CD8+ T cells: The past and future of immune regulation

Development and implementation of a prognostic model for clear cell renal cell carcinoma based on heterogeneous TLR4 expression

Objective

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cell carcinomas and has the worst prognosis, originating from renal tubular epithelial cells. Toll-like receptor 4 (TLR4) plays a crucial role in ccRCC proliferation, infiltration, and metastasis. The aim of this study was to construct a prognostic scoring model for ccRCC based on TLR4 expression heterogeneity and to explore its association with immune infiltration, thereby providing insights for the treatment and prognostic evaluation of ccRCC.

Methods

Using R software, a differential analysis was conducted on normal samples and ccRCC samples, and in conjunction with the KEGG database, a correlation analysis for the clear cell renal cell carcinoma pathway (hsa05211) was carried out. We observed the expression heterogeneity of TLR4 in the TCGA-KIRC cohort and identified its related differential genes (TRGs). Based on the expression levels of TRGs, consensus clustering was employed to identify TLR4-related subtypes, and further clustering heatmaps, principal component, and single-sample gene set enrichment analyses were conducted. Overlapping differential genes (ODEGs) between subtypes were analysed, and combined with survival data, univariate Cox regression, LASSO, and multivariate Cox regression were used to establish a prognostic risk model for ccRCC. This model was subsequently evaluated through ROC analysis, risk factor correlation analysis, independent prognostic factor analysis, and intergroup differential analysis. The ssGSEA model was employed to explore immune heterogeneity in ccRCC, and the performance of the model in predicting patient prognosis was evaluated using box plots and the oncoPredict software package.

Results

In the TCGA-KIRC cohort, TLR4 expression was notably elevated in ccRCC samples compared to normal samples, correlating with improved survival in the high-expression group. The study identified distinct TLR4-related differential genes and categorized ccRCC into three subtypes with varied survival outcomes. A risk prognosis model based on overlapping differential genes was established, showing significant associations with immune cell infiltration and key immune checkpoints (PD-1, PD-L1, CTLA4). Additionally, drug sensitivity differences were observed between risk groups.

Conclusion

In the TCGA-KIRC cohort, the expression of TLR4 in ccRCC samples exhibited significant heterogeneity. Through clustering analysis, we identified that the primary immune cells across subtypes are myeloid-derived suppressor cells, central memory CD4 T cells, and regulatory T cells. Furthermore, we successfully constructed a prognostic risk model for ccRCC composed of 17 genes. This model provides valuable references for the prognosis prediction and treatment of ccRCC patients.

Trained Innate Immunity in Animal Models of Cardiovascular Diseases

Acquisition of immunological memory is an important evolutionary strategy that evolved to protect the host from repetitive challenges from infectious agents. It was believed for a long time that memory formation exclusively occurs in the adaptive part of the immune system with the formation of highly specific memory T cells and B cells. In the past 10-15 years, it has become clear that innate immune cells, such as monocytes, natural killer cells, or neutrophil granulocytes, also have the ability to generate some kind of memory. After the exposure of innate immune cells to certain stimuli, these cells develop an enhanced secondary response with increased cytokine secretion even after an encounter with an unrelated stimulus. This phenomenon has been termed trained innate immunity (TI) and is associated with epigenetic modifications (histone methylation, acetylation) and metabolic alterations (elevated glycolysis, lactate production). TI has been observed in tissue-resident or circulating immune cells but also in bone marrow progenitors. Risk-factors for cardiovascular diseases (CVDs) which are associated with low-grade inflammation, such as hyperglycemia, obesity, or high salt, can also induce TI with a profound impact on the development and progression of CVDs. In this review, we briefly describe basic mechanisms of TI and summarize animal studies which specifically focus on TI in the context of CVDs.

Inflammation in the peripheral blood system of Crohn's Disease

Crohn's disease (CD) is an inflammatory bowel disease that is characterized by chronic inflammation of digestive system and has a nickname "green cancer" because of its sustained alternation of periods of flares and remissions. Here, we investigated the inflammation changes in peripheral blood system of CD patients, which are less reported in China. Peripheral blood samples of 167 CD patients and 30 healthy people, as well as their clinical information, were collected at the Second Affiliated Hospital of Soochow University. Flow cytometry was performed to analyze the ratio of CD4 T cells to CD8 T cells. Cytometric Bead Array kit was used to detect the cytokines in peripheral blood in CD patients. Moreover, the expression of inflammasomes was also detected by RT-PCR. The percentage and cell number of lymphocytes in CD patients' peripheral blood system decreased significantly, while monocytes increased remarkably. Interestingly, there was an inversion of the CD4 T cells/CD8 T cells ratio in peripheral blood of CD patients. The levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) increased significantly in CD patients' peripheral blood, and lipopolysaccharide (LPS) stimulation aggravate inflammatory response. In addition, the expression of nucleotide-binding oligomerization domain-like receptor family, pyrin domain-containing 1 (NLRP1) and NLRP3 in peripheral blood mononuclear cells (PBMC) of CD patients increased significantly after LPS stimulation. The inflammation in peripheral blood of CD patients had significant changes, including PBMC, cytokines and inflammasomes. These results are helpful to get a deeper understanding of CD and improve the efficiency of diagnosis and treatment in China.

Investigating the relationship between the number and activity of natural killer cells with increased cytomegalovirus and CMV disease after kidney transplantation

BACKGROUND

Cytomegalovirus (CMV) infections caused by the cytomegalovirus are one of the most common problems in patients after kidney transplant. We examined the association of the relationship between the number and activity of natural killer cells with increased cytomegalovirus and its related disease after kidney transplantation.

MATERIAL AND METHODS

In this analytical study, 58 new transplant patients in the Labbafinejad Hospital, who did not have any evidence of CMV infection, were evaluated based on the number and percentage of CD56+/16+, CD56+/16-, and CD69+ Natural Killer (NK) cells.

RESULTS

The results of this study showed that CD16+ and CD56+ cells in the group of CMV Ag-positive patients are less than negative patients (p = 0.003) and the difference between the two groups are significant (p = 0.01). However, CD69+ cells did not differ significantly between the two groups (p = 0.1). Moreover, the absolute number of CD16+ and CD56+ cells declined significantly after infection with CMV unlike the CMV Ag - group(p = 0.003).

DISCUSSION

These results indicate that kidney transplant patients suffering from CMV infection after transplantation have a significantly reduced total number of NK cells. On the other hand, a slight decrease in the number of NK subgroups was observed with an increase in the peak serum levels of cyclosporine. As a consequence of these findings, it can be assumed that more dosage and a higher level of the drug will result in more severe immunosuppression and, consequently, increased susceptibility to CMV infections. Thus, taking the right dose of the drug would prevent viral infections and immune system from over-activation.

Construction of the metabolic reprogramming-associated gene signature for clear cell renal cell carcinoma prognosis prediction

BACKGROUND

Metabolism reprogramming is a hallmark that associates tumor growth, metastasis, progressive, and poor prognosis. However, the metabolism-related molecular patterns and mechanism in clear cell renal cell carcinoma (ccRCC) remain unclear. Herein, the purpose of this study was to identify metabolism-related molecular pattern and to investigate the characteristics and prognostic values of the metabolism-related clustering.

METHODS

We comprehensively analyzed the differentially expressed genes (DEGs), and metabolism-related genes (MAGs) in ccRCC based on the TCGA database. Consensus clustering was used to construct a metabolism-related molecular pattern. Then, the biological function, molecular characteristics, Estimate/immune/stomal scores, immune cell infiltration, response to immunotherapy, and chemotherapy were analyzed. We also identified the DEGs between subclusters and constructed a poor signature and risk model based on LASSO regression cox analysis and univariable and multivariable cox regression analyses. Then, a predictive nomogram was constructed and validated by calibration curves.

RESULTS

A total of 1942 DEGs (1004 upregulated and 838 downregulated) between ccRCC tumor and normal samples were identified, and 254 MRGs were screened out from those DEGs. Then, 526 ccRCC patients were divided into two subclusters. The 7 metabolism-related pathways enriched in cluster 2. And cluster 2 with high Estimate/immune/stomal scores and poor survival. While, cluster 1 with higher immune cell infiltrating, expression of the immune checkpoint, IFN, HLA, immune activation-related genes, response to anti-CTLA4 treatment, and chemotherapy. Moreover, we identified 295 DEGs between two metabolism-related subclusters and constructed a 15-gene signature and 9 risk factors. Then, a risk score was calculated and the patients into high- and low-risk groups in TCGA-KIRC and E-MTAB-1980 datasets. And the prediction viability of the risk score was validated by ROC curves. Finally, the clinicopathological characteristics (age and stage), risk score, and molecular clustering, were identified as independent prognostic variables, and were used to construct a nomogram for 1-, 3-, 5-year overall survival predicting. The calibration curves were used to verify the performance of the predicted ability of the nomogram.

CONCLUSION

Our finding identified two metabolism-related molecular subclusters for ccRCC, which facilitates the estimation of response to immunotherapy and chemotherapy, and prognosis after treatment.

A novel anoikis-related gene prognostic signature and its correlation with the immune microenvironment in colorectal cancer

Background: Anoikis is a type of apoptosis associated with cell detachment. Resistance to anoikis is a focal point of tumor metastasis. This study aimed to explore the relationship among anoikis-related genes (ARGs), immune infiltration, and prognosis in colorectal cancer (CRC). Methods: The transcriptome profile and clinical data on patients with CRC were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Patients were divided into two clusters based on the expression of ARGs. Differences between the two ARG molecular subtypes were analyzed in terms of prognosis, functional enrichment, gene mutation frequency, and immune cell infiltration. An ARG-related prognostic signature for predicting overall survival in patients with CRC was developed and validated using absolute value convergence and selection operator (LASSO) regression analysis. The correlation between the signature risk score and clinicopathological features, immune cell infiltration, immune typing, and immunotherapy response was analyzed. The risk score combined with clinicopathological characteristics was used to construct a nomogram to assess CRC patients' prognosis. Results: Overall, 151 ARGs were differentially expressed in CRC. Two ARG subtypes, namely, ARG-high and ARG-low groups, were identified and correlated with CRC prognosis. The gene mutation frequency and immune, stromal, and ESTIMATE scores of the ARG-high group were higher than those of the ARG-low group. Moreover, CD8, natural killer cells, M1 macrophages, human leukocyte antigen (HLA), and immune checkpoint-related genes were significantly increased in the ARG-high group. An optimized 25-gene CRC prognostic signature was successfully constructed, and its prognostic predictive ability was validated. The high-risk score was correlated with T, N, M, and TNM stages. Risk scores were negatively correlated with dendritic cells, eosinophils, and CD4 cells, and significantly positively correlated with regulatory T cells. Patients in the high-risk group were more likely to exhibit immune unresponsiveness. Finally, the nomogram model was constructed and showed good prognostic predictive power. Conclusion: ARGs are associated with clinicopathological features and the prognosis of CRC, and play important roles in the immune microenvironment. Herein, we underpinned the usefulness of ARGs in CRC to develop more effective immunotherapy techniques.

KIF2C is a prognostic biomarker associated with immune cell infiltration in breast cancer

BACKGROUND

The kinesin-13 family member 2C (KIF2C) is a versatile protein participating in many biological processes. KIF2C is frequently up-regulated in multiple types of cancer and is associated with cancer development. However, the role of KIF2C in immune cell infiltration of tumor microenvironment and immunotherapy in breast cancer remains unclear.

METHODS

The expression of KIF2C was analyzed using Tumor Immune Estimation Resource (TIMER) database and further verified by immunohistochemical staining in human breast cancer tissues. The correlation between KIF2C expression and clinical parameters, the impact of KIF2C on clinical prognosis and independent prognostic factors were analyzed by using TCGA database, the Kaplan-Meier plotter, and Univariate and multivariate Cox analyses, respectively. The nomograms were constructed according to independent prognostic factors and validated with C-index, calibration curves, ROC curves, and decision curve analysis. A gene set enrichment analysis (GSEA) was performed to explore the underlying molecular mechanisms of KIF2C. The degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA (ssGSEA). The Tumor mutational burden and Tumor Immune Dysfunction and Rejection (TIDE) were used to analyze immunotherapeutic efficiency. Finally, the KIF2C-related competing endogenous RNA (ceRNA) network was constructed to predict the putative regulatory mechanisms of KIF2C.

RESULTS

KIF2C was remarkably up-regulated in 18 different types of cancers, including breast cancer. Kaplan-Meier survival analysis showed that high KIF2C expression was associated with poor overall survival (OS). KIF2C expression was associated with clinical parameters such as age, TMN stage, T status, and molecular subtypes. We identified age, stage, estrogen receptor (ER) and KIF2C expression as OS-related independent prognosis factors for breast cancer. An OS-related nomogram was developed based on these independent prognosis factors and displayed good predicting ability for OS of breast cancer patients. Finally, our results revealed that KIF2C was significantly related to immune cell infiltration, tumor mutational burden, and immunotherapy in patients with breast cancer.

CONCLUSION

KIF2C was overexpressed in breast cancer and was positively correlated with immune cell infiltration and immunotherapy response. Therefore, KIF2C can serve as a potential biomarker for prognosis and immunotherapy in breast cancer.

Exploring Prognosis, Tumor Microenvironment and Tumor Immune Infiltration in Hepatocellular Carcinoma Based on ATF/CREB Transcription Factor Family Gene-Related Model

Introduction

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer. It is the fourth leading cause of cancer-related death worldwide. Deregulation of the ATF/CREB family is associated with the progression of metabolic homeostasis and cancer. Because the liver plays a central role in metabolic homeostasis, it is critical to assess the predictive value of the ATF/CREB family in the diagnosis and prognosis of HCC.

Methods

Using data from The Cancer Genome Atlas (TCGA), this research evaluated the expression, copy number variations, and frequency of somatic mutations of 21 genes in the ATF/CREB family in HCC. A prognostic model based on the ATF/CREB gene family was developed via Lasso and Cox regression analyses, with the TCGA cohort serving as the training dataset and the International Cancer Genome Consortium (ICGC) cohort serving as the validation set. Kaplan-Meier and receiver operating characteristic analyses verified the accuracy of the prognostic model. Furthermore, the association among the prognostic model, immune checkpoints, and immune cells was examined.

Results

High-risk patients exhibited an unfavorable outcome as opposed to those in the low-risk category. Multivariate Cox analysis revealed that the risk score calculated based on the prognostic model was an independent prognostic factor for HCC. Analysis of immune mechanisms revealed that the risk score had a positive link to the expression of immune checkpoints, particularly CD274, PDCD1, LAG3, and CTLA4. Differences in immune cells and immune-associated roles were found between the high- and low-risk patients, as determined by single-sample gene set enrichment analysis. The core genes ATF1, CREB1, and CREB3 in the prognostic model were shown to be upregulated in HCC tissues as opposed to adjoining normal tissues, and the 10-year overall survival (OS) rate was worse among patients with elevated expression levels of ATF1, CREB1, and CREB3. Elevated expression levels of ATF1, CREB1, and CREB3 in HCC tissues were confirmed by qRT-PCR and immunohistochemistry studies.

Conclusion

According to the results of our training set and test set, the risk model based on the six ATF/CREB gene signatures predicting prognosis has certain predictive accuracy in predicting the survival of HCC patients. This study provides novel insights into the individualized treatment of patients with HCC.

Improved cancer immunotherapy strategies by nanomedicine

Cancer immunotherapy agents fight cancer via immune system stimulation and have made significant advances in minimizing side effects and prolonging the survival of patients with solid tumors. However, major limitations still exist in cancer immunotherapy, including the inefficiency of immune response stimulation in specific cancer types, therapy resistance caused by the tumor microenvironment (TME), toxicities by the immune imbalance, and short lifetime of stimulator of interferon genes (STING) agonist. Recent advances in nanomedicine have shown significant potential in overcoming the obstacles of cancer immunotherapy. Several nanoscale agents have been reported for cancer immunotherapy, including nanoscale cancer vaccines impacting the STING pathway, nanomaterials reprogramming TME, nano-agents triggering immune response with immune checkpoint inhibitor synergy, ferroptosis-mediated and indoleamine-2,3-dioxygenase immunosuppression-mediated cancer immunotherapy, and nanomedicine-meditated chimeric antigen receptor-T-cell therapy. Herein, we summarize the major advances and innovations in nanomedicine-based cancer immunotherapy, and outline the opportunities and challenges to integrate more advanced nanomaterials into cancer immunotherapy. This article is categorized under: Nanotechnology Approaches to Biology > Nanoscale Systems in Biology Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Therapeutic Approaches and Drug Discovery > Emerging Technologies.

IL-10-Secreting CD8(+) T Cells Specific for Human Cytomegalovirus (HCMV): Generation, Maintenance and Phenotype

HCMV-specific CD8⁺ T-cells are potent anti-viral effector cells in HCMV infected individuals, but evidence from other viral infections suggests that CD8⁺ T-cells can also produce the immunomodulatory cytokine IL-10. In this work we show that there are HCMV-specific IL-10 CD8⁺ T-cell responses in a cohort of individuals aged 23-76 years of age, predominantly directed against the HCMV proteins known to be expressed during latent infections as well as towards the proteins US3 and pp71. The analysis of HCMV-specific responses established during primary infection has shown that the IL-10 responses to US3 and pp71 HCMV proteins are detectable in the first weeks post infection, but not the responses to latency-associated proteins, and this IL-10 response is produced by both CD8⁺ and CD4⁺ T-cells. Phenotyping studies of HCMV-specific IL-10⁺ CD8⁺ T-cells show that these are CD45RA⁺ effector memory cells and co-express CD28 and CD57, however, the expression of the inhibitory receptor PD-1 varied from 90% to 30% between donors. In this study we have described for the first time the HCMV-specific IL-10 CD8⁺ T-cell responses and have demonstrated their broad specificity and the potential immune modulatory role of the immune response to HCMV latent carriage and periodic reactivation.

Identification of biomarkers associated with CD8+ T cells in rheumatoid arthritis and their pan-cancer analysis

Introduction

Rheumatoid arthritis (RA), a prevailing chronic progressive autoimmune disease, seriously affects the patient's quality of life. However, there is still a lack of precise treatment and management methods in clinical practice. Previous studies showed that CD8+ T cells take a lead in the progression of RA.

Methods

Genes closely related to CD8+T cells in RA were identified through multiple RA datasets, CIBERSORT, and WGCNA algorithms. Further machine learning analysis were performed to identify CD8+T cell-related genes most closely related to RA. In addition, the relationship between these three key genes and 33 cancer species was also explored in this study.

Results

In this study, 10 genes were identified to be closely related to CD8+T cells in RA. Machine learning analysis identified 3 CD8+T cell-related genes most closely related to RA: CD8A, GZMA, and PRF1.

Discussion

Our research aims to provide new ideas for the clinical treatment of RA.

Necroptosis throws novel insights on patient classification and treatment strategies for hepatocellular carcinoma

Introduction

Necroptosis is a novel pattern of immunogenic cell death and has triggered an emerging wave in antitumor therapy. More evidence has suggested the potential associations between necroptosis and intra-tumoral heterogeneity. Currently, the underlying role of necroptosis remains elusive in hepatocellular carcinoma (HCC) at antitumor immunity and inter-tumoral heterogeneity.

Methods

This study enrolled a total of 728 HCC patients and 139 immunotherapy patients from eight public datasets. The consensus clustering approach was employed to depict tumor heterogeneity of cancer necroptosis. Subsequently, our study further decoded the heterogeneous clinical outcomes, genomic landscape, biological behaviors, and immune characteristics in necroptosis subtypes. For each patient, providing curative clinical recommendations and developing potential therapeutic drugs were used to promote precise medicine.

Results

With the use of the weighted gene coexpression network analysis (WGCNA) algorithm, necroptosis-associated long non-coding RNAs (lncRNAs) (NALRs) were identified in HCC. Based on the NALR expression, two heterogeneous subtypes were decoded with distinct clinical outcomes. Compared to patients in C1, patients in C2 harbored superior pathological stage and presented more unfavorable overall survival and recurrence-free survival. Then, the robustness and reproducibility of necroptosis subtypes were further validated via the nearest template prediction (NTP) approach and classical immune phenotypes. Through comprehensive explorations, C1 was characterized by enriched immune-inflammatory and abundant immune infiltration, while C2 possessed elevated proliferative and metabolic activities and highly genomic instability. Moreover, our results indicated that C1 was more prone to obtain desirable benefits from immunotherapy. For patients in C2, numerous underlying therapeutic agents were developed, which might produce significant efficacy.

Conclusion

This study identified two necroptosis subtypes with distinct characteristics, decoding the tumor heterogeneity. For an individualized patient, our work tailored corresponding treatment strategies to improve clinical management.

Generation and Analysis of Pyroptosis-Based and Immune-Based Signatures for Kidney Renal Clear Cell Carcinoma Patients, and Cell Experiment

Background: Pyroptosis is a programmed cell death caused by inflammasomes, which is closely related to immune responses and tumor progression. The present study aimed to construct dual prognostic indices based on pyroptosis-associated and immune-associated genes and to investigate the impact of the biological signatures of these genes on Kidney Renal Clear Cell Carcinoma (KIRC).

Materials and Methods: All the KIRC samples from the Cancer Genome Atlas (TCGA) were randomly and equally divided into the training and testing datasets. Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis were used to screen crucial pyroptosis-associated genes (PAGs), and a pyroptosis-associated genes prognostic index (PAGsPI) was constructed. Immune-associated genes (IAGs) related to PAGs were identified, and then screened through Cox and LASSO regression analyses, and an immune-associated genes prognostic index (IAGsPI) was developed. These two prognostic indices were verified by using the testing and the Gene Expression Omnibus (GEO) datasets and an independent cohort. The patients’ response to immunotherapy was analyzed. A nomogram was constructed and calibrated. qRT-PCR was used to detect the expression of PAGs and IAGs in the tumor tissues and normal tissues. Functional experiment was carried out.

Results: 86 PAGs and 1,774 differentially expressed genes (DEGs) were obtained. After intersecting PAGs with DEGs, 22 differentially expressed PAGs (DEPAGs) were included in Cox and LASSO regression analyses, identifying 5 crucial PAGs. The PAGsPI was generated. Patients in the high-PAGsPI group had a poor prognosis. 82 differentially expressed IAGs (DEIAGs) were highly correlated with DEPAGs. 7 key IAGs were screened out, and an IAGsPI was generated. Patients in the high-IAGsPI group had a poor prognosis. PAGsPI and IAGsPI were verified to be robust and reliable. The results revealed patients in low-PAGsPI group and high-IAGsPI group may be more sensitive to immunotherapy. The calibrated nomogram was proved to be reliable. An independent cohort study also proved that PAGsPI and IAGsPI performed well in prognosis prediction. We found that the expression of AIM2 may affect proliferation of KIRC cells.

Conclusion: PAGsPI and IAGsPI could be regarded as potential biomarkers for predicting the prognosis of patients with KIRC.

The Expression of CD28 and Its Synergism on the Immune Response of Flounder (Paralichthys olivaceus) to Thymus-Dependent Antigen

CD28 is well known as a critical T-cell costimulatory receptor involved in T cell activation by binding to its ligands. In this study, CD28 was cloned, and its expression profiles were characterized in flounder (Paralichthys olivaceus); variations of CD28+ cells after being stimulated with different types of antigens and the function of the CD28 costimulatory pathway on T-cell activation were investigated in vitro. fCD28 consists of four exons and three introns, and the full-length cDNA of fCD28 was 675-bp encoded 224 amino acids. The conserved motif (121TFPPPF126) binding to the CD80/86 ligand exists in the Ig-superfamily homology domain. The high expression of fCD28 is in gills, PBLs, head kidney, and spleen. CD28+ cells were co-localized with CD4+ T lymphocytes but not on IgM+ B lymphocyte cells. Moreover, the expression of CD28 was significantly varied in flounder after being stimulated by keyhole limpet hemocyanin (KLH) at both the transcriptional and cellular levels, while no significant differences were observed between lipopolysaccharide (LPS) stimulation and the control group. Notably, treatment of PBLs cultured in vitro with CD28 molecule-specific antibody (anti-CD28 Abs) and PHA produced more cell colonies and stimulated the proliferation of cultured leukocytes compared to PHA stimulation alone and the control group, and a higher level of IL-2 was detected in the culture medium. Meanwhile, anti-CD28 Abs increased the percent of CD28+ cells (10.41 ± 1.35%), CD4+ T lymphocytes (18.32 ± 2.15%), and CD28+/CD4+ double-positive cells (6.24 ± 1.52%). This effect also resulted in significant variations in the genes of cell membrane-bound molecules, cytokines, and related signaling pathways in cultured leukocytes, with significant changes in the genes of interleukin-2 (IL-2) and nuclear factor of activated T cells (NFAT) in the early stages of culture, and the expression of other molecules increased over time. These results proved the localization of the CD28 molecule on T lymphocytes in flounder, and anti-CD28 may act as the B7 ligand involved in T cell activation after antigen stimulation. These data provide a basis for a more in-depth study of the mechanism of the CD28 costimulatory pathway in T cell activation.

CD8+ T effector and immune checkpoint signatures predict prognosis and responsiveness to immunotherapy in bladder cancer

Immune-checkpoint blockade (ICB) has been routinely implemented to treat bladder cancer; however, most patients have little or no clinical benefit. In this study, 348 pretreated metastatic urothelial cancer samples from the IMvigor210 cohort were used to identify important genes significantly associated with CD8+ T effector and immune checkpoint signatures. The immune checkpoint inhibitor score (IMS) scoring system was constructed to predict the immunotherapy responsiveness. Transcriptome analysis confirmed that the high IMS score group had significant immune activation with better prognosis and higher immunotherapy responsiveness, which was a powerful biomarker for predicting the prognosis and responsiveness of ICB. Tumor immune dysfunction and exclusion (TIDE) scores were calculated using 2031 external bladder cancer samples for further validation. We selected the important Hub genes as potential therapeutic targets, and validated the genes using genomic, transcriptomic, immunomic, and other multi-omics methods. In addition, we construct a risk prediction model which could stratify patients with bladder cancer and predict patient prognosis and ICB treatment responsiveness. In conclusion, this study identified effective biomarkers for the prediction of immune checkpoint inhibitor treatment responsiveness in bladder cancer patients and provided new immunotherapeutic targets.

The abscopal effect: a sense of DNA damage is in the air

Tumor metastasis is a singularly important determinant of survival in most cancers. Historically, radiation therapy (RT) directed at a primary tumor mass was associated infrequently with remission of metastasis outside the field of irradiation. This away-from-target or "abscopal effect" received fringe attention because of its rarity. With the advent of immunotherapy, there are now increasing reports of abscopal effects upon RT in combination with immune checkpoint inhibition. This sparked investigation into underlying mechanisms and clinical trials aimed at enhancement of this effect. While these studies clearly attribute the abscopal effect to an antitumor immune response, the initial molecular triggers for its onset and specificity remain enigmatic. Here, we propose that DNA damage-induced inflammation coupled with neoantigen generation is essential during this intriguing phenomenon of systemic tumor regression and discuss the implications of this model for treatment aimed at triggering the abscopal effect in metastatic cancer.

Super-Treg: Toward a New Era of Adoptive Treg Therapy Enabled by Genetic Modifications

Regulatory Tcells (Treg) are essential components of peripheral immune homeostasis. Adoptive Treg cell therapy has shown efficacy in a variety of immune-mediated diseases in preclinical studies and is now moving from phase I/IIa to larger phase II studies aiming to demonstrate efficacy. However, hurdles such as in vivo stability and efficacy remain to be addressed. Nevertheless, preclinical models have shown that Treg function and specificity can be increased by pharmacological substances or gene modifications, and even that conventional T cells can be converted to Treg potentially providing new sources of Treg and facilitating Treg cell therapy. The exponential growth in genetic engineering techniques and their application to T cells coupled to a large body of knowledge on Treg open numerous opportunities to generate Treg with "superpowers". This review summarizes the genetic engineering techniques available and their applications for the next-generation of Super-Treg with increased function, stability, redirected specificity and survival.