CMA1 is potent prognostic marker and associates with immune infiltration in gastric cancer

Prediction of clear cell renal cell carcinoma prognosis based on an immunogenomic landscape analysis

Immune cell infiltration and tumor-related immune molecules play key roles in tumorigenesis and tumor progression. The influence of immune interactions on the molecular characteristics and prognosis of clear cell renal cell carcinoma (ccRCC) remains unclear. A machine learning algorithm was applied to the transcriptome data from The Cancer Genome Atlas database to determine the immunophenotypic and immunological characteristics of ccRCC patients. These algorithms included single-sample gene set enrichment analyses and cell type identification. Using bioinformatics techniques, we examined the prognostic potential and regulatory networks of immune-related genes (IRGs) involved in ccRCC immune interactions. Fifteen IRGs (CCL7, CHGA, CMA1, CRABP2, IFNE, ISG15, NPR3, PDIA2, PGLYRP2, PLA2G2A, SAA1, TEK, TGFA, TNFSF14, and UCN2) were identified as prognostic IRGs associated with overall survival and were used to construct a prognostic model. The area under the receiver operating characteristic curve at 1 year was 0.927; 3 years, 0.822; and 5 years, 0.717, indicating good predictive accuracy. Molecular regulatory networks were found to govern immune interactions in ccRCC. Additionally, we developed a nomogram containing the model and clinical characteristics with high prognostic potential. By systematically examining the sophisticated regulatory mechanisms, molecular characteristics, and prognostic potential of ccRCC immune interactions, we provided an important framework for understanding the molecular mechanisms of ccRCC and identifying new prognostic markers and therapeutic targets for future research.

Use of Transcriptomics to Reveal the Joint Immunotoxicity Mechanism Initiated by Difenoconazole and Chlorothalonil in the Human Jurkat T-Cell Line

It is very important to evaluate the immunotoxicity and molecular mechanisms of pesticides. In this study, difenoconazole and chlorothalonil were evaluated for immunotoxicity by using the human Jurkat T-cell line, and the EC50 were 24.66 and 1.17 mg/L, respectively. The joint exposure of difenoconazole and chlorothalonil showed a synergistic effect at low concentrations (lower than 10.58 mg/L) but an antagonistic effect at high concentrations (higher than 10.58 mg/L). With joint exposure at a concentration of EC10, the proportion of late apoptotic cells was 2.26- and 2.91-fold higher than that with exposure to difenoconazole or chlorothalonil alone, respectively. A transcriptomics analysis indicated that the DEGs for single exposure are associated with immunodeficiency disease. Single exposure to chlorothalonil was mainly involved in cation transportation, extracellular matrix organization, and leukocyte cell adhesion. Single exposure to difenoconazole was mainly involved in nervous system development, muscle contraction, and immune system processes. However, when the joint exposure dose was EC10, the DEGs were mainly involved in the formation of cell structures, but the DEGs were mainly involved in cellular processes and metabolism when the joint exposure dose was EC25. The results indicated that the immunotoxicological mechanisms underlying joint exposure to difenoconazole and chlorothalonil are different under low and high doses.

Role of mast cells activation in the tumor immune microenvironment and immunotherapy of cancers

The mast cell is an important cellular component that plays a crucial role in the crosstalk between innate and adaptive immune responses within the tumor microenvironment (TME). Recently, numerous studies have indicated that mast cells related to tumors play a dual role in regulating cancers, with conflicting results seemingly determined by the degranulation medium. As such, mast cells are an ignored but very promising potential target for cancer immunotherapy based on their immunomodulatory function. In this review, we present a comprehensive overview of the roles and mechanisms of mast cells in diverse cancer types. Firstly, we evaluated the infiltration density and location of mast cells on tumor progression. Secondly, mast cells are activated by the TME and subsequently release a range of inflammatory mediators, cytokines, chemokines, and lipid products that modulate their pro-or anti-tumor functions. Thirdly, activated mast cells engage in intercellular communication with other immune or stromal cells to modulate the immune status or promote tumor development. Finally, we deliberated on the clinical significance of targeting mast cells as a therapeutic approach to restrict tumor initiation and progression. Overall, our review aims to provide insights for future research on the role of mast cells in tumors and their potential as therapeutic targets for cancer treatment.

Identification of Immune-Related Prognostic Markers in Gastric Cancer

Gastric cancer (GC) is a malignant tumor with a high fatality rate. Poor prognosis is the main cause of death caused by GC. In this study, the gene expression difference between GC and the control group was analyzed. Differentially expressed genes (DEGs) related to immunity were screened for enrichment analysis. The differences in immune cell infiltration and immune function between GC and normal were identified. Cox regression analysis and survival analysis were used to determine the prognostic genes of GC in TCGA and GSE62254. The potential prognostic role of genes was further evaluated by risk score. Difference genes in GC were analyzed in TCGA. Candidate genes in TCGA and GSE62254 are analyzed, and prognostic genes are determined. The potential prognostic role of genes was further evaluated by risk score. The immune-related prognostic markers in GC were determined. FABP4, LBP, LCN1, CMA1, INHBA, ANGPTL1, ACKR1, GHR, and OGN may be used as markers for monitoring the prognosis of GC in the future.

Exploring the potential biomarkers for prognosis of glioblastoma via weighted gene co-expression network analysis

BACKGROUND

Glioblastoma (GBM) is the most common malignant tumor in the central system with a poor prognosis. Due to the complexity of its molecular mechanism, the recurrence rate and mortality rate of GBM patients are still high. Therefore, there is an urgent need to screen GBM biomarkers to prove the therapeutic effect and improve the prognosis.

RESULTS

We extracted data from GBM patients from the Gene Expression Integration Database (GEO), analyzed differentially expressed genes in GEO and identified key modules by weighted gene co-expression network analysis (WGCNA). GSE145128 data was obtained from the GEO database, and the darkturquoise module was determined to be the most relevant to the GBM prognosis by WGCNA (r =  - 0.62, p = 0.01). We performed enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to reveal the interaction activity in the selected modules. Then Kaplan-Meier survival curve analysis was used to extract genes closely related to GBM prognosis. We used Kaplan-Meier survival curves to analyze the 139 genes in the darkturquoise module, identified four genes (DARS/GDI2/P4HA2/TRUB1) associated with prognostic GBM. Low expression of DARS/GDI2/TRUB1 and high expression of P4HA2 had a poor prognosis. Finally, we used tumor genome map (TCGA) data, verified the characteristics of hub genes through Co-expression analysis, Drug sensitivity analysis, TIMER database analysis and GSVA analysis. We downloaded the data of GBM from the TCGA database, the results of co-expression analysis showed that DARS/GDI2/P4HA2/TRUB1 could regulate the development of GBM by affecting genes such as CDC73/CDC123/B4GALT1/CUL2. Drug sensitivity analysis showed that genes are involved in many classic Cancer-related pathways including TSC/mTOR, RAS/MAPK.TIMER database analysis showed DARS expression is positively correlated with tumor purity (cor = 0.125, p = 1.07e-02)), P4HA2 expression is negatively correlated with tumor purity (cor =-0.279, p = 6.06e-09). Finally, GSVA analysis found that DARS/GDI2/P4HA2/TRUB1 gene sets are closely related to the occurrence of cancer.

CONCLUSION

We used two public databases to identify four valuable biomarkers for GBM prognosis, namely DARS/GDI2/P4HA2/TRUB1, which have potential clinical application value and can be used as prognostic markers for GBM.

Comprehensive Analysis of CPA4 as a Poor Prognostic Biomarker Correlated with Immune Cells Infiltration in Bladder Cancer

Simple Summary

The overexpression of Carboxypeptidase A4 (CPA4) has been observed in plenty of types of cancer and has been elucidated to promote tumor growth and invasion; however, its role in bladder urothelial carcinoma (BLCA) is still unclear. Therefore, we aimed to show the prognostic role of CPA4 and its relationship with immune infiltrates in BLCA. We confirmed that the overexpression of CPA4 is associated with shorter overall survival, disease-specific survival, progress-free intervals, and higher dead events. Moreover, we found that several infiltrating immune cells (Th1cell, Th2 cell, T cell exhaustion, and Tumor-associated macrophage) were correlated with the expression of CPA4 in bladder cancer using TIMER2 and GEPIA2. In conclusion, CPA4 may be a novel and great prognostic biomarker based on bioinformation analysis in BLCA.

Abstract

Carboxypeptidase A4 (CPA4) has shown the potential to be a biomarker in the early diagnosis of certain cancers. However, no previous research has linked CPA4 to therapeutic or prognostic significance in bladder cancer. Using data from The Cancer Genome Atlas (TCGA) database, we set out to determine the full extent of the link between CPA4 and BLCA. We further analyzed the interacting proteins of CPA4 and infiltrated immune cells via the TIMER2, STRING, and GEPIA2 databases. The expression of CPA4 in tumor and normal tissues was compared using the TCGA + GETx database. The connection between CPA4 expression and clinicopathologic characteristics and overall survival (OS) was investigated using multivariate methods and Kaplan–Meier survival curves. The potential functions and pathways were investigated via gene set enrichment analysis. Furthermore, we analyze the associations between CPA4 expression and infiltrated immune cells with their respective gene marker sets using the ssGSEA, TIMER2, and GEPIA2 databases. Compared with matching normal tissues, human CPA4 was found to be substantially expressed. We confirmed that the overexpression of CPA4 is linked with shorter OS, DSF(Disease-specific survival), PFI(Progression-free interval), and increased diagnostic potential using Kaplan–Meier and ROC analysis. The expression of CPA4 is related to T-bet, IL12RB2, CTLA4, and LAG3, among which T-bet and IL12RB2 are Th1 marker genes while CTLA4 and LAG3 are related to T cell exhaustion, which may be used to guide the application of checkpoint blockade and the adoption of T cell transfer therapy.

PMEL as a Prognostic Biomarker and Negatively Associated With Immune Infiltration in Skin Cutaneous Melanoma (SKCM)

Premelanosome protein (PMEL) is crucial for the formation of melanosomal fibrils through the transition from stage I to stage II melanosomes. It was used as a target antigen in some adoptive T-cell therapy of melanoma. The correlation of PMEL to prognosis and immune cell infiltration level are unknown in melanoma. The PMEL expression was evaluated via Tumor Immune Estimation Resource, Oncomine and Gene Expression Profiling Interactive Analysis (GEPIA). We also evaluate the influence of PMEL on overall survival via GEPIA, PrognoScan, and immunohistochemistry in human tissue microarray. The correlation between PMEL expression level and immune cell or gene markers of immune infiltration level was explored on Tumor Immune Estimation Resource and GEPIA. PMEL expression was significantly higher in skin cutaneous melanoma (SKCM) and SKCM-metastasis in comparison with the other cancers. In SKCM, PMEL expression in high levels was associated with poor overall survival. In both SKCM and SKCM-metastasis patients, PMEL expression is negatively correlated with the infiltration cells of CD8+ T cells, macrophages, and neutrophils. Programmed cell-death protein 1 just showed response rates ranging from 20% to 40% in patients with melanoma, so it is critical to discover a new therapeutic target. PMEL is negatively associated with immune cell infiltration and can be as a negative prognosis marker or new immunotherapy target in SKCM and SKCM-metastasis.

The Angiotensin-(1-12)/Chymase axis as an alternate component of the tissue renin angiotensin system

The identification of an alternate extended form of angiotensin I composed of the first twelve amino acids at the N-terminal of angiotensinogen has generated new knowledge of the importance of noncanonical mechanisms for renin independent generation of angiotensins. The human sequence of the dodecapeptide angiotensin-(1-12) [N-Asp¹-Arg²-Val³-Tyr⁴-Ile⁵-His⁶-Pro⁷-Phe⁸-His⁹-Leu¹⁰-Va^l1-Ile¹²-COOH] is an endogenous substrate that in the rat has been documented to be present in multiple organs including the heart, brain, kidney, gut, adrenal gland, and the bone marrow. Newer studies have confirmed the existence of Ang-(1-12) as an Ang II-forming substrate in the blood and heart of normal and diseased patients. Studies to-date document that angiotensin II generation from angiotensin-(1-12) does not require renin participation while chymase rather than angiotensin converting enzyme shows high catalytic activity in converting this tissue substrate into angiotensin II directly.

Sema4D correlates with tumour immune infiltration and is a prognostic biomarker in bladder cancer, renal clear cell carcinoma, melanoma and thymoma

Sema4D, a member of the immune semaphorin family, plays crucial roles in the immune regulation, bone resorption and nervous system. It is also involved in angiogenesis and tumour progression. However, systemic studies on the correlation between Sema4D expression and the immune infiltration or clinical outcomes in tumours are still limited. Here, we analysed the landscape of Sema4D expression and its prognostic value in the cancer genome atlas pan-cancer as well as the correlation between Sema4D and immune cell infiltration by Tumour Immune Estimation Resource and Gene Expression Profiling interactive analysis online tools. Results showed that a higher Sema4D expression was significantly correlated with a favourable overall survival in diverse solid tumours including bladder cancer (Hazards Ratio (HR)=0.68, p = .0095), kidney renal clear cell carcinoma (HR = 0.61, p = .0016), melanoma (HR = 0.58, p = 6.6e-05) and thymoma (HR = 0.1, p = .011). Interestingly, Sema4D expression has positive correlation with various tumour infiltrating immune cells and immune cell biomarkers in these tumours. These results suggest that Sema4D could be a prospective biomarker for calculating hazard ratio of tumour patients and their tumour immune infiltration levels.

Identification of ANXA1 as a potential prognostic biomarker and correlating with immune infiltrates in colorectal cancer

BACKGROUND

ANXA1 is a calcium-dependent phospholipid-binding protein and is frequently associated with inflammation, cell proliferation and apoptosis. However, the relationship between ANXA1 and the prognosis of multiple tumours and tumour infiltrating immune cells remains unclear.

METHODS

Multivariate Cox proportional regression analysis was used for signature genes exploration in the basic of colon adenocarcinoma (COAD) RNA-sequence dataset obtained from TCGA, following the identification of 267 common differentially expressed genes, including ANXA1, among three expression profile datasets (GSE41328, GSE110224, and GSE113513). The differential expression of ANXA1 in different tumours and their corresponding normal tissues were evaluated through the Tumour Immune Estimation Resource (TIMER) and Oncomine database. Subsequently, we investigated the correlation between the expression level of ANXA1 and diverse panel of infiltrating immune cells and their related gene markers in colorectal cancer using correlation analysis in TIMER and GEPIA database.

RESULTS

The high expression of ANXA1 was demonstrated to be closely correlated with poor survival in patients with colorectal cancer. More importantly, we found that changes in ANXA1 expression showed a moderate to strong, and statistically significant, correlation with infiltrating levels of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells. By contrast, there are only weak correlations between ANXA1 expression and immune cell infiltration in ESCA and STAD. ANXA1 expression was considerably associated with various immune markers involving immune cell recruitment, polarization of tumour-associated macrophages, and T cell exhaustion.

CONCLUSION

ANXA1 is not only an independent risk factor in the prediction of the prognosis of colorectal cancer, but also a crucial regulator in immune cell infiltration. This study may shed light on the clinical value of ANXA1, especially in the areas of early diagnosis of colorectal cancer and therapeutic target discovery.

T cell immune regulator 1 is a prognostic marker associated with immune infiltration in glioblastoma multiforme

Glioma is the most common primary brain tumor and glioblastoma multiforme (GBM) is the most malignant brain glioma with the worst prognosis. T cell immune regulator 1 (TCIRG1) constitutes the V₀a₃ subunit of vacuolar ATPase (V-ATPase), and the function of V-ATPase in malignant tumors, such as breast cancer, melanoma and hepatocellular carcinoma, has been reported. However, the effect of the TCIRG1 subunit on GBM remains to be fully elucidated. mRNA levels of TCIRG1 in different cancer types and the corresponding normal tissues were extracted from the Oncomine and Tumor Immune Estimation Resource (TIMER) databases. The Gene Expression Omnibus (access number: GSE16011), the Chinese Glioma Genome Atlas and The Cancer Genome Atlas were used to investigate the mRNA level of TCIRG1 in glioma. Protein level validation in glioma was performed using western blotting. The Database for Annotation, Visualization and Integrated Discovery was used to analyze Gene Ontology (GO) categories for genes correlated with TCIRG1 in GBM. Protein-protein interaction (PPI) networks and module analyses were performed using Cytoscape software and the MCODE plugin. The correlation between tumor immune cell infiltration and TCIRG1 expression was explored using the TIMER database. Additionally, the correlation between TCIRG1 and the gene signature of immune infiltration was explored through TIMER and Gene Expression Profiling Interactive Analysis. External validation of TCIRG1 expression according to immune signatures in GBM was performed using the GSE16011 dataset with the GlioVis online tool. It was found that TCIRG1 expression was increased in GBM and numerous malignant tumors and may serve as a biomarker of the mesenchymal subtype of GBM. GO category analysis of positively correlated genes revealed that TCIRG1 was correlated with the immune response in GBM. PPI network and module analyses also supported the potential function of TCIRG1 in the local immune response. The expression of TCIRG1 was associated with various immune markers. It was therefore speculated that TCIRG1 is associated with glioma malignancy and may be a marker of unfavorable prognosis in patients with GBM, and it could be regarded as a prognostic biomarker and an indicator of immune infiltration in GBM.