scholarly journals Identification of Tumor Microenvironment-related Prognostic Genes in Colorectal Cancer based on Bioinformatic Methods

2021 ◽  
Author(s):  
Yi Liu ◽  
Long Cheng ◽  
Chao Li ◽  
Chen Zhang ◽  
Wang Lei ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Networks ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

Abstract Colorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to malignant progression of CRC (stage, p=0.014; metastasis, p=0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein-protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine-cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in an independent cohort (GSE17386). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.

scholarly journals Identification of tumor microenvironment-related prognostic genes in colorectal cancer based on bioinformatic methods

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yi Liu ◽  
Long Cheng ◽  
Chao Li ◽  
Chen Zhang ◽  
Lei Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Ppi Networks ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

AbstractColorectal cancer (CRC) ranks fourth among the deadliest cancers globally, and the progression is highly affected by the tumor microenvironment (TME). This study explores the relationship between TME and colorectal cancer prognosis and identifies prognostic genes related to the CRC microenvironment. We collected the gene expression data from The Cancer Genome Atlas (TCGA) and calculated the scores of stromal/immune cells and their relations to clinical outcomes in colorectal cancer by the ESTIMATE algorithm. Lower immune scores were significantly related to the malignant progression of CRC (metastasis, p = 0.001). We screened 292 differentially expressed genes (DEGs) by dividing CRC cases into high and low stromal/immune score groups. Functional enrichment analyses and protein–protein interaction (PPI) networks illustrated that these DEGs were closely involved in immune response, cytokine–cytokine receptor interaction, and chemokine signaling pathway. Six DEGs (FABP4, MEOX2, MMP12, ERMN, TNFAIP6, and CHST11) with prognostic value were identified by survival analysis and validated in two independent cohorts (GSE17538 and GSE161158). The six DEGs were significantly related to immune cell infiltration levels based on the Tumor Immune Estimation Resource (TIMER). The results might contribute to discovering new diagnostic and prognostic biomarkers and new treatment targets for colorectal cancer.

scholarly journals Comprehensive analysis of tumor microenvironment landscape and potential therapeutic agents based on tumor-infiltrating immune cells in colorectal cancer

2021 ◽  
Author(s):  
Wenhui Zhong ◽  
Feng Zhang ◽  
Xin Lu ◽  
Kaijun Huang ◽  
Junming Bi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Transforming Growth Factor ◽  
Immune Cell ◽  
Cancer Therapeutics ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Chemotherapy Drugs ◽  
Drug Compounds

Abstract Background: Tumor-infiltrating immune cells (TIIC) are the major components of the tumor microenvironment (TME) and play vital roles in the tumorigenesis and progression of colorectal cancer (CRC). Increasing evidence has elucidated their significances in predicting prognosis and therapeutic efficacy. Nonetheless, the immune infiltrative landscape of CRC remains largely unknown. Methods: All the RNA-seq transcriptome data and full clinical annotation of 1213 colorectal cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene-Expression Omnibus (GEO) database. The “CIBERSORT” and “estimate” R package were applied to calculate 22 infiltrated immune cell fractions and stromal and immune score. Three TIIC patterns were determined by Unsupervised clustering methods. Through using principal-component analysis, TIIC scores were established. Data for potential agents comes from the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) and Cancer Therapeutics Response Portal database (CTRP). Results：In this study, we identified three distinct TIIC patterns characterized by distinct immunological features in 1213 CRC samples from multiple platforms. Base on the TIIC-related gene signatures from three clusters, we constructed a scoring system to quantify the immune infiltration level of individual samples in the CRC cohort and the clinical benefits of different groups. The high TIIC score group was marked by increased immune activation status and favorable prognosis. Conversely, low TIIC score group was featured with immune-desert phenotype and poor prognosis, along with the activation of transforming growth factor-β (TGF-β), WNT, ECM receptor interaction, and VEGF signaling pathways. Meanwhile, the high TIIC score group was also correlated with enhanced efficacy of immunotherapy. Additional, four chemotherapy drugs, seven CTRP-derived drug compounds and six PRISM-derived drug compounds were identified as potential drug for CRC among high and low TIIC subgroups.Conclusions: Collectively, as an effective prognostic biomarker and predictive indicator, the TIIC score plays an important role in the evaluation of CRC prognosis and the response of immunotherapy. Investigation of the TIIC patterns might provide us a promising target for improving immunotherapeutic efficacy in CRC.

scholarly journals Effects of Hypoxia in Intestinal Tumors on Immune Cell Behavior in the Tumor Microenvironment

2020 ◽  
Author(s):  
Luping Zhang ◽  
Shaokun Wang ◽  
Yachen Wang ◽  
Weidan Zhao ◽  
Yingli Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Risk Score ◽  
Immune Cell ◽  
Risk Groups ◽  
Low Risk ◽  
Computational Method ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Behavior

Abstract Background: Imbalanced nutritional supply and demand in the tumor microenvironment often leads to hypoxia. The subtle interaction between hypoxia and immune cell behavior plays an important role in tumor occurrence and development. However, the functional relationship between hypoxia and the tumor microenvironment remains unclear. Therefore, we aimed to investigate the effect of hypoxia on the intestinal tumor microenvironment.Method: We extracted the names of hypoxia-related genes from the Gene Set Enrichment Analysis (GSEA) database and screened them for those associated with the prognosis of colorectal cancer, with the final list including ALDOB, GPC1, ALDOC, and SLC2A3. Using the sum of the expression levels of these four genes, provided by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and the expression coefficients, we developed a hypoxia risk score model. Using the median risk score value, we divided the patients in the two databases into high- and low-risk groups.GSEA was used to compare the enrichment differences between the two groups.We used the CIBERSORT computational method to analyze immune cell infiltration.Finally,the correlation between these five genes and hypoxia was analyzed. Result: The prognosis of the two groups differed significantly, with a higher survival rate in the low-risk group than in the high-risk group.We found that the different risk groups were enriched by immune-related and inflammatory pathways. We identified activated CD4 memory T cells and M0 macrophages in TCGA and GEO databases and found that CCL2/4/5, CSF1, and CX3CL1 contributed toward the increased infiltration rate of these immune cell types. Finally, we observed a positive correlation between the five candidate genes’ expression and the risk of hypoxia, with significant differences in the level of expression of each of these genes between patient risk groups.Conclusion: Overall, our data suggest that hypoxia is associated with the prognosis and rate of immune system infiltration in patients with colorectal cancer. This finding may improve immunotherapy for colorectal cancer.

scholarly journals Identification of prognostic immune-related gene signature associated with tumor microenvironment of colorectal cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yuanyuan Wang ◽  
Wei Li ◽  
Xiaojing Jin ◽  
Xia Jiang ◽  
Shang Guo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Clinical Parameters ◽  
Cox Regression Analysis ◽  
Ppi Networks ◽  
Tumor Purity ◽  
Immune Related Genes ◽  
Immune Score

Abstract Background The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC). Methods Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database. Results Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717–0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates. Conclusions In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.

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

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.

scholarly journals The possible role of SRMS in colorectal cancer by bioinformatics analysis

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jie Zhang ◽  
Weidong Liu ◽  
Sisi Feng ◽  
Baiyun Zhong
Keyword(s):  
Colorectal Cancer ◽  
Immune Cell ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Marker Genes ◽  
Cell Marker ◽  
Translational Initiation ◽  
Expression Levels

Abstract Background Src-related kinase lacking C-terminal regulatory tyrosine and N-terminal myristoylation sites (SRMS) is a non-receptor tyrosine kinase that has been found to be overexpressed in various tumors. However, the role of SRMS in colorectal cancer (CRC) has not been well established. Methods We evaluated the expression levels of SRMS in CRC using GEPIA, Oncomine, and HPA datasets. Survival information and gene expression data of CRC were obtained from The Cancer Genome Atlas (TCGA). Then, the association between SRMS and clinicopathological features was analyzed using UALCAN dataset. LinkedOmics was used to determine co-expression and functional networks associated with SRMS. Besides, we used TISIDB to assess the correlation between SRMS and immune signatures, including tumor-infiltrating immune cells and immunomodulators. Lastly, protein-protein interaction network (PPI) was established and the function enrichment analysis of the SRMS-associated immunomodulators and immune cell marker genes were performed using the STRING portal. Results Compared to normal colorectal tissues, SRMS was found to be overexpressed in CRC tissues, which was correlated with a poor prognosis. In colon adenocarcinoma (COAD), the expression levels of SRMS are significantly correlated with pathological stages and nodal metastasis status. Functional network analysis suggested that SRMS regulates intermediate filament-based processes, protein autophosphorylation, translational initiation, and elongation signaling through pathways involving ribosomes, proteasomes, oxidative phosphorylation, and DNA replication. In addition, SRMS expression was correlated with infiltrating levels of CD4+ T cells, CD56dim, MEM B, Neutrophils, Th2, Th17, and Act DC. The gene ontology (GO) analysis of SRMS-associated immunomodulators and immune cell marker genes showed that they were mainly enriched in the immune microenvironment molecule-related signals. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of these genes indicated that they are involved in multiple cancer-related pathways. Conclusions SRMS is a promising prognostic biomarker and potential therapeutic target for CRC patients. In particular, SRMS regulates CRC progression by modulating cytokine-cytokine receptor interaction, chemokines, IL-17, and intestinal immune networks for IgA production signaling pathways among others. However, more studies are needed to validate these findings.

The study of the significance and prognosis of the differential expressed miRNAs and their target genes associated with biological in colorectal cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15088-e15088
Author(s):  
Mingyun Wang ◽  
Mi Yang
Keyword(s):  
Colorectal Cancer ◽  
Target Genes ◽  
Biological Significance ◽  
Differentially Expressed ◽  
Prognostic Indicators ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Prognostic Information ◽  
Chemokine Signaling ◽  
Chemokine Signaling Pathway

e15088 Background: MicroRNAs (miRNAs) have been related to prognostic indicators (such as stage and survival) in colorectal cancer. This study aimed to identify differentially expressed miRNAs and their target genes associated with biological significance and prognosis in colorectal cancer. Methods: The colorectal cancer, colorectal adenoma, and normal samples were obtained from the gene expression profile of GSE71187. A union of differentially expressed genes (DEGs) in the three groups was identified. The significantly different modules with highly interconnected DEGs were identified using weighted correlation network analysis (WGCNA) and were enriched to the KEGG pathway and GO function. Subsequently, the protein-protein interaction (PPI) network for DEGs in the module and the integrated regulatory network of miRNA-DEGs were constructed. In addition, the relationship of target DEGs and prognostic information was analyzed. Results: Three significantly different modules were identified, such as the brown, turquoise, and grey modules. The turquoise module including LTC4S, KLRK1, UNC5C, etc., which was mainly enriched to cell adhesion, cytokine−cytokine receptor interaction, and chemokine signaling pathway, inhibited the development of colorectal cancer. Subsequently, PPI network was constructed with the 678 DEGs in the three modules. Moreover, the miRNA-DEGs network was constructed with the 17 target DEGs (CXCR1, LTC4S, BTK, IGF1, etc.) and 14 miRNA (hsa-miR-335-5p, etc.). Finally, the overexpressed LTC4S was a good prognostic biomarker for colorectal cancer. Conclusions: The hsa-miR-335-5p might have potential prognosis value by targeting LTC4S and CXCR1 in colorectal cancer.

scholarly journals Identification of a tumor microenvironment-related gene signature to improve the prediction of cervical cancer prognosis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qian Chen ◽  
Bingqing Qiu ◽  
Xiaoyun Zeng ◽  
Lang Hu ◽  
Dongping Huang ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Tumor Microenvironment ◽  
Prognostic Model ◽  
Immune Cell ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Risk Scores ◽  
Kaplan Meier ◽  
Cox Analysis

Abstract Background Previous studies have found that the microenvironment of cervical cancer (CESC) affects the progression and treatment of this disease. Thus, we constructed a multigene model to assess the survival of patients with cervical cancer. Methods We scored 307 CESC samples from The Cancer Genome Atlas (TCGA) and divided them into high and low matrix and immune scores using the ESTIMATE algorithm for differential gene analysis. Cervical cancer patients were randomly divided into a training group, testing group and combined group. The multigene signature prognostic model was constructed by Cox analyses. Multivariate Cox analysis was applied to evaluate the significance of the multigene signature for cervical cancer prognosis. Prognosis was assessed by Kaplan–Meier curves comparing the different groups, and the accuracy of the prognostic model was analyzed by receiver operating characteristic-area under the curve (ROC-AUC) analysis and calibration curve. The Tumor Immune Estimation Resource (TIMER) database was used to analyze the relationship between the multigene signature and immune cell infiltration. Results We obtained 420 differentially expressed genes in the tumor microenvironment from 307 patients with cervical cancer. A three-gene signature (SLAMF1, CD27, SELL) model related to the tumor microenvironment was constructed to assess patient survival. Kaplan–Meier analysis showed that patients with high risk scores had a poor prognosis. The ROC-AUC value indicated that the model was an accurate predictor of cervical cancer prognosis. Multivariate cox analysis showed the three-gene signature to be an independent risk factor for the prognosis of cervical cancer. A nomogram combining the three-gene signature and clinical features was constructed, and calibration plots showed that the nomogram resulted in an accurate prognosis for patients. The three-gene signature was associated with T stage, M stage and degree of immune infiltration in patients with cervical cancer. Conclusions This research suggests that the developed three-gene signature may be applied as a biomarker to predict the prognosis of and personalized therapy for CESC.

Crosstalk between the MSI status and tumor microenvironment in colorectal cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15236-e15236
Author(s):  
Peng Luo ◽  
Anqi Lin ◽  
Jian Zhang
Keyword(s):  
Colorectal Cancer ◽  
Tumor Microenvironment ◽  
Microsatellite Instability ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Immune Microenvironment ◽  
Mutation Data ◽  
Immune Related Genes

e15236 Background: In recent years, cancer immunotherapy has been extensively studied, and colorectal cancer (CRC) patients have also derived clinical benefits from immunotherapy, especially CRC patients with mismatch repair deficiency (dMMR)/microsatellite instability-high (MSI-H), whose sensitivity to immune checkpoint inhibitors (ICIs) is significantly higher than that of patients with microsatellite-stable (MSS)/microsatellite instability-low (MSI-L) disease. This study suggests that patients with MSI-H CRC have a higher mutational burden and more immune cell infiltration than those with MSS/MSI-L disease. However, most studies have not systematically evaluated the immune characteristics and immune microenvironments of MSI-H and MSS/MSI-L CRC. Methods: A published CRC cohort with mutation and immunotherapy-related prognostic data was collected. We analyzed the relationship between the MSI status and prognosis of ICI treatment in an immunotherapy cohort. We then further used mutation data for the immunotherapy and The Cancer Genome Atlas (TCGA)-CRC (colon adenocarcinoma (COAD) + rectum adenocarcinoma (READ) cohorts. For mRNA expression, mutation data analysis of the immune microenvironment and immunogenicity under different MSI status was performed. Results: Compared with MSS/MSI-L CRC patients, patients with MSI-H CRC significantly benefited from ICI treatment. We found that MSI-H CRC had more immune cell infiltration, higher expression of immune-related genes and higher immunogenicity than MSS/MSI-L disease. The MANTIS score used to predict the MSI status was positively correlated with immune cells, immune-related genes, and immunogenicity. In addition, subtype analysis showed that COAD and READ might have different tumor immune microenvironments. Conclusions: MSI-H CRC may have an inflammatory tumor microenvironment and increased sensitivity to ICIs. Unlike those of MSI-H READ, the immune characteristics of MSI-H COAD may be consistent with those of MSI-H CRC. Furthermore, the possible mechanism underlying the prognostic differences among CRC patients receiving ICIs in relation to the immune microenvironment were elucidated to provide theoretical guidance for further improving the curative effect of ICIs treatment on MSI-H CRC patients in the future and solve the problems underlying why MSS/MSI-L CRC patients do not benefit from ICIs treatment.

scholarly journals Bioinformatics Analysis to Screen the Key Prognostic Genes in Tumor Microenvironment of Bladder Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhao Zhang ◽  
Dongshan Chen ◽  
Zeyan Li ◽  
Zhao Liu ◽  
Lei Yan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bladder Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cancer Genomics ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Marker Genes ◽  
High Morbidity ◽  
Tumor Prognosis

Bladder cancer (BLCA) is the fifth most common cancer and has the features of low survival rate and high morbidity and mortality. The Cancer Genome Atlas (TCGA) is a pool of global gene expression profile and contains huge amounts of cancer genomics data, which makes it possible to inquire the relationship between gene expression and prognosis of a series of malignant tumors including BLCA. Immune and stromal cells are two major components of tumor microenvironment (TME) which play an important role in judging the prognosis of tumor and influencing the progression of malignant, inflammatory, and metabolic disorders. In our study, we conducted a quantitative analysis of immune and stromal elements based on the ESTIMATE algorithm and thus divided BLCA cases into high and low groups. Then the differentially expressed genes closely related to tumor prognosis between groups were identified and had been shown to correlate with immune response and stromal alterations, which was further confirmed by functional enrichment analysis and protein-protein interaction networks. We validated those genes through BLCA dates downloaded from ArrayExpress and thus got the marker genes to predict prognosis of BLCA. Additionally, immune cell infiltration analysis explored the correlation between the verified genes and immune cells. In conclusion, we identified a series of TME-related genes that assess the prognosis and explored the interaction between TME and tumor prognosis to guide clinical individualized treatment.

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