Survival analysis of presumptive prognostic markers among oligodendrogliomas

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.

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

Frontiers in Genetics ◽

10.3389/fgene.2020.521004 ◽

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.

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

BMC Neurology ◽

10.1186/s12883-021-02187-8 ◽

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.

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An analysis about heterogeneity among cancers based on the DNA Methylation Patterns

10.21203/rs.2.11636/v1 ◽

2019 ◽

Author(s):

Yang Liu ◽

Yue Gu ◽

Mu Su ◽

Hui Liu ◽

Shumei Zhang ◽

...

Keyword(s):

Dna Methylation ◽

Survival Analysis ◽

Environmental Factors ◽

Prognostic Markers ◽

Cox Regression ◽

Regulation Of Gene Expression ◽

Absolute Difference ◽

Marker Genes ◽

Gene Markers ◽

Significant Difference

Abstract Background: The occurrence of cancer is usually the result of a co-effect of genetic and environmental factors. It is generally believed that the main cause of cancer is the accumulation of genetic mutations, and DNA methylation, as one of the epigenetic modifications closely related to environmental factors, participates in the regulation of gene expression and cell differentiation and plays an important role in the development of cancer. Methods: This article discusses the epigenetic heterogeneity of cancer in detail. Firstly DNA methylation data of 7 cancer types were obtained from Illumina Infinium HumanMethylation 450K platform of TCGA database. Diagnostic markers of each cancer were obtained by t-test and absolute difference of DNA differencial methylation analysis. Enrichment analysis of these specific markers indicated that they were involved in different biological functions. Secondly, important gene markers were obtained by constructing the DNA methylation correlation network and the gene interaction network in the KEGG pathway, and 317 marker genes set obtained from two networks were integrated as candidate markers for the prognosis model. The univariate and multivariate COX regression models were used to select specific independent prognostic markers for each cancer, and a risk-score model was constructed to divide patients of each cancer into two groups, highly-risky and lowly-risky groups. Results: Kaplan-Meier survival analysis showed that there was significant difference in survival between the two groups. In the verification set, there was also a difference in survival between the highly and lowly risky 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. Kewords: DNA methylation; cancer; epigenetic heterogeneity; survival analysis

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Identifying Mitochondrial-Related Genes NDUFA10 and NDUFV2 as Prognostic Markers for Prostate Cancer through Biclustering

BioMed Research International ◽

10.1155/2021/5512624 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Haokun Zhang ◽

Yuanhua Shao ◽

Weijun Chen ◽

Xin Chen

Keyword(s):

Gene Expression ◽

Prostate Cancer ◽

Survival Analysis ◽

Cancer Patients ◽

Gene Expression Profile ◽

Expression Profile ◽

Prognostic Markers ◽

The United States ◽

The Core ◽

Core Genes

Prostate cancer is currently associated with higher morbidity and mortality in men in the United States and Western Europe, so it is important to identify genes that regulate prostate cancer. The high-dimension gene expression profile impedes the discovery of biclusters which are of great significance to the identification of the basic cellular processes controlled by multiple genes and the identification of large-scale unknown effects hidden in the data. We applied the biclustering method MCbiclust to explore large biclusters in the TCGA cohort through a large number of iterations. Two biclusters were found with the highest silhouette coefficient value. The expression patterns of one bicluster are highly similar to those found by the gene expression profile of the known androgen-regulated genes. Further gene set enrichment revealed that mitochondrial function-related genes were negatively correlated with AR regulation-related genes. Then, we performed differential analysis, AR binding site analysis, and survival analysis on the core genes with high phenotypic contribution. Among the core genes, NDUFA10 showed a low expression value in cancer patients across different expression profiles, while NDUFV2 showed a high expression value in cancer patients. Survival analysis of NDUFA10 and NDUFV2 demonstrated that both genes were unfavorable prognostic markers.

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Potential prognostic markers and significant lncRNA–mRNA co-expression pairs in laryngeal squamous cell carcinoma

Open Life Sciences ◽

10.1515/biol-2021-0052 ◽

2021 ◽

Vol 16 (1) ◽

pp. 544-557

Author(s):

Junguo Wang ◽

Dingding Liu ◽

Yajun Gu ◽

Han Zhou ◽

Hui Li ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

Survival Analysis ◽

Cell Carcinoma ◽

Squamous Cell ◽

Laryngeal Squamous Cell Carcinoma ◽

Prognostic Markers ◽

Interaction Network ◽

Protein Protein Interaction ◽

Qrt Pcr ◽

Cancer Tissues

Abstract lncRNA–mRNA co-expression pairs and prognostic markers related to the development of laryngeal squamous cell carcinoma (LSCC) were investigated. The lncRNA and mRNA expression data of LSCC in GSE84957 and RNA-seq data of 112 LSCC samples from TCGA database were used. Differentially expressed genes (DEGs) and lncRNAs (DE-lncRNAs) between LSCC and para-cancer tissues were identified. Co-expression analysis of DEGs and DE-lncRNA was conducted. Protein–protein interaction network for co-expressed DEGs of top 25 DE-lncRNA was constructed, followed by survival analysis for key nodes in co-expression network. Finally, expressions of several DE-lncRNAs and DEGs were verified using qRT-PCR. The lncRNA–mRNA network showed that ANKRD20A5P, C21orf15, CYP4F35P, LOC_I2_011146, XLOC_006053, XLOC_I2_003881, and LOC100506027 were highlighted in network. Some DEGs, including FUT7, PADI1, PPL, ARHGAP40, MUC21, and CEACAM1, were co-expressed with above lncRNAs. Survival analysis showed that PLOD1, GLT25D1, and KIF22 were significantly associated with prognosis. qRT-PCR results showed that the expressions of MUC21, CEACAM1, FUT7, PADI1, PPL, ARHGAP40, ANKRD20A5P, C21orf15, CYP4F35P, XLOC_I2_003881, LOC_I2_011146, and XLOC_006053 were downregulated, whereas the expression of LOC100506027 was upregulated in LSCC tissues. PLOD1, GLT25D1, and KIF22 may be potential prognostic markers in the development of LSCC. C21orf15-MUC21/CEACAM1/FUT7/PADI1/PPL/ARHGAP40 are potential lncRNA–mRNA pairs that play significant roles in the development of LSCC.

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Conditional transcriptional relationships may serve as cancer prognostic markers

BMC Medical Genomics ◽

10.1186/s12920-021-00958-3 ◽

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.

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Cancer-Testis Gene Expression in Hepatocellular Carcinoma: Identification of Prognostic Markers and Potential Targets for Immunotherapy

Technology in Cancer Research & Treatment ◽

10.1177/1533033820944274 ◽

2020 ◽

Vol 19 ◽

pp. 153303382094427

Author(s):

Yan-Peng Zhang ◽

Zhi-Wei Bao ◽

Jing-Bang Wu ◽

Yun-Hao Chen ◽

Jun-Ru Chen ◽

...

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Survival Analysis ◽

T Cell ◽

Prognostic Markers ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Pathway Enrichment ◽

T Cell Infiltration ◽

Cancer Testis

Background: Cancer-testis genes can serve as prognostic biomarkers and valuable targets for immunotherapy in multiple tumors because of their restricted expression in testis and cancer. However, their expression pattern in hepatocellular carcinoma is still not well understood. The purpose is to comprehensively characterize the cancer-testis gene expression in hepatocellular carcinoma as well as identify prognostic markers and potential targets for immunotherapy. Methods: Cancer-testis database and publicly available data sets reporting new cancer-testis genes were integrated, and then restricted them in a testis and hepatocellular carcinoma expression pattern. Pathway enrichment analysis and survival analysis were conducted to evaluate the biological function and prognostic effect of cancer-testis genes. Clustering analysis and coexpression analysis were performed to illustrate cancer-testis gene expression patterns in hepatocellular carcinoma. The association of gene expression of each cancer-testis gene to the corresponding methylation status was detected. Finally, we explored the associations between cancer-testis genes and CD8+ T-cell infiltration in hepatocellular carcinoma by TISIDB, and then validated it in an independent hepatocellular carcinoma cohort with 72 patients. Results: A total of 59 testis-specific genes were identified highly expressed in hepatocellular carcinoma. Pathway enrichment analysis revealed that cancer-testis genes in hepatocellular carcinoma significantly involves in the process of cell cycle regulation. Most of the cancer-testis genes were coexpressed, and cluster analysis suggested that cancer-testis gene expressed in hepatocellular carcinoma is independent of sex, hepatitis status, and histology type. We also found that demethylation might be a regulatory mechanism of cancer-testis gene expression in hepatocellular carcinoma. Survival analysis indicated that cancer-testis genes could predict the prognosis of patients with hepatocellular carcinoma. Furthermore, BUB1B was identified contributing to the resistance of CD8+ T-cell infiltration in hepatocellular carcinoma and was an independent prognostic factor both for overall survival and disease-free survival. Conclusions: Our analysis enables better understanding of cancer-testis genes in hepatocellular carcinoma and provides potential targets for hepatocellular carcinoma treatment. Experimental and clinical studies are needed for further validations.

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