Tumor-infiltrating TNFRSF9+ CD8+ T cells define different subsets of clear cell renal cell carcinoma with prognosis and immunotherapeutic response

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.

Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma

BACKGROUND

Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers.

METHODS

10 machine-learning algorithms and their combinations were applied in this work. A stable Tstr-related score (TCs) was constructed to predict the outcomes and PD-1 blockade treatment response in ccRCC patients. A nomogram based on TCs for personalized prediction of patient prognosis was constructed. Functional enrichment analysis and TimiGP algorithm were used to explore the underlying role of Tstr in ccRCC. The key TCs-related gene was identified by comprehensive analysis, and the bioinformatics results were verified by immunohistochemistry using a tissue microarray.

RESULTS

A robust TCs was constructed and validated in four independent cohorts. TCs accurately predicted the prognosis and PD-1 blockade treatment response in ccRCC patients. The novel nomogram was able to precisely predict the outcomes of ccRCC patients. The underlying biological process of Tstr was related to acute inflammatory response and acute-phase response. Mast cells were identified to be involved in the role of Tstr as a protective factor in ccRCC. TNFS13B was shown to be the key TCs-related gene, which was an independent predictor of unfavorable prognosis. The protein expression analysis of TNFSF13B was consistent with the mRNA analysis results. High expression of TNFSF13B was associated with poor response to PD-1 blockade treatment.

CONCLUSIONS

This study provides a Tstr cell-related score for predicting outcomes and PD-1 blockade therapy response in ccRCC. Tstr cells may exert their pro-tumoral role in ccRCC, acting against mast cells, in the acute inflammatory tumor microenvironment. TNFSF13B could serve as a key biomarker related to TCs.

NKG2A+CD8+ T cells infiltration determines immunosuppressive contexture and inferior response to immunotherapy in clear cell renal cell carcinoma

BACKGROUND

Immunotherapy is gaining momentum, but current treatments have limitations in terms of beneficiaries. Clear cell renal cell carcinoma (ccRCC) harbors the highest expression of human leukocyte antigen E (HLA-E), ligand of NKG2A, among all solid tumors. In this study, we aim to investigate the role of NKG2A+CD8+ T cells in tumor microenvironment and its potential as a novel target in ccRCC.

METHODS

This study included four independent cohorts, including 234 patients from Zhongshan cohort (ZSHC) who underwent partial or radical nephrectomy at Zhongshan Hospital, and 117 metastatic patients from metastatic Zhongshan cohort (ZSHC-metastatic renal cell carcinoma) who were treated with immune checkpoint inhibitor or tyrosine kinase inhibitor alone. We also incorporated a cohort of 530 patients diagnosed with ccRCC from The Cancer Genome Atlas (referred to as TCGA-kidney renal clear cell carcinoma) and 311 patients from CheckMate cohort for bioinformatics exploration and hypothesis validation. Fresh surgical specimens from 15 patients who underwent ccRCC surgery at Zhongshan Hospital were collected for flow cytometry analysis. Another 10 fresh surgical specimens were used to investigate the therapeutic potential of NKG2A blockade after in vitro intervention. The infiltration of NKG2A+CD8+ T cells was assessed using immunohistochemical staining, flow cytometry, and immunofluorescence staining in ZSHC cohort.

RESULTS

Patients with higher infiltration of NKG2A+CD8+ T cells in ccRCC exhibited shorter overall survival and resistance to immunotherapy. NKG2A+CD8+ T cells expressed upregulated checkpoint molecules and displayed impaired effector functions, along with tissue-residency characteristics. Combination of programmed cell death protein-1 (PD-1) blockade and NKG2A blockade demonstrated an enhanced capability in reactivating CD8+ T cells effector functions.

CONCLUSION

Intense infiltration of NKG2A+CD8+ T cells were associated with poorer prognosis and response to immunotherapy. NKG2A blockade combined with current immunotherapy exhibited a robust ability to reactivate CD8+ T cells effector functions.

Circulating antigen-primed cytotoxic T-cells in patients with renal tumors treated with surgery

INTRODUCTION

Systemic immunotherapy has changed the paradigm of treatment of advanced renal cell carcinoma, but nephrectomy continues to benefit selected patients. While we continue to identify mechanisms behind drug resistance, the effect of surgery on natural anti-tumor immunity is poorly understood. Specifically, peripheral blood mononuclear cell (PBMC) profile and tumor reactive cytotoxic T lymphocytes changes secondary to tumor resection have not been extensively characterized. Hence, we aimed to evaluate the effect of nephrectomy on PMBC profile and circulating antigen-primed CD8+ T-cells for patients undergoing solid renal mass resection.

METHODS

Patients with localized or metastatic solid renal masses who underwent nephrectomy from 2016 to 2018 were enrolled. Blood samples were collected at 3 timepoints for PBMCs analysis (pre-op, 1 day, and 3 months post-op). Flow cytometry was used to identify CD11ahigh CD8+ T lymphocytes that were then further characterized according to the expression of CX3CR1/GZMB, Ki67, Bim, and PD-1. Changes in circulating CD8+ T-cells from pre-op to 1 day and 3 months post-op were evaluated using Wilcoxon signed rank tests.

RESULTS

Antigen-primed CX3CR1+GZMB+ T-cells significantly increased by 3 months after surgery among patients with RCC (0.8 × 109 cells; P = 0.01). In contrast, there was a decrease in absolute numbers of Bim+ T-cells at 3 months (-1.9 × 109 cells; P = 0.02). There were no significant absolute changes in PD-1+ (-1.4 × 109; P = 0.7) and CD11ahigh CD8+ T lymphocytes (1.3 × 109; P = 0.9). Ki67+ T-cells decreased by 3 months (-0.8 × 109; P < 0.001).

CONCLUSIONS

Nephrectomy is associated with an increase in cytolytic antigen-primed CD8+ T-cells and specific PBMC profile changes. Further studies are warranted to ascertain the role surgery may have in the restoration of anti-tumor immunity.

Methylation-related genes involved in renal carcinoma progression

Renal carcinomas are a group of malignant tumors often originating in the cells lining the small tubes in the kidney responsible for filtering waste from the blood and urine production. Kidney tumors arise from the uncontrolled growth of cells in the kidneys and are responsible for a large share of global cancer-related morbidity and mortality. Understanding the molecular mechanisms driving renal carcinoma progression results crucial for the development of targeted therapies leading to an improvement of patient outcomes. Epigenetic mechanisms such as DNA methylation are known factors underlying the development of several cancer types. There is solid experimental evidence of relevant biological functions modulated by methylation-related genes, associated with the progression of different carcinomas. Those mechanisms can often be associated to different epigenetic marks, such as DNA methylation sites or chromatin conformation patterns. Currently, there is no definitive method to establish clear relations between genetic and epigenetic factors that influence the progression of cancer. Here, we developed a data-driven method to find methylation-related genes, so we could find relevant bonds between gene co-expression and methylation-wide-genome regulation patterns able to drive biological processes during the progression of clear cell renal carcinoma (ccRC). With this approach, we found out genes such as ITK oncogene that appear hypomethylated during all four stages of ccRC progression and are strongly involved in immune response functions. Also, we found out relevant tumor suppressor genes such as RAB25 hypermethylated, thus potentially avoiding repressed functions in the AKT signaling pathway during the evolution of ccRC. Our results have relevant implications to further understand some epigenetic-genetic-affected roles underlying the progression of renal cancer.

Functional interrogation of lymphocyte subsets in alopecia areata using single-cell RNA sequencing

Alopecia areata (AA) is among the most prevalent autoimmune diseases, but the development of innovative therapeutic strategies has lagged due to an incomplete understanding of the immunological underpinnings of disease. Here, we performed single-cell RNA sequencing (scRNAseq) of skin-infiltrating immune cells from the graft-induced C3H/HeJ mouse model of AA, coupled with antibody-based depletion to interrogate the functional role of specific cell types in AA in vivo. Since AA is predominantly T cell-mediated, we focused on dissecting lymphocyte function in AA. Both our scRNAseq and functional studies established CD8+ T cells as the primary disease-driving cell type in AA. Only the depletion of CD8+ T cells, but not CD4+ T cells, NK, B, or γδ T cells, was sufficient to prevent and reverse AA. Selective depletion of regulatory T cells (Treg) showed that Treg are protective against AA in C3H/HeJ mice, suggesting that failure of Treg-mediated immunosuppression is not a major disease mechanism in AA. Focused analyses of CD8+ T cells revealed five subsets, whose heterogeneity is defined by an "effectorness gradient" of interrelated transcriptional states that culminate in increased effector function and tissue residency. scRNAseq of human AA skin showed that CD8+ T cells in human AA follow a similar trajectory, underscoring that shared mechanisms drive disease in both murine and human AA. Our study represents a comprehensive, systematic interrogation of lymphocyte heterogeneity in AA and uncovers a novel framework for AA-associated CD8+ T cells with implications for the design of future therapeutics.

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.

Downregulation of RAB17 have a poor prognosis in kidney renal clear cell carcinoma and its expression correlates with DNA methylation and immune infiltration

BACKGROUND

RAB17 is one of the RAB family members. It has been reported to be closely associated with a variety of tumors and has different roles in various tumors. However, the effect of RAB17 in KIRC remains unclear.

MATERIALS AND METHODS

We analyzed the differential expression of RAB17 in kidney renal clear cell carcinoma (KIRC) tissues and normal tissues using the public databases. The prognostic role of RAB17 in KIRC was analyzed using the Cox regression methods, and a prognostic model was constructed based on the results of the Cox analysis. In addition, further analysis of RAB17 in KIRC was performed in relation to genetic alterations, DNA methylation m6A methylation and immune infiltration. Finally, RAB17 mRNA and protein expression levels were analyzed in tissue samples (KIRC tissues and normal tissues) and cell lines (normal renal tubular cell and KIRC cells), and in vitro functional assays were performed.

RESULTS

RAB17 was low-expressed in KIRC. Downregulation of RAB17 expression is correlated with unfavorable clinicopathological characteristics and a worse prognosis in KIRC. The RAB17 gene alteration in KIRC was primarily characterized by copy number alteration. Six CpG sites of RAB17 DNA methylation levels are higher in KIRC tissues than in normal tissues, and are correlated with RAB17 mRNA expression levels, showing a significant negative correlation. cg01157280 site DNA methylation levels are associated with pathological stage and overall survival, and it may be the only CpG site with independent prognostic significance. Functional mechanism analysis revealed that RAB17 is closely associated with immune infiltration. RAB17 expression was found to be negatively correlated with most immune cell infiltration according to two different methods. Furthermore, most immunomodulators were significantly negatively correlated with RAB17 expression, and significantly positively correlated with RAB17 DNA methylation levels. RAB17 was significantly low expression in KIRC cells and KIRC tissues. In vitro, silencing of RAB17 promoted KIRC cell migration.

CONCLUSION

RAB17 can be used as a potential prognostic biomarker for patients with KIRC and for assessing immunotherapy response.

Tumor and immune remodeling following radiotherapy in human renal cell carcinoma

BACKGROUND

Studies evaluating peripheral patient samples show radiation can modulate immune responses, yet the biological changes in human tumors particularly at the cellular level remain largely unknown. Here, we address how radiation treatment shapes the immune compartment and interactions with cancer cells within renal cell carcinoma (RCC) patient tumors.

METHODS

To identify how radiation shaped the immune compartment and potential immune interactions with tumor cells we evaluated RCC tumors from patients treated only with nephrectomy or with radiation followed by nephrectomy. Spectral flow cytometry using a 35-marker panel was performed on cell suspensions to evaluate protein expression within immune subsets. To reveal how radiation alters programming of immune populations and interactions with tumor cells, we examined transcriptional changes by single-cell RNA sequencing (scRNAseq).

RESULTS

Spectral flow cytometry analysis revealed increased levels of early-activated as well as effector programmed cell death protein-1 (PD-1)⁺ CD8 T-cell subsets within irradiated tumors. Following quality control, scRNAseq of tumor samples from nephrectomy-only or radiation followed by nephrectomy-treated patients generated an atlas containing 34,626 total cells. Transcriptional analysis revealed increased transition from stem-like T-cell populations to effector T cells in irradiated tumors. Interferon (IFN) pathways, that are central to radiation-induced immunogenicity, were enriched in irradiated lymphoid, myeloid, and cancer cell populations. Focused cancer cell analysis showed enhanced antigen presentation and increased predicted TRAIL-mediated and IFN-mediated interactions between tumor cells and the same effector T-cell subsets increased by radiation. TRAIL and IFN pathways enriched in irradiated tumors were associated with survival in patients treated with immunotherapy.

CONCLUSIONS

These findings identify the source of IFN enrichment within irradiated RCC and reveal heightened levels of PD-1⁺ CD8⁺ T-cell subsets and increased probability of interactions with tumor cells following standalone radiation treatment. This study provides a window into the irradiated tumor-immune microenvironment of patients and rationale for treatment combinations.

Single-cell analysis of localized prostate cancer patients links high Gleason score with an immunosuppressive profile

BACKGROUND

Evading immune surveillance is a hallmark for the development of multiple cancer types. Whether immune evasion contributes to the pathogenesis of high-grade prostate cancer (HGPCa) remains an area of active inquiry.

METHODS

Through single-cell RNA sequencing and multicolor flow cytometry of freshly isolated prostatectomy specimens and matched peripheral blood, we aimed to characterize the tumor immune microenvironment (TME) of localized prostate cancer (PCa), including HGPCa and low-grade prostate cancer (LGPCa).

RESULTS

HGPCa are highly infiltrated by exhausted CD8⁺ T cells, myeloid cells, and regulatory T cells (TRegs). These HGPCa-infiltrating CD8⁺ T cells expressed high levels of exhaustion markers including TIM3, TOX, TCF7, PD-1, CTLA4, TIGIT, and CXCL13. By contrast, a high ratio of activated CD8⁺  effector T cells relative to TRegs and myeloid cells infiltrate the TME of LGPCa. HGPCa CD8⁺  tumor-infiltrating lymphocytes (TILs) expressed more androgen receptor and prostate-specific membran antigen yet less prostate-specific antigen than the LGPCa CD8⁺  TILs. The PCa TME was infiltrated by macrophages but these did not clearly cluster by M1 and M2 markers.

CONCLUSIONS

Our study reveals a suppressive TME with high levels of CD8⁺ T cell exhaustion in localized PCa, a finding enriched in HGPCa relative to LGPCa. These studies suggest a possible link between the clinical-pathologic risk of PCa and the associated TME. Our results have implications for our understanding of the immunologic mechanisms of PCa pathogenesis and the implementation of immunotherapy for localized PCa.

Senescence Rewires Microenvironment Sensing to Facilitate Antitumor Immunity

Cellular senescence involves a stable cell-cycle arrest coupled to a secretory program that, in some instances, stimulates the immune clearance of senescent cells. Using an immune-competent liver cancer model in which senescence triggers CD8 T cell-mediated tumor rejection, we show that senescence also remodels the cell-surface proteome to alter how tumor cells sense environmental factors, as exemplified by type II interferon (IFNγ). Compared with proliferating cells, senescent cells upregulate the IFNγ receptor, become hypersensitized to microenvironmental IFNγ, and more robustly induce the antigen-presenting machinery-effects also recapitulated in human tumor cells undergoing therapy-induced senescence. Disruption of IFNγ sensing in senescent cells blunts their immune-mediated clearance without disabling the senescence state or its characteristic secretory program. Our results demonstrate that senescent cells have an enhanced ability to both send and receive environmental signals and imply that each process is required for their effective immune surveillance.

SIGNIFICANCE

Our work uncovers an interplay between tissue remodeling and tissue-sensing programs that can be engaged by senescence in advanced cancers to render tumor cells more visible to the adaptive immune system. This new facet of senescence establishes reciprocal heterotypic signaling interactions that can be induced therapeutically to enhance antitumor immunity. See related article by Marin et al., p. 410. This article is highlighted in the In This Issue feature, p. 247.

Cuproptosis-related gene FDX1 as a prognostic biomarker for kidney renal clear cell carcinoma correlates with immune checkpoints and immune cell infiltration

Background: Kidney renal clear cell carcinoma (KIRC) is not sensitive to radiotherapy and chemotherapy, and only some KIRC patients can benefit from immunotherapy and targeted therapy. Cuproptosis is a new mechanism of cell death, which is closely related to tumor progression, prognosis and immunity. The identification of prognostic markers related to cuproptosis in KIRC may provide targets for treatment and improve the prognosis of KIRC patients. Methods: Ten cuproptosis-related genes were analyzed for differential expression in KIRC-TCGA and a prognostic model was constructed. Nomogram diagnostic model was used to screen independent prognostic molecules. The screened molecules were verified in multiple datasets (GSE36895 and GSE53757), and in KIRC tumor tissues by RT-PCR and immunohistochemistry (IHC). Clinical correlation of cuproptosis-related independent prognostic molecules was analyzed. According to the molecular expression, the two groups were divided into high and low expression groups, and the differences of immune checkpoint and tumor infiltrating lymphocytes (TILs) between the two groups were compared by EPIC algorithm. The potential Immune checkpoint blocking (ICB) response of high and low expression groups was predicted by the "TIDE" algorithm. Results: FDX1 and DLAT were protective factors, while CDKN2A was a risk factor. FDX1 was an independent prognostic molecule by Nomogram, and low expressed in tumor tissues compared with adjacent tissues (p < 0.05). FDX1 was positively correlated with CD274, HAVCR2, PDCD1LG2, and negatively correlated with CTLA4, LAG3, and PDCD1. The TIDE score of low-FDX1 group was higher than that of high-FDX1 group. The abundance of CD4⁺ T cells, CD8⁺ T cells and Endothelial cells in FDX1-low group was lower than that in FDX1-high group (p < 0.05). Conclusion: FDX1, as a key cuproptosis-related gene, was also an independent prognostic molecule of KIRC. FDX1 might become an interesting biomarker and potential therapeutic target for KIRC.

A Novel Lymphangiogenesis-Related Gene Signature can Predict Prognosis and Immunosuppressive Microenvironment in Patients with Clear Cell Renal Cell Carcinoma

Background: Lymphangiogenesis represents a key event in the progression and metastasis of patients with clear cell renal cell carcinoma (ccRCC). Nevertheless, the prognostic value of lymphangiogenesis-related genes (LRGs) in ccRCC patients remains unknown. Method: Differential analyses were performed to identify differentially expressed LRGs between normal and tumor tissues. A univariate Cox analysis was performed to identify differently expressed LRGs associated with overall survival (OS). LASSO and multivariate Cox analyses were performed to construct and optimize the LRG signature. To further explore the molecular characterization of the LRG signature, a functional enrichment analysis, immune signature, somatic mutations, and drug sensitivity were assessed. Immunohistochemistry (IHC) and immunofluorescence staining were performed to validate the relationship between lymphangiogenesis and immunity using our ccRCC samples. Results: Four candidate genes (IL4, CSF2, PROX1, and TEK) were eventually available to construct the LRG signature in the training set. Patients in the high-risk group had a shorter survival than those in the low-risk group. The LRG signature was an independent prognostic factor of OS. These results were confirmed in the validation group. The LRG signature was correlated with immunosuppressive cell infiltration, T cell exhaustion markers, somatic mutations, and drug sensitivity. The IHC and immunofluorescence staining results confirmed the correlation between lymphangiogenesis and CD163⁺ macrophages, exhausted CD8⁺PD-1⁺, and CD8⁺ LAG3⁺ T cells. Conclusion: A novel prognostic signature based on LRGs could provide insight into the prognostic evaluation and treatment of ccRCC patients.

Identification and experimental validation of a tumor-infiltrating lymphocytes-related long noncoding RNA signature for prognosis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common aggressive malignant tumor of the urinary system. Given the heterogeneity of the tumor microenvironment, immunotherapy may not fully exert its role in the treatment of advanced patients. Long noncoding RNA (lncRNA) has been reported to be critically associated with the differentiation and maturation of tumor-infiltrating lymphocytes (TILs), which work against tumor cells. In this study, we identified 10 TIL-related lncRNAs (AL590094.1, LINC02027, LINC00460, AC147651.1, AC026401.3, LINC00944, LINC01615, AP000439.2, AL162586.1, and AC084876.1) by Pearson correlation, univariate Cox regression, Lasso regression, and multivariate Cox regression based on The Cancer Genome Atlas (TCGA) database. A risk score model was established based on these lncRNAs. Next, a nomogram was constructed to predict the overall survival. By employing differentially expressed genes (DEGs) between groups with high and low risk scores, gene ontology (GO) enrichment analysis was performed to identify the major biological processes (BP) related to immune DEGs. We analyzed the mutation data of the groups and demonstrated that SETD2 and BAP1 had the highest mutation frequency in the high-risk group. The "CIBERSORT" R package was used to detect the abundance of TILs in the groups. The expression of lymphocyte markers was compared. We also determined the expression of two lncRNAs (AC084876.1 and AC026401.3) and their relationship with lymphocyte markers in the kidney tissue of ccRCC patients and showed that there was a positive correlation between AC084876.1 and FoxP3. Proliferation, migration, and invasion of AC084876.1-downregulated ccRCC cell lines were inhibited, and the expression of PD-L1 and TGF-β secretion decreased. To our knowledge, this is the first bioinformatics study to establish a prognostic model for ccRCC using TIL-related lncRNAs. These lncRNAs were associated with T-cell activities and may serve as biomarkers of disease prognosis.

m7G regulator-mediated molecular subtypes and tumor microenvironment in kidney renal clear cell carcinoma

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear.

Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity.

Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib.

Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC.

Tumor-Infiltrated CD8+ T Cell 10-Gene Signature Related to Clear Cell Renal Cell Carcinoma Prognosis

Clear cell renal cell carcinoma (ccRCC) usually affects multiple organs (e.g., bone and brain), and patient prognosis is usually poor. Although it is known that CD8+ T cell infiltration can potentially alleviate ccRCC progression, few studies have concentrated on the correlation between CD8+ T cell infiltration and ccRCC prognosis. In this study, ten genes expressed by infiltrated CD8+ T cells (i.e., AMD1, CCSER2, CIB1, DRAP1, HMGB2, HMGN1, NPIPB5, PTP4A2, RORA, and SAP18) were suggested as potential ccRCC prognostic biomarkers, by using next-generation sequencing (i.e. bulk sequencing and single-cell sequencing) of ccRCC, papillary renal cell carcinoma (papRCC), and control kidney biopsies. Specifically, we identified four genes (i.e., CCSER2, DRAP1, NPIPB5, and SAP18) as potential novel prognostic biomarkers for ccRCC. It is noteworthy that SAP18 derived from CD8+ T cells negatively correlates to Atg7+ neutrophils in ccRCC, compared with papRCC, indicating a potential decreased neutrophil metabolic function in autophagy and fatty acids. This study elucidated the protective role of infiltrated CD8+ T cells in ccRCC and identified ten candidate genes related to an improved prognosis in patients with ccRCC.

A novel nine-microRNA-based model to improve prognosis prediction of renal cell carcinoma

Background

With the improved knowledge of disease biology and the introduction of immune checkpoints, there has been significant progress in treating renal cell carcinoma (RCC) patients. Individual treatment will differ according to risk stratification. As the clinical course varies in RCC, it has developed different predictive models for assessing patient’s individual risk. However, among other prognostic scores, no transparent preference model was given. MicroRNA as a putative marker shown to have prognostic relevance in RCC, molecular analysis may provide an innovative benefit in the prophetic prediction and individual risk assessment. Therefore, this study aimed to establish a prognostic-related microRNA risk score model of RCC and further explore the relationship between the model and the immune microenvironment, immune infiltration, and immune checkpoints. This practical model has the potential to guide individualized surveillance protocols, patient counseling, and individualized treatment decision for RCC patients and facilitate to find more immunotherapy targets.

Methods

Downloaded data of RCC from the TCGA database for difference analysis and divided it into a training set and validation set. Then the prognostic genes were screened out by Cox and Lasso regression analysis. Multivariate Cox regression analysis was used to establish a predictive model that divided patients into high-risk and low-risk groups. The ENCORI online website and the results of the RCC difference analysis were used to search for hub genes of miRNA. Estimate package and TIMER database were used to evaluate the relationship between risk score and tumor immune microenvironment (TME) and immune infiltration. Based on Kaplan-Meier survival analysis, search for immune checkpoints related to the prognosis of RCC.

Results

There were nine miRNAs in the established model, with a concordance index of 0.702 and an area under the ROC curve of 0.701. Nine miRNAs were strongly correlated with the prognosis (P < 0.01), and those with high expression levels had a poor prognosis. We found a common target gene PDGFRA of hsa-miR-6718, hsa-miR-1269b and hsa-miR-374c, and five genes related to ICGs (KIR2DL3, TNFRSF4, LAG3, CD70 and TNFRSF9). The immune/stromal score, immune infiltration, and immune checkpoint genes of RCC were closely related to its prognosis and were positively associated with a risk score.

Conclusions

The established nine-miRNAs prognostic model has the potential to facilitate prognostic prediction. Moreover, this model was closely related to the immune microenvironment, immune infiltration, and immune checkpoint genes of RCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09322-9.

Anti-4-1BB antibody-based combination therapy augments antitumor immunity by enhancing CD11c+CD8+ T cells in renal cell carcinoma

To improve the potential treatment strategies of incurable renal cell carcinoma (RCC), which is highly resistant to chemotherapy and radiotherapy, the present study established a combination therapy with immunostimulatory factor (ISTF) and anti-4-1BB monoclonal antibodies (mAbs) to augment the antitumor response in a murine RCC model. ISTF isolated from Actinobacillus actinomycetemcomitans stimulates macrophages, dendritic cells and B cells to produce IL-6, TNF-α, nitric oxide and major histocompatibility complex class II expression. 4-1BB (CD137) is expressed in activated immune cells, including activated T cells, and is a promising target for cancer immunotherapy. The administration of anti-4-1BB mAbs promoted antitumor immunity via enhancing CD11c⁺CD8⁺ T cells. The CD11c⁺CD8⁺ T cells were characterized by high killing activity and IFN-γ-producing ability, representing a phenotype of active effector cytotoxic T lymphocytes. The present study showed that combination therapy with ISTF and anti-4-1BB mAbs promoted partial tumor regression with established RCC, but monotherapy with ISTF or anti-4-1BB mAbs did not. These effects were speculated to be caused by the increase in CD11c⁺CD8⁺ T cells in the spleen and tumor, and IFN-γ production. These insights into the effector mechanisms of the combination of ISTF and anti-4-1BB mAbs may be useful for targeting incurable RCC.

CD8+ T Cell-Based Molecular Classification With Heterogeneous Immunogenomic Landscapes and Clinical Significance of Clear Cell Renal Cell Carcinoma

The tumor microenvironment (TME) exerts a high impact on tumor biology and immunotherapy. The heterogeneous phenotypes and the clinical significance of CD8⁺ T cells in TME have not been fully elucidated. Here, a comprehensive immunogenomic analysis based on multi-omics data was performed to investigate the clinical significance and tumor heterogeneity between CD8⁺ T cell-related molecular clusters. We identified two distinct molecular clusters of ccRCC (C1 and C2) in TCGA and validated in E-MTAB-1980 cohorts. The C1 cluster was characterized by unfavorable prognosis, increased expression levels of CD8⁺ T cell exhaustion markers, high immune infiltration levels as well as more immune escape mechanisms. The C2 cluster was featured by favorable prognosis, elevated expression levels of CD8⁺ T cell effector markers, low load of copy number loss and low frequency of 9p21.3 deletion. Moreover, the effect of molecular classifications on Nivolumab therapeutic efficacy in the CheckMate 025 cohort was examined, and the C2 cluster exhibited a better prognosis. Taken together, we determine two CD8⁺ T cell-related molecular clusters in ccRCC, and provide new insights for evaluating the functions of CD8⁺ T cells. Our molecular classification is a potential strategy for prognostic prediction and immunotherapeutic guidance for ccRCC patients.

From Bench to Bedside: How the Tumor Microenvironment Is Impacting the Future of Immunotherapy for Renal Cell Carcinoma

Immunotherapy has revolutionized the treatment landscape for many cancer types. The treatment for renal cell carcinoma (RCC) has especially evolved in recent years, from cytokine-based immunotherapies to immune checkpoint inhibitors. Although clinical benefit from immunotherapy is limited to a subset of patients, many combination-based approaches have led to improved outcomes. The success of such approaches is a direct result of the tumor immunology knowledge accrued regarding the RCC microenvironment, which, while highly immunogenic, demonstrates many unique characteristics. Ongoing translational work has elucidated some of the mechanisms of response, as well as primary and secondary resistance, to immunotherapy. Here, we provide a comprehensive review of the RCC immunophenotype with a specific focus on how preclinical and clinical data are shaping the future of immunotherapy.

A Dynamic Transcriptome Map of Different Tissue Microenvironment Cells Identified During Gastric Cancer Development Using Single-Cell RNA Sequencing

Gastric cancer (GC) development trends have identified multiple processes ranging from inflammation to carcinogenesis, however, key pathogenic mechanisms remain unclear. Tissue microenvironment (TME) cells are critical for the progression of malignant tumors. Here, we generated a dynamic transcriptome map of various TME cells during multi-disease stages using single-cell sequencing analysis. We observed a set of key transition markers related to TME cell carcinogenic evolution, and delineated landmark dynamic carcinogenic trajectories of these cells. Of these, macrophages, fibroblasts, and endothelial cells exerted considerable effects toward epithelial cells, suggesting these cells may be key TME factors promoting GC occurrence and development. Our results suggest a phenotypic convergence of different TME cell types toward tumor formation processes in GC. We believe our data would pave the way for early GC detection, diagnosis, and treatment therapies.

Prognostic Value of Metabolism-Related Genes and Immune Infiltration in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent cancers. Thus, it is warranted to detect the status of metabolism-related genes (MRGs) and infiltrating immune cells in ccRCC progression for the prognosis of ccRCC. This research was designed to establish and verify the prognostic signature of ccRCC using MRGs. In addition, we investigated the potential link between the relative proportion of tumor infiltrated immune cells (TIICs) and ccRCC prognosis.

Methods

Sequencing data of metabolism-related gene sets in ccRCC cases were obtained from The Cancer Genome Atlas database (TCGA) and Gene Expression Omnibus Database (GEO). The R Programming Language software packages were applied for differential analysis of MRGs. First, a univariate Cox regression model was applied to determine the MRGs linked with overall survival (OS). Then, the multivariate Cox regression model was applied to establish the prognostic signature. Finally, the CIBERSORT algorithm was used to determine the proportion of TIICs.

Results

Overall, 286 differentially expressed MRGs were identified in the TCGA dataset. Univariate and multivariate Cox regression models were applied to develop a prognostic signature with six MRGs. The predictive capability of the prognostic signature was further verified by TCGA and GEO database. In addition, RS positively correlated with memory B cells, plasma cells, activated memory CD4+ T cells, follicular helper T cells, regulatory T cells, CD8+ T cells, and M0 macrophages, and were negatively associated with resting memory CD4+ T cells, resting dendritic cells, activated dendritic cells, M2 macrophages, monocytes, resting mast cells, and eosinophils.

Conclusion

Herein, a prognostic signature was developed using MRGs for ccRCC prognosis. The proportion of 22 TIICs in ccRCC and the association between TIICs and clinical outcomes were also determined. The identified genes and cells could guide future targeted therapy and immunotherapy.

Multidiscipline Immunotherapy-Based Rational Combinations for Robust and Durable Efficacy in Brain Metastases from Renal Cell Carcinoma

Advanced imaging techniques for diagnosis have increased awareness on the benefits of brain screening, facilitated effective control of extracranial disease, and prolonged life expectancy of metastatic renal cell carcinoma (mRCC) patients. Brain metastasis (BM) in patients with mRCC (RCC-BM) is associated with grave prognoses, a high degree of morbidity, dedicated assessment, and unresponsiveness to conventional systemic therapeutics. The therapeutic landscape of RCC-BM is rapidly changing; however, survival outcomes remain poor despite standard surgery and radiation, highlighting the unmet medical needs and the requisite for advancement in systemic therapies. Immune checkpoint inhibitors (ICIs) are one of the most promising strategies to treat RCC-BM. Understanding the role of brain-specific tumor immune microenvironment (TIME) is important for developing rationale-driven ICI-based combination strategies that circumvent tumor intrinsic and extrinsic factors and complex positive feedback loops associated with resistance to ICIs in RCC-BM via combination with ICIs involving other immunological pathways, anti-antiangiogenic multiple tyrosine kinase inhibitors, and radiotherapy; therefore, novel combination approaches are being developed for synergistic potential against RCC-BM; however, further prospective investigations with longer follow-up periods are required to improve the efficacy and safety of combination treatments and to elucidate dynamic predictive biomarkers depending on the interactions in the brain TIME.

Agent-Based Learning Model for the Obesity Paradox in RCC

A recent study on the immunotherapy treatment of renal cell carcinoma reveals better outcomes in obese patients compared to lean subjects. This enigmatic contradiction has been explained, in the context of the debated obesity paradox, as the effect produced by the cell-cell interaction network on the tumor microenvironment during the immune response. To better understand this hypothesis, we provide a computational framework for the in silico study of the tumor behavior. The starting model of the tumor, based on the cell-cell interaction network, has been described as a multiagent system, whose simulation generates the hypothesized effects on the tumor microenvironment. The medical needs in the immunotherapy design meet the capabilities of a multiagent simulator to reproduce the dynamics of the cell-cell interaction network, meaning a reaction to environmental changes introduced through the experimental data.