CTLA4 promoter hypomethylation is a negative prognostic biomarker at initial diagnosis but predicts response and favorable outcome to anti-PD-1 based immunotherapy in clear cell renal cell carcinoma

Basic immunologic study as a foundation for engineered therapeutic development

Bioengineering and drug delivery technologies play an important role in bridging the gap between basic scientific discovery and clinical application of therapeutics. To identify the optimal treatment, the most critical stage is to diagnose the problem. Often these two may occur simultaneously or in parallel, but in this review, we focus on bottom-up approaches in understanding basic immunologic phenomena to develop targeted therapeutics. This can be observed in several fields; here, we will focus on one of the original immunotherapy targets-cancer-and one of the more recent targets-regenerative medicine. By understanding how our immune system responds in processes such as malignancies, wound healing, and medical device implantation, we can isolate therapeutic targets for pharmacologic and bioengineered interventions.

PD1/PD-L1 blockade in clear cell renal cell carcinoma: mechanistic insights, clinical efficacy, and future perspectives

The advent of PD1/PD-L1 inhibitors has significantly transformed the therapeutic landscape for clear cell renal cell carcinoma (ccRCC). This review provides an in-depth analysis of the biological functions and regulatory mechanisms of PD1 and PD-L1 in ccRCC, emphasizing their role in tumor immune evasion. We comprehensively evaluate the clinical efficacy and safety profiles of PD1/PD-L1 inhibitors, such as Nivolumab and Pembrolizumab, through a critical examination of recent clinical trial data. Furthermore, we discuss the challenges posed by resistance mechanisms to these therapies and potential strategies to overcome them. We also explores the synergistic potential of combination therapies, integrating PD1/PD-L1 inhibitors with other immunotherapies, targeted therapies, and conventional modalities such as chemotherapy and radiotherapy. In addition, we examine emerging predictive biomarkers for response to PD1/PD-L1 blockade and biomarkers indicative of resistance, providing a foundation for personalized therapeutic approaches. Finally, we outline future research directions, highlighting the need for novel therapeutic strategies, deeper mechanistic insights, and the development of individualized treatment regimens. Our work summarizes the latest knowledge and progress in this field, aiming to provide a valuable reference for improving clinical efficacy and guiding future research on the application of PD1/PD-L1 inhibitors in ccRCC.

PD-L1 (CD274) promoter hypomethylation predicts immunotherapy response in metastatic urothelial carcinoma

PD-L1 status assessed by immunohistochemistry (IHC) has failed to reliably predict outcomes for patients with metastatic urothelial carcinoma (mUC) on immune checkpoint blockade (ICB). PD-L1 promoter methylation is an epigenetic mechanism that has been shown to regulate PD-L1 mRNA expression in various malignancies. The aim of our present study was to evaluate the predictive potential of PD-L1 promoter methylation status (mPD-L1) in ICB-treated mUC compared to conventional IHC-based PD-L1 assessment. We quantified mPD-L1 in formalin-fixed and paraffin-embedded tissue sections using an established quantitative methylation-specific PCR assay (qMSP) in a well-characterized multicenter ICB-treated cohort comprising N = 107 patients with mUC. Additionally, PD-L1 protein expression in tumor tissues was assessed using regulatory approved IHC protocols. The effect of pharmacological hypomethylation by the DNA methyltransferase inhibitor decitabine in combination with interferon-γ stimulation in urothelial carcinoma cell lines was investigated by IHC and FACS. mPD-L1 hypomethylation predicted objective response rate at the first staging on ICB. Patients with tumors categorized as PD-L1 hypomethylated (lower quartile) showed significantly prolonged progression-free (PFS) and overall survival (OS) after ICB initiation. In contrast, PD-L1 protein expression status neither correlated with response nor survival. In multivariable Cox regression analyses, PD-L1 promoter hypermethylation remained an independent predictor of unfavorable PFS and OS. In urothelial carcinoma cell lines, pharmacological demethylation led to an upregulation of membranous PD-L1 expression and an enhanced inducibility of PD-L1 expression by interferon γ. Hypomethylation of the PD-L1 promoter is a promising predictive biomarker for response to ICB in patients with mUC.

Functional analysis of CTLA4 promoter variant and its possible implication in colorectal cancer immunotherapy

Background

Colorectal cancer (CRC) is a prevalent cancer, ranking as the third most common. Recent advances in our understanding of the molecular causes of this disease have highlighted the crucial role of tumor immune evasion in its initiation and progression. CTLA4, a receptor that acts as a negative regulator of T cell responses, plays a pivotal role in this process, and genetic variations in CTLA4 have been linked to CRC susceptibility, prognosis, and response to therapy.

Methods

We conducted a case-control study involving 98 CRC patients and 424 controls. We genotyped the CTLA4 c.-319C > T variant (rs5742909) and performed an association analysis by comparing allele frequencies between the patients and controls. To assess the potential functional impact of this variant, we first performed an In Silico analysis of transcription factor binding sites using Genomatix. Finally, to validate our findings, we conducted a luciferase reporter gene assay using different cell lines and an electrophoretic mobility shift assay (EMSA).

Results

The case-control association analysis revealed a significant association between CTLA4 c.-319C > T and CRC susceptibility (p = 0.023; OR 1.89; 95% CI = 1.11-3.23). Genomatix analysis identified LEF1 and TCF7 transcription factors as specific binders to CTLA4 c.-319C. The reporter gene assay demonstrated notable differences in luciferase activity between the c.-319 C and T alleles in COS-7, HCT116, and Jurkat cell lines. EMSA analysis showed differences in TCF7 interaction with the CTLA4 C and T alleles.

Conclusion

CTLA4 c.-319C > T is associated with CRC susceptibility. Based on our functional validation results, we proposed that CTLA4 c.-319C > T alters gene expression at the transcriptional level, triggering a stronger negative regulation of T-cells and immune tumoral evasion.

Deep learning identifies a T-cell exhaustion-dependent transcriptional signature for predicting clinical outcomes and response to immune checkpoint blockade

Immune checkpoint blockade (ICB) therapies have brought unprecedented advances in cancer treatment, but responses are limited to a fraction of patients. Therefore, sustained and substantial efforts are required to advance clinical and translational investigation on managing patients receiving ICB. In this study, we investigated the dynamic changes in molecular profiles of T-cell exhaustion (TEX) during ICB treatment using single-cell and bulk transcriptome analysis, and demonstrated distinct exhaustion molecular profiles associated with ICB response. By applying an ensemble deep-learning computational framework, we identified an ICB-associated transcriptional signature consisting of 16 TEX-related genes, termed ITGs. Incorporating 16 ITGs into a machine-learning model called MLTIP achieved reliable predictive power for clinical ICB response with an average AUC of 0.778, and overall survival (pooled HR = 0.093, 95% CI, 0.031-0.28, P < 0.001) across multiple ICB-treated cohorts. Furthermore, the MLTIP consistently demonstrated superior predictive performance compared to other well-established markers and signatures, with an average increase in AUC of 21.5%. In summary, our results highlight the potential of this TEX-dependent transcriptional signature as a tool for precise patient stratification and personalized immunotherapy, with clinical translation in precision medicine.

CTLA4 DNA methylation is associated with CTLA-4 expression and predicts response to immunotherapy in head and neck squamous cell carcinoma

BACKGROUND

The majority of patients with recurrent or metastasized head and neck squamous cell carcinoma (HNSCC) do not benefit from immune checkpoint blockade (ICB) while several patients experience severe and persistent immune-mediated side effects. Therefore, predictive biomarkers are urgently needed to allow for a personalized treatment. In this study, we investigated DNA methylation of the immune checkpoint gene CTLA4 with regard to its predictive value.

METHODS

We analyzed CTLA4 promoter methylation in tumors of HNSCC patients (N = 29) treated with ICB at the University Medical Center Bonn with regard to response to ICB and progression-free survival. We further analyzed a second cohort (N = 138) of patients that did not receive ICB with regard to CTLA4 promoter methylation, CTLA-4 protein expression, and immune cell infiltrates. Finally, we tested inducibility of CTLA-4 protein expression in HNSCC cells using the DNA methyltransferase inhibitor decitabine.

RESULTS

Lower CTLA4 promoter methylation correlated with response to ICB and prolonged progression-free survival. We could show that not only tumor infiltrating immune cells, but also HNSCC cells harbor cytoplasmic and nuclear CTLA-4 expression. CTLA4 promoter methylation inversely correlated with infiltrates of CD3+, CD4+, CD8+, and CD45+ immune cells. CTLA4 methylation did not correlate with protein expression in tumors, however, decitabine treatment led to decreased CTLA4 methylation and an induction of CTLA4 mRNA and CTLA-4 protein expression in HNSCC cell lines.

CONCLUSIONS

Our results indicate that CTLA4 DNA hypomethylation is a predictive biomarker for response to ICB in HNSCC. Our study warrants further analyses of the predictive value of CTLA4 DNA methylation in clinical trials of anti-PD-1 and/or anti-CTLA-4 immunotherapy in HNSCC.

Biological Biomarkers of Response and Resistance to Immune Checkpoint Inhibitors in Renal Cell Carcinoma

Renal cell carcinoma (RCC) represents around 2% of cancer-related deaths worldwide per year. RCC is an immunogenic malignancy, and treatment of metastatic RCC (mRCC) has greatly improved since the advent of the new immunotherapy agents, including immune checkpoint inhibitors (ICIs). However, it should be stressed that a large proportion of patients does not respond to these therapies. There is thus an urgent need to identify predictive biomarkers of efficacy or resistance associated with ICIs or ICI/Tyrosine kinase inhibitor (TKI) combinations; this is a major challenge to achieve precision medicine for mRCC in routine practice. To identify potential biomarkers, it is necessary to improve our knowledge on the biology of immune checkpoints. A lot of efforts have been made over the last decade in the field of immuno-oncology. We summarize here the main data obtained in this field when considering mRCC. As for clinical biomarkers, clinician and scientific experts of the domain are facing difficulties in identifying such molecular entities, probably due to the complexity of immuno-oncology and the constant adaptation of tumor cells to their changing environment.

The components of tumor microenvironment as biomarker for immunotherapy in metastatic renal cell carcinoma

Substantial improvement in prognosis among metastatic renal cell carcinoma (mRCC) patients has been achieved, owing to the rapid development and utilization of immunotherapy. In particular, immune checkpoint inhibitors (ICIs) have been considered the backbone of systemic therapy for patients with mRCC alongside multi-targeted tyrosine kinase inhibitors (TKIs) in the latest clinical practice guidelines. However, controversies and challenges in optimal individualized treatment regarding immunotherapy remains still About 2/3 of the patients presented non-response or acquired resistance to ICIs. Besides, immune-related toxicities, namely immune-related adverse events, are still elusive and life-threatening. Thus, reliable biomarkers to predict immunotherapeutic outcomes for mRCC patients are needed urgently. Tumor microenvironment (TME), consisting of immune cells, vasculature, signaling molecules, and extracellular matrix and regulates tumor immune surveillance and immunological evasion through complex interplay, plays a critical role in tumor immune escape and consequently manipulates the efficacy of immunotherapy. Various studied have identified the different TME components are significantly associated with the outcome of mRCC patients receiving immunotherapy, making them potential valuable biomarkers in therapeutic guidance. The present review aims to summarize the latest evidence on the associations between the components of TME including immune cells, cytokines and extracellular matrix, and the therapeutic responses among mRCC patients with ICI-based treatment. We further discuss the feasibility and limitation of these components as biomarkers.

ICOS DNA methylation regulates melanoma cell-intrinsic ICOS expression, is associated with melanoma differentiation, prognosis, and predicts response to immune checkpoint blockade

BACKGROUND

Inducible T cell costimulator ICOS is an emerging target in immuno-oncology. The aim of this study was to investigate the epigenetic regulation of ICOS in melanoma by DNA methylation.

METHODS

We comprehensively investigate ICOS DNA methylation of specific CpG sites and expression pattern within the melanoma microenvironment with regard to immune correlates, differentiation, clinical outcomes, and immune checkpoint blockade (ICB) response.

RESULTS

Our study revealed a sequence-contextual CpG methylation pattern consistent with an epigenetically regulated gene. We found a cell type-specific methylation pattern and locus-specific correlations and associations of CpG methylation with ICOS mRNA expression, immune infiltration, melanoma differentiation, prognosis, and response to ICB. High ICOS mRNA expression was identified as a surrogate for enriched immune cell infiltration and was associated with favorable overall survival (OS) in non-ICB-treated patients and predicted response and a prolonged progression-free survival (PFS) following ICB therapy initiation. ICOS hypomethylation, however, significantly correlated with poor OS in non-ICB patients but predicted higher response and prolonged PFS and OS in ICB-treated patients. Moreover, we observed cytoplasmic and sporadically nuclear tumor cell-intrinsic ICOS protein expression. Tumor cell-intrinsic ICOS protein and mRNA expression was inducible by pharmacological demethylation with decitabine.

CONCLUSION

Our study identified ICOS DNA methylation and mRNA expression as promising prognostic and predictive biomarkers for immunotherapy in melanoma and points towards a hitherto undescribed role of ICOS in tumor cells.

Reshaping the tumour immune microenvironment in solid tumours via tumour cell and immune cell DNA methylation: from mechanisms to therapeutics

In recent years, the tumour microenvironment (TME) of solid tumours has attracted more and more attention from researchers, especially those non-tumour components such as immune cells. Infiltration of various immune cells causes tumour immune microenvironment (TIME) heterogeneity, and results in different therapeutic effects. Accumulating evidence showed that DNA methylation plays a crucial role in remodelling TIME and is associated with the response towards immune checkpoint inhibitors (ICIs). During carcinogenesis, DNA methylation profoundly changes, specifically, there is a global loss of DNA methylation and increased DNA methylation at the promoters of suppressor genes. Immune cell differentiation is disturbed, and exclusion of immune cells from the TME occurs at least in part due to DNA methylation reprogramming. Therefore, pharmaceutical interventions targeting DNA methylation are promising. DNA methyltransferase inhibitors (DNMTis) enhance antitumor immunity by inducing transcription of transposable elements and consequent viral mimicry. DNMTis upregulate the expression of tumour antigens, mediate immune cells recruitment and reactivate exhausted immune cells. In preclinical studies, DNMTis have shown synergistic effect when combined with immunotherapies, suggesting new strategies to treat refractory solid tumours.

DNA methylation of GITR, OX40, 4-1BB, CD27 , and CD40 correlates with BAP1 aberrancy and prognosis in uveal melanoma

Uveal melanoma represents an aggressive tumor that responds mostly poorly to established melanoma treatments. Comprehensive methylation profiling of the next-generation immunotherapeutic target genes, for example, members of the tumor necrosis factor receptor superfamily, might allow for the development of companion predictive biomarkers. We have analyzed CpG sites within the immune checkpoint genes GITR, OX40, 4-1BB, CD 27, and CD40 probed by the Illumina Infinium HumanMethylation450 BeadChip in N  = 80 uveal melanomas included in The Cancer Genome Atlas with regard to BAP1 aberrancy, mRNA expression, and overall survival. In all analyzed immune checkpoint genes, BAP1 aberrancy was associated with decreased CpG methylation levels. We identified specific CpG sites that significantly correlated with BAP1 aberrancy, mRNA expression levels, and overall survival. Our results suggest epigenetic regulation of the analyzed immune checkpoint genes via DNA methylation in uveal melanoma and provide rationale for methylation testing in biomarker programs in clinical trials.

A novel gene signature related to oxidative stress predicts the prognosis in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is considered to be related to the worse prognosis, which might in part be attributed to the early recurrence and metastasis, compared with other type of kidney cancer. Oxidative stress refers to an imbalance between production of oxidants and antioxidant defense. Accumulative studies have indicated that oxidative stress genes contribute to the tumor invasion, metastasis and drug sensitivity. However, the biological functions of oxidative stress genes in ccRCC remain largely unknown. In this study, we identified 1,399 oxidative stress genes from GeneCards with a relevance score ≥7. Data for analysis were accessed from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database, and were utilized as training set and validation set respectively. Univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox were employed to construct a prognostic signature in ccRCC. Finally, a prognostic signature including four different oxidative stress genes was constructed from 1,399 genes, and its predictive performance was verified through Kaplan-Meier survival analysis and the receiver operating characteristic (ROC) curve. Interestingly, we found that there was significant correlation between the expression of oxidative stress genes and the immune infiltration and the sensitivity of tumor cells to chemotherapeutics. Moreover, the highest hazard ratio gene urocortin (UCN) was chosen for further study; some necessary vitro experiments proved that the UCN could promote the ability of ccRCC proliferation and migration and contribute to the degree of oxidative stress. In conclusion, it was promising to predict the prognosis of ccRCC through the four oxidative stress genes signature. UCN played oncogenic roles in ccRCC by influencing proliferation and oxidative stress pathway, which was expected to be the novel therapeutic target for ccRCC.

Special issue "The advance of solid tumor research in China": Multi-omics analysis based on 1311 clear cell renal cell carcinoma samples identifies a glycolysis signature associated with prognosis and treatment response

In clear cell renal cell carcinoma (ccRCC), glycolysis is enhanced mainly because of the increased expression of key enzymes in glycolysis. Hence, the discovery of new molecular biomarkers for glycolysis may help guide and establish a precise system of diagnosis and treatment for ccRCC. Expression profiles of 1079 tumor samples of ccRCC patients (including 311 patients treated with everolimus or nivolumab) were downloaded from public databases. Proteomic profiles of 232 ccRCC samples were obtained from Fudan University Shanghai Cancer Center (FUSCC). Biological changes, tumor microenvironment and prognostic differences were explored between samples with various glycolysis characteristics. There were significant differences in CD8⁺ effector T cells, epithelial-to-mesenchymal transition and pan-fibroblast TGFb between the Low and High glyScore groups. The tumor mutation burden of the Low glyScore group was lower than that of the High glyScore group. And higher glyScore was significantly associated with worse overall survival (OS) in 768 ccRCC patients (P < .0001). External validation in FUSCC cohort also indicated that glyScore was of strong ability for predicting OS (P < .05). GlyScore may serve as a biomarker for predicting everolimus response in ccRCC patients due to its significant associations with progression-free survival (PFS). And glyScore may also predict overall survival in patients treated with nivolumab. We calculated the glyScore in ccRCC and the defined glyScore was of strong ability for predicting OS. In addition, glyScore may also serve as a biomarker for predicting PFS in patients treated with everolimus and could predict OS in patients treated with nivolumab.

An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy-a retrospective cohort study examining 66 circulating immune cell subsets

Introduction

Immune checkpoint blockade inhibitor (ICI) therapy offers significant survival benefits for malignant melanoma. However, some patients were observed to be in disease progression after the first few treatment cycles. As such, it is urgent to find convenient and accessible indicators that assess whether patients can benefit from ICI therapy.

Methods

In the training cohort, flow cytometry was used to determine the absolute values of 66 immune cell subsets in the peripheral blood of melanoma patients (n=29) before treatment with anti-PD-1 inhibitors. The least absolute shrinkage and selection operator (LASSO) Cox regression model was followed for the efficacy of each subset in predicting progression-free survival. Then we validated the performance of the selected model in validation cohorts (n=20), and developed a nomogram for clinical use.

Results

A prognostic immune risk score composed of CD1c⁺ dendritic cells and three subsets of T cells (CD8⁺CD28⁺, CD3⁺TCRab⁺HLA-DR⁺, CD3⁺TCRgd⁺HLA-DR⁺) with a higher prognostic power than individual features (AUC = 0.825). Using this model, patients in the training cohort were divided into high- and low-risk groups with significant differences in mean progression-free survival (3.6 vs. 12.3 months), including disease control rate (41.2% vs. 91.7%), and objective response rate (17.6% vs. 41.6%). Integrating four-immune cell-subset based classifiers and three clinicopathologic risk factors can help to predict which patients might benefit from anti-PD-1 antibody inhibitors and remind potential non-responders to pursue effective treatment options in a timely way.

Conclusions

The prognostic immune risk score including the innate immune and adaptive immune cell populations could provide an accurate prediction efficacy in malignant melanoma patients with ICI therapy.

Computed tomography‐based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma

OBJECTIVES

To predict CTLA4 expression levels and prognosis of clear cell renal cell carcinoma (ccRCC) by constructing a computed tomography-based radiomics model and establishing a nomogram using clinicopathologic factors.

METHODS

The clinicopathologic parameters and genomic data were extracted from 493 ccRCC cases of the Cancer Genome Atlas (TCGA)-KIRC database. Univariate and multivariate Cox regression and Kaplan-Meier analysis were performed for prognosis analysis. Cibersortx was applied to evaluate the immune cell composition. Radiomic features were extracted from the TCGA/the Cancer Imaging Archive (TCIA) (n = 102) datasets. The support vector machine (SVM) was employed to establish the radiomics signature for predicting CTLA4 expression. Receiver operating characteristic curve (ROC), decision curve analysis (DCA), and precision-recall curve were utilized to assess the predictive performance of the radiomics signature. Correlations between radiomics score (RS) and selected features were also evaluated. An RS-based nomogram was constructed to predict prognosis.

RESULTS

CTLA4 was significantly overexpressed in ccRCC tissues and was related to lower overall survival. A higher CTLA4 expression was independently linked to the poor prognosis (HR = 1.458, 95% CI 1.13-1.881, p = 0.004). The radiomics model for the prediction of CTLA4 expression levels (AUC = 0.769 in the training set, AUC = 0.724 in the validation set) was established using seven radiomic features. A significant elevation in infiltrating M2 macrophages was observed in the RS high group (p < 0.001). The predictive efficiencies of the RS-based nomogram measured by AUC were 0.826 at 12 months, 0.805 at 36 months, and 0.76 at 60 months.

CONCLUSIONS

CTLA4 mRNA expression status in ccRCC could be predicted noninvasively using a radiomics model based on nephrographic phase contrast-enhanced CT images. The nomogram established by combining RS and clinicopathologic factors could predict overall survival for ccRCC patients. Our findings may help stratify prognosis of ccRCC patients and identify those who may respond best to ICI-based treatments.

Expression of immune checkpoint regulators, programmed death-ligand 1 (PD-L1/PD-1), cytotoxic T lymphocyte antigen 4 (CTLA-4), and indolaimine-2, 3-deoxygenase (IDO) in uterine mesenchymal tumors

BACKGROUND

Immune checkpoints including programmed death-ligand 1/programmed death-1/ (PD-L1/PD-1), cytotoxic T lymphocyte antigen 4 (CTLA-4), and indolaimine-2, 3-deoxygenase (IDO) have recently emerged as effective candidates for treatment against a range of human malignancies. We have investigated their expression in the uterine mesenchymal tumors.

METHODS

Sixty-eight mesenchymal tumors were categorized into 6 diagnostic groups. We assessed PD-L1, PD-1, CTLA-4, and IDO expression on paraffin embedded tissue blocks of the uterine tumors using the respective antibodies. Immunohistochemical (IHC) stains were classified as positive when the reactions were present in at least 1% of the cell membranes for PD-L1/PD-1 or in cytoplasm for CTLA-4 and IDO, regardless of intensity. Student's t-test and McNemar's chi-square tests were carried out to analyze the results.

RESULTS

The mesenchymal neoplasms had expressed the immune checkpoints in the tumor and/or the lymphoid cells at the rate of 49% and 54% respectively. The tumor cells were positive in 10 (18%, PD-L1), 0 (0%, PD-1), 18 (32%, CTLA-4), and 13 (23%, IDO) cases while the infiltrating lymphoid cells were positive in 10 (18%, PD-L1), 23 (40%, PD-1), 18 (32%, CTLA-4), and 13 (23%, IDO) cases. Overall, comparison of paired tumor vs lymphoid cells resulted in p-values of ≤ 0.04.

CONCLUSIONS

Nearly 50% of the uterine tumors express at least one of the immune checkpoints in tumor and/or the infiltrating lymphoid cells. However, expression of the proteins in the two cellular components are mutually exclusive. Namely, when tumor cells express an immune checkpoint, the infiltrating lymphoid cells do not, and vice versa. Since the leiomyosarcomas are reportedly resistant to the immunotherapy when PD-L1 is expressed in the tumor cells, it can be posited that presence of the IHC positive lymphoid cells may be a better indicator of response to the treatment.

T cell proliferation-related genes: Predicting prognosis, identifying the cold and hot tumors, and guiding treatment in clear cell renal cell carcinoma

Background: Immunotherapy has become a new direction of current research because the effect of traditional radiotherapy and chemotherapy on clear cell renal cell carcinoma (ccRCC) is not satisfactory. T cell proliferation-related genes (TRGs) play a pivotal role in tumor progression by regulating the proliferation, activity, and function of immune cells. The purpose of our study is to construct and verify a prognostic model based on TRGs and to identify tumor subtypes that may guide treatment through comprehensive bioinformatics analyses.

Methods: RNA sequencing data, clinical information, and somatic mutation data of ccRCC are obtained from The Cancer Genome Atlas (TCGA) database. We identified the prognosis-related TRGs which were differentially expressed between normal and tumor tissues. After dividing the patients into a train set and a test set according to proportion 1:1 randomly, the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis were performed to construct a risk-stratified model. Its prediction performance was verified. Then, Gene Set Enrichment Analysis (GSEA), principal component analysis (PCA), tumor microenvironment (TME) analysis, and the half-maximal inhibitory concentration (IC50) prediction were performed between the different groups of patients. To further discuss the immunotherapy between hot and cold tumors, we divided all patients into two clusters based on TRGs through unsupervised learning. Analyzing the gene mutation and calculating the tumor mutation burden (TMB), we further explored the relationship between somatic mutations and grouping or clustering.

Results: Risk-stratified model and nomogram predict the prognosis of ccRCC patients accurately. Functional enrichment analyses suggested that TRGs mainly focused on the biological pathways related to tumor progression and immune response. Different tumor microenvironment, drug resistance, and TMB can be distinguished clearly according to both risk stratification and tumor subtype clustering.

Conclusion: In this study, a new stratification model of ccRCC based on TRGs was established, which can accurately predict the prognosis of patients. IC50 prediction may guide the application of anti-tumor drugs. The distinction between hot and cold tumors provides a reference for clinical immunotherapy.

CTLA4 , PD-1 , PD-L1 , PD-L2 , TIM-3 , TIGIT , and LAG3 DNA Methylation Is Associated With BAP1 -Aberrancy, Transcriptional Activity, and Overall Survival in Uveal Melanoma

Uveal melanoma (UM) is an aggressive disease with poor response to oncological treatment, including immunotherapy. Loss of the epigenetic modifier BRCA1-associated protein 1 (BAP1) function drives UM oncogenesis and is associated with an immune-suppressive tumor microenvironment, poor prognosis, and a distinct DNA methylation and gene expression profile. Our study aimed to analyze comprehensively the DNA methylation status of the immune checkpoint genes PD-1 , PD-L1 , PD-L2 , CTLA4, TIM-3 ( HAVCR2 ), TIGIT , and LAG3 and its association with mRNA expression, BAP1 -aberrancy, and patients' survival. We analyzed the DNA methylation landscape of immune checkpoint genes at single CpG resolution in N=80 UM samples provided by The Cancer Genome Atlas. We analyzed CpG methylation levels of the immune checkpoints with regard to their transcriptional signatures and patient outcomes.Methylation of specific CpG sites within the immune checkpoint genes PD-1 , PD-L1 , PD-L2 , CTLA4 , TIM-3 , TIGIT , and LAG3 correlated strongly with mRNA expression levels, indicating a strong regulation of gene expression through DNA methylation. Moreover, immune checkpoint gene methylation was strongly associated with BAP1 -mutation status and associated with overall survival in UM. Our data indicate an epigenetic regulation of immune checkpoints through DNA methylation in UM. Further, our data highlight the prognostic significance of DNA methylation of immune checkpoint genes in UM thereby providing a rationale for methylation testing as predictive biomarkers for immunotherapy response.

Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

Background

Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC.

Methods

A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data.

Results

The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC.

Conclusion

These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

DNA methylation regulates TIGIT expression within the melanoma microenvironment, is prognostic for overall survival, and predicts progression-free survival in patients treated with anti-PD-1 immunotherapy

BACKGROUND

TIGIT is an immune checkpoint under investigation as therapeutic target. Understanding the regulation of TIGIT on an epigenetic level might support the development of companion biomarkers.

METHODS

We correlated TIGIT DNA methylation of single CpG sites with gene expression, signatures of immune infiltrates and interferon-γ, and survival in melanoma. We further analyzed methylation levels in immune cell subsets, melanocyte and melanoma cell lines. TIGIT expression patterns within components of the melanoma microenvironment were analyzed by single cell sequencing. We used quantitative methylation-specific PCR, flow cytometry, and immunohistochemistry for correlations between expression and methylation and to assess the effect of pharmacological demethylation of melanoma cells treated with 5-aza-2-deoxycytidine (decitabine). Finally, we investigated the association of patients' survival with TIGIT mRNA and methylation.

RESULTS

Depending on the sequence context of the analyzed CpG site, we found a cell type-specific TIGIT gene locus methylation pattern and significant correlations of TIGIT methylation with mRNA expression, an interferon γ signature, and distinct immune cell infiltrates, including TIGIT⁺ lymphocytes. We detected a melanoma cell-intrinsic TIGIT protein expression. Pharmacological demethylation of the A375 melanoma cell line led to a constitutive TIGIT expression. Low promoter flank methylation and high mRNA expression was associated with patients' prognosis and predicted progression-free survival in patients treated with anti-PD-1 immunotherapy. A high TIGIT⁺ lymphocyte score was associated with better progression-free survival under anti-PD-1 immunotherapy.

CONCLUSIONS

Our data demonstrate an epigenetic regulation of TIGIT expression via DNA methylation within the melanoma microenvironment. TIGIT DNA methylation and expression may serve as predictive biomarkers in the context of immunotherapies in melanoma.