scholarly journals Identification of PKP 2/3 as potential biomarkers of ovarian cancer based on bioinformatics and experiments

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lingling Gao ◽  
Xiao Li ◽  
Qian Guo ◽  
Xin Nie ◽  
Yingying Hao ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Signaling Pathway ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Behavior ◽  
Cell Junction ◽  
Immune Infiltration ◽  
Potential Biomarker

Abstract Background Plakophilins (PKPs) are widely involved in gene transcription, translation, and signal transduction, playing a crucial role in tumorigenesis and progression. However, the function and potential mechanism of PKP1/2/3 in ovarian cancer (OC) remains unclear. It’s of great value to explore the expression and prognostic values of PKP1/2/3 and their potential mechanisms, immune infiltration in OC. Methods The expression levels, prognostic values and genetic variations of PKP1/2/3 in OC were explored by various bioinformatics tools and databases, and PKP2/3 were selected for further analyzing their regulation network and immune infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathways (KEGG) enrichment were also conducted. Finally, the expression and prognosis of PKP2 were validated by immunohistochemistry. Results The expression level and prognosis of PKP1 showed little significance in ovarian cancer, and the expression of PKP2/3 mRNA and protein were upregulated in OC, showing significant correlations with poor prognosis of OC. Functional enrichment analysis showed that PKP2/3 and their correlated genes were significantly enriched in adaptive immune response, cytokine receptor activity, organization of cell–cell junction and extracellular matrix; KEGG analysis showed that PKP2/3 and their significantly correlated genes were involved in signaling pathways including cytokine-mediated signaling pathway, receptor signaling pathway and pathways in cancer. Moreover, PKP2/3 were correlated with lymphocytes and immunomodulators. We confirmed that high expression of PKP2 was significantly associated with advanced stage, poor differentiation and poor prognosis of OC patients. Conclusion Members of plakophilins family showed various degrees of abnormal expressions and prognostic values in ovarian cancer. PKP2/3 played crucial roles in tumorigenesis, aggressiveness, malignant biological behavior and immune infiltration of OC, and can be regarded as potential biomarker for early diagnosis and prognosis evaluation in OC.

scholarly journals SPP1 is a Prognostic Related Biomarker and Correlated With Tumor-Infiltrating Immune Cells in Ovarian Cancer

2021 ◽  
Author(s):  
Wen Gao ◽  
Sheng Yin ◽  
Haiyan Sun ◽  
Zhuyan Shao ◽  
Peipei Shi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
T Cells ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Vital Role ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Kaplan Meier ◽  
Secreted Phosphoprotein 1

Abstract Background: Secreted phosphoprotein 1 (SPP1) plays a vital role in tumor progression of some cancer types, but little is known whether it is a bystander or an actual player on driving immune infiltration in ovarian cancer.Methods: In this study, the expression of SPP1 was identified by Oncomine, GEPIA and TIMER databases, and SPP1 immumohistochemical staining analysis was assessed by The HPA database. The clinical outcomes between SPP1 expression and ovarian cancer patients were evaluated via Kaplan-Meier Plotter and PrognoScan dataset. Immune infiltration analyses were explored using TIMER and TISIDB dataset. In addition, Functional enrichment analyses were performed with Metascape and GeneMANIA database.Results: SPP1 was found overexpressed in ovarian tumor tissues and high SPP1 expression was correlated with shorter OS and PFS survivals. Particularly, elevated SPP1 expression was significantly associated with stage III ovarian cancer. Notably, SPP1 expression was positively correlated with infiltrating levels of CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells. Furthermore, SPP1 expression showed strong correlations with diverse immune hallmark sets in ovarian cancer. Of particular importance, functional enrichment analysis suggested that SPP1 strong related with immune response.Conclusions: These findings imply that SPP1 is correlated with prognosis and immune cell infiltrating, offering a new potential immunotherapeutic target in ovarian cancer.Trial registration: Not applicable.

scholarly journals PDIA4 correlates with poor prognosis and is a potential biomarker in glioma

2020 ◽  
Author(s):  
Haoyu Li ◽  
Qing Liu ◽  
Kai Xiao ◽  
Jun Yang ◽  
Chao Wu ◽  
...  
Keyword(s):  
Poor Prognosis ◽  
Molecular Mechanisms ◽  
Rna Extraction ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Protein Protein Interaction ◽  
Kaplan Meier ◽  
Potential Biomarker ◽  
Immunosuppressive Tumor Microenvironment

Abstract Background: Gliomas, characterized by aggressiveness and invasiveness, remain incurable after conventional therapies. The molecular mechanisms driving the progression and maintenance of glioma are still poorly understood.Methods: PDIA4 expression was analyzed via Gene Expression Profiling Interactive Analysis (GEPIA) which data were from TCGA and GTEx databases. We estimated the prognostic value of PDIA4 using Kaplan–Meier survival analysis and the Cox proportional hazard model. The functional enrichment analysis was done by using cluster Profiler package in R language, including gene ontology (GO) analysis comprised of cellular component (CC), molecular function (MF), and biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. In addition, correlation between PDIA4 and immunity were analyzed by Protein-protein interaction (PPI) analysis, RNA extraction and Real-time RT-PCR.Results: In this study, we identified PDIA4 was highly expressed in gliomas and closely correlated with poor prognosis. The association with IDH1 and different patterns of gliomas also indicates the potential biological processes that PDIA4 involves in the development of tumor. Mechanistically, PDIA4 interacts with multiple immunological components to promote an immunosuppressive tumor microenvironment (TME).Conclusions: Our results confirm PDIA4 is an efficient biomarker of gliomas, with implications for prognosis and therapeutic strategies.

HMMR Functions as a Prognostic Biomarker in Uterine Carcinosarcoma Identified by Comprehensive Bioinformatics Analysis

2020 ◽  
Author(s):  
Hui Sun ◽  
Li Ma ◽  
Jie Chen
Keyword(s):  
Cancer Progression ◽  
Poor Prognosis ◽  
Bioinformatics Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Normal Tissues ◽  
Potential Biomarker

Abstract BackgroundUterine carcinosarcoma (UCS) is a rare aggressive tumor with a high metastasis rate and poor prognosis. Bioinformatics analysis has been widely applied to screen and analyze genes in linkage to various types of cancer progression. This study aims to explore the molecular mechanism of UCS. MethodsFirst, transcriptional different expression data between UCS and normal samples were got from the GEPIA database. Subsequently, differentially expressed genes were analyzed through the Metascape with Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the STRING website and Cytoscape software were applied to construct the protein-protein interaction network. Finally, the top 30 genes obtained through the MCC algorithm were selected as hub genes, which was finally validated in TIMER, and UALCAN databases. ResultsA total of 1894 DEGs (579 up-regulated and 1315 down-regulated) were identified, GO and KEGG functional enrichment analysis were performed for the DEGs. The PPI network was constructed based on DEGs, and four clusters were excavated for further analysis and the top 30 genes were identified as hub genes. Our data showed that the expression of HMMR is significantly higher in UCS tissues compared to the paired normal tissues (p<0.05) and the elevated expression of HMMR is related to poor prognosis in patients with UCS (p= 0.0031). TPX2, AURKA, BRCA1 and BARD1 are essential for the function of HMMR. TPX2 and AURKA were found to be significantly higher in UCS compared to the normal tissue (p<0.05), and there was a statistically significant positive correlation between the expression of HMMR and AURKA, TPX2, BRCA1, BARD1 in UCS (p=1.08e-07, p=1.62e-05, p=2.02e-3, p=6.54e-6). ConclusionsOur study suggested that HMMR may be a potential biomarker for predicting the prognosis of UCS patients.

scholarly journals Identification of key genes and biological processes contributing to colitis associated dysplasia in ulcerative colitis

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11321
Author(s):  
Di Zhang ◽  
Pengguang Yan ◽  
Taotao Han ◽  
Xiaoyun Cheng ◽  
Jingnan Li
Keyword(s):  
Ulcerative Colitis ◽  
Mitochondrial Dysfunction ◽  
Single Gene ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Junction ◽  
Biological Processes ◽  
Hub Genes ◽  
Key Genes

Background Ulcerative colitis-associated colorectal cancer (UC-CRC) is a life-threatening complication of ulcerative colitis (UC). The mechanisms underlying UC-CRC remain to be elucidated. The purpose of this study was to explore the key genes and biological processes contributing to colitis-associated dysplasia (CAD) or carcinogenesis in UC via database mining, thus offering opportunities for early prediction and intervention of UC-CRC. Methods Microarray datasets (GSE47908 and GSE87466) were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between groups of GSE47908 were identified using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) based on DEGs between the CAD and control groups was conducted subsequently. Functional enrichment analysis was performed, and hub genes of selected modules were identified using the “clusterProfiler” R package. Single-gene gene set enrichment analysis (GSEA) was conducted to predict significant biological processes and pathways associated with the specified gene. Results Six functional modules were identified based on 4929 DEGs. Green and blue modules were selected because of their consistent correlation with UC and CAD, and the highest correlation coefficient with the progress of UC-associated carcinogenesis. Functional enrichment analysis revealed that genes of these two modules were significantly enriched in biological processes, including mitochondrial dysfunction, cell-cell junction, and immune responses. However, GSEA based on differential expression analysis between sporadic colorectal cancer (CRC) and normal controls from The Cancer Genome Atlas (TCGA) indicated that mitochondrial dysfunction may not be the major carcinogenic mechanism underlying sporadic CRC. Thirteen hub genes (SLC25A3, ACO2, AIFM1, ATP5A1, DLD, TFE3, UQCRC1, ADIPOR2, SLC35D1, TOR1AIP1, PRR5L, ATOX1, and DTX3) were identified. Their expression trends were validated in UC patients of GSE87466, and their potential carcinogenic effects in UC were supported by their known functions and other relevant studies reported in the literature. Single-gene GSEA indicated that biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to angiogenesis and immune response were positively correlated with the upregulation of TFE3, whereas those related to mitochondrial function and energy metabolism were negatively correlated with the upregulation of TFE3. Conclusions Using WGCNA, this study found two gene modules that were significantly correlated with CAD, of which 13 hub genes were identified as the potential key genes. The critical biological processes in which the genes of these two modules were significantly enriched include mitochondrial dysfunction, cell-cell junction, and immune responses. TFE3, a transcription factor related to mitochondrial function and cancers, may play a central role in UC-associated carcinogenesis.

scholarly journals The Role of Circular RNA CDR1as/ciRS-7 in Regulating Tumor Microenvironment: A Pan-Cancer Analysis

Biomolecules ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 429 ◽  
Author(s):  
Zou ◽  
Zheng ◽  
Deng ◽  
Yang ◽  
Xie ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Signaling Pathway ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Circular Rna ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction

Circular RNA CDR1as/ciRS-7 functions as an oncogenic regulator in various cancers. However, there has been a lack of systematic and comprehensive analysis to further elucidate its underlying role in cancer. In the current study, we firstly performed a bioinformatics analysis of CDR1as among 868 cancer samples by using RNA-seq datasets of the MiOncoCirc database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), CIBERSORT, Estimating the Proportion of Immune and Cancer cells (EPIC), and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were applied to investigate the underlying functions and pathways. Functional enrichment analysis suggested that CDR1as has roles associated with angiogenesis, extracellular matrix (ECM) organization, integrin binding, and collagen binding. Moreover, pathway analysis indicated that it may regulate the TGF-β signaling pathway and ECM-receptor interaction. Therefore, we used CIBERSORT, EPIC, and the ESTIMATE algorithm to investigate the association between CDR1as expression and the tumor microenvironment. Our data strongly suggest that CDR1as may play a specific role in immune and stromal cell infiltration in tumor tissue, especially those of CD8+ T cells, activated NK cells, M2 macrophages, cancer-associated fibroblasts (CAFs) and endothelial cells. Generally, systematic and comprehensive analyses of CDR1as were conducted to shed light on its underlying pro-cancerous mechanism. CDR1as regulates the TGF-β signaling pathway and ECM-receptor interaction to serve as a mediator in alteration of the tumor microenvironment.

scholarly journals Identification of novel genes and pathways in carotid atheroma using integrated bioinformatic methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Wenqing Nai ◽  
Diane Threapleton ◽  
Jingbo Lu ◽  
Kewei Zhang ◽  
Hongyuan Wu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Transforming Growth Factor ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Transforming Growth Factor Β ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Atheromatous Plaques

Abstract Atherosclerosis is the primary cause of cardiovascular events and its molecular mechanism urgently needs to be clarified. In our study, atheromatous plaques (ATH) and macroscopically intact tissue (MIT) sampled from 32 patients were compared and an integrated series of bioinformatic microarray analyses were used to identify altered genes and pathways. Our work showed 816 genes were differentially expressed between ATH and MIT, including 443 that were up-regulated and 373 that were down-regulated in ATH tissues. GO functional-enrichment analysis for differentially expressed genes (DEGs) indicated that genes related to the “immune response” and “muscle contraction” were altered in ATHs. KEGG pathway-enrichment analysis showed that up-regulated DEGs were significantly enriched in the “FcεRI-mediated signaling pathway”, while down-regulated genes were significantly enriched in the “transforming growth factor-β signaling pathway”. Protein-protein interaction network and module analysis demonstrated that VAV1, SYK, LYN and PTPN6 may play critical roles in the network. Additionally, similar observations were seen in a validation study where SYK, LYN and PTPN6 were markedly elevated in ATH. All in all, identification of these genes and pathways not only provides new insights into the pathogenesis of atherosclerosis, but may also aid in the development of prognostic and therapeutic biomarkers for advanced atheroma.

scholarly journals Long Noncoding RNA RP11-357H14.17 Plays an Oncogene Role in Gastric Cancer by Activating ATF2 Signaling and Enhancing Treg Cells

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Tang Xiaoli ◽  
Wang Wenting ◽  
Zhang Meixiang ◽  
Zuo Chunlei ◽  
Hu Chengxia
Keyword(s):  
Gastric Cancer ◽  
Noncoding Rna ◽  
Prognostic Value ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Treg Cells ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Biological Behavior

Background. Gastric cancer (GC) is one of the most common malignant tumors in the world. The potential functions and mechanisms of long noncoding RNAs (lncRNAs) in GC development are still unclear. It is of great significance to explore the prognostic value of LncRNA signatures for GC. Methods. LncRNAs differently expressed in GC and their prognostic value were studied based on The Cancer Genome Atlas (TCGA) database. The functional regulatory network and immune infiltration of RP11-357H14.17 were further studied using a variety of bioinformatics tools and databases. Results. We found that the high expression of RP11-357H14.17 was closely associated with shortened overall survival (OS) and poor prognosis in gastric cancer patients. We also found that its expression was related to clinical features including tumor volume, metastasis, and differentiation. Functional enrichment analysis revealed that RP11-357H14.17 is closely related to enhanced DNA replication and metabolism; ssGSEA analysis implied the oncogenic roles of RP11-357H14.17 was related to ATF2 signaling and Treg cell differentiation. Furthermore, we verified such link by using real-time PCR and IHC staining in human GC samples. Conclusion. We demonstrate that RP11-357H14.17 may play a crucial role in the occurrence, development, and malignant biological behavior of gastric cancer as a potential prognostic marker for gastric cancer.

scholarly journals Comprehensive Analysis of the Prognostic Value and Immune Infiltration of Calpains in Pancreatic Cancer

2021 ◽  
Author(s):  
Lan Chuan ◽  
Haoyou Tang ◽  
Sheng Liu ◽  
Lin Ma ◽  
Yifu Hou
Keyword(s):  
Pancreatic Cancer ◽  
Immune Cell ◽  
Treatment Strategies ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Surface Receptor ◽  
Cell Junction ◽  
Expression Levels ◽  
Surface Receptor

Abstract Background: Calpains (CAPNs) are intracellular calcium-activated neutral cysteine proteinases that are involved in cancer initiation, progression, and metastasis; however, their role in pancreatic cancer (PC) remains unclear. Methods: We combined data from various mainstream databases (i.e., Oncomine, GEPIA, Kaplan-Meier plotter, cBioPortal, STRING, GeneMANIA, and ssGSEA) and investigated the role of CAPNs in the prognosis of PC and immune cell infiltration.Results: Our results showed that CAPN1, 2, 4, 5, 6, 8, 9, 10, and 12 were highly expressed in PC. The expression levels of CAPN1, 5, 8, and 12 were positively correlated with the individual cancer stages. Moreover, the expression levels of CAPN1, 2, 5, and 8 were negatively correlated with the overall survival (OS) and recurrence-free survival (RFS); whereas that of CAPN10 was positively correlated with OS and RFS. We found that CAPN1, 2, 5, and 8 were correlated with tumour-infiltrating T follicular helper cells and CAPN10 with tumour-infiltrating T helper 2 cells. Functional enrichment analysis showed that the differentially expressed CAPNs (CAPN1, 2, 5, 8, and 10) are involved in axonogenesis, cell-substrate adhesion, immune response-activating cell surface receptor signalling pathway, and cell junction organisation in PC.Conclusions: These results suggested that CAPN1, 2, 5, 8, and 10 could be used as prognostic biomarkers in PC and can assist in improving individualised treatment strategies.

scholarly journals Identification of long noncoding RNA RP11-89K21.1 and RP11-357H14.17 as prognostic signature of endometrial carcinoma via integrated bioinformatics analysis

2020 ◽  
Author(s):  
Lingling Gao ◽  
Xin Nie ◽  
Wenchao Zhang ◽  
Rui Gou ◽  
Yuexin Hu ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Noncoding Rna ◽  
Growth Regulation ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Biological Behavior ◽  
Vessel Development

Abstract Background: Endometrial carcinoma (EC) is one of the most common malignant tumors in gynecology. The potential functions and mechanisms of long noncoding RNAs (lncRNAs) in the occurrence and progression of EC remains unclear. It’s meaningful to explore lncRNAs signature for providing prognostic value of EC. Methods：The differentially expressed lncRNAs and their prognostic values in EC were investigated based on The Cancer Genome Atlas (TCGA) database; the transcriptional factors (TFs), the competing endogenous RNA (ceRNA) mechanism, functional regulatory network and immune infiltration of RP11-89K21.1 and RP11-357H14.17 were further explored by various bioinformatics tools and databases. Results: We first identified high expression of RP11-89K21.1 and RP11-357H14.17 were closely associated with shorten overall survival (OS) and poor prognosis in patients with EC. We also elucidated the networks of transcription factor and co-expression genes associated with RP11-89K21.1 and RP11-357H14.17. Furthermore, the ceRNA network mechanism was successfully constructed through 2 lncRNAs (RP11-89K21.1 and RP11-357H14.17), 11 miRNAs and 183 mRNAs. Functional enrichment analysis revealed that the targeting genes of RP11-89K21.1 and RP11-357H14.17 were strongly associated with microRNAs in cancer, vessel development, growth regulation, growth factor and cell differentiation, and involved in pathways including pathways in cancer, microRNAs in cancer and apoptotic signaling pathway. Conclusions: We demonstrated for the first time that RP11-89K21.1 and RP11-357H14.17 may play crucial roles in the occurrence, development and malignant biological behavior of EC, and can be regarded as potential prognostic biomarkers for EC.

scholarly journals High PRMT6 expression Associated With Prognosis and Immune Infiltration in Glioma

2021 ◽  
Author(s):  
Yi Yang ◽  
Zhenshuang Wang ◽  
Shengrong Long ◽  
Jinhai Huang ◽  
Chengran Xu ◽  
...  
Keyword(s):  
Risk Factor ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Arginine Methyltransferase ◽  
Clinical Indicators ◽  
Immune Infiltration ◽  
Tumor Tissues ◽  
Potential Biomarker ◽  
The Relationship

Abstract Background Glioma is characterised by easy invasion of surrounding tissues, high mortality and poor prognosis. Moreover, the prognosis of glioma is getting worse and worse with the increase of grade, which is not optimistic. Therefore, biological markers for glioma are needed in clinical to detect and evaluate the situation and prognosis of patients with glioma. In many studies, we have found that the protein arginine methyltransferase 6 (PRMT6) expression is elevated in various tumors, which is associated with prognosis of patient. However, there has been no report or study on the role of PRMT6 in glioma. Methods In this study, we used various tumor-related databases to analyze the mechanism of PRMT6 in tumors, especially gliomas, from bioinformatics, and carried out relevant experimental verification with tumor tissues extracted from patients during surgery. Besides, we analyzed the relationship between PRMT6 expression and immune infiltration and immune-related cells, and discussed the possible mechanisms. We also discussed the role of PRMT6 expression in glioma from mutation, clinical indicators, enrichment analysis, and immunohistochemical results. Results PRMT6 is significantly differentially expressed in multiple tumors, which is associated with survival and prognosis. Especially in gliomas, the PRMT6 expression gradually increased with the grade increasing. Besides, PRMT6 can be used as an independent prognostic risk factor in the nomogram and has been verified in various databases. Conclusions Our results indicate that high PRMT6 expression is a potential biomarker for predicting prognosis and progression of glioma.

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