scholarly journals Integrated analysis of immune-related genes in endometrial carcinoma

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Yiru Wang ◽  
Yunduo Liu ◽  
Yue Guan ◽  
Hao Li ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Endometrial Carcinoma ◽  
Roc Analysis ◽  
Prognostic Indicator ◽  
Integrated Analysis ◽  
High Morbidity ◽  
Qrt Pcr ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Immune Related Genes

Abstract Background Exploring novel and sensitive targets is urgent due to the high morbidity of endometrial cancer (EC). The purpose of our study was to explore the transcription factors and immune-related genes in EC and further identify immune-based lncRNA signature as biomarker for predicting survival prognosis. Methods Transcription factors, aberrantly expressed immune-related genes and immune-related lncRNAs were explored through bioinformatics analysis. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related lncRNAs. The accuracy of model was evaluated by Kaplan–Meier method and receiver operating characteristic (ROC) analysis, and the independent prognostic indicator was identified with Cox analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the accuracy of our results. Results A network of 29 transcription factors and 17 immune-related genes was constructed. Furthermore, four immune-prognosis-related lncRNAs were screened out. Kaplan–Meier survival analysis and time-dependent ROC analysis revealed a satisfactory predictive potential of the 4-lncRNA model. Consistency was achieved among the results from the training set, testing set and entire cohort. The distributed patterns between the high- and low-risk groups could be distinguished in principal component analysis. Comparisons of the risk score and clinical factors confirmed the four-lncRNA-based signature as an independent prognostic indicator. Last, the reliability of the results was verified by qRT-PCR in 29 cases of endometrial carcinoma and in cells. Conclusions Overall, our study constructed a network of transcription factors and immune-related genes and explored a four immune-related lncRNA signature that could serve as a novel potential biomarker of EC.

scholarly journals Integrated analysis of immune-related genes in endometrial carcinoma

2020 ◽  
Author(s):  
Yiru Wang ◽  
Yunduo Liu ◽  
Yue Guan ◽  
Hao Li ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Endometrial Carcinoma ◽  
Roc Analysis ◽  
Prognostic Indicator ◽  
Integrated Analysis ◽  
High Morbidity ◽  
Qrt Pcr ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Immune Related Genes

Abstract Background: Exploring novel and sensitive targets is urgent due to the high morbidity of endometrial cancer (EC). The purpose of our study was to explore the transcription factors and immune-related genes in EC and further identify immune-based lncRNA signature as biomarker for predicting survival prognosis.Methods: Transcription factors, aberrantly expressed immune-related genes and immune-related lncRNAs were explored through bioinformatics analysis. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related lncRNAs. The accuracy of model was evaluated by Kaplan-Meier method and receiver operating characteristic (ROC) analysis, and the independent prognostic indicator was identified with Cox analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the accuracy of our results.Results: A network of 29 transcription factors and 17 immune-related genes was constructed. Furthermore, four immune-prognosis-related lncRNAs were screened out. Kaplan-Meier survival analysis and time-dependent ROC analysis revealed a satisfactory predictive potential of the 4-lncRNA model. Consistency was achieved among the results from the training set, testing set and entire cohort. The distributed patterns between the high- and low-risk groups could be distinguished in principal component analysis. Comparisons of the risk score and clinical factors confirmed the four-lncRNA-based signature as an independent prognostic indicator. Last, the reliability of the results was verified by qRT-PCR in 29 cases of endometrial carcinoma and in cells.Conclusions: Overall, our study constructed a network of transcription factors and immune-related genes and explored a four immune-related lncRNA signature that could serve as a novel potential biomarker of EC.

scholarly journals Integrated Analysis of Immune-Related Genes in Endometrial Carcinoma

2020 ◽  
Author(s):  
Yiru Wang ◽  
Yunduo Liu ◽  
Yue Guan ◽  
Hao Li ◽  
Yuan Liu ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Endometrial Carcinoma ◽  
Roc Analysis ◽  
Prognostic Indicator ◽  
Integrated Analysis ◽  
High Morbidity ◽  
Qrt Pcr ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Immune Related Genes

Abstract Background:Exploring novel and sensitive targets is urgent due to the high morbidity of endometrial cancer (EC). The purpose of our study was to explore the transcription factors and immune-related genes in EC and further identify immune-based lncRNA signature as biomarker for predicting survival prognosis.Methods:Transcription factors, aberrantly expressed immune-related genes and immune-related lncRNAs were explored through bioinformatics analysis. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related lncRNAs. The accuracy of model was evaluated by Kaplan-Meier method and receiver operating characteristic (ROC) analysis, and the independent prognostic indicator was identified with Cox analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the accuracy of our results.Results:A network of 29 transcription factors and 17 immune-related genes was constructed. Furthermore, four immune-prognosis-related lncRNAs were screened out. Kaplan-Meier survival analysis and time-dependent ROC analysis revealed a satisfactory predictive potential of the 4-lncRNA model. Consistency was achieved among the results from the training set, testing set and entire cohort. The distributed patterns between the high- and low-risk groups could be distinguished in principal component analysis. Comparisons of the risk score and clinical factors confirmed the four-lncRNA-based signature as an independent prognostic indicator. Last, the reliability of the results was verified by qRT-PCR in 29 cases of endometrial carcinoma.Conclusions:Overall, our study constructed a network of transcription factors and immune-related genes and explored a four immune-related lncRNA signature that could serve as a novel potential biomarker of EC.

Integrated Analysis of Immune-Related Genes in High-Risk Neuroblastoma

2020 ◽  
Author(s):  
FengLing Shao ◽  
Zhenni Wang ◽  
Shan Wang
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Clinical Characteristics ◽  
Roc Analysis ◽  
Risk Group ◽  
High Risk Group ◽  
Data Sets ◽  
Qrt Pcr ◽  
Kaplan Meier ◽  
Immune Related Genes

Abstract BackgroundDue to the extremely high mortality rate of children with high-risk Neuroblastoma (NB), there is an urgent need for new indicators to further classify children in the high-risk group for more precise treatment. The purpose of our research is to explore the immune-related genes in NB in the high-risk group, and to further identify and develop a prognostic nomogram based on immune IRG signatures. MethodsThrough bioinformatics analysis to explore the abnormal expression of immune-related genes in the high-risk group. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related mRNA. The accuracy of the risk score is evaluated by Kaplan-Meier method and receiver operating characteristics (ROC) analysis, which is used to build a nomogram in combination with other clinical characteristics.. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to detect the accuracy of our results. ResultsA total of 127 common differentially expressed immune genes were found between the high-risk group and the non-high-risk group of the two data sets. Four immune-related genes (IRG) related to prognosis were identified and a risk score was established. Kaplan–Meier survival analysis and time-dependent ROC analysis showed that the 4-IRG risk score has satisfactory predictive potential and achieved consistency in the verification of external data sets. Subsequently, the risk score combined with clinical characteristics draws a nomogram. The reliability of the results was verified on 29 cases of NB tissues by qRT-PCR. ConclusionsOverall, we have developed a powerful multi-gene classifier that can effectively classify NB patients into low- and high-risk groups with poor prognosis, and draw a nomogram for children in the high-risk group. This feature can help select high-risk patients who need more aggressive adjuvant target therapy or immunotherapy.

scholarly journals Bioinformatics Analysis Combined with Experiments to Explore Neuroblastoma Prognostic Indicators Based on Immune-related Genes.

2020 ◽  
Author(s):  
FengLing Shao ◽  
Zhenni Wang ◽  
Shan Wang
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Roc Analysis ◽  
Bioinformatics Analysis ◽  
Risk Group ◽  
High Risk Group ◽  
Data Sets ◽  
Qrt Pcr ◽  
Kaplan Meier ◽  
Immune Related Genes

Abstract Background：Due to the extremely high mortality rate of children with high-risk Neuroblastoma (NB), there is an urgent need for new indicators to further classify children in the high-risk group for more precise treatment. The purpose of our research is to explore the immune-related genes in NB in the high-risk group, and to further identify and develop a prognostic nomogram based on immune IRG signatures. Methods：Through bioinformatics analysis to explore the abnormal expression of immune-related genes in the high-risk group. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related mRNA. The accuracy of the risk score is evaluated by Kaplan-Meier method and receiver operating characteristics (ROC) analysis, which is used to build a nomogram in combination with other clinical characteristics.. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to detect the accuracy of our results. Results：A total of 127 common differentially expressed immune genes were found between the high-risk group and the non-high-risk group of the two data sets. Four immune-related genes (IRG) related to prognosis were identified and a risk score was established. Kaplan–Meier survival analysis and time-dependent ROC analysis showed that the 4-IRG risk score has satisfactory predictive potential and achieved consistency in the verification of external data sets. Subsequently, the risk score combined with clinical characteristics draws a nomogram. The reliability of the results was verified on 29 cases of NB tissues by qRT-PCR. Conclusions：Overall, we have developed a powerful multi-gene classifier that can effectively classify NB patients into low- and high-risk groups with poor prognosis, and draw a nomogram for children in the high-risk group. This feature can help select high-risk patients who need more aggressive adjuvant target therapy or immunotherapy.

Prospective Multicenter Validation Confirms the Prognostic Superiority of the Endometrial Carcinoma Prognostic Index in International Federation of Gynecology and Obstetrics Stage 1 and 2 Endometrial Carcinoma

2003 ◽  
Vol 21 (22) ◽  
pp. 4214-4221 ◽  
Author(s):  
Jan P.A. Baak ◽  
Wim Snijders ◽  
Bianca van Diermen ◽  
Paul J. van Diest ◽  
Fred W. Diepenhorst ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Prognostic Value ◽  
Dna Ploidy ◽  
Prognostic Index ◽  
Prognostic Indicator ◽  
International Federation ◽  
Kaplan Meier ◽  
Gynecology And Obstetrics ◽  
Stage 1 ◽  
Endometrial Carcinomas

Purpose: To validate the prognostic value of the endometrial carcinoma prognostic index (ECPI; combined myometrium invasion, flow cytometric DNA ploidy, and morphometric mean shortest nuclear axis [MSNA]) versus classic prognosticators. Patients and Methods: Prospective multicenter ECPI analysis was conducted in 463 endometrial carcinomas with a median of 6.5 years (range, 1 to 10 years) follow-up, review of pathology features, and univariate (Kaplan-Meier) and multivariate (Cox) analyses. Results: Initial routine and review diagnoses varied considerably (invasion depth, 11%; type, 20%; grade, 34%; vessel invasion, 72%); the review diagnoses were stronger prognostically. In International Federation of Gynecology and Obstetrics stage 1 (after histopathologic examination; pFIGO-1; n = 372; 38 deaths occurred as a result of disease [10.2%]), DNA ploidy was prognostic in hysterectomies (P < .00001) but not in curettages (P = .06). ECPI was a stronger prognostic indicator than other features. ECPI, MSNA, and DNA ploidy were also prognostic in pFIGO-1B and -1C subgroups. Multivariate analysis in pFIGO-1 showed that uterine MSNA ≤ versus > 7.93 μm (hazard ratio [HR], 3.4) and grade (as 1 + 2 v 3; HR, 2.6) added to the ECPI (HR, 32), but only in patients with an unfavorable ECPI of > 0.87. Adjuvant radiotherapy was not an independent prognostic factor in any of the subgroups. In pFIGO-2 (n = 46), ECPI, DNA-ploidy, and age (≤ 64, > 64 years) were significant. In FIGO-3 (n = 31) and FIGO-4 (n = 14), none of the classic or other features analyzed was of prognostic value, which explains why in previous studies using different mixtures of FIGO stages, DNA ploidy prognostic results varied. Conclusion: In endometrial carcinoma, DNA-ploidy is prognostic in hysterectomy and not in curettage samples. The ECPI is prognostically much stronger than the classic features widely used for therapy triage in pFIGO-1 and -2.

scholarly journals An Immune-related Signature Predicted Survival in Patients With Kidney Papillary Cell Carcinoma

2021 ◽  
Author(s):  
Shen junwen ◽  
Wang rongjiang ◽  
Chen yu ◽  
Fang zhihai ◽  
Tang jianer ◽  
...  
Keyword(s):  
Cell Carcinoma ◽  
Roc Analysis ◽  
Clinical Information ◽  
Training Set ◽  
Test Set ◽  
Kaplan Meier ◽  
Rnaseq Data ◽  
Differential Expression Genes ◽  
Cox Analysis ◽  
Immune Related Genes

Abstract Immune-related genes are important factors in tumor progression. The main aim of this study was to identify the immune-related genes in Kidney papillary cell carcinoma (pRCC) patients. We downloaded RNAseq data and clinical information of pRCC patients from the TCGA database and retrieved the immune-related genes list from Immport. From the data, we mined out 2468 differential expression genes (DEGs) and 183 immune-related DEGs. Four hub DEGs (NTS, BIRC5, ELN, and CHGA) were identified after conducting Cox analysis and LASSO analysis. Moreover, the prognostic value of the signature based on 4 hub DEGs was verified using Kaplan-Meier analysis (P=0.0041 in the training set and p=0.021 in the test set) and ROC analysis (AUC: 0.957 in 1 year, 0.965 in 2 years, and 0.901 in 3 years in the training set, and 0.963 in 1 year, 0.898 in 2 years, and 0.742 in 3 years in the test set). Furthermore, we found that the high-risk score group had a higher percentage of B cells in the immune component, a higher expression of immune-related genes (CTLA4, LAG3, PDCD1LG2, and TIGIT), and a better immunotherapy response.

scholarly journals Enabled homolog shown to be a potential biomarker and prognostic indicator for breast cancer by bioinformatics analysis

2019 ◽  
Vol 41 (4) ◽  
pp. E186-E195 ◽  
Author(s):  
Qiang Li ◽  
Yan-Ling Su ◽  
Min Zeng ◽  
Wei-Xi Shen
Keyword(s):  
Breast Cancer ◽  
Cancer Cell ◽  
System Development ◽  
Cancer Cell Line ◽  
Prognostic Indicator ◽  
Nervous System Development ◽  
Luminal B ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Potential Biomarker

Background: Human enabled homolog (ENAH; also known as human ortholog of mammalian enabled, hMENA) is a member of the enabled/vasodilator-stimulated phosphor protein family that regulates fibroblast movement and nervous system development. The ENAH over-expression promotes breast cancer (BC) cell invasion and metastasis. Methods: We studied ENAH mRNA expression in various tumors and normal tissues using the ONCOMINE database, and in an array of cancer cell lines using Cancer Cell Line Encyclopedia data. We also investigated the prognostic value of ENAH expression in patients with BC using Kaplan-Meier plots. Results: Compared with normal tissues, ENAH expression levels were markedly elevated in BC. We identified a correlation between low ENAH and superior relapse-free survival (RFS) of patients with BC; specifically, those with ER(-), HER-2(+), Grade 3 and wild-type TP53 subtypes. Additionally, a correlation was detected between low ENAH and prolonged overall survival of patients with luminal B disease. Conclusion: ENAH is a potential biomarker and important prognostic factor in BC.

scholarly journals Identification of MicroRNAs as Potential Biomarker for Gastric Cancer by System Biological Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Wenying Yan ◽  
Shouli Wang ◽  
Zhandong Sun ◽  
Yuxin Lin ◽  
Shengwei Sun ◽  
...  
Keyword(s):  
Roc Analysis ◽  
Mortality Rates ◽  
Literature Mining ◽  
High Morbidity ◽  
Rna Seq ◽  
Diagnostic Biomarkers ◽  
The Public ◽  
Potential Biomarker ◽  
First Time ◽  
Potential Biomarkers

Gastric cancers (GC) have the high morbidity and mortality rates worldwide and there is a need to identify sufficiently sensitive biomarkers for GC. MicroRNAs (miRNAs) could be promising potential biomarkers for GC diagnosis. We employed a systematic and integrative bioinformatics framework to identify GC-related microRNAs from the public microRNA and mRNA expression dataset generated by RNA-seq technology. The performance of the 17 candidate miRNAs was evaluated by hierarchal clustering, ROC analysis, and literature mining. Fourteen have been found to be associated with GC and three microRNAs (miR-211, let-7b, and miR-708) were for the first time reported to associate with GC and may be used for diagnostic biomarkers for GC.

scholarly journals A Novel lncRNA Panel Related to Ferroptosis, Tumor Progression, and Microenvironment is a Robust Prognostic Indicator for Glioma Patients

2021 ◽  
Vol 9 ◽  
Author(s):  
Yikang He ◽  
Yangfan Ye ◽  
Wei Tian ◽  
Huaide Qiu
Keyword(s):  
Tumor Progression ◽  
Cox Regression ◽  
Expression Profiles ◽  
Predictive Performance ◽  
Roc Curves ◽  
Prognostic Indicator ◽  
High Risk Group ◽  
Lasso Regression ◽  
Qrt Pcr ◽  
Kaplan Meier

Objective: To establish a lncRNA panel related to ferroptosis, tumor progression, and microenvironment for prognostic estimation in patients with glioma.Methods: LncRNAs associated with tumor progression and microenvironment were screened via the weighted gene co-expression network analysis (WGCNA). Overlapped lncRNAs highlighted in WGCNA, related to ferroptosis, and incorporated in Chinese Glioma Genome Atlas (CGGA) were identified as hub lncRNAs. With expression profiles of the hub lncRNA, we conducted the least absolute shrinkage and selection operator (LASSO) regression and built a ferroptosis-related lncRNA signature to separate glioma patients with distinct survival outcomes. The lncRNA signature was validated in TCGA, the CGGA_693, and CGGA_325 cohorts using Kaplan-Meier survival analysis and ROC curves. The ferroptosis-related lncRNA panel was validated with 15 glioma samples using quantitative real-time PCR (qRT-PCR). Multivariate Cox regression was performed, and a nomogram was mapped and validated. Immune infiltration correlated to the signature was explored using TIMER and CIBERSORT algorithms.Results: The present study identified 30 hub lncRNAs related to ferroptosis, tumor progression, and microenvironment. With the 30 hub lncRNAs, we developed a lncRNA signature with distinct stratification of survival chance in patients with glioma in two independent cohorts (HRs&gt;1, p &lt; 0.05). The lncRNA signature revealed a panel of 14 lncRNAs, i.e., APCDD1L-AS1, H19, LINC00205, LINC00346, LINC00475, LINC00484, LINC00601, LINC00664, LINC00886, LUCAT1, MIR155HG, NEAT1, PVT1, and SNHG18. These lncRNA expressions were validated in clinical specimens using qRT-PCR. Robust predictive accuracies of the signature were present across different datasets at multiple timepoints. With univariate and multivariate regressions, we demonstrated that the risk score based on the lncRNA signature is an independent prognostic indicator after clinical factors were adjusted. A nomogram was constructed with these prognostic factors, and it has demonstrated decent classification and accuracy. Additionally, the signature-based classification was observed to be correlated with multiple clinical characteristics and molecular subtypes. Further, extensive immune cells were upregulated in the high-risk group, such as CD8+ T cell, neutrophil, macrophage, and myeloid dendritic cell, indicating increased immune infiltrations.Conclusion: We established a novel ferroptosis-related lncRNA signature that could effectively stratify the prognosis of glioma patients with adequate predictive performance.

scholarly journals RNA-Seq Profiling Revealed PBMC RNA as Potential Biomarker for Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Zhiyi Han ◽  
Wenxing Feng ◽  
Rui Hu ◽  
Qinyu Ge ◽  
Wenfeng Ma ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mononuclear Cells ◽  
Malignant Tumors ◽  
High Morbidity ◽  
Healthy Controls ◽  
Rna Seq ◽  
Sequencing Data ◽  
Qrt Pcr ◽  
Potential Biomarker ◽  
Response Expression

Abstract Background: Hepatocellular carcinoma with extremely high morbidity and mortality is one of the most common malignant tumors. Although many existing studies focus on the study of its biomarkers, little information has been released on the PBMC RNA profile of hepatocellular carcinoma. Methods: We tried to make a profile throughout this analysis with the expression of Peripheral Blood Mononuclear Cells (PBMCs) RNA by using RNA-seq technology and compared the transcriptome between hepatocellular carcinoma patients and the healthy controls. 17 patients and 17 healthy controls involved in this study, PBMCs RNA were sequenced. The sequencing data were analyzed with bioinformatics tools and qRT-PCR was used for selected differential expressed gene validation. Results: It is showed that 1578 dysregulated genes found including 1334 upregulated genes and 244 downregulated genes. GO enrichment and KEGG studies showed that hepatocellular carcinoma is a closely linked source of the most differentially expressed genes (DEGs), implicated in the immune response. Expression of the 6 selected genes (SELENBP1, SLC4A1, SLC26A8, HSPA8P4, CALM1, and RPL7p24) were confirmed by qRT-PCR, and higher sensitivity and specificity obtained by ROC analysis of the 6 genes. CALM1 was found gradually decreasing along with the tumor enlarged. Conclusions: It is suggested potential biomarker for diagnosis of hepatocellular carcinomas. This study provided new perspectives for liver cancer development and possible future successful clinical diagnosis.

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