A novel pyroptosis-associated gene signature for immune status and prognosis of cutaneous melanoma

Background Cutaneous melanoma (CM) is a life-threatening destructive malignancy. Pyroptosis significantly correlates with programmed tumor cell death and its microenvironment through active host-tumor crosstalk. However, the prognostic value of pyroptosis-associated gene signatures in CM remains unclear. Methods Gene profiles and clinical data of patients with CM were downloaded from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes associated with pyroptosis and overall survival (OS). We constructed a prognostic gene signature using LASSO analysis, then applied immune cell infiltration scores and Kaplan-Meier, Cox, and pathway enrichment analyses to determine the roles of the gene signature in CM. A validation cohort was collected from the Gene Expression Omnibus (GEO) database. Results Four pyroptosis-associated genes were identified and incorporated into a prognostic gene signature. Integrated bioinformatics findings showed that the signature correlated with patient survival and was associated with tumor growth and metastasis. The results of Gene Set Enrichment Analysis of a risk signature indicated that several enriched pathways are associated with cancer and immunity. The risk signature for immune status significantly correlated with tumor stem cells, the immune microenvironment, immune cell infiltration and immune subtypes. The expression of four pyroptosis genes significantly correlated with the OS of patients with CM and was related to the sensitivity of cancer cells to several antitumor drugs. A signature comprising four genes associated with pyroptosis offers a novel approach to the prognosis and survival of patients with CM and will facilitate the development of individualized therapy.

Download Full-text

An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

Scientific Reports ◽

10.1038/s41598-021-96373-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hualin Chen ◽

Yang Pan ◽

Xiaoxiang Jin ◽

Gang Chen

Keyword(s):

Bladder Cancer ◽

Immune Cells ◽

Immune Cell ◽

External Validation ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Prognostic Indicators ◽

Immune Cell Infiltration ◽

Related Gene

AbstractTo explore novel therapeutic targets, develop a gene signature and construct a prognostic nomogram of bladder cancer (BCa). Transcriptome data and clinical traits of BCa were downloaded from UCSC Xena database and Gene Expression Omnibus (GEO) database. We then used the method of Single sample Gene Set Enrichment analysis (ssGSEA) to calculate the infiltration abundances of 24 immune cells in eligible BCa samples. By weighted correlation network analysis (WGCNA), we identified turquoise module with strong and significant association with the infiltration abundance of immune cells which were associated with overall survival of BCa patients. Subsequently, we developed an immune cell infiltration-related gene signature based on the module genes (MGs) and immune-related genes (IRGs) from the Immunology Database and Analysis Portal (ImmPort). Then, we tested the prognostic power and performance of the signature in both discovery and external validation datasets. A nomogram integrated with signature and clinical features were ultimately constructed and tested. Five prognostic immune cell infiltration-related module genes (PIRMGs), namely FPR1, CIITA, KLRC1, TNFRSF6B, and WFIKKN1, were identified and used for gene signature development. And the signature showed independent and stable prognosis predictive power. Ultimately, a nomogram consisting of signature, age and tumor stage was constructed, and it showed good and stable predictive ability on prognosis. Our prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for BCa. Further researches are needed to verify the clinical effectiveness of this nomogram and these biomarkers.

Download Full-text

Comprehensive Analysis of the Immune and Prognostic Implication of COL6A6 in Lung Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.633420 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yi Ma ◽

Mantang Qiu ◽

Haifa Guo ◽

Haiming Chen ◽

Jiawei Li ◽

...

Keyword(s):

T Cell ◽

Lung Adenocarcinoma ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Signature ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Gene Copy ◽

Immune Cell Infiltration ◽

Term Survival

Collagen type VI alpha 6 chain (COL6A6), a novel collagen, has been considered as a tumor suppressor and therapeutic target in several tumors. However, the functional role of COL6A6 in immune cell infiltration and prognostic value in lung adenocarcinoma (LUAD) remains unknown. Here, we evaluated COL6A6 expression and its impact on survival among LUAD patients from The Cancer Genome Atlas (TCGA) and several other databases. COL6A6 was downregulated in LUAD tissues compared to normal tissues at both mRNA and protein levels. COL6A6 expression was negatively associated with pathological stage, tumor stage, and lymph node metastasis. High COL6A6 expression was a favorable prognostic factor in LUAD. Next, we explored the associations between COL6A6 expression and immune cell infiltration. COL6A6 expression was positively associated with the infiltration of B cells, T cells, neutrophils and dendritic cells. Additionally, the immune cell infiltration levels were associated with COL6A6 gene copy number in LUAD. Consistently, gene set enrichment analysis showed that various immune pathways were enriched in the LUAD samples with high COL6A6 expression, including pathways related to T cell activation and T cell receptor signaling. The impacts of COL6A6 on immune activity were further assessed by enrichment analysis of 50 COL6A6-associated immunomodulators. Thereafter, using Cox regression, we identified a seven-gene risk prediction signature based on the COL6A6-associated immunomodulators. The resulting risk score was an independent prognostic predictor in LUAD. Receiver operating characteristic curve analysis confirmed that the seven-gene signature had good prognostic accuracy in the TCGA-LUAD cohort and a Gene Expression Omnibus dataset. Finally, we constructed a clinical nomogram to predict long-term survival probabilities, and calibration curves verified its accuracy. Our findings highlight that COL6A6 is involved in tumor immunity, suggesting COL6A6 may be a potential immunotherapeutic target in LUAD. The proposed seven-gene signature is a promising prognostic biomarker in LUAD.

Download Full-text

RTP4 is a novel prognosis-related hub gene in cutaneous melanoma

Hereditas ◽

10.1186/s41065-021-00183-z ◽

2021 ◽

Vol 158 (1) ◽

Author(s):

Yiqi Li ◽

Jue Qi ◽

Jiankang Yang

Keyword(s):

Cutaneous Melanoma ◽

Gene Networks ◽

Immune Cell ◽

Cox Model ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Hub Genes ◽

Hub Gene ◽

Rank Analysis ◽

Prognostic Gene

Abstract Objective Melanoma accounts for 80% of skin cancer deaths. The pathogenesis of melanoma is regulated by gene networks. Thus, we aimed here to identify gene networks and hub genes associated with melanoma and to further identify their underlying mechanisms. Methods GTEx (normal skin) and TCGA (melanoma tumor) RNA-seq datasets were employed for this purpose. We conducted weighted gene co-expression network analysis (WGCNA) to identify key modules and hub genes associated with melanoma. Log-rank analysis and multivariate Cox model analysis were performed to identify prognosis genes, which were validated using two independent melanoma datasets. We also evaluated the correlation between prognostic gene and immune cell infiltration. Results The blue module was the most relevant for melanoma and was thus considered the key module. Intersecting genes were identified between this module and differentially expressed genes (DEGs). Finally, 72 genes were identified and verified as hub genes using the Oncomine database. Log-rank analysis and multivariate Cox model analysis identified 13 genes that were associated with the prognosis of the metastatic melanoma group, and RTP4 was validated as a prognostic gene using two independent melanoma datasets. RTP4 was not previously associated with melanoma. When we evaluated the correlation between prognostic gene and immune cell infiltration, we discovered that RTP4 was associated with immune cell infiltration. Further, RTP4 was significantly associated with genes encoding components of immune checkpoints (PDCD1, TIM-3, and LAG3). Conclusions RTP4 is a novel prognosis-related hub gene in cutaneous melanoma. The novel gene RTP4 identified here will facilitate the exploration of the molecular mechanism of the pathogenesis and progression of melanoma and the discovery of potential new target for drug therapy.

Download Full-text

Immuno-Genomic Landscape of Cutaneous Melanoma Identifies a Prognostic and Immunotherapeutically Relevant Gene Signature

10.21203/rs.3.rs-617208/v1 ◽

2021 ◽

Author(s):

Ronghua Yang ◽

Yidan Sun ◽

Tianqi Chen ◽

Jiehua Li ◽

Xiaobing Pi ◽

...

Keyword(s):

Risk Score ◽

Cutaneous Melanoma ◽

Immune Cell ◽

Gene Signature ◽

Low Risk ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Hub Genes ◽

Gene Set ◽

Immune Infiltration

Abstract BackgroundThe tumorigenesis of Skin cutaneous melanoma (SKCM) is still a mystery. Our study conducted a comprehensive analysis of the immune cell infiltration in the TME of SKCM. Based on the differential expression genes in the cluster grouped by the immune infiltration status, a set of hub genes related to the clinical prognosis of SKCM and tumor immune infiltration were explored.MethodsWe analyzed the immune cell infiltration in two independent cohorts, and then assessed the relationship between the internal pattern of immune cell infiltration and SKCM characteristics, including clinicopathological features, potential biological pathways and gene mutations. We further divided the three clusters of differential genes into two groups with different unique biological processes. The Signature gene-A gene set was mainly manifested as exon skipping (ES) in SKCM patients, while the Signature gene-B gene set has no obvious alternative splicing form. Subsequently, we not only analyzed the genetic variation of the two signatures, but also constructed a ceRNA regulatory network..LASSO Cox regression was utilized to find the immune infiltration signature and the risk score of SKCM. ResultWe finally obtained 13 Hub genes, and calculated the risk score based on the coefficient of each gene to further explore the impact of the high and low-risk score on the biologically related functions and prognosis of SKCM patients.The correlation between the risk score and the clinicopathological characteristics of SKCM patients indicated that the low risk score was associated with TMECluster-A classification (P <0.001) and metastatic SKCM (P <0.001). We finally obtained 13 Hub genes which showed different prognostic effects in pan-cancers. The IHC staining results showed that Ube2L6, SRPX2, IFIT2 were higher expression while CLEC4E, END3, KIR2DL4 were lower expression in 25 melanoma specimens.ConclusionWe performed a comprehensive assessment of SKCM's immune environment and constructed a set of unprecedented immune signatures related to the immune landscape (EDN3、CLEC4E、SRPX2、KIR2DL4、UBE2L6、IFIT2), which are correlated with the different prognosis and drug response of SKCM. The immune gene signature we constructed can be used as a robust prognostic biomarker of SKCM and a predictor of immunotherapy effect.

Download Full-text

Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysis

Journal of Translational Medicine ◽

10.1186/s12967-020-02698-x ◽

2021 ◽

Vol 19 (1) ◽

Cited By ~ 1

Author(s):

Xingwang Zhao ◽

Longlong Zhang ◽

Juan Wang ◽

Min Zhang ◽

Zhiqiang Song ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Lupus Erythematosus ◽

Immune Cell ◽

Expression Profiles ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Tissue Destruction ◽

Systemic Lupus ◽

Ppi Networks

Abstract Background Systemic lupus erythematosus (SLE) is a multisystemic, chronic inflammatory disease characterized by destructive systemic organ involvement, which could cause the decreased functional capacity, increased morbidity and mortality. Previous studies show that SLE is characterized by autoimmune, inflammatory processes, and tissue destruction. Some seriously-ill patients could develop into lupus nephritis. However, the cause and underlying molecular events of SLE needs to be further resolved. Methods The expression profiles of GSE144390, GSE4588, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between SLE and healthy samples. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichments of DEGs were performed by metascape etc. online analyses. The protein–protein interaction (PPI) networks of the DEGs were constructed by GENEMANIA software. We performed Gene Set Enrichment Analysis (GSEA) to further understand the functions of the hub gene, Weighted gene co‐expression network analysis (WGCNA) would be utilized to build a gene co‐expression network, and the most significant module and hub genes was identified. CIBERSORT tools have facilitated the analysis of immune cell infiltration patterns of diseases. The receiver operating characteristic (ROC) analyses were conducted to explore the value of DEGs for SLE diagnosis. Results In total, 6 DEGs (IFI27, IFI44, IFI44L, IFI6, EPSTI1 and OAS1) were screened, Biological functions analysis identified key related pathways, gene modules and co‐expression networks in SLE. IFI27 may be closely correlated with the occurrence of SLE. We found that an increased infiltration of moncytes, while NK cells resting infiltrated less may be related to the occurrence of SLE. Conclusion IFI27 may be closely related pathogenesis of SLE, and represents a new candidate molecular marker of the occurrence and progression of SLE. Moreover immune cell infiltration plays important role in the progession of SLE.

Download Full-text

Development of an Immune-Related Gene Signature for Prognosis in Melanoma

Frontiers in Oncology ◽

10.3389/fonc.2020.602555 ◽

2021 ◽

Vol 10 ◽

Author(s):

Jia-An Zhang ◽

Xu-Yue Zhou ◽

Dan Huang ◽

Chao Luan ◽

Heng Gu ◽

...

Keyword(s):

T Cells ◽

Immune Cell ◽

Treatment Method ◽

Gene Signature ◽

Cell Infiltration ◽

Venn Diagram ◽

Immune Cell Infiltration ◽

Tumor Purity ◽

New Treatment ◽

Immune Related Genes

Melanoma remains a potentially deadly malignant tumor. The incidence of melanoma continues to rise. Immunotherapy has become a new treatment method and is widely used in a variety of tumors. Original melanoma data were downloaded from TCGA. ssGSEA was performed to classify them. GSVA software and the "hclust" package were used to analyze the data. The ESTIMATE algorithm screened DEGs. The edgeR package and Venn diagram identified valid immune-related genes. Univariate, LASSO and multivariate analyses were used to explore the hub genes. The "rms" package established the nomogram and calibrated the curve. Immune infiltration data were obtained from the TIMER database. Compared with that of samples in the high immune cell infiltration cluster, we found that the tumor purity of samples in the low immune cell infiltration cluster was higher. The immune score, ESTIMATE score and stromal score in the low immune cell infiltration cluster were lower. In the high immune cell infiltration cluster, the immune components were more abundant, while the tumor purity was lower. The expression levels of TIGIT, PDCD1, LAG3, HAVCR2, CTLA4 and the HLA family were also higher in the high immune cell infiltration cluster. Survival analysis showed that patients in the high immune cell infiltration cluster had shorter OS than patients in the low immune cell infiltration cluster. IGHV1-18, CXCL11, LTF, and HLA-DQB1 were identified as immune cell infiltration-related DEGs. The prognosis of melanoma was significantly negatively correlated with the infiltration of CD4+ T cells, CD8+ T cells, dendritic cells, neutrophils and macrophages. In this study, we identified immune-related melanoma core genes and relevant immune cell subtypes, which may be used in targeted therapy and immunotherapy of melanoma.

Download Full-text

Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.611058 ◽

2021 ◽

Vol 12 ◽

Author(s):

Zhuomao Mo ◽

Daiyuan Liu ◽

Dade Rong ◽

Shijun Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Cancer Genome ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Checkpoints ◽

Immune Cell Infiltration ◽

Immunosuppressive Microenvironment

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.

Download Full-text

SERPINE1 associated with remodeling of the tumor microenvironment in colon cancer progression: a novel therapeutic target

BMC Cancer ◽

10.1186/s12885-021-08536-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Shaokun Wang ◽

Li Pang ◽

Zuolong Liu ◽

Xiangwei Meng

Keyword(s):

Colorectal Cancer ◽

Colon Cancer ◽

Immune Cells ◽

Immune Cell ◽

Cox Regression ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

The Relationship

Abstract Background The change of immune cell infiltration essentially influences the process of colorectal cancer development. The infiltration of immune cells can be regulated by a variety of genes. Thus, modeling the immune microenvironment of colorectal cancer by analyzing the genes involved can be more conducive to the in-depth understanding of carcinogenesis and the progression thereof. Methods In this study, the number of stromal and immune cells in malignant tumor tissues were first estimated by using expression data (ESTIMATE) and cell-type identification with relative subsets of known RNA transcripts (CIBERSORT) to calculate the proportion of infiltrating immune cell and stromal components of colon cancer samples from the Cancer Genome Atlas database. Then the relationship between the TMN Classification and prognosis of malignant tumors was evaluated. Results By investigating differentially expressed genes using COX regression and protein-protein interaction network (PPI), the candidate hub gene serine protease inhibitor family E member 1 (SERPINE1) was found to be associated with immune cell infiltration. Gene Set Enrichment Analysis (GSEA) further projected the potential pathways with elevated SERPINE1 expression to carcinogenesis and immunity. CIBERSORT was subsequently utilized to investigate the relationship between the expression differences of SERPINE1 and immune cell infiltration and to identify eight immune cells associated with SERPINE1 expression. Conclusion We found that SERPINE1 plays a role in the remodeling of the colon cancer microenvironment and the infiltration of immune cells.

Download Full-text

Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis

10.21203/rs.2.12276/v1 ◽

2019 ◽

Author(s):

Yiling Cao ◽

Weihao Tang ◽

Wanxin Tang

Keyword(s):

Gene Expression ◽

Lupus Nephritis ◽

Molecular Mechanisms ◽

Immune Cell ◽

Expression Profiles ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Spearman Correlation ◽

Core Genes

Abstract Objects Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. Methods Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues of living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Result Five types of immune cells revealed important associations with LN, and monocytes emerged to be the prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features. Conclusion This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

Download Full-text

KRT17 Serves as an Oncogene and a Predictor of Poor Survival in Hepatocellular Carcinoma Patients

10.21203/rs.3.rs-117723/v1 ◽

2020 ◽

Author(s):

yuyan chen ◽

Jing Chen ◽

Zu-Cheng Tian ◽

Dan-Hua Zhou ◽

Ran Ji ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Cell ◽

Immune Cell ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Cancer Type ◽

Immune Cell Infiltration ◽

Functional Link ◽

Network Analyses ◽

Ppi Networks

Abstract Background: Hepatocellular carcinoma (HCC) is the second most common cancer-associated cause of death globally. It is thus vital that novel diagnostic and prognostic biomarkers associated with early-stage HCC be identified. While keratin 17 (KRT17) has previously been reported to be associated with certain cancer types, its relationship with HCC remains to be defined. Methods：The expression of KRT17 in the TCGA LIHC database and in 44 pairs of HCC patient samples was assessed via qRT-PCR, western blotting, and immunohistochemical staining. The prognostic relevance of KRT17 was assessed using Kaplan-Meir curves, while important cancer- and KRT17-related biological processes were defined through gene set enrichment analysis (GSEA). The functional link between KRT17 expression and tumor cell proliferation/survival was assessed through flow cytometry, colony formation assay, CCK-8 assay, and subcutaneous tumor model approaches. Protein-protein interaction (PPI) networks and analyses of immune cell infiltration were also employed to define key signaling pathways associated with KRT17 expression in HCC. Results：HCC tissue samples exhibited increased KRT17 mRNA and protein expression that was predictive of poorer patient survival (P<0.001). GSEA and functional experiments revealed that KRT17 functioned as a regulator of HCC tumor cell survival, proliferation, and cell cycle progression in vitro and in vivo. PPI network analyses also revealed that KRT17 expression was linked to immune cell infiltration and activation in patients with HCC. Conclusion: We found that increased KRT17 levels were associated with poorer survival, more aggressive disease, and altered immune cell infiltration in patients suffering from HCC. As such, KRT17 may function as an oncogene and a prognostic biomarker in this cancer type.

Download Full-text