Integrative genomic analysis of a novel small nucleolar RNAs prognostic signature in patients with acute myelocytic leukemia

<abstract> <p>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. 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. 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. In 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.</p> </abstract>

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

10.21203/rs.3.rs-47484/v1 ◽

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.

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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 ◽

10.3390/biomedicines9121894 ◽

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.

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Infiltrative tumour growth pattern correlates with poor outcome in oesophageal cancer

BMJ Open Gastroenterology ◽

10.1136/bmjgast-2020-000431 ◽

2020 ◽

Vol 7 (1) ◽

pp. e000431

Author(s):

Maelle Anciaux ◽

Pieter Demetter ◽

Roland De Wind ◽

Maria Gomez Galdon ◽

Sylvie Vande Velde ◽

...

Keyword(s):

Rna Sequencing ◽

Oesophageal Cancer ◽

Growth Pattern ◽

Prognostic Value ◽

Epithelial To Mesenchymal Transition ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Sequencing Data ◽

Mesenchymal Transition

ObjectiveOesophageal cancer (OEC) is an aggressive disease with a poor survival rate. Prognostic markers are thus urgently needed. Due to the demonstrated prognostic value of histopathological growth pattern (HGP) in other cancers, we performed a retrospective assessment of HGP in patients suffering from invasive OEC.DesignA first cohort composed of 89 treatment-naïve operated patients with OEC from The Cancer Genome Atlas (TCGA) public database was constituted, from which H&E images and RNA-sequencing data were retrieved. Next, a second cohort composed of 99 patients with OEC treated and operated in a Belgian hospital was established. H&E-stained sections and extracted tumorous RNA were obtained from the samples. HGP were assessed on H&E slides as infiltrative (IGP) or expansive (EGP). TCGA RNA-sequencing data were analysed through the gene set enrichment analysis and Cytoscape softwares. Real-time quantitative PCR (qPCR) experiments were performed to assess gene expression in the Belgian cohort.ResultsIGP patients displayed a grim prognosis compared with EGP patients, while IGP was found as associated with numerous lymphovascular emboli and perinervous infiltrations. Analyses of the TCGA expression data showed that angiogenesis, epithelial-to-mesenchymal transition (EMT) and inflammation were significantly upregulated in IGP compared with EGP samples. qPCR experiments of three genes appearing as highly upregulated in each pathway showed no difference in expression according to the HGP.ConclusionThe current study demonstrates the poor prognostic value carried by IGP in OC and suggests angiogenesis, EMT and inflammation as key carcinogenetic pathways upregulated in this pattern.

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Identification of an epithelial-mesenchymal transition-related lncRNA prognostic signature for patients with glioblastoma

Scientific Reports ◽

10.1038/s41598-021-03213-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

XinJie Yang ◽

Sha Niu ◽

JiaQiang Liu ◽

Jincheng Fang ◽

ZeYu Wu ◽

...

Keyword(s):

Immune Cell ◽

Cox Regression ◽

Epithelial Mesenchymal Transition ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Prognostic Signature ◽

Mesenchymal Transition

AbstractGlioblastoma (GBM) is a strikingly heterogeneous and lethal brain tumor with very poor prognosis. LncRNAs play critical roles in the tumorigenesis of GBM through regulation of various cancer-related genes and signaling pathways. Here, we focused on the essential role of EMT and identified 78 upregulated EMT-related genes in GBM through differential expression analysis and Gene set enrichment analysis (GSEA). A total of 301 EMT-related lncRNAs were confirmed in GBM through Spearman correlation analysis and a prognostic signature consisting of seven EMT-related lncRNAs (AC012615.1, H19, LINC00609, LINC00634, POM121L9P, SNHG11, and USP32P3) was established by univariate and multivariate Cox regression analyses. Significantly, Kaplan–Meier analysis and receiver-operating-characteristic (ROC) curve validated the accuracy and efficiency of the signature to be satisfactory. Quantitative real-time (qRT)-PCR assay demonstrated the expression alterations of the seven lncRNAs between normal glial and glioma cell lines. Functional enrichment analysis revealed multiple EMT and metastasis-related pathways were associated with the EMT-related lncRNA prognostic signature. In addition, we observed the degree of immune cell infiltration and immune responses were significantly increased in high-risk subgroup compared with low-risk subgroup. In conclusion, we established an effective and robust EMT-related lncRNA signature which was expected to predict the prognosis and immunotherapy response for GBM patients.

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Identification of An Epithelial-Mesenchymal Transition-Related lncRNA Prognostic Signature For Patients With Glioblastoma

10.21203/rs.3.rs-820534/v1 ◽

2021 ◽

Author(s):

XinJie Yang ◽

Sha Niu ◽

JiaQiang Liu ◽

ZeYu Wu ◽

Shizhang Ling ◽

...

Keyword(s):

High Risk ◽

Signaling Pathways ◽

Epithelial Mesenchymal Transition ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Prognostic Signature ◽

Mesenchymal Transition ◽

Underlying Mechanisms

Abstract Purpose: Glioblastoma (GBM) is a class of strikingly heterogeneous and lethal brain tumor with very poor prognosis. LncRNAs play critical roles in the tumorigenesis and progression of GBM through regulation of various cancer-related genes and signaling pathways. Here, we aimed to establish an epithelial-mesenchymal transition (EMT)-related lncRNA signature for GBM and explore its underlying mechanisms. Methods: Differential expression analysis and Gene set enrichment analysis (GSEA) were performed to explore key genes and signaling pathways associated with GBM. Spearman correlation analysis, Univariate and multivariate Cox regression analyses were used to construct a lncRNA prognostic signature for GBM patients. Kaplan-Meier analysis and receiver-operating-characteristic (ROC) analysis were applied to assess the performance of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichment analyses were performed to explore the underlying mechanisms of the signature. Single-sample GSEA (ssGSEA) was employed to explore the relationship of the signature and immune activities in GBM.Results: We focused on the essential role of EMT in GBM and identified 78 upregulated EMT-related genes in GBM. A total of 301 EMT-related lncRNAs were confirmed in GBM and a prognostic signature consisting of seven EMT-related lncRNAs (AC012615.1, H19, LINC00609, LINC00634, POM121L9P, SNHG11, and USP32P3) was established, which could divide GBM patients into low- and high-risk subgroups. The accuracy and efficiency of the signature were validated to be satisfactory. Functional enrichment analysis revealed multiple EMT and metastasis-related pathways were associated with the EMT-related lncRNA prognostic signature. In addition, we found the degree of immune cell infiltration and immune responses were significantly increased in high-risk subgroup compared with low-risk subgroup. Conclusion: we established an effective and robust EMT-related lncRNA signature which is expected to predict the prognosis and immunotherapy response for GBM patients.

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

Translational Neuroscience ◽

10.1515/tnsci-2021-0002 ◽

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.

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Identification of a Novel Epithelial-Mesenchymal Transition Gene Signature Regulated by KEAP1-NRF2 Pathway in Esophageal Carcinoma

10.21203/rs.3.rs-77379/v1 ◽

2020 ◽

Author(s):

Mohamed Elshaer ◽

Ahmed Hammad ◽

Xiu Jun Wang ◽

Xiuwen Tang

Keyword(s):

Cell Lines ◽

Epithelial Mesenchymal Transition ◽

Cancer Cell Line ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Mesenchymal Transition ◽

Gene Set ◽

Over Expression

Abstract BackgroundKEAP1-NRF2 pathway alterations were identified in many cancers including, esophageal cancer (ESCA). Identifying biomarkers that are associated with mutations in this pathway will aid in defining this cancer subset; and hence in supporting precision and personalized medicine. MethodsIn this study, 182 tumor samples from the Cancer Genome Atlas (TCGA)-ESCA RNA-Seq V2 level 3 data were segregated into two groups KEAP1-NRF2-mutated (22) and wild-type (160).The two groups were subjected to differential gene expression analysis, and we performed Gene Set Enrichment Analysis (GSEA) to determine all significantly affected biological pathways. Then, the enriched gene set was integrated with the differentially expressed genes (DEGs) to identify a gene signature regulated by the KEAP1-NRF2 pathway in ESCA. Furthermore, we validated the gene signature using mRNA expression data of ESCA cell lines provided by the Cancer Cell Line Encyclopedia (CCLE). The identified signature was tested in 3 independent ESCA datasets to assess its prognostic value.ResultsWe identified 11 epithelial-mesenchymal transition (EMT) genes regulated by the KEAP1-NRF2 pathway in ESCA patients. Five of the 11 genes showed significant over-expression in KEAP1-NRF2-mutated ESCA cell lines. In addition, the over-expression of these five genes was significantly associated with poor survival in 3 independent ESCA datasets, including the TCGA-ESCA dataset.ConclusionAltogether, we identified a novel EMT 5-gene signature regulated by the KEAP1-NRF2 axis and this signature is strongly associated with metastasis and drug resistance in ESCA. These 5-genes are potential biomarkers and therapeutic targets for ESCA patients in whom the KEAP1-NRF2 pathway is altered.

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Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

10.21203/rs.3.rs-19937/v2 ◽

2020 ◽

Author(s):

Zhenhua Yin ◽

Dejun Wu ◽

Jianping Shi ◽

Xiyi Wei ◽

Nuyun Jin ◽

...

Keyword(s):

Gene Expression ◽

Reference Value ◽

Enrichment Analysis ◽

Predictive Marker ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Fatty Aldehyde ◽

Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further.Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database.Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4.Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

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BACH1: A Potential Predictor of Survival in Early-Stage Lung Adenocarcinoma

Oxidative Medicine and Cellular Longevity ◽

10.1155/2022/3921095 ◽

2022 ◽

Vol 2022 ◽

pp. 1-16

Author(s):

Jin Zhou ◽

Zheming Liu ◽

Huibo Zhang ◽

Tianyu Lei ◽

Jiahui Liu ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Prognostic Model ◽

Cox Regression ◽

Early Stage ◽

External Validation ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Cox Regression Analysis

Purpose. Recent researches showed the vital role of BACH1 in promoting the metastasis of lung cancer. We aimed to explore the value of BACH1 in predicting the overall survival (OS) of early-stage (stages I-II) lung adenocarcinoma. Patients and Methods. Lung adenocarcinoma cases were screened from the Cancer Genome Atlas (TCGA) database. Functional enrichment analysis was performed to obtain the biological mechanisms of BACH1. Gene set enrichment analysis (GSEA) was performed to identify the difference of biological pathways between high- and low-BACH1 groups. Univariate and multivariate COX regression analysis had been used to screen prognostic factors, which were used to establish the BACH1 expression-based prognostic model in the TCGA dataset. The C-index and time-dependent AUC curve were used to evaluate predictive power of the model. External validation of prognostic value was performed in two independent datasets from Gene Expression Omnibus (GEO). Decision analysis curve was finally used to evaluate clinical usefulness of the BACH1-based model beyond pathologic stage alone. Results. BACH1 was an independent prognostic factor for lung adenocarcinoma. High-expression BACH1 cases had worse OS. BACH1-based prognostic model showed an ideal C-index and t -AUC and validated by two GEO datasets, independently. More importantly, the BACH1-based model indicated positive clinical applicability by DCA curves. Conclusion. Our research confirmed that BACH1 was an important predictor of prognosis in early-stage lung adenocarcinoma. The higher the expression of BACH1, the worse OS of the patients.

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

PeerJ ◽

10.7717/peerj.7091 ◽

2019 ◽

Vol 7 ◽

pp. e7091 ◽

Cited By ~ 5

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.

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