scholarly journals Comprehensive Pan-Cancer Analyses of Pyroptosis-Related Genes to Predict Survival and Immunotherapeutic Outcome

Cancers ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 237
Author(s):  
Qilin Wang ◽  
Qian Liu ◽  
Sihan Qi ◽  
Junyou Zhang ◽  
Xian Liu ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Risk Model ◽  
Tissue Expression ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Transcriptional Level ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Novel Strategy

Pyroptosis is a newly characterized type of programmed cell death. However, its function in cancer progression and its response to treatments remain controversial. Here, we extensively and systematically compiled genes associated with pyroptosis, integrated multiomics data and clinical data across 31 cancer types from The Cancer Genome Atlas, and delineated the global alterations in PRGs at the transcriptional level. The underlying transcriptional regulations by copy number variation, miRNAs, and enhancers were elucidated by integrating data from the Genotype-Tissue Expression and International Cancer Genome Consortium. A prognostic risk model, based on the expression of PRGs across 31 cancer types, was constructed. To investigate the role of pyroptosis in immunotherapy, we found five PRGs associated with effectiveness by exploring the RNA-Seq data of patients with immunotherapy, and further identified two small-molecule compounds that are potentially beneficial for immunotherapy. For the first time, from a pyroptosis standpoint, this study establishes a novel strategy to predict cancer patient survival and immunotherapeutic outcomes.

scholarly journals Prognostic values of GMPS, PR, CD40, and p21 in ovarian cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6301 ◽  
Author(s):  
Ping Wang ◽  
Zengli Zhang ◽  
Yujie Ma ◽  
Jun Lu ◽  
Hu Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Cancer Patients ◽  
Differential Expression ◽  
Cancer Progression ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Progression Model ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Early detection and prediction of prognosis and treatment responses are all the keys in improving survival of ovarian cancer patients. This study profiled an ovarian cancer progression model to identify prognostic biomarkers for ovarian cancer patients. Mouse ovarian surface epithelial cells (MOSECs) can undergo spontaneous malignant transformation in vitro cell culture. These were used as a model of ovarian cancer progression for alterations in gene expression and signaling detected using the Illumina HiSeq2000 Next-Generation Sequencing platform and bioinformatical analyses. The differential expression of four selected genes was identified using the gene expression profiling interaction analysis (http://gepia.cancer-pku.cn/) and then associated with survival in ovarian cancer patients using the Cancer Genome Atlas dataset and the online Kaplan–Meier Plotter (http://www.kmplot.com) data. The data showed 263 aberrantly expressed genes, including 182 up-regulated and 81 down-regulated genes between the early and late stages of tumor progression in MOSECs. The bioinformatic data revealed four genes (i.e., guanosine 5′-monophosphate synthase (GMPS), progesterone receptor (PR), CD40, and p21 (cyclin-dependent kinase inhibitor 1A)) to play an important role in ovarian cancer progression. Furthermore, the Cancer Genome Atlas dataset validated the differential expression of these four genes, which were associated with prognosis in ovarian cancer patients. In conclusion, this study profiled differentially expressed genes using the ovarian cancer progression model and identified four (i.e., GMPS, PR, CD40, and p21) as prognostic markers for ovarian cancer patients. Future studies of prospective patients could further verify the clinical usefulness of this four-gene signature.

scholarly journals Development and validation of an oxidative stress—associated prognostic risk model for melanoma

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11258
Author(s):  
Yu Yang ◽  
Xuan Long ◽  
Kun Li ◽  
Guiyun Li ◽  
Xiaohong Yu ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Cancer Progression ◽  
Risk Model ◽  
Risk Group ◽  
Roc Curves ◽  
Tissue Expression ◽  
Diagnostic Value ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Hub Genes

Background Oxidative stress (OS) is key to various diseases and is implicated in cancer progression and oncogenesis. However, the potential diagnostic value of OS-related genes in skin cutaneous melanoma (SKCM) remains unclear. Methods We used data of RNA sequencing from 471 tumor tissues and one healthy tissue acquired from The Cancer Genome Atlas (TCGA)-SKCM cohort. The Genome Tissue Expression database was used to acquire transcriptome data from 812 healthy samples. OS-related genes that were differentially expressed between SKCM and healthy samples were investigated and 16 prognosis-associated OS genes were identified. The prognostic risk model was built using univariate and Cox multivariate regressions. The prognostic value of the hub genes was validated in the GSE65904 cohort, which included 214 SKCM patients. Results The overall survival rate of SKCM patients in the high-risk group was decreased compared to the low-risk group. In both TCGA and GSE65904 cohorts, the ROC curves suggested that our prognostic risk model was more accurate than other clinicopathological characteristics to diagnose SKCM. Moreover, risk score and nomograms associated with the expression of hub genes were developed. These presented reiterated our prognostic risk model. Altogether, this study provides novel insights with regards to the pathogenesis of SKCM. The 16 hub genes identified may help in SKCM prognosis and individualized clinical treatment.

scholarly journals Claudin-1, A Double-Edged Sword in Cancer

2020 ◽  
Vol 21 (2) ◽  
pp. 569 ◽  
Author(s):  
Ajaz A. Bhat ◽  
Najeeb Syed ◽  
Lubna Therachiyil ◽  
Sabah Nisar ◽  
Sheema Hashem ◽  
...  
Keyword(s):  
Cancer Progression ◽  
Malignant Tumors ◽  
Interaction Analysis ◽  
Vital Role ◽  
The Cancer Genome Atlas ◽  
Tumor Promoter ◽  
Pathway Interaction ◽  
Cancer Genome Atlas ◽  
Cell Growth And Differentiation ◽  
Cancer Types

Claudins, a group of membrane proteins involved in the formation of tight junctions, are mainly found in endothelial or epithelial cells. These proteins have attracted much attention in recent years and have been implicated and studied in a multitude of diseases. Claudins not only regulate paracellular transepithelial/transendothelial transport but are also critical for cell growth and differentiation. Not only tissue-specific but the differential expression in malignant tumors is also the focus of claudin-related research. In addition to up- or down-regulation, claudin proteins also undergo delocalization, which plays a vital role in tumor invasion and aggressiveness. Claudin (CLDN)-1 is the most-studied claudin in cancers and to date, its role as either a tumor promoter or suppressor (or both) is not established. In some cancers, lower expression of CLDN-1 is shown to be associated with cancer progression and invasion, while in others, loss of CLDN-1 improves the patient survival. Another topic of discussion regarding the significance of CLDN-1 is its localization (nuclear or cytoplasmic vs perijunctional) in diseased states. This article reviews the evidence regarding CLDN-1 in cancers either as a tumor promoter or suppressor from the literature and we also review the literature regarding the pattern of CLDN-1 distribution in different cancers, focusing on whether this localization is associated with tumor aggressiveness. Furthermore, we utilized expression data from The Cancer Genome Atlas (TCGA) to investigate the association between CLDN-1 expression and overall survival (OS) in different cancer types. We also used TCGA data to compare CLDN-1 expression in normal and tumor tissues. Additionally, a pathway interaction analysis was performed to investigate the interaction of CLDN-1 with other proteins and as a future therapeutic target.

scholarly journals Identification of ubiquitination-related genes in human glioma as indicators of patient prognosis

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250239
Author(s):  
Lei Wang ◽  
Yuelin Liu ◽  
Chengmin Xuan ◽  
Yong Liu ◽  
Hengliang Shi ◽  
...  
Keyword(s):  
Risk Model ◽  
Tissue Expression ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Multiple Tumor ◽  
Metabolism Regulation ◽  
Ubiquitin Proteasome ◽  
Cancer Genome Atlas ◽  
Patient Prognosis ◽  
Cox Analysis

Ubiquitination is a dynamic and reversible process of a specific modification of target proteins catalyzed by a series of ubiquitination enzymes. Because of the extensive range of substrates, ubiquitination plays a crucial role in the localization, metabolism, regulation, and degradation of proteins. Although the treatment of glioma has been improved, the survival rate of patients is still not satisfactory. Therefore, we explore the role of ubiquitin proteasome in glioma. Survival-related ubiquitination related genes (URGs) were obtained through analysis of the Genotype-Tissue Expression (GTEx) and the Cancer Genome Atlas (TCGA). Cox analysis was performed to construct risk model. The accuracy of risk model is verified by survival, Receiver operating characteristic (ROC) and Cox analysis. We obtained 36 differentially expressed URGs and found that 25 URGs were related to patient prognosis. We used the 25 URGs to construct a model containing 8 URGs to predict glioma patient risk by Cox analysis. ROC showed that the accuracy rate of this model is 85.3%. Cox analysis found that this model can be used as an independent prognostic factor. We also found that this model is related to molecular typing markers. Patients in the high-risk group were enriched in multiple tumor-related signaling pathways. In addition, we predicted TFs that may regulate the risk model URGs and found that the risk model is related to B cells, CD4 T cells, and neutrophils.

scholarly journals A Comprehensive Multiomics Analysis Identified Ubiquilin 4 as a Promising Prognostic Biomarker of Immune-Related Therapy in Pan-Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Jie Li ◽  
Ye Tong ◽  
Zhi Wang ◽  
Yi Liu ◽  
Xiaobo Dai ◽  
...  
Keyword(s):  
Prognostic Biomarker ◽  
Tissue Expression ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Human Protein Atlas ◽  
Tumor Mutational Burden ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Pan Cancer

Recently, it was reported that ubiquilin 4 (UBQLN4) alteration was associated with genomic instability in some cancers. However, whether UBQLN4 is a valuable biomarker for the prognosis of immunotherapy in pan-cancer was not identified. We evaluated the biologic and oncologic significance of UBQLN4 in pan-cancer at multiomics level, such as expression, mutation, copy number variation (CNV), methylation, and N6-methyladenosine (m6A) methylation. These omics data were obtained from several public databases, including Oncomine, The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), the Genotype-Tissue Expression (GTEx), the Human Protein Atlas (HPA), Gene Set Cancer Analysis (GSCA), m6A-Atlas, CancerSEA, and RNAactDrug. We found that UBQLN4 mRNA and protein were overexpressed in most cancer types, and the expression, mutation, CNV, and methylation of UBQLN4 were associated with the prognosis of some cancers. Mechanistically, UBQLN4 was involved in angiogenesis, DNA damage, apoptosis, and the pathway of PI3K/AKT and TSC/mTOR. Moreover, UBQLN4 mRNA was significantly correlated with immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), and mismatch repair (MMR). And, the correlation among UBQLN4 mRNA, CNV, and methylation and immune microenvironment was also identified. Furthermore, UBQLN4 was associated with the sensitivity of chemotherapy and targeted drugs at multiomics level. In conclusion, UBQLN4 was a promising prognostic biomarker of immune-related therapy in pan-cancer.

scholarly journals KMT2C is Potential Prognostic Biomarker and its Immune Regulating Roles in Pan-Cancer: A Comprehensive Analysis

2021 ◽  
Author(s):  
Guangnan Wei ◽  
Yuchen Zhang ◽  
Hongkai Zhuang ◽  
Yingzi Li ◽  
Chongyang Ren ◽  
...  
Keyword(s):  
Immune Therapy ◽  
Cancer Cell Line ◽  
Tissue Expression ◽  
Early Recurrence ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
High Expression ◽  
Cancer Type ◽  
Cancer Types ◽  
Histone Lysine Methyltransferases

Abstract Background: A member of histone lysine methyltransferases subfamily, The histone 3 lysine 4 (H3K4) monomethylase KMT2C, has mutations across many cancer types. However, the role of KMT2C in different cancers and its correlation with tumor infiltration and immune therapy indicators remain unknown.Method: Expression and mutation information of KMT2C has been analyzed through the Genotype-Tissue Expression (GTEx), The Cancer Genome Atlas (TCGA) Cancer Cell Line Encyclopedia (CCLE) and International Cancer Genome Consortium (ICGC) database in our study. Prognostic value of KMT2C was evaluated via univariate survival analysisand expression detection in different cancer cells. Result: Survival analysis showed that high expression of KMT2C in some cancer type may be a indication of better outcome, while in other cancer like UVM, patient with high expression of KMT2C suffered from early recurrence. Further, we found there is a strongly link between KMT2C expression and immune cells infiltration, mutation indicators through analysising in the Tumor Immune Evaluation Resource (TIMER) database. Conclusion: The bioinformatics analysis here deliver us a message that KMT2C might be a good molecular biomarker for prognostic and therapeutic evaluation in specific cancer types.

scholarly journals RHPCG: a database of the Regulation of the Hippo Pathway in Cancer Genome

Database ◽  
2019 ◽  
Vol 2019 ◽  
Author(s):  
Chengyu Wang ◽  
Fan Yang ◽  
Tingting Chen ◽  
Qi Dong ◽  
Zhangxiang Zhao ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Hippo Pathway ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Hippo Signaling ◽  
Protein Coding ◽  
Hippo Signaling Pathway ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
The Hippo Pathway

Abstract The Hippo signaling pathway is a highly conserved pathway controlling organ size, cell proliferation, apoptosis and other biological functions. Recent studies have shown that Hippo signaling pathway also plays important roles in cancer initiation and progression. However, a database offering multi-omics analyses and visualization of Hippo pathway genes in cancer, as well as comprehensive Hippo regulatory relationships is still lacking. To fill this gap, we constructed the Regulation of the Hippo Pathway in Cancer Genome (RHPCG) database. Currently, RHPCG focuses on analyzing the 21 core Hippo-protein-encoding genes in over 10 000 patients across 33 TCGA (The Cancer Genome Atlas) cancer types at the levels of genomic, epigenomic and transcriptomic landscape. Concurrently, RHPCG provides in its motif section 11 regulatory motif types associated with 21 core Hippo pathway genes containing 180 miRNAs, 6182 lncRNAs, 728 circRNAs and 335 protein coding genes. Thus, RHPCG is a powerful tool that could help researchers understand gene alterations and regulatory mechanisms in the Hippo signaling pathway in cancer.

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