scholarly journals Modular signature of long non-coding RNA association networks as a prognostic biomarker in lung cancer

2021 ◽  
Vol 14 (S3) ◽  
Author(s):  
Albert Li ◽  
Wen-Hsuan Yu ◽  
Chia-Lang Hsu ◽  
Hsuan-Cheng Huang ◽  
Hsueh-Fen Juan
Keyword(s):  
Lung Cancer ◽  
Epithelial Mesenchymal Transition ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Operating Characteristics ◽  
Mesenchymal Transition ◽  
Cancer Hallmarks ◽  
Non Coding Rna

Abstract Background Increasing amount of long non-coding RNAs (lncRNAs) have been found involving in many biological processes and played salient roles in cancers. However, up until recently, functions of most lncRNAs in lung cancer have not been fully discovered, particularly in the co-regulated lncRNAs. Thus, this study aims to investigate roles of lncRNA modules and uncover a module-based biomarker in lung adenocarcinoma (LUAD). Results We used gene expression profiles from The Cancer Genome Atlas (TCGA) to construct the lncRNA association networks, from which the highly-associated lncRNAs are connected as modules. It was found that the expression of some modules is significantly associated with patient’s survival, including module N1 (HR = 0.62, 95% CI = 0.46–0.84, p = 0.00189); N2 (HR = 0.68, CI = 0.50–0.93, p = 0.00159); N4 (HR = 0.70, CI = 0.52–0.95, p = 0.0205) and P3 (HR = 0.68, CI = 0.50–0.92, p = 0.0123). The lncRNA signature consisting of these four prognosis-related modules, a 4-modular lncRNA signature, is associated with favourable prognosis in TCGA-LUAD (HR = 0.51, CI = 0.37–0.69, p value = 2.00e−05). Afterwards, to assess the performance of the generic modular signature as a prognostic biomarker, we computed the time-dependent area under the receiver operating characteristics (AUC) of this 4-modular lncRNA signature, which showed AUC equals 68.44% on 336th day. In terms of biological functions, these modules are correlated with several cancer hallmarks and pathways, including Myc targets, E2F targets, cell cycle, inflammation/immunity-related pathways, androgen/oestrogen response, KRAS signalling, DNA repair and epithelial-mesenchymal transition (EMT). Conclusion Taken together, we identified four novel LUAD prognosis-related lncRNA modules, and assessed the performance of the 4-modular lncRNA signature being a prognostic biomarker. Functionally speaking, these modules involve in oncogenic hallmarks as well as pathways. The results unveiled the co-regulated lncRNAs in LUAD and may provide a framework for further lncRNA studies in lung cancer.

scholarly journals AEBP1 Is One of the Epithelial-Mesenchymal Transition Regulatory Genes in Colon Adenocarcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Dandan Li ◽  
Zhi Liu ◽  
Xiaorong Ding ◽  
Zhensheng Qin
Keyword(s):  
Cancer Metastasis ◽  
Epithelial Mesenchymal Transition ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Colon Adenocarcinoma ◽  
The Cancer Genome Atlas ◽  
Mrna Levels ◽  
Mesenchymal Transition ◽  
Tumor Cell Migration ◽  
Promising Target

Epithelial-mesenchymal transition (EMT) is involved in various tumor processes, including tumorigenesis, tumor cell migration and metastasis, tumor stemness, and therapeutic resistance. Therefore, it is important to identify the genes most associated with EMT and develop them as therapeutic targets. In this work, we first analyzed EMT hallmark gene expression profiles among 10,535 pan-cancer samples from The Cancer Genome Atlas (TCGA) and divided them into EMT high and EMT low groups according to the metagene scores. Then, we identified 12 genes that were most associated with high EMT metagene score ( R > 0.9 ) in 329 colon adenocarcinoma (COAD) patients. Among them, only 4 genes (AEBP1, KCNE4, GFPT2, and FAM26E) had statistically significant differences in prognosis ( P < 0.05 ). Next, we selected AEBP1 as a candidate and showed that AEBP1 mRNA levels and EMT biomarkers strongly coexpressed in 329 COAD samples. In addition, AEBP1 was highly expressed and associated with poor clinical outcomes and prognosis in COAD patients. Finally, to explore whether AEBP1-mediated EMT was related to the tumor microenvironment (TME), we examined AEBP1 expression levels at the single-cell levels. Our results showed that AEBP1 levels were extremely high in tumor-associated fibroblasts, which may induce EMT. AEBP1 expression was also positively correlated with the expression of fibroblast biomarkers and also with EMT metascores, suggesting that AEBP1-mediated EMT may be associated with the stimulation of fibroblast activation. Therefore, AEBP1 may be a promising target for EMT inhibition, which reduces cancer metastasis and drug resistance in COAD patients.

Identification of five Hub Genes Associated with Development and Prognosis of Lung Adenocarcinoma by Co-Expression Analysis

2021 ◽  
Vol 16 ◽  
Author(s):  
Sangsang Chen ◽  
Xuqing Zhu ◽  
Jing Zheng ◽  
Tingting Xu ◽  
Yinmin Xu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Network Analyses ◽  
Study Gene Expression

Objective: Non-small cell lung cancer (NSCLC) is one of the most common types of lung cancer, while lung adenocarcinoma (LUAD) is the most common subtype of NSCLC. In this study, we aimed to identify potential markers that are associated with the prognosis and development of LUAD. Methods and results: In this study, gene expression profiles from 594 LUAD samples were downloaded from The Cancer Genome Atlas (TCGA) database, and 2,503 differentially expressed genes (DEGs) were obtained. Secondly, weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression network for these DEGs, and 16 modules were obtained. Among these, the genes related to the most significant module (turquoise) were found to be closely associated with the stage of LUAD. Then, functional annotation revealed that the genes in the turquoise module were mainly enriched in the pathways involved in the cell cycle and meiosis. Seven candidate hub genes were further screened by using WGCNA and protein-protein interaction network analyses. Expression data of the 7 candidate hub genes in different pathological stages in TCGA-LUAD were taken as the training set, while those in the GSE41271 dataset were used as the validation set. As a result, 5 hub genes (KIF11, KIF23, KIF4A, NUSPA1, RRM2) closely related to the pathological stage of LUAD were screened. Finally, survival and tissue expression analyses were performed on the five hub genes. The results suggested that the five hub genes were closely related to the occurrence and prognosis of LUAD. Conclusion: The study identified five hub genes that could be used as important predictors for the prognosis and development of LUAD.

Epigenetic Regulation of EMT in Non-Small Cell Lung Cancer

2017 ◽  
Vol 18 (1) ◽  
pp. 89-96 ◽  
Author(s):  
Karen O’Leary ◽  
Alice Shia ◽  
Peter Schmid
Keyword(s):  
Lung Cancer ◽  
Epithelial Mesenchymal Transition ◽  
Synthetic Lethality ◽  
Large Cell ◽  
Small Cell ◽  
Epigenetic Changes ◽  
Cell Lung Carcinoma ◽  
Mesenchymal Transition ◽  
Non Coding Rna ◽  
Large Cell Lung Carcinoma

Lung cancer remains the most diagnosed cancer in the world, with a high mortality rate and fewer therapeutic options. The most common lung cancer is non-small cell, consisting of adenocarcinoma, squamous cell carcinoma and large cell lung carcinoma. As per all solid tumours, the changes that occur for the initiation and metastasis of lung cancer can be described using the EMT (epithelial mesenchymal transition). Cells progressing through EMT lose their epithelial cell characteristics, expressing more mesenchymal markers and are phenotypically different. The transition can be controlled by changes in various pathways, such as TGF-β, PI3K, MAPK, Hedgehog and Wnt. The changes in those pathways can be controlled epigenetically, via DNA methylation, histone modifications or changes in small/non-coding RNA. We will describe the epigenetic changes that occur in these pathways and how we can consider novel methods to generate a synthetic lethality target in an epigenetically regulated pathway in EMT.

scholarly journals KRT6A Promotes EMT and Cancer Stem Cell Transformation in Lung Adenocarcinoma

2020 ◽  
Vol 19 ◽  
pp. 153303382092124
Author(s):  
Bin Yang ◽  
Wei Zhang ◽  
Mengmeng Zhang ◽  
Xuhong Wang ◽  
Shengzu Peng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Lung Adenocarcinoma ◽  
Biological Function ◽  
Epithelial Mesenchymal Transition ◽  
The Cancer Genome Atlas ◽  
Normal Lung ◽  
Mesenchymal Transition

Aim: Keratin 6A is a type II cytokeratin which is important in forming nail bed, filiform papillae, the epithelial lining of oral mucosa, and esophagus; recently, keratin 6A was found hyperexpressed in different types of cancer. But, the biological function of keratin 6A in lung adenocarcinoma still remains unclear. Therefore, in current study, we investigated the biological role of keratin 6A in lung adenocarcinoma. Methods: By utilizing The Cancer Genome Atlas database, we investigated the expression profile of keratin 6A and its relationship with other clinical parameters in lung adenocarcinoma. The biological function of keratin 6A in lung adenocarcinoma was also investigated by using A549 and PC-9 lung cancer cell lines in vitro. Results: Our data indicate that, compared with normal lung tissue samples, keratin 6A was hyperexpressed in lung adenocarcinoma. Moreover, keratin 6A hyperexpression was positively correlated with lymph node positive and aggressive tumor T stage. Keratin 6A knockdown inhibited the cell proliferation, migration, and colony formation ability but not cell death in lung adenocarcinoma cells. In addition, we found keratin 6A exerted its phenotype via promoting cancer stem cells (CXCR4high/CD133high) transformation and epithelial–mesenchymal transition. Conclusion: In conclusion, current study suggests that hyperexpressed keratin 6A in lung adenocarcinoma promotes lung cancer proliferation and metastasis via epithelial–mesenchymal transition and cancer stem cells transformation.

scholarly journals Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Qingyu Liang ◽  
Gefei Guan ◽  
Xue Li ◽  
Chunmi Wei ◽  
Jianqi Wu ◽  
...  
Keyword(s):  
Cox Regression ◽  
Expression Profiles ◽  
Treatment Strategies ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Risky Behaviors ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Transition ◽  
Genome Atlas

Abstract Background Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated. Methods Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed. Results According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma. Conclusions We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

scholarly journals COPB2: A Novel Prognostic Biomarker That Affects Progression of HCC

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jiayao Zhang ◽  
Xiaoyu Wang ◽  
Guangbing Li ◽  
Jingyi He ◽  
Ziwen Lu ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Epithelial Mesenchymal Transition ◽  
Prognostic Biomarker ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion ◽  
Clinicopathologic Characteristics ◽  
Mesenchymal Transition ◽  
Kaplan Meier

Purpose. This study is aimed at investigating the expression, underlying biological function, and clinical significance of coatomer protein complex subunit beta 2 (COPB2) in hepatocellular carcinoma (HCC). Methods. HCC-related data were extracted from The Cancer Genome Atlas (TCGA) database, International Cancer Genome Consortium (ICGC) database, and Gene Expression Omnibus (GEO) database. A logistic regression module was applied to analyze the relationship between the expression of COPB2 and clinicopathologic characteristics. The Cox proportional hazard regression model and Kaplan–Meier method were used for survival analysis. Gene set enrichment analysis (GSEA) was used to annotate the underlying biological functions. Loss-of-function experiments were conducted to determine the underlying mechanisms. Results. COPB2 was overexpressed in HCC, and high expression of COPB2 was significantly correlated with higher alpha fetoprotein (AFP) (odds ratio OR = 1.616 , >20 vs. ≤20, p < 0.05 ), stage ( OR = 1.744 , III vs. I, p < 0.05 ), and grade ( OR = 1.746 , G4+G3 vs. G2+G1, p < 0.05 ). Kaplan–Meier survival analysis showed that HCC patients with high COPB2 expression had a worse prognosis than those with low COPB2 expression ( p < 0.0001 for TCGA cohort, p < 0.05 for ICGC cohort). The univariate Cox (hazard ratio HR = 1.068 , p < 0.0001 ) and multivariate Cox ( HR = 2.011 , p < 0.05 ) regression analyses suggested that COPB2 was an independent risk factor. GSEA showed that mTOR and other tumor-related signaling pathways were differentially enriched in the high COPB2 expression phenotype. Silencing of COPB2 inhibited the proliferation, migration, and invasion abilities by suppressing epithelial-mesenchymal transition and mTOR signaling. Conclusion. COPB2 is a novel prognostic biomarker and a promising therapeutic target for HCC.

scholarly journals A COMPARATIVE ANALAYSIS OF INTER-SITE GENE EXPRESSION HETEROGENICITY OF NORMAL HUMAN BUCCAL MUCOSA WITH NORMAL GINGIVAL MUCOSA

2021 ◽  
Author(s):  
Rooban Thavarajah ◽  
Kannan Ranganathan
Keyword(s):  
Gene Expression ◽  
Buccal Mucosa ◽  
Epithelial Mesenchymal Transition ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Genotypic Difference ◽  
Mesenchymal Transition ◽  
Normal Human ◽  
The Difference

BACKGROUND: Description of heterogeneity of gene expression of various human intraoral sites are not adequate. The aim of this study was to explore the difference of gene expression profiles of whole tissue obtained from apparently normal human gingiva and buccal mucosa (HGM, HBM). MATERIALS AND METHODS: Gene sets fulfilling inclusion and exclusion criteria of HGM and HBM in gene Expression Omnibus(GEO) database were identified, segregated, filtered and analysed using the ExAtlas online web tool using pre-determined cut-off. The differentially expressed genes were studied for epithelial keratinization related, housekeeping(HKG), extracellular matrix related(ECMRG) and epithelial-mesenchymal transition related genes(EMTRGs). RESULTS: In all 40 HBM and 64 HGM formed the study group. In all there were 18012 significantly expressed genes. Of this, 1814 were over-expressed and 1862 under-expressed HBM genes as compared to HGM. One in five of all studied genes significantly differed between HBM and HGM. For the keratinization genes, 1 in 6 differed. One of every 5 HKG-proteomics genes differed between HBM and HGM, while this ratio was 1-in 4 for all ECMRGs and EMTRGs. DISCUSSION: This difference in the gene expression between the HBM and HGM could possibly influence a multitude of biological pathways. This result could explain partly the difference in clinicopathological features of oral lesions occurring in HBM and HGM. The innate genotypic difference between the two intra-oral niches could serve as confounding factor in genotypic studies. Hence studies that compare the HBM and HGM should factor-in these findings while evaluating their results.

scholarly journals Gene expression profiling of fast- and slow-growing non-functioning gonadotroph pituitary adenomas

2018 ◽  
Vol 178 (3) ◽  
pp. 295-307 ◽  
Author(s):  
Camilla Maria Falch ◽  
Arvind Y M Sundaram ◽  
Kristin Astrid Øystese ◽  
Kjersti Ringvoll Normann ◽  
Tove Lekva ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Growth ◽  
Epithelial Mesenchymal Transition ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Growth Potential ◽  
Mesenchymal Transition ◽  
Volume Doubling Time ◽  
Slow Growing

ObjectiveReliable biomarkers associated with aggressiveness of non-functioning gonadotroph adenomas (GAs) are lacking. As the growth of tumor remnants is highly variable, molecular markers for growth potential prediction are necessary. We hypothesized that fast- and slow-growing GAs present different gene expression profiles and reliable biomarkers for tumor growth potential could be identified, focusing on the specific role of epithelial-mesenchymal transition (EMT).Design and methodsEight GAs selected for RNA sequencing were equally divided into fast- and slow-growing group by the tumor volume doubling time (TVDT) median (27.75 months). Data were analyzed by tophat2, cufflinks and cummeRbund pipeline. 40 genes were selected for RT-qPCR validation in 20 GAs based on significance, fold-change and pathway analyses. The effect of silencingMTDH(metadherin) andEMCN(endomucin) onin vitromigration of human adenoma cells was evaluated.Results350 genes were significantly differentially expressed (282 genes upregulated and 68 downregulated in the fast group,P-adjusted <0.05). Among 40 selected genes, 11 showed associations with TVDT (−0.669<R<−0.46,P < 0.05). These werePCDH18, UNC5D, EMCN, MYO1B, GPM6Aand six EMT-related genes (SPAG9, SKIL, MTDH, HOOK1, CNOT6LandPRKACB).MTDH, but notEMCN, demonstrated involvement in cell migration and association with EMT markers.ConclusionsFast- and slow-growing GAs present different gene expression profiles, and genes related to EMT have higher expression in fast-growing tumors. In addition toMTDH, identified as an important contributor to aggressiveness, the other genes might represent markers for tumor growth potential and possible targets for drug therapy.

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