CXCL12, A Potential Biomarker and A Vital Modulator of Tumor Immune Microenvironment (TIME) of Bladder Cancer: From A Comprehensive Analysis of TCGA Database

Abstract Background: Tumor immune microenvironment (TIME) played a significant role in the initiation and progression of bladder cancer (BC). However, there are few researches regarding the association between immune-related genes (IRGs) and tumor-infiltrating immune cells (TICs) in TME of BC. Methods: We calculated the proportion of immune/stromal component and TICs in TME of 414 BC samples and 19 normal samples downloaded from The Cancer Genome Atlas (TCGA) database with the help of ESTIMATE and CIBERSORT algorithms. Differentially expressed genes (DEGs) were obtained from the comparison between Stromal and Immune Score and further analyzed by GO and KEGG enrichment analysis, as well as protein–protein interaction (PPI) network and COX regression analysis. CXC chemokine ligand-12 (CXCL12) was overlapping from the above analysis. Afterwards, single gene analysis of CXCL12 was carried out through difference analysis, paired analysis and Gene Set Enrichment Analysis (GSEA). The association between the expression of CXCL12 and TICs was assessed by difference analysis and correlation analysis.Results: The results indicated that immune and stromal component in TME of BC were associated with patients’ clinic-pathological characteristics. We further confirmed that 284 DEGs were primarily enriched in immune-associated activities and CXCL12 was the most significant gene, which shared the leading nodes in PPI network and closely related with BC patients’ survival. Single gene analysis revealed that CXCL12 was down-regulated in BC samples and significantly related with the clinic-pathological characteristics of patients. Further analysis indicated that CXCL12 greatly participated in immune-associated activities through closely communicating with TICs in TIME of BC.Conclusions: CXCL12 might be a potential biomarker and a vital modulator of TIME through communicating with multiple TICs, which might provide an extra insight for the immunotherapy of BC.

Download Full-text

TGFβ1: an Indicator for Tumor Immune Microenvironment (TIME) of Colon Cancer from a Comprehensive Analysis of TCGA

10.21203/rs.3.rs-69238/v1 ◽

2020 ◽

Author(s):

Jinyan Wang ◽

Jinqiu Wang ◽

Quan Gu ◽

Yan Yang ◽

Yajun Ma ◽

...

Keyword(s):

Colon Cancer ◽

Cox Regression ◽

Enrichment Analysis ◽

Ppi Network ◽

Immune Microenvironment ◽

Cox Regression Analysis ◽

Difference Analysis ◽

Stromal Component ◽

Tumor Immune Microenvironment ◽

The Difference

Abstract Background: Tumor microenvironment (TME) and tumor-infiltrating immune cells (TIC) greatly participated in the genesis and development of colon cancer (CC). However, there are few researches exploring the dynamic modulation of TME. Methods: In our study, we analyzed the proportion of immune/stromal component and TIC in TME of 473 CC samples and 41 normal samples from The Cancer Genome Atlas (TCGA) database through ESTIMATE and CIBERSORT algorithm. Correlation analysis was carried out to evaluate the association between immune/stromal component in TME and clinicopathological characteristics of CC patients. The difference analysis was performed to obtain the differentially expressed genes (DEGs). These DEGs were further analyzed by gene ontology (GO), kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses, protein–protein interaction (PPI) network construction and COX regression analysis. Transforming growth factor β1 (TGFβ1) was finally overlapping from the above analysis. Furthermore, TGFβ1 was analyzed by paired analysis, Gene Set Enrichment Analysis (GSEA). The intersection between the difference analysis and correlation analysis was also conducted to learn the association between TGFβ1 and TICs.Results: Our result showed that immune component in TME was negatively related with the stages of CC. GO and KEGG enrichment analysis revealed that 1110 DEGs obtained from difference analysis were mainly enriched in immune-related activities. The intersection analysis between PPI network and COX regression analysis indicted that TGFβ1 was significantly associated with the communication of genes in PPI network and the Hazard Ratio (HR) of CC patients’ survival. In addition, TGFβ1 was up-regulated in the tumor samples and significantly related with poor prognosis of CC patients. Further GSEA suggested that genes in TGFβ1 up-regulated group were primarily enriched in immune-related activities and the function of TGFβ1 might depend on the communications with TICs, including T cells CD4 naïve and T cells regulatory (Tregs). Conclusions: The expression of TGFβ1 might be an indicator for tumor immune microenvironment (TIME) of CC and sever as a prognostic factor of CC. Drugs targeting TGFβ1 might be a potential immunotherapy for CC patients in the future.

Download Full-text

TGFβ1: An Indicator for Tumor Immune Microenvironment of Colon Cancer From a Comprehensive Analysis of TCGA

Frontiers in Genetics ◽

10.3389/fgene.2021.612011 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jinyan Wang ◽

Jinqiu Wang ◽

Quan Gu ◽

Yan Yang ◽

Yajun Ma ◽

...

Keyword(s):

Colon Cancer ◽

Regression Analysis ◽

Cox Regression ◽

Ppi Network ◽

Immune Microenvironment ◽

Cox Regression Analysis ◽

Difference Analysis ◽

Stromal Component ◽

Tumor Immune Microenvironment ◽

The Difference

BackgroundTumor microenvironment (TME) and tumor-infiltrating immune cells (TICs) greatly participate in the genesis and development of colon cancer (CC). However, there is little research exploring the dynamic modulation of TME.MethodsWe analyzed the proportion of immune/stromal component and TICs in the TME of 473 CC samples and 41 normal samples from The Cancer Genome Atlas (TCGA) database through ESTIMATE and CIBERSORT algorithms. Correlation analysis was conducted to evaluate the association between immune/stromal component in the TME and clinicopathological characteristics of CC patients. The difference analysis was performed to obtain the differentially expressed genes (DEGs). These DEGs were further analyzed by GO and KEGG enrichment analyses, PPI network, and COX regression analysis. Transforming growth factor β1 (TGFβ1) was finally overlapped from the above analysis. Paired analysis and GSEA were carried out to understand the role of TGFβ1 in colon cancer. The intersection between the difference analysis and correlation analysis was conducted to learn the association between TGFβ1 and TICs.ResultsOur results showed that the immune component in the TME was negatively related with the stages of CC. GO and KEGG enrichment analysis revealed that 1,110 DEGs obtained from the difference analysis were mainly enriched in immune-related activities. The intersection analysis between PPI network and COX regression analysis indicated that TGFβ1 was significantly associated with the communication of genes in the PPI network and the survival of CC patients. In addition, TGFβ1 was up-regulated in the tumor samples and significantly related with poor prognosis of CC patients. Further GSEA suggested that genes in the TGFβ1 up-regulated group were enriched in immune-related activities and the function of TGFβ1 might depend on the communications with TICs, including T cells CD4 naïve and T cells regulatory.ConclusionThe expression of TGFβ1 might be an indicator for the tumor immune microenvironment of CC and serve as a prognostic factor. Drugs targeting TGFβ1 might be a potential immunotherapy for CC patients in the future.

Download Full-text

CCL19 has potential to be a prognostic biomarker and a modulator of tumor immune microenvironment (TIME) of breast cancer: a comprehensive analysis based on TCGA database

10.21203/rs.3.rs-87457/v1 ◽

2020 ◽

Author(s):

Jinyan Wang ◽

Jinqiu Wang ◽

Quan Gu ◽

Yan Yang ◽

Yajun Ma ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Cells ◽

Immune Cells ◽

Prognostic Biomarker ◽

Comprehensive Analysis ◽

Ppi Network ◽

Intrinsic Properties ◽

Immune Microenvironment ◽

Stromal Component ◽

Tumor Immune Microenvironment

Abstract The development of cancer was determined by not only the intrinsic properties of cancer cells, but also the communication between cancer cells and tumor microenvironment (TME). We applied ESTIMATE and CIBERSORT algorithms to calculate the immune/stromal component and tumor-infiltrating immune cells (TICs) in TME of BC. The results showed that immune component in TME predicted patients’ survival and associated with progression of BC. Differentially expressed genes (DEGs) were primarily enriched in immune-related activities. Finally, CCL19 was acquired which shared the leading nodes in PPI network and was associated with patients’ survival. High expression of CCL19 predicted better prognosis and participated in progression of BC. Genes in CCL19 up-regulated group were enriched in immune-related activities and these functions might depend on the communications between CCL19 and multiple TICs in TIME. In conclusion, CCL19 functioned as a potential prognostic biomarker and a modulator of TIME in BC through communicating with various TICs.

Download Full-text

Alteration in the immune microenvironment based on APC status in MSS/pMMR colon cancer data retrieved from TCGA

10.21203/rs.3.rs-56379/v1 ◽

2020 ◽

Author(s):

Haishan Lin ◽

Hongchao Zhen ◽

Kun Shan ◽

Xiaoting Ma ◽

Bangwei Cao

Keyword(s):

Colon Cancer ◽

Cancer Patients ◽

Enrichment Analysis ◽

Tumor Immunotherapy ◽

Immune Checkpoints ◽

Immune Microenvironment ◽

Cancer Data ◽

T Cell Infiltration ◽

Colon Cancers ◽

Tumor Immune Microenvironment

Abstract Immunotherapy is currently the most advanced anti-tumor treatment approach. The efficacy of anti-tumor immunotherapy is closely related to the tumor immune microenvironment, including immune cells, infiltration of immune factors, and expression of immune checkpoints. At present, the biomarkers for predicting the efficacy of colon cancer immunotherapy do not cover all colon cancer patients suitable for immunotherapy. In this study, TCGA database was used to identify tumor genotypes suitable for anti-tumor immunotherapy. We found that some of the MSS/pMMR populations, that were initially considered unsuitable for immunotherapy, might actually be suitable. In APC-wt/MSS colon cancer, the expression of PD-1, PD-L1, CTLA4 and CYT（GZMA and PRF1）were increased. Based on calculations done by ESTIMATE and CIBERSORT algorithms, the ImmunoScore and the proportion of CT8+ T cell infiltration is increased in these patients. Enrichment analysis was done to screen signaling pathways involved in immune response, extracellular matrix, and cell adhesion. Tumors from 42 colon cancer patients, including 22 APC-mt/MSS and 20 APC-wt/MSS, were immunohistochemically evaluated for expression of CD8 and PD-L1. And APC-wt/MSS tumors showed significantly higher expression of CD8 and PD-L1 than APC-mt/MSS tumor. Based on the results, we found that some colon cancers of APC-wt/MSS are classified by Tumor Immune Microenvironment types (TIMTs) TMIT I. So that we speculate that APC-wt/MSS colon cancer patients could benefit from anti-tumor immunotherapy.

Download Full-text

Tumor Expression Profile Analysis Developed and Validated a Prognostic Model Based on Immune-Related Genes in Bladder Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.696912 ◽

2021 ◽

Vol 12 ◽

Author(s):

Bingqi Dong ◽

Jiaming Liang ◽

Ding Li ◽

Wenping Song ◽

Shiming Zhao ◽

...

Keyword(s):

Bladder Cancer ◽

Regression Analysis ◽

Malignant Tumors ◽

Immune Therapy ◽

Enrichment Analysis ◽

R Package ◽

Gene Set Enrichment Analysis ◽

Lasso Regression ◽

Potential Biomarker ◽

Immune Related Genes

Background: Bladder cancer (BLCA) ranks 10th in incidence among malignant tumors and 6th in incidence among malignant tumors in males. With the application of immune therapy, the overall survival (OS) rate of BLCA patients has greatly improved, but the 5-year survival rate of BLCA patients is still low. Furthermore, not every BLCA patient benefits from immunotherapy, and there are a limited number of biomarkers for predicting the immunotherapy response. Therefore, novel biomarkers for predicting the immunotherapy response and prognosis of BLCA are urgently needed.Methods: The RNA sequencing (RNA-seq) data, clinical data and gene annotation files for The Cancer Genome Atlas (TCGA) BLCA cohort were extracted from the University of California, Santa Cruz (UCSC) Xena Browser. The BLCA datasets GSE31684 and GSE32894 from the Gene Expression Omnibus (GEO) database were extracted for external validation. Immune-related genes were extracted from InnateDB. Significant differentially expressed genes (DEGs) were identified using the R package “limma,” and Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for the DEGs were performed using R package “clusterProfiler.” Least absolute shrinkage and selection operator (LASSO) regression analysis were used to construct the signature model. The infiltration level of each immune cell type was estimated using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The performance of the model was evaluated with receiver operating characteristic (ROC) curves and calibration curves.Results: In total, 1,040 immune-related DEGs were identified, and eight signature genes were selected to construct a model using LASSO regression analysis. The risk score of BLCA patients based on the signature model was negatively correlated with OS and the immunotherapy response. The ROC curve for OS revealed that the model had good accuracy. The calibration curve showed good agreement between the predictions and actual observations.Conclusions: Herein, we constructed an immune-related eight-gene signature that could be a potential biomarker to predict the immunotherapy response and prognosis of BLCA patients.

Download Full-text

Tumor immune microenvironment drives prognostic relevance correlating with bladder cancer subtypes

European Urology Supplements ◽

10.1016/s1569-9056(19)31049-8 ◽

2019 ◽

Vol 18 (1) ◽

pp. e1455-e1456 ◽

Cited By ~ 1

Author(s):

P. Strissel ◽

C. Pfannstiel ◽

K. Chiappinelli ◽

D. Sikic ◽

S. Wach ◽

...

Keyword(s):

Bladder Cancer ◽

Immune Microenvironment ◽

Cancer Subtypes ◽

Prognostic Relevance ◽

Tumor Immune Microenvironment

Download Full-text

DDX10 Promotes the Proliferation and Metastasis of Colorectal Cancer Cells via Splicing RPL35

10.21203/rs.3.rs-907936/v1 ◽

2021 ◽

Author(s):

Xin Zhou ◽

Zhihong Liu ◽

Cuifeng Zhang ◽

Manman Jiang ◽

Yuxiao Jin ◽

...

Keyword(s):

Colorectal Cancer ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Migration And Invasion ◽

Ppi Network ◽

Interacting Protein ◽

Network Analyses ◽

Potential Biomarker

Abstract Background: Colorectal cancer (CRC) has become the second deadliest cancer in the world and severely threatens human health. An increasing number of studies have focused on the role of the RNA helicase DEAD-box (DDX) family in CRC. However, the mechanism of DDX10 in CRC has not been elucidated.Methods: In our study, we analysed the expression data of CRC samples from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Subsequently, we performed cytological experiments and animal experiments to explore the role of DDX10 in CRC cells. Furthermore, we performed Gene Ontology (GO)/ Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network analyses. Finally, we predicted the interacting protein of DDX10 by LC-MS/MS and verified it by coimmunoprecipitation (Co-IP) and qPCR.Results: In the present study, we identified that DDX10 mRNA was extremely highly expressed in CRC tissues compared with normal colon tissues in the TCGA and GEO databases. The protein expression of DDX10 was measured by immunochemistry (IHC) in 17 CRC patients. The biological roles of DDX10 were explored via cell and molecular biology experiments in vitro and in vivo and cell cycle assays. We found that DDX10 knockdown markedly reduced CRC cell proliferation, migration and invasion. Then, we constructed a PPI network with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). GO and KEGG enrichment analysis and gene set enrichment analysis (GSEA) showed that DDX10 was closely related to RNA splicing and E2F targets. Using LC-MS/MS and Co-IP assays, we discovered that RPL35 is the interacting protein of DDX10. In addition, we hypothesize that RPL35 is related to the E2F pathway and the immune response in CRC.Conclusions: In conclusion, provides a better understanding of the molecular mechanisms of DDX10 in CRC and provides a potential biomarker for the diagnosis and treatment of CRC.

Download Full-text

Pseudogene HLA-DRB6 Regulates Immune Microenvironment of Cutaneous Melanoma by miR-338/CXCL10 Axis

10.21203/rs.3.rs-1228103/v1 ◽

2022 ◽

Author(s):

Jianmin Ren ◽

Jinglu Yu ◽

Yang Shi ◽

Inam Ullah Khan ◽

Jiansheng Huang

Keyword(s):

Single Cell ◽

Immune Cells ◽

Cutaneous Melanoma ◽

Target Genes ◽

Mrna Levels ◽

Sequencing Data ◽

Immune Microenvironment ◽

Potential Biomarker ◽

Tumor Immune Microenvironment ◽

The Relationship

Abstract Background: The relationship between the pseudogene and tumor immune microenvironment in cutaneous melanoma is unclear. In this study, we analyzed the role of the pseudogene HLA-DRB6 and its effect on the tumor immune microenvironment in skin cutaneous melanoma (SKCM) using bioinformatics tools. Method: The GEPIA database was used to analyze the expression of HLA-DRB6 and CXCL10 mRNA in tumor tissues. The TIMER database was used to analyze the relationship between mRNA levels and the infiltration of immune cells. The enrichment of HLA-DRB6 and CXCL10 in melanoma tissues was analyzed by single cell portal. The binding sites of HLA-DRB6 with its target genes was predicted via starBase database. The gene expression profiling and clinical data from GEO database (GSE94873) was used to verify the potential of CXCL10 as a biomarker. Result: The expression of HLA-DRB6 in SKCM tumor is higher than in normal tissues, and patients with high HLA-DRB6 expression had a better prognosis (P<0.05). Furthermore, HLA-DRB6 is positively correlated with the infiltration of immune cells such as B cells, CD4+ T, and CD8+ T lymphocytes, and the expression of immune checkpoint molecules such as PD-1, PD-L1, and CTLA-4. Single cell transcriptome sequencing data showed that HLA-DRB6 is mainly enriched in macrophages and had the highest correlation with CXCL10 than other chemokines (cor=0.66, P<0.0001). In addition, we found that CXCL10 can be used as a potential biomarker for predicting responsiveness and survival rate in SKCM patients who treated with Tremelimumab (a human anti-CTLA-4 antibody). Conclusion: In the microenvironment of SKCM, HLA-DRB6 is mainly enriched in macrophages and regulates the expression of CXCL10 through the ceRNA mechanism. Furthermore, the CXCL10 in peripheral blood can be used as a biomarker to predict the responsiveness and the prognosis for patients treated with tremelimumab.

Download Full-text