GLT8D2 is a prognostic biomarker and regulator of immune cell infiltration in gastric cancer.

Because of the considerable tumor heterogeneity in gastric cancer (GC), only a limited group of patients experiences positive outcomes from immunotherapy. Herein, we aim to develop predictive models related to glycosylation genes to provide a more comprehensive understanding of immunotherapy for GC. RNA sequencing (RNA-seq) data and corresponding clinical outcomes were obtained from GEO and TCGA databases, and glycosylation-related genes were obtained from GlycoGene DataBase. We identified 48 differentially expressed glycosylation-related genes and established a prognostic model (seven prognosis genes including GLT8D2, GALNT6, ST3GAL6, GALNT15, GBGT1, FUT2, GXYLT2) based on these glycosylation-related genes using the results from Cox regression analysis. We found that these glycosylation-related genes revealed a robust correlation with the abundance of Tumor Infiltrating Lymphocytes (TILs), especially the GLT8D2 which is associated with many TILs. Finally, we employed immunohistochemistry and Multiplex Immunohistochemical to discover that GLT8D2 serves as a valuable prognostic biomarker in GC and is closely associated with macrophage-related markers. Collectively, we established a prognostic model based on glycosylation-related genes to provide a more comprehensive understanding of prediction for GC prognosis, and identified that GLT8D2 is closely correlated with adverse prognosis and may underscore its role in regulating immune cell infiltration in GC patients.

Immune cell infiltration and prognostic index in cervical cancer: insights from metabolism-related differential genes.

Background: Cervical cancer remains a significant gynecologic malignancy in both China and the United States, posing a substantial threat to women's lives and health due to its high morbidity and mortality rates. Altered energy metabolism and dysregulated mitochondrial function play crucial roles in the development, growth, metastasis, and recurrence of malignant tumors. In this study, we aimed to predict prognosis and assess efficacy of anti-tumor therapy in cervical cancer patients based on differential genes associated with mitochondrial metabolism. Methods: Transcriptomic data and clinical profiles of cervical cancer patients were retrieved from the TCGA and GEO databases. Differential gene-related cellular pathways were identified through GO, KEGG, and GSEA analyses. Prognostic indices were constructed using LASSO regression analysis. Immune cell infiltration was assessed using CIBERSORT and ssGSEA, and the correlation between immune checkpoint inhibitor genes and differential genes was examined. Tumor mutation load (TMB) and its association with prognostic indices were analyzed using nucleotide variant data from the TCGA database. Patient response to immunotherapy and sensitivity to antitumor drugs were determined using the TIDE algorithm and the oncoPredic algorithm, respectively. Results: A prognostic index based on metabolism-related differential genes was developed to predict the clinical outcome of cervical cancer patients, enabling their classification into two distinct subtypes. The prognostic index emerged as an independent risk factor for unfavorable prognosis. The high-index group exhibited a significantly worse overall prognosis, along with elevated tumor mutation burden (TMB), increased immune cell infiltration, and lower TIDE scores, indicating a potential benefit from immunotherapy. Conversely, the low-index group demonstrated increased sensitivity to metabolism-related antitumor agents, specifically multikinase inhibitors. Conclusion: The aim of this study was to develop a prognostic index based on differential genes associated with mitochondrial metabolism, which could be used to predict cervical cancer patients' prognoses. When combined with TIDE and TMB analyses, this prognostic index offers insights into the immune cell infiltration landscape, as well as the potential efficacy of immunotherapy and targeted therapy. Our analysis suggests that the Iron-Sulfur Cluster Assembly Enzyme (ISCU) gene holds promise as a biomarker for cervical cancer immunotherapy.

USP47 deficiency in mice modulates tumor infiltrating immune cells and enhances antitumor immune responses in prostate cancer.

This study investigates the role of USP47, a deubiquitinating enzyme, in the tumor microenvironment and its impact on antitumor immune responses. Analysis of TCGA database revealed distinct expression patterns of USP47 in various tumor tissues and normal tissues. Prostate adenocarcinoma showed significant downregulation of USP47 compared to normal tissue. Correlation analysis demonstrated a positive association between USP47 expression levels and infiltrating CD8+ T cells, neutrophils, and macrophages, while showing a negative correlation with NKT cells. Furthermore, using Usp47 knockout mice, we observed a slower tumor growth rate and reduced tumor burden. The absence of USP47 led to increased infiltration of immune cells, including neutrophils, macrophages, NK cells, NKT cells, and T cells. Additionally, USP47 deficiency resulted in enhanced activation of cytotoxic T lymphocytes (CTLs) and altered T cell subsets within the tumor microenvironment. These findings suggest that USP47 plays a critical role in modulating the tumor microenvironment and promoting antitumor immune responses, highlighting its potential as a therapeutic target in prostate cancer.

Rocaglamide promotes infiltration and differentiation of T cells and coordinates with PD-1 inhibitor to overcome checkpoint resistance in multiple tumor models.

Tumor-infiltrating lymphocyte (TIL) deficiency is the most conspicuous obstacle to limit the cancer immunotherapy. Immune checkpoint inhibitors (ICIs), such as anti-PD-1 antibody, have achieved great success in clinical practice. However, due to the limitation of response rates of ICIs, some patients fail to benefit from monotherapy. Thus, novel combination therapy that could improve the response rates emerges as new strategies for cancer treatment. Here, we reported that the natural product rocaglamide (RocA) increased tumor-infiltrating T cells and promoted Th17 differentiation of CD4+ TILs. Despite RocA monotherapy upregulated PD-1 expression of TILs, which was considered as the consequence of T cell activation, combining RocA with anti-PD-1 antibody significantly downregulated the expression of PD-1 and promoted proliferation of TILs. Taken together, these findings demonstrated that RocA could fuel the T cell anti-tumor immunity and revealed the remarkable potential of RocA as a therapeutic candidate when combining with the ICIs.

Enhanced abscopal anti-tumor response via a triple combination of thermal ablation, IL-21, and PD-1 inhibition therapy.

Despite the success of immune checkpoint inhibitors (ICIs) in treating solid tumors, lots of patients remain unresponsive to this therapy. Microwave ablation (MWA) stimulates systemic adaptive immunity against tumor cells by releasing tumor antigens. Additionally, IL-21 has demonstrated importance in stimulating T-cell effector function. The combination of these three therapies-MWA, IL-21, and anti-PD-1 monoclonal antibodies (mAbs)-has yet to be explored in the context of cancer treatment.In this study, we explored the impact of thermal ablation on IL-21R expression in tumor-infiltrating lymphocytes (TILs). Subsequently, we assessed alterations in the tumor microenvironment (TME) and peripheral lymphoid organs. Additionally, we conducted a thorough examination of tumor-infiltrating CD45+ immune cells across various treatment groups using single-cell RNA sequencing (scRNA-seq). Moreover, we determined the potential anti-tumor effects of the triple combination involving MWA, IL-21, and anti-PD-1 mAbs.Our findings revealed that MWA upregulated the expression of IL-21R on various immune cells in the untreated tumors. The combination of MWA with IL-21 exhibited a robust abscopal anti-tumor effect, enhancing the effector function of CD8+ T cells and facilitating dendritic cells' maturation and antigen presentation in the untreated tumor. Notably, the observed abscopal anti-tumor effect resulting from the combination is contingent upon T-cell recirculation, indicating the reliance of systemic adaptive immunity for this treatment regimen. Additionally, the combination of MWA, IL-21, and PD-1 mAbs demonstrated profound abscopal anti-tumor efficacy. Our findings provide support for further clinical investigation into a triple combination therapy involving MWA, IL-21, and ICIs for the treatment of metastatic cancer.

Machine learning-based identification of a cell death-related signature associated with prognosis and immune infiltration in glioma.

Accumulating evidence suggests that a wide variety of cell deaths are deeply involved in cancer immunity. However, their roles in glioma have not been explored. We employed a logistic regression model with the shrinkage regularization operator (LASSO) Cox combined with seven machine learning algorithms to analyse the patterns of cell death (including cuproptosis, ferroptosis, pyroptosis, apoptosis and necrosis) in The Cancer Genome Atlas (TCGA) cohort. The performance of the nomogram was assessed through the use of receiver operating characteristic (ROC) curves and calibration curves. Cell-type identification was estimated by using the cell-type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) and single sample gene set enrichment analysis methods. Hub genes associated with the prognostic model were screened through machine learning techniques. The expression pattern and clinical significance of MYD88 were investigated via immunohistochemistry (IHC). The cell death score represents an independent prognostic factor for poor outcomes in glioma patients and has a distinctly superior accuracy to that of 10 published signatures. The nomogram performed well in predicting outcomes according to time-dependent ROC and calibration plots. In addition, a high-risk score was significantly related to high expression of immune checkpoint molecules and dense infiltration of protumor cells, these findings were associated with a cell death-based prognostic model. Upregulated MYD88 expression was associated with malignant phenotypes and undesirable prognoses according to the IHC. Furthermore, high MYD88 expression was associated with poor clinical outcomes and was positively related to CD163, PD-L1 and vimentin expression in the in-horse cohort. The cell death score provides a precise stratification and immune status for glioma. MYD88 was found to be an outstanding representative that might play an important role in glioma.

GGT5: a potential immunotherapy response inhibitor in gastric cancer by modulating GSH metabolism and sustaining memory CD8+ T cell infiltration.

PURPOSE: The variable responses to immunotherapy observed in gastric cancer (GC) patients can be attributed to the intricate nature of the tumor microenvironment. Glutathione (GSH) metabolism significantly influences the initiation and progression of gastric cancer. Consequently, targeting GSH metabolism holds promise for improving the effectiveness of Immune checkpoints inhibitors (ICIs). METHODS: We investigated 16 genes related to GSH metabolism, sourced from the MSigDB database, using pan-cancer datasets from TCGA. The most representative prognosis-related gene was identified for further analysis. ScRNA-sequencing analysis was used to explore the tumor heterogeneity of GC, and the results were confirmed by  Multiplex immunohistochemistry (mIHC). RESULTS: Through DEGs, LASSO, univariate and multivariate Cox regression analyses, and survival analysis, we identified GGT5 as the hub gene in GSH metabolism with the potential to promote GC. Combining CIBERSORT, ssGSEA, and scRNA analysis, we constructed the immune architecture of GC. The subpopulations of T cells were isolated, revealing a strong association between GGT5 and memory CD8+ T cells. Furthermore, specimens from 10 GC patients receiving immunotherapy were collected. mIHC was used to assess the expression levels of GGT5 and memory CD8+ T cell markers. Our results established a positive correlation between GGT5 expression, the enrichment of memory CD8+ T cells, and a suboptimal response to immunotherapy. CONCLUSIONS: Our study identifies GGT5, a hub gene in GSH metabolism, as a potential therapeutic target for inhibiting the response to immunotherapy in GC patients. These findings offer new insights into strategies for optimizing immunotherapy of GC.

The cell cycle regulator p16 promotes tumor infiltrated CD8+ T cell exhaustion and apoptosis.

The therapeutic efficacy of adoptive T cell therapy is largely restricted by reduced viability and dysfunction of CD8+ T cells. Continuous antigen stimulation disrupts the expansion, effector function, and metabolic fitness of CD8+ T cells, leading to their differentiation into an exhausted state within the tumor microenvironment (TME). While the function of the cell cycle negative regulator p16 in senescent cells is well understood, its role in T cell exhaustion remains unclear. In this study, we demonstrated that TCR stimulation of CD8+ T cells rapidly upregulates p16 expression, with its levels positively correlating with TCR affinity. Chronic TCR stimulation further increased p16 expression, leading to CD8+ T cell apoptosis and exhaustion differentiation, without inducing DNA damage or cell senescence. Mechanistic investigations revealed that p16 downregulates mTOR, glycolysis, and oxidative phosphorylation (OXPHOS) associated gene expression, resulting in impaired mitochondrial fitness, reduced T cell viability, and diminished effector function. Furthermore, the deletion of p16 significantly enhances the persistence of CD8+ T cells within tumors and suppresses the terminal exhaustion of tumor-infiltrating T cells. Overall, our findings elucidate how increased p16 expression reshapes T cell intracellular metabolism, drives T cell apoptosis and exhaustion differentiation, and ultimately impairs T cell anti-tumor function.

An NGS-based assay for accurate detection and quantification of immune gene expression in mouse tumor models.

Tumor microenvironment (TME) is a complex dynamic system with many tumor-interacting components including tumor-infiltrating leukocytes (TILs), cancer associated fibroblasts, blood vessels, and other stromal constituents. It intrinsically affects tumor development and pharmacology of oncology therapeutics, particularly immune-oncology (IO) treatments. Accurate measurement of TME is therefore of great importance for understanding the tumor immunity, identifying IO treatment mechanisms, developing predictive biomarkers, and ultimately, improving the treatment of cancer. Here, we introduce a mouse-IO NGS-based (NGSmIO) assay for accurately detecting and quantifying the mRNA expression of 1080 TME related genes in mouse tumor models. The NGSmIO panel was shown to be superior to the commonly used microarray approach by hosting 300 more relevant genes to better characterize various lineage of immune cells, exhibits improved mRNA and protein expression correlation to flow cytometry, shows stronger correlation with mRNA expression than RNAseq with 10x higher sequencing depth, and demonstrates higher sensitivity in measuring low-expressed genes. We describe two studies; firstly, detecting the pharmacodynamic change of interferon-γ expression levels upon anti-PD-1: anti-CD4 combination treatment in MC38 and Hepa 1-6 tumors; and secondly, benchmarking baseline TILs in 14 syngeneic tumors using transcript level expression of lineage specific genes, which demonstrate effective and robust applications of the NGSmIO panel.

Response to Neoadjuvant Chemotherapy in Invasive Breast Cancer Predicted by CD4+, CD8+, and FOXP3+ Tumor-Infiltrating Lymphocytes.

BACKGROUND: Response to neoadjuvant chemotherapy (NC) in individuals with invasive breast cancer (IBC) must be monitored, and biomarkers are needed. NC can activate an anti-tumour immune response in its microenvironment, known as Tumor-infiltrating Lymphocytes (TIL). TIL components believed to have great potential as predictors are CD4+, CD8+, and FOXP3+ TIL. This study aims to explore TIL components that can potentially be predictive biomarkers of NC pathological responses. METHODS: A sample size of 40 were analyzed based on the relationship between CD4+, CD8+, and FOXP3+ TIL expression with the Miller-Payne (MP) grading system. Age, tumour grade, PR, ER, Ki-67, and HER2 were also evaluated. CD4+, CD8+, and FOXP3+ TIL expressions were analayzed by IHC staining, while other data were collected from archives. Data was analyzed using univariate and multivariate analysis. RESULTS: Univariate analysis showed a significant relationship between CD4+ TIL and MP (p<0.001), CD8+ and MP (p=0.004), and FOXP3 with MP (p<0.001). The simultaneous integration of the three biomarkers in one model was not good enough to be a predictive model. Therefore, an exploratory analysis was conducted by testing several alternative models that combined two of the three existing biomarkers. It turned out that CD4+ TIL in model 2 (CD4+CD8+) and FOXP3+ TIL in model 4 (CD8+FOXP3+) showed significant coefficient values. Moreover, all of the threshold coefficients in model 4 are significant. CONCLUSION: This study shows that CD4+, CD8+, and FOXP3+ TIL have promising potential as predictive biomarkers. In particular, FOXP3+ is dominant in predictive models of pathological response in patients with IBC.

Profiling of Tumor-Infiltrating Immune Cells and Their Impact on Survival in Glioblastoma Patients Undergoing Immunotherapy with Dendritic Cells.

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients' overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.

Tumor-Intrinsic Enhancer of Zeste Homolog 2 Controls Immune Cell Infiltration, Tumor Growth, and Lung Metastasis in a Triple-Negative Breast Cancer Model.

Triple-negative breast cancer (TNBC) is an aggressive and highly metastatic type of tumor. TNBC is often enriched in tumor-infiltrating neutrophils (TINs), which support cancer growth in part by counteracting tumor-infiltrating lymphocytes (TILs). Prior studies identified the enhancer of zeste homolog 2 (EZH2) as a pro-tumor methyltransferase in primary and metastatic TNBCs. We hypothesized that EZH2 inhibition in TNBC cells per se would exert antitumor activity by altering the tumor immune microenvironment. To test this hypothesis, we used CRISPR to generate EZH2 gene knockout (KO) and overexpressing (OE) lines from parent (wild-type-WT) 4T1 cells, an established murine TNBC model, resulting in EZH2 protein KO and OE, respectively. In vitro, EZH2 KO and OE cells showed early, transient changes in replicative capacity and invasiveness, and marked changes in surface marker profile and cytokine/chemokine secretion compared to WT cells. In vivo, EZH2 KO cells showed significantly reduced primary tumor growth and a 10-fold decrease in lung metastasis compared to WT cells, while EZH2 OE cells were unchanged. Compared to WT tumors, TIN:TIL ratios were greatly reduced in EZH2 KO tumors but unchanged in EZH2 OE tumors. Thus, EZH2 is key to 4T1 aggressiveness as its tumor-intrinsic knockout alters their in vitro secretome and in vivo primary tumor growth, TIN/TIL poise, and metastasis.

Tumorigenic role of Pak4 in ovarian cancer and its correlation with immune infiltration.

BACKGROUND: Ovarian cancer is the most common cause of gynecological cancer death. Pak4 has been proved to be tumorigenic in many types of cancers, but its role in ovarian cancer is still not clarified. METHODS: In this study, we used immunohistochemistry to investigate into Pak4 expression in different histological types of ovarian cancer. TIMER, TISCH2, GEPIA, ualcan, KM plotter, GSCA and GeneMANIA were used to identify the prognostic roles and gene regulation networks of Pak4 in ovarian cancer. Immune infiltration levels were investigated using TIMER database. RESULTS: Pak4 was highly expressed in ovarian cancers, regardless of different FIGO stages and histological grades. Single cell sequencing database proved that Pak4 was highly expressed in malignant ovarian cancer cells. Pak4 level was significantly correlated with different histological types of ovarian cancer. Pak4 expression was negatively connected with OS and PFS of ovarian cancer patients. Functions of Pak4 and its interacted genes were mainly involved in protein serine/threonine kinase activity, regulation of actin filament-based process and regulation of cytoskeleton organization. Pak4 level was negatively correlated with immune biomarkers of B cell infiltration (p = 2.39e-05), CD8 + T cell infiltration (p = 1.51e-04), neutrophil (p = 1.74e-06) and dendritic cell (p = 4.41e-08). Close correlation was found between Pak4 expression and T cell exhaustion (p < 0.05). CONCLUSIONS: Our results demonstrated the expression level, gene interaction networks and immune infiltration levels of Pak4 in ovarian cancer. And the results revealed role of Pak4 in tumorigenesis and the possibility to be a potential immunotherapeutic target.

Single-cell sequencing of tumour infiltrating T cells efficiently identifies tumour-specific T cell receptors based on the T cell activation score.

Adoptively transferred T cell receptor-engineered T cells are a promising cancer treatment strategy, and the identification of tumour-specific TCRs is essential. Previous studies reported that tumour-reactive T cells and TCRs could be isolated based on the expression of activation markers. However, since T cells with different cell states could not respond uniformly to activation but show a heterogeneous expression profile of activation and effector molecules, isolation of tumour-reactive T cells based on single activation or effector molecules could result in the absence of tumour-reactive T cells; thus, combinations of multiple activation and effector molecules could improve the efficiency of isolating tumour-specific TCRs. We enrolled two patients with lung adenocarcinoma and obtained their tumour infiltrating lymphocytes (TILs) and autologous tumour cells (ATCs). TILs were cocultured with the corresponding ATCs for 12 h and subjected to single-cell RNA sequencing. First, we identified three TCRs with the highest expression levels of IFNG and TNFRSF9 mRNA for each patient, yet only the top one or two recognized the corresponding ATCs in each patient. Next, we defined the activation score based on normalized expression levels of IFNG, IL2, TNF, IL2RA, CD69, TNFRSF9, GZMB, GZMA, GZMK, and PRF1 mRNA for each T cell and then identified three TCRs with the highest activation score for each patient. We found that all three TCRs in each patient could specifically identify corresponding ATCs. In conclusion, we established an efficient approach to isolate tumour-reactive TCRs based on combinations of multiple activation and effector molecules through single-cell RNA sequencing.

MLXIPL associated with tumor-infiltrating CD8+ T cells is involved in poor prostate cancer prognosis.

Introduction: Within tumor microenvironment, the presence of preexisting antitumor CD8+ T Q7 cells have been shown to be associated with a favorable prognosis in most solid cancers. However, in the case of prostate cancer (PCa), they have been linked to a negative impact on prognosis. Methods: To gain a deeper understanding of the contribution of infiltrating CD8+ T cells to poor prognosis in PCa, the infiltration levelsof CD8+ T cells were estimated using the TCGA PRAD (The Cancer Genome Atlas Prostate Adenocarcinoma dataset) and MSKCC (Memorial Sloan Kettering Cancer Center) cohorts. Results: Bioinformatic analyses revealed that CD8+ T cells likely influence PCa prognosis through increased expression of immune checkpoint molecules and enhanced recruitment of regulatory T cells. The MLXIPL was identified as the gene expressed in response to CD8+ T cell infiltration and was found to be associated with PCa prognosis. The prognostic role of MLXIPL was examined in two cohorts: TCGA PRAD (p = 2.3E-02) and the MSKCC cohort (p = 1.6E-02). Subsequently, MLXIPL was confirmed to be associated with an unfavorable prognosis in PCa, as evidenced by an independent cohort study (hazard ratio [HR] = 2.57, 95% CI: 1.42- 4.65, p = 1.76E-03). Discussion: In summary, the findings suggested that MLXIPL related to tumor-infiltrating CD8+ T cells facilitated a poor prognosis in PCa.

In situ analysis of CCR8+ regulatory T cells in lung cancer: suppression of GzmB+ CD8+ T cells and prognostic marker implications.

BACKGROUND: CCR8-expressing regulatory T cells (Tregs) are selectively localized within tumors and have gained attention as potent suppressors of anti-tumor immunity. This study focused on CCR8+ Tregs and their interaction with CD8+ T cells in the tumor microenvironment of human lung cancer. We evaluated their spatial distribution impact on CD8+ T cell effector function, specifically granzyme B (GzmB) expression, and clinical outcomes. METHODS: A total of 81 patients with lung squamous cell carcinoma (LSCC) who underwent radical surgical resection without preoperative treatment were enrolled. Histological analyses were performed, utilizing an automated image analysis system for double-stained immunohistochemistry assays of CCR8/Foxp3 and GzmB/CD8. We investigated the association of CCR8+ Tregs and GzmB+ CD8+ T cells in tumor tissues and further evaluated the prognostic impact of their distribution profiles. RESULTS: Histological evaluation using the region of interest (ROI) protocol showed that GzmB expression levels in CD8+ T cells were decreased in areas with high infiltration of CCR8+ Tregs, suggesting a suppressive effect of CCR8+ Tregs on T cell cytotoxicity in the local tumor microenvironment. Analysis of the association with clinical outcomes showed that patients with more CCR8+ Tregs and lower GzmB expression, represented by a low GzmB/CCR8 ratio, had worse progression-free survival. CONCLUSIONS: Our data suggest that local CCR8+ Treg accumulation is associated with reduced CD8+ T cell cytotoxic activity and poor prognosis in LSCC patients, highlighting the biological role and clinical significance of CCR8+ Tregs in the tumor microenvironment. The GzmB/CCR8 ratio may be a useful prognostic factor for future clinical applications in LSCC.

Immune cell infiltration and inflammatory landscape in primary brain tumours.

BACKGROUND: Primary malignant brain tumours are more than one-third of all brain tumours and despite the molecular investigation to identify cancer driver mutations, the current therapeutic options available are challenging due to high intratumour heterogeneity. In addition, an immunosuppressive and inflammatory tumour microenvironment strengthens cancer progression. Therefore, we defined an immune and inflammatory profiling of meningioma and glial tumours to elucidate the role of the immune infiltration in these cancer types. METHODS: Using tissue microarrays of 158 brain tumour samples, we assessed CD3, CD4, CD8, CD20, CD138, Granzyme B (GzmB), 5-Lipoxygenase (5-LOX), Programmed Death-Ligand 1 (PD-L1), O-6-Methylguanine-DNA Methyltransferase (MGMT) and Transglutaminase 2 (TG2) expression by immunohistochemistry (IHC). IHC results were correlated using a Spearman correlation matrix. Transcript expression, correlation, and overall survival (OS) analyses were evaluated using public datasets available on GEPIA2 in Glioblastoma (GBM) and Lower Grade Glioma (LGG) cohorts. RESULTS: Seven out of ten markers showed a significantly different IHC expression in at least one of the evaluated cohorts whereas CD3, CD4 and 5-LOX were differentially expressed between GBMs and astrocytomas. Correlation matrix analysis revealed that 5-LOX and GzmB expression were associated in both meningiomas and GBMs, whereas 5-LOX expression was significantly and positively correlated to TG2 in both meningioma and astrocytoma cohorts. These findings were confirmed with the correlation analysis of TCGA-GBM and LGG datasets. Profiling of mRNA levels indicated a significant increase in CD3 (CD3D, CD3E), and CD138 (SDC1) expression in GBM compared to control tissues. CD4 and 5-LOX (ALOX5) mRNA levels were significantly more expressed in tumour samples than in normal tissues in both GBM and LGG. In GBM cohort, GzmB (GZMB), SDC1 and MGMT gene expression predicted a poor overall survival (OS). Moreover, in LGG cohort, an increased expression of CD3 (CD3D, CD3E, CD3G), CD8 (CD8A), GZMB, CD20 (MS4A1), SDC1, PD-L1, ALOX5, and TG2 (TGM2) genes was associated with worse OS. CONCLUSIONS: Our data have revealed that there is a positive and significant correlation between the expression of 5-LOX and GzmB, both at RNA and protein level. Further evaluation is needed to understand the interplay of 5-LOX and immune infiltration in glioma progression.

PD-1-CD28-enhanced receptor and CD19 CAR-modified tumor-infiltrating T lymphocytes produce potential anti-tumor ability in solid tumors.

The limited expansion ability and functional inactivation of T cells within the solid tumor microenvironment are major problems faced during in the application of using tumor-infiltrating lymphocytes (TILs) in vivo. We sought to determine whether TILs carrying a PD-1-CD28-enhanced receptor and CD19 CAR could overcome this limitation and mediate tumor regression. First, anti-tumor effects of PD-1-CD28-enhanced receptor or CD19 CAR modified NY-ESO-1-TCR-T cells to mimic the TILs function (hereafter "PD-1-CD28-TCR-T" or "CD19 CAR-TCR-T" cells, respectively) were tested using the NY-ESO-1 over-expressed tumor cell line in vitro and in a tumor-bearing model. Furthermore, the safety and anti-tumor ability of S-TILs (TILs modified through transduction with a plasmid encoding the PD-1-CD28-T2A-CD19 CAR) were evaluated in vivo. PD-1-CD28-TCR-T cells showed a formidable anti-tumor ability that was not subject to PD-1/PD-L1 signaling in vivo. CD19 CAR-TCR-T cells stimulated with CD19+ B cells exhibited powerful expansion and anti-tumor abilities both in vitro and in vivo. Three patients with refractory solid tumors received S-TILs infusion. No treatment-related mortality was observed, and none of the patients experienced serious side effects. One patient with melanoma achieved a partial response, and two patients with colon or kidney cancer achieved long-term stable disease following S-TILs therapy. To the best of our knowledge, this is the first study describing the safety and efficacy of the adoptive transfer of autologous S-TILs to control disease in patients with advanced cancers, suggesting that S-TILs may be a promising alternative therapy for cancer.

Fluorescence tracking demonstrates T cell recirculation is transiently impaired by radiation therapy to the tumor.

T cells recirculate through tissues and lymphatic organs to scan for their cognate antigen. Radiation therapy provides site-specific cytotoxicity to kill cancer cells but also has the potential to eliminate the tumor-specific T cells in field. To dynamically study the effect of radiation on CD8 T cell recirculation, we used the Kaede mouse model to photoconvert tumor-infiltrating cells and monitor their movement out of the field of radiation. We demonstrate that radiation results in loss of CD8 T cell recirculation from the tumor to the lymph node and to distant sites. Using scRNASeq, we see decreased proliferating CD8 T cells in the tumor following radiation therapy resulting in a proportional enrichment in exhausted phenotypes. By contrast, 5 days following radiation increased recirculation of T cells from the tumor to the tumor draining lymph node corresponds with increased immunosurveillance of the treated tumor. These data demonstrate that tumor radiation therapy transiently impairs systemic T cell recirculation from the treatment site to the draining lymph node and distant untreated tumors. This may inform timing therapies to improve systemic T cell-mediated tumor immunity.