular signatures and pathways among The Cancer Genome Atlas or GEO datasets. Correlations between SERPINE1 and markers of epithelial-to-mesenchymal transition (EMT) were analyzed using the GEPIA database and quantitative real-time PCR (qRT-PCR). Interactive networks of selected genes were built by STRING and Cytoscape software. Finally, selected genes were verified with the Kaplan–Meier (KM) plotter database.ResultsA total of 104 overlapped upregulated and 61 downregulated DEGs were obtained. Multiple GO and KEGG terms associated with the extracellular matrix were enriched among the DEGs. SERPINE1 was identified as the only regulator of angiogenesis and the plasminogen activator system among the DEGs. A high level of SERPINE1 was associated with a poor prognosis in GC. GSEA analysis showed a strong correlation between SERPINE1 and EMT, which was also confirmed with the GEPIA database and qRT-PCR validation. FN1, TIMP1, MMP2, and SPARC were correlated with SERPINE1.The KM plotter database showed that an overexpression of these genes correlated with a shorter survival time in GC patients.ConclusionsIn conclusion, SERPINE1 is a potent biomarker associated with EMT and a poor prognosis in GC. Furthermore, FN1, TIMP1, MMP2, and SPARC are correlated with SERPINE1 and may serve as therapeutic targets in reversing EMT in GC.

Weighted correlation network analysis identifies FN1, COL1A1 and SERPINE1 associated with the progression and prognosis of gastric cancer

2021 ◽  
pp. 1-17
Author(s):  
Qiaoyun Zhao ◽  
Jun Xie ◽  
Jinliang Xie ◽  
Rulin Zhao ◽  
Conghua Song ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Poor Prognosis ◽  
Epithelial Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Correlation Network ◽  
Receptor Interaction ◽  
Hub Genes ◽  
Mesenchymal Transition ◽  
Weighted Correlation

BACKGROUND: Gastric cancer (GC) is one of the most deadliest tumours worldwide, and its prognosis remains poor. OBJECTIVE: This study aims to identify and validate hub genes associated with the progression and prognosis of GC by constructing a weighted correlation network. METHODS: The gene co-expression network was constructed by the WGCNA package based on GC samples and clinical data from the TCGA database. The module of interest that was highly related to clinical traits, including stage, grade and overall survival (OS), was identified. GO and KEGG pathway enrichment analyses were performed using the clusterprofiler package in R. Cytoscape software was used to identify the 10 hub genes. Differential expression and survival analyses were performed on GEPIA web resources and verified by four GEO datasets and our clinical gastric specimens. The receiver operating characteristic (ROC) curves of hub genes were plotted using the pROC package in R. The potential pathogenic mechanisms of hub genes were analysed using gene set enrichment analysis (GSEA) software. RESULTS: A total of ten modules were detected, and the magenta module was identified as highly related to OS, stage and grade. Enrichment analysis of magenta module indicated that ECM-receptor interaction, focal adhesion, PI3K-Akt pathway, proteoglycans in cancer were significantly enriched. The PPI network identified ten hub genes, namely COL1A1, COL1A2, FN1, POSTN, THBS2, COL11A1, SPP1, MMP13, COMP, and SERPINE1. Three hub genes (FN1, COL1A1 and SERPINE1) were finally identified to be associated with carcinogenicity and poor prognosis of GC, and all were independent risk factors for GC. The area under the curve (AUC) values of FN1, COL1A1 and SERPINE1 for the prediction of GC were 0.702, 0.917 and 0.812, respectively. GSEA showed that three hub genes share 15 common upregulated biological pathways, including hypoxia, epithelial mesenchymal transition, angiogenesis, and apoptosis. CONCLUSION: We identified FN1, COL1A1 and SERPINE1 as being associated with the progression and poor prognosis of GC.

scholarly journals IKBIP is a novel EMT-related biomarker and predicts poor survival in glioma

2021 ◽  
Vol 12 (1) ◽  
pp. 009-019
Author(s):  
Ying Yang ◽  
Jin Wang ◽  
Shihai Xu ◽  
Wen Lv ◽  
Fei Shi ◽  
...  
Keyword(s):  
Epithelial To Mesenchymal Transition ◽  
Molecular Subtype ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Transcriptional Level ◽  
Who Grade ◽  
Interacting Protein ◽  
Mesenchymal Transition ◽  
Gene Set ◽  
Substrate Adhesion

Abstract Background In cancer, kappa B-interacting protein (IKBIP) has rarely been reported. This study aimed at investigating its expression pattern and biological function in brain glioma at the transcriptional level. Methods We selected 301 glioma patients with microarray data from CGGA database and 697 glioma patients with RNAseq data from TCGA database. Transcriptional data and clinical data of 998 samples were analyzed. Statistical analysis and figure generating were performed with R language. Results We found that IKBIP expression showed positive correlation with WHO grade of glioma. IKBIP was increased in isocitrate dehydrogenase (IDH) wild type and mesenchymal molecular subtype of glioma. Gene ontology analysis demonstrated that IKBIP was profoundly associated with extracellular matrix organization, cell–substrate adhesion and response to wounding in both pan-glioma and glioblastoma. Subsequent gene set enrichment analysis revealed that IKBIP was particularly correlated with epithelial-to-mesenchymal transition (EMT). To further elucidate the relationship between IKBIP and EMT, we performed gene set variation analysis to screen the EMT-related signaling pathways and found that IKBIP expression was significantly associated with PI3K/AKT, hypoxia and TGF-β pathway. Moreover, IKBIP expression was found to be synergistic with key biomarkers of EMT, especially with N-cadherin, vimentin, snail, slug and TWIST1. Finally, higher IKBIP indicated significantly shorter survival for glioma patients. Conclusions IKBIP was associated with more aggressive phenotypes of gliomas. Furthermore, IKBIP was significantly involved in EMT and could serve as an independent prognosticator in glioma.

scholarly journals Centromere Protein I (CENP-I) Is Upregulated in Gastric Cancer, Predicts Poor Prognosis, and Promotes Tumor Cell Proliferation and Migration

2021 ◽  
Vol 20 ◽  
pp. 153303382110455
Author(s):  
Jiahui Wang ◽  
Xin Liu ◽  
Hong-jin Chu ◽  
Ning Li ◽  
Liu-ye Huang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cell Proliferation ◽  
Poor Prognosis ◽  
Cellular Function ◽  
Mesenchymal Transition ◽  
Qrt Pcr ◽  
Lauren Classification ◽  
Centromere Protein ◽  
Laurén Classification ◽  
And Migration

This study aimed to investigate the expression and cellular function of the centromeric family of proteins (CENPs), especially centromere protein I (CENP-I), in gastric cancer (GC) and identified its clinical significance and cellular functions. CENP-I expression in GC was studied by cDNA microarray, quantitative real-time PCR (qRT-PCR), and immunohistochemistry (IHC), and using datasets from The Cancer Genome Atlas (TCGA), UALCAN, and Gene Expression Omnibus (GEO) databases. Microarray and bioinformatic analyses identified upregulated CENP-A/E/F/H/I/K/P/W and HJURP in stomach adenocarcinoma (STAD), but not in signet ring cell carcinoma (SRCC). Significantly higher CENP-I mRNA expression was also confirmed in 40 pairs of GC tissues than in paired normal gastric tissues by qRT-PCR ( P<.001). IHC showed that elevated CENP-I expression was associated with higher tumor stage, lymph node invasion, increased HER2-positive rate (36.7% vs 10.0%), and intestinal Lauren classification in 69 GC samples compared to paired paracancerous normal tissues. The survival of the high-CENP-I group members was poor compared with that of the low-CENP-I group ( P = .0011). Cox univariate regression analysis identified tumor size ( P = .008), HER2 status ( P = .027), and CENP-I expression ( P = .049) were independent prognostic factors of GC. The cellular function of CENP-I was studied in MKN45 and MKN28 GC cell lines in vitro. Cell proliferation, migration, and apoptosis were determined using CCK-8, transwell assay, TUNEL assay, and flow cytometry. Our results showed that CENP-I promoted GC cell proliferation, inhibited apoptosis, facilitated cell migration, and induced epithelial–mesenchymal transition (EMT), possibly by activating the AKT pathway. CENP-I expression was correlated with genetic signatures of the proliferative subtype of GC, characterized by intestinal Lauren classification, HER2 amplification, and TP53 mutation. In conclusion, this study revealed an elevated CENP-I expression in GC, which was associated with malignant features and poor prognosis of GC patients, and identified its function in modulating cell proliferation, apoptosis, and migration.

scholarly journals AKNA Is a Potential Prognostic Biomarker in Gastric Cancer and Function as a Tumor Suppressor by Modulating EMT-Related Pathways

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Gang Wang ◽  
Dan Sun ◽  
Wenhui Li ◽  
Yan Xin
Keyword(s):  
Gastric Cancer ◽  
Cell Adhesion ◽  
Tumor Suppressor ◽  
Western Blot ◽  
Signaling Pathway ◽  
Gene Set Enrichment Analysis ◽  
Mesenchymal Transition ◽  
Qrt Pcr ◽  
Potential Biomarker ◽  
Cell To Cell Adhesion

The AT-hook transcription factor, AKNA, is a nuclear protein that affects a few physiological and pathological processes including cancer. Here, we investigated the role of AKNA in gastric cancer (GC). By using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot assays, AKNA was found deregulated in both GC cell lines and 32 paired GC tissues. Subsequently, Kaplan-Meier analysis and clinicopathological analysis were conducted using both 32 GC cases’ data above and RNA-Seq data of AKNA in 354 GC patients and the corresponding clinical-pathological data obtained from The Cancer Genome Atlas (TCGA), and AKNA expression was found closely related to location, metastasis, and TNM staging of GC. Then, the potential molecular mechanisms of AKNA in GC were explored by gene set enrichment analysis (GSEA), qRT-PCR, and Western blot assays. AKNA was found to be a hub gene related to homotypic cell to cell adhesion, regulation of cell to cell adhesion, leukocyte cell to cell adhesion, and regulation of T cell proliferation in GC. GO analysis revealed that AKNA involved in the regulation of epithelial-mesenchymal transition (EMT)-related pathways including chemokine signaling pathway, cytokine to cytokine receptor interaction, cell adhesion molecules, and jak-stat signaling pathway in GC. To explore the regulation of AKNA expression, Targetscan and TargetMiner were used to predict the possible miRNA which targeted AKNA and found the expression of AKNA was negatively correlated to miR-762 which could be sponged by circTRNC18. In conclusion, AKNA could function as a tumor suppressor by modulating EMT-related pathways in GC. The expression of AKNA might be regulated by circTRNC18/miR-762 axis. AKNA could serve as a potential biomarker and an effective target for GC diagnosis and therapy.

scholarly journals Increased IGFBP7 Expression Correlates with Poor Prognosis and Immune Infiltration in Gastric Cancer: An Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Qiaoyun Zhao ◽  
Rulin Zhao ◽  
Conghua Song ◽  
Huan Wang ◽  
Jianfang Rong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Biological Processes ◽  
Coexpressed Genes

Abstract Background Insulin-like growth factor binding protein-7 (IGFBP7) contributes to multiple biological processes in various tumors. However, the role of IGFBP7 in gastric cancer (GC) is still undetermined. The study aims to explore the role of IGFBP7 in GC via an integrated bioinformatics analysis.Methods IGFBP7 expression levels in GC and its normal gastric tissues were analyzed using multiple databases, including the Tumor Immune Estimation Resource (TIMER), Oncomine, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The methylation analysis was conducted with MEXPRESS, UALCAN and Xena online tools. The survival analysis was conducted using the Kaplan-Meier Plotter and Gene Expression Profiling Interactive Analysis (GEPIA) databases. Coexpressed genes of IGFBP7 were selected with the cBioPortal tool and enrichment analysis was conducted with the clusterProfiler package in R software. Gene set enrichment analysis (GSEA) was performed to explore the IGFBP7-related biological processes involved in GC. Correlations between IGFBP7 and immune cell infiltrates were analyzed using the TIMER database.Results IGFBP7 expression was significantly upregulated in GC and correlated with stage, grade, tumor status and Helicobacter pylori infection. High IGFBP7 expression and low IGFBP7 methylation levels were significantly associated with short survival of patients with GC. Univariate and multivariate analyses revealed that IGFBP7 was an independent risk factor for GC. The coexpressed genes LHFPL6, SEPTIN4, HSPB2, LAYN and GGT5 predicted unfavorable outcomes of GC. Enrichment analysis showed that the coexpressed genes were involved in extracellular matrix (ECM)-related processes. GSEA indicated that IGFBP7 was positively related to ECM and inflammation-related pathways. TIMER analysis indicated that the IGFBP7 expression level was strongly correlated with genes related to various infiltrating immune cells in GC, especially with gene markers of tumor associated macrophages (TAMs).Conclusions We demonstrate that increased IGFBP7 expression correlates with poor prognosis and immune cell infiltration in GC. IGFBP7 might be a potential biomarker for the diagnosis and targeted therapy for GC.

scholarly journals Transgelin Contributes to a Poor Response of Metastatic Renal Cell Carcinoma to Sunitinib Treatment

Biomedicines ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1145
Author(s):  
Pavla Bouchalova ◽  
Jindrich Beranek ◽  
Petr Lapcik ◽  
David Potesil ◽  
Jan Podhorec ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Epithelial To Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Poor Response ◽  
Gene Set Enrichment Analysis ◽  
Tyrosine Kinase Receptor ◽  
Mesenchymal Transition ◽  
Data Independent Acquisition

Renal cell carcinoma (RCC) represents about 2–3% of all cancers with over 400,000 new cases per year. Sunitinib, a vascular endothelial growth factor tyrosine kinase receptor inhibitor, has been used mainly for first-line treatment of metastatic clear-cell RCC with good or intermediate prognosis. However, about one-third of metastatic RCC patients do not respond to sunitinib, leading to disease progression. Here, we aim to find and characterize proteins associated with poor sunitinib response in a pilot proteomics study. Sixteen RCC tumors from patients responding (8) vs. non-responding (8) to sunitinib 3 months after treatment initiation were analyzed using data-independent acquisition mass spectrometry, together with their adjacent non-cancerous tissues. Proteomics analysis quantified 1996 protein groups (FDR = 0.01) and revealed 27 proteins deregulated between tumors non-responding vs. responding to sunitinib, representing a pattern of deregulated proteins potentially contributing to sunitinib resistance. Gene set enrichment analysis showed an up-regulation of epithelial-to-mesenchymal transition with transgelin as one of the most significantly abundant proteins. Transgelin expression was silenced by CRISPR/Cas9 and RNA interference, and the cells with reduced transgelin level exhibited significantly slower proliferation. Our data indicate that transgelin is an essential protein supporting RCC cell proliferation, which could contribute to intrinsic sunitinib resistance.

scholarly journals miR-154 Influences HNSCC Development and Progression through Regulation of the Epithelial-To-Mesenchymal Transition Process and Could Be Used as a Potential Biomarker

Biomedicines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1894
Author(s):  
Weronika Tomaszewska ◽  
Joanna Kozłowska-Masłoń ◽  
Dawid Baranowski ◽  
Anna Perkowska ◽  
Sandra Szałkowska ◽  
...  
Keyword(s):  
Immune Response ◽  
Epithelial To Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Clinicopathological Parameters ◽  
Mesenchymal Transition ◽  
Diagnostic Potential ◽  
Potential Biomarker

MicroRNAs and their role in cancer have been extensively studied for the past decade. Here, we analyzed the biological role and diagnostic potential of miR-154-5p and miR-154-3p in head and neck squamous cell carcinoma (HNSCC). miRNA expression analyses were performed using The Cancer Genome Atlas (TCGA) data accessed from cBioPortal, UALCAN, Santa Cruz University, and Gene Expression Omnibus (GEO). The expression data were correlated with clinicopathological parameters. The functional enrichment was assessed with Gene Set Enrichment Analysis (GSEA). The immunological profiles were assessed using the ESTIMATE tool and RNAseq data from TCGA. All statistical analyses were performed with GraphPad Prism and Statistica. The study showed that both miR-154-5p and miR-154-3p were downregulated in the HNSCC samples and their expression levels correlated with tumor localization, overall survival, cancer stage, tumor grade, and HPV p16 status. GSEA indicated that individuals with the increased levels of miR-154 had upregulated AKT-MTOR, CYCLIN D1, KRAS, EIF4E, RB, ATM, and EMT gene sets. Finally, the elevated miR-154 expression correlated with better immune response. This study showed that miR-154 is highly involved in HNSCC pathogenesis, invasion, and immune response. The implementation of miR-154 as a biomarker may improve the effectiveness of HNSCC treatment.

scholarly journals Comprehensive Analysis of circRNA-associated Competing Endogenous RNA Networks and Immune Infiltration in Gastric Cancer

2021 ◽  
Author(s):  
beibei xu ◽  
Endian Zheng ◽  
Yi Huang ◽  
Liang Zheng ◽  
Qiaoli Lan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
T Cells ◽  
Immune Cell ◽  
Clinical Stage ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Cell Infiltration ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Ppi Networks

Abstract BackgroundCircular RNA (circRNA) has been shown to be an important regulator in gastric cancer (GC). However, functions and regulatory mechanisms of circRNA-related competitive endogenous RNA (ceRNA) in GC have not been established.MethodsCircRNA data and clinical data were downloaded from the GEO and TCGA databases. The ceRNA and Protein-Protein Interaction (PPI) networks were constructed through bioinformatics analysis. Function enrichment analysis was performed. Additionally, correlations between expression levels of the top 10 hub genes and immune cell infiltration levels, histopathological grade and clinical stage were determined to establish their clinical values. The differentially expressed circRNA (DEcircRNA) was validated by quantitative real-time PCR (qRT-PCR).ResultsScreening of the GEO and TCGA databases revealed a total of 1627 DEcircRNAs, 6516 DEmRNAs, and 1451 DEmiRNAs. The ceRNA interaction network contained 2 circRNAs, 3 miRNAs and 55 mRNAs. Meanwhile, Gene Ontology (GO) analysis revealed a total of 323 biological processes (BP) terms, 53 cellular components (CC) terms, 51 molecular functions (MF) terms, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed 4 signaling pathways. Gene Set Enrichment Analysis (GSEA) analysis revealed that EPHA4, NCAM1 and NRXN1 were positively correlated with the axon guidan and adhesion molecules pathways. Most of top 10 hub genes were positively correlated with B cells, CD8+ T cells, CD4+ T cells, Neutrophils and Dendritic Cell infiltration. Correlation analysis between hub genes and clinical phenotypes revealed that elevated expressions of EPHA4 and KCNA1 indicated poor tissue differentiation and were associated with clinically advanced stages of GC. The qRT-PCR results revealed that the expression of has_circ_0002504 was significantly down-regulated in 3 GC cell lines which was consistent with the results of our bioinformatics analysis.ConclusionsHas_circ_0001998 and has_circ_0002504 are potential diagnostic biomarkers for GC, and the high expressions of both EPHA4 and KCNA1 may predict poor prognosis.

Effect of GPC1 on epithelial-to-mesenchymal transition and stemness and interaction with ITGB1 in gastric cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e15580-e15580
Author(s):  
Shiqing Wang ◽  
Zhenzhen Wu ◽  
Minyu Zhou ◽  
Wangjun Liao
Keyword(s):  
Gastric Cancer ◽  
Western Blot ◽  
Poor Prognosis ◽  
Tumor Metastasis ◽  
Epithelial To Mesenchymal Transition ◽  
Underlying Mechanism ◽  
Mesenchymal Transition ◽  
Normal Tissues ◽  
Epithelial Marker

e15580 Background: Gastric cancer is the fourth frequently diagnosed cancer worldwide and tumor metastasis plays an important role in its poor prognosis. EMT, which occurs during embryonic development and carcinoma progression, contributes to metastasis and regulates stemness. GPC1, a member of the heparan sulfate proteoglycans family, is overexpressed in many types of cancer, and associates with metastasis and tumor progression. However, it is unknown that the functions of GPC1 and its underlying mechanism in gastric cancer. Methods: Immunohistochemistry analysis was performed in 245 GC tissues to explore the relationship between GPC1 and tumor metastasis. Transwell migration and wound-healing assay were conducted to evaluate the effects of GPC1 on migration and invasiveness. Epithelial marker and mesenchymal markers expression in GC cells were detected by Western blot and immunofluorescence. GPC1 expression induced by TGF-β was detected by Western Blot. After GPC1 was knock downed, the metastatic effect and EMT markers induced by TGF-β were detected. Co-Immunoprecipitation was used to detect the interaction between ITGB1 and GPC1. Results: The expression of GPC1 was higher in GC tissues than in adjacent normal tissues and associated with poor prognosis. Knocking down GPC1 suppressed EMT and stemness which reduced metastasis in vivo and vitro by inhibiting Erk1/2 MAPK and FAK/Akt pathways. TGF-β stimulation significantly upregulated the expression of GPC1 whereas knocking down of GPC1 reversed TGF-β-mediated EMT and stemness. Moreover, we found that knocking down GPC1 could downregulate ITGB1 which was known to promote EMT in gastric cancer. Overexpression of ITGB1 counteracted the influence of knocking down GPC1 on EMT and stemness. Furthermore, GPC1 formed a complex with ITGB1, which indicated that the ability of GPC1 to stimulate EMT is ITGB1-dependent. Conclusions: We conclude that GPC1, through its interaction with ITGB1, plays an important role in regulating TGF-β-mediated EMT and stemness, and could be a potential future therapeutic target to prevent progression of gastric cancer.

Identification of a novel small nucleolar RNAs prognostic signature for patients with acute myelocytic leukemia

2020 ◽  
Author(s):  
Rui Huang ◽  
Xiwen Liao ◽  
Qiaochuan Li
Keyword(s):  
Rna Sequencing ◽  
Epithelial To Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Acute Myelocytic Leukemia ◽  
Prognostic Signature ◽  
Mesenchymal Transition

Abstract Background: This study mainly used The Cancer Genome Atlas (TCGA) RNA sequencing dataset to screen prognostic snoRNAs of acute myeloid leukemia (AML), and used for the construction of prognostic snoRNAs signature for AML. Methods: A total of 130 AML patients with RNA sequencing dataset were used for prognostic snoRNAs screenning. SnoRNAs co-expressed genes and differentially expressed genes (DEGs) were used for functional annotation, as well as gene set enrichment analysis (GSEA). Connectivity Map (CMap) also used for potential targeted drugs screening. Results:Through genome-wide screening, we identified 30 snoRNAs that were significantly associated with the prognosis of AML. Then we used the step function to screen a prognostic signature composed of 14 snoRNAs (SNORD72, SNORD38, U3, SNORA73B, SNORD79, SNORA73, SNORD12B, SNORA74, SNORD116-12, SNORA65, SNORA14, snoU13, SNORA75, SNORA31), which can significantly divide AML patients into high- and low-risk groups. Through GSEA, snoRNAs co-expressed genes and DEGs functional enrichment analysis, we screened a large number of potential functional mechanisms of this prognostic signature in AML, such as phosphatidylinositol 3-kinase-Akt ,Wnt, epithelial to mesenchymal transition, T cell receptors, NF-kappa B, mTOR and other classic cancer-related signaling pathways. In the subsequent targeted drug screening using CMap, we also identified six drugs that can be used for AML targeted therapy, they were alimemazine, MG-262, fluoxetine, quipazine, naltrexone and oxybenzone. Conclusion: Our current study was constructed an AML prognostic signature based on the 14 prognostic snoRNAs, which may serve as a novel prognostic biomarker for AML.

Sign in / Sign up

Export Citation Format

Share Document