Profiles of tumor-infiltrating immune cells and prognostic genes associated with the microenvironment of bladder cancer

Bladder cancer immune-related markers: diagnosis, surveillance, and prognosis

As an immune-related tumor type, bladder cancer has been attracting much attention in the study of its markers. In recent years, researchers have made rapid progress in the study of immune-related markers for bladder cancer. Studies have shown that immune-related markers play an important role in the diagnosis, prognosis assessment and treatment of bladder cancer. In addition, the detection of immune-related markers can also be used to evaluate the efficacy of immunotherapy and predict the treatment response of patients. Therefore, in depth study of the expression of immune-related markers in bladder cancer and their application in the clinic is of great significance and is expected to provide new breakthroughs for individualized treatment of bladder cancer. Future studies will focus more on how to detect immune-related markers with low cost and high accuracy, as well as develop new immunotherapeutic strategies to bring better therapeutic outcomes to bladder cancer patients.

Clinical significance of KRT7 in bladder cancer prognosis

BACKGROUND

Typically, the overexpressed keratin 7 (KRT7) is considered a validated therapeutic target and prognosis marker in bladder cancer. However, the crucial roles of KRT7 in the clinical prognosis and immune microenvironment in bladder cancer remain unclear.

METHODS

Initially, the expression levels of KRT7 in public databases were analyzed that is,Tumor Immune Estimation Resource (TIMER) 2.0 and Gene Expression Profiling Interactive Analysis (GEPIA). Further, the clinical tissue samples from patients (n = 10 pairs) were collected to confirm the expression trends of KRT7 and detected by immunohistochemistry (IHC) analysis. Meanwhile, the relationship between KRT7 and the prognosis of bladder cancer patients was analyzed by Kaplan-Meier plotter estimation and Cox regression analysis. Finally, TIMER 2.0 and IHC staining analyses were performed to calculate the infiltration abundances of three kinds of immune cells in eligible bladder tumor samples.

RESULTS

The TIMER 2.0 and GEPIA datasets suggested the differences in the expression levels of KRT7 in tumors, in which KRT7 was significantly upregulated in bladder cancer. The KRT7 expression was closely associated with patients' gender, tumor histologic subtypes, T status, and American Joint Committee on Cancer stages. Notably, the increased KRT7 indicated poor overall survival and disease-free survival rates. Moreover, KRT7 expression could be responsible for immune infiltration in the cancer microenvironment of the bladder. Finally, the high expression level of KRT7 increased the presence of regulatory T cells (Tregs) but reduced the infiltration of CD8+ T and natural killer cells.

CONCLUSION

KRT7 as a biomarker potentiated the prediction of bladder cancer prognosis and the immune microenvironment.

MIF as a potential diagnostic and prognostic biomarker for triple-negative breast cancer that correlates with the polarization of M2 macrophages

Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine that plays a crucial role in antitumor immunity. However, the role of MIF in influencing the tumor microenvironment (TME) and prognosis of triple-negative breast cancer (TNBC) remains to be elucidated. Using R, we analyzed single-cell RNA sequencing (scRNA-seq) data of 41 567 cells from 10 TNBC tumor samples and spatial transcriptomic data from two patients. Relationships between MIF expression and immune cell infiltration, clinicopathological stage, and survival prognosis were determined using samples from The Cancer Genome Atlas (TCGA) and validated in a clinical cohort using immunohistochemistry. Analysis of scRNA-seq data revealed that MIF secreted by epithelial cells in TNBC patients could regulate the polarization of macrophages into the M2 phenotype, which plays a key role in modulating the TME. Spatial transcriptomic data also showed that epithelial cells (tumor cells) and MIF were proximally located. Analysis of TCGA samples confirmed that tumor tissues of patients with high MIF expression were enriched with M2 macrophages and showed a higher T stage. High MIF expression was significantly associated with poor patient prognosis. Immunohistochemical staining showed high MIF expression was associated with younger patients and worse clinicopathological staging. MIF secreted by epithelial cells may represent a potential biomarker for the diagnosis and prognosis of TNBC and may promote TNBC invasion by remodeling the tumor immune microenvironment.

Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer

BACKGROUNDS

Glucose metabolism is associated with the development of cancers, and m6A RNA methylation regulator-related genes play vital roles in bladder urothelial carcinoma (BLCA). However, the role of m6A-related glucose metabolism genes in BLCA occurrence and development has not yet been reported. Our study aims to integrate m6A- and glycolysis-related genes and find potential gene targets for clinical diagnosis and prognosis of BLCA patients.

METHODS

Sequencing data and clinical information on BLCA were extracted from common databases. Univariate Cox analysis was used to screen prognosis-related m6A glucose metabolism genes; BLCA subtypes were distinguished using consensus clustering analysis. Subsequently, genes associated with BLCA occurrence and development were identified using the "limma" R package. The risk score was then calculated, and a nomogram was constructed to predict survival rate of BLCA patients. Functional and immune microenvironment analyses were performed to explore potential functions and mechanisms of the different risk groups.

RESULTS

Based on 70 prognosis-related m6A glucose metabolism genes, BLCA was classified into two subtypes, and 34 genes associated with its occurrence and development were identified. Enrichment analysis revealed an association of genes in high-risk groups with tricarboxylic acid cycle function and glycolysis. Moreover, significantly higher levels of seven immune checkpoints, 14 immune checkpoint inhibitors, and 32 immune factors were found in high-risk score groups.

CONCLUSIONS

This study identified two biomarkers associated with BLCA prognosis; these findings may deepen our understanding of the role of m6A-related glucose metabolism genes in BLCA development. We constructed a m6A-related glucose metabolism- and immune-related gene risk model, which could effectively predict patient prognosis and immunotherapy response and guide individualized immunotherapy.

Duality of the SVIL expression in bladder cancer and its correlation with immune infiltration

SVIL is a member of the villin/gelsolin superfamily and is responsible for encoding supervillin. It has been reported to be closely related to the occurrence and development of various tumors. However, the mechanism of SVIL in bladder cancer has not been reported yet. In this research, we evaluated the relationship between SVIL expression and bladder cancer in public dataset and examined the expression of SVIL in bladder cancer cell lines, tissue microarrays and patients in our cohort. Our work determined that the expression of SVIL in bladder cancer tissue was significantly lower than that in normal tissue. However, in bladder cancer tissues, the high expression of SVIL is significantly associated with poor prognosis. This kind of duality is very novel and has great research value. The expression level of SVIL can well predict the survival time of bladder cancer patients, and is an independent risk factor of bladder cancer patients. The expression of SVIL is also closely related to the immune tumor microenvironment of bladder cancer. Our research provides a basis for personalized therapeutic targets for bladder cancer.

B7H3 Role in Reshaping Immunosuppressive Landscape in MSI and MSS Colorectal Cancer Tumours

The study aimed to assess the expression of B7H3 concerning clinicopathological and histological parameters, including MSI/MSS status, CD-8 cells, tumour-infiltrating lymphocytes (TILs), budding, TNM scale and grading. Moreover, we analyzed the B7H3-related pathways using available online datasets and the immunological context of B7H3 expression, through the 48-cytokine screening panel of cancer tissues homogenates, immunogenic features and immune composition. The study included 158 patients diagnosed with CRC. To assess B7H3 levels, we performed an immunohistochemistry method (IHC) and enzyme-linked immunosorbent assay (ELISA). To elucidate the immune composition of colorectal cancer, we performed the Bio-Plex Pro Human 48-cytokine panel. To study biological characteristics of B7H3, we used online databases. Expression of B7H3 was upregulated in CRC tumour tissues in comparison to adjacent noncancerous margin tissues. The concentrations of B7H3 in tumours were positively associated with T parameter of patients and negatively with tumour-infiltrating lymphocytes score. Additionally, Principal Component Analysis showed that B7H3 expression in tumours correlated positively with cytokines associated with M2-macrophages and protumour growth factors. The expression of B7H3 in tumours was independent of MSI/MSS status. These findings will improve our understanding of B7H3 role in colorectal cancer immunity. Our study suggests that B7-H3 is a promising potential target for cancer therapy. Further studies must clarify the mechanisms of B7H3 overexpression and its therapeutic importance in colorectal cancer.

Leucyl and Cystinyl Aminopeptidase as a Prognostic-Related Biomarker in OV Correlating with Immune Infiltrates

Background

It was indicated that tumor intrinsic heterogeneity and the tumor microenvironment (TME) of ovarian cancer (OV) influence immunotherapy efficacy and patient outcomes. Leucyl and cystinyl aminopeptidase (LNPEP) encodes a zinc-dependent aminopeptidase, which has been proved to participant in the vesicle-mediated transport and class I MHC mediated antigen processing and presentation. However, the function of LNPEP in TME of OV and its potential molecular mechanisms have not been determined. Therefore, we aimed to investigate a prognostic biomarker which may be helpful in identifying TME heterogeneity of ovarian cancer.

Methods

In this study, bioinformatics databases were used to explore the expression profile and immune infiltration of LNPEP. Bioinformatics analyses of survival data and interactors of LNPEP were conducted to predict the prognostic value of LNPEP in OV. The protein levels of LNPEP were validated by Western blot and immunohistochemistry.

Results

Based on the TCGA data, our data displayed that the mRNA expression of LNPEP was markedly down-regulated in ovarian cancer than that in para-cancer tissues, contrary to the protein level. Importantly, high LNPEP expression was associated with poor prognosis in patients with OV. Furthermore, Cox regression analysis showed that LNPEP was an independent prognostic factor in OV. GO and KEGG pathway analyses indicated the co-expressed genes of LNPEP were mainly related to a variety of immune-related pathways, including Th1 and Th2 cell differentiation, Th17 cell differentiation, and immunoregulatory interaction. Our data also demonstrated that the expression of LNPEP was strongly correlated with immune infiltration levels, immunomodulators, chemokines and chemokine receptors.

Conclusion

In our study, we identified and established a prognostic signature of immune-related LNPEP in OV, which will be of great value in predicting the prognosis of clinical trials and may become a new therapeutic target for immunological research and potential prognostic biomarker in OV.

B7H4 Expression Is More Frequent in MSS Status Colorectal Cancer and Is Negatively Associated with Tumour Infiltrating Lymphocytes

The immunotherapies based on ICIs in CRC are nowadays limited to microsatellite unstable tumours which are approximately 15% of all CRC cases. There are a few new immune checkpoints belonging to the B7 family, including B7H4. B7H4 expression is associated with so-called “cold tumours”, and its function is linked to the downregulation of various immune cell populations. Our study aimed to investigate whether B7H4 expression is dependent on microsatellite status in CRC and on elucidating the immunological context in which the expression of B7H4 occurs. We enrolled 167 patients in the study. We prepared the homogenates from tumour tissues and healthy adjacent tissue to assess the B7H4 levels and the Bio-Plex Pro Human 48-cytokine panel. We assessed the microsatellite status of the tumour, B7H4 expression, CD8+ T cell population, and the TILs and budding in H + E stained slides by the IHC method. We used an online available database for further exploring the biological characteristics of B7H4. The expression of B7H4 was more frequent in microsatellite stable tumours, and was negatively associated with TILs. B7H4 is positively correlated with antitumour immunosuppressive iTME, thus contributing to the immunosuppressive environment in CRC.

Role of Sostdc1 in skeletal biology and cancer

Sclerostin domain-containing protein-1 (Sostdc1) is a member of the sclerostin family and encodes a secreted 28–32 kDa protein with a cystine knot-like domain and two N-linked glycosylation sites. Sostdc1 functions as an antagonist to bone morphogenetic protein (BMP), mediating BMP signaling. It also interacts with LRP6, mediating LRP6 and Wnt signaling, thus regulating cellular proliferation, differentiation, and programmed cell death. Sostdc1 plays various roles in the skin, intestines, brain, lungs, kidneys, and vasculature. Deletion of Sostdc1 gene in mice resulted in supernumerary teeth and improved the loss of renal function in Alport syndrome. In the skeletal system, Sostdc1 is essential for bone metabolism, bone density maintenance, and fracture healing. Recently, Sostdc1 has been found to be closely related to the development and progression of multiple cancer types, including breast, renal, gastric, and thyroid cancers. This article summarises the role of Sostdc1 in skeletal biology and related cancers to provide a theoretical basis for the treatment of related diseases.

B7-H4 is a potential diagnostic and prognostic biomarker in colorectal cancer and correlates with the epithelial-mesenchymal transition

Background

As a negative co-stimulatory molecule of the B7 family, B7-H4 has recently attracted increased attention. However, the clinical value of B7-H4 in colorectal cancer (CRC) remains controversial and requires further investigation. This study aimed to investigate the role of B7-H4 in the clinical diagnosis and survival prognosis of CRC.

Methods

The relationships between B7-H4 expression, immune cell infiltration, epithelial-mesenchymal transition (EMT), clinicopathological features, and survival prognosis were determined through the TCGA database and verified in a large CRC cohort (n = 1118).

Results

The results showed the level of B7-H4 mRNA expression was significantly increased in the CRC tumor tissues compared with normal tissues (P <  0.001). Immunohistochemistry showed that B7-H4 protein expression was also up-regulated in CRC. The positive rate of B7-H4 in CRC tumor tissues was 76.38%, which was significantly higher than that in non-tumor tissues (P <  0.001). Overexpression of B7-H4 was positively correlated with lymph node metastasis, advanced TNM stage, and poor tumor differentiation (P = 0.012; 0.009; 0.014). Prognostic analysis showed high B7-H4 expression was associated with significantly shorter OS. Multivariate analysis demonstrated the risk of death in CRC patients with high B7-H4 expression is 1.487 times that of low B7-H4 expression. In addition, B7-H4 expression was negatively correlated with the epithelial marker E-cadherin (P <  0.001) and positively correlated with the mesenchymal marker vimentin (P <  0.001) in CRC tissues. However, B7-H4 expression was not associated with the immunosuppressive microenvironment in CRC.

Conclusion

B7-H4 may represent a potential biomarker for the diagnosis and prognosis of CRC and enhance CRC invasion by promoting EMT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10159-5.

Construction and validation of a gene signature related to bladder urothelial carcinoma based on immune gene analysis

BACKGROUND

This study developed a gene signature associated with a malignant and common tumor of the urinary system, the Bladder Urothelial Carcinoma (BLCA).

METHODS

The Cancer Genome Atlas (TCGA) database was searched to obtain 414 BLCA samples and the expression spectra of 19 normal samples. Single-sample Gene Set Enrichment Analysis (ssGSEA) was conducted to determine the enrichment levels in the BLCA samples of the 29 immune genes. Unsupervised hierarchical clustering, gene set enrichment analysis (GSEA), single-factor Cox analysis, least absolute shrinkage and selection operator (LASSO) regression models, and GEO queues were used to determine the BLCA immune gene subtype, analyze the biological pathway differences between immune gene subtypes, determine the characteristic genes of BLCA associated with prognosis, identify the BLCA-related genes, and verify the gene signature, respectively.

RESULTS

We identified two immune gene subtypes (immunity_L and immunity_H). The latter was significantly related to receptors, JAK STAT signaling pathways, leukocyte interleukin 6 generation, and cell membrane signal receptor complexes. Four characteristic genes (RBP1, OAS1, LRP1, and AGER) were identified and constituted the gene signature. Significant survival advantages, higher mutation frequency, and superior immunotherapy were observed in the low-risk group patients. The gene signature had good predictive ability. The results of the validation group were consistent with TCGA queue results.

CONCLUSIONS

We constructed a 4-gene signature that helps monitor BLCA occurrence and prognosis, providing an important basis for developing personalized BLCA immunotherapy.

Comprehensive analysis of the PD-L1 and immune infiltrates of N6-methyladenosine related long non-coding RNAs in bladder cancer

Bladder cancer (BLCA) is one of the most frequent genitourinary cancers, with a high rate of morbidity and mortality. The connection of m6A-related lncRNAs with PD-L1 and tumor immune microenvironment (TIME) in BLCA prognosis was extensively investigated in this study, which could suggest novel therapeutic targets for further investigation. 30 m6A-associated lncRNAs with predictive values from the TCGA data set were identified with co-expression analysis. Cluster2 was correlated with a poor prognosis, upregulated PD-L1 expression, and higher immune ratings. Cluster2 had larger amounts of resting CD4 memory-activated T cells, M2 macrophages, neutrophils, and NK cells infiltration. "CHEMOKINE SIGNALING PATHWAY" was the most significantly enriched signaling pathway according to GSEA, which may play an important role in the different immune cell infiltrates between cluster1/2. The risk model for m6A-related lncRNAs could be employed in a prognostic model to predict BLCA prognosis, regardless of other clinical features. Collectively, m6A-related lncRNAs were linked to PD-L1 and TIME, which would dynamically affect the number of tumor-infiltrating immune cells. m6A-related lncRNAs may be key mediators of PD-L1 expression and immune cells infiltration and may strongly affect the TIME of BLCA.

High Expression of PLAGL2 is Associated With Poor Prognosis in High-Grade Glioma

Pleomorphic adenoma gene like-2 (PLAGL2) has been implicated in the development and progression of diverse malignancies, including glioblastoma. An increasing number of studies have reported that dysregulated expression of PLAGL2 is a common phenomenon in different malignancies. However, the mechanism and biological functions of PLAGL2 in patients with high-grade glioma (HGG) remain unclear. In addition, the expression and clinical significance of PLAGL2 in HGG have not yet been reported. Herein, we investigated the expression patterns and prognostic values of PLAGL2 in patients with HGG by using various databases, including Tumor Immune Estimation Resource 2.0 (TIMER2.0), GENT2, ONCOMINE, GEPIA, Human Protein Atlas, and Gene Expression Omnibus datasets. In the present study, we analyzed the relationship between PLAGL2 mRNA expression and clinical parameters in 184 HGG cases and found that PLAGL2 presented positively high expression and was relevant to poor prognosis. Immunohistochemistry analysis confirmed the overexpression of PLAGL2 protein, which is mainly expressed in the nucleus of glioma. Additionally, a high level of expression of the PLAGL2 gene was associated with lower survival in progression-free survival and overall survival in GBM patients. The correlation analysis between PLAGL2 and immune infiltration related to the abundance of B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, DCs, and neutrophils was also performed using TIMER2.0. GSEA results showed that high PLAGL2 expression was associated with cell migration, proliferation, actin cytoskeletal, and angiogenesis. To sum up, our findings indicated that PLAGL2 could serve as an independent prognostic biomarker and might be a potential therapeutic target for HGG, which should be further investigated.

Evaluation of tumor microenvironmental immune regulation and prognostic in lung adenocarcinoma from the perspective of purinergic receptor P2Y13

Tumor-infiltrating immune cells (TICs) can serve as an important indicator to evaluate the prognosis and therapeutic response in lung adenocarcinoma (LUAD). The identification of mutated genes that can affect the abundance of TICs and prognosis has practical implications. In the presented study, tumor microenvironment (TME) scoring was performed by the ESTIMATE scoring system on 598 RNA transcripts selected from the TCGA database to determine the proportions of immune cells and stromal cells. The infiltration difference of TICs in LUAD samples was obtained by CIBERSORT. The 'immuneeconv' R software package, which integrates six latest algorithms, including TIMER, xCell, MCP-counter, CIBERSORT, EPIC and quanTIseq were used to verify the correlation between purinergic receptor P2Y13 (P2RY13) and immune cells. Based on RNA sequencing analysis of the Lewis lung cancer-bearing model in C57BL/6 mice and immunohistochemistry (IHC) of human LUAD tissues, the expression of P2RY13 and associated pathways were verified. It was shown that differentially expressed genes (DEGs) obtained by interactive analysis based on Immunescore and Stromalscore were significantly enriched in immune-related pathways. The expression of P2RY13 was significantly associated with prognosis and clinicopathological characteristics of LUAD patients. More importantly, this gene played an important role in maintaining the immune dominant environment and changing the regulation of TICs. P2RY13 expression was positively correlated with the infiltration of dendritic cells (DCs) in various of tumor tissues as validated by the PanglaoDB scRNA-seq database. Therefore, P2RY13 is expected to be a potential biomarker for predicting TME and the prognosis of LUAD after verification.

Identification of Immune-Related Subtypes and Characterization of Tumor Microenvironment Infiltration in Bladder Cancer

Tumors are closely related to the tumor microenvironment (TME). The complex interaction between tumor cells and the TME plays an indisputable role in tumor development. Tumor cells can affect the TME, promote tumor angiogenesis and induce immune tolerance by releasing cell signaling molecules. Immune cell infiltration (ICI) in the TME can affect the prognosis of patients with bladder cancer. However, the pattern of ICI of the TME in bladder cancer has not yet been elucidated. Herein, we identified three distinct ICI subtypes based on the TME immune infiltration pattern of 584 bladder cancer patients using the ESTIMATE and CIBERSORT algorithms. Then, we identified three gene clusters based on the differentially expressed genes (DEGs) between the three ICI subtypes. In addition, the ICI score was determined using single sample gene set enrichment analysis (ssGSEA). The results suggested that patients in the high ICI score subgroup had a favorable prognosis and higher expression of checkpoint-related and immune activity-related genes. The high ICI score subgroup was also linked to increased tumor mutation burden (TMB) and neoantigen burden. A cohort treated with anti-PD-L1 immunotherapy confirmed the therapeutic advantage and clinical benefit of patients with higher ICI scores. In the end, our study also shows that the ICI score represents an effective prognostic predictor for evaluating the response to immunotherapy. In conclusion, our study deepened the understanding of the TME, and it provides new ideas for improving patients' response to immunotherapy and promoting individualized tumor immunotherapy in the future.

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

To 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.

m6A-Related lncRNA to Develop Prognostic Signature and Predict the Immune Landscape in Bladder Cancer

Abnormal m6A methylation plays a significant role in cancer progression. Increasingly, researchers have focused on developing lncRNA signatures to evaluate the prognosis of cancer patients. The specific function of m6A-related lncRNAs in the prognosis of bladder cancer patients and the immune microenvironment of bladder cancer remains elusive. Herein, we performed a comprehensive analysis of m6A-related lncRNA prognostic values and their association with the immune microenvironment in bladder cancer using the TCGA dataset. A total of 9 m6A-related lncRNAs were dramatically correlated with overall survival outcomes in bladder cancer. Two molecular subtypes (cluster 1 and cluster 2) were identified by consensus clustering for 9 m6A-related prognostic lncRNAs. Cluster 1 was significantly correlated with poor prognosis, advanced clinical stage, higher PD-L1 expression, a higher ESTIMATEScore and immuneScore, and distinct immune cell infiltration. GSEA revealed the enrichment of apoptosis and the JAK-STAT signaling pathway in cluster 2. A prognostic risk score was constructed using 9 m6A-related prognostic lncRNAs, which functioned as an independent prognostic factor for bladder cancer. Moreover, bladder cancer patients in the low-risk score group had a higher pN stage, pT stage, and clinical stage and a lower tumor grade and immuneScore. The risk score was correlated with the infiltration levels of certain immune cells, including B cells, plasma cells, follicular helper T cells, regulatory T cells, resting NK cells, neutrophils, M0 macrophages, M1 macrophages, and M2 macrophages. Collectively, our study elucidated the important role of m6A-related lncRNAs in the prognosis of bladder cancer patients and in the bladder cancer immune microenvironment. The results suggest that the components of the m6A-related prognostic lncRNA signature might serve as a crucial mediator of the immune microenvironment in bladder cancer, representing promising therapeutic targets for improving immunotherapeutic efficacy.

A novel immune-related gene pair prognostic signature for predicting overall survival in bladder cancer

Background

Bladder cancer (BC) is the ninth most common malignant tumor. We constructed a risk signature using immune-related gene pairs (IRGPs) to predict the prognosis of BC patients.

Methods

The mRNA transcriptome, simple nucleotide variation and clinical data of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database (TCGA-BLCA). The mRNA transcriptome and clinical data were also extracted from Gene Expression Omnibus (GEO) datasets (GSE31684). A risk signature was built based on the IRGPs. The ability of the signature to predict prognosis was analyzed with survival curves and Cox regression. The relationships between immunological parameters [immune cell infiltration, immune checkpoints, tumor microenvironment (TME) and tumor mutation burden (TMB)] and the risk score were investigated. Finally, gene set enrichment analysis (GSEA) was used to explore molecular mechanisms underlying the risk score.

Results

The risk signature utilized 30 selected IRGPs. The prognosis of the high-risk group was significantly worse than that of the low-risk group. We used the GSE31684 dataset to validate the signature. Close relationships were found between the risk score and immunological parameters. Finally, GSEA showed that gene sets related to the extracellular matrix (ECM), stromal cells and epithelial-mesenchymal transition (EMT) were enriched in the high-risk group. In the low-risk group, we found a number of immune-related pathways in the enriched pathways and biofunctions.

Conclusions

We used a new tool, IRGPs, to build a risk signature to predict the prognosis of BC. By evaluating immune parameters and molecular mechanisms, we gained a better understanding of the mechanisms underlying the risk signature. This signature can also be used as a tool to predict the effect of immunotherapy in patients with BC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08486-0.

The Expression of PD-L1 and B7-H4 in Thymic Epithelial Tumor and Its Relationship With Tumor Immune-Infiltrating Cells

Background

PD-L1 and B7-H4 have been reported to be expressed in various malignancies and are considered as promising prognostic factors and potential immunotherapy targets.

Methods

We analyzed the correlation between the expression of PD-L1 and B7-H4 transcriptomes and clinicopathological characteristics in 121 TET patients from The Cancer Genome Atlas (TCGA) database. The immune-infiltration levels in the TET microenvironment were estimated using ssGSEA and quanTiseq algorithms. We collected 80 TET cases from 2008 to 2015. PD-L1、B7-H4、FOXP3 and CD163 protein expression in tumor tissues were detected by immunohistochemistry.

Results

TCGA database showed PD-L1 mRNA levels can predict the OS (P = 0.018) and DFS (P = 0.033) of TET patients. B7-H4 mRNA levels were positively related to the World Health Organization (WHO) pathological classification (P = 0.003) but not correlated with patient prognosis. Immune infiltration analysis showed PD-L1 is positively correlated with Tregs and M2 macrophages, B7-H4 is positively correlated with Tregs. Patients with high PD-L1 and Tregs or M2 macrophages, high B7-H4 and Tregs had a worse prognosis. Immunohistochemistry showed PD-L1 expression was positively correlated with the WHO pathological classification and Masaoka stage (P = 0.025, 0.003) and high PD-L1 expression can predict the poor OS of patients (P = 0.043); B7-H4 was also positively correlated with WHO pathological classification and Masaoka stage (P = 0.036, 0.049). However, B7-H4 expression did not correlate with patient prognosis. Evaluation of co-expression patterns showed TET patients with a high-grade WHO pathological classification harbored a 44.4% co-expression of PD-L1 and B7-H4. In addition, we found the expression level of PD-L1 is positively correlated with FOXP3 and CD163 (P = 0.004, P = 0.029) and B7-H4 is positively correlated with FOXP3 (P = 0.037). High PD-L1 combined with High FOXP3 and High CD163, High B7-H4 combined with High FOXP3 can be used to predict the poor prognosis of TET patients (P = 0.026, 0.031, 0.028, respectively).

Conclusion

PD-L1 and B7-H4 were related to the aggressiveness of TET and their expression level can indicate the suppressive immune microenvironment. Combined with FOXP3 and CD163, PD-L1 and B7-H4 can indicate a poor prognosis of TET.

Comprehensive Analysis and Identification of an Immune-Related Gene Signature with Prognostic Value for Prostate Cancer

Background

The tumor microenvironment (TME) has recently been proven to play a crucial role in the development and prognosis of tumors. However, the current knowledge on the potential of the TME in prostate cancer (PCa) remains scarce.

Purpose

This study aims to elucidate the value of TME-related genes for PCa prognosis by integrative bioinformatics analysis.

Materials and Methods

We downloaded the immune and stromal scores of PCa samples via the ESTIMATE and correlated these scores to clinicopathological characteristics and recurrence-free survival (RFS) of patients. Based on these scores, the TME-related differentially expressed genes were identified for functional enrichment analysis. Cox regression analyses were performed to identify prognostic genes and establish a predictive risk model. Moreover, gene set enrichment analysis (GSEA) was performed to evaluate the relationship between risk score and immune pathway.

Results

The stromal and immune scores were associated with clinicopathological characteristics and RFS in PCa patients. In total, 238 intersecting differentially expressed genes were identified. Functional enrichment analysis further revealed that these genes dramatically participated in the immune-related pathways. The immune-related risk model was built with C-type lectin domain containing 7A (CLEC7A) and collagen type XI alpha 1 chain (COL11A1) using Cox regression analyses. Kaplan–Meier survival analysis showed that the expression levels of CLEC7A and COL11A1 were significantly associated with the RFS. Further, the RFS time in high-risk group was significantly shorter than that in low-risk group. The areas under the curve for the risk model in predicting 3- and 5-year RFS rates were 0.694 and 0.731, respectively. GSEA suggested that immunosuppression existed in high-risk PCa patients.

Conclusion

CLEC7A and COL11A1 were selected to build a predictive risk model, which may help clinicians to assess the prognosis of PCa patients and select appropriate targets for immunotherapy.

Prediction of bladder cancer outcome by identifying and validating a mutation-derived genomic instability-associated long noncoding RNA (lncRNA) signature

Bladder cancer is one of the most common malignant tumors worldwide. Accordingly, its incidence and mortality are high. One of the characteristics of cancer is genomic instability. New studies suggest that long non-coding RNAs (lncRNAs) play an important role in maintaining genomic instability. This study aimed to identify a genomic instability-associated lncRNA signature to predict the outcome of patients with bladder cancer. We downloaded data for bladder cancer patients from The Cancer Genome Atlas database to obtain lncRNA expression profiles as well as somatic mutation profiles. Using the lncRNA computational framework, a genomic instability-related lncRNA signature (GIlncSig) was established and the prognostic value of this signature was assessed and validated. A five-lncRNA signature based on genomic instability (CFAP58-DT, MIR100HG, LINC02446, AC078880.3, and LINC01833) was obtained from 58 differentially expressed lncRNAs. Patients were divided into high-risk and low-risk groups, with the high-risk group having a substantially worse prognosis than the low-risk group. Univariate and multivariate Cox analyses indicated that GIlncSig may be an independent prognostic factor; this finding was subsequently validated. In addition, enrichment analysis indicated that GIlncSig is associated with genomic instability in bladder cancer. GIlncSig has a predictive value for the prognosis of bladder cancer patients and provides guidance for the clinical treatment of these patients.

Construction and analysis of a ceRNA network and patterns of immune infiltration in bladder cancer

Background

Bladder cancer (BC) is the ninth most common malignant tumor, accounting for an estimate of 549,000 new BC cases and 200,000 BC-related deaths worldwide in 2018. The prognosis of BC has not substantially improved despite significant advances in the diagnosis and treatment of the disease.

Methods

The RNA sequencing (RNA-seq) data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm was used to assess immune infiltration. The survival analyses were performed using the selected components of a ceRNA network and selected immune cell types by least absolute shrinkage and selection operator (LASSO) Cox regression to calculate the risk score. The accuracy of prognosis prediction was determined by receiver operating characteristic (ROC) curves, survival curves, and nomograms. Finally, the correlation analysis was performed to investigate the relationships between the signature components of the ceRNA network and the immune cell signature.

Results

Two completed survival analyses included selected components of the ceRNA network (ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p) and selected immune cell types (M0 macrophages, M2 macrophages, resting mast cells, and neutrophils). ROC curves, survival curves (all P values <0.05), nomograms, and calibration curves indicated that the accuracy of the two survival analyses was acceptable. Moreover, the correlations between TTLL7 and resting mast cells (R=0.24, P<0.001), DSC2 and resting mast cells (R=−0.23, P<0.001), ELN and resting mast cells (R=0.44, P<0.001), and hsa-miR-29c-3p and M0 macrophages (R=−0.29, P<0.001) were significant, indicating that interactions of these factors may play significant roles in the prognosis of BC.

Conclusions

TTLL7, DSC2, ELN, hsa-miR-29c-3p, resting mast cells, and M0 macrophages may play an important role in the development of BC. However, additional studies are needed to confirm this hypothesis.

STAT1 is a key gene in a gene regulatory network related to immune phenotypes in bladder cancer: An integrative analysis of multi-omics data

The immunophenotype of bladder cancer plays a pivotal role in the prognosis of cancer, but the effect of different epigenetic factors on different immunophenotypes in bladder tumours remains unclear. This study used multi-omics data analysis to provide molecular basis support for different immune phenotypes. Unsupervised cluster analysis revealed distinct subclusters with higher (subcluster B2) or lower cytotoxic immune phenotypes (subcluster A1) related to PD-L1 and IFNG expression. Mutational landscape analyses showed that the mutation level of TP53 in subcluster B1 was highest than other subclusters, and subcluster B1 had a lower frequency of concurrent mutation than subcluster A2. A total of 2364 differentially expressed genes were identified between subclusters A2 and B1, and the main functions of the up-regulated genes in subcluster B1 were enriched in the activation of T cells and other related pathways. We found that STAT1 was a key gene in a gene regulatory network related to immune phenotypes in bladder cancer. Finally, we constructed a prognostic prediction model by LASSO Cox regression which could distinguish high-risk and low-risk cases significantly. In conclusion, the present study addressed a field synopsis between genetic and epigenetic events in immune phenotypes of bladder cancer.

The Effect of Local Renin Angiotensin System in the Common Types of Cancer

The Renin Angiotensin System (RAS) is a hormonal system that is responsible for blood pressure hemostasis and electrolyte balance. It is implicated in cancer hallmarks because it is expressed locally in almost all of the body's tissues. In this review, current knowledge on the effect of local RAS in the common types of cancer such as breast, lung, liver, prostate and skin cancer is summarised. The mechanisms by which RAS components could increase or decrease cancer activity are also discussed. In addition to the former, this review explores how the administration of AT1R blockers and ACE inhibitors drugs intervene with cancer therapy and contribute to the outcomes of cancer.

Mining of prognosis-related genes in cervical squamous cell carcinoma immune microenvironment

Purpose

The aim of this study was to explore the effective immune scoring method and mine the novel and potential immune microenvironment-related diagnostic and prognostic markers for cervical squamous cell carcinoma (CSSC).

Materials and Methods

The Cancer Genome Atlas (TCGA) data was downloaded and multiple data analysis approaches were initially used to search for the immune-related scoring system on the basis of Estimation of STromal and Immune cells in MAlignant Tumour tissues using Expression data (ESTIMATE) algorithm. Afterwards, the representative genes in the gene modules correlated with immune-related scores based on ESTIMATE algorithm were further screened using Weighted Gene Co-expression Network Analysis (WGCNA) and network topology analysis. Gene functions were mined through enrichment analysis, followed by exploration of the correlation between these genes and immune checkpoint genes. Finally, survival analysis was applied to search for genes with significant association with overall survival and external database was employed for further validation.

Results

The immune-related scores based on ESTIMATE algorithm was closely associated with other categories of scores, the HPV infection status, prognosis and the mutation levels of multiple CSCC-related genes (HLA and TP53). Eighteen new representative immune microenvironment-related genes were finally screened closely associated with patient prognosis and were further validated by the independent dataset GSE44001.

Conclusion

Our present study suggested that the immune-related scores based on ESTIMATE algorithm can help to screen out novel immune-related diagnostic indicators, therapeutic targets and prognostic predictors in CSCC.

Prognostic Value of Immune-Related Genes in the Tumor Microenvironment of Bladder Cancer

The tumor microenvironment (TME) is a complex system that plays an important role in tumor development and progression, but the current knowledge about its effect on bladder cancer (BC) is scarce. In this study, we performed a comprehensive analysis of the relationship between the TME and gene expression profiles to identify prognostic biomarkers for BC. The ESTIMATE algorithm was used to calculate immune and stromal scores of BC patients who were obtained from the Gene Expression Omnibus database. We found that the immune and stromal scores were associated with clinical characteristics and the prognosis of BC patients. Based on these scores, 104 immune-related differentially expressed genes were identified. Further, functional enrichment analysis revealed that these genes were mainly involved in the immune-related biological processes and signaling pathways. Three prognostic genes were then identified and used to establish a risk prediction model using Cox regression analyses. Kaplan–Meier survival analysis showed that the expression levels of COL1A1, COMP, and SERPINE2 significantly correlated with cancer-specific survival and overall survival of BC patients. Additionally, we validated the prognostic values of these genes using two independent cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases. Finally, the relationships between the three prognostic genes and several immune cells were evaluated using Tumor Immune Estimation Resource, indicating that the expression levels of COL1A1, COMP, and SERPINE2 correlated positively with the tumor infiltration levels of CD4⁺ T cells and macrophages. In conclusion, the current study comprehensively analyzed the TME and presented immune-related prognostic genes for BC, providing new insights into immunotherapeutic strategies for BC patients.