Decreased Expression of CPEB3 Predicts a Poor Prognosis in Patients with Melanoma: A Study Based on TCGA Data

Aim. Cytoplasmic polyadenylation element-binding protein 3 (CPEB3) has been acknowledged as a tumor-suppressive gene in several cancers; however, there are few reports on the clinical significance of CPEB3 in melanoma. The aim of this study was to investigate the role of CPEB3 in predicting the prognosis of melanoma patients. Methods. The association of CPEB3 expression and clinical pathologic features was performed using The Cancer Genome Atlas (TCGA) data set. The role of CPEB3 expression in prognosis was also analyzed. In addition, CPEB3 expression-related pathways were enriched by gene set enrichment analysis (GSEA). Association analysis of CPEB3 gene expression and immune infiltration was performed by ssGSEA. Results. The mRNA was significantly less in melanoma than in normal tissues ( p < 0.001 ). The decrease in CPEB3 expression in melanoma was significantly correlated with T staging ( p < 0.001 ), clinical staging ( p = 0.029 ), melanoma Clark level ( p = 0.014 ), and melanoma ulceration ( p = 0.003 ), while it was marginally significant in N staging ( p = 0.089 ). Melanoma with low CPEB3 expression was associated with worse OS (overall survival), progression-free survival (PFS), and disease-specific survival (DSS) than in that with high expression. In the univariate analysis, expression of CPEB3, melanoma ulceration, Clark level of melanoma, age, clinical stage, T stage, and N stage were correlated with OS ( p < 0.05 ). Further analysis by multivariate Cox regression showed that N stage ( p = 0.029 ), melanoma ulceration ( p = 0.004 ), and CPEB3 expression ( p < 0.001 ) were independent prognostic factors of OS in melanoma. Moreover, GSEA showed that several pathways were enriched in CPEB3, such as PD1 signaling, CTLA4 pathway, CTCF pathway, CHEMOKIN signaling, VEGF signaling, and JAK-STAT pathway. CPEB3 was significantly correlated with the infiltration level of B cells ( p < 0.001 ), T cells ( p < 0.001 ), T helper cells ( p < 0.001 ), and central memory T (Tcm) cells ( p < 0.001 ). Conclusion. CPEB3 may be a potential prognostic marker in melanoma with poor survival. Moreover, PD1 signaling, CTLA4 pathway, CTCF pathway, CHEMOKIN signaling, VEGF signaling, and JAK-STAT pathway may be the key pathway regulated by CPEB3. Moreover, the expression of CPEB3 in melanoma is related to the level of immune infiltration.

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An Immune Signature Robustly Predicts Clinical Deterioration for Hepatitis C Virus-Related Early-Stage Cirrhosis Patients

Frontiers in Medicine ◽

10.3389/fmed.2021.716869 ◽

2021 ◽

Vol 8 ◽

Author(s):

Cheng Guo ◽

Chenglai Dong ◽

Junjie Zhang ◽

Rui Wang ◽

Zhe Wang ◽

...

Keyword(s):

Hepatitis C Virus ◽

Hepatitis C ◽

Early Stage ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Calibration Plot ◽

Prognostic Signature ◽

Data Set ◽

Immune Infiltration ◽

Immune Related Genes

Hepatitis C virus (HCV)-related cirrhosis leads to a heavy global burden of disease. Clinical risk stratification in HCV-related compensated cirrhosis remains a major challenge. Here, we aim to develop a signature comprised of immune-related genes to identify patients at high risk of progression and systematically analyze immune infiltration in HCV-related early-stage cirrhosis patients. Bioinformatics analysis was applied to identify immune-related genes and construct a prognostic signature in microarray data set. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted with the “clusterProfiler” R package. Besides, the single sample gene set enrichment analysis (ssGSEA) was used to quantify immune-related risk term abundance. The nomogram and calibrate were set up via the integration of the risk score and clinicopathological characteristics to assess the effectiveness of the prognostic signature. Finally, three genes were identified and were adopted to build an immune-related prognostic signature for HCV-related cirrhosis patients. The signature was proved to be an independent risk element for HCV-related cirrhosis patients. In addition, according to the time-dependent receiver operating characteristic (ROC) curves, nomogram, and calibration plot, the prognostic model could precisely forecast the survival rate at the first, fifth, and tenth year. Notably, functional enrichment analyses indicated that cytokine activity, chemokine activity, leukocyte migration and chemotaxis, chemokine signaling pathway and viral protein interaction with cytokine and cytokine receptor were involved in HCV-related cirrhosis progression. Moreover, ssGSEA analyses revealed fierce immune-inflammatory response mechanisms in HCV progress. Generally, our work developed a robust prognostic signature that can accurately predict the overall survival, Child-Pugh class progression, hepatic decompensation, and hepatocellular carcinoma (HCC) for HCV-related early-stage cirrhosis patients. Functional enrichment and further immune infiltration analyses systematically elucidated potential immune response mechanisms.

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Analysis of HSD11B2 as a prognostic marker in Melanoma via TCGA data mining

10.21203/rs.3.rs-42538/v1 ◽

2020 ◽

Author(s):

Hongyi Fu ◽

Yaqin Tang ◽

Ying Ding

Keyword(s):

Cox Regression ◽

Signalling Pathway ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Rank Test ◽

Clinicopathologic Characteristics ◽

Data Set ◽

Receptor Signalling ◽

Pathologic Features ◽

Melanoma Patients

Abstract Background: Hydroxysteroid 11-Beta Dehydrogenase 2 (HSD11B2) expression has been reported to be present in melanoma. We investigated the association of HSD11B2 with melanoma using publicly available data from The Cancer Genome Atlas (TCGA). Methods: The relationship between clinical pathologic features and HSD11B2 were analysed via Wilcoxon signed-rank test and logistic regression. Clinicopathologic characteristics associated with overall survival in melanoma patients were calculated using Cox regression and the Kaplan-Meier method. Gene Set Enrichment Analysis (GSEA) and gene co-association of HSD11B2 were performed using TCGA data set. Results: Reduced HSD11B2 expression was significantly lower in melanoma patients compared to normal patients (p value = 3.004e-122) and also associated with lower survivability. low HSD11B2 expression in melanoma was also significantly associated with cancer stages T (p value = 0.002) and N (p value < 0.001) and age (p value = 0.003). Genes TFCP2L1, PRR15L, ATP6V1B1, C9orf152, AC009948.1, AL391244.1, WDCP, HNRNPCP2 and GTF2E1 were all shown to be co-associated with changes in HSD1B2 expression. Multiple signalling pathway including cytosolic DNA sensing pathway, JAK STAT signalling pathway, NOD like receptor signalling pathway, T cell receptor signalling pathway and Toll like receptor signalling pathway were differentially enriched in low HSD11B2 expression phenotype. Conclusion: Our study revealed that HSD11B2 expression is closely associated with melanoma development and age, as well as multiple cancer related genes and pathways, thus highlighting HSD11B2 as a potential therapeutic marker of melanoma.

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An Integrated Analysis of C5AR2 Related to Malignant Properties and Immune Infiltration of Breast Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.736725 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yumeng Zhu ◽

Xiaochao Wang ◽

Yanqing Xu ◽

Lu Chen ◽

Peipei Ding ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Cells ◽

Breast Cancer Cells ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Integrated Analysis ◽

Immune Infiltration ◽

Mutation Burden ◽

Multiple Signaling

BackgroundC5AR2 (GPR77, C5L2) is the second receptor for C5a that is a potent protein generated by complement activation. C5AR2 can mediate its own signaling events and exert significant immunomodulatory effects through those events. However, research of C5AR2 in cancer is limited, and its function remains unclear in breast cancer.MethodsThe expression of C5AR2 and its correlations with prognosis, immune infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI) in more than thirty types of cancers were described through GTEx, TCGA, PrognoScan, TIMER2.0, CCLE, HPA, and TISIDB database. C5AR2 showed strong relationships to those immune marker sets in breast cancer. Otherwise, CCK8 assay and Transwell assay were conducted to illustrate the role of C5AR2 in migration, invasion, and proliferation of breast cancer cells.ResultsGenerally, C5AR2 expression differed across most cancerous and noncancerous tissues, and high C5AR2 expression significantly related to poor prognosis in BRCA, GBM, KICH, LAML, LGG, LIHC, PAAD, and STAD. Moreover, C5AR2 expression levels were dramatically correlated with recognized immune infiltration, especially the polarization of macrophages in breast cancer. Gene set enrichment analysis confirmed that C5AR2 participates in regulating multiple signaling pathways involved in tumorigenesis as well as tumor immunity. C5AR2 overexpression facilitated the functions such as migration, invasion, and proliferation in breast cancer cells, which is consistent with bioinformatics analysis.ConclusionsC5AR2 is involved in immune infiltration and malignant characteristics of breast cancer, which may be a prospective biomarker for breast cancer.

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The Role of M6A-related CBLL1 in the Prognosis and Immune Infiltration of Pan-cancer

10.21203/rs.3.rs-40873/v1 ◽

2020 ◽

Author(s):

Qiang Guo ◽

Dan Li ◽

Yan-Mei Ji ◽

Jialong Guo

Keyword(s):

Mrna Expression ◽

Immune Cells ◽

Gene Set Enrichment Analysis ◽

Expression Level ◽

Cycle Phase ◽

Immune Infiltration ◽

The Relationship ◽

Pan Cancer ◽

Ucsc Database

Abstract Background The modification of N6-methyladenosine (m6A) plays an important role in physiology and disease progression. The relationship between the role of m6a-related gene CBLL1 in pan-carcinoma and tumor immune infiltrates has remained unknown. Methods To explore the expression level of CBLL1 methylation in pan-cancer in SMART database, and download mRNA expression, mutation and clinical data in UCSC database, to analyze the expression level of CBLL1, and the relationship between CBLL1 expression and clinicopathological features, prognosis, mutation and immune microenvironment in pan-cancer. CIBERSORT was used to analyze the relationship between the expression of CBLL1 and the infiltration of pan-carcinoma immune cells. The mRNA expression data of UCSC database were used to analyze the correlation between CBLL1 expression and pan-cancer immunomodulations, checkpoints and receptor molecules. Gene Set enrichment analysis (GSEA) revealed the possible mechanism of CBLL1 in the regulation of pan-cancer progression. Results The levels of CBLL1 methylation and mRNA expression in pan-cancer tissues were abnormal. The level of CBLL1 is related to the age, race, clinical stage and treatment effect of patients with pan-carcinoma and associated with the prognosis of patients with KIRC, LUSC, THCA, THYM, MESO, PRAD, STAD, and UVM. Univariate COX regression analysis showed that expression of CBLL1 was a risk factor for poor prognosis in patients with KICH, KIRC, LAML, THYM, KIRC, PCPG, OV, PRAD, STAD, GBM and UVM.The expression level of CBLL1 was correlated with BLCA, BRCA, COAD, LAML, LGG, LUAD, LUSC, SARC, STAD, THCA, THYM and UVM tumor mutational burden (TMB), and with ACC, BRCA, CESC, COAD, DLBC, HNSC, PRAD, READ, SARC, STAD, TGCT, THCA and UCEC microsatellite instability (MSI). The expression level of CBLL1 was correlated with pan-cancer stromal cells and immune cells. The expression of CBLL1 is related to pan-cancer immunomodulators, checkpoints and receptor molecules. GSEA found that CBLL1 may participate in the progression of pan-cancer through B cell receptor singaling pathway, mRNA binding, immunoglobulin receptor binding, Positive Regulation of cell cycle phase transition and other mechanisms. Conclusions CBLL1 is abnormally expressed in patients with pan-carcinoma, which is expected to be a biomarker for prognosis, mutation and immune infiltration in patients with pan-carcinoma.

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Establishment of a 8 Immune-Related LncRNA Signature for Predicting the Prognosis of Soft Tissue Sarcoma

10.21203/rs.3.rs-882267/v1 ◽

2021 ◽

Author(s):

Yuhang Liu ◽

Changjiang Liu ◽

Aixi Yu

Keyword(s):

Soft Tissue ◽

Soft Tissue Sarcoma ◽

Cox Regression ◽

Hot Spot ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

Prognostic Models ◽

Data Set ◽

Cox Regression Analysis ◽

Immune Infiltration

Abstract Background: Soft tissue sarcoma is relatively rare and highly heterogeneous, which brings great difficulties to treatment. Long non-coding RNA acts a vital role in the occurrence and progression of soft tissue sarcoma, especially in the tumor-related immune process, which has become a hot spot of current research. Therefore, we are committed to developing lncRNA markers related to immunity to promote the treatment and prognosis of patients with soft tissue sarcoma.Methods：Based on the TCGA-SARC and GTEx data set, we screened out 8 prognostic-related immune lncRNAs and constructed a nomogram, which was verified in the test set. Furthermore, immune infiltration analysis was carried out on patients of high and low risk.Results: Based on the results of Pearson's correlation coefficient, we obtained 859 immune-related lncRNAs. After difference analysis, we finally determined 54 different lncRNAs. Univariate and multivariate cox regression analysis finally determined 8 immune-related lncRNAs to construct prognostic models and nomograms to predict the prognosis of STS patients. The above results have been verified in external data sets, indicating that this model has good predictive ability. Gene Set Enrichment Analysis and ESTIMATE analysis showed obviously differences exist in the immune infiltration status and immune cell subtypes of high- and low-risk patients.Conclusion: We constructed an immune-related lncRNA pattern to predict the survival status of soft tissue sarcoma patients.

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The Role of NLRP3 in The Prognosis and Immune Infiltrates of Skin Cutaneous Melanoma (SKCM)

10.21203/rs.3.rs-93268/v1 ◽

2020 ◽

Author(s):

Shaobo Wu ◽

Qijuan Zang ◽

Bingling Dai

Keyword(s):

T Cells ◽

Logistic Regression ◽

Cutaneous Melanoma ◽

Survival Rates ◽

Gene Set Enrichment Analysis ◽

Receptor Protein ◽

Data Set ◽

Immune Infiltration ◽

The Impact ◽

Nlrp3 Expression

Abstract BackgroundSkin cutaneous melanoma is one of most aggressive type of cancers worldwide, Therefore, the identification of SKCM biomarkers is of great importance. NLRP3 Inflammasome Complex Nodelike Receptor protein 3 (NLRP3) is one of the most characteristic inflammasomes belonging to the NLR protein family. This is the first time to use TCGA data to study NLRP3 expression in SKCM patients and its prognostic value, potential biological function, and impact on the immune system. MethodsThe expression of NLRP3 in SKCM was analyzed by GEPIA. We assessed the impact of NLRP3 on SKCM patient survival through the survival module. Then download the SKCM data set from TCGA. Logistic regression was used to analyze the correlation between clinical data and NLRP3 expression. Univariate survival rate and multivariate Cox analysis were used to compare several clinical features and survival rates. We also used CIBERSORT to investigate the association between NLRP3 and cancer immune infiltration. We used TIMER to investigate NLRP3 expression and collection of immune infiltration levels in SKCM, as well as cumulative survival in SKCM. Gene set enrichment analysis (GSEA) was performed using the TCGA dataset. In addition, data from the HPA was used to validate the results.ResultsUnivariate Logistic regression analysis showed that increased NLRP3 expression was significantly correlated with age, stage and tumor status. Specifically, NLRP3 expression level has significant positive correlations with infiltrating levels of B cell, CD4+ T cells, CD8+ T cells, Macrophages, Neutrophils and DCs in SKCM. GSEA revealed that NLRP3 is closely correlated with pathways in cancer. HPA showed that in tumor tissues, NLRP3 has higher levels of expression compared to normal tissues.ConclusionThe discovery of NLRP3 as a new biomarker of SKCM helps to elucidate how changes in the immune environment promote the occurrence of cutaneous melanoma. Further analysis suggested that NLRP3 might be a predictor of SKCM prognosis.

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Role of JAK-STAT pathway in pulmonary fibrosis

Pneumologie ◽

10.1055/s-0033-1345044 ◽

2013 ◽

Vol 67 (05) ◽

Cited By ~ 2

Author(s):

J Eschenbrenner ◽

W Janssen ◽

B Kojonazarov ◽

K Murmann ◽

A Ghofrani ◽

...

Keyword(s):

Pulmonary Fibrosis ◽

Stat Pathway

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Exchange Spin Coupling from Gaussian Process Regression

10.26434/chemrxiv.12589541.v3 ◽

2020 ◽

Author(s):

Marc Philipp Bahlke ◽

Natnael Mogos ◽

Jonny Proppe ◽

Carmen Herrmann

Keyword(s):

Machine Learning ◽

Gaussian Process ◽

Gaussian Process Regression ◽

Molecular Magnets ◽

Molecular Structures ◽

Spin Coupling ◽

Structure Property ◽

Data Set ◽

Uncertainty Estimates

Heisenberg exchange spin coupling between metal centers is essential for describing and understanding the electronic structure of many molecular catalysts, metalloenzymes, and molecular magnets for potential application in information technology. We explore the machine-learnability of exchange spin coupling, which has not been studied yet. We employ Gaussian process regression since it can potentially deal with small training sets (as likely associated with the rather complex molecular structures required for exploring spin coupling) and since it provides uncertainty estimates (“error bars”) along with predicted values. We compare a range of descriptors and kernels for 257 small dicopper complexes and find that a simple descriptor based on chemical intuition, consisting only of copper-bridge angles and copper-copper distances, clearly outperforms several more sophisticated descriptors when it comes to extrapolating towards larger experimentally relevant complexes. Exchange spin coupling is similarly easy to learn as the polarizability, while learning dipole moments is much harder. The strength of the sophisticated descriptors lies in their ability to linearize structure-property relationships, to the point that a simple linear ridge regression performs just as well as the kernel-based machine-learning model for our small dicopper data set. The superior extrapolation performance of the simple descriptor is unique to exchange spin coupling, reinforcing the crucial role of choosing a suitable descriptor, and highlighting the interesting question of the role of chemical intuition vs. systematic or automated selection of features for machine learning in chemistry and material science.

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Vocational Development in Emerging Adulthood

10.1093/oso/9780199934263.003.0006 ◽

2018 ◽

Author(s):

Michael W. Pratt ◽

M. Kyle Matsuba

Keyword(s):

Turning Point ◽

Life Stories ◽

Life Story ◽

Emerging Adult ◽

Vocational Development ◽

Data Set ◽

The World ◽

Key Concepts

Chapter 6 reviews research on the topic of vocational/occupational development in relation to the McAdams and Pals tripartite personality framework of traits, goals, and life stories. Distinctions between types of motivations for the work role (as a job, career, or calling) are particularly highlighted. The authors then turn to research from the Futures Study on work motivations and their links to personality traits, identity, generativity, and the life story, drawing on analyses and quotes from the data set. To illustrate the key concepts from this vocation chapter, the authors end with a case study on Charles Darwin’s pivotal turning point, his round-the-world voyage as naturalist for the HMS Beagle. Darwin was an emerging adult in his 20s at the time, and we highlight the role of this journey as a turning point in his adult vocational development.

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Actors, Partisan Inclination, and Emotions: An Analysis of Government Shutdown News Stories Shared on Twitter

Social Media + Society ◽

10.1177/20563051211008816 ◽

2021 ◽

Vol 7 (2) ◽

pp. 205630512110088

Author(s):

Colin Agur ◽

Lanhuizi Gan

Keyword(s):

Emotional Responses ◽

The United States ◽

Online Information ◽

News Frames ◽

Data Set ◽

Political Issues ◽

News Stories ◽

News Sharing ◽

Government Shutdown

Scholars have recognized emotion as an increasingly important element in the reception and retransmission of online information. In the United States, because of existing differences in ideology, among both audiences and producers of news stories, political issues are prone to spark considerable emotional responses online. While much research has explored emotional responses during election campaigns, this study focuses on the role of online emotion in social media posts related to day-to-day governance in between election periods. Specifically, this study takes the 2018–2019 government shutdown as its subject of investigation. The data set shows the prominence of journalistic and political figures in leading the discussion of news stories, the nuance of emotions employed in the news frames, and the choice of pro-attitudinal news sharing.

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