Identification of a gene set correlated with immune status in ovarian cancer by transcriptome-wide data mining

Abstract Background : Ovarian cancer (OC) is a serious tumor disease in gynecology. Many papers have reported that high tumor mutational burden (TMB) can generate many neoantigens to result in a higher degree of tumor immune infiltration, so our study aims to predict the key molecules in OC immunotherapy by combined TMB with immunoactivity-related gene. Method: We divided OC cases into two groups: the low & high TMB group hinged on the somatic mutation data from the Cancer Genome Atlas (TCGA). We also used single-sample gene set enrichment analysis (ssGSEA) scores of immune cell types to conduct unsupervised clustering of OC patients in the TCGA cohort and some of them were defined as the low & high immunity group. Besides, to further understand the function of these genes, we conducted Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway, protein-protein interaction network, survival prognosis analysis and immune infiltration analysis. Finally, the effects on prognosis and immunotherapy in OC patients were explored by the Group on Earth Observations verification the patients' responses to immunotherapy. Results: We found that the higher the TMB was associated with the higher OC grades. Moreover, both high TMB and high immunity were significantly correlated with a good prognosis of OC. Then, 14 up-regulated differential expression genes (Up-DEGs) that were closely related to the prognosis of OC patients were screened according to the high TMB group and the high immunity group. Next, pathway analysis revealed that Up-DGEs were mainly involved in immune response and T cell proliferation. Finally, four genes had a good prognosis and were validated in the GEO dataset which included CXCL13, FCRLA, PLA2G2D, and MS4A1. We also identified that four genes had a good prognosis in melanoma patients treated with anti-PD-L1 and anti-CTLA-4 in the TIDE database. Conclusion: High TMB can promote immune cell infiltration and increases immune activity. And our analysis also demonstrated that the higher the TMB, the higher the immune activity, the better the prognosis of OC. Altogether, we found that CXCL13, FCRLA, PLA2G2D, and MS4A1 may be biomarkers for OC immunotherapy. Keywords: ovarian cancer, TMB, immune cells infiltration, survival prognosis.

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TRPV4 is a Prognostic Biomarker that Correlates with the Immunosuppressive Microenvironment and Chemoresistance of Anti-Cancer Drugs

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.690500 ◽

2021 ◽

Vol 8 ◽

Author(s):

Kai Wang ◽

Xingjun Feng ◽

Lingzhi Zheng ◽

Zeying Chai ◽

Junhui Yu ◽

...

Keyword(s):

Ovarian Cancer ◽

Transient Receptor Potential ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Cancer Drugs ◽

Free Interval ◽

Anti Cancer ◽

Pan Cancer

Background: Transient receptor potential cation channel subfamily V member 4 (TRPV4) has been reported to regulate tumor progression in many tumor types. However, its association with the tumor immune microenvironment remains unclear.Methods: TRPV4 expression was assessed using data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. The clinical features and prognostic roles of TRPV4 were assessed using TCGA cohort. Gene set enrichment analysis (GSEA) of TRPV4 was conducted using the R package clusterProfiler. We analyzed the association between TRPV4 and immune cell infiltration scores of TCGA samples downloaded from published articles and the TIMER2 database. The IC50 values of 192 anti-cancer drugs were downloaded from the Genomics of Drug Sensitivity in Cancer (GDSC) database and the correlation analysis was performed.Results: TRPV4 was highly expressed and associated with worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in colon adenocarcinoma (COAD) and ovarian cancer. Furthermore, TRPV4 expression was closely associated with immune regulation-related pathways. Moreover, tumor-associated macrophage (TAM) infiltration levels were positively correlated with TRPV4 expression in TCGA pan-cancer samples. Immunosuppressive genes such as PD-L1, PD-1, CTLA4, LAG3, TIGIT, TGFB1, and TGFBR1 were positively correlated with TRPV4 expression in most tumors. In addition, patients with high expression of TRPV4 might be resistant to the treatment of Cisplatin and Oxaliplatin.Conclusion: Our results suggest that TRPV4 is an oncogene and a prognostic marker in COAD and ovarian cancer. High TRPV4 expression is associated with tumor immunosuppressive status and may contribute to TAM infiltration based on TCGA data from pan-cancer samples. Patients with high expression of TRPV4 might be resistant to the treatment of Cisplatin and Oxaliplatin.

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TRPV4 is a Prognostic Biomarker That Correlates With the Immunosuppressive Microenvironment and Chemoresistance of Anti-Cancer Drugs

10.21203/rs.3.rs-383566/v1 ◽

2021 ◽

Author(s):

kai wang ◽

Jun xing Feng ◽

Zhi ling Zheng ◽

Ying ze Chai ◽

Hui jun Yu ◽

...

Keyword(s):

Ovarian Cancer ◽

Transient Receptor Potential ◽

Immune Cell ◽

Colon Adenocarcinoma ◽

Enrichment Analysis ◽

Receptor Potential ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Free Interval ◽

Pan Cancer

Abstract Background: Transient receptor potential cation channel subfamily V member 4 (TRPV4) has been reported to regulate tumor progression in many tumor types. However, its association with the tumor immune microenvironment remains unclear.Methods: TRPV4 expression was assessed using data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. The clinical features and prognostic roles of TRPV4 were assessed using TCGA cohort. Gene set enrichment analysis (GSEA) of TRPV4 was conducted using the R package clusterProfiler. We analyzed the association between TRPV4 and immune cell infiltration scores of TCGA samples downloaded from published articles and the TIMER2 database.Results: TRPV4 was highly expressed and associated with worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in colon adenocarcinoma (COAD) and ovarian cancer. Furthermore, TRPV4 expression was closely associated with immune regulation-related pathways. Moreover, tumor-associated macrophage (TAM) infiltration levels were positively correlated with TRPV4 expression in TCGA pan-cancer samples. Immunosuppressive genes such as PD-L1, PD-1, CTLA4, LAG3, TIGIT, TGFB1, and TGFBR1 were positively correlated with TRPV4 expression in most tumors.Conclusions: Our results suggest that TRPV4 is an oncogene and a prognostic marker in COAD and ovarian cancer. High TRPV4 expression is associated with tumor immunosuppressive status and may contribute to TAM infiltration based on TCGA data from pan-cancer samples.

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PVT1 is a prognostic marker associated with immune invasion of bladder urothelial carcinoma

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2022009 ◽

2021 ◽

Vol 19 (1) ◽

pp. 169-190

Author(s):

Peiyuan Li ◽

◽

Gangjie Qiao ◽

Jian Lu ◽

Wenbin Ji ◽

...

Keyword(s):

Urothelial Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Gene Set Enrichment ◽

Cox Regression Analysis ◽

Gene Set ◽

Bladder Urothelial Carcinoma

<abstract> <p>Plasmacytoma variant translocation 1 (PVT1) is involved in multiple signaling pathways and plays an important regulatory role in a variety of malignant tumors. However, its role in the prognosis and immune invasion of bladder urothelial carcinoma (BLCA) remains unclear. This study investigated the expression of PVT1 in tumor tissue and its relationship with immune invasion, and determined its prognostic role in patients with BLCA. Patients were identified from the cancer genome atlas (TCGA). The enrichment pathway and function of PVT1 were explained by gene ontology (GO) term analysis, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA), and the degree of immune cell infiltration was quantified. Kaplan–Meier analysis and Cox regression were used to analyze the correlation between PVT1 and survival rate. PVT1-high BLCA patients had a lower 10-year disease-specific survival (DSS P < 0.05) and overall survival (OS P < 0.05). Multivariate Cox regression analysis showed that PVT1 (high vs. low) (P = 0.004) was an independent prognostic factor. A nomogram was used to predict the effect of PVT1 on the prognosis. PVT1 plays an important role in the progression and prognosis of BLCA and can be used as a medium biomarker to predict survival after cystectomy.</p> </abstract>

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Identification of two molecular subtypes of dysregulated immune lncRNAs in ovarian cancer

Experimental Biology and Medicine ◽

10.1177/1535370220972024 ◽

2020 ◽

pp. 153537022097202

Author(s):

Xiaojun Liu ◽

Jinghai Gao ◽

Jing Wang ◽

Jing Chu ◽

Jiahao You ◽

...

Keyword(s):

Ovarian Cancer ◽

Differentially Expressed Genes ◽

Immune Cell ◽

Molecular Subtypes ◽

Good Prognosis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Receptor Interaction ◽

Cancer Multiple

Long non-coding RNA (lncRNA) has increasingly been identified as a key regulator in pathologies such as cancer. Multiple platforms were used for comprehensive analysis of ovarian cancer to identify molecular subgroups. However, lncRNA and its role in mapping the ovarian cancer subpopulation are still largely unknown. RNA-sequencing and clinical characteristics of ovarian cancer were acquired from The Cancer Genome Atlas database (TCGA). A total of 52 lncRNAs were identified as aberrant immune lncRNAs specific to ovarian cancer. We redefined two different molecular subtypes, C1(188) and C2(184 samples), in “iClusterPlus” R package, among which C2 grouped ovarian cancer samples have higher survival probability and longer median survival time ( P <0.05) with activated IFN-gamma response, Wound Healing and Cytotoxic lymphocytes signal; 456 differentially expressed genes were acquired in C1 and C2 subtypes using limma (3.40.6) package, among which 419 were up-regulated and 37 were down-regulated, in TCGA dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis revealed that these genes were actively involved in ECM-receptor interaction, PI3K-Akt signaling pathway interaction KEGG pathway. Compared with the existing immune subtype, the Cluster2 sample showed a substantial increase in the proportion of the existing C2 immune subtype, accounting for 81.37%, which was associated with good prognosis. Our C1 subtype contains only 56.49% of the existing immune C1 and C4, which also explains the poor prognosis of C1. Furthermore, 52 immune-related lncRNAs were used to divide the TCGA-endometrial cancer and cervical cancer samples into two categories, and C2 had a good prognosis. The differentially expressed genes were highly correlated with immune-cell-related pathways. Based on lncRNA, two molecular subtypes of ovarian cancer were identified and had significant prognostic differences and immunological characteristics.

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Identification of a gene set correlated with immune status in ovarian cancer by transcriptome-wide data mining

10.21203/rs.3.rs-35960/v1 ◽

2020 ◽

Author(s):

Lili Fan ◽

Han Lei ◽

Ying Lin ◽

Tianxiang Zhang ◽

Zhengwei Zhou ◽

...

Keyword(s):

Ovarian Cancer ◽

Immune Response ◽

Immune Status ◽

Checkpoint Blockade ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Limited Information ◽

Gene Set ◽

Prognosis Prediction ◽

Signature Genes

Abstract Background: Checkpoint block-mediated tumor immunotherapy has obtained huge success in treating various malignancies. However, the efficacy of immunotherapies against ovarian cancer (OC) was low largely due to limited information on the tumor immune microenvironment (TIME) of OC. This results in lacking reliable biomarkers to select the right patients for immunotherapy and prognosis prediction. Published studies have reported that high tumor mutation burden (TMB) can generate many neoantigens resulting in a higher degree of an anti-tumor immune response. However, the correlation between TMB and TIME of OC remains controversial let along a collection of TMB information is time and resource consuming. In this study, we considered the TMB and TIME of OC comprehensively to categorize patients based on their tumor local immune status and provide information that could guide further OC immunotherapy trials as well as the prognosis prediction.Method: OC RNAseq data were downloaded from The Cancer Genome Atlas (TCGA) and divided into TMBhigh and TMBlow subgroups according to TMB scores for comparison. OC cases were also grouped into immunityhigh or immunitylow based on their profiles of tumor-infiltrating leukocytes (TILs) analyzed by ssGSEA (Single Sample Gene Set Enrichment Analysis). Besides, the function of genes enriched in both TMBhigh and immunityhigh was analyzed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway (KEGG), and protein-protein interaction (PPI) network. The correlation of each gene with overall survival was also analyzed.Results: Positive association was observed between the OC grade and the TMB. Both TMBhigh and immunityhigh were significantly correlated with a better prognosis. However, different from the findings of other studies, TMB of OC didn’t correlated with preferable TIME in our analysis. By comparing the up-regulated signature genes in TMBhigh and immunityhigh cases, we found 14 overlapped genes that were mainly involved in immune response-related pathways. We further analyzed the prognostic value of these 14 genes and found the upregulation of 4 of them, CXCL13, FCRLA, PLA2G2D, and MS4A1 are significantly associated with better survival. With available data collected form a melanoma cohort, we also found that these four genes are positively associated with better response to immune checkpoint blockade-based immunotherapy.Conclusion: By comparing signature genes enriched in TMBhigh and immunityhigh subgroups, four genes, CXCL13, FCRLA, PLA2G2D, and MS4A1, were found positively correlated with both OC immune infiltration and better prognosis. Additionally, these four genes predicted the response to checkpoint blockade-based immunotherapy in a melanoma cohort indicating that they can also be used as biomarkers for further immunotherapy clinical trials of OC.

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An Analysis Regarding the Prognostic Significance of MAVS and Its Underlying Biological Mechanism in Ovarian Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.728061 ◽

2021 ◽

Vol 9 ◽

Author(s):

Lifeng Chen ◽

Jing Hou ◽

Bingbing You ◽

Feifei Song ◽

Xinyi Tu ◽

...

Keyword(s):

Ovarian Cancer ◽

Immune Cell ◽

Critical Role ◽

Prognostic Significance ◽

Gene Set Enrichment Analysis ◽

Biological Behavior ◽

Biological Mechanism ◽

Bioinformatics Analyses ◽

Γδt Cells ◽

Gene Set

The present study evaluates the value of mitochondrial antiviral signaling (MAVS) expression as a potential diagnostic biomarker and therapeutic target for ovarian cancer (OC) and analyses the underlying biological mechanism in this pathology. First, the association between MAVS expression determined by immunohistochemical (IHC) and clinical characteristics was systematically investigated. Overexpression of MAVS was associated with advanced clinical factors and poor survival of OC patients. Second, bioinformatics analyses, namely, gene expression, mutation analysis, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), and weighted gene co-expression network analysis (WGCNA), were performed to evaluate the potential biological functions of MAVS in OC. The results showed that MAVS may play a critical role in immune cell infiltration. CIBERSORT was applied to assess the infiltration of immune cells in OC. CD8+ T cells, γδT cells, and eosinophils had significantly negative correlations with MAVS expression. Finally, sensitivity analysis found that patients with high MAVS expression were predicted to be significantly less responsive to cisplatin and paclitaxel. In conclusion, these findings suggested that MAVS influences biological behavior by regulating the immune response and that it can be used as a predictive marker for poor prognosis in OC.

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Combination of gene set signatures correlates with response to nivolumab in platinum-resistant ovarian cancer

10.21203/rs.3.rs-371906/v1 ◽

2021 ◽

Author(s):

Ryusuke Murakami ◽

Junzo Hamanishi ◽

J. B. Brown ◽

Kaoru Abiko ◽

Koji Yamanoi ◽

...

Keyword(s):

Ovarian Cancer ◽

Clinical Response ◽

Clear Cell ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Specific Gene ◽

Gene Signatures ◽

Gene Set ◽

Platinum Resistant

Abstract Background Based on our previous phase II clinical trial of anti-programmed death-1 (PD-1) antibody nivolumab for platinum-resistant ovarian cancer (n=19, UMIN000005714), we aimed to identify the therapeutic response biomarkers to nivolumab in ovarian cancer. Methods Tumor gene expressions were evaluated by proliferative, mesenchymal, differentiated, and immunoreactive gene signatures derived from high-grade serous carcinomas in The Cancer Genome Atlas and a signature established prior to ovarian clear cell carcinoma. Gene sets were scored using the single-sample gene set enrichment analysis, and resulting scores were used to assess the correlation between each gene set and the clinical response to nivolumab therapy. Statistical analyses were performed to identify pathways differentially expressed by either the complete response (CR) or progressive disease (PD) groups. Results The clear cell gene signature significantly had higher score in the CR group, and the proliferative gene signature had significantly higher score in the PD group where nivolumab was not effective (respective p-values 0.005 and 0.026). Combinations of gene signatures improved correlation with response, where a projection of immunoreactive, proliferative, and clear cell signatures differentiated clinical response. Conclusion Ovarian cancer-specific gene signature and related pathway scores provide a preliminary indicator for ovarian cancer prior to receiving anti-PD-1 antibody therapy.

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SNHG3/miR-148a-3p Axis–mediated High Expression of DNMT1 Correlates with Poor Prognosis and Tumor Immune Infiltration of Hepatocellular Carcinoma

10.21203/rs.3.rs-864636/v1 ◽

2021 ◽

Author(s):

Ninghua Yao ◽

Wei Jiang ◽

Jie Sun ◽

Chen Yang ◽

Wenjie Zheng ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Immune Cell Infiltration ◽

Gene Set Enrichment ◽

Gene Set ◽

Immune Infiltration ◽

Computer Analyses ◽

Dnmt1 Expression

Abstract Background Epigenetic reprogramming plays an important role in the occurrence, development, and prognosis of hepatocellular carcinoma (HCC). DNA methylation is a key epigenetic regulatory mechanism, and DNA methyltransferase 1 (DNMT1) is the major enzyme responsible for maintenance methylation. Nevertheless, the role and mechanism of DNMT1 in HCC remains poorly defined. Methods In the current study, we conducted pan-cancer analysis for DNMT1’s expression and prognosis using The Cancer Genome Atlas (TCGA) data set. We conducted gene Set Enrichment Analysis (GSEA) between high-and-low DNMT1 expression groups to identify DNMT1-related functional significance. We also investigated the relationship between DNMT1 expression and tumor immune microenvironment, including immune cell infiltration and the expression of immune checkpoints. Through a combination series of computer analyses (including expression analyses, correlation analyses, and survival analyses), the noncoding RNAs (ncRNAs) that contribute to the overexpression of DNMT1 were ultimately identified. Results We found that DNMT1 was upregulated in 16 types of human carcinoma including HCC, and DNMT1 might be a biomarker predicting unfavorable prognosis in HCC patients. DNMT1 mRNA expression was statistically associated with age, histological grade, and the level of serum AFP. Moreover, DNMT1 level was significantly and positively linked to tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint expression. Meanwhile, Gene Set Enrichment Analysis (GSEA) revealed that high-DNMT1 expression was associated with epithelial mesenchymal transition (EMT), E2F target, G2M checkpoint, and inflammatory response. Finally, through a combination series of computer analyses the SNHG3/hsa-miR-148a-3p/DNMT1 axis was confirmed as the potential regulatory pathway in HCC. Conclusion SNHG3/miR-148a-3p axis upregulation of DNMT1 may be related to poor outcome, tumor immune infiltration, and regulated malignant properties in HCC.

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Comprehensive Analysis of the Tumor Microenvironment and Ferroptosis-Related Genes Predict Prognosis with Ovarian Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.774400 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiao-xue Li ◽

Li Xiong ◽

Yu Wen ◽

Zi-jian Zhang

Keyword(s):

Ovarian Cancer ◽

Cox Regression ◽

Enrichment Analysis ◽

Roc Curves ◽

Gene Set Enrichment Analysis ◽

Drug Resistant ◽

Cox Regression Analysis ◽

Gene Set ◽

Immune Infiltration ◽

Tcga Dataset

The early diagnosis of ovarian cancer (OC) is critical to improve the prognosis and prevent recurrence of patients. Nevertheless, there is still a lack of factors which can accurately predict it. In this study, we focused on the interaction of immune infiltration and ferroptosis and selected the ESTIMATE algorithm and 15 ferroptosis-related genes (FRGs) to construct a novel E-FRG scoring model for predicting overall survival of OC patients. The gene expression and corresponding clinical characteristics were obtained from the TCGA dataset (n = 375), GSE18520 (n = 53), and GSE32062 (n = 260). A total of 15 FRGs derived from FerrDb with the immune score and stromal score were identified in the prognostic model by using least absolute shrinkage and selection operator (LASSO)–penalized COX regression analysis. The Kaplan–Meier survival analysis and time-dependent ROC curves performed a powerful prognostic ability of the E-FRG model via multi-validation. Gene Set Enrichment Analysis and Gene Set Variation Analysis elucidate multiple potential pathways between the high and low E-FRG score group. Finally, the proteins of different genes in the model were verified in drug-resistant and non–drug-resistant tumor tissues. The results of this research provide new prospects in the role of immune infiltration and ferroptosis as a helpful tool to predict the outcome of OC patients.

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Uncovering of the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

10.21203/rs.3.rs-580707/v1 ◽

2021 ◽

Author(s):

Xinyu Gu ◽

Haibo Zhou ◽

Qingfei Chu ◽

Qiuxian Zheng ◽

Jing Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cells ◽

Immune Cell ◽

Enrichment Analysis ◽

Tumour Microenvironment ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Gene Set ◽

Normal Tissues

Abstract Background: 5-Methylcytosine (m5C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m5C regulation and immune cell infiltration in HCC has not yet been clarified.Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m5C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.Results: Among the 371 patients, 41 had mutations in m5C regulators, the frequency of which was 11.26%. Then, we identified three m5C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. Cluster-1 had an immune rejection phenotype; Cluster-2 had an immunoinflammatory phenotype; and Cluster-3 had an immune desert phenotype. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m5C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three Immu-clusters that were consistent with the immune characteristics of the m5C methylation modification patterns. We also discovered differences in the levels of immune cells and expression of chemokines and cytokines among the three Immu-clusters.Conclusions: Our work revealed the association between m5C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

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