scholarly journals Comprehensive analysis of genomic mutation signature and tumor mutation burden for prognosis of intrahepatic cholangiocarcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rui Zhang ◽  
Qi Li ◽  
Jialu Fu ◽  
Zhechuan Jin ◽  
Jingbo Su ◽  
...  
Keyword(s):  
Intrahepatic Cholangiocarcinoma ◽  
Cox Regression ◽  
Tnm Stage ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Tumor Mutation Burden ◽  
Kaplan Meier ◽  
Mutation Burden ◽  
Significant Difference ◽  
Genomic Mutation

Abstract Background Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy of the biliary tract. Analysis of somatic mutational profiling can reveal new prognostic markers and actionable treatment targets. In this study, we explored the utility of genomic mutation signature and tumor mutation burden (TMB) in predicting prognosis in iCCA patients. Methods Whole-exome sequencing and corresponding clinical data were collected from the ICGC portal and cBioPortal database to detect the prognostic mutated genes and determine TMB values. To identify the hub prognostic mutant signature, we used Cox regression and Lasso feature selection. Mutation-related signature (MRS) was constructed using multivariate Cox regression. The predictive performances of MRS and TMB were assessed using Kaplan–Meier (KM) analysis and receiver operating characteristic (ROC). We performed a functional enrichment pathway analysis using gene set enrichment analysis (GSEA) for mutated genes. Based on the MRS, TMB, and the TNM stage, a nomogram was constructed to visualize prognosis in iCCA patients. Results The mutation landscape illustrated distributions of mutation frequencies and types in iCCA, and generated a list of most frequently mutated genes (such as Tp53, KRAS, ARID1A, and IDH1). Thirty-two mutated genes associated with overall survival (OS) were identified in iCCA patients. We obtained a six-gene signature using the Lasso and Cox method. AUCs for the MRS in the prediction of 1-, 3-, and 5-year OS were 0.759, 0.732, and 0.728, respectively. Kaplan–Meier analysis showed a significant difference in prognosis for patients with iCCA having a high and low MRS score (P < 0.001). GSEA was used to show that several signaling pathways, including MAPK, PI3K-AKT, and proteoglycan, were involved in cancer. Conversely, survival analysis indicated that TMB was significantly associated with prognosis. GSEA indicated that samples with high MRS or TMB also showed an upregulated expression of pathways involved in tumor signaling and the immune response. Finally, the predictive nomogram (that included MRS, TMB, and the TNM stage) demonstrated satisfactory performance in predicting survival in patients with iCCA. Conclusions Mutation-related signature and TMB were associated with prognosis in patients with iCCA. Our study provides a valuable prognostic predictor for determining outcomes in patients with iCCA.

scholarly journals Comprehensive Analysis of Genomic Mutation Signature and Tumor Mutation Burden for Prognosis of Intrahepatic Cholangiocarcinoma

2020 ◽  
Author(s):  
Rui Zhang ◽  
Qi Li ◽  
Jialu Fu ◽  
Zhechuan Jin ◽  
Jingbo Su ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Signaling Pathway ◽  
Intrahepatic Cholangiocarcinoma ◽  
Cox Regression ◽  
Tnm Stage ◽  
Gene Set Enrichment Analysis ◽  
Tumor Mutation Burden ◽  
Kaplan Meier ◽  
Mutation Burden ◽  
Genomic Mutation

Abstract Background: The intrahepatic cholangiocarcinoma (iCCA) is highly lethal malignancy of biliary tract cancer. Analysis of somatic mutational profiling could help to reveal new prognostic markers and actionable targets for treatment. We aim to explore the impact of genomic mutation signature and tumor mutation burden (TMB) on prognosis of iCCA patients. Methods: The whole-exome sequencing and corresponding clinical data were collected from ICGC portal and cBioPortal database to detect the mutation prognostic genes and TMB values. To identify the hub prognostic mutant signature, Cox regression and Lasso feature selection were conducted. We built a mutation related signature (MRS) through multivariate Cox regression. The predictive performance of MRS and TMB were assessed using Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC). We performed a functional enrichment pathway analysis with gene set enrichment analysis (GSEA) for mutated genes were conducted. Moreover, on the base of MRS, TMB and TNM stage, a nomogram was constructed to visualize the prognosis of iCCA patients.Results: The mutation landscape illustrated the distributions of mutation frequencies and types on iCCA, and revealed a list of most frequent mutation genes (such as Tp53, KRAS, ARID1A, IDH1). We obtain a 6- gene signature using the Lasso and Cox method. The AUC of MRS in 1, 3, 5-year OS prediction were 0.759, 0.732, 0.728, respectively. Moreover, Kaplan-Meier analysis showed a significant difference on the prognosis of iCCA with high and low MRS score (P <0.001). Interestingly, GSEA was utilized to show several signaling pathways including MAPK signaling pathway, PI3K-AKT signaling pathway and proteoglycans in cancer. On the other hand, survival analysis indicated that TMB was significantly associated with prognosis. And GSEA indicated that samples with high MRS or TMB upregulated signaling pathways involved in tumor signaling and immune system. At last, we constructed a predictive nomogram (included MRS, TMB and TNM stage) with satisfactory performance in survival prediction. Conclusions: The mutation genes signature and TMB were associated with prognosis in patients with iCCA. Our study provides a valuable prognostic predictor for further uncovering molecular pathogenesis in iCCA.

scholarly journals Construction and Evaluation of a Tumor Mutation Burden-Related Prognostic Signature for Thyroid Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Haodong Lu ◽  
Qian Liu ◽  
Qing Chang ◽  
Jinghai Du ◽  
Chunying Zhang ◽  
...  
Keyword(s):  
Thyroid Carcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Clinicopathological Features ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Tumor Mutation Burden ◽  
Cox Regression Analysis ◽  
Survival Status ◽  
Mutation Burden

Thyroid carcinoma is a type of prevalent cancer. Its prognostic evaluation depends on clinicopathological features. However, such conventional methods are deficient. Based on mRNA, single nucleotide variants (SNV), and clinical information of thyroid carcinoma from The Cancer Genome Atlas (TCGA) database, this study statistically analyzed mutational signature of patients with this disease. Missense mutation and SNV are the most common variant classification and variant type, respectively. Next, tumor mutation burden (TMB) of sample was calculated. Survival status of high/low TMB groups was analyzed, as well as the relationship between TMB and clinicopathological features. Results revealed that patients with high TMB had poor survival status, and TMB was related to several clinicopathological features. Through analysis on DEGs in high/low TMB groups, 381 DEGs were obtained. They were found to be mainly enriched in muscle tissue development through enrichment analysis. Then, through Cox regression analysis, a 5-gene prognostic signature was established, which was then evaluated through survival curves and receiver operation characteristic (ROC) curves. The result showed that the signature was able to effectively predict patient’s prognosis and to serve as an independent prognostic risk factor. Finally, through Gene Set Enrichment Analysis (GSEA) on high/low-risk groups, DEGs were found to be mainly enriched in signaling pathways related to DNA repair. Overall, based on the TCGA-THCA dataset, we constructed a 5-gene prognostic signature through a trail of bioinformatics analysis.

scholarly journals The effect of NLRP3 on tumors based on pan-cancer research

2021 ◽  
Author(s):  
Desheng Tang ◽  
Wei Li ◽  
Zhengjie Xu ◽  
Suxiao Jiang ◽  
Kun Fang
Keyword(s):  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cox Regression ◽  
Tumor Mutation Burden ◽  
Cox Regression Analysis ◽  
Related Data ◽  
Immune Resistance ◽  
Kaplan Meier ◽  
Mutation Burden ◽  
The Relationship

Abstract NLRP3 is a multi-protein complex in cells, which can directly or indirectly affect the tumor microenvironment and participate in tumor growth, invasion and metastasis. Tumor and normal tissue gene sequencing was downloaded, clinical and mutation-related data was obtained from the TCGA website, and Kaplan-Meier and cox regression analysis was used to analyze the relationship between NLRP3 and overall survival (OS) as well as Hazard ratio (HR). The correlation between NLRP3 and tumor microenvironment score, immune cell invasion, and immune resistance indicators (tumor mutation burden and microsatellite instability) was performed. Finally, the function of NLRP3 in tumors was analyzed by GSEA.Inflammation is one of the important factors that cause cancer.

scholarly journals Prognostic and immunological value of LTB4R in pan-cancer

2021 ◽  
Vol 18 (6) ◽  
pp. 9336-9356
Author(s):  
Sidan Long ◽  
◽  
Shuangshuang Ji ◽  
Kunmin Xiao ◽  
Peng Xue ◽  
...  
Keyword(s):  
Immune Cells ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Negative Influence ◽  
Leukotriene B4 ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Significant Difference ◽  
Pan Cancer

<abstract> <sec><title>Background</title><p>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain.</p> </sec> <sec><title>Methods</title><p>We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies.</p> </sec> <sec><title>Results</title><p>In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns.</p> </sec> <sec><title>Conclusion</title><p>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer.</p> </sec> </abstract>

scholarly journals A Prognostic Autophagy-Related Long Non-coding RNA (ARlncRNA) Signature in Acute Myeloid Leukemia (AML)

2021 ◽  
Vol 12 ◽  
Author(s):  
Chunxia Zhao ◽  
Yulu Wang ◽  
Famei Tu ◽  
Shuai Zhao ◽  
Xiaoying Ye ◽  
...  
Keyword(s):  
Cox Regression ◽  
Survival Curve ◽  
Pearson Correlation ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Kaplan Meier ◽  
Non Coding Rna ◽  
Novel Biomarkers ◽  
Meier Survival Curve

BackgroundSome studies have proven that autophagy and lncRNA play important roles in AML. Several autophagy related lncRNA signatures have been shown to affect the survival of patients in some other cancers. However, the role of autophagy related lncRNA in AML has not been explored yet. Hence, this study aims to find an autophagy related lncRNA signature that can affect survival for AML patients.MethodA Pearson correlation analysis, a Kaplan–Meier survival curve, a univariate cox regression, and a multivariate cox regression were performed to establish an autophagy related lncRNA signature. A univariate cox regression, a multivariate cox regression, a Kaplan–Meier survival curve, and a ROC curve were applied to confirm if the signature is an independent prognosis for AML patients. The relationship between the signature and the clinical features was explored by using a T test. Gene Set Enrichment Analysis (GSEA) was used to investigate the potential tumor related pathways.ResultsA four-autophagy related lncRNA (MIR133A1HG, AL359715.1, MIRLET7BHG, and AL356752.1) signature was established. The high risk score based on signature was related to the short survival time of AML patients. The signature was an independent factor for the prognosis for AML patients (HR = 1.684, 95% CI = 1.324–2.142, P &lt; 0.001). The signature was correlated with age, leukocyte numbers, and FAB (M3 or non-M3). The P53, IL6/JAK/STAT3, TNF-α, INF-γ, and IL2/STAT5 pathways might contribute to the differences between the risk groups based on signature in AML.ConclusionThe four autophagy related lncRNAs and their signature might be novel biomarkers for predicting the survival of AML patients. Some biological pathways might be the potential mechanisms of the signature for the survival of AML patients.

scholarly journals The prognosis of hepatoid adenocarcinoma of the stomach: a propensity score-based analysis

2020 ◽  
Author(s):  
Kai Zhou ◽  
Anqiang Wang ◽  
Sheng Ao ◽  
Jiahui Chen ◽  
Ke Ji ◽  
...  
Keyword(s):  
Propensity Score ◽  
Cox Regression ◽  
Radical Surgery ◽  
Survival Rates ◽  
Cancer Type ◽  
Radical Gastrectomy ◽  
Hepatoid Adenocarcinoma ◽  
Kaplan Meier ◽  
Significant Difference ◽  
Propensity Matching

Abstract Background : To investigate whether there is a distinct difference in prognosis between hepatoid adenocarcinoma of the stomach ( HAS) and non-hepatoid adenocarcinoma of the stomach (non-HAS) and whether HAS can benefit from radical surgery. Methods : We retrospectively reviewed 722 patients with non-HAS and 75 patients with HAS who underwent radical gastrectomy between 3 November 2009 and 17 December 2018. Propensity score matching (PSM) analysis was used to eliminate the bias among the patients in our study. The relationships between gastric cancer type and overall survival (OS) were evaluated by the Kaplan-Meier method and Cox regression. Results : Our data demonstrate that there was no statistically significant difference in the OS between HAS and non-HAS {K-M, P=log rank (Mantel-Cox), (before PSM P=0.397); (1:1 PSM P=0.345); (1:2 PSM P=0.195)}. Moreover, there were no significant differences in the 1-, 2-, or 3-year survival rates between patients with non-HAS and patients with HAS (before propensity matching, after 1:1 propensity matching, and after 1:2 propensity matching). Conclusion : HAS was generally considered to be an aggressive gastric neoplasm, but its prognosis may not be as unsatisfactory as previously believed.

scholarly journals N6-Methyladenosine RNA Methylation Regulators Contribute to Malignant Progression and Survival Prediction in Chronic Lymphocytic Leukemia

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1738-1738 ◽  
Author(s):  
Ya Zhang ◽  
Xiaosheng Fang ◽  
Na Chen ◽  
Xiao Lv ◽  
Xueling Ge ◽  
...  
Keyword(s):  
Risk Score ◽  
Cox Regression ◽  
Lymphocytic Leukemia ◽  
Functional Enrichment ◽  
Biological Mechanism ◽  
Regression Analyses ◽  
Rna Methylation ◽  
Kaplan Meier ◽  
M6a Rna Methylation

Introduction N6-methyladenosine (m6A) RNA methylation is the most abundant epitranscriptomic modification, dynamically installed by the m6A methyltransferases (termed as "writers"), reverted by the demethylases (termed as "erasers"), and recognized by m6A binding proteins (termed as "readers"). Emerging evidence suggests that m6A RNA methylation regulates RNA stability, and participates in the pathogenesis of multiple diseases including cancers. Nevertheless, the role of m6A RNA methylation in chronic lymphocytic leukemia (CLL) remains to be unveiled. Herein, we hypothesized that m6A RNA methylation contributed to the tumorigenesis and maintenance of CLL. Moreover, the risk-prediction model integrated with the m6A regulators could serve as a novel and effective prognostic indicator in CLL. This study aimed to identify robust m6A RNA methylation-associated fingerprints for risk stratification in patients with CLL. Methods A total of 714 de novo CLL patients from 4 cohorts (China, Spain, Germany and Italy) were enrolled with informed consents. EpiQuik m6A RNA methylation colorimetric quantification assay was utilized to assess m6A RNA methylation levels. LASSO Cox regression algorithm was performed to calculate m6A RNA methylation-associated risk score (short for "m6A risk score") in R software. Besides, Kaplan-Meier survival analysis with log-rank test, univariate and multivariate Cox regression analyses and ROC curve analysis of overall survival (OS) were conduct to explore the prognostic value of m6A signature in CLL. Furthermore, RNA-seq, MeRIP-seq, Ribo-seq, functional enrichment analyses in silico and preclinical experiments ex vivo were applied to confirm the biological mechanism of the m6A regulators in CLL. Results In the present study, we performed a comprehensive analysis to dissect the role of m6A RNA methylation regulators in CLL. Compared with normal B cells from healthy donors, obvious decreased level of m6A RNA methylation was observed in primary CLL cells (p<0.01; Figure 1A). In addition, down-regulated m6A RNA methylation was also detected in CLL cell lines MEC1 and EHEB (p<0.05; Figure 1A). Then, we further investigated the association of the m6A RNA methylation regulators with clinical outcomes of CLL patients. By LASSO Cox regression analysis in 486 CLL patients, the m6A risk score was established with the coefficients of fourteen m6A regulators at the minimum lambda value of 0.00892 (Figure 1B-C). Based on the median risk score as the cut-off value, a clear distribution pattern was delineated in CLL patients (Figure 1D). Kaplan-Meier curves showed stratified high-risk patients presented significantly shorter OS versus the low-risk group (HR=4.477, p<0.001; Figure 2A). Besides, m6A risk score also predicts inferior prognosis in stable subgroup (HR=3.097, p=0.037; Figure 2B), and progressed/ relapsed subgroup (HR=3.325, p=0.001; Figure 2C). Moreover, univariate, multivariate cox regression analyses and ROC curve confirmed high m6A risk score as an independent survival predictor in CLL patients (p<0.001; Figure 2D-E). Thereafter, the clinicopathological relevance and underlying mechanism of m6A risk score were explored. Significant elevated m6A risk score was detected in patients with unfavorable treatment responses compared with stable status (p<0.001; Figure 3A). Furthermore, CLL patients with advanced Binet stage, positive ZAP-70 and unmutated IGHV present increased m6A risk score (p<0.05; Figure 3B-C). Intriguingly, we also observed the significantly negative correlation between highrisk score and 13q14 deletion, in accordance with patients' inferior outcome (p=0.047; Figure 3D). Moreover, Pearson correlation analysis, STRING interactive network and functional enrichment analyses deciphered that the m6A regulators exerted crucial roles in CLL progression potentially via modulating RNA metabolism and oncogenic pathways (Figure 4A-C). Conclusion To date, our study provides evidence for the first time that reduced m6A RNA methylation contributes to the tumorigenesis of CLL. Distinct m6A risk scoreis demonstrated as an efficient tool facilitating prognosis evaluation in CLL patients. However, validation of the signature in more independent cohorts are warranted. Further interrogations will be elucidated on the biological mechanism of m6A regulators, highlighting insights into pathogenesis and therapy strategy of CLL. Disclosures No relevant conflicts of interest to declare.

scholarly journals Identification of Epithelial–Mesenchymal Transition-Related Prognostic lncRNAs Biomarkers Associated With Melanoma Microenvironment

2021 ◽  
Vol 9 ◽  
Author(s):  
Bo Xiao ◽  
Liyan Liu ◽  
Zhuoyuan Chen ◽  
Aoyu Li ◽  
Pingxiao Wang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Epithelial Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Roc Curves ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Mesenchymal Transition ◽  
Cox Regression Analysis ◽  
Kaplan Meier

Melanoma is the most common cancer of the skin, associated with a worse prognosis and distant metastasis. Epithelial–mesenchymal transition (EMT) is a reversible cellular biological process that plays significant roles in diverse tumor functions, and it is modulated by specific genes and transcription factors. The relevance of EMT-related lncRNAs in melanoma has not been determined. Therefore, RNA expression data and clinical features were collected from the TCGA database (N = 447). Melanoma samples were randomly assigned into the training (315) and testing sets (132). An EMT-related lncRNA signature was constructed via comprehensive analyses of lncRNA expression level and corresponding clinical data. The Kaplan-Meier analysis showed significant differences in overall survival in patients with melanoma in the low and high-risk groups in two sets. Receiver operating characteristic (ROC) curves were used to measure the performance of the model. Cox regression analysis indicated that the risk score was an independent prognostic factor in two sets. Besides, a nomogram was constructed based on the independent variables. Gene Set Enrichment Analysis (GSEA) was applied to evaluate the potential biological functions in the two risk groups. Furthermore, the melanoma microenvironment was evaluated using ESTIMATE and CIBERSORT algorithms in the risk groups. This study indicates that EMT-related lncRNAs can function as potential independent prognostic biomarkers for melanoma survival.

PPM1D is Associated With Prognosis of Bladder Cancer in the Chinese Population

2020 ◽  
Author(s):  
Shuangqing Cao ◽  
Lei Zheng
Keyword(s):  
Bladder Cancer ◽  
Mrna Expression ◽  
Cox Regression ◽  
Histological Grade ◽  
Tnm Stage ◽  
Cox Regression Analysis ◽  
Relative Expression ◽  
Kaplan Meier ◽  
Normal Bladder ◽  
Cancer Tissues

Abstract Background: Present study was to investigate the relative expression and prognostic performance of protein phosphatase magnesium/manganese-dependent 1D (PPM1D) in bladder cancer.Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) assay was performed to examine the relative expression of PPM1D mRNA in bladder cancer tissues and adjacent normal bladder tissues. The associations of PPM1D mRNA expression with clinicopathological features and the prognostic value were statistically analyzed via Chi-square test, Kaplan-Meier method and Cox regression analysis.Results: In comparison to adjacent normal tissues, PPM1D mRNA expression was obviously increased in bladder cancer tissues (P<0.001). Abnormal PPM1D expression was remarkably related to histological grade (P=0.017), TNM stage (P=0.032) and lymph nodes metastasis (P=0.035). Kaplan-Meier method showed that a close relationship was found between PPM1D expression and overall survival time (P=0.000). Multivariate analysis indicated that PPM1D expression (P=0.000, HR=3.530, 95%CI: 2.001-6.228) was a promising independent predictor for the prognosis of bladder cancer patients, as well as TNM stage (P=0.042, HR=1.768, 95%CI: 1.021-3.062).Conclusion: Taken together, our data showed that the potential performance of PPM1D as a prognostic biomarker and therapeutic target of bladder cancer.

scholarly journals Integrated Analyses Identify Immune-Related Signature Associated with Qingyihuaji Formula for Treatment of Pancreatic Ductal Adenocarcinoma Using Network Pharmacology and Weighted Gene Co-Expression Network

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Xiang Qian ◽  
Zhuo Chen ◽  
Sha Sha Chen ◽  
Lu Ming Liu ◽  
Ai Qin Zhang
Keyword(s):  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Ductal Adenocarcinoma ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Kaplan Meier ◽  
Human Protein Atlas

The study aimed to clarify the potential immune-related targets and mechanisms of Qingyihuaji Formula (QYHJ) against pancreatic cancer (PC) through network pharmacology and weighted gene co-expression network analysis (WGCNA). Active ingredients of herbs in QYHJ were identified by the TCMSP database. Then, the putative targets of active ingredients were predicted with SwissTargetPrediction and the STITCH databases. The expression profiles of GSE32676 were downloaded from the GEO database. WGCNA was used to identify the co-expression modules. Besides, the putative targets, immune-related targets, and the critical module genes were mapped with the specific disease to select the overlapped genes (OGEs). Functional enrichment analysis of putative targets and OGEs was conducted. The overall survival (OS) analysis of OGEs was investigated using the Kaplan-Meier plotter. The relative expression and methylation levels of OGEs were detected in UALCAN, human protein atlas (HPA), Oncomine, DiseaseMeth version 2.0 and, MEXPRESS database, respectively. Gene set enrichment analysis (GSEA) was conducted to elucidate the key pathways of highly-expressed OGEs further. OS analyses found that 12 up-regulated OGEs, including CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 that could be utilized as potential diagnostic indicators for PC. Further, methylation analyses suggested that the abnormal up-regulation of these OGEs probably resulted from hypomethylation, and GSEA revealed the genes markedly related to cell cycle and proliferation of PC. This study identified CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 might be used as reliable immune-related biomarkers for prognosis of PC, which may be essential immunotherapies targets of QYHJ.

Sign in / Sign up

Export Citation Format

Share Document