scholarly journals The Construction and Analysis of ceRNA Network and Immune Infiltration in Kidney Renal Clear Cell Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Lugang Deng ◽  
Peixi Wang ◽  
Zhi Qu ◽  
Nan Liu
Keyword(s):  
Immune Cells ◽  
Proportional Hazards ◽  
Immune Cell ◽  
Clear Cell ◽  
Cell Types ◽  
Renal Clear Cell Carcinoma ◽  
Cox Proportional Hazards ◽  
Tissue Samples ◽  
Cerna Network ◽  
Proportional Hazards Regression

Background: Kidney renal clear cell carcinoma (KIRC) has the highest invasion, mortality and metastasis of the renal cell carcinomas and seriously affects patient’s quality of life. However, the composition of the immune microenvironment and regulatory mechanisms at transcriptomic level such as ceRNA of KIRC are still unclear.Methods: We constructed a ceRNA network associated with KIRC by analyzing the long non-coding RNA (lncRNA), miRNA and mRNA expression data of 506 tumor tissue samples and 71 normal adjacent tissue samples downloaded from The Cancer Genome Atlas (TCGA) database. In addition, we estimated the proportion of 22 immune cell types in these samples through “The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts.” Based on the ceRNA network and immune cells screened by univariate Cox analysis and Lasso regression, two nomograms were constructed to predict the prognosis of patients with KIRC. Receiver operating characteristic curves (ROC) and calibration curves were employed to assess the discrimination and accuracy of the nomograms. Consequently, co-expression analysis was carried out to explore the relationship between each prognostic gene in a Cox proportional hazards regression model of ceRNA and each survival-related immune cell in a Cox proportional hazards regression model of immune cell types to reveal the potential regulatory mechanism.Results: We established a ceRNA network consisting of 12 lncRNAs, 25 miRNAs and 136 mRNAs. Two nomograms containing seven prognostic genes and two immune cells, respectively, were successfully constructed. Both ROC [area under curves (AUCs) of 1, 3, and 5-year survival in the nomogram based on ceRNA network: 0.779, 0.747, and 0.772; AUCs of 1, 3, and 5-year survivals in nomogram based on immune cells: 0.603, 0.642, and 0.607] and calibration curves indicated good accuracy and clinical application value of both models. Through co-correlation analysis between ceRNA and immune cells, we found both LINC00894 and KIAA1324 were positively correlated with follicular helper T (Tfh) cells and negatively correlated with resting mast cells.Conclusion: Based on the ceRNA network and tumor-infiltrating immune cells, we constructed two nomograms to predict the survival of KIRC patients and demonstrated their value in improving the personalized management of KIRC.

scholarly journals The Construction and Analysis of ceRNA Network and Immune Infiltration in Kidney Renal Clear Cell Carcinoma

2021 ◽  
Author(s):  
Lugang Deng ◽  
Zhi Qu ◽  
Peixi Wang ◽  
Nan Liu
Keyword(s):  
Immune Cells ◽  
Proportional Hazards ◽  
Immune Cell ◽  
Clear Cell ◽  
Cell Types ◽  
Renal Clear Cell Carcinoma ◽  
Cox Proportional Hazards ◽  
Tissue Samples ◽  
Cerna Network ◽  
Proportional Hazards Regression

Abstract Purpose Kidney renal clear cell carcinoma (KIRC) has the highest invasion, mortality and metastasis of the renal cell carcinomas and seriously affects patients’ quality of life. However, the composition of the immune microenvironment and regulatory mechanisms at transcriptomic level such as ceRNA of KIRC are still unclear. Methods We constructed a ceRNA network associated with KIRC by analyzing the long noncoding RNA (lncRNA), miRNA and mRNA expression data of 506 tumor tissue samples and 71 normal adjacent tissue samples downloaded from the Cancer Genome Atlas (TCGA) database. In addition, we estimated the proportion of 22 immune cell types in these samples through “CIBERSORT”. Based on the ceRNA network and immune cells screened by univariate Cox analysis and Lasso regression, two nomograms were constructed to predict the prognosis of patients with KIRC. Receiver operating characteristic curves (ROC) and calibration curves were employed to assess the discrimination and accuracy of the nomograms. Consequently, co-expression analysis was carried out to explore the relationship between each prognostic gene in a Cox proportional hazards regression model of ceRNA and each survival-related immune cell in a Cox proportional hazards regression model of immune cell types to reveal the potential regulatory mechanism. Results We established a ceRNA network consisting of 12 lncRNAs, 25 miRNAs and 136 mRNAs. Two nomograms containing seven prognostic genes and two immune cells, respectively, were successfully constructed. Both ROC [Area Under Curves (AUCs) of 1, 3 and 5-year survival in the nomogram based on ceRNA network: 0.779, 0.747 and 0.772; AUCs of 1, 3 and 5-year survivals in nomogram based on immune cells: 0.603, 0.642 and 0.607] and calibration curves indicated good accuracy and clinical application value of both models. Through co-correlation analysis between ceRNA and immune cells, we found both LINC00894 and KIAA1324 were positively correlated with follicular helper T (Tfh) cells and negatively correlated with resting mast cells. Conclusions Based on the ceRNA network and tumor-infiltrating immune cells, we constructed two nomograms to predict the survival of KIRC patients and demonstrated their value in improving the personalized management of KIRC.

scholarly journals The Construction and Analysis of ceRNA Network and Immune Infiltration in Kidney Renal Clear Cell Carcinoma

2021 ◽  
Author(s):  
Lugang Deng ◽  
Zhi Qu ◽  
Peixi Wang ◽  
Nan Liu
Keyword(s):  
Immune Cells ◽  
Proportional Hazards ◽  
Immune Cell ◽  
Clear Cell ◽  
Cell Types ◽  
Renal Clear Cell Carcinoma ◽  
Cox Proportional Hazards ◽  
Tissue Samples ◽  
Cerna Network ◽  
Proportional Hazards Regression

AbstractBackgroundKidney renal clear cell carcinoma (KIRC) has the highest invasion, mortality and metastasis of the renal cell carcinomas and seriously affects patients’ quality of life. However, the composition of the immune microenvironment and regulatory mechanisms at transcriptomic level such as ceRNA of KIRC are still unclear.MethodsWe constructed a ceRNA network associated with KIRC by analyzing the long noncoding RNA (lncRNA), miRNA and mRNA expression data of 506 tumor tissue samples and 71 normal adjacent tissue samples downloaded from the Cancer Genome Atlas (TCGA) database. In addition, we estimated the proportion of 22 immune cell types in these samples through “The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts”. Based on the ceRNA network and immune cells screened by univariate Cox analysis and Lasso regression, two nomograms were constructed to predict the prognosis of patients with KIRC. Receiver operating characteristic curves (ROC) and calibration curves were employed to assess the discrimination and accuracy of the nomograms. Consequently, co-expression analysis was carried out to explore the relationship between each prognostic gene in a Cox proportional hazards regression model of ceRNA and each survival-related immune cell in a Cox proportional hazards regression model of immune cell types to reveal the potential regulatory mechanism.ResultsWe established a ceRNA network consisting of 12 lncRNAs, 25 miRNAs and 136 mRNAs. Two nomograms containing seven prognostic genes and two immune cells, respectively, were successfully constructed. Both ROC [Area Under Curves (AUCs) of 1, 3 and 5-year survival in the nomogram based on ceRNA network: 0.779, 0.747 and 0.772; AUCs of 1, 3 and 5-year survivals in nomogram based on immune cells: 0.603, 0.642 and 0.607] and calibration curves indicated good accuracy and clinical application value of both models. Through co-correlation analysis between ceRNA and immune cells, we found both LINC00894 and KIAA1324 were positively correlated with follicular helper T (Tfh) cells and negatively correlated with resting mast cells.ConclusionsBased on the ceRNA network and tumor-infiltrating immune cells, we constructed two nomograms to predict the survival of KIRC patients and demonstrated their value in improving the personalized management of KIRC.

scholarly journals The prognostic value of B7-H6 in esophageal squamous cell carcinoma

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Huan Zhou ◽  
Jun Dong ◽  
Liyi Guo ◽  
Xicheng Wang ◽  
Kailin Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lymphatic Metastasis ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Tissue Samples ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

AbstractB7-H6, a member of the B7 family molecules, participates in the clearance of tumor cells by binding to NKp30 on NK cells. B7-H6 expression level in esophageal squamous cell carcinoma (ESCC) and the clinical value remain unknown. The goal of this study was to determine the expression of B7-H6 in ESCC and further explore its clinical significance. We retrospectively collected the clinical data of 145 patients diagnosed with ESCC between January 2007 and December 2008. The expression of B7-H6 of the pathological tissue samples was detected by immunohistochemistry. The chi-square (χ2) test was used to analyse the relationships of B7-H6 and clinicopathological characteristics. Survival and hazard functions were estimated using the Kaplan-Meier method, and survival between groups was compared using the two-sided log-rank test. The Cox proportional hazards regression model was used to adjust for the risk factors related to overall survival (OS). 133/145 (91.72%) of the ESCC tissue samples exhibited B7-H6 expression. The expression level of B7-H6 was correlated with T stage (P = 0.036) and lymphatic metastasis status (P = 0.044). High B7-H6 expression (P = 0.003) was associated with a significantly worse OS than low B7-H6 expression. Multivariate Cox proportional hazards regression analysis demonstrated that tumour size (P = 0.021), B7-H6 expression (P = 0.025) and lymphatic metastasis status (P = 0.049) were independent prognostic factors of OS for ESCC. Collectively, our findings suggest that B7-H6 is widely expressed in ESCC samples. And B7-H6 may represent a predictor of poor prognosis for ESCC.

Utilization and sequencing of targeted therapy and cytoreductive nephrectomy in non–clear cell metastatic kidney cancer.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 615-615
Author(s):  
Liam Connor Macleod ◽  
Scott S. Tykodi ◽  
Sarah Holt ◽  
John L. Gore
Keyword(s):  
Overall Survival ◽  
Targeted Therapy ◽  
Kidney Cancer ◽  
Proportional Hazards ◽  
Clear Cell ◽  
Cox Proportional Hazards ◽  
Average Treatment Effect ◽  
Targeted Agents ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

615 Background: Many patients with metastatic kidney cancer (mRCC) are ineligible for trials due to non-clear cell histology. Efficacy of targeted therapy agents in non-clear cell mRCC is still being investigated. We hypothesized that sequencing CN upfront is associated with improved overall survival. We analyze a population-based cohort of non-clear cell mRCC patients in the targeted therapy era. Methods: Patients from the SEER-Medicare files (2005-2011) with non-clear cell mRCC were categorized as having received upfront targeted therapy or upfront CN. Additional exclusions were age < 66 to avoid confounding by uncaptured non-Medicare coverage, and competing stage IV cancer. Targeted therapy was identified through Medicare Part D files. Cox proportional hazards regression determined association between treatment groups, clinical and cancer-related characteristics, and the main outcome, median overall survival (OS). Propensity matching controlled for measurable confounding in treatment selection. Results: Of 1,326 mRCC cases, 528 met inclusion criteria of whom 433 (82%) received targeted agents and 172 (33%) underwent CN. Of those not having CN, 74% were diagnosed by biopsy, 10% by cytology, and 16% radiographically (confirmed at autopsy). Thirteen percent received CN then targeted therapy (OS 14 mos, IQR 9-25), 2.5% received targeted therapy then CN (OS 14 mos, IQR 9-26), 18% received CN only (OS 14 mos, IQR5-40), 67% received targeted therapy only (OS 9 mos, IQR 4-19). On multivariable Cox proportional hazards regression upfront CN (regardless of post-CN therapy) was associated with improved OS (HR 0.54,95% CI 0.41,0.72). Using propensity scores, upfront CN patients (N = 161) were matched to upfront targeted therapy patient (N = 111) and the average treatment effect of CN was 8.3 months survival improvement (95% CI 4.0, 13.2). Conclusions: Although utilization of targeted agents in non-clear cell mRCC exceeds 80%, those with greatest OS received CN either upfront or after targeted therapy, though the latter was rare (2.5%). The variety of sequencing strategies observed is evidence of uncertainty regarding the best care for non-clear cell mRCC patients given limited options.

scholarly journals Comprehensive analysis of ceRNA network related to lincRNA in glioblastoma and prediction of clinical prognosis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guangdong Liu ◽  
Danian Liu ◽  
Jingjing Huang ◽  
Jianxin Li ◽  
Chuang Wang ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Cox Regression ◽  
Cox Model ◽  
Differential Expression Analysis ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Normal Brain ◽  
Tissue Samples ◽  
Clinical Prognosis ◽  
Cerna Network

Abstract Background Long intergenic non-coding RNAs (lincRNAs) are capable of regulating several tumours, while competitive endogenous RNA (ceRNA) networks are of great significance in revealing the biological mechanism of tumours. Here, we aimed to study the ceRNA network of lincRNA in glioblastoma (GBM). Methods We obtained GBM and normal brain tissue samples from TCGA, GTEx, and GEO databases, and performed weighted gene co-expression network analysis and differential expression analysis on all lincRNA and mRNA data. Subsequently, we predicted the interaction between lincRNAs, miRNAs, and target mRNAs. Univariate and multivariate Cox regression analyses were performed on the mRNAs using CGGA data, and a Cox proportional hazards regression model was constructed. The ceRNA network was further screened by the DEmiRNA and mRNA of Cox model. Results A prognostic prediction model was constructed for patients with GBM. We assembled a ceRNA network consisting of 18 lincRNAs, 6 miRNAs, and 8 mRNAs. Gene Set Enrichment Analysis was carried out on four lincRNAs with obvious differential expressions and relatively few studies in GBM. Conclusion We identified four lincRNAs that have research value for GBM and obtained the ceRNA network. Our research is expected to facilitate in-depth understanding and study of the molecular mechanism of GBM, and provide new insights into targeted therapy and prognosis of the tumour.

scholarly journals Pancancer survival analysis of cancer hallmark genes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ádám Nagy ◽  
Gyöngyi Munkácsy ◽  
Balázs Győrffy
Keyword(s):  
Survival Data ◽  
Proportional Hazards ◽  
Clear Cell ◽  
Genome Instability ◽  
Cell Cancer ◽  
Renal Clear Cell Carcinoma ◽  
Cox Proportional Hazards ◽  
Multiple Hypothesis Testing ◽  
Low Grade ◽  
Cancer Types

AbstractCancer hallmark genes are responsible for the most essential phenotypic characteristics of malignant transformation and progression. In this study, our aim was to estimate the prognostic effect of the established cancer hallmark genes in multiple distinct cancer types. RNA-seq HTSeq counts and survival data from 26 different tumor types were acquired from the TCGA repository. DESeq was used for normalization. Correlations between gene expression and survival were computed using the Cox proportional hazards regression and by plotting Kaplan–Meier survival plots. The false discovery rate was calculated to correct for multiple hypothesis testing. Signatures based on genes involved in genome instability and invasion reached significance in most individual cancer types. Thyroid and glioblastoma were independent of hallmark genes (61 and 54 genes significant, respectively), while renal clear cell cancer and low grade gliomas harbored the most prognostic changes (403 and 419 genes significant, respectively). The eight genes with the highest significance included BRCA1 (genome instability, HR 4.26, p < 1E−16), RUNX1 (sustaining proliferative signaling, HR 2.96, p = 3.1E−10) and SERPINE1 (inducing angiogenesis, HR 3.36, p = 1.5E−12) in low grade glioma, CDK1 (cell death resistance, HR = 5.67, p = 2.1E−10) in kidney papillary carcinoma, E2F1 (tumor suppressor, HR 0.38, p = 2.4E−05) and EREG (enabling replicative immortality, HR 3.23, p = 2.1E−07) in cervical cancer, FBP1 (deregulation of cellular energetics, HR 0.45, p = 2.8E−07) in kidney renal clear cell carcinoma and MYC (invasion and metastasis, HR 1.81, p = 5.8E−05) in bladder cancer. We observed unexpected heterogeneity and tissue specificity when correlating cancer hallmark genes and survival. These results will help to prioritize future targeted therapy development in different types of solid tumors.

scholarly journals Comprehensive Analysis of lincRNA-Related ceRNA Network in Glioblastoma

2020 ◽  
Author(s):  
Guangdong Liu ◽  
Danian Liu ◽  
Jingjing Huang ◽  
Jianxin Li ◽  
Chuang Wang ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Cox Regression ◽  
Cox Model ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Cox Proportional Hazards ◽  
Gene Set Enrichment Analysis ◽  
Normal Brain ◽  
Tissue Samples ◽  
Cerna Network

Abstract BackgroundLong intergenic non-coding RNAs (lincRNAs) are capable of regulating several tumours, while competitive endogenous RNA (ceRNA) networks are of great significance in revealing the biological mechanism of tumours. Currently, there is a dearth of studies on the ceRNA network of lincRNAs in glioblastoma (GBM), which we aimed to assess in the present study. MethodsWe obtained GBM and normal brain tissue samples from TCGA, GTEx, and GEO databases, and performed weighted gene co-expression network analysis and differential expression analysis on all lincRNA and mRNA data. Subsequently, we predicted the interaction between lincRNAs, miRNAs, and target mRNAs. Univariate and multivariate Cox regression analyses were performed on the mRNAs using CGGA data, and a Cox proportional hazards regression model was constructed. ResultsAccording to the Cox model, we assembled a ceRNA network consisting of 23 lincRNAs, 14 miRNAs, and 13 mRNAs. Gene Set Enrichment Analysis was carried out on four lincRNAs with obvious differential expressions and relatively few studies in GBM. ConclusionWe identified four lincRNAs that have the most research values for GBM and obtained the ceRNA network. Our research is expected to facilitate in-depth understanding and study of the molecular mechanism of GBM, and provide new insights into targeted therapy and prognosis of the tumour.

scholarly journals Identification a ceRNA (XIST/miR-10a-5p/SERPINE1) Axis as a Prognostic Biomarker in Kidney Renal Clear Cell Carcinoma.

2021 ◽  
Author(s):  
Rui-ji Liu ◽  
Zhi-Peng Xu ◽  
Shuying Li ◽  
Jun-Jie Yu ◽  
Bin Xu ◽  
...  
Keyword(s):  
T Cell ◽  
Cell Carcinoma ◽  
Immune Cell ◽  
Clear Cell ◽  
Prognostic Biomarker ◽  
Clear Cell Carcinoma ◽  
Renal Clear Cell Carcinoma ◽  
Immune Cell Infiltration ◽  
Cerna Network

Abstract Background: Kidney cancer is one of the most common malignancies, of which the most aggressive subtype was kidney renal clear cell carcinoma (KIRC), accounting for 80% of them. A growing number of studies point to the involvement of competitive endogenous RNAs in tumor development. However, the role of ceRNA network involved in KIRC remains unclear. Thus, the aim of this study was to investigate the BAP1-associated prognostic ceRNA in KIRC. Methods: We downloaded the RNAseq data from TCGA along with the relevant clinical data. We screened the differentially expressed lncRNAs, miRNAs, mRNAs according to the expression of BAP1 and established a ceRNA network. Results: After comprehensive bioinformatics analysis, we identified the XIST-miR-10a-5p-SERPINE1 ceRNA axis. Next, we confirmed the prognostic role of miR-10a-5p/SERPINE1 in KIRC using survival analysis and Cox regression analysis. To investigate the abnormally high expression of SERPINE1, we performed methylation analysis of SERPINE1 and concluded that the methylation level of SERPINE1 in KIRC was significantly lower than that in normal tissues. Furthermore, to study the role of SERPINE1 in the immune microenvironment in KIRC, we performed immune cell infiltration analysis and found that SERPINE1 expression was positively correlated with the level of multiple immune cell infiltration (CD 4+ T cell, CD 8+ T cell, macrophages, dendritic cells, neutrophils). Conclusion: We constructed a ceRNA (XIST/has-miR-10a-5p/SERPINE1) that can be used as prognostic biomarker of KIRC. Furthermore, we found that miR-10a-5p/SERPINE1 were significantly associated with clinical features and were independent prognostic factors of KIRC.

ceRNA network development and tumor-infiltrating immune cell analysis in Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Li Chen ◽  
Weijie Zou ◽  
Lei Zhang ◽  
Huijuan Shi ◽  
Zhi Li ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cells ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
High Morbidity ◽  
Clinical Prognosis ◽  
Cerna Network ◽  
Kaplan Meier

Abstract Background: Hepatocellular carcinoma is among the primary causes of cancer deaths globally. Despite efforts to understand liver cancer, its high morbidity and mortality remain high. Herein, we constructed two nomograms based on ceRNA networks and invading immune cells to describe the molecular mechanisms along with the clinical prognosis of HCC patients.Methods: RNA maps of tumors and normal samples were downloaded from TCGA. HTseq counts and fragments per megapons per thousand bases were read from 421 samples, including 371 tumor samples and 50 normal samples. We established a ceRNA network based on differential gene expression in normal versus tumor subjects. CIBERSORT was employed to differentiate 22 immune cell types according to tumor transcriptomes. Kaplan-Meier along with Cox proportional hazard analyses were employed to determine the prognosis-linked factors. Nomograms were constructed based on prognostic immune cells and ceRNAs. We employed ROC (Receiver operating characteristic) and calibration curve analyses to estimate these nomogram. Results: The difference analysis found 2028 mRNAs, 128 miRNAs, and 136 lncRNAs to be significantly differentially expressed in tumor samples relative to normal samples. We set up a ceRNA network containing 21 protein-coding mRNAs, 12 miRNAs, and 3 lncRNAs. In kaplan-Meier analysis, 21 of the 36 ceRNAs were considered significant. Of the 22 cell types, resting dendritic cell levels were markedly different in tumor samples versus normal controls. Calibration and ROC curve analysis of the ceRNA network, as well as immune-infiltration of tumor showed resultful accuracy (three-year survival AUC: 0.691, five-year survival AUC: 0.700; three-years survival AUC: 0.674, five-year survival AUC: 0.694). Our data suggest that Tregs, CD4 T-cells, mast cells, SNHG1, HMMR and hsa-miR-421 are associated with HCC based on ceRNA-immune cells co-expression patterns. Conclusion: On the basis of ceRNA network modeling and immune cell infiltration analysis, our study offers an effective bioinformatics strategy for studying HCC molecular mechanisms and prognosis.

scholarly journals Pancancer survival analysis of cancer hallmark genes

2020 ◽  
Author(s):  
Ádám Nagy ◽  
Gyöngyi Munkácsy ◽  
Balázs Győrffy
Keyword(s):  
Survival Data ◽  
Proportional Hazards ◽  
Clear Cell ◽  
Genome Instability ◽  
Cell Cancer ◽  
Renal Clear Cell Carcinoma ◽  
Cox Proportional Hazards ◽  
Multiple Hypothesis Testing ◽  
Low Grade ◽  
Cancer Types

ABSTRACTCancer hallmark genes are responsible for the most essential phenotypic characteristics of malignant transformation and progression. In this study, our aim was to estimate the prognostic effect of the established cancer hallmark genes in multiple distinct cancer types.RNA-seq HTSeq counts and survival data from 26 different tumor types were acquired from the TCGA repository. DESeq was used for normalization. Correlations between gene expression and survival were computed using the Cox proportional hazards regression and by plotting Kaplan-Meier survival plots. The false discovery rate was calculated to correct for multiple hypothesis testing.Signatures based on genes involved in genome instability and invasion reached significance in most individual cancer types. Thyroid and glioblastoma were independent of hallmark genes (61 and 54 genes significant, respectively), while renal clear cell cancer and low grade gliomas harbored the most prognostic changes (403 and 419 genes significant, respectively). The eight genes with the highest significance included BRCA1 (genome instability, HR=4.26, p<1E-16), RUNX1 (sustaining proliferative signaling, HR=2.96, p=3.1E-10) and SERPINE1 (inducing angiogenesis, HR=3.36, p=1.5E-12) in low grade glioma, CDK1 (cell death resistance, HR=5.67, p=2.1E-10) in kidney papillary carcinoma, E2F1 (tumor suppressor, HR=0.38, p=2.4E-05) and EREG (enabling replicative immortality, HR=3.23, p=2.1E-07) in cervical cancer, FBP1 (deregulation of cellular energetics, HR=0.45, p=2.8E-07) in kidney renal clear cell carcinoma and MYC (invasion and metastasis, HR=1.81, p=5.8E-05) in bladder cancer.We observed unexpected heterogeneity and tissue specificity when correlating cancer hallmark genes and survival. These results will help to prioritize future targeted therapy development in different types of solid tumors.

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