Identification of Immune-Related Genes Associated With Bladder Cancer Based on Immunological Characteristics and Their Correlation With the Prognosis

Identification of bladder cancer subtypes and predictive signature for prognosis, immune features, and immunotherapy based on immune checkpoint genes

Immunotherapy based on immune checkpoint genes (ICGs) has recently made significant progress in the treatment of bladder cancer patients, but many patients still cannot benefit from it. In the present study, we aimed to perform a comprehensive analysis of ICGs in bladder cancer tissues with the aim of evaluating patient responsiveness to immunotherapy and prognosis. We scored ICGs in each BLCA patient from TCGA and GEO databases by using ssGSEA and selected genes that were significantly associated with ICGs scores by using the WCGNA algorithm. NMF clustering analysis was performed to identify different bladder cancer molecular subtypes based on the expression of ICGs-related genes. Based on the immune related genes differentially expressed among subgroups, we further constructed a novel stratified model containing nine genes by uni-COX regression, LASSO regression, SVM algorithm and multi-COX regression. The model and the nomogram constructed based on the model can accurately predict the prognosis of bladder cancer patients. Besides, the patients classified based on this model have large differences in sensitivity to immunotherapy and chemotherapy, which can provide a reference for individualized treatment of bladder cancer.

ZAP70 interaction with 13 mRNAs as a potential immunotherapeutic target for endometrial cancer

For advanced, refractory endometrial cancer (EC), it is advisable to find effective immunotherapeutic targets. In the present study, genes affecting the immune status of uterine corpus endometrial carcinoma (UCEC) samples within The Cancer Genome Atlas were explored by weighted correlation network analysis and differential gene expression analysis. The protein function and immune correlation of 14 key genes, including ζ-chain-associated protein kinase 70 (ZAP70), were analyzed. Based on the expression levels of key genes, the patients with UCEC were divided into two groups using consensus clustering, low expression (group 1) and high expression (group 2). Next, the functions of differentially expressed genes (DEGs) between the two groups were identified using Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes analysis and Gene Set Enrichment Analysis. The immune status of the patients in the two groups was evaluated using immune infiltration score and the expression levels of targets of immune checkpoint inhibitors. The role of ZAP70 in the prognosis of patients with UCEC and the differences in ZAP70 expression between EC tissues and healthy intimal tissues were determined by reverse transcription-quantitative PCR and immunohistochemistry. The present study found strong correlations between key genes, including ZAP70, LCK, FOXP3, TIGIT, CTLA4, ICOS, CD5, IL2RG, PDCD1, TNFRSF4, CD27, CCR7, GZMB, CXCL9. From the enrichment analyses, it was found that the functions of these DEGs were related to T cells. Patients in group 2 had stronger immune infiltration and higher immune checkpoints expression compared with those in group 1. ZAP70 was expressed at higher levels in EC tissues compared with in normal tissues, and may act as a protective factor in EC. In conclusion, ZAP70 interaction with 13 mRNAs may affect the immune status of patients with EC and may be a potential target for immunotherapy.

Identification of Immune-Related Subtypes and Construction of a Novel Prognostic Model for Bladder Urothelial Cancer

The purpose of this study was to explore the relationship between bladder urothelial cancer (BLCA) and immunity, to screen prognosis-related immune genes (PIGs), and to construct an immune-related prognosis model (IRPM). We processed the relevant data of The Cancer Genome Atlas (TCGA-BLCA) and GSE13507 using R software and Perl. We divided BLCA into high-immunity and low-immunity subtypes. There were significant differences in the two subtypes. In addition, we identified 13 PIGs of BLCA by jointly analyzing the gene expression data and survival information of GSE13507 and TCGA-BLCA, and constructed IRPM through nine of them. The low-risk group had better survival outcome than the high-risk group. We also constructed a nomogram based on clinicopathological information and risk scores of the patients. Moreover, the prognosis of BLCA patients was significantly impacted by the expression of almost every gene used to calculate the risk score. The result of real-time fluorescence quantitative polymerase chain reaction revealed that all the genes used to calculate the risk score were differentially expressed between BLCA and adjacent normal tissues, except PDGFRA. Our research provided potential targets for the treatment of BLCA and a reference for judging the prognosis of BLCA.

Construction of a tumor immune infiltration macrophage signature for predicting prognosis and immunotherapy response in liver cancer

Liver cancer is an extraordinarily heterogeneous malignant disease. The tumor microenvironment (TME) and tumor-associated macrophages (TAMs) are the major drivers of liver cancer initiation and progression. It is critical to have a better understanding of the complicated interactions between liver cancer and the immune system for the development of cancer immunotherapy. Based on the gene expression profiles of tumor immune infiltration cells (TIICs), upregulated genes in TAMs and downregulated genes in other types of immune cells were identified as macrophage-specific genes (MSG). In this study, we combined MSG, immune subtypes, and clinical information on liver cancer to develop a tumor immune infiltration macrophage signature (TIMSig). A four-gene signature (S100A9, SLC22A15, TRIM54, and PPARGC1A) was identified as the TAM-related prognostic genes for liver cancer, independent of multiple clinicopathological parameters. Survival analyses showed that patients with low TIMSig had a superior survival rate than those with high TIMSig. Additionally, clinical immunotherapy response and TIMSig was observed as highly relevant. In addition, TIMSig could predict the response to chemotherapy. Collectively, the TIMSig could be a potential tool for risk-stratification, clinical decision making, treatment planning, and oncology immunotherapeutic drug development.

Identification and Validation of Cuproptosis-Related Prognostic Signature and Associated Regulatory Axis in Uterine Corpus Endometrial Carcinoma

Background: Uterine corpus endometrial carcinoma (UCEC) is a common gynecological malignancy globally with high recurrence and mortality rates. Cuproptosis is a new type of programmed cell death involved in tumor cell proliferation and growth, angiogenesis, and metastasis.

Methods: The difference in cuproptosis-related genes (CRGs) between UCEC tissues and normal tissues deposited in The Cancer Genome Atlas database was calculated using the “limma” R package. LASSO Cox regression analysis was conducted to construct a prognostic cuproptosis–related signature. Kaplan–Meier analysis was conducted to compare the survival of UCEC patients. A ceRNA network was constructed to identify the lncRNA–miRNA–mRNA regulatory axis. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed to verify CRG expression in UCEC.

Results: The expression of FDX1, LIAS, DLAT, and CDKN2A were upregulated, whereas the expression of LIPT1, DLD, PDHB, MTF1, and GLS were downregulated in UCEC versus normal tissues. The genetic mutation landscape of CRGs in UCEC was also summarized. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that these CRGs were enriched in the tricarboxylic acid (TCA) cycle, glycolysis, and HIF-1 signaling pathway. LASSO Cox regression analysis was performed and identified a cuproptosis-related prognostic signature including these three prognostic biomarkers (CDKN2A, GLS, and LIPT1). UCEC patients with high risk scores had a poor prognosis with an area under the curve of 0.782 and 0.764 on 3- and 5-year receiver operating characteristic curves. Further analysis demonstrated a significant correlation between CDKN2A and pTNM stage, tumor grade, immune cell infiltration, drug sensitivity, tumor mutational burden (TMB) score, and microsatellite instable (MSI) score. The data validation of qRT-PCR further demonstrated the upregulation of CDKN2A and the downregulation of LIPT1 and GLS in UCEC versus normal tissues. The ceRNA network also identified lncRNA XIST/miR-125a-5p/CDKN2A regulatory axis for UCEC.

Conclusion: The current study identified a cuproptosis-related prognostic signature including these three prognostic biomarkers (CDKN2A, GLS, and LIPT1) for UCEC. The ceRNA network also identified that lncRNA XIST/miR-125a-5p/CDKN2A regulatory axis may be involved in the progression of UCEC. Further in vivo and in vitro studies should be conducted to verify these results.

CD3D Is an Independent Prognostic Factor and Correlates With Immune Infiltration in Gastric Cancer

The protein encoded by CD3D is part of the T-cell receptor/CD3 complex (TCR/CD3 complex) and is involved in T-cell development and signal transduction. Previous studies have shown that CD3D is associated with prognosis and treatment response in breast, colorectal, and liver cancer. However, the expression and clinical significance of CD3D in gastric cancer are not clear. In this study, we collected 488 gastric cancer tissues and 430 paired adjacent tissues to perform tissue microarrays (TMAs). Then, immunohistochemical staining of CD3D, CD3, CD4, CD8 and PD-L1 was conducted to investigate the expression of CD3D in gastric cancer and the correlation between the expression of CD3D and tumor infiltrating lymphocytes (TILs) and PD-L1. The results showed that CD3D was highly expressed in gastric cancer tissues compared with paracancerous tissues (P<0.000). Univariate and multivariate analyses showed that CD3D was an independent good prognostic factor for gastric cancer (P=0.004, HR=0.677, 95%CI: 0.510-0.898 for univariate analyses; P=0.046, HR=0.687, 95%CI: 0.474-0.994 for multivariate analyses). In addition, CD3D was negatively correlated with the tumor location, Borrmann type and distant metastasis (P=0.012 for tumor location; P=0.007 for Borrmann type; P=0.027 for distant metastasis). In addition, the expression of CD3D was highly positively correlated with the expression of CD3, CD4, CD8, and PD-L1, and the combination of CD3D with CD3, CD4, CD8 and PD-L1 predicted the best prognosis (P=0.043). In summary, CD3D may play an important regulatory role in the tumor immune microenvironment of gastric cancer and may serve as a potential indicator of prognosis and immunotherapy response.

Immune Microenvironment of Muscular-Invasive Urothelial Carcinoma: The Link to Tumor Immune Cycle and Prognosis

In this study, we investigated the relationship between the tumor immune microenvironment (TIME), histological differentiation and hypoxia in patients with muscular-invasive urothelial carcinomas (MIUC) after radical cystectomy. Forty-two cases of pT2-3N0M0 MIUCs underwent clinical, histological and immunohistochemical evaluation by counting CD8+, FOXP3+, CD68+, CD163+ cells and polymorphonuclear leukocytes (PMN) in intra-tumoral and peritumoral areas, assessing PD-L1 and GLUT1 expression for defining the impact of tumor immune contexture on patients’ outcomes. Five-year survival rates and overall survival were calculated. Most of the MIUCs demonstrated the immune-desert or immune-excluded TIME, reflecting altered mechanisms of T-cells’ activation or traffic into tumors. Tumor immune contexture was closely related to histological differentiation. CD8+ cells were scant in MIUCs with papillary and squamous differentiation, while basal-like or mesenchymal-like histological differentiation was associated with increased density of CD8+ cells. A high rate of PD-L1 expression (47.6%) was not related to immune cell infiltration. M2-macrophages predominated under CD8+ lymphocytes. The abundance of PMN and CD163+ macrophages in MIUCs was associated with high GLUT1 expression. CD8+, CD68+, FOXP3+ cells and PD-L1 status did not affect patients’ outcomes, while high CD163+ density and PMN infiltration were associated with the unfavorable outcome of patients with MIUC. These data drive the hypothesis that in MIUC, immune escape mechanisms are shifted towards the role of the innate immunity cells rather than CD8+ lymphocytes’ functioning.

An HDAC9-associated immune-related signature predicts bladder cancer prognosis

Background

The close relationship between histone deacetylase 9 (HDAC9) and immunity has attracted attention. We constructed an immune signature for HDAC9, a vital epigenetic modification, to predict the survival status and treatment benefits in bladder cancer (BC).

Methods

An exhaustive analysis of HDAC9 and immunology via the tumor and immune system interaction database (TISIDB) was performed, and an immune prognostic risk signature was developed based on genes enriched in the top five immune-related pathways under high HDAC9 status. Comprehensive analysis of survival curves and Cox regression were used to estimate the effectiveness of the risk signature. The relationship between immunological characteristics and the risk score was evaluated, and the mechanisms were also explored.

Results

In the TISIDB, HDAC9 was closely related to various immunological characteristics. The risk signature was obtained based on genes related to prognosis enriched in the top five immune-related pathways under high HDAC9 status. The survival rate of the high-risk BC patients was poor. The risk score was closely related to multiple immunological characteristics, drug sensitivity, immunotherapy benefits and biofunctions.

Conclusion

An immune-related prognostic signature established for HDAC9 expression status could independently predict the prognosis of BC patients. The use of this signature could help clinicians make personalized treatment decisions.