scholarly journals Investigating Strength that Comprehensive mRNA Expression Level of Prognostic Genes Influences on Patient Survival for Every Cancer Type

2019 ◽  
Author(s):  
Minhyeong Lee
Keyword(s):  
Mrna Expression ◽  
Patient Survival ◽  
Scientific Evidence ◽  
Prognostic Indicator ◽  
Cancer Type ◽  
Rna Seq ◽  
Kaplan Meier ◽  
Specific Cancer ◽  
Protective Genes ◽  
Tcga Dataset

This study aimed to rank cancers by the strength of relationship between comprehensive mRNA expression of the most harmful or protective genes and patient survival. Using TCGA dataset including RNA-SEQ and clinical data, we investigated not only gene specific prognostic availability, but also comprehensive prognostic availability of prognostic genes filtered by cox coefficient, and ranked cancers by specially designed prognostic indicator. Through Kaplan-Meier plots, we checked that cancers vary in the strength of influence of prognostic genes, and they follow as the rank. Developing treatment with method to reduce or increase expression of biomarkers for specific cancer which ranked bottom, it would be not efficient in high probability. The results of this study can be a scientific evidence for that.

Investigating the Influence of the Comprehensive mRNA Expression Levels of Prognostic Genes on Patient Survival in Every Type of Cancer

2020 ◽  
Author(s):  
Minhyeong Lee
Keyword(s):  
Mrna Expression ◽  
Patient Survival ◽  
Scientific Evidence ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Expression Levels ◽  
Kaplan Meier ◽  
Protective Genes ◽  
Cancer Genome Atlas ◽  
Mrna Expression Levels

This study aimed to rank cancers based on the strength of the relationship between the comprehensive mRNA expression levels of the most harmful or protective genes and patient survival. Using The Cancer Genome Atlas dataset that includes the RNA sequencing and c linical data, we investigated not only gene specific prognostic availability, but also comprehensive prognostic availability of prognostic genes filtered by the Cox coefficient values, and ranked cancers using a specially designed prognostic indicator. Usi ng Kaplan Meier plots, we found that cancers vary in the strength of the influence of their prognostic genes, and can be ranked based on this finding. There is a high probability that the treatment developed by using methods that reduce or increase the exp ression levels of biomarkers, for cancers that ranked at the bottom will not be efficient. The results of this study could be used as scientific evidence for the same.

scholarly journals OncoLnc: Linking TCGA survival data to mRNAs, miRNAs, and lncRNAs

2016 ◽  
Author(s):  
Jordan Anaya
Keyword(s):  
Survival Data ◽  
The Cancer Genome Atlas ◽  
Specific Gene ◽  
Expression Data ◽  
Rna Seq ◽  
Kaplan Meier ◽  
Specific Cancer ◽  
Cancer Genome Atlas ◽  
Cancer Studies ◽  
Publication Quality

OncoLnc is a tool for interactively exploring survival correlations, and for downloading clinical data coupled to expression data for mRNAs, miRNAs, or lncRNAs. OncoLnc contains survival data for 8,647 patients from 21 cancer studies performed by The Cancer Genome Atlas (TCGA), along with RNA-SEQ expression for mRNAs and miRNAs from TCGA, and lncRNA expression from MiTranscriptome beta. Storing this data gives users the ability to separate patients by gene expression, and then create publication-quality Kaplan-Meier plots or download the data for further analyses. OncoLnc also stores precomputed survival analyses, allowing users to quickly explore survival correlations for up to 21 cancers in a single click. This resource allows researchers studying a specific gene to quickly investigate if it may have a role in cancer, and the supporting data allows researchers studying a specific cancer to identify the mRNAs, miRNAs, and lncRNAs most correlated with survival, and researchers looking for a novel lncRNA involved with cancer lists of potential candidates. OncoLnc is available at http://www.oncolnc.org

scholarly journals OncoLnc: Linking TCGA survival data to mRNAs, miRNAs, and lncRNAs

2016 ◽  
Author(s):  
Jordan Anaya
Keyword(s):  
Survival Data ◽  
The Cancer Genome Atlas ◽  
Specific Gene ◽  
Expression Data ◽  
Rna Seq ◽  
Kaplan Meier ◽  
Specific Cancer ◽  
Cancer Genome Atlas ◽  
Cancer Studies ◽  
Publication Quality

OncoLnc is a tool for interactively exploring survival correlations, and for downloading clinical data coupled to expression data for mRNAs, miRNAs, or lncRNAs. OncoLnc contains survival data for 8,647 patients from 21 cancer studies performed by The Cancer Genome Atlas (TCGA), along with RNA-SEQ expression for mRNAs and miRNAs from TCGA, and lncRNA expression from MiTranscriptome beta. Storing this data gives users the ability to separate patients by gene expression, and then create publication-quality Kaplan-Meier plots or download the data for further analyses. OncoLnc also stores precomputed survival analyses, allowing users to quickly explore survival correlations for up to 21 cancers in a single click. This resource allows researchers studying a specific gene to quickly investigate if it may have a role in cancer, and the supporting data allows researchers studying a specific cancer to identify the mRNAs, miRNAs, and lncRNAs most correlated with survival, and researchers looking for a novel lncRNA involved with cancer lists of potential candidates. OncoLnc is available at http://www.oncolnc.org

scholarly journals High KRT8 Expression Independently Predicts Poor Prognosis for Lung Adenocarcinoma Patients

Genes ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 36 ◽  
Author(s):  
Longxiang Xie ◽  
Yifang Dang ◽  
Jinshuai Guo ◽  
Xiaoxiao Sun ◽  
Tiantian Xie ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Mrna Expression ◽  
Prognostic Significance ◽  
Lung Squamous Cell Carcinoma ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Normal Lung ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Dna Copy Number Alterations

Keratin 8 (KRT8), a type II basic intermediate filament (IF) protein, is essential for the development and metastasis of various cancers. In this study, by analyzing RNA-seq data from the Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), we have determined the expression profile of KRT8, and assessed its prognostic significance and the possible mechanism underlying the dysregulation. Our results showed that KRT8 mRNA expression was significantly up-regulated in both LUAD and LUSC tissues compared with normal lung tissues. The high KRT8 expression group for LUAD patients significantly reduced overall survival (OS) and recurrence-free survival (RFS). Univariate and multivariate analysis revealed that KRT8 expression was an independent prognostic indicator for poor OS and RFS in LUAD patients. However, KRT8 expression had no prognostic value in terms of OS and RFS for LUSC. By exploring DNA copy number alterations (CNAs) of the KRT8 gene in LUAD, we found that DNA low copy gain (+1 and +2) was associated with elevated KRT8 mRNA expression. From the above findings, we have deduced that KRT8 is aberrantly expressed in LUAD tissues and that its expression might independently predict poor OS and RFS for LUAD patients, but not for LUSC patients.

scholarly journals Chromatin Accessibility Regulates Gene Expression and Correlates With Tumor-Infiltrating Immune Cells in Gastric Adenocarcinoma

2021 ◽  
Vol 10 ◽  
Author(s):  
Chenshen Huang ◽  
Runzhi Huang ◽  
Hong Chen ◽  
Zhizhan Ni ◽  
Qi Huang ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Gastric Adenocarcinoma ◽  
Survival Data ◽  
Pearson Correlation ◽  
Mrna Level ◽  
Chromatin Accessibility ◽  
Clinical Samples ◽  
Rna Seq ◽  
Promoter Regions ◽  
Kaplan Meier

BackgroundWe explored key molecules affecting the prognosis of gastric adenocarcinoma (STAD) using co-analysis of chromatin accessibility (ATAC-seq), mRNA expression (RNA-seq), and overall survival.MethodsWe used the assay for transposase-accessible chromatin using sequencing (ATAC-seq) profiles to identify genes with chromatin accessibilities in their promoter regions. The RNA-seq profiles were processed for differentially expressed genes (DEGs) at mRNA level. The DEGs with chromatin accessibilities in promoter regions were further filtered using the Pearson correlation with TP53 expression. After co-analysis, genes were identified for the prognostic value using Kaplan–Meier method, followed by Pearson correlation analysis with significant pathways. For verification, we acquired clinical samples for qPCR and immunohistochemistry (IHC). Multidimensional database validations were performed to prevent the bias introduced by the use of a single database.ResultsWe identified 11,557 DEGs and 57 genes with chromatin accessibilities. The co-analysis of ATAC-seq, RNA-seq, and clinical survival data revealed that interleukin-18 binding protein (IL18BP), with significant chromatin accessibility in its promoter region and differential mRNA expression, might be directly regulated by TP53 and influence STAD prognosis. Further, gene set variation analysis indicated that IL18BP may impact the survival of STAD patients in an immune-related manner. According to the CIBERSORT algorithm and Pearson correlation, the integration of IL18BP and CD4+ T memory cells may play an important role in the prognosis of STAD patients.ConclusionIL18BP, regulated by TP53, may serve as a key molecule affecting STAD prognosis. And the mechanism is proposed to be the interaction between IL18BP and CD4+ T cells.

scholarly journals OncoLnc: linking TCGA survival data to mRNAs, miRNAs, and lncRNAs

2016 ◽  
Vol 2 ◽  
pp. e67 ◽  
Author(s):  
Jordan Anaya
Keyword(s):  
Survival Data ◽  
The Cancer Genome Atlas ◽  
Specific Gene ◽  
Expression Data ◽  
Rna Seq ◽  
Kaplan Meier ◽  
Specific Cancer ◽  
Cancer Genome Atlas ◽  
Cancer Studies ◽  
Publication Quality

OncoLnc is a tool for interactively exploring survival correlations, and for downloading clinical data coupled to expression data for mRNAs, miRNAs, or long noncoding RNAs (lncRNAs). OncoLnc contains survival data for 8,647 patients from 21 cancer studies performed by The Cancer Genome Atlas (TCGA), along with RNA-SEQ expression for mRNAs and miRNAs from TCGA, and lncRNA expression from MiTranscriptome beta. Storing this data gives users the ability to separate patients by gene expression, and then create publication-quality Kaplan-Meier plots or download the data for further analyses. OncoLnc also stores precomputed survival analyses, allowing users to quickly explore survival correlations for up to 21 cancers in a single click. This resource allows researchers studying a specific gene to quickly investigate if it may have a role in cancer, and the supporting data allows researchers studying a specific cancer to identify the mRNAs, miRNAs, and lncRNAs most correlated with survival, and researchers looking for a novel lncRNA involved with cancer lists of potential candidates. OncoLnc is available athttp://www.oncolnc.org.

scholarly journals TRIM27 interacts with Iκbα to promote the growth of human renal cancer cells through regulating the NF-κB pathway

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chengwu Xiao ◽  
Wei Zhang ◽  
Meimian Hua ◽  
Huan Chen ◽  
Bin Yang ◽  
...  
Keyword(s):  
Cell Lines ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Mrna Levels ◽  
Loss Of Function ◽  
Protein Levels ◽  
Kaplan Meier ◽  
Cancer Genome Atlas

Abstract Background The tripartite motif (TRIM) family proteins exhibit oncogenic roles in various cancers. The roles of TRIM27, a member of the TRIM super family, in renal cell carcinoma (RCC) remained unexplored. In the current study, we aimed to investigate the clinical impact and roles of TRIM27 in the development of RCC. Methods The mRNA levels of TRIM27 and Kaplan–Meier survival of RCC were analyzed from The Cancer Genome Atlas database. Real-time PCR and Western blotting were used to measure the mRNA and protein levels of TRIM27 both in vivo and in vitro. siRNA and TRIM27 were exogenously overexpressed in RCC cell lines to manipulate TRIM27 expression. Results We discovered that TRIM27 was elevated in RCC patients, and the expression of TRIM27 was closely correlated with poor prognosis. The loss of function and gain of function results illustrated that TRIM27 promotes cell proliferation and inhibits apoptosis in RCC cell lines. Furthermore, TRIM27 expression was positively associated with NF-κB expression in patients with RCC. Blocking the activity of NF-κB attenuated the TRIM27-mediated enhancement of proliferation and inhibition of apoptosis. TRIM27 directly interacted with Iκbα, an inhibitor of NF-κB, to promote its ubiquitination, and the inhibitory effects of TRIM27 on Iκbα led to NF-κB activation. Conclusions Our results suggest that TRIM27 exhibits an oncogenic role in RCC by regulating NF-κB signaling. TRIM27 serves as a specific prognostic indicator for RCC, and strategies targeting the suppression of TRIM27 function may shed light on future therapeutic approaches.

scholarly journals Reprogramming mRNA Expression in Response to Defect in RNA Polymerase III Assembly in the Yeast Saccharomyces cerevisiae

2021 ◽  
Vol 22 (14) ◽  
pp. 7298
Author(s):  
Izabela Rudzińska ◽  
Małgorzata Cieśla ◽  
Tomasz W. Turowski ◽  
Alicja Armatowska ◽  
Ewa Leśniewska ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Ribosome Biogenesis ◽  
Rna Polymerase Iii ◽  
Mrna Levels ◽  
Rna Seq ◽  
Yeast Saccharomyces Cerevisiae ◽  
Protein Coding ◽  
General Transcription Factor ◽  
Pol I ◽  
Pol Iii

The coordinated transcription of the genome is the fundamental mechanism in molecular biology. Transcription in eukaryotes is carried out by three main RNA polymerases: Pol I, II, and III. One basic problem is how a decrease in tRNA levels, by downregulating Pol III efficiency, influences the expression pattern of protein-coding genes. The purpose of this study was to determine the mRNA levels in the yeast mutant rpc128-1007 and its overdose suppressors, RBS1 and PRT1. The rpc128-1007 mutant prevents assembly of the Pol III complex and functionally mimics similar mutations in human Pol III, which cause hypomyelinating leukodystrophies. We applied RNAseq followed by the hierarchical clustering of our complete RNA-seq transcriptome and functional analysis of genes from the clusters. mRNA upregulation in rpc128-1007 cells was generally stronger than downregulation. The observed induction of mRNA expression was mostly indirect and resulted from the derepression of general transcription factor Gcn4, differently modulated by suppressor genes. rpc128-1007 mutation, regardless of the presence of suppressors, also resulted in a weak increase in the expression of ribosome biogenesis genes. mRNA genes that were downregulated by the reduction of Pol III assembly comprise the proteasome complex. In summary, our results provide the regulatory links affected by Pol III assembly that contribute differently to cellular fitness.

scholarly journals Overexpressed P75CUX1 promotes EMT in glioma infiltration by activating β-catenin

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Anqi Xu ◽  
Xizhao Wang ◽  
Jie Luo ◽  
Mingfeng Zhou ◽  
Renhui Yi ◽  
...  
Keyword(s):  
Epithelial Mesenchymal Transition ◽  
Tumor Grade ◽  
Prognostic Indicator ◽  
Migration And Invasion ◽  
Poor Overall Survival ◽  
Mesenchymal Transition ◽  
Kaplan Meier ◽  
Homeobox Protein

AbstractThe homeobox protein cut-like 1 (CUX1) comprises three isoforms and has been shown to be involved in the development of various types of malignancies. However, the expression and role of the CUX1 isoforms in glioma remain unclear. Herein, we first identified that P75CUX1 isoform exhibited consistent expression among three isoforms in glioma with specifically designed antibodies to identify all CUX1 isoforms. Moreover, a significantly higher expression of P75CUX1 was found in glioma compared with non-tumor brain (NB) tissues, analyzed with western blot and immunohistochemistry, and the expression level of P75CUX1 was positively associated with tumor grade. In addition, Kaplan–Meier survival analysis indicated that P75CUX1 could serve as an independent prognostic indicator to identify glioma patients with poor overall survival. Furthermore, CUX1 knockdown suppressed migration and invasion of glioma cells both in vitro and in vivo. Mechanistically, this study found that P75CUX1 regulated epithelial–mesenchymal transition (EMT) process mediated via β-catenin, and CUX1/β-catenin/EMT is a novel signaling cascade mediating the infiltration of glioma. Besides, CUX1 was verified to promote the progression of glioma via multiple other signaling pathways, such as Hippo and PI3K/AKT. In conclusion, we suggested that P75CUX1 could serve as a potential prognostic indicator as well as a novel treatment target in malignant glioma.

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

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