Progressive immune dysfunction with advancing disease stage in renal cell carcinoma

Comprehensive proteogenomic characterization of rare kidney tumors

Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes. RCCs with high genome instability display overexpression of IGF2BP3 and PYCR1. Integration of single-cell and bulk transcriptome data predicts diverse cell-of-origin and clarifies RCC subtype-specific proteogenomic signatures. Expression of biomarkers MAPRE3, ADGRF5, and GPNMB differentiates renal oncocytoma from chromophobe RCC, and PIGR and SOSTDC1 distinguish papillary RCC from MTSCC. This study expands our knowledge of proteogenomic signatures, biomarkers, and potential therapeutic targets in non-ccRCC.

A spatial architecture-embedding HLA signature to predict clinical response to immunotherapy in renal cell carcinoma

An important challenge in the real-world management of patients with advanced clear-cell renal cell carcinoma (aRCC) is determining who might benefit from immune checkpoint blockade (ICB). Here we performed a comprehensive multiomics mapping of aRCC in the context of ICB treatment, involving discovery analyses in a real-world data cohort followed by validation in independent cohorts. We cross-connected bulk-tumor transcriptomes across >1,000 patients with validations at single-cell and spatial resolutions, revealing a patient-specific crosstalk between proinflammatory tumor-associated macrophages and (pre-)exhausted CD8+ T cells that was distinguished by a human leukocyte antigen repertoire with higher preference for tumoral neoantigens. A cross-omics machine learning pipeline helped derive a new tumor transcriptomic footprint of neoantigen-favoring human leukocyte antigen alleles. This machine learning signature correlated with positive outcome following ICB treatment in both real-world data and independent clinical cohorts. In experiments using the RENCA-tumor mouse model, CD40 agonism combined with PD1 blockade potentiated both proinflammatory tumor-associated macrophages and CD8+ T cells, thereby achieving maximal antitumor efficacy relative to other tested regimens. Thus, we present a new multiomics and spatial map of the immune-community architecture that drives ICB response in patients with aRCC.

Preoperative neoadjuvant targeted therapy remodels intra-tumoral heterogeneity of clear-cell renal cell carcinoma and ferroptosis inhibition induces resistance progression

Neoadjuvant tyrosine kinase inhibitor (TKI) therapy is an important treatment option for advanced renal cell carcinoma (RCC). Many RCC patients may fail to respond or be resistant to TKI therapy. We aimed to explore the key mechanisms of neoadjuvant therapy résistance. We obtained tumor samples from matched pre-treatment biopsy and post-treatment surgical samples and performed single-cell RNA sequencing. Sunitinib-resistant ccRCC cell lines were established. Ferroptosis was detected by ferrous ion and lipid peroxidation levels. Tumor growth and resistance to Sunitinib was validated in vitro and vivo. Immunohistochemistry was used to validate the levels key genes and lipid peroxidation. Multi-center cohorts were included, including TCGA, ICGC, Checkmate-025 and IMmotion151 clinical trial. Survival analysis was performed to identify the associated clinical and genomic variables. Intratumoral heterogeneity was first described in the whole neoadjuvant management. The signature of endothelial cells was correlated with drug sensitivity and progression-free survival. Ferroptosis was shown to be the key biological program in malignant cell resistance. We observed tissue lipid peroxidation was negatively correlated with IL6 and tumor response. TKI-resistant cell line was established. SLC7A11 knockdown promoted cell growth and lipid peroxidation, increased the ferroptosis level, and suppressed the growth of tumor xenografts significantly (P < 0.01). IL6 could reverse the ferroptosis and malignant behavior caused by SLC7A11 (-) via JAK2/STAT3 pathway, which was rescued by the ferroptosis inducer Erastin. Our data indicate that ferroptosis is a novel strategy for advanced RCC treatment, which activated by IL6, providing a new idea for resistance to TKIs.

PABPC1L Induces IDO1 to Promote Tryptophan Metabolism and Immune Suppression in Renal Cell Carcinoma

The tumor microenvironment (TME) in renal cell carcinomas (RCC) is marked by substantial immunosuppression and immune resistance despite having extensive T-cell infiltration. Elucidation of the mechanisms underlying immune evasion could help identify therapeutic strategies to boost the efficacy of immune checkpoint blockade (ICB) in RCC. This study uncovered a mechanism wherein the polyadenylate-binding protein PABPC1L modulates indoleamine 2,3-dioxygenase 1 (IDO1), a prospective target for immunotherapy. PABPC1L was markedly upregulated in RCC, and high PABPC1L expression correlated with unfavorable prognosis and resistance to ICB. PABPC1L bolstered tryptophan metabolism by upregulating IDO1, inducing T-cell dysfunction and Treg infiltration. PABPC1L enhanced the stability of JAK2 mRNA, leading to increased JAK2-STAT1 signaling that induced IDO1 expression. Additionally, PABPC1L-induced activation of the JAK2-STAT1 axis created a positive feedback loop to promote PABPC1L transcription. Conversely, loss of PABPC1L diminished IDO1 expression, mitigated cytotoxic T-cell suppression, and enhanced responsiveness to anti-PD-1 therapy in patient-derived xenograft models. These findings reveal the crucial role of PABPC1L in facilitating immune evasion in RCC and indicate that inhibiting PABPC1L could be a potential immunotherapeutic approach in combination with ICB to improve patient outcomes.

SIGNIFICANCE

PABPC1L functions as a key factor in renal cell carcinoma immune evasion, enhancing IDO1 and impeding T-cell function, and represents a potential target to enhance the efficacy of immune checkpoint blockade therapy.

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.

Paraoxonase-2 shRNA-mediated gene silencing suppresses proliferation and migration, while promotes chemosensitivity in clear cell renal cell carcinoma cell lines

Clear cell renal cell carcinoma (ccRCC) represents the most common subtype of renal tumor. Despite recent advances in identifying novel target molecules, the prognosis of patients with ccRCC continues to be poor, mainly due to the lack of sensitivity to chemo- and radiotherapy and because of one-third of renal cell carcinoma patients displays metastatic disease at diagnosis. Thus, identifying new molecules for early detection and for developing effective targeted therapies is mandatory. In this work, we focused on paraoxonase-2 (PON2), an intracellular membrane-bound enzyme ubiquitously expressed in human tissues, whose upregulation has been reported in a variety of malignancies, thus suggesting its possible role in cancer cell survival and proliferation. To investigate PON2 involvement in tumor cell metabolism, human ccRCC cell lines were transfected with plasmid vectors coding short harpin RNAs targeting PON2 transcript and the impact of PON2 silencing on cell viability, migration, and response to chemotherapeutic treatment was then explored. Our results showed that PON2 downregulation was able to trigger a decrease in proliferation and migration of ccRCC cells, as well as an enhancement of cell sensitivity to chemotherapy. Thus, taken together, data reported in this study suggest that the enzyme may represent an interesting therapeutic target for ccRCC.

Integrative analysis of the cuproptosis-related gene ATP7B in the prognosis and immune infiltration of IDH1 wild-type glioma

Glioma is the most common malignant tumor in the brain and the central nervous system with a poor prognosis, and wild-type isocitrate dehydrogenase (IDH) glioma indicates a worse prognosis. Cuproptosis is a recently discovered form of cell death regulated by copper-dependent mitochondrial respiration. However, the effect of cuproptosis on tumor prognosis and immune infiltration is not clear. In this research, we analyzed of public databases to show the correlation between cuproptosis-related genes and the prognosis of IDH1 wild-type glioma. Nine out of 12 genes were upregulated in IDH1 wild-type glioma patients, and 6 genes were significantly associated with overall survival (OS), while 5 genes were associated with progression-free survival (PFS). Then, we constructed a prognostic cuproptosis-related gene signature for IDH1 wild-type glioma patients. ATP7B was considered an independent prognostic indicator, and a low expression level of ATP7B was related to a shorter period of OS and PFS. Moreover, downregulation of ATP7B was correlated not only with the infiltration of activated NK cells, CD8 + T cells and M2 macrophages; but also with high expression of immune checkpoint genes and tumor mutation burden (TMB). In the IDH1 wild-type glioma tissues we collected, our data also confirmed that high tumor grade was accompanied by low expression of ATP7B and high expression of PD-L1, which was associated with increasing infiltration of CD8 + immune cells. In conclusion, our research constructed a prognostic cuproptosis-related gene signature model to predict the prognosis of IDH1 wild-type glioma. ATP7B is deemed to be a potential prognostic indicator and novel immunotherapy biomarker for IDH1 wild-type glioma patients.

Analyses of tumor microenvironment in patients with advanced renal cell carcinoma receiving immunotherapy (Meet-URO 18 study)

Introduction: The Meet-URO 18 study is a multicentric study of patients with metastatic renal cell carcinoma receiving nivolumab in the second-line and beyond, categorized as responders (progression-free survival ≥ 12 months) and non-responders (progression-free survival < 3 months). Areas covered: The current study includes extensive immunohistochemical analysis of T-lineage markers (CD3, CD4, CD8, CD8/CD4 ratio), macrophages (CD68), ph-mTOR, CD15 and CD56 expression on tumor cells, and PD-L1 expression, on an increased sample size including 161 tumor samples (113 patients) compared with preliminary presented data. Responders' tumor tissue (n = 90; 55.9%) was associated with lower CD4 expression (p = 0.014), higher CD56 expression (p = 0.046) and higher CD8/CD4 ratio (p = 0.030). Expert opinion/commentary: The present work suggests the regulatory role of a subpopulation of T cells on antitumor response and identifies CD56 as a putative biomarker of immunotherapy efficacy.

Crosstalk of disulfidptosis-related subtypes identifying a prognostic signature to improve prognosis and immunotherapy responses of clear cell renal cell carcinoma patients

BACKGROUND

Disulfidptosis is a novel form of programmed cell death induced by high SLC7A11 expression under glucose starvation conditions, unlike other known forms of cell death. However, the roles of disulfidptosis in cancers have yet to be comprehensively well-studied, particularly in ccRCC.

METHODS

The expression profiles and somatic mutation of DGs from the TCGA database were investigated. Two DGs clusters were identified by unsupervised consensus clustering analysis, and a disulfidptosis-related prognostic signature (DR score) was constructed. Furthermore, the predictive capacity of the DR score in prognosis was validated by several clinical cohorts. We also developed a nomogram based on the DR score and clinical features. Then, we investigated the differences in the clinicopathological information, TMB, tumor immune landscapes, and biological characteristics between the high- and low-risk groups. We evaluated whether the DR score is a robust tool for predicting immunotherapy response by the TIDE algorithm, immune checkpoint genes, submap analysis, and CheckMate immunotherapy cohort.

RESULTS

We identified two DGs clusters with significant differences in prognosis, tumor immune landscapes, and clinical features. The DR score has been demonstrated as an independent risk factor by several clinical cohorts. The high-risk group patients had a more complicated tumor immune microenvironment and suffered from more tumor immune evasion in immunotherapy. Moreover, patients in the low-risk group had better prognosis and response to immunotherapy, particularly in anti-PD1 and anti-CTLA-4 inhibitors, which were verified in the CheckMate immunotherapy cohort.

CONCLUSION

The DR score can accurately predict the prognosis and immunotherapy response and assist clinicians in providing a personalized treatment regime for ccRCC patients.

Macrophage-Derived Nanosponges Adsorb Cytokines and Modulate Macrophage Polarization for Renal Cell Carcinoma Immunotherapy

Renal cell carcinoma (RCC) is a hot tumor infiltrated by large numbers of CD8+ T cells and is highly sensitive to immunotherapy. However, tumor-associated macrophages (TAMs), mainly M2 macrophages, tend to undermine the efficacy of immunotherapy and promote the progression of RCC. Here, macrophage-derived nanosponges are fabricated by M2 macrophage membrane-coated poly（lactic-co-glycolic acid）（PLGA）, which could chemotaxis to the CXC and CC chemokine subfamily-enriched RCC microenvironment via corresponding membrane chemokine receptors. Subsequently, the nanosponges act like cytokine decoys to adsorb and neutralize broad-spectrum immunosuppressive cytokines such as colony stimulating factor-1(CSF-1), transforming growth factor-β（TGF-β）, and Lnterleukin-10（IL-10）, thereby reversing the polarization of M2-TAMs toward the pro-inflammatory M1 phenotype, and enhancing the anti-tumor effect of CD8+ T cells. To further enhance the polarization reprogramming efficiency of TAMs, DSPE-PEG-M2pep is conjugated on the surface of macrophage-derived nanosponges for specific recognition of M2-TAMs, and the toll like receptors 7/8（TLR7/8） agonist, R848, is encapsulated in these nanosponges to induce M1 polarization, which result in significant efficacy against RCC. In addition, these nanosponges exhibit undetectable biotoxicity, making them suitable for clinical applications. In summary, a promising and facile strategy is provided for immunomodulatory therapies, which are expected to be used in the treatment of tumors, autoimmune diseases, and inflammatory diseases.

TIM-3+ CD8 T cells with a terminally exhausted phenotype retain functional capacity in hematological malignancies

Chronic antigen stimulation is thought to generate dysfunctional CD8 T cells. Here, we identify a CD8 T cell subset in the bone marrow tumor microenvironment that, despite an apparent terminally exhausted phenotype (TPHEX), expressed granzymes, perforin, and IFN-γ. Concurrent gene expression and DNA accessibility revealed that genes encoding these functional proteins correlated with BATF expression and motif accessibility. IFN-γ+ TPHEX effectively killed myeloma with comparable efficacy to transitory effectors, and disease progression correlated with numerical deficits in IFN-γ+ TPHEX. We also observed IFN-γ+ TPHEX within CD19-targeted chimeric antigen receptor T cells, which killed CD19+ leukemia cells. An IFN-γ+ TPHEX gene signature was recapitulated in TEX cells from human cancers, including myeloma and lymphoma. Here, we characterize a TEX subset in hematological malignancies that paradoxically retains function and is distinct from dysfunctional TEX found in chronic viral infections. Thus, IFN-γ+ TPHEX represent a potential target for immunotherapy of blood cancers.

Pan-Cancer Single-Cell and Spatial-Resolved Profiling Reveals the Immunosuppressive Role of APOE+ Macrophages in Immune Checkpoint Inhibitor Therapy

The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single-cell RNA sequencing (scRNA-seq) and machine learning methods. The scRNA-seq and bulk RNA-seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single-cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan-cancer patients. The proportion of APOE+ macrophages is higher in ICI non-responders of triple-negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor-bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real-world immunotherapy data accurately predicts the ICI response of pan-cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

METTL3/16-mediated m6A modification of ZNNT1 promotes hepatocellular carcinoma progression by activating ZNNT1/osteopontin/S100A9 positive feedback loop-mediated crosstalk between macrophages and tumour cells

Macrophages are the major components of tumour microenvironment, which play critical roles in tumour development. N6-methyladenosine (m6A) also contributes to tumour progression. However, the potential roles of m6A in modulating macrophages in hepatocellular carcinoma (HCC) are poorly understood. Here, we identified ZNNT1 as an HCC-related m6A modification target, which was upregulated and associated with poor prognosis of HCC. METTL3 and METTL16-mediated m6A modification contributed to ZNNT1 upregulation through stabilizing ZNNT1 transcript. ZNNT1 exerted oncogenic roles in HCC. Furthermore, ZNNT1 recruited and induced M2 polarization of macrophages via up-regulating osteopontin (OPN) expression and secretion. M2 Macrophages-recruited by ZNNT1-overexpressed HCC cells secreted S100A9, which further upregulated ZNNT1 expression in HCC cells via AGER/NF-κB signaling. Thus, this study demonstrates that m6A modification activated the ZNNT1/OPN/S100A9 positive feedback loop, which promoted macrophages recruitment and M2 polarization, and enhanced malignant features of HCC cells. m6A modification-triggered ZNNT1/OPN/S100A9 feedback loop represents potential therapeutic target for HCC.

Unveiling CXCR2 as a promising therapeutic target in renal cell carcinoma: exploring the immunotherapeutic paradigm shift through its inhibition by RCT001

BACKGROUND

In clear cell renal cell carcinoma (ccRCC), first-line treatment combines nivolumab (anti-PD-1) and ipilimumab (anti-CTLA4), yielding long-term remissions but with only a 40% success rate. Our study explored the potential of enhancing ccRCC treatment by concurrently using CXCR2 inhibitors alongside immunotherapies.

METHODS

We analyzed ELR + CXCL levels and their correlation with patient survival during immunotherapy. RCT001, a unique CXCR2 inhibitor, was examined for its mechanism of action, particularly its effects on human primary macrophages. We tested the synergistic impact of RCT001 in combination with immunotherapies in both mouse models of ccRCC and human ccRCC in the presence of human PBMC.

RESUTS

Elevated ELR + CXCL cytokine levels were found to correlate with reduced overall survival during immunotherapy. RCT001, our optimized compound, acted as an inverse agonist, effectively inhibiting angiogenesis and reducing viability of primary ccRCC cells. It redirected M2-like macrophages without affecting M1-like macrophage polarization directed against the tumor. In mouse models, RCT001 enhanced the efficacy of anti-CTLA4 + anti-PD1 by inhibiting tumor-associated M2 macrophages and tumor-associated neutrophils. It also impacted the activation of CD4 T lymphocytes, reducing immune-tolerant lymphocytes while increasing activated natural killer and dendritic cells. Similar effectiveness was observed in human RCC tumors when RCT001 was combined with anti-PD-1 treatment.

CONCLUSIONS

RCT001, by inhibiting CXCR2 through its unique mechanism, effectively suppresses ccRCC cell proliferation, angiogenesis, and M2 macrophage polarization. This optimization potentiates the efficacy of immunotherapy and holds promise for significantly improving the survival prospects of metastatic ccRCC patients.

LRP1 induces anti-PD-1 resistance by modulating the DLL4-NOTCH2-CCL2 axis and redirecting M2-like macrophage polarisation in bladder cancer

The tumour microenvironment (TME) drives bladder cancer (BLCA) progression. Targeting the TME has emerged as a promising strategy for BLCA treatment in recent years. Furthermore, checkpoint blockade therapies are only beneficial for a minority of patients with BLCA, and drug resistance is a barrier to achieving significant clinical effects of anti-programmed cell death protein-1 (PD-1)/programmed death protein ligand-1 (PD-L1) therapy. In this study, higher low-density lipoprotein receptor-related protein 1 (LRP1) levels were related to a poorer prognosis for patients with various cancers, including those with higher grades and later stages of BLCA. Enrichment analysis demonstrated that LRP1 plays a role in the epithelial-mesenchymal transition (EMT), NOTCH signalling pathway, and ubiquitination. LRP1 knockdown in BLCA cells delayed BLCA progression both in vivo and in vitro. Furthermore, LRP1 knockdown suppressed EMT, reduced DLL4-NOTCH2 signalling activity, and downregulated M2-like macrophage polarisation. Patients with BLCA and higher LRP1 levels responded weakly to anti-PD-1 therapy in the IMvigor210 cohort. Moreover, LRP1 knockdown enhanced the therapeutic effects of anti-PD-1 in mice. Taken together, our findings suggest that LRP1 is a potential target for improving the efficacy of anti-PD-1/PD-L1 therapy by preventing EMT and M2-like macrophage polarisation by blocking the DLL4-NOTCH2 axis.

Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics

Single-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.

Advanced insights on tumor-associated macrophages revealed by single-cell RNA sequencing: The intratumor heterogeneity, functional phenotypes, and cellular interactions

Single-cell RNA sequencing (scRNA-seq) is an emerging technology used for cellular transcriptome analysis. The application of scRNA-seq has led to profoundly advanced oncology research, continuously optimizing novel therapeutic strategies. Intratumor heterogeneity extensively consists of all tumor components, contributing to different tumor behaviors and treatment responses. Tumor-associated macrophages (TAMs), the core immune cells linking innate and adaptive immunity, play significant roles in tumor progression and resistance to therapies. Moreover, dynamic changes occur in TAM phenotypes and functions subject to the regulation of the tumor microenvironment. The heterogeneity of TAMs corresponding to the state of the tumor microenvironment has been comprehensively recognized using scRNA-seq. Herein, we reviewed recent research and summarized variations in TAM phenotypes and functions from a developmental perspective to better understand the significance of TAMs in the tumor microenvironment.

Integrated analysis of single-cell and bulk RNA sequencing data reveals the association between hypoxic tumor cells and exhausted T cells in predicting immune therapy response

Continuous stimulation of tumor neoantigens and various cytokines in the tumor microenvironment leads to T cell dysfunction, but the specific mechanisms by which these key factors are distributed among different cell subpopulations and how they affect patient outcomes and treatment response are incompletely characterized. By integrating single-cell and bulk sequencing data of non-small cell lung cancer patients, we constructed a clinical outcome-associated T cell exhaustion signature. We discovered a significant association between the T cell exhaustion state and tumor cell hypoxia. Hypoxic malignant cells were significantly correlated with the proportion of exhausted T cells, and they co-occurred in patients at advanced stage. By analyzing the ligand-receptor interactions between these two cell states, we observed that T cells were recruited towards tumor cells through production of chemokines such as CXCL16-CXCR6 axis and CCL3/CCL4/CCL5-CCR5 axis. Based on 15 immune checkpoint blockade (ICB)-treatment cohorts, we constructed an interaction signature that can be used to predict the response to immune checkpoint blockade therapy. Among genes composed of the signature, CXCR6 alone has similarly high prediction efficacy (Area Under Curve (AUC) = 1, 0.89 and 0.73 for GSE126044, GSE135222 and GSE93157, respectively) with the signature and thus could serve as a potential biomarker for predicting immunotherapy response. Together, we have discovered and validated a significant association between exhausted T cells and hypoxic malignant cells, elucidating key interaction factors that significantly associated with response to immunotherapy.

Multi-omic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression

Clear cell renal cell carcinoma (ccRCC) is a complex disease with remarkable immune and metabolic heterogeneity. Here we perform genomic, transcriptomic, proteomic, metabolomic and spatial transcriptomic and metabolomic analyses on 100 patients with ccRCC from the Tongji Hospital RCC (TJ-RCC) cohort. Our analysis identifies four ccRCC subtypes including De-clear cell differentiated (DCCD)-ccRCC, a subtype with distinctive metabolic features. DCCD cancer cells are characterized by fewer lipid droplets, reduced metabolic activity, enhanced nutrient uptake capability and a high proliferation rate, leading to poor prognosis. Using single-cell and spatial trajectory analysis, we demonstrate that DCCD is a common mode of ccRCC progression. Even among stage I patients, DCCD is associated with worse outcomes and higher recurrence rate, suggesting that it cannot be cured by nephrectomy alone. Our study also suggests a treatment strategy based on subtype-specific immune cell infiltration that could guide the clinical management of ccRCC.

Distinct spatial landscapes in clear-cell renal cell carcinoma as revealed by whole transcriptome analysis

Background

Clear-cell renal cell carcinoma (ccRCC) is the most common and aggressive form of renal cancer and a paradigm of inter- and intratumor heterogeneity. We carried out an exploratory digital spatial profiling of the tumor interior and periphery of two ccRCC tumor specimens and mapped spatially the molecular and cellular composition of their tumor microenvironment and ecosystem.

Materials and methods

Digital spatial profiling of the whole transcriptome of 19 regions of interest (ROIs) was carried out from two selected highly immunogenic stage pT3a/grade 3 (G3) and stage pT3a/grade 4 (G4) ccRCC. A total of 9-10 ROIs were selected from distinct areas from each tumor, including tumor interior and tumor periphery, and differences in gene expression were analyzed by RNA sequencing, pathway enrichment analysis, and cell deconvolution.

Results

The distinct areas from the two locally advanced tumors displayed unique gene expression spatial patterns defining distinct biological pathways. Dimensional reduction analysis showed that the G3 ccRCC, compared to the G4 ccRCC, correlated with more variability between regions from the tumor interior and tumor periphery. Cell deconvolution analysis illustrated higher abundance of immune cells, including macrophages, myeloid dendritic cells, and CD4 T cells, and lower abundance of regulatory T cells in the tumor periphery compared to the tumor interior.

Conclusions

Transcriptome spatial profiling revealed high inter- and intratumor heterogeneity in the analyzed tumors and provided information with potential clinical utility. This included the finding of less intratumor heterogeneity and more tumor-infiltrated T cells in the ccRCC tumor specimen with a higher grade.

Metabolic heterogeneity in clear cell renal cell carcinoma revealed by single-cell RNA sequencing and spatial transcriptomics

BACKGROUND

Clear cell renal cell carcinoma is a prototypical tumor characterized by metabolic reprogramming, which extends beyond tumor cells to encompass diverse cell types within the tumor microenvironment. Nonetheless, current research on metabolic reprogramming in renal cell carcinoma mostly focuses on either tumor cells alone or conducts analyses of all cells within the tumor microenvironment as a mixture, thereby failing to precisely identify metabolic changes in different cell types within the tumor microenvironment.

METHODS

Gathering 9 major single-cell RNA sequencing databases of clear cell renal cell carcinoma, encompassing 195 samples. Spatial transcriptomics data were selected to conduct metabolic activity analysis with spatial localization. Developing scMet program to convert RNA-seq data into scRNA-seq data for downstream analysis.

RESULTS

Diverse cellular entities within the tumor microenvironment exhibit distinct infiltration preferences across varying histological grades and tissue origins. Higher-grade tumors manifest pronounced immunosuppressive traits. The identification of tumor cells in the RNA splicing state reveals an association between the enrichment of this particular cellular population and an unfavorable prognostic outcome. The energy metabolism of CD8+ T cells is pivotal not only for their cytotoxic effector functions but also as a marker of impending cellular exhaustion. Sphingolipid metabolism evinces a correlation with diverse macrophage-specific traits, particularly M2 polarization. The tumor epicenter is characterized by heightened metabolic activity, prominently marked by elevated tricarboxylic acid cycle and glycolysis while the pericapsular milieu showcases a conspicuous enrichment of attributes associated with vasculogenesis, inflammatory responses, and epithelial-mesenchymal transition. The scMet facilitates the transformation of RNA sequencing datasets sourced from TCGA into scRNA sequencing data, maintaining a substantial degree of correlation.

CONCLUSIONS

The tumor microenvironment of clear cell renal cell carcinoma demonstrates significant metabolic heterogeneity across various cell types and spatial dimensions. scMet exhibits a notable capability to transform RNA sequencing data into scRNA sequencing data with a high degree of correlation.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Immune-restoring CAR-T cells display antitumor activity and reverse immunosuppressive TME in a humanized ccRCC mouse model

One of the major barriers that have restricted successful use of chimeric antigen receptor (CAR) T cells in the treatment of solid tumors is an unfavorable tumor microenvironment (TME). We engineered CAR-T cells targeting carbonic anhydrase IX (CAIX) to secrete anti-PD-L1 monoclonal antibody (mAb), termed immune-restoring (IR) CAR G36-PDL1. We tested CAR-T cells in a humanized clear cell renal cell carcinoma (ccRCC) orthotopic mouse model with reconstituted human leukocyte antigen (HLA) partially matched human leukocytes derived from fetal CD34+ hematopoietic stem cells (HSCs) and bearing human ccRCC skrc-59 cells under the kidney capsule. G36-PDL1 CAR-T cells, haploidentical to the tumor cells, had a potent antitumor effect compared to those without immune-restoring effect. Analysis of the TME revealed that G36-PDL1 CAR-T cells restored active antitumor immunity by promoting tumor-killing cytotoxicity, reducing immunosuppressive cell components such as M2 macrophages and exhausted CD8+ T cells, and enhancing T follicular helper (Tfh)-B cell crosstalk.

Management of Renal Cell Carcinoma: Promising Biomarkers and the Challenges to Reach the Clinic

The incidence of renal cell carcinoma (RCC) is increasing worldwide, yet research within this field is lagging behind other cancers. Despite increased detection of early disease as a consequence of the widespread use of diagnostic CT scans, 25% of patients have disseminated disease at diagnosis. Similarly, around 25% progress to metastatic disease following curatively intended surgery. Surgery is the cornerstone in the treatment of RCC; however, when the disease is disseminated, immunotherapy or immunotherapy in combination with a tyrosine kinase inhibitor is the patient's best option. Immunotherapy is a potent treatment, with durable treatment responses and potential to cure the patient, but only half of the patients benefit from the administered treatment, and there are currently no methods that can identify which patients will respond to immunotherapy. Moreover, there is a need to identify the patients in greatest risk of relapsing after surgery for localized disease and direct adjuvant treatment there. Even though several molecular biomarkers have been published to date, we are still lacking routinely used biomarkers to guide optimal clinical management. The purpose of this review is to highlight some of the most promising biomarkers, discuss the efforts made within this field to date, and describe the barriers needed to be overcome to have reliable and robust predictive and prognostic biomarkers in the clinic for renal cancer.

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683 + GZMB + CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

Novel tumor-associated macrophage populations and subpopulations by single cell RNA sequencing

Tumor-associated macrophages (TAMs) are present in almost all solid tumor tissues. 16They play critical roles in immune regulation, tumor angiogenesis, tumor stem cell activation, tumor invasion and metastasis, and resistance to therapy. However, it is unclear how TAMs perform these functions. With the application of single-cell RNA sequencing (scRNA-seq), it has become possible to identify TAM subpopulations associated with distinct functions. In this review, we discuss four novel TAM subpopulations in distinct solid tumors based on core gene signatures by scRNA-seq, including FCN1 +, SPP1 +, C1Q + and CCL18 + TAMs. Functional enrichment and gene expression in scRNA-seq data from different solid tumor tissues found that FCN1 + TAMs may induce inflammation; SPP1 + TAMs are potentially involved in metastasis, angiogenesis, and cancer cell stem cell activation, whereas C1Q + TAMs participate in immune regulation and suppression; And CCL18 + cells are terminal immunosuppressive macrophages that not only have a stronger immunosuppressive function but also enhance tumor metastasis. SPP1 + and C1Q + TAM subpopulations can be further divided into distinct populations with different functions. Meanwhile, we will also present emerging evidence highlighting the separating macrophage subpopulations associated with distinct functions. However, there exist the potential disconnects between cell types and subpopulations identified by scRNA-seq and their actual function.

Single-cell analysis of immune and stroma cell remodeling in clear cell renal cell carcinoma primary tumors and bone metastatic lesions

BACKGROUND

Despite therapeutic advances, once a cancer has metastasized to the bone, it represents a highly morbid and lethal disease. One third of patients with advanced clear cell renal cell carcinoma (ccRCC) present with bone metastasis at the time of diagnosis. However, the bone metastatic niche in humans, including the immune and stromal microenvironments, has not been well-defined, hindering progress towards identification of therapeutic targets.

METHODS

We collected fresh patient samples and performed single-cell transcriptomic profiling of solid metastatic tissue (Bone Met), liquid bone marrow at the vertebral level of spinal cord compression (Involved), and liquid bone marrow from a different vertebral body distant from the tumor site but within the surgical field (Distal), as well as bone marrow from patients undergoing hip replacement surgery (Benign). In addition, we incorporated single-cell data from primary ccRCC tumors (ccRCC Primary) for comparative analysis.

RESULTS

The bone marrow of metastatic patients is immune-suppressive, featuring increased, exhausted CD8 + cytotoxic T cells, T regulatory cells, and tumor-associated macrophages (TAM) with distinct transcriptional states in metastatic lesions. Bone marrow stroma from tumor samples demonstrated a tumor-associated mesenchymal stromal cell population (TA-MSC) that appears to be supportive of epithelial-to mesenchymal transition (EMT), bone remodeling, and a cancer-associated fibroblast (CAFs) phenotype. This stromal subset is associated with poor progression-free and overall survival and also markedly upregulates bone remodeling through the dysregulation of RANK/RANKL/OPG signaling activity in bone cells, ultimately leading to bone resorption.

CONCLUSIONS

These results provide a comprehensive analysis of the bone marrow niche in the setting of human metastatic cancer and highlight potential therapeutic targets for both cell populations and communication channels.

ADGRE5-centered Tsurv model in T cells recognizes responders to neoadjuvant cancer immunotherapy

Background

Neoadjuvant immunotherapy with anti-programmed death-1 (neo-antiPD1) has revolutionized perioperative methods for improvement of overall survival (OS), while approaches for major pathologic response patients' (MPR) recognition along with methods for overcoming non-MPR resistance are still in urgent need.

Methods

We utilized and integrated publicly-available immune checkpoint inhibitors regimens (ICIs) single-cell (sc) data as the discovery datasets, and innovatively developed a cell-communication analysis pipeline, along with a VIPER-based-SCENIC process, to thoroughly dissect MPR-responding subsets. Besides, we further employed our own non-small cell lung cancer (NSCLC) ICIs cohort's sc data for validation in-silico. Afterward, we resorted to ICIs-resistant murine models developed by us with multimodal investigation, including bulk-RNA-sequencing, Chip-sequencing and high-dimensional cytometry by time of flight (CYTOF) to consolidate our findings in-vivo. To comprehensively explore mechanisms, we adopted 3D ex-vivo hydrogel models for analysis. Furthermore, we constructed an ADGRE5-centered Tsurv model from our discovery dataset by machine learning (ML) algorithms for a wide range of tumor types (NSCLC, melanoma, urothelial cancer, etc.) and verified it in peripheral blood mononuclear cells (PBMCs) sc datasets.

Results

Through a meta-analysis of multimodal sequential sc sequencing data from pre-ICIs and post-ICIs, we identified an MPR-expanding T cells meta-cluster (MPR-E) in the tumor microenvironment (TME), characterized by a stem-like CD8+ T cluster (survT) with STAT5-ADGRE5 axis enhancement compared to non-MPR or pre-ICIs TME. Through multi-omics analysis of murine TME, we further confirmed the existence of survT with silenced function and immune checkpoints (ICs) in MPR-E. After verification of the STAT5-ADGRE5 axis of survT in independent ICIs cohorts, an ADGRE5-centered Tsurv model was then developed through ML for identification of MPR patients pre-ICIs and post-ICIs, both in TME and PBMCs, which was further verified in pan-cancer immunotherapy cohorts. Mechanistically, we unveiled ICIs stimulated ADGRE5 upregulation in a STAT5-IL32 dependent manner in a 3D ex-vivo system (3D-HYGTIC) developed by us previously, which marked Tsurv with better survival flexibility, enhanced stemness and potential cytotoxicity within TME.

Conclusion

Our research provides insights into mechanisms underlying MPR in neo-antiPD1 and a well-performed model for the identification of non-MPR.

A promising natural killer cell-based model and a nomogram for the prognostic prediction of clear-cell renal cell carcinoma

BACKGROUND

Clear-cell renal cell carcinoma (ccRCC) is one of prevalent kidney malignancies with an unfavorable prognosis. There is a need for a robust model to predict ccRCC patient survival and guide treatment decisions.

METHODS

RNA-seq data and clinical information of ccRCC were obtained from the TCGA and ICGC databases. Expression profiles of genes related to natural killer (NK) cells were collected from the Immunology Database and Analysis Portal database. Key NK cell-related genes were identified using consensus clustering algorithms to classify patients into distinct clusters. A NK cell-related risk model was then developed using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression to predict ccRCC patient prognosis. The relationship between the NK cell-related risk score and overall survival, clinical features, tumor immune characteristics, as well as response to commonly used immunotherapies and chemotherapy, was explored. Finally, the NK cell-related risk score was validated using decision tree and nomogram analyses.

RESULTS

ccRCC patients were stratified into 3 molecular clusters based on expression of NK cell-related genes. Significant differences were observed among the clusters in terms of prognosis, clinical characteristics, immune infiltration, and therapeutic response. Furthermore, six NK cell-related genes (DPYSL3, SLPI, SLC44A4, ZNF521, LIMCH1, and AHR) were identified to construct a prognostic model for ccRCC prediction. The high-risk group exhibited poor survival outcomes, lower immune cell infiltration, and decreased sensitivity to conventional chemotherapies and immunotherapies. Importantly, the quantitative real-time polymerase chain reaction (qRT-PCR) confirmed significantly high DPYSL3 expression and low SLC44A4 expression in ACHN cells. Finally, the decision tree and nomogram consistently show the dramatic prediction performance of the risk score on the survival outcome of the ccRCC patients.

CONCLUSIONS

The six-gene model based on NK cell-related gene expression was validated and found to accurately mirror immune microenvironment and predict clinical outcomes, contributing to enhanced risk stratification and therapy response for ccRCC patients.

Non-Metastatic Clear Cell Renal Cell Carcinoma Immune Cell Infiltration Heterogeneity and Prognostic Ability in Patients Following Surgery

Predicting which patients will progress to metastatic disease after surgery for non-metastatic clear cell renal cell carcinoma (ccRCC) is difficult; however, recent data suggest that tumor immune cell infiltration could be used as a biomarker. We evaluated the quantity and type of immune cells infiltrating ccRCC tumors for associations with metastatic progression following attempted curative surgery. We quantified immune cell densities in the tumor microenvironment and validated our findings in two independent patient cohorts with multi-region sampling to investigate the impact of heterogeneity on prognostic accuracy. For non-metastatic ccRCC, increased CD8+ T cell infiltration was associated with a reduced likelihood of progression to metastatic disease. Interestingly, patients who progressed to metastatic disease also had increased percentages of exhausted CD8+ T cells. Finally, we evaluated the spatial heterogeneity of the immune infiltration and demonstrated that patients without metastatic progression had CD8+ T cells in closer proximity to ccRCC cells. These data strengthen the evidence for CD8+ T cell infiltration as a prognostic biomarker in non-metastatic ccRCC and demonstrate that multi-region sampling may be necessary to fully characterize immune infiltration within heterogeneous tumors. Tumor CD8+ T cell infiltration should be investigated as a biomarker in adjuvant systemic therapy clinical trials for high-risk non-metastatic RCC.

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.

Immunomodulatory response to neoadjuvant nivolumab in non-metastatic clear cell renal cell carcinoma

Novel perioperative strategies are needed to reduce recurrence rates in patients undergoing nephrectomy for high-risk, non-metastatic clear cell renal cell carcinoma (ccRCC). We conducted a prospective, phase I trial of neoadjuvant nivolumab prior to nephrectomy in 15 evaluable patients with non-metastatic ccRCC. We leveraged tissue from that cohort to elucidate the effects of PD-1 inhibition on immune cell populations in ccRCC and correlate the evolving immune milieu with anti-PD-1 response. We found that nivolumab durably induces a pro-inflammatory state within the primary tumor, and baseline immune infiltration within the primary tumor correlates with nivolumab responsiveness. Nivolumab increases CTLA-4 expression in the primary tumor, and subsequent nephrectomy increases circulating concentrations of sPD-L1, sPD-L3 (sB7-H3), and s4-1BB. These findings form the basis to consider neoadjuvant immune checkpoint inhibition (ICI) for high-risk ccRCC while the tumor remains in situ and provide the rationale for perioperative strategies of novel ICI combinations.

FKBP10 promotes clear cell renal cell carcinoma progression and regulates sensitivity to the HIF2α blockade by facilitating LDHA phosphorylation

Renal cell carcinoma (RCC) is one of the three major malignant tumors of the urinary system and originates from proximal tubular epithelial cells. Clear cell renal cell carcinoma (ccRCC) accounts for approximately 80% of RCC cases and is recognized as a metabolic disease driven by genetic mutations and epigenetic alterations. Through bioinformatic analysis, we found that FK506 binding protein 10 (FKBP10) may play an essential role in hypoxia and glycolysis pathways in ccRCC progression. Functionally, FKBP10 promotes the proliferation and metastasis of ccRCC in vivo and in vitro depending on its peptidyl-prolyl cis-trans isomerase (PPIase) domains. Mechanistically, FKBP10 binds directly to lactate dehydrogenase A (LDHA) through its C-terminal region, the key regulator of glycolysis, and enhances the LDHA-Y10 phosphorylation, which results in a hyperactive Warburg effect and the accumulation of histone lactylation. Moreover, HIFα negatively regulates the expression of FKBP10, and inhibition of FKBP10 enhances the antitumor effect of the HIF2α inhibitor PT2385. Therefore, our study demonstrates that FKBP10 promotes clear cell renal cell carcinoma progression and regulates sensitivity to HIF2α blockade by facilitating LDHA phosphorylation, which may be exploited for anticancer therapy.

Single-cell profiling of the microenvironment in human bone metastatic renal cell carcinoma

Bone metastasis is of common occurrence in renal cell carcinoma with poor prognosis, but no optimal treatment approach has been established for bone metastatic renal cell carcinoma. To explore the potential therapeutic targets for bone metastatic renal cell carcinoma, we profile single cell transcriptomes of 6 primary renal cell carcinoma and 9 bone metastatic renal cell carcinoma. We also include scRNA-seq data of early-stage renal cell carcinoma, late-stage renal cell carcinoma, normal kidneys and healthy bone marrow samples in the study to better understand the bone metastasis niche. The molecular properties and dynamic changes of major cell lineages in bone metastatic environment of renal cell carcinoma are characterized. Bone metastatic renal cell carcinoma is associated with multifaceted immune deficiency together with cancer-associated fibroblasts, specifically appearance of macrophages exhibiting malignant and pro-angiogenic features. We also reveal the dominance of immune inhibitory T cells in the bone metastatic renal cell carcinoma which can be partially restored by the treatment. Trajectory analysis showes that myeloid-derived suppressor cells are progenitors of macrophages in the bone metastatic renal cell carcinoma while monocytes are their progenitors in primary tumors and healthy bone marrows. Additionally, the infiltration of immune inhibitory CD47+ T cells is observed in bone metastatic tumors, which may be a result of reduced phagocytosis by SIRPA-expressing macrophages in the bone microenvironment. Together, our results provide a systematic view of various cell types in bone metastatic renal cell carcinoma and suggest avenues for therapeutic solutions.

Historical perspective and future directions: computational science in immuno-oncology

Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, underscoring the importance of elucidating molecular mechanisms responsible for response and resistance to inform the development and selection of treatments. Breakthroughs in molecular sequencing technologies have led to the generation of an immense amount of genomic and transcriptomic sequencing data that can be mined to uncover complex tumor-immune interactions using computational tools. In this review, we discuss existing and emerging computational methods that contextualize the composition and functional state of the tumor microenvironment, infer the reactivity and clonal dynamics from reconstructed immune cell receptor repertoires, and predict the antigenic landscape for immune cell recognition. We further describe the advantage of multi-omics analyses for capturing multidimensional relationships and artificial intelligence techniques for integrating omics data with histopathological and radiological images to encapsulate patterns of treatment response and tumor-immune biology. Finally, we discuss key challenges impeding their widespread use and clinical application and conclude with future perspectives. We are hopeful that this review will both serve as a guide for prospective researchers seeking to use existing tools for scientific discoveries and inspire the optimization or development of novel tools to enhance precision, ultimately expediting advancements in immunotherapy that improve patient survival and quality of life.

Targeting STAT3 in tumor-associated antigen-presenting cells as a strategy for kidney and bladder cancer immunotherapy

Introduction

Immune checkpoint blockade (ICB) improved clinical outcomes in renal and bladder cancer patients, but the response rates remain limited especially in metastatic disease. While STAT3 transcription factor is well-known master regulator of tumor immune evasion, little is known about the role of STAT3 in the resistance of renal or bladder cancers to immunotherapy.

Methods

To better understand immune alterations associated with ICB resistance, we assessed blood biomarkers in renal cancer patients classified as responders or non-responders to first line nivolumab/ipilimumab immunotherapy.

Results

We observed that non-responders showed elevated levels of proinflammatory mediators, such as IL-1RA, IL-6, IL-8 and to lesser extent IL-10, which are associated with STAT3 activation and tumor immunosuppression. In addition, we found STAT3 activation primarily in circulating myeloid immune cells such as tolerogenic MDSCs. To assess whether STAT3 inhibition within these cell subsets can promote antitumor immune responses and/or enhance sensitivity to ICB in vivo, we used an original antisense oligonucleotide (ASO) strategy for myeloid-cell selective STAT3 knockdown (CpG-STAT3ASO). Our results in syngeneic models of renal and bladder cancers in mice demonstrated potent antitumor activity of CpG-STAT3ASO alone in contrast to PD1 blockade alone in both models. The CpG-STAT3ASO/anti-PD1 combination improved therapeutic efficacy especially against bladder tumors. Therapeutic efficacy correlated with activation of dendritic cells (DCs) and M1 macrophages in the tumor microenvironment, reduced percentages of regulatory T cells (Tregs) and the expansion of CD8 T cells in both tumor models.

Discussion/Conclusion

Our study underscores the potential of using myeloid-cell targeted CpG-STAT3 inhibitors for genitourinary cancer therapy to disrupt tolerogenic signaling, restore immune cell activity and sensitivity to immune checkpoint inhibitors and/or T cell-based immunotherapies.

IL4I1 in M2-like macrophage promotes glioma progression and is a promising target for immunotherapy

Background

Glioma is the prevailing malignant intracranial tumor, characterized by an abundance of macrophages. Specifically, the infiltrating macrophages often display the M2 subtype and are known as tumor-associated macrophages (TAMs). They have a critical role in promoting the oncogenic properties of tumor cells. Interleukin-4-induced-1 (IL4I1) functions as an L-phenylalanine oxidase, playing a key part in regulating immune responses and the progression of various tumors. However, there is limited understanding of the IL4I1-mediated cross-talk function between TAMs and glioma cell in the glioma microenvironment.

Methods

TCGA, GTEx, and HPA databases were applied to assess the IL4I1 expression, clinical characteristics, and prognostic value of pan-cancer. The link between IL4I1 levels and the prognosis, methylation, and immune checkpoints (ICs) in gliomas were explored through Kaplan-Meier curve, Cox regression, and Spearman correlation analyses. The IL4I1 levels and their distribution were investigated by single-cell analysis and the TIMER 2 database. Additionally, validation of IL4I1 expression was performed by WB, RT-qPCR, IHC, and IF. Co-culture models between glioma cells and M2-like macrophages were used to explore the IL4I1-mediated effects on tumor growth, invasion, and migration of glioma cells. Moreover, the function of IL4I1 on macrophage polarization was evaluated by ELISA, RT-qPCR, WB, and siRNA transfection.

Results

Both transcriptome and protein levels of IL4I1 were increased obviously in various tumor types, and correlated with a dismal prognosis. Specifically, IL4I1 was implicated in aggressive progression and a dismal prognosis for patients with glioma. A negative association was noticed between the glioma grade and DNA promoter methylation of IL4I1. Enrichment analyses in glioma patients suggested that IL4I1 was linked to cytokine and immune responses, and was positively correlated with ICs. Single-cell analysis, molecular experiments, and in vitro assays showed that IL4I1 was significantly expressed in TAMs. Importantly, co-culture models proved that IL4I1 significantly promoted the invasion and migration of glioma cells, and induced the polarization of M2-like macrophages.

Conclusion

IL4I1 could be a promising immunotherapy target for selective modulation of TAMs and stands as a novel macrophage-related prognostic biomarker in glioma.

Fcγ receptors and immunomodulatory antibodies in cancer

The discovery of both cytotoxic T lymphocyte-associated antigen 4 (CTLA4) and programmed cell death protein 1 (PD1) as negative regulators of antitumour immunity led to the development of numerous immunomodulatory antibodies as cancer treatments. Preclinical studies have demonstrated that the efficacy of immunoglobulin G (IgG)-based therapies depends not only on their ability to block or engage their targets but also on the antibody's constant region (Fc) and its interactions with Fcγ receptors (FcγRs). Fc-FcγR interactions are essential for the activity of tumour-targeting antibodies, such as rituximab, trastuzumab and cetuximab, where the killing of tumour cells occurs at least in part due to these mechanisms. However, our understanding of these interactions in the context of immunomodulatory antibodies designed to boost antitumour immunity remains less explored. In this Review, we discuss our current understanding of the contribution of FcγRs to the in vivo activity of immunomodulatory antibodies and the challenges of translating results from preclinical models into the clinic. In addition, we review the impact of genetic variability of human FcγRs on the activity of therapeutic antibodies and how antibody engineering is being utilized to develop the next generation of cancer immunotherapies.

Update on Biomarkers in Renal Cell Carcinoma

Immune checkpoint inhibitors have significantly transformed the treatment paradigm for metastatic renal cell carcinoma (RCC), offering prolonged overall survival and achieving remarkable deep and durable responses. However, given the multiple ICI-containing, standard-of-care regimens approved for RCC, identifying biomarkers that predict therapeutic response and resistance is of critical importance. Although tumor-intrinsic features such as pathological characteristics, genomic alterations, and transcriptional signatures have been extensively investigated, they have yet to provide definitive, robust predictive biomarkers. Current research is exploring host factors through in-depth characterization of the immune system. Additionally, innovative technological approaches are being developed to overcome challenges presented by existing techniques, such as tumor heterogeneity. Promising avenues in biomarker discovery include the study of the microbiome, radiomics, and spatial transcriptomics.

Unveiling the impact of tertiary lymphoid structures on immunotherapeutic responses of clear cell renal cell carcinoma

Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that form under pathological conditions. However, the predictive value of TLS in clear cell renal cell carcinoma (ccRCC) for immunotherapies remains unclear. We comprehensively assessed the implications for prognosis and immunological responses of the TLS spatial and maturation heterogeneity in 655 ccRCC patients. A higher proportion of early-TLS was found in peritumoral TLS, while intratumoral TLS mainly comprised secondary follicle-like TLS (SFL-TLS), indicating markedly better survival. Notably, presence of TLS, especially intratumoral TLS and SFL-TLS, significantly correlated with better survival and objective reflection rate for ccRCC patients receiving anti-Programmed Cell Death Protein-1 (PD-1)/Programmed Cell Death-Ligand-1 (PD-L1) immunotherapies. In peritumoral TLS cluster, primary follicle-like TLS, the proportion of tumor-associated macrophages, and Treg infiltration in the peritumoral regions increased prominently, suggesting an immunosuppressive tumor microenvironment. Interestingly, spatial transcriptome annotation and multispectral fluorescence showed that an abundance of mature plasma cells within mature TLS has the capacity to produce IgA and IgG, which demonstrate significantly higher objective response rates and a superior prognosis for ccRCC patients subjected to immunotherapy. In conclusion, this study revealed the implications of TLS spatial and maturation heterogeneity on the immunological status and clinical responses, allowing the improvement of precise immunotherapies of ccRCC.

CHEK2 is a potential prognostic biomarker associated with immune infiltration in clear cell renal cell carcinoma

Checkpoint kinase 2 (CHEK2) plays a crucial role in responding to DNA damage and is linked to diverse cancer types. However, its significance in the prediction of prognosis and impacts on the immune status of clear cell renal cell carcinoma (ccRCC) remains unclear. This study aimed to identify the role of CHEK2 in prognosis and immune microenvironment of ccRCC. We analyzed transcriptome and clinicopathological data from the cancer genome atlas (TCGA) database and conducted functional enrichment analysis to explore molecular mechanisms. The relationship between CHEK2 and immune infiltration was evaluated, and drug sensitivity analysis was performed using the CellMiner database. The results showed that CHEK2 was an independent predictor of ccRCC prognosis and was closely associated with immune-related processes. Additionally, high expression of CHEK2 was linked to resistance to certain targeted drugs. These findings suggest that CHEK2 could serve as a biomarker for ccRCC, providing insights into tumor immune microenvironment alterations and immunotherapeutic response. Further investigation is needed to fully understand the potential of CHEK2 as a prognostic predictor and therapeutic target for ccRCC.

Long-Term Survival of Patients with Stage T1N0M1 Renal Cell Carcinoma

Metastatic renal cell carcinoma (RCC) is among the most lethal urological malignancies. However, small, localized RCCs (≤7 cm, stage T1) have an excellent prognosis. There is a rare patient subgroup diagnosed with synchronous distant metastasis (T1N0M1), of which very little is known in terms of survival outcomes and underlying disease biology. Herein, we examined the long-term survival of 27 patients with clear cell RCC (ccRCC) stage T1N0M1 in comparison to 18 patients without metastases (T1N0M0). Tumor tissue was stained by immunohistochemistry for CD8+ tumor infiltrating lymphocytes (TILs). As expected, patients with stage T1N0M1 showed a significantly worse median cancer specific survival (CSS; 2.8 years) than patients with stage T1N0M0 (17.7 years; HR 0.077; 95% CI, 0.022-0.262). However, eight patients (29.6%) with ccRCC stage T1N0M1 survived over five years, and three of those patients (11.1%) survived over a decade. Some of these patients benefitted from an intensified, multimodal treatment including metastasis-directed therapy. The number of CD8+ TILs was substantially higher in stage T1N0M1 ccRCCs than in stage T1N0M0 ccRCCs, suggesting a more aggressive tumor biology. In conclusion, long-term survival is possible in patients with ccRCC stage T1N0M1, with some patients benefitting from an intensified, multimodal treatment approach.

The dysfunctional immune response in renal cell carcinoma correlates with changes in the metabolic landscape of ccRCC during disease progression

Renal cell carcinoma is an immunogenic tumour with a prominent dysfunctional immune cell infiltrate, unable to control tumour growth. Although tyrosine kinase inhibitors and immunotherapy have improved the outlook for some patients, many individuals are non-responders or relapse despite treatment. The hostile metabolic environment in RCC affects the ability of T-cells to maintain their own metabolic programme constraining T-cell immunity in RCC. We investigated the phenotype, function and metabolic capability of RCC TILs correlating this with clinicopathological features of the tumour and metabolic environment at the different disease stages. Flow cytometric analysis of freshly isolated TILs showed the emergence of exhausted T-cells in advanced disease based on their PD-1high and CD39 expression and reduced production of inflammatory cytokines upon in vitro stimulation. Exhausted T-cells from advanced stage disease also displayed an overall phenotype of metabolic insufficiency, characterized by mitochondrial alterations and defects in glucose uptake. Nanostring nCounter cancer metabolism assay on RNA obtained from 30 ccRCC cases revealed significant over-expression of metabolic genes even at early stage disease (pT1-2), while at pT3-4 and the locally advanced thrombi stages, there was an overall decrease in differentially expressed metabolic genes. Notably, the gene PPARGC1A was the most significantly down-regulated gene from pT1-2 to pT3-4 RCC which correlated with loss of mitochondrial function in tumour-infiltrating T-cells evident at this tumour stage. Down-regulation of PPARGC1A into stage pT3-4 may be the 'tipping-point' in RCC disease progression, modulating immune activity in ccRCC and potentially reducing the efficacy of immunotherapies in RCC and poorer patient outcomes.

Genitourinary cancer neoadjuvant therapies: current and future approaches

Neoadjuvant therapies can improve tolerability, reduce tumor volume to facilitate surgery, and assess subsequent treatment response. Therefore, there is much enthusiasm for expanding the benefits of cancer therapies to the neoadjuvant setting to reduce recurrence and improve survival in patients with localized or locally advanced genitourinary (GU) cancer. This approach is clinically pertinent because these treatments are administered primarily to treatment-naive patients and can elicit the greatest drug response. In addition, the results are not impacted by other anticancer treatments. While neoadjuvant therapies have been the standard treatment for bladder cancer in the past, they are presently restricted to clinical trials for renal and prostate cancer (PCa); however, changes are imminent. Precision neoadjuvant therapies will be ushered in by biomarker-stratified neoadjuvant trials with appropriate survival endpoints and comprehensive correlative and imaging studies. This review discusses neoadjuvant studies in GU malignancies and how they inform future study design considerations.

The immunometabolic ecosystem in cancer

Our increased understanding of how key metabolic pathways are activated and regulated in malignant cells has identified metabolic vulnerabilities of cancers. Translating this insight to the clinics, however, has proved challenging. Roadblocks limiting efficacy of drugs targeting cancer metabolism may lie in the nature of the metabolic ecosystem of tumors. The exchange of metabolites and growth factors between cancer cells and nonmalignant tumor-resident cells is essential for tumor growth and evolution, as well as the development of an immunosuppressive microenvironment. In this Review, we will examine the metabolic interplay between tumor-resident cells and how targeted inhibition of specific metabolic enzymes in malignant cells could elicit pro-tumorigenic effects in non-transformed tumor-resident cells and inhibit the function of tumor-specific T cells. To improve the efficacy of metabolism-targeted anticancer strategies, a holistic approach that considers the effect of metabolic inhibitors on major tumor-resident cell populations is needed.

Heterogeneity in tertiary lymphoid structures predicts distinct prognosis and immune microenvironment of clear cell renal cell carcinoma

BACKGROUND

Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that develop postnatally in non-lymphoid tissues and are associated with pathological conditions. TLS typically comprise B-cell follicles containing and are encompassed by T- cell zones and dendritic cells. The prognostic and predictive value of TLS in the tumor microenvironment (TME) as potential mediators of antitumor immunity have gained interest. However, the precise relationship between localization and maturation of TLS and the clinical outcome of their presence in clear cell renal cell carcinoma (ccRCC) is yet to be elucidated.

METHODS

Immunohistochemistry and multispectral fluorescence were used to evaluate the TLS heterogeneity along with TME cell-infiltrating characterizations. A thorough investigation of the prognostic implications of the TLS heterogeneity in 395 patients with ccRCC from two independent cohorts was conducted. Associations between TLS heterogeneity and immunologic activity were assessed by quantifying the immune cell infiltration.

RESULTS

Infiltrated TLS were identified in 34.2% of the ccRCC samples (N=395). These TLS were found to be tumor-proximal, tumor-distal, or both in 37.8%, 74.1%, and 11.9% of the TLS-positive cases, respectively. A higher proportion of early TLS was found in tumor-distal TLS (p=0.016), while tumor-proximal TLS primarily comprised secondary follicle-like structures (p=0.004). In the main study cohort (Fudan University Shanghai Cancer Center, N=290), Kaplan-Meier analyses revealed a significant correlation between the presence of tumor-proximal TLS and improved progression-free survival (PFS, p<0.001) and overall survival (OS, p=0.002). Conversely, the presence of tumor-distal TLS was associated with poor PFS (p=0.02) and OS (p=0.021). These findings were further validated in an external validation set of 105 patients with ccRCC. Notably, the presence of mature TLS (namely secondary follicle-like TLS, with CD23+ germinal center) was significantly associated with better clinical outcomes in patients with ccRCC. Furthermore, novel nomograms incorporating the presence of tumor-proximal TLS demonstrated remarkable predictability for the 8-year outcomes of resected ccRCC (area under the curve >0.80). Additionally, ccRCC samples with tumor-distal TLS enriched with primary follicle-like TLS exhibited higher programmed death-ligand 1 tumor-associated macrophages levels and regulatory T cells infiltration in the tumor-distal region, indicative of a suppressive TME.

CONCLUSION

This study for the first time elucidates the impact of TLS localization and maturation heterogeneities on the divergent clinical outcomes of ccRCC. The findings reveal that most TLS in ccRCC are located in the tumor-distal area and are associated with immature, immunosuppressive characterizations. Furthermore, our findings corroborate previous research demonstrating that tumor-proximal TLS were associated with favorable clinical outcomes.

The utilization of single-cell sequencing technology in investigating the immune microenvironment of ccRCC

The growth and advancement of ccRCC are strongly associated with the presence of immune infiltration and the tumor microenvironment, comprising tumor cells, immune cells, stromal cells, vascular cells, myeloid-derived cells, and extracellular matrix (ECM). Nevertheless, as a result of the diverse and constantly evolving characteristics of the tumor microenvironment, prior advanced sequencing methods have frequently disregarded specific less prevalent cellular traits at varying intervals, thereby concealing their significance. The advancement and widespread use of single-cell sequencing technology enable us to comprehend the source of individual tumor cells and the characteristics of a greater number of individual cells. This, in turn, minimizes the impact of intercellular heterogeneity and temporal heterogeneity of the same cell on experimental outcomes. This review examines the attributes of the tumor microenvironment in ccRCC and provides an overview of the progress made in single-cell sequencing technology and its particular uses in the current focus of immune infiltration in ccRCC.

Increased spatial coupling of integrin and collagen IV in the immunoresistant clear cell renal cell carcinoma tumor microenvironment

Background

Immunotherapy (IO) has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with IO naïve and IO exposed primary ccRCC tumors to better understand IO resistance. Spatial molecular imaging (SMI) was obtained for tumor and adjacent stroma samples. Spatial gene set enrichment analysis (GSEA) and autocorrelation (coupling with high expression) of ligand-receptor transcript pairs were assessed. Multiplex immunofluorescence (mIF) validation was used for significant autocorrelative findings and the cancer genome atlas (TCGA) and the clinical proteomic tumor analysis consortium (CPTAC) databases were queried to assess bulk RNA expression and proteomic correlates.

Results

21 patient samples underwent SMI. Viable tumors following IO harbored more stromal CD8+ T cells and neutrophils than IO naïve tumors. YES1 was significantly upregulated in IO exposed tumor cells. The epithelial-mesenchymal transition pathway was enriched on spatial GSEA and the associated transcript pair COL4A1 - ITGAV had significantly higher autocorrelation in the stroma. Fibroblasts, tumor cells, and endothelium had the relative highest expression. More integrin αV+ cells were seen in IO exposed stroma on mIF validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV . In CPTAC, collagen IV protein was more abundant in advanced stages of disease.

Conclusions

On spatial transcriptomics, COL4A1 and ITGAV were more autocorrelated in IO-exposed stroma compared to IO-naïve tumors, with high expression amongst fibroblasts, tumor cells, and endothelium. Integrin represents a potential therapeutic target in IO treated ccRCC.

Stem-like exhausted and memory CD8+ T cells in cancer

T cells can acquire a broad spectrum of differentiation states following activation. At the extreme ends of this continuum are short-lived cells equipped with effector machinery and more quiescent, long-lived cells with heightened proliferative potential and stem cell-like developmental plasticity. The latter encompass stem-like exhausted T cells and memory T cells, both of which have recently emerged as key determinants of cancer immunity and response to immunotherapy. Here, we discuss key similarities and differences in the regulation and function of stem-like exhausted CD8+ T cells and memory CD8+ T cells, and consider their context-specific contributions to protective immunity in diverse outcomes of cancer, including tumour escape, long-term control and eradication. Finally, we emphasize how recent advances in the understanding of the molecular regulation of stem-like exhausted T cells and memory T cells are being explored for clinical benefit in cancer immunotherapies such as checkpoint inhibition, adoptive cell therapy and vaccination.

From mucosal infection to successful cancer immunotherapy

The clinical management of advanced malignancies of the upper and lower urinary tract has been revolutionized with the advent of immune checkpoint blockers (ICBs). ICBs reinstate or bolster pre-existing immune responses while creating new T cell specificities. Immunogenic cancers, which tend to benefit more from immunotherapy than cold tumours, harbour tumour-specific neoantigens, often associated with a high tumour mutational burden, as well as CD8+ T cell infiltrates and ectopic lymphoid structures. The identification of beneficial non-self tumour antigens and natural adjuvants is the focus of current investigation. Moreover, growing evidence suggests that urinary or intestinal commensals, BCG and uropathogenic Escherichia coli influence long-term responses in patients with kidney or bladder cancer treated with ICBs. Bacteria infecting urothelium could be a prominent target for T follicular helper cells and B cells, linking innate and cognate CD8+ memory responses. In the urinary tract, commensal flora differ between healthy and tumoural mucosae. Although antibiotics can affect the prognosis of urinary tract malignancies, bacteria can have a major influence on cancer immunosurveillance. Beyond their role as biomarkers, immune responses against uropathogenic commensals could be harnessed for the design of future immunoadjuvants that can be advantageously combined with ICBs.