scholarly journals Consensus outlier detection in survival analysis using the rank product test

2018 ◽  
Author(s):  
Eunice Carrasquinha ◽  
André Veríssimo ◽  
Susana Vinga
Keyword(s):  
Survival Analysis ◽  
Outlier Detection ◽  
Survival Data ◽  
Multiple Testing ◽  
The Cancer Genome Atlas ◽  
Medical Field ◽  
Rank Product ◽  
Product Test ◽  
Cancer Genome Atlas ◽  
Rank Product Test

AbstractSurvival analysis is a well known technique in the medical field. The identification of individuals whose survival time is too short or to long given their profile, assumes great importance for the detection of new prognostic factors. The study of these outlying observations have gained increasing relevancy with the availability of high-throughput molecular and clinical data for large cohorts of patients. Several methods for outlier detection in survival data have been proposed, which include the analysis of the residuals, the measurement of the concordance c-index, and methods based on quantile regression for censored data. However, different results are obtained depending on the type of method used. In order to solve the disparity of results we proposed to apply the Rank Product test. A simulated dataset, and two clinical datasets were used to illustrate our proposed consensus outlier detection method, one from myeloma disease and the other from The Cancer Genome Atlas (TCGA) ovarian cancer. Finally, the Rank Product with multiple testing corrections was performed in order to identify which observations have the highest rank amongst the methods considered. Our results illustrate the potential of this consensus approach for the automated retrieval of outliers and also the identification of biomarkers associated with survival in large datasets.

scholarly journals Predicted CD4+ T cell infiltration levels could indicate better overall survival in sarcoma patients

2021 ◽  
Vol 49 (1) ◽  
pp. 030006052098153
Author(s):  
Qing Bi ◽  
Yang Liu ◽  
Tao Yuan ◽  
Huizhen Wang ◽  
Bin Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
T Cell ◽  
Survival Data ◽  
Tumor Infiltrating Lymphocytes ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
T Cell Infiltration ◽  
Whole Exome ◽  
Cancer Genome Atlas ◽  
Infiltrating Lymphocytes

Objective The role of tumor-infiltrating lymphocytes (TILs) has not yet been characterized in sarcomas. The aim of this bioinformatics study was to explore the effect of TILs on sarcoma survival and genome alterations. Methods Whole-exome sequencing, transcriptome sequencing, and survival data of sarcoma were obtained from The Cancer Genome Atlas. Immune infiltration scores were calculated using the Tumor Immune Estimation Resource. Potential associations between abundance of infiltrating TILs and survival or genome alterations were examined. Results Levels of CD4+ T cell infiltration were associated with overall survival of patients with pan-sarcomas, and higher CD4+ T cell infiltration levels were associated with better survival. Somatic copy number alterations, rather than mutations, were found to correlate with CD4+ T cell infiltration levels. Conclusions This data mining study indicated that CD4+ T cell infiltration levels predicted from RNA sequencing could predict sarcoma prognosis, and higher levels of CD4+ T cells infiltration indicated a better chance of survival.

scholarly journals Angiogenin Upregulation Independently Predicts Unfavorable Overall Survival in Proneural Subtype of Glioblastoma

2019 ◽  
Vol 18 ◽  
pp. 153303381984663
Author(s):  
Ji-liang Hu ◽  
Wei-Jian Luo ◽  
Hao Wang
Keyword(s):  
Overall Survival ◽  
Survival Data ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Isocitrate Dehydrogenase 1 ◽  
Study Results ◽  
Cancer Genome Atlas ◽  
Secondary Study ◽  
Independent Indicator ◽  
Temozolomide Chemotherapy

Objective: Angiogenin is a small protein that exerts potent stimulating effects on angiogenesis. In this study, we aimed to examine the expression of angiogenin in different subtypes of glioblastoma and estimated its independent prognostic value. Methods: The genomic and survival data from The Cancer Genome Atlas-glioblastoma were extracted for a secondary study. Results The expression of angiogenin was upregulated in glioblastoma tissues and varied significantly in different subtypes. Although the proneural subtype had the lowest angiogenin expression, high angiogenin expression was associated with significantly worse overall survival. However, this association was not observed in other subtypes. By performing univariate and multivariate analysis using Cox regression model, we observed that high angiogenin expression was an independent indicator of shorter overall survival in proneural glioblastoma (hazard ratio: 1.669, 95% confidence interval: 1.033-2.696, P = .036), after adjustment of age, gender, isocitrate dehydrogenase 1 mutation, temozolomide chemotherapy and radiation therapy. In addition, we also observed a correlation between elevated angiogenin expression and the hypomethylated status of its DNA. The hypermethylation group had significantly better overall survival. Conclusions: Angiogenin upregulation might serve as a biomarker for unfavorable overall survival in the proneural subtype of glioblastoma.

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 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

Genome-wide methylation and expression profiling identify a novel epigenetic signature in gastrointestinal pan-adenocarcinomas

Epigenomics ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 907-920
Author(s):  
Wei Song ◽  
Jun Ren ◽  
Wen-Jie Wang ◽  
Chun-Tao Wang ◽  
Tao Fu
Keyword(s):  
Overall Survival ◽  
Survival Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Predictive Ability ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Clinicopathologic Factors ◽  
Cancer Genome Atlas

Aim: To identify methylation-driven genes and establish a novel epigenetic signature for gastrointestinal (GI) pan-adenocarcinomas. Materials & methods: Methylation and RNA-seq data for GI adenocarcinomas were downloaded from the Cancer Genome Atlas database. A methylation-driven gene signature was established by multivariate Cox regression analysis. We developed a prognostic nomogram using a combination of methylation-driven gene risk score and clinicopathological variables. A joint survival analysis based on gene expression and methylation was conducted to further investigate the prognostic role of methylation-driven genes. Results: An epigenetic signature was established based on five methylation-driven genes. We also established a prognostic nomogram based on methylation-driven gene risk score and clinicopathologic factors, with a favorable predictive ability. Joint survival analysis revealed that 28 methylation-driven genes could be independent prognostic factors for overall survival for GI adenocarcinomas. Conclusion: An epigenetic signature was established that effectively predicts the overall survival for GI adenocarcinomas across anatomic boundaries.

scholarly journals GIANT: an online resource for comprehensive survival analysis in pan-cancer from The Cancer Genome Atlas (Preprint)

2018 ◽  
Author(s):  
Myoung-Eun Han ◽  
Tae Sik Goh ◽  
Dae Cheon Jeong ◽  
Chi-Seung Lee ◽  
Ji-Young Kim ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Single Gene ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Rna Seq ◽  
Web Based ◽  
Online Resource ◽  
Cancer Genome Atlas ◽  
Or Gene ◽  
Pan Cancer

BACKGROUND Prognostic genes or gene signatures have been widely used to predict patients’ survival and aid the decision of therapeutic options. Although few web-based survival analysis tools to identify them have been developed, they only provide limited information. OBJECTIVE To overcome limitations of previous web-based tools and provide comprehensive survival analysis, we developed GIANT, an online resource for identifying prognostic biomarkers in pan-cancer from The Cancer Genome Atlas (TCGA). METHODS We used R program to code survival analysis based on RNA-seq data from TCGA (n=10,320). To perform survival analyses, we excluded patients and genes that have insufficient information (survival status, tumor stage, age, gender, cancer type, blast count, and histologic grade). The GIANT is programmed by applying appropriate cross validation methods and survival analysis methods to provide three analysis services (survival analysis by single gene, cancer type, variable signature). RESULTS It can perform comprehensive survival analysis to identify prognostic genes or gene signatures with reflecting tumor heterogeneity. Using RNA-seq, clinical data and pathway databases in combination, it provides gene/variable signature by grouped variable selection methods (least absolute shrinkage and selection operator, Elastic Net regularization, Network-Regularized high-dimensional Cox-regression) that has better discriminatory power than single gene. Users also can find prognostic values of gene and statistically significant genes in specific cancer. All results are presented as Kaplan-Meier curve with median/optimal cutoff value, C-index, and area under the curve (AUC) value at t-years. Moreover, users can easily obtain results in the forms of graphs and tables. CONCLUSIONS In conclusion, the GIANT has made it possible to easily perform integrated survival analysis while overcoming the limitations of previous online tools. It will help scientists of those who are vulnerable to computer technology to do database analysis can easily perform comprehensive survival analysis.

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 Identification of Hub Genes for Controlling Cancer Stem Cell Characteristics in Colorectal Cancer by Bioinformatics Analysis

2021 ◽  
Author(s):  
Xiang Li ◽  
Shuoyang Huang ◽  
Chao Yang ◽  
Yongbin Zheng
Keyword(s):  
Colorectal Cancer ◽  
Stem Cell ◽  
Survival Data ◽  
Prognostic Model ◽  
The Cancer Genome Atlas ◽  
Lasso Regression ◽  
Immune Microenvironment ◽  
Hub Genes ◽  
Normal Tissues ◽  
Cancer Genome Atlas

Abstract Background Cancer stem cells (CSCs), which are capable of infinite proliferation and self-renewal, play a crucial role in the occurrence and development of colorectal cancer (CRC). The study of the expression characteristics of CRC stem cell-related genes and their interaction with the immune microenvironment may contribute to CRC treatment. Results In order to explore the hub genes that regulate the stemness characteristics of CRC, we obtained gene expression values of the Cancer Genome Atlas (TCGA), stemness indices (mRNAsi), and corresponding survival data from UCSC Xena Browser. Differentially expressed genes (DEGs) were identified in cancer and normal tissues. Then we screened 2 modules and 210 mRNAsi-related genes from 4,941 DEGs by weighted gene co-expression network analysis. A prognostic model including ten genes (VCAN, SPARC, COL12A1, THBS2, COL1A2, COL5A1, TAGLN, DCN, MYH11, CDH11) was constructed using protein interaction networks and LASSO regression. We also evaluated the relationship between cancer stemness and immune response and found there was a strong correlation between each other. Conclusions Our study establishes a prognostic model associated with CSCs and reveals the association between mRNAsi and the tumor immune microenvironment, which is useful for the targeted therapy of CRC.

20q amplification defined by genomic and clinical characteristics as a subgroup with increased prevalence and better survival in metastatic colorectal cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16003-e16003
Author(s):  
Satish Maharaj ◽  
RuoBing Xue ◽  
Anmol Cheema
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Survival Data ◽  
Information Exchange ◽  
Clinical Characteristics ◽  
The Cancer Genome Atlas ◽  
Independent Prognostic Marker ◽  
Cancer Genome Atlas ◽  
Microsatellite Stability ◽  
Next Generation Sequencing Ngs

e16003 Background: Genomic instability from 20q amplification is an oncogenic pathway in colorectal cancer (CRC). Several genes have been implicated, including BCL2L1, AURKA, SRC, ASXL1, GNAS and TOP1. There is a lack of data regarding 20q amplified group and one study implicating these genes suggested these patients have better overall survival. Next Generation Sequencing (NGS) has become widely used in metastatic CRC (mCRC) and easily identifies patients with 20q amplification. Nevertheless, most oncologists do not routinely consider 20q amplification status and this subgroup remains underinvestigated. This study aims to investigate genomic and clinical characteristics of 20q amplified mCRC using a single-center retrospective cohort and a multi-center genomic dataset. Methods: A cohort was identified comprising patients with mCRC who had NGS testing of tumor DNA and were treated between 2014-2019. Cases with and without 20q amplification were identified. Genomic, clinical and survival data were analyzed. Significant genomic findings were compared with all-stage CRC data using the AACR Genomic Evidence Neoplasia Information Exchange (GENIE) and The Cancer Genome Atlas (TCGA) databases. Results: Of the mCRC cohort ( n= 72), 15% ( n= 11) had 20q amplification. Amplified and non-amplified groups had no significant differences in age, sex or follow-up time. Patients with 20q amplification were more likely to have never smoked, and less likely to have treatment with targeted therapy. Survival analysis showed clear separation with longer overall survival for the amplified group. Eight genes at loci 20q11 to 20q13 were amplified - in order of frequency: ASXL1, GNAS, ARFRP1, ZNF217, AURKA, BCL2L1, SRC and TOP1. 20q amplification was significantly associated with wild-type RAS and BRAF, microsatellite stability, mutant TP53 and mutant APC. Using the GENIE and TCGA databases, it was found that metastatic disease had increased prevalence of all 20q amplified genes except TOP1, when compared to all-stage CRC. Conclusions: Clinical use of NGS identifies the 20q amplification subgroup that has increased prevalence in mCRC (compared to all CRC). Compared to non-20q amplified mCRC, this group had better survival, suggesting genomic pattern in mCRC is a novel independent prognostic marker. We believe mCRC patients would benefit from further studies defining a genomic prognostication model and development of therapy targeting the 20q amplification pathway.

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