Identification of immunogenic cell death-related signature on prognosis and immunotherapy in kidney renal clear cell carcinoma.

Background: Immunogenic cell death (ICD) is considered a particular cell death modality of regulated cell death (RCD) and plays a significant role in various cancers. The connection between kidney renal clear cell carcinoma (KIRC) and ICD remains to be thoroughly explored. Methods: We conducted a variety of bioinformatics analyses using R software, including cluster analysis, prognostic analysis, enrichment analysis and immune infiltration analysis. In addition, we performed Quantitative Real-time PCR to evaluate RNA levels of specific ICD genes. The proliferation was measured through Cell Counting Kit-8 (CCK-8) assay and colony-formation assay in RCC cell lines. Results: We determined two ICD subtypes through consensus clustering analysis. The two subtypes showed significantly different clinical outcomes, genomic alterations and tumor immune microenvironment. Moreover, we constructed the ICD prognostic signature based on TF, FOXP3, LY96, SLC7A11, HSP90AA1, UCN, IFNB1 and TLR3 and calculated the risk score for each patient. Kaplan-Meier survival analysis and ROC curve demonstrated that patients in the high-risk group had significantly poorer prognosis compared with the low-risk group. We then validated the signature through external cohort and further evaluated the relation between the signature and clinical features, tumor immune microenvironment and immunotherapy response. Given its critical role in ICD, we conducted further analysis on LY96. Our results indicated that downregulation of LY96 inhibited the proliferation ability of RCC cells. Conclusions: Our research revealed the underlying function of ICD in KIRC and screened out a potential biomarker, which provided a novel insight into individualized immunotherapy in KIRC.

A novel signature constructed by differential genes of muscle-invasive and non-muscle-invasive bladder cancer for the prediction of prognosis in bladder cancer.

Background: Bladder cancer (BCa) is a malignant tumor that usually forms cancer cells in the inner lining of the bladder. Hundreds of thousands of people worldwide have BCa diagnosed each year. The purpose of this study was to construct a prognostic model by differential expression of genes between muscular and non-muscular invasive BCa, and to investigate the prognosis of BCa patients. Methods: The data of BCa patients was sourced from the GEO and TCGA database. Single-cell sequencing data was obtained from three patients in the GSE135337 database, and microarray data for verification was obtained from GSE32894. Univariate, Lasso and multivariate cox regression analyses were performed to construct the prognostic model. The prognostic features, immune features and drug sensitivity of the model were further evaluated. Single-cell data and microarray data were used to validate the differential expression of model genes between muscle-invasive and non-muscle-invasive BCa. The invasion and migration of BCa cells were evaluated using the transwell assay and wound-healing assay. The cell proliferation capacity was simultaneously evaluated using Colony formation experiments. The protein expression of the specific gene was detected by western blot analysis. Results: We identified 183 differentially expressed muscle-invasive-related differential genes (MIRDGs), among which four were selected to establish a prognostic model. Based on our signature, patients in different groups displayed varying levels of immune infiltration and immunotherapy profiles. Single-cell sequencing data and microarray data confirmed that four invasion-related genes were expressed at higher levels in muscle-invasive BCa. Given the critical role of S100A9 in the progression of BCa, we performed further analysis. The results showed that protein expression of S100A9 was high in muscle-invasive BCa, and S100A9 knockdown could inhibit the proliferation, migration and invasion of BCa. Conclusion: These findings demonstrated that the prognostic model for BCa patients was reasonably accurate and valid, and it may prove to be of considerable value for the treatment and prognosis of BCa patients in the future. S100A9 may become a better prognostic marker and potential therapeutic target to further guide clinical treatment decisions.

Comprehensive RNA expression profile analysis of γδ T cells from peripheral blood and decidual tissues in normal pregnancy (NP) donors and patients with recurrent pregnancy loss (RPL).

Recurrent pregnancy loss (RPL) is a significant adverse pregnancy complication. The loss of immune tolerance has been proposed in the pathogenesis of RPL, however, the role of γδ T cells in RPL is still controversial. In this study, the gene expression patterns of circulated and decidual tissue-resident γδ T cells from normal pregnancy donors and patients with RPL were analyzed by SMART-seq. We demonstrate that the transcriptional expression profile of different subsets of γδ T cells in peripheral blood and decidual tissue is strikingly different. Vδ2 γδ T cells, as the major cytotoxic subset, are found to be enriched considerably, and the potential cytotoxicity of this subset is further enhanced in the decidua of RPL patients may be due to detrimental ROS reduction, enhanced metabolic activity, downregulation of immunosuppressive molecules expression in resident γδ T cells. Time-series Expression Miner (STEM) analysis of transcriptome indicates complex changes in gene expression in decidual γδ T cells over time from NP and RPL patients. Taken together, our work identifies high heterogeneity of gene signature in γδ T cells from NP and RPL patients between peripheral blood and decidua, which will be a useful resource for further studies of the critical roles of γδ T cells in RPL.

COVID-19 vaccination influences subtypes of γδ-T cells during pregnancy.

Up to now, there has been insufficient clinical data to support the safety and effects of vaccination on pregnancy post COVID-19 vaccination. The γδ-T cells are considered an important component in the immune system to fight against viral infection and exhibit critical roles throughout the pregnancy period. However, the immunological roles of γδ-T cells in pregnant women with the COVID-19 vaccination remain unclear. Therefore, the objective of this study is to investigate the alteration of frequency and expression pattern of activation receptors and inhibitory receptors in γδ-T cell and its subsets in peripheral blood samples collected from non-pregnant vaccinated women, vaccinated pregnant women, and unvaccinated pregnant women. Our findings indicated that the frequency of CD3+γδ-T+ cells is lower in vaccinated pregnant women than in unvaccinated pregnant women. But no significant difference was found in the frequency of CD3+γδ-T+ cells between non-pregnant vaccinated women and vaccinated pregnant women. In addition, there were no significant differences in the frequencies of CD3+γδ-T+Vδ1+T cells, CD3+γδ-T+Vδ2+T cells, CD3+γδ-T+Vδ1-Vδ2-T cells, and Vδ1+T cell/Vδ2+T cell ratio between the pregnant women with or without COVID-19 vaccination. Similar results were found after comparing non-pregnant and pregnant women who received the COVID-19 vaccine. However, there was a significant difference in the fraction of Vδ1-Vδ2-T cells in CD3+γδ-T+ cells between non-pregnant vaccinated women and vaccinated pregnant women. The frequency of NKG2D+ cells in Vδ2+T cells was not significantly different in the vaccinated pregnant women when compared to that in unvaccinated pregnant women or non-pregnant vaccinated women. But the percentage of NKG2D+ cells in Vδ1+T cells was the lowest in pregnant women after COVID-19 vaccination. Furthermore, down-regulation of NKP46 and NKP30 were found in Vδ2+T and Vδ1+T cells in the vaccinated pregnant women, respectively. After the vaccination, up-regulation of PD-1 expression in Vδ1+T cells and Vδ2+T cells indicated γδ-T cells could respond to COVID-19 vaccination and display an exhausted phenotype following activation. In conclusion, COVID-19 vaccination influences subtypes of γδ-T cells during pregnancy, but the side effects might be limited. The phenotypical changes of Vδ1+T cells and Vδ2+T cells will be a promising predictor for evaluating the clinical outcome of the COVID-19 vaccine.

Phenotypic Changes of Peripheral γδ T Cell and Its Subsets in Patients With Coronary Artery Disease.

Coronary atherosclerotic heart disease (CAD) is a chronic inflammatory cardiovascular disease with high morbidity and mortality. Growing data indicate that many immune cells are involved in the development of atherosclerosis. However, the immunological roles of γδ T cells in the initiation and progression of CAD are not fully understood. Here, we used flow cytometry to determine phenotypical changes of γδ T cells and their subpopulations in peripheral blood samples collected from 37 CAD patients. The Pearson correlation coefficient was used to analyze the relationship between the clinical parameter (serum LDL-C level) and the changes of immunophenotypes of γδ T cells. Our results demonstrated that the frequencies and absolute numbers of total γδ T cells and Vδ2+ T cells were significantly decreased in CAD patients when compared to healthy individuals. However, the proportion of Vδ1+ T cells was much lower in CAD patients than that of healthy individuals. Most importantly, a significant alteration of the Vδ1/Vδ2 ratio was found in CAD patients. In addition, a series of surface markers that are associated with costimulatory signals (CD28, CD40L, CD80, CD86), activation levels (CD69, CD25, HLA-DR), activating NK cell receptors (NKp30, NKp46, NKG2D) and inhibitory receptors (PD-1, CTLA-4, PD-1, Tim-3) were determined and then analyzed in the total γδ T cells, Vδ2+T cells and Vδ2-T cells of CAD patients and healthy individuals. The data demonstrated that immunological activities of total γδ T cells, Vδ2+T cells, and Vδ2-T cells of CAD patients were much lower than those in healthy individuals. Moreover, we found that there were positive correlations between the serum LDL-C levels and frequencies of CD3+γδ+ T cells, CD69+Vδ2+T cells, NKG2D+Vδ2+T cells, and NKp46+Vδ2+T cells. By contrast, there was an inverse correlation between the levels of serum LDL-C and the frequencies of CD69+Vδ2-T cells and NKp46+Vδ2-T cells. Accordingly, these findings could help us to better understand the roles of γδ T cells in the CAD, and shed light on the development of novel diagnostic techniques and therapeutic strategies by targeting γδ T cells for CAD patients.

PD-1 mediates decidual γδ T cells cytotoxicity during recurrent pregnancy loss.

PROBLEM: Recurrent pregnancy loss (RPL) is one of the big challenges of normal pregnancy. Immune dysregulation has been proposed for the key underline mechanisms of RPL. However, the essential roles of T cells, especially γδ T cells, have not been defined. METHOD OF STUDY: Decidua were obtained from normal pregnancy women or recurrent pregnancy loss patients and the surface molecules of γδ T cells in decidua were evaluated via flow cytometric analysis. The expression of PD-1 in clinical samples was analyzed by immunohistochemistry assay. The intracellular cytokines of decidual PD-1+ and PD-1- γδ T cells were evaluated by flow cytometric analysis. The cytotoxicity of PD-1- γδ T cells were confirmed via an in vitro co-culture experiment. The specific inhibitors for Erk, p38 and JNK against the MAPK pathway were added to the co-culture media to evaluate the functions of the Erk, p38 and JNK. RESULTS: We demonstrated that PD-1 was significantly decreased on decidual tissue γδ T cells of patients with RPL, resulting in the enhanced cytotoxicity of γδ T cells against trophoblasts. We further elucidated an Erk-dependent TNF-α production mediates the γδ T cell cytotoxicity against the trophoblast cells. Finally, the reduced expression of PD-L1 in the villi tissues of patients with RPL might be the cause of the reduction of PD-1 on the tissue γδ T cells. CONCLUSION: Our study uncovers an important role of PD-1 expression on decidual γδ T cells in maintaining the normal pregnancy, and may provide a new strategy for immune therapy against RPL.

Immune Microenvironment and Response in Prostate Cancer Using Large Population Cohorts.

Immune microenvironment of prostate cancer (PCa) is implicated in disease progression. However, previous studies have not fully explored PCa immune microenvironment. This study used ssGSEA algorithm to explore expression levels of 53 immune terms in a combined PCa cohort (eight cohorts; 1,597 samples). The top 10 immune terms were selected based on the random forest analysis and used for immune-related risk score (IRS) calculation. Furthermore, we explored differences in clinical and genomic features between high and low IRS groups. An IRS signature based on the 10 immune terms showed high prediction potential for PCa prognosis. Patients in the high IRS group showed significantly higher percentage of immunotherapy response factors, implying that IRS is effective in predicting immunotherapy response rate. Furthermore, consensus clustering was performed to separate the population into three IRSclusters with different clinical outcomes. Patients in IRScluster3 showed the worst prognosis and highest immunotherapy response rate. On the other hand, patients in IRScluster2 showed better prognosis and low immunotherapy response rate. In addition, VGLL3, ANPEP, CD38, CCK, DPYS, CST2, COMP, CRISP3, NKAIN1, and F5 genes were differentially expressed in the three IRSclusters. Furthermore, CMap analysis showed that five compounds targeted IRS signature, thioridazine, trifluoperazine, 0175029-0000, trichostatin A, and fluphenazine. In summary, immune characteristics of PCa tumor microenvironment was explored and an IRS signature was constructed based on 10 immune terms. Analysis showed that this signature is a useful tool for prognosis and prediction of immunotherapy response rate of PCa.

Integrated Analysis of the Prognosis-Associated RNA-Binding Protein Genes and Candidate Drugs in Renal Papillary Cell Carcinoma.

RNA-binding proteins (RBPs) play significant roles in various cancer types. However, the functions of RBPs have not been clarified in renal papillary cell carcinoma (pRCC). In this study, we identified 31 downregulated and 89 upregulated differentially expressed RBPs on the basis of the cancer genome atlas (TCGA) database and performed functional enrichment analyses. Subsequently, through univariate Cox, random survival forest, and multivariate Cox regression analysis, six RBPs of SNRPN, RRS1, INTS8, RBPMS2, IGF2BP3, and PIH1D2 were screened out, and the prognostic model was then established. Further analyses revealed that the high-risk group had poor overall survival. The area under the curve values were 0.87 and 0.75 at 3 years and 0.78 and 0.69 at 5 years in the training set and test set, respectively. We then plotted a nomogram on the basis of the six RBPs and tumor stage with the substantiation in the TCGA cohort. Moreover, we selected two intersectant RBPs and evaluate their biological effects by GSEA and predicted three drugs, including STOCK1N-28457, pyrimethamine, and trapidil by using the Connectivity Map. Our research provided a novel insight into pRCC and improved the determination of prognosis and individualized therapeutic strategies.

Prognostic model of 10 immune-related genes and identification of small molecule drugs in bladder urothelial carcinoma (BLCA).

BACKGROUND: We aimed to establish an immune-related gene (IRG) based signature that could provide guidance for clinical bladder cancer (BC) prognostic surveillance. METHODS: Differentially expressed IRGs and transcription factors (TFs) between BCs and normal tissues were extracted from transcriptome data downloaded from the TCGA database. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out to identify related pathways based on differently expressed IRGs. Then, univariate Cox regression analysis was performed to investigate IRGs with prognostic values and LASSO penalized Cox regression analysis was utilized to develop the prognostic index (PI) model. RESULTS: A total of 411 BC tissue samples and 19 normal bladder tissues in the TCGA database were enrolled in this study and 259 differentially expressed IRGs were identified. Networks between TFs and IRGs were also provided to seek the upstream regulators of differentially expressed IRGs. By means of univariate Cox regression analysis, 57 IRGs were analyzed with prognostic values and 10 IRGs were finally identified by LASSO penalized Cox regression analysis to construct the PI model. This model could significantly classified BC patients into high-risk group and low-risk group in terms of OS (P=9.923e-07) and its AUC reached 0.711. By means of univariate and multivariate COX regression analysis, this PI was proven to be a valuable independent prognostic factor (HR =1.119, 95% CI =1.066-1.175, P<0.001). CMap database analysis was also utilized to screen out 10 small molecules drugs with the potential for the treatment of BC. CONCLUSIONS: Our study successfully provided a novel PI based on IRGs with the potential to predict the prognosis of BC and screened out 10 small molecules drugs with the potential to treat BC. Besides, networks between TFs and IRGs were also displayed to seek its upstream regulators for future researches.