scholarly journals Identification of key survival genes of the tumor microenvironment and immune infiltration in head and neck squamous cell carcinoma

2021 ◽  
Author(s):  
Min Wang ◽  
Tao Lu ◽  
Yanshi Li ◽  
Min Pan ◽  
Zhihai Wang ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Tumor Microenvironment ◽  
Head And Neck ◽  
Stromal Cells ◽  
Survival Data ◽  
Expression Profiles ◽  
Critical Role ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Kaplan Meier

Abstract Background: Head and neck cancer (HNC) are highly aggressive solid tumors with poor prognoses. The tumor microenvironment (TME) plays a critical role in angiogenesis, invasion, and metastasis of HNC. In the TME, immune and stromal cells influence tumor initiation, response, and therapy. Our study aimed to evaluate the progression and prognosis of HNC by analyzing the key genes involved in immunization and stromal cells. Methods: Gene expression profiles, demographics, and survival data were downloaded from the TCGA database. Patients with HNC were divided into high immune/stromal score groupss or low immune/stromal score groups based on the ESTIMATE algorithm. Differentially expressed genes (DEGs) were identified via functional enrichment analysis and protein-protein interaction networks, and survival analysis based on DEGs was also performed.Results: A total of 522 patients with HNC were enrolled for analysis. The average age was 60.87, and one-third of the patients were HPV-positive. Kaplan-Meier survival analysis showed that patients' median survival time in the low-score group was shorter than that of the high-score group (625 vs. 680 days, log-rank, p = 0.1716). According to immune scores, 925 genes were upregulated, and 72 genes were downregulated in the high-score group compared with the low-score group. Top Gene Ontology terms identified that T-cell costimulation, regulation of immune response, and the external side of the plasma membrane were the most involved pathways. Moreover, Kaplan-Meier analysis revealed that 480 DEGs were upregulated in the high-immune scores group, and a total of 126 DEGs were significantly associated with poor survival. Besides, we identified the hub genes of DEGs through protein-protein interactions and found that PTPRC, CD247, and CD4 are associated with immune infiltration and all-cause mortality.Conclusions: We identified a series of TME‐related genes significantly associated with overall mortality; this information is crucial for further understanding the role of TME and immune infiltration in the prognosis of HNC.

scholarly journals COL5A3 is a prognostic biomarker and correlated with immune infiltrates in pancreatic cancer

2021 ◽  
Author(s):  
Yongjie Li ◽  
Min Zeng ◽  
Ting Wang ◽  
Feng Jiang
Keyword(s):  
Pancreatic Cancer ◽  
Roc Curve ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
High Expression ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Tumor Tissues

Abstract Background Pancreatic cancer is a malignant tumor of digestive system with high fatality rate, and its prognosis is very poor. Type Ⅴ collagen α3 (COL5A3) is highly expressed in a variety of tumor tissues, but its prognostic value and immune infiltration in pancreatic cancer are still unclear. Therefore, we evaluated the prognostic role of COL5A3 in pancreatic cancer and its correlation with immune infiltration. Methods The transcriptional expression profiles of COL5A3 in pancreatic cancer and normal tissues were downloaded from the Cancer Genome Atlas (TCGA). In the GEO (Gene expression omnibus) dataset (GSE16515), we compared the expression of COL5A3 in normal and tumor tissues. The expression of COL5A3 protein was evaluated by the human protein atlas (THPA). The effect of COL5A3 on survival was evaluated by Kaplan-Meier method. Receiver operating characteristic (ROC) curve was used to distinguish pancreatic cancer from paracancerous normal tissues. Protein-protein interaction (PPI) network was constructed by the STRING. Use the "ClusterProfiler" package for functional enrichment analysis. Tumor immune estimation resource (TIMER) and tumor-immune system interaction database (TISIDB) were used to determine the relationship between COL5A3mRNA expression and immune infiltration. Results Compared with normal tissues, COL5A3 is highly expressed in pancreatic cancer tissues. The high expression of COL5A3 is related to the poor clinicopathological features and poor prognosis of pancreatic cancer. Kaplan-Meier survival analysis showed that the prognosis of pancreatic cancer patients with high expression of COL5A3 was worse than that of patients with low expression of COL5A3. ROC curve shows that COL5A3 has high sensitivity and specificity in the diagnosis of pancreatic cancer. Correlation analysis showed that the expression of COL5A3mRNA was related to immune cell infiltration. Conclusion This study reveals for the first time that COL5A3 may be a new prognostic biomarker related to immune infiltration and provide a new target for the diagnosis and treatment of pancreatic cancer.

scholarly journals Identification of Potential Therapeutic Targets Among CXC Chemokines in Breast Tumor Microenvironment Using Integrative Bioinformatics Analysis

2018 ◽  
Vol 45 (5) ◽  
pp. 1731-1746 ◽  
Author(s):  
Erbao Chen ◽  
Xuan Qin ◽  
Ke Peng ◽  
Xiaojing Xu ◽  
Wei Li ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Survival Data ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Tumor Development ◽  
Mrna Levels ◽  
Kaplan Meier ◽  
Tumor Tissues ◽  
Precision Therapy ◽  
Kaplan Meier Plotter

Background/Aims: Breast cancer is a common cause of cancer mortality throughout the world. The cross-talk between cancer cells and interstitial cells exerts significant effects on neoplasia and tumor development and is modulated in part by chemokines. CXC is one of four chemokine families involved in mediating survival, angiogenesis, and immunosensitization by chemoattracting leukocytes, and it incentivizes tumor cell growth, invasion and metastasis in the tumor microenvironment. However, the differential expression profiles and prognostic values of these chemokines remains to be elucidated. Methods: In this study, we compared transcriptional CXC chemokines and survival data of patients with breast carcinoma (BC) using the ONCOMINE dataset, Kaplan-Meier Plotter, TCGA and cBioPortal. Results: We discovered increased mRNA levels for CXCL8/10/11/16/17, whereas mRNA expression of CXCL1/2/3/4/5/6/7/12/14 was lower in BC patients compared to non-tumor tissues. Kaplan-Meier plots revealed that high mRNA levels of CXCL1/2/3/4/5/6/7/12/14 correlate with relapse-free survival (RFS) in all types of BC patients. Conversely, high CXCL8/10/11 predicted worse RFS in BC patients. Significantly, high transcription levels of CXCL9/12/13/14 conferred an overall survival (OS) advantage in BC patients, while high levels of CXCL8 demonstrated shorter OS in all BC sufferers. Conclusions: Integrative bioinformatics analysis suggests that CXCL8/12/14 are potential suitable targets for precision therapy in BC patients compared to other CXC chemokines.

scholarly journals COL5A3 is a Prognostic Biomarker and Correlated with Immune Infiltrates in Pancreatic Cancer

2021 ◽  
Author(s):  
Yongjie Li ◽  
Min Zeng ◽  
Ting Wang ◽  
Feng Jiang
Keyword(s):  
Pancreatic Cancer ◽  
Roc Curve ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
High Expression ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Tumor Tissues

Abstract Pancreatic cancer is a malignant tumor of digestive system with high fatality rate, and its prognosis is very poor. Type Ⅴ collagen α3 (COL5A3) is highly expressed in a variety of tumor tissues, but its prognostic value and immune infiltration in pancreatic cancer are still unclear. Therefore, we evaluated the prognostic role of COL5A3 in pancreatic cancer and its correlation with immune infiltration. The transcriptional expression profiles of COL5A3 in pancreatic cancer and normal tissues were downloaded from the Cancer Genome Atlas (TCGA). In the GEO (Gene expression omnibus) dataset (GSE16515), we compared the expression of COL5A3 in normal and tumor tissues. The expression of COL5A3 protein was evaluated by the human protein atlas (THPA). The effect of COL5A3 on survival was evaluated by Kaplan-Meier method. Receiver operating characteristic (ROC) curve was used to distinguish pancreatic cancer from paracancerous normal tissues. Protein-protein interaction (PPI) network was constructed by the STRING. Use the "ClusterProfiler" package for functional enrichment analysis. Tumor immune estimation resource (TIMER) and tumor-immune system interaction database (TISIDB) were used to determine the relationship between COL5A3 mRNA expression and immune infiltration. Compared with normal tissues, COL5A3 is highly expressed in pancreatic cancer tissues. The high expression of COL5A3 is related to the poor clinicopathological features and poor prognosis of pancreatic cancer. Kaplan-Meier survival analysis showed that the prognosis of pancreatic cancer patients with high expression of COL5A3 was worse than that of patients with low expression of COL5A3. ROC curve shows that COL5A3 has high sensitivity and specificity in the diagnosis of pancreatic cancer. Correlation analysis showed that the expression of COL5A3 mRNA was related to immune cell infiltration. This study reveals for the first time that COL5A3 may be a new prognostic biomarker related to immune infiltration and provide a new target for the diagnosis and treatment of pancreatic cancer.

scholarly journals Identification of the Immune-Related Genes in Tumor Microenvironment That Associated With the Recurrence of Head and Neck Squamous Cell Carcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Liu Chengcheng ◽  
Qi Wenwen ◽  
Gong Ningyue ◽  
Zhu Fangyuan ◽  
Xu Runtong ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Head And Neck ◽  
Squamous Cell ◽  
Immune Cells ◽  
Functional Enrichment ◽  
Prognostic Scores ◽  
Expression Data ◽  
Immune Infiltration ◽  
Ppi Networks ◽  
Immune Related Genes

Head and neck squamous cell carcinomas (HNSCC) are still one of the most common malignant tumors in China, with a high metastasis rate and poor prognosis. The tumor immune microenvironment can affect the occurrence, development and prognosis of tumors, but the underlying mechanism is still unclear. In this study, we tried to describe the correlation between the recurrence of HNSCC and the tumor microenvironment (TME). The expression data [estimate the level of tumor stromal and immune infiltration, expression data (ESTIMATE)] algorithm was used to identify and estimate highly correlated stromal cells, immune cells, and prognostic scores in 116 samples of head and neck cancer patients from The Cancer Genome Atlas (TCGA) dataset. The functional enrichment analysis and protein-protein interaction (PPI) networks of differential expressed genes (DEGs) were constructed. Subsequently, the abundance of various infiltrating immune cells was estimated with the tumor immune estimation resource (TIMER) and the infiltration pattern of immune cells were explored in HNSCC. A total of 407 immune-related genes were identified to involve in the TME. We found that CCR5, CD3E, CD4, and HLA -DRB1 were the most obvious DEGs and the dendritic cells (DCs) showed the highest abundance in the TME of HNSCC. In addition, the unsupervised cluster analysis determined 10 clusters of immune infiltration patterns, and indicated that immune infiltrated CD4 + T and B cells may be related to the prognosis of HNSCC. In conclusion, our research determined the list of immune genes and immune infiltrating cells related to the prognosis of HNSCC, and provided a perspective for HNSCC evolution, anti-tumor drugs selection, and drug resistance research.

scholarly journals CCTs as new biomarkers for the prognosis of head and neck squamous cancer

Open Medicine ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 672-688
Author(s):  
Yanbo Dong ◽  
Siyu Lu ◽  
Zhenxiao Wang ◽  
Liangfa Liu
Keyword(s):  
Head And Neck ◽  
Survival Data ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Advanced Tumor Stage ◽  
Expression Levels ◽  
T Complex ◽  
Advanced Tumor ◽  
Squamous Cancer

AbstractThe chaperonin-containing T-complex protein 1 (CCT) subunits participate in diverse diseases. However, little is known about their expression and prognostic values in human head and neck squamous cancer (HNSC). This article aims to evaluate the effects of CCT subunits regarding their prognostic values for HNSC. We mined the transcriptional and survival data of CCTs in HNSC patients from online databases. A protein–protein interaction network was constructed and a functional enrichment analysis of target genes was performed. We observed that the mRNA expression levels of CCT1/2/3/4/5/6/7/8 were higher in HNSC tissues than in normal tissues. Survival analysis revealed that the high mRNA transcriptional levels of CCT3/4/5/6/7/8 were associated with a low overall survival. The expression levels of CCT4/7 were correlated with advanced tumor stage. And the overexpression of CCT4 was associated with higher N stage of patients. Validation of CCTs’ differential expression and prognostic values was achieved by the Human Protein Atlas and GEO datasets. Mechanistic exploration of CCT subunits by the functional enrichment analysis suggests that these genes may influence the HNSC prognosis by regulating PI3K-Akt and other pathways. This study implies that CCT3/4/6/7/8 are promising biomarkers for the prognosis of HNSC.

scholarly journals Genomic Expression Profiling of Colorectal Cancer in Silico

2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Hub Genes ◽  
Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

scholarly journals Identification of Tumor Microenvironment-Related Genes in Kidney Renal Clear Cell Carcinoma Patients via Bioinformatic Analysis

2021 ◽  
Author(s):  
Rongjiong Zheng ◽  
Yaosen SHao ◽  
Mingming Wang ◽  
Yeli Tang ◽  
Meiling Hu
Keyword(s):  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Renal Clear Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment

Abstract BackgroundTumor microenvironment has been implicated in the development and progression of cancers. However, the prognostic significance of tumor microenvironment-related genes in kidney renal clear cell carcinoma (KIRC) remains unclear. MethodsIn this study, we obtained and analyzed gene expression profiles from The Cancer Genome Atlas database. Stromal and immune scores were calculated based on the ESTIMATE algorithm. ResultsIn the discovery series of 537 patients, we identified a list of differentially expressed genes which was significantly associated with prognosis in KIRC patients. Protein-protein interaction networks and functional enrichment analysis were both performed, indicating that these identified genes were related to the immune response. ConclusionsThe tumor microenvironment-related genes could serve as the potential biomarkers for KIRC.

scholarly journals Integrated analysis identifies AQP9 correlates with immune infiltration and acts as a prognosticator in multiple cancers

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Xiaohong Liu ◽  
Qian Xu ◽  
Zijing Li ◽  
Bin Xiong
Keyword(s):  
Survival Data ◽  
Integrated Analysis ◽  
Immune Gene ◽  
Gene Markers ◽  
Lung Cancers ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Aquaporin 9 ◽  
Infiltrating Cells ◽  
The Relationship

AbstractAquaporin 9 (AQP9), as an aquaglyceroporin, is expressed in many immune cells and plays important role in tumor initiation and progression. However, the relationship between AQP9 and tumor-infiltrating cells, and its prognostic value in cancers still require comprehensive understanding. Herein, we aimed to elucidate the correlations of AQP9 with prognosis and immune infiltration levels in diverse cancers. We detected the expression and survival data of AQP9 through Oncomine, TIMER, Kaplan–Meier Plotter and PrognoScan databases. The correlations between AQP9 and immune infiltrates were analyzed in TIMER database. Our results found that high AQP9 expression was significantly correlated with worse prognosis in breast, colon and lung cancers, while predicted better prognosis in gastric cancer. Moreover, AQP9 had significant association with various immune infiltrating cells including CD8+ and CD4+ T cells, neutrophils, macrophages and dendritic cells (DCs), and diverse immune gene markers in BRCA, COAD, LUAD, LUSC and STAD. AQP9 was also significantly correlated with the regulation of tumor associated macrophages (TAM). These results indicate that AQP9 can play as a significant biomarker to determine the prognosis and the immune infiltrating levels in different cancers. It might also contribute to the development of the immunotherapy in breast, colon, lung and gastric cancers.

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.

scholarly journals The what, when and how of orthopaedic registers: an introduction into register-based research

2019 ◽  
Vol 4 (6) ◽  
pp. 337-343 ◽  
Author(s):  
Claus Varnum ◽  
Alma Bečić Pedersen ◽  
Per Hviid Gundtoft ◽  
Søren Overgaard
Keyword(s):  
Survival Analysis ◽  
Selection Bias ◽  
Survival Data ◽  
Cox Regression ◽  
Research Question ◽  
Cox Regression Analysis ◽  
Information Bias ◽  
Kaplan Meier ◽  
Routinely Collected Health Data ◽  
Competing Events

Establishment of orthopaedic registers started in 1975 and many registers have been initiated since. The main purpose of registers is to collect information on patients, implants and procedures in order to monitor and improve the outcome of the specific procedure. Data validity reflects the quality of the registered data and consists of four major aspects: coverage of the register, registration completeness of procedures/patients, registration completeness of variables included in the register and accuracy of registered variables. Survival analysis is often used in register studies to estimate the incidence of an outcome. The most commonly used survival analysis is the Kaplan–Meier survival curves, which present the proportion of patients who have not experienced the defined event (e.g. death or revision of a prosthesis) in relation to the time. Depending on the research question, competing events can be taken into account by using the cumulative incidence function. Cox regression analysis is used to compare survival data for different groups taking differences between groups into account. When interpreting the results from observational register-based studies a number of factors including selection bias, information bias, chance and confounding have to be taken into account. In observational register-based studies selection bias is related to, for example, absence of complete follow-up of the patients, whereas information bias is related to, for example, misclassification of exposure (e.g. risk factor of interest) or/and outcome. The REporting of studies Conducted using Observational Routinely-collected Data guidelines should be used for studies based on routinely-collected health data including orthopaedic registers. Linkage between orthopaedic registers, other clinical quality databases and administrative health registers may be of value when performing orthopaedic register-based research. Cite this article: EFORT Open Rev 2019;4 DOI: 10.1302/2058-5241.4.180097

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