scholarly journals Conditional transcriptional relationships may serve as cancer prognostic markers

2021 ◽  
Vol 14 (S2) ◽  
Author(s):  
Hui Yu ◽  
Limei Wang ◽  
Danqian Chen ◽  
Jin Li ◽  
Yan Guo
Keyword(s):  
Survival Analysis ◽  
Prognostic Markers ◽  
Individual Level ◽  
Expression Correlation ◽  
Prognostic Gene ◽  
Differential Coexpression ◽  
Global Correlation ◽  
Global Trend ◽  
Cancer Types ◽  
Multiple Samples

Abstract Background While most differential coexpression (DC) methods are bound to quantify a single correlation value for a gene pair across multiple samples, a newly devised approach under the name Correlation by Individual Level Product (CILP) revolutionarily projects the summary correlation value to individual product correlation values for separate samples. CILP greatly widened DC analysis opportunities by allowing integration of non-compromised statistical methods. Methods Here, we performed a study to verify our hypothesis that conditional relationships, i.e., gene pairs of remarkable differential coexpression, may be sought as quantitative prognostic markers for human cancers. Alongside the seeking of prognostic gene links in a pan-cancer setting, we also examined whether a trend of global expression correlation loss appeared in a wide panel of cancer types and revisited the controversial subject of mutual relationship between the DE approach and the DC approach. Results By integrating CILP with classical univariate survival analysis, we identified up to 244 conditional gene links as potential prognostic markers in five cancer types. In particular, five prognostic gene links for kidney renal papillary cell carcinoma tended to condense around cancer gene ESPL1, and the transcriptional synchrony between ESPL1 and PTTG1 tended to be elevated in patients of adverse prognosis. In addition, we extended the observation of global trend of correlation loss in more than ten cancer types and empirically proved DC analysis results were independent of gene differential expression in five cancer types. Conclusions Combining the power of CILP and the classical survival analysis, we successfully fetched conditional transcriptional relationships that conferred prognosis power for five cancer types. Despite a general trend of global correlation loss in tumor transcriptomes, most of these prognosis conditional links demonstrated stronger expression correlation in tumors, and their stronger coexpression was associated with poor survival.

scholarly journals Non-Coding RNAs as Prognostic Markers for Endometrial Cancer

2021 ◽  
Vol 22 (6) ◽  
pp. 3151 ◽  
Author(s):  
Roberto Piergentili ◽  
Simona Zaami ◽  
Anna Franca Cavaliere ◽  
Fabrizio Signore ◽  
Giovanni Scambia ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Prognostic Markers ◽  
Classification Systems ◽  
Prognostic Role ◽  
Protein Coding ◽  
Pathological Characteristics ◽  
Epigenetic Events ◽  
Cancer Types ◽  
Non Coding Rnas

Endometrial cancer (EC) has been classified over the years, for prognostic and therapeutic purposes. In recent years, classification systems have been emerging not only based on EC clinical and pathological characteristics but also on its genetic and epigenetic features. Noncoding RNAs (ncRNAs) are emerging as promising markers in several cancer types, including EC, for which their prognostic value is currently under investigation and will likely integrate the present prognostic tools based on protein coding genes. This review aims to underline the importance of the genetic and epigenetic events in the EC tumorigenesis, by expounding upon the prognostic role of ncRNAs.

Survival analysis of presumptive prognostic markers among oligodendrogliomas

Cancer ◽  
2005 ◽  
Vol 104 (8) ◽  
pp. 1693-1699 ◽  
Author(s):  
Roger E. McLendon ◽  
James E. Herndon ◽  
Bryan West ◽  
David Reardon ◽  
Rodney Wiltshire ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Prognostic Markers

scholarly journals Who Is Purged? Determinants of Elite Purges in North Korea

2021 ◽  
Vol 54 (3) ◽  
pp. 73-96
Author(s):  
Taekbin Kim
Keyword(s):  
Survival Analysis ◽  
North Korea ◽  
Career Path ◽  
Educational Background ◽  
Low Risk ◽  
Individual Factors ◽  
Individual Level ◽  
Studying Abroad ◽  
Military Background ◽  
The Individual

The existing literature on elite purges in dictatorships claims that the risk of coups to replace dictators is the main cause of the dictator’s choice of purge strategy. Why then do elite purges occur even in well-established dictatorships with a consistently low risk of coups? This article argues that elite purges in consolidated dictatorships have a different purpose and logic. Dictators, who have consolidated their position, seek to maximize the efficiency of rule by making the elite obedient through purges. For this purpose, dictators carefully select the purge target by considering various factors. To test this theory, the article examines the pattern of elite purges in North Korea based on an original individual-level dataset, which contains the personal background of 367 North Korean elites and their purge records between 1948 and 2019. The result of survival analysis shows that the purge risk of the elite is not significantly associated with their military background but is associated with the characteristics of the institution to which the individual elite member belongs. Other individual factors, including the elite’s educational background, the experience of studying abroad, and the career path, are also significantly related to the probability of being purged. The finding suggests that coup-proofing is not the only purpose of elite purges but that ensuring the leader’s political superiority is another purpose of elite purges in consolidated dictatorships.

scholarly journals LINC02257, an Enhancer RNA of Prognostic Value in Colon Adenocarcinoma, Correlates With Multi-Omics Immunotherapy-Related Analysis in 33 Cancers

2021 ◽  
Vol 8 ◽  
Author(s):  
Junbo Xiao ◽  
Yajun Liu ◽  
Jun Yi ◽  
Xiaowei Liu
Keyword(s):  
Survival Analysis ◽  
Signaling Pathway ◽  
Large Scale ◽  
Immune Cell ◽  
Colon Adenocarcinoma ◽  
Akt Signaling ◽  
The Cancer Genome Atlas ◽  
Akt Signaling Pathway ◽  
Free Interval ◽  
Cancer Types

Accumulated evidence supports that long non-coding RNAs (lncRNAs) are involved significantly in the development of human cancers. Enhancer RNAs (eRNAs), a subtype of lncRNAs, have recently attracted much attention about their roles in carcinogenesis. Colon adenocarcinoma is one of the most commonly diagnosed tumors with unfavorable prognosis. It highlights the great significance of screening and identifying novel biomarkers. More importantly, it remains to be elucidated with respect to the function of eRNAs in colon adenocarcinoma, as is in pan-cancers. The expression of LINC02257 was determined based on the data obtained from The Cancer Genome Atlas (TCGA). Further evaluation was performed on the basis of the following analyses: clinicopathology and survival analysis, gene ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, as well as multi-omics immunotherapy-related analysis and co-expression analysis. The statistical analysis was conducted in R software, and immune cell infiltration of LINC02257 expression in cancers was investigated by using the CIBERSORT algorithm. By large-scale data mining, our study highlighted that a total of 39 eRNA genes were associated with colon adenocarcinoma prognosis, among which 25 eRNAs showed significant associations with their predicted target genes. LINC02257 was identified as the most significant survival-associated eRNA, with DUSP10 as its target gene. Besides, the high expression of LINC02257 in colon adenocarcinoma was more vulnerable to unfavorable prognosis and correlated with various clinical characteristics. GO and KEGG analyses revealed that LINC02257 was closely correlated with extracellular matrix organization via the PI3K-Akt signaling pathway. Besides, LINC02257 expression correlated with a multi-omics analysis of 33 cancer types, such as survival analysis [overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI)] and immunotherapy-related analysis [tumor microenvironment (TME), tumor mutational burden (TMB), and microsatellite instability (MSI)]. Finally, we investigated the co-expression genes of LINC02257 and its potential signaling pathways across different cancer types. LINC02257 is screened and can function as an independent prognostic biomarker through the PI3K-Akt signaling pathway for colon adenocarcinoma. Simultaneously, LINC02257 may be a multifaceted and significant immunotherapy-related eRNA in different cancers.

scholarly journals An analysis about heterogeneity among cancers based on the DNA methylation patterns

BMC Cancer ◽  
2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yang Liu ◽  
Yue Gu ◽  
Mu Su ◽  
Hui Liu ◽  
Shumei Zhang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Survival Analysis ◽  
Prognostic Markers ◽  
Differential Methylation ◽  
Specific Gene ◽  
Cancer Type ◽  
Methylation Analysis ◽  
Gene Markers ◽  
Significant Difference ◽  
Differential Methylation Analysis

Abstract Background It is generally believed that DNA methylation, as one of the most important epigenetic modifications, participates in the regulation of gene expression and plays an important role in the development of cancer, and there exits epigenetic heterogeneity among cancers. Therefore, this study tried to screen for reliable prognostic markers for different cancers, providing further explanation for the heterogeneity of cancers, and more targets for clinical transformation studies of cancer from epigenetic perspective. Methods This article discusses the epigenetic heterogeneity of cancer in detail. Firstly, DNA methylation data of seven cancer types were obtained from Illumina Infinium HumanMethylation 450 K platform of TCGA database. Then, differential methylation analysis was performed in the promotor region. Secondly, pivotal gene markers were obtained by constructing the DNA methylation correlation network and the gene interaction network in the KEGG pathway, and 317 marker genes obtained from two networks were integrated as candidate markers for the prognosis model. Finally, we used the univariate and multivariate COX regression models to select specific independent prognostic markers for each cancer, and studied the risk factor of these genes by doing survival analysis. Results First, the cancer type-specific gene markers were obtained by differential methylation analysis and they were found to be involved in different biological functions by enrichment analysis. Moreover, specific and common diagnostic markers for each type of cancer was sorted out and Kaplan-Meier survival analysis showed that there was significant difference in survival between the two risk groups. Conclusions This study screened out reliable prognostic markers for different cancers, providing a further explanation for the heterogeneity of cancer at the DNA methylation level and more targets for clinical conversion studies of cancer.

scholarly journals Identification and Validation of Potential Pathogenic Genes and Prognostic Markers in ESCC by Integrated Bioinformatics Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Lu Tang ◽  
Yuqiao Chen ◽  
Xiong Peng ◽  
Yuan Zhou ◽  
Hong Jiang ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Prognostic Markers ◽  
Epithelial Mesenchymal Transition ◽  
Quantitative Polymerase Chain Reaction ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Migration Ability ◽  
Mesenchymal Transition

Esophageal squamous cell carcinoma (ESCC) is one of the most fatal malignancies of the digestive tract, but its underlying molecular mechanisms are not known. We aim to identify the genes involved in ESCC carcinogenesis and discover potential prognostic markers using integrated bioinformatics analysis. Three pairs of ESCC tissues and paired normal tissues were sequenced by high-throughput RNA sequencing (RNA-seq). Integrated bioinformatics analysis was used to identify differentially expressed coding genes (DECGs) and differentially expressed long non-coding RNA (lncRNA) genes (DELGs). A protein–protein interaction (PPI) network of DECGs was established using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website and visualized with Cytoscape. Survival analysis was conducted by log-rank tests to identify “hub” genes with potential prognostic value, and real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was conducted to assess expression of these genes in ESCC tissues. TranswellTM assays were employed to examine the migration ability of cells after knockdown of LINC01614 expression, followed by investigation of epithelial–mesenchymal transition (EMT) by western blotting (WB). A total of 106 upregulated genes and 42 downregulated genes were screened out from the ESCC data sets. Survival analysis showed two hub protein-coding genes with higher expression in module 1 of the PPI network (SPP1 and BGN) and another three upregulated lncRNAs (LINC01614, LINC01415, NKILA) that were associated with a poor prognosis. High expression of SPP1, BGN, LINC01614, and LINC01415 in tumor samples was validated further by RT-qPCR. In vitro experiments show that knockdown of LINC01614 expression could significantly inhibit the migration of ESCC cells by regulating EMT, which was confirmed by WB. These results indicate that BGN, SPP1, LINC01614, and LINC01415 might be critical genes in ESCC and potential prognostic biomarkers.

scholarly journals Prediction of survival in amyotrophic lateral sclerosis: a nationwide, Danish cohort study

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Anne-Lene Kjældgaard ◽  
Katrine Pilely ◽  
Karsten Skovgaard Olsen ◽  
Anders Hedegaard Jessen ◽  
Anne Øberg Lauritsen ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Survival Analysis ◽  
Prognostic Marker ◽  
Palliative Treatment ◽  
Rating Scale ◽  
Prognostic Markers ◽  
Progression Rate ◽  
Duration Of Symptoms ◽  
Sporadic Als ◽  
Lateral Sclerosis

Abstract Introduction Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease with great heterogeneity. Biological prognostic markers are needed for the patients to plan future supportive treatment, palliative treatment, and end-of-life decisions. In addition, prognostic markers are greatly needed for the randomization in clinical trials. Objective This study aimed to test the ALS Functional Rating Scale-Revised (ALSFRS-R) progression rate (ΔFS) as a prognostic marker of survival in a Danish ALS cohort. Methods The ALSFRS-R score at test date in association with duration of symptoms, from the onset of symptoms until test date, (defined as ΔFS’) was calculated for 90 Danish patients diagnosed with either probable or definite sporadic ALS. Median survival time was then estimated from the onset of symptoms until primary endpoint (either death or tracheostomy). ΔFS’ was subjected to survival analysis using Cox proportional hazards modelling, log-rank test, and Kaplan-Meier survival analysis. Results and conclusions Both ΔFS’ and age was found to be strong predictors of survival of the Danish ALS cohort. Both variables are easily obtained at the time of diagnosis and could be used by clinicians and ALS patients to plan future supportive and palliative treatment. Furthermore, ΔFS’, is a simple, prognostic marker that predicts survival in the early phase of disease as well as at later stages of the disease.

scholarly journals Clinical and Prognostic Significance of TZAP Expression in Cervical Cancer

Medicina ◽  
2020 ◽  
Vol 56 (5) ◽  
pp. 207
Author(s):  
Won-Jin Park ◽  
Jae-Hee Park ◽  
Ho-Yong Shin ◽  
Jae-Ho Lee
Keyword(s):  
Cervical Cancer ◽  
Survival Analysis ◽  
Prognostic Value ◽  
Prognostic Significance ◽  
Telomeric Repeat ◽  
The Cancer Genome Atlas ◽  
Genetic Changes ◽  
Cancer Pathogenesis ◽  
Cancer Genome Atlas ◽  
Cancer Types

Background and Objectives: Telomeric zinc finger-associated protein (TZAP) is a telomere-associated factor that was previously called ZBTB48. This protein binds preferentially to long telomeres, competing with telomeric repeat factors 1 and 2. Genetic changes in TZAP may be associated with cancer pathogenesis; however, this relationship has not yet been elucidated for any type of cancer. In this study, we aimed to examine the clinicopathologic and prognostic value of TZAP expression in cervical cancer (CC). Materials and Methods: The data were extracted from The Cancer Genome Atlas cohorts by OncoLnc (21 cancer types, 7700 cancers). The prognostic value of TZAP for different stages of 264 CCs was examined using survival analysis. Results: The TZAP expression did not differ significantly between CC and normal matched tissues. Age, cancer stage, and viral infection were not associated with TZAP expression. Survival analysis revealed a shorter overall survival in CC patients with a lower TZAP expression (χ2 = 3.62, p = 0.057). The prognostic value of TZAP expression was greater in patients with N1 stage CC (χ2 = 5.64, p = 0.018). Conclusion: TZAP expression is a possible prognostic marker for CC, especially stage N1 CC.

scholarly journals SCANVIS – a tool for SCoring, ANnotating and VISualizing splice junctions

2019 ◽  
Author(s):  
Phaedra Agius ◽  
Heather Geiger ◽  
Nicolas Robine
Keyword(s):  
Detailed Analysis ◽  
Read Coverage ◽  
Visualization Technique ◽  
Link Type ◽  
Diagnosis And Therapy ◽  
Junction Type ◽  
Cancer Types ◽  
Multiple Samples ◽  
Splice Junctions ◽  
Tissue Cancer

AbstractMotivationThe association of splicing signatures with disease is a leading area of study for prognosis, diagnosis and therapy, frequently requiring detailed analysis of splicing events across multiple samples. We present a novel fast-performing annotation-dependent tool called SCANVIS for scoring and annotating splice junctions by gene name, junction type and any frame shifts incurred. SCANVIS has a novel and fast visualization technique that distinguishes annotated splice junctions from unannotated ones in the context of nearby variants and read coverage. It also allows users to merge samples across cohorts, thereby allowing for quick comparisons of splice junctions across diseases and tissue types.ResultsWe show that SCANVIS generates reasonable PSI scores by demonstrating that tissue/cancer types in GTEX and TCGA are well separated and easily predicted from a few thousand SJs. We also show how SCANVIS can be used to map out junctions overlaid with variants and read coverage for one or more samples, with line types and colors delineating frame shifts and junction types.AvailabilitySCANVIS is available for download at https://github.com/nygenome/[email protected]

Sign in / Sign up

Export Citation Format

Share Document