Renal Cell Carcinoma: A Study through NMR-Based Metabolomics Combined with Transcriptomics

CD276 enhances sunitinib resistance in clear cell renal cell carcinoma by promoting DNA damage repair and activation of FAK-MAPK signaling pathway

OBJECTIVE

This study aimed to explore the effect of CD276 expression on the sunitinib sensitivity of clear cell renal cell carcinoma (ccRCC) cell and animal models and the potential mechanisms involved.

METHODS

CD276 expression levels of ccRCC and normal samples were analyzed via online databases and real-time quantitative PCR (RT-qPCR). CD276 was knocked down in ccRCC cell models (sunitinib-resistant 786-O/R cells and sunitinib-sensitive 786-O cells) using shRNA transfection, and the cells were exposed to a sunitinib (2 µM) environment. Cells proliferation was then analyzed using MTT assay and colony formation experiment. Alkaline comet assay, immunofluorescent staining, and western blot experiments were conducted to assess the DNA damage repair ability of the cells. Western blot was also used to observe the activation of FAK-MAPK pathway within the cells. Finally, a nude mouse xenograft model was established and the nude mice were orally administered sunitinib (40 mg/kg/d) to evaluate the in vivo effects of CD276 knockdown on the therapeutic efficacy of sunitinib against ccRCC.

RESULTS

CD276 was significantly upregulated in both ccRCC clinical tissue samples and cell models. In vitro experiments showed that knocking down CD276 reduced the survival rate, IC50 value, and colony-forming ability of ccRCC cells. Knocking down CD276 increased the comet tail moment (TM) values and γH2AX foci number, and reduced BRCA1 and RAD51 protein levels. Knocking down CD276 also decreased the levels of p-FAK, p-MEK, and p-ERK proteins.

CONCLUSION

Knocking down CD276 effectively improved the sensitivity of ccRCC cell and animal models to sunitinib treatment.

Function of NEK2 in clear cell renal cell carcinoma and its effect on the tumor microenvironment

BACKGROUND

Previous studies have revealed the critical functions of NEK2 in controlling the cell cycle which is linked to poor prognosis in multiple tumor types, but less research has been devoted to clear cell renal cell carcinoma (ccRCC).

METHODS

We downloaded clinical data from the gene expression omnibus (GEO) and TCGA databases together with transcriptional and mutational datasets. Strongly coexpressed genes with NEK2 were extracted from TCGA-KIRC cohort, and were submitted to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional analyses. According to NEK2 levels, the survival status, mutational characteristics, response to immunotherapy and sensitivity to drugs of the patients were studied. The potential correlations between NEK2 levels and immune cell state as well as immune cell infiltration were examined using the GEPIA, TIMER and TISIDB databases. Double immunofluorescence (IF) was performed to identify the NEK2 overexpression and relationship with CD8 in ccRCC.

RESULTS

The NEK2 gene was overexpressed and would enhance the nuclear division and cell cycle activities in ccRCC. ccRCC patients with high NEK2 expression had worse clinical outcomes, higher mutation burden and better therapeutic response. Moreover, NEK2 gene overexpression was positively related to various immune cell marker sets, which was also proved by validation cohort, and more infiltration of various immune cells.

CONCLUSION

ccRCC patients with NEK2 high expression have a poorer prognosis than those with NEK2 low expression, resulting from its function of promoting proliferation, accompanied by increased infiltration of CD8 + T cells and Tregs and T-cell exhaustion and will respond better to proper treatments.

ZNF692 promotes the migration and response to immunotherapy of clear cell renal cell carcinoma cells by targeting metabolic pathway

Clear cell renal cell carcinoma (ccRCC), with high mortality and poor prognosis, is the most common type of renal malignancy. It is necessary to identify new biomarkers that can serve as indicators for the detection of ccRCC at its early stages. In this study, we analyzed the role of classical zinc finger protein 692 (ZNF692) in ccRCC using datasets from The Cancer Genome Atlas (TCGA) and Single Cell Portal and immunohistochemical (IHC) staining of a tissue-microarray, and analyzed the function of ZNF692 in ccRCC cells. The analyses indicated that ZNF692 was upregulated in ccRCC samples compared with normal or paracancerous control samples (P < 0.001) and that the expression of this gene was linked to poor overall survival (HR = 2.1, P < 0.0001). The knockdown of ZNF692 inhibited the proliferation and migration of ccRCC cells by target GTPase-activating protein (SH3 domain)-binding protein 2 (G3BP2), and transmembrane 9 superfamily member 2 (TM9SF2)). T, B, proximal, and collecting tubule cells are the dominant cell types in normal kidney tissue where ZNF692 is expressed. In addition, immune checkpoint blockade (ICB) therapy dramatically changed the expression patterns of ZNF692. Collectively, these data indicate that ZNF692 may serve as prognosis, and as a potential indicator of the response to ICB therapy, a possibility needs to be verified by a case‒control study.

Elevated histone deacetylase 10 expression promotes the progression of clear cell renal cell carcinoma by Notch-1-PTEN signaling axis

BACKGROUND

Clear cell renal cell carcinoma (ccRCC), the most common pathological subtype of kidney cancer, accounts for approximately 70% to 80% of all cases. Histone deacetylase 10 (HDAC10) belongs to the HDAC class IIb subgroup, one of the histone deacetylases (HDAC) family. Previous studies suggest that HDAC10 may regulate the development of multiple tumor types. The specific molecular mechanisms employed by HDAC10 in the etiology of ccRCC still need to be discovered.

METHODS

The analysis included examining HDAC10 expression levels and their clinical importance within a cohort of inpatients and ccRCC patients documented in the Tumor Genome Atlas (TCGA). Moreover, the biological functions and underlying molecular mechanisms of HDAC10 were investigated.

RESULTS

HDAC10 showed increased expression in ccRCC tumor tissues. Subsequent analysis revealed overexpression of HDAC10 was associated with advanced clinical phenotype and unfavorable prognosis. The absence of HDAC10 significantly decreased ccRCC cell proliferation and migration capabilities. Mechanistic research suggests that HDAC10 may promote RCC development by activating the Notch-1 pathway and downregulating PTEN expression levels.

CONCLUSION

In summary, HDAC10 can modulate critical biological processes in ccRCC, including proliferation, migration, and apoptosis. Notably, the Notch-1 pathway and PTEN serve as crucial signaling pathways and target genes through which HDAC10 regulates the progression of ccRCC. These findings offer a novel outlook for ccRCC treatment.

MIER2/PGC1A elicits sunitinib resistance via lipid metabolism in renal cell carcinoma

INTRODUCTION

Renal cell carcinoma (RCC) is one of the most common malignant tumors of the urinary system and accounts for more than 90 % of all renal tumors. Resistance to targeted therapy has emerged as a pivotal factor that contributes to the progressive deterioration of patients with advanced RCC. Metabolic reprogramming is a hallmark of tumorigenesis and progression, with an increasing body of evidence indicating that abnormal lipid metabolism plays a crucial role in the advancement of renal clear cell carcinoma.

OBJECTIVES

Clarify the precise mechanisms underlying abnormal lipid metabolism and drug resistance.

METHODS

Bioinformatics screening and analyses were performed to identify hub gene. qRT-PCR, western blot, chromatin immunoprecipitation (ChIP) assays, and other biological methods were used to explore and verify related pathways. Various cell line models and animal models were used to perform biological functional experiments.

RESULTS

In this study, we identified Mesoderm induction early response 2 (MIER2) as a novel biomarker for RCC, demonstrating its role in promoting malignancy and sunitinib resistance by influencing lipid metabolism in RCC. Mechanistically, MIER2 facilitated P53 deacetylation by binding to HDAC1. Acetylation modification augmented the DNA-binding stability and transcriptional function of P53, while deacetylation of P53 hindered the transcriptional process of PGC1A, leading to intracellular lipid accumulation in RCC. Furthermore, Trichostatin A (TSA), an inhibitor of HDAC1, was found to impede the MIER2/HDAC1/P53/PGC1A pathway, offering potential benefits for patients with sunitinib-resistant renal cell cancer.

CONCLUSION

Our findings highlight MIER2 as a key player in anchoring HDAC1 and inhibiting PGC1A expression through the deacetylation of P53, thereby inducing lipid accumulation in RCC and promoting drug resistance. Lipid-rich RCC cells compensate for energy production and sustain their own growth in a glycolysis-independent manner, evading the cytotoxic effects of targeted drugs and ultimately culminating in the development of drug resistance.

Exploring the causal relationship between omega-3 and omega-6 fatty acids and kidney cancer: a Mendelian randomization study

Background

The causal link between kidney cancer and omega-3/6 (ω-3/6) fatty acids is yet to be clearly established. Therefore, the objective of our study was to investigate these potential causal relationships.

Methods

We conducted a two-sample Mendelian randomization (MR) analysis to investigate the possible causal association between ω-3/6 fatty acids and kidney cancer. We utilized the random effect inverse variance weighted (IVW) method as our primary analytical approach for the two-sample MR analysis. In addition, sensitivity analyses such as heterogeneity tests, pleiotropy analyses, and leave-one-out analyses were performed to assess the robustness of the MR analysis results.

Results

The IVW method showed statistically significant associations between ω-3 and ω-6 fatty acids and increased risk of kidney cancer. The result for ω-3 and ω-6 were [odds ratio (OR) =1.27; 95% confidence interval (CI): 1.04-1.55; P=0.02] and (OR =1.56; 95% CI: 1.17-2.09; P=0.003), respectively. Moreover, in the results of sensitivity analyses, no apparent horizontal gene pleiotropy nor heterogeneity was observed. After performing "the leave-one-out" sensitivity analysis of the data one by one, no single nucleotide polymorphisms (SNPs) sites in each instrumental variable (IV) were found to have greatly affected the disease outcome.

Conclusions

Elevated serum ω-3/6 fatty acids levels are causally associated with an increased risk of kidney cancer. Therefore, it is crucial to monitor dietary intake and properly intervene to lower these levels in those at risk of kidney cancer.

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.

CDCA5-EEF1A1 interaction promotes progression of clear cell renal cell carcinoma by regulating mTOR signaling

BACKGROUND

Cell division cycle associated 5 (CDCA5) plays ontogenetic role in various human cancers. However, its specific function and regulatory mechanism in ccRCC remain uncertain.

METHODS

Immunohistochemistry and western blots were performed to investigate the expression of CDCA5 in ccRCC tissues. Genetic knockdown and upregulation of CDCA5 were performed to investigate its functional roles in ccRCC proliferation, migration, apoptosis and sunitinib resistance. Furthermore, Co-IP assay and LC-MS/MS were performed to investigate the underlying mechanisms.

RESULTS

We found that CDCA5 expression is frequently upregulated in ccRCC tumors and is associated with poor prognosis of ccRCC patients. Functionally, CDCA5 promotes proliferation, migration, and sunitinib resistance, while inhibiting apoptosis in ccRCC cells. In vivo mouse xenograft model confirms that silencing of CDCA5 drastically inhibits the growth of ccRCC. Mechanistically, we discovered that CDCA5 interacts with Eukaryotic Translation Elongation Factor 1 Alpha 1 (EEF1A1) to regulate mTOR signaling pathway, thereby promoting ccRCC progression.

CONCLUSIONS

Taken together, our results demonstrate the significant role of CDCA5 in ccRCC progression. The findings may provide insights for the development of new treatment strategies targeting CDCA5 for ccRCC patients.

Integrating tumor and healthy epithelium in a micro-physiology multi-compartment approach to study renal cell carcinoma pathophysiology

The advent of micro-physiological systems (MPS) in biomedical research has enabled the introduction of more complex and relevant physiological into in vitro models. The recreation of complex morphological features in three-dimensional environments can recapitulate otherwise absent dynamic interactions in conventional models. In this study we developed an advanced in vitro Renal Cell Carcinoma (RCC) that mimics the interplay between healthy and malignant renal tissue. Based on the TissUse Humimic platform our model combines healthy renal proximal tubule epithelial cells (RPTEC) and RCC. Co-culturing reconstructed RPTEC tubules with RCC spheroids in a closed micro-perfused circuit resulted in significant phenotypical changes to the tubules. Expression of immune factors revealed that interleukin-8 (IL-8) and tumor necrosis factor-alfa (TNF-α) were upregulated in the non-malignant cells while neutrophil gelatinase-associated lipocalin (NGAL) was downregulated in both RCC and RPTEC. Metabolic analysis showed that RCC prompted a shift in the energy production of RPTEC tubules, inducing glycolysis, in a metabolic adaptation that likely supports RCC growth and immunogenicity. In contrast, RCC maintained stable metabolic activity, emphasizing their resilience to external factors. RNA-seq and biological process analysis of primary RTPTEC tubules demonstrated that the 3D tubular architecture and MPS conditions reverted cells to a predominant oxidative phosphorylate state, a departure from the glycolytic metabolism observed in 2D culture. This dynamic RCC co-culture model, approximates the physiology of healthy renal tubules to that of RCC, providing new insights into tumor-host interactions. Our approach can show that an RCC-MPS can expand the complexity and scope of pathophysiology and biomarker studies in kidney cancer research.

Multi-omics and immunogenomics analysis revealed PFKFB3 as a targetable hallmark and mediates sunitinib resistance in papillary renal cell carcinoma: in silico study with laboratory verification

Glycolysis-related metabolic reprogramming is a central hallmark of human cancers, especially in renal cell carcinoma. However, the regulatory function of glycolytic signature in papillary RCC has not been well elucidated. In the present study, the glycolysis-immune predictive signature was constructed and validated using WGCNA, glycolysis-immune clustering analysis. PPI network of DEGs was constructed and visualized. Functional enrichments and patients' overall survival were analyzed. QRT-PCR experiments were performed to detect hub genes' expression and distribution, siRNA technology was used to silence targeted genes; cell proliferation and migration assays were applied to evaluate the biological function. Glucose concentration, lactate secretion, and ATP production were measured. Glycolysis-Immune Related Prognostic Index (GIRPI) was constructed and combined analyzed with single-cell RNA-seq. High-GIRPI signature predicted significantly poorer outcomes and relevant clinical features of pRCC patients. Moreover, GIRPI also participated in several pathways, which affected tumor immune microenvironment and provided potential therapeutic strategy. As a key glycolysis regulator, PFKFB3 could promote renal cancer cell proliferation and migration in vitro. Blocking of PFKFB3 by selective inhibitor PFK-015 or glycolytic inhibitor 2-DG significantly restrained renal cancer cells' neoplastic potential. PFK-015 and sunitinib could synergistically inhibit pRCC cells proliferation. Glycolysis-Immune Risk Signature is closely associated with pRCC prognosis, progression, immune infiltration, and therapeutic response. PFKFB3 may serve as a pivotal glycolysis regulator and mediates Sunitinib resistance in pRCC patients.

Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC

Clear cell renal cell carcinoma (ccRCC) is the prevailing histological subtype of renal cell carcinoma and has unique metabolic reprogramming during its occurrence and development. Cell senescence is one of the newly identified tumor characteristics. However, there is a dearth of methodical and all-encompassing investigations regarding the correlation between the broad-ranging alterations in metabolic processes associated with aging and ccRCC. We utilized a range of analytical methodologies, such as protein‒protein interaction network analysis and least absolute shrinkage and selection operator (LASSO) regression analysis, to form and validate a risk score model known as the senescence-metabolism-related risk model (SeMRM). Our study demonstrated that SeMRM could more precisely predict the OS of ccRCC patients than the clinical prognostic markers in use. By utilizing two distinct datasets of ccRCC, ICGC-KIRC (the International Cancer Genome Consortium) and GSE29609, as well as a single-cell dataset (GSE156632) and real patient clinical information, and further confirmed the relationship between the senescence-metabolism-related risk score (SeMRS) and ccRCC patient progression. It is worth noting that patients who were classified into different subgroups based on the SeMRS exhibited notable variations in metabolic activity, immune microenvironment, immune cell type transformation, mutant landscape, and drug responsiveness. We also demonstrated that PTGER4, a key gene in SeMRM, regulated ccRCC cell proliferation, lipid levels and the cell cycle in vivo and in vitro. Together, the utilization of SeMRM has the potential to function as a dependable clinical characteristic to increase the accuracy of prognostic assessment for patients diagnosed with ccRCC, thereby facilitating the selection of suitable treatment strategies.

Implications of MTHFD2 expression in renal cell carcinoma aggressiveness

Renal cell carcinoma (RCC) is the most common type of cancer in kidney and is often diagnosed in advanced stages. Until now, there is no reliable biomarker to assess tumor prognosis during histopathological diagnosis. The Methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) overexpression has been suggested as prognostic indicator for RCC, however, its protein profile needs to be clarified. This study investigated the MTHFD2 expression in different RCC cohorts, associating it with tumor characteristics and prognostic factors. Gene expression comparisons between non-neoplastic (NN) and tumor samples, as well as patients' survival analysis, were assessed using KM-Plotter tool. MTHFD2 protein pattern was evaluated in 117 RCC by immunohistochemistry and associations with prognosis, clinical and pathological data were investigated. The tumors exhibited higher MTHFD2 transcript levels than NN, being even higher in the metastatic group. Opposite gene expression patterns were found among clear cell renal cell carcinoma (ccRCC) and pappilary renal cell carcinoma (pRCC) subtypes, showing higher and lower expressions compared to NN samples respectively. Overexpression was associated with shorter overall survival for ccRCC and pRCC subtypes, and shorter recurrence-free survival for pRCC. The immunolabeling profile varied according to tumor subtypes, with lower intensity and expression scores in ccRCC compared to pRCC and to chromophobe renal cell carcinoma (chRCC). MTHFD2 protein expression was associated with larger tumors and higher Fuhrman grades. Although prognostic value of protein immunostaining was not confirmed, patients with higher MTHFD2 tended to have lower survival rates in the pRCC group. The results highlight MTHFD2 different patterns according to RCC histological subtypes, revealing marked variations at both the genetic and protein levels. The mRNA indicated tumor prognosis, and greater expression in the tumor samples. Although MTHFD2 immunolabeling suggests tumor aggressiveness, it needs to be validated in other cohorts as potential prognostic factor.

DNA damage response alterations in clear cell renal cell carcinoma: clinical, molecular, and prognostic implications

BACKGROUND

DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic responses. Nonetheless, the characteristics and significance of DDR alterations in clear cell renal cell carcinoma (ccRCC) remain undefined. This study aimed to explore the predictive role, molecular mechanism, and tumor immune profile of DDR genes in ccRCC.

METHODS

We prospectively sequenced 757 tumors and matched blood DNA samples from Chinese patients with ccRCC using next-generation sequencing (NGS) and analyzed data from 537 patients from The Cancer Genome Atlas (TCGA). A comprehensive analysis was performed.

RESULTS

Fifty-two percent of Chinese patients with ccRCC harbored DDR gene mutations and 57% of TCGA patients. The immunotherapy treatment prognosis of patients with DDR gene mutations was superior to that of patients without DDR gene mutations (p = 0.047). DDR gene mutations were associated with more gene mutations and a higher tumor mutation load (TMB, p < 0.001). Moreover, patients with DDR gene mutations have a distinct mutational signature compared with those with wild-type DDR. Furthermore, the DDR-mut group had elevated neoantigen load (including single-nucleotide variants (SNV) and indel neoantigen load, p = 0.037 and p = 0.002, respectively), TCR Shannon (p = 0.025), and neutrophils (p = 0.010). DDR gene mutations exhibited a distinct immune profile with significantly higher expression levels of TNFSF9, CD70, ICAM1, and indoleamine-2,3-dioxygenase (IDO) and lower expression levels of VTCN1 and IL12A.

CONCLUSIONS

Our data suggest that the detection of somatic mutations in DDR genes can predict the efficacy of immunotherapy in patients with ccRCC. Furthermore, we revealed the unique molecular and immune mechanisms underlying ccRCC with DDR gene mutations.

Identifying endoplasmic reticulum stress-related genes as new diagnostic and prognostic biomarkers in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers worldwide, and its incidence is increasing every year. Endoplasmic reticulum stress (ERS) caused by protein misfolding has broad and profound effects on the progression and metastasis of various cancers. Accumulating evidence suggests that ERS is closely related to the occurrence and progression of ccRCC. This study aimed to identify ERS-related genes for evaluating the prognosis of ccRCC.

Methods

Transcriptomic expression profiles were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), and clinical data were downloaded from the TCGA. First, the differentially expressed genes (DEGs) were analyzed using the limma package, and the DEGs related to ERS (ERS-DEGs) were identified from the GeneCards database. Second, a function and pathway enrichment analysis and a Gene Set Enrichment Analysis (GSEA) were performed. Third, a protein-protein interaction (PPI) network was constructed to identify the hub genes, and a gene-micro RNA (miRNA) network and gene-transcription factor (TF) network were established using the hub genes. Finally, a least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to establish a diagnostic model, and a Cox analysis was used to analyze the correlations between the expression of the characteristic genes and the clinical characteristics.

Results

We identified 11 signature genes and established a diagnostic model. Further, the Cox analysis results revealed a correlation between the expression levels of the signature genes and the clinical characteristics. Ultimately, five signature genes (i.e., TNFSF13B, APOL1, COL5A3, and CDH5) were found to be associated with a poor prognosis.

Conclusions

This study suggests that TNFSF13B, APOL1, COL5A3, and CDH5 may have potential as prognostic biomarkers in ccRCC and may provide new evidence to support targeted therapy in ccRCC.

Metabolomic profiling of human bladder tissue extracts

INTRODUCTION

Bladder cancer is a common malignancy affecting the urinary tract and effective biomarkers and for which monitoring therapeutic interventions have yet to be identified.

OBJECTIVES

Major aim of this work was to perform metabolomic profiling of human bladder cancer and adjacent normal tissue and to evaluate cancer biomarkers.

METHODS

This study utilized nuclear magnetic resonance (NMR) and high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS) methods to investigate polar metabolite profiles in tissue samples from 99 bladder cancer patients.

RESULTS

Through NMR spectroscopy, six tissue metabolites were identified and quantified as potential indicators of bladder cancer, while LDI-MS allowed detection of 34 compounds which distinguished cancer tissue samples from adjacent normal tissue. Thirteen characteristic tissue metabolites were also found to differentiate bladder cancer tumor grades and thirteen metabolites were correlated with tumor stages. Receiver-operating characteristics analysis showed high predictive power for all three types of metabolomics data, with area under the curve (AUC) values greater than 0.853.

CONCLUSION

To date, this is the first study in which bladder human normal tissues adjacent to cancerous tissues are analyzed using both NMR and MS method. These findings suggest that the metabolite markers identified in this study may be useful for the detection and monitoring of bladder cancer stages and grades.

Comprehensive analysis of a tryptophan metabolism-related model in the prognostic prediction and immune status for clear cell renal carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is characterized as one of the most common types of urological cancer with high degrees of malignancy and mortality. Due to the limited effectiveness of existing traditional therapeutic methods and poor prognosis, the treatment and therapy of advanced ccRCC patients remain challenging. Tryptophan metabolism has been widely investigated because it significantly participates in the malignant traits of multiple cancers. The functions and prognostic values of tryptophan metabolism-related genes (TMR) in ccRCC remain virtually obscure.

METHODS

We employed the expression levels of 40 TMR genes to identify the subtypes of ccRCC and explored the clinical characteristics, prognosis, immune features, and immunotherapy response in the subtypes. Then, a model was constructed for the prediction of prognosis based on the differentially expressed genes (DEGs) in the subtypes from the TCGA database and verified using the ICGC database. The prediction performance of this model was confirmed by the receiver operating characteristic (ROC) curves. The relationship of Risk Score with the infiltration of distinct tumor microenvironment cells, the expression profiles of immune checkpoint genes, and the treatment benefits of immunotherapy and chemotherapy drugs were also investigated.

RESULTS

The two subtypes revealed dramatic differences in terms of clinical characteristics, prognosis, immune features, and immunotherapy response. The constructed 6-gene-based model showed that the high Risk Score was significantly connected to poor overall survival (OS) and advanced tumor stages. Furthermore, increased expression of CYP1B1, KMO, and TDO2 was observed in ccRCC tissues at the translation levels, and an unfavorable prognosis for these patients was also found.

CONCLUSION

We identified 2 molecular subtypes of ccRCC based on the expression of TMR genes and constructed a prognosis-related model that may be used as a powerful tool to guide the prediction of ccRCC prognosis and personalized therapy. In addition, CYP1B1, KMO, and TDO2 can be regarded as the risk prognostic genes for ccRCC.

Impact of sunitinib resistance on clear cell renal cell carcinoma therapeutic sensitivity in vitro

Sunitinib resistance creates a major clinical challenge for the treatment of advanced clear cell renal cell carcinoma (ccRCC) and functional and metabolic changes linked to sunitinib resistance are not fully understood. We sought to characterize the molecular and metabolic changes induced by the development of sunitinib resistance in ccRCC by developing and characterizing two human ccRCC cell lines resistant to sunitinib. Consistent with the literature, sunitinib-resistant ccRCC cell lines presented an aberrant overexpression of Axl and PD-L1, as well as a metabolic rewiring characterized by enhanced OXPHOS and glutamine metabolism. Therapeutic challenges of sunitinib-resistant ccRCC cell lines in vitro using small molecule inhibitors targeting Axl, AMPK and p38, as well as using PD-L1 blocking therapeutic antibodies, showed limited CTL-mediated cytotoxicity in a co-culture model. However, the AMPK activator metformin appears to sensitize the effect of PD-L1 blocking therapeutic antibodies and to enhance CTLs' cytotoxic effects on ccRCC cells. These effects were not broadly observed with the Axl and the p38 inhibitors. Taken together, these data suggest that targeting certain pathways aberrantly activated by sunitinib resistance such as the AMPK/PDL1 axis might sensitize ccRCC to immunotherapies as a second-line therapeutic approach.

The role of RNA modification in urological cancers: mechanisms and clinical potential

RNA modification is a post-transcriptional level of regulation that is widely distributed in all types of RNAs, including mRNA, tRNA, rRNA, miRNA, and lncRNA, where N6-methyladenine (m6A) is the most abundant mRNA methylation modification. Significant evidence has depicted that m6A modifications are closely related to human diseases, especially cancer, and play pivotal roles in RNA transcription, splicing, stabilization, and translation processes. The most common urological cancers include prostate, bladder, kidney, and testicular cancers, accounting for a certain proportion of human cancers, with an ever-increasing incidence and mortality. The recurrence, systemic metastasis, poor prognosis, and drug resistance of urologic tumors have prompted the identification of new therapeutic targets and mechanisms. Research on m6A modifications may provide new solutions to the current puzzles. In this review, we provide a comprehensive overview of the key roles played by RNA modifications, especially m6A modifications, in urologic cancers, as well as recent research advances in diagnostics and molecularly targeted therapies.

The functions of long non-coding RNA (lncRNA)-MALAT-1 in the pathogenesis of renal cell carcinoma

Renal cell carcinoma (RCC), a prevalent form of renal malignancy, is distinguished by its proclivity for robust tumor proliferation and metastatic dissemination. Long non-coding RNAs (lncRNAs) have emerged as pivotal modulators of gene expression, exerting substantial influence over diverse biological processes, encompassing the intricate landscape of cancer development. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT-1), an exemplar among lncRNAs, has been discovered to assume functional responsibilities within the context of RCC. The conspicuous expression of MALAT-1 in RCC cells has been closely linked to the advancement of tumors and an unfavorable prognosis. Experimental evidence has demonstrated the pronounced ability of MALAT-1 to stimulate RCC cell proliferation, migration, and invasion, thereby underscoring its active participation in facilitating the metastatic cascade. Furthermore, MALAT-1 has been implicated in orchestrating angiogenesis, an indispensable process for tumor expansion and metastatic dissemination, through its regulatory influence on pro-angiogenic factor expression. MALAT-1 has also been linked to the evasion of immune surveillance in RCC, as it can regulate the expression of immune checkpoint molecules and modulate the tumor microenvironment. Hence, the potential utility of MALAT-1 as a diagnostic and prognostic biomarker in RCC emerges, warranting further investigation and validation of its clinical significance. This comprehensive review provides an overview of the diverse functional roles exhibited by MALAT-1 in RCC.

A Notch signaling-related lncRNA signature for predicting prognosis and therapeutic response in clear cell renal cell carcinoma

Increasing evidence has confirmed the vital role of Notch signaling in the tumorigenesis of clear cell renal cell carcinoma (ccRCC). The underlying function of long non-coding RNA (lncRNA) related to Notch signaling in ccRCC remains unclear. In present study, the prognostic value and therapeutic strategy of Notch signaling-related lncRNA are comprehensively explored in ccRCC. In total, we acquired 1422 NSRlncRNAs, of which 41 lncRNAs were identified the key NSRlncRNAs associated with the occurrence of ccRCC. The prognostic signature containing five NSRlncRNAs (AC092611.2, NNT-AS1, AGAP2-AS1, AC147651.3, and AC007406.3) was established and validated, and the ccRCC patients were clustered into the high- and low-risk groups. The overall survival of patients in the low-risk group were much more favorable than those in the high-risk group. Multivariate Cox regression analysis indicated that the risk score was an independent prognostic biomarker. Based on the risk score and clinical variables, a nomogram for predicting prognosis of ccRCC patients was constructed, and the calibration curves and DCA curves showed the superior predictive ability of nomogram. The risk score was correlated with immune cell infiltration, targeted therapy or chemotherapy sensitivity, and multiple oncogenic pathways. Additionally, consensus clustering analysis stratified the ccRCC patients into four clusters with obvious different outcomes, immune microenvironments, and expression of immune checkpoints. The constructed NSRlncRNA-based signature might serve as a potential biomarker for predicting prognosis and response to immunotherapy or targeted therapy in patients with ccRCC.

Complement System and the Kidney: Its Role in Renal Diseases, Kidney Transplantation and Renal Cell Carcinoma

The crosstalk among the complement system, immune cells, and mediators of inflammation provides an efficient mechanism to protect the organism against infections and support the repair of damaged tissues. Alterations in this complex machinery play a role in the pathogenesis of different diseases. Core complement proteins C3 and C5, their activation fragments, their receptors, and their regulators have been shown to be active intracellularly as the complosome. The kidney is particularly vulnerable to complement-induced damage, and emerging findings have revealed the role of complement system dysregulation in a wide range of kidney disorders, including glomerulopathies and ischemia-reperfusion injury during kidney transplantation. Different studies have shown that activation of the complement system is an important component of tumorigenesis and its elements have been proved to be present in the TME of various human malignancies. The role of the complement system in renal cell carcinoma (RCC) has been recently explored. Clear cell and papillary RCC upregulate most of the complement genes relative to normal kidney tissue. The aim of this narrative review is to provide novel insights into the role of complement in kidney disorders.

CD72, a new immune checkpoint molecule, is a novel prognostic biomarker for kidney renal clear cell carcinoma

BACKGROUND

The incidence and mortality of clear cell carcinoma of the kidney increases yearly. There are limited screening methods and advances in treating kidney renal clear cell carcinoma (KIRC). It is important to find new biomarkers to screen, diagnose and predict the prognosis of KIRC. Some studies have shown that CD72 influences the development and progression of colorectal cancer, nasopharyngeal cancer, and acute lymphoid leukemia. However, there is a lack of research on the role of CD72 in the pathogenesis of KIRC. This study aimed to determine whether CD72 is associated with the prognosis and immune infiltration of KIRC, providing an essential molecular basis for the early non-invasive diagnosis and immunotherapy of KIRC.

METHODS

Using TCGA, GTE, GEO, and ImmPort databases, we obtained the differentially expressed mRNA (DEmRNA) associated with the prognosis and immunity of KIRC patients. We used the Kruskal-Wallis test to identify clinicopathological parameters associated with target gene expression. We performed univariate and multivariate COX regression analyses to determine the effect of target gene expression and clinicopathological parameters on survival. We analyzed the target genes' relevant functions and signaling pathways through enrichment analysis. Finally, the correlation of target genes with tumor immune infiltration was explored by ssGSEA and Spearman correlation analysis.

RESULTS

The results revealed that patients with KIRC with higher expression of CD72 have a poorer prognosis. CD72 was associated with the Pathologic T stage, Pathologic stage, Pathologic M stage, Pathologic N stage, Histologic grade in KIRC patients, Laterality, and OS event. It was an independent predictor of the overall survival of KIRC patients. Functional enrichment analysis showed that CD72 was significantly enriched in oncogenic and immune-related pathways. According to ssGSEA and Spearman correlation analysis, CD72 expression was significantly associated with tumor immune cells and immune checkpoints.

CONCLUSION

Our study suggests that CD72 is associated with tumor immunity and may be a biomarker relevant to the diagnosis and prognosis of KIRC patients.

STAT3 phosphorylation at serine 727 activates specific genetic programs and promotes clear cell renal cell carcinoma (ccRCC) aggressiveness

The signal transducer and activator of transcription 3 (STAT3) is a transcription factor mainly activated by phosphorylation in either tyrosine 705 (Y705) or serine 727 (S727) residues that regulates essential processes such as cell differentiation, apoptosis inhibition, or cell survival. Aberrant activation of STAT3 has been related to development of nearly 50% of human cancers including clear cell renal cell carcinoma (ccRCC). In fact, phosho-S727 (pS727) levels correlate with overall survival of ccRCC patients. With the aim to elucidate the contribution of STAT3 phosphorylation in ccRCC development and progression, we have generated human-derived ccRCC cell lines carrying STAT3 Y705 and S727 phosphomutants. Our data show that the phosphomimetic substitution Ser727Asp facilitates a pro-tumoral phenotype in vitro, in a Y705-phosphorylation-independent manner. Moreover, we describe that STAT3 phosphorylation state determines the expression of different subsets of target genes associated with distinct biological processes, being pS727-dependent genes the most related to cellular hallmarks of cancer. In summary, the present study constitutes the first analysis on the role of overall STAT3 phosphorylation state in ccRCC and demonstrates that pS727 promotes the expression of a specific subset of target genes that might be clinically relevant as novel biomarkers and potential therapeutic targets for ccRCC.

CENPE and LDHA were potential prognostic biomarkers of chromophobe renal cell carcinoma

BACKGROUND

Most sarcomatoid differentiated renal cell carcinoma was differentiated from Chromophobe renal cell carcinoma (KICH) and related to a bad prognosis. Thus, finding biomarkers is important for the therapy of KICH.

METHODS

The UCSC was used for determining the expression of mRNA and miRNA and clinical data in KICH and normal samples. KEGG and GO were used for predicting potential function of differently expressed genes (DEGs). Optimal prognostic markers were determined by Lasso regression. Kaplan-Meier survival, ROC, and cox regression were used for assessing prognosis value. GSEA was used for predicting potential function of markers. The relations between markers and immune cell infiltration were determined by Pearson method. The upstream miRNA of markers was predicted in TargetScan and DIANA.

RESULTS

The 6162 upregulated and 13,903 downregulated DEGs were identified in KICH. Further CENPE and LDHA were screened out as optimal prognostic risk signatures. CENPE was highly expressed while LDHA was lowly expressed in KICH samples, and the high expressions of 2 genes contributed to bad prognosis. The functions of CENPE and LDHA were mainly enriched in proliferation related pathways such as cell cycle and DNA replication. In addition, the correlation of 2 genes with immune infiltrates in KICH was also observed. Finally, we found that has-miR-577 was the common upstream of 2 genes and the binding sites can be predicted.

CONCLUSION

CENPE and LDHA were identified as the important prognostic biomarkers in KICH, and they might be involved in the proliferation of cancer cell.

Identification of anoikis-related subtypes and immune landscape in kidney renal clear cell carcinoma

Anoikis is a specific form of programmed cell death induced by the loss of cell contact with the extracellular matrix and other cells, and plays an important role in organism development, tissue homeostasis, disease development and tumor metastasis. We comprehensively investigated the expression patterns of anoikis-related genes (ARGs) in kidney renal clear cell carcinoma (KIRC) from public databases. Anoikis-related prognostic signatures were established based on four ARGs expression, in which KIRC patients were assigned different risk scores and divided into two different risk groups. In addition, four ARGs expression was validated by qRT-PCR. A better prognosis was observed in the low-risk group, but with lower immune activity (including immune cells and immune-related functions) in the tumor microenvironment. Combined with the relevant clinical characteristics, a nomogram for clinical application was established. Receiver operating characteristics (ROC) and calibration curves were constructed to demonstrate the predictive power of this risk signature. In addition, higher risk scores were significantly and positively correlated with higher gene expression of tumor mutation load (TMB), immune checkpoints (ICPs) and mismatch repair (MMR)-related proteins in general. The results also suggested that the high-risk group was more sensitive to immunotherapy and certain chemotherapeutic agents. Anoikis-related prognostic signatures may provide a better understanding of the roles of ARGs and offer new perspectives for clinical prognosis and individualized treatment.

Identification of pyroptosis-related subtypes and comprehensive analysis of characteristics of the tumor microenvironment infiltration in clear cell renal cell carcinoma

Pyroptosis is a kind of programmed cell death triggered by the inflammasome. Growing evidence has revealed the crucial utility of pyroptosis in tumors. However, the potential mechanism of pyroptosis in clear cell renal cell carcinoma (ccRCC) is still unclear. In this research, we systematically analyze the genetic and transcriptional alterations of pyroptosis-related genes (PRGs) in ccRCC, identify pyroptosis-related subtypes, analyze the clinical and microenvironmental differences among different subtypes, develop a corresponding prognostic model to predict the prognosis of patients, and interpret the effect of pyroptosis on ccRCC microenvironment. This study provides a new perspective for a comprehensive understanding of the role of pyroptosis in ccRCC and its impact on the immune microenvironment, and a reliable scoring system was established to predict patients' prognosis.

m1A Regulatory gene signatures are associated with certain immune cell compositions of the tumor microenvironment and predict survival in kidney renal clear cell carcinoma

Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.

HMGCS2 serves as a potential biomarker for inhibition of renal clear cell carcinoma growth

3-Hydroxymethylglutaryl-CoA synthase 2 (HMGCS2) is the rate-limiting enzyme for ketone body synthesis, and most current studies focus on mitochondrial maturation and metabolic reprogramming. The role of HMGCS2 was evaluated in a pan-cancer multi-database using R language, and HMGCS2 was lowly expressed or not differentially expressed in all tumor tissues compared with normal tissues. Correlation analysis of clinical case characteristics, genomic heterogeneity, tumor stemness, and overall survival revealed that HMGCS2 is closely related to clear cell renal cell carcinoma (KIRC). Single-cell sequencing data from normal human kidneys revealed that HMGCS2 is specifically expressed in proximal tubular cells of normal adults. In addition, HMGCS2 is associated with tumor immune infiltration and microenvironment, and KIRC patients with low expression of HMGCS2 have worse prognosis. Finally, the results of cell counting kit 8 assays, colony formation assays, flow cytometry, and Western blot analysis suggested that upregulation of HMGCS2 increased the expression of key tumor suppressor proteins, inhibited the proliferation of clear cell renal cell carcinoma cells and promoted cell apoptosis. In conclusion, HMGCS2 is abnormally expressed in pan-cancer, may play an important role in anti-tumor immunity, and is expected to be a potential tumor prognostic marker, especially in clear cell renal cell carcinoma.

Cancer Stem Cells in Renal Cell Carcinoma: Origins and Biomarkers

The term "cancer stem cell" (CSC) refers to a cancer cell with the following features: clonogenic ability, the expression of stem cell markers, differentiation into cells of different lineages, growth in nonadhesive spheroids, and the in vivo ability to generate serially transplantable tumors that reflect the heterogeneity of primary cancers (tumorigenicity). According to this model, CSCs may arise from normal stem cells, progenitor cells, and/or differentiated cells because of striking genetic/epigenetic mutations or from the fusion of tissue-specific stem cells with circulating bone marrow stem cells (BMSCs). CSCs use signaling pathways similar to those controlling cell fate during early embryogenesis (Notch, Wnt, Hedgehog, bone morphogenetic proteins (BMPs), fibroblast growth factors, leukemia inhibitory factor, and transforming growth factor-β). Recent studies identified a subpopulation of CD133+/CD24+ cells from ccRCC specimens that displayed self-renewal ability and clonogenic multipotency. The development of agents targeting CSC signaling-specific pathways and not only surface proteins may ultimately become of utmost importance for patients with RCC.

Multi-omics analysis uncovers clinical, immunological, and pharmacogenomic implications of cuproptosis in clear cell renal cell carcinoma

OBJECTIVE

The latest research proposed a novel copper-dependent programmed cell death named cuproptosis. We aimed to elucidate the influence of cuproptosis in clear cell renal cell carcinoma (ccRCC) from a multi-omic perspective.

METHODS

This study systematically assessed mRNA expression, methylation, and genetic alterations of cuproptosis genes in TCGA ccRCC samples. Through unsupervised clustering analysis, the samples were classified as different cuproptosis subtypes, which were verified through NTP method in the E-MTAB-1980 dataset. Next, the cuproptosis score (Cuscore) was computed based on cuproptosis-related genes via PCA. We also evaluated clinical and immunogenomic features, drug sensitivity, immunotherapeutic response, and post-transcriptional regulation.

RESULTS

Cuproptosis genes presented multi-layer alterations in ccRCC, and were linked with patients' survival and immune microenvironment. We defined three cuproptosis subtypes [C1 (moderate cuproptosis), C2 (low cuproptosis), and C3 (high cuproptosis)], and the robustness and reproducibility of this classification was further proven. Overall survival was best in C3, moderate in C1, and worst in C2. C1 had the highest sensitivity to pazopanib, and sorafenib, while C2 was most sensitive to sunitinib. Furthermore, C1 patients benefited more from anti-PD-1 immunotherapy. Patients with high Cuscore presented the notable survival advantage. Cuscore was highly linked with immunogenomic features, and post-transcriptional events that contributed to ccRCC development. Finally, several potential compounds and druggable targets (NMU, RARRES1) were selected for low Cuscore group.

CONCLUSION

Overall, our study revealed the non-negligible role of cuproptosis in ccRCC development. Evaluation of the cuproptosis subtypes improves our cognition of immunogenomic features and better guides personalized prognostication and precision therapy.

Reprogramming of lipid metabolism in hepatocellular carcinoma resulting in downregulation of phosphatidylcholines used as potential markers for diagnosis and prediction

BACKGROUND

Aberrant methylation and metabolic perturbations may deepen our understanding of hepatocarcinogenesis and help identify novel biomarkers for diagnosing hepatocellular carcinoma (HCC). We aimed to develop an HCC model based on a multi-omics.

RESEARCH DESIGN AND METHODS

Four hundred patient samples (200 with HCC and 200 with hepatitis B virus-related liver disease (HBVLD)) were subjected to liquid chromatography-mass spectrometry and multiplex bisulfite sequencing. Integrative analysis of clinical data, CpG data, and metabolome for the 20 complete imputation datasets within a for-loopwas used to identify biomarker.

RESULTS

Totally, 1,140 metabolites were annotated, of which 125 were differentially expressed. Lipid metabolism reprogramming in HCC, resulting in phosphatidylcholines (PC) significantly downregulated, partly due to the altered mitochondrial beta-oxidation of fatty acids with diverse chain lengths. Age, sex, serum-fetoprotein levels, cg05166871,cg14171514, cg18772205, PC (O-16:0/20:3(8Z, 11Z, 14Z)), and PC (16:1(9Z)/P-18:0) were used to develop the HCC model. The model presented a good diagnostic and an acceptable predictive performance. The cumulative incidence of HCC in low- and high-risk groups of HBVLD patients were 1.19% and 21.40%, respectively (p = 0.0039).

CONCLUSIONS

PCs serve as potential plasma biomarkers and help identify patients with HBVLD at risk of HCC who should be screened for early diagnosis and intervention.

Cellular and Molecular Players in the Tumor Microenvironment of Renal Cell Carcinoma

Globally, clear-cell renal cell carcinoma (ccRCC) represents the most prevalent type of kidney cancer. Surgery plays a key role in the treatment of this cancer, although one third of patients are diagnosed with metastatic ccRCC and about 25% of patients will develop a recurrence after nephrectomy with curative intent. Molecular-target-based agents, such as tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), are recommended for advanced cancers. In addition to cancer cells, the tumor microenvironment (TME) includes non-malignant cell types embedded in an altered extracellular matrix (ECM). The evidence confirms that interactions among cancer cells and TME elements exist and are thought to play crucial roles in the development of cancer, making them promising therapeutic targets. In the TME, an unfavorable pH, waste product accumulation, and competition for nutrients between cancer and immune cells may be regarded as further possible mechanisms of immune escape. To enhance immunotherapies and reduce resistance, it is crucial first to understand how the immune cells work and interact with cancer and other cancer-associated cells in such a complex tumor microenvironment.

Aldolase B attenuates clear cell renal cell carcinoma progression by inhibiting CtBP2

Aldolase B (ALDOB), a glycolytic enzyme, is uniformly depleted in clear cell renal cell carcinoma (ccRCC) tissues. We previously showed that ALDOB inhibited proliferation through a mechanism independent of its enzymatic activity in ccRCC, but the mechanism was not unequivocally identified. We showed that the corepressor C-terminal-binding protein 2 (CtBP2) is a novel ALDOB-interacting protein in ccRCC. The CtBP2-to-ALDOB expression ratio in clinical samples was correlated with the expression of CtBP2 target genes and was associated with shorter survival. ALDOB inhibited CtBP2-mediated repression of multiple cell cycle inhibitor, proapoptotic, and epithelial marker genes. Furthermore, ALDOB overexpression decreased the proliferation and migration of ccRCC cells in an ALDOB-CtBP2 interaction-dependent manner. Mechanistically, our findings showed that ALDOB recruited acireductone dioxygenase 1, which catalyzes the synthesis of an endogenous inhibitor of CtBP2, 4-methylthio 2-oxobutyric acid. ALDOB functions as a scaffold to bring acireductone dioxygenase and CtBP2 in close proximity to potentiate acireductone dioxygenase-mediated inhibition of CtBP2, and this scaffolding effect was independent of ALDOB enzymatic activity. Moreover, increased ALDOB expression inhibited tumor growth in a xenograft model and decreased lung metastasis in vivo. Our findings reveal that ALDOB is a negative regulator of CtBP2 and inhibits tumor growth and metastasis in ccRCC.

Comprehensive Analysis of the Roles of Fatty Acid Transport Related Proteins in Clear Cell Renal Cell Carcinoma

OBJECTIVE

This study aimed to explore the clinical significance of fatty acid transport-related protein (FATRP) in patients with clear cell renal cell carcinoma(ccRCC).

METHODS

RNA-seq data and corresponding clinical data of ccRCC were obtained from TCGA data portal. Seventeen key FATRP genes were comprehensively investigated using bioinformatics approaches to systematically investigate their expression patterns in ccRCC. In addition, the correlation between the expression levels of these genes and clinicopathological features in ccRCC was further explored.

RESULTS

Among the 17 key FATRP genes, only FABP5, FABP6, and FABP7 could be regarded as ideal biomarkers for ccRCC, as they were highly expressed in ccRCC tumor tissues, and positively correlates with tumor progression and poor prognosis. FABP6 had the highest copy number variations (CNV) events (63.07%), and ccRCC patients with FABP6 amplification had a better prognosis than the unaltered group. DNA methylation levels of FABP6 and FABP7 were downregulated in ccRCC tumor tissues compared to those in normal tissues. FABP5 showed the opposite results. Moreover, a novel four FATRP gene (FABP1, FABP5, FABP7, FATP2) and three clinical parameter (age, stage, and grade) prediction model was constructed and that comprised a significant independent prognostic signature.

CONCLUSIONS

Only a few FATRP genes are upregulated in ccRCC tumor tissue, and positively correlate with tumor progression and poor prognosis. The accuracy of a single gene of these FATRP genes as predictors of progression and prognosis of ccRCC is limited. The performance of the novel prediction model proposed by this study was much better than that of any single gene.

Immune Checkpoint Inhibitors in Renal Cell Carcinoma: Molecular Basis and Rationale for Their Use in Clinical Practice

Renal cell carcinoma (RCC) is the seventh most common cancer in men and the ninth most common cancer in women worldwide. There is plenty of evidence about the role of the immune system in surveillance against tumors. Thanks to a better understanding of immunosurveillance mechanisms, immunotherapy has been introduced as a promising cancer treatment in recent years. Renal cell carcinoma (RCC) has long been thought chemoresistant but highly immunogenic. Considering that up to 30% of the patients present metastatic disease at diagnosis, and around 20–30% of patients undergoing surgery will suffer recurrence, we need to identify novel therapeutic targets. The introduction of immune checkpoint inhibitors (ICIs) in the clinical management of RCC has revolutionized the therapeutic approach against this tumor. Several clinical trials have shown that therapy with ICIs in combination or ICIs and the tyrosine kinase inhibitor has a very good response rate. In this review article we summarize the mechanisms of immunity modulation and immune checkpoints in RCC and discuss the potential therapeutic strategies in renal cancer treatment.

Endoplasmic Reticulum Stress in Renal Cell Carcinoma

The endoplasmic reticulum is an organelle exerting crucial functions in protein production, metabolism homeostasis and cell signaling. Endoplasmic reticulum stress occurs when cells are damaged and the capacity of this organelle to perform its normal functions is reduced. Subsequently, specific signaling cascades, together forming the so-called unfolded protein response, are activated and deeply impact cell fate. In normal renal cells, these molecular pathways strive to either resolve cell injury or activate cell death, depending on the extent of cell damage. Therefore, the activation of the endoplasmic reticulum stress pathway was suggested as an interesting therapeutic strategy for pathologies such as cancer. However, renal cancer cells are known to hijack these stress mechanisms and exploit them to their advantage in order to promote their survival through rewiring of their metabolism, activation of oxidative stress responses, autophagy, inhibition of apoptosis and senescence. Recent data strongly suggest that a certain threshold of endoplasmic reticulum stress activation needs to be attained in cancer cells in order to shift endoplasmic reticulum stress responses from a pro-survival to a pro-apoptotic outcome. Several endoplasmic reticulum stress pharmacological modulators of interest for therapeutic purposes are already available, but only a handful were tested in the case of renal carcinoma, and their effects in an in vivo setting remain poorly known. This review discusses the relevance of endoplasmic reticulum stress activation or suppression in renal cancer cell progression and the therapeutic potential of targeting this cellular process for this cancer.

MUC1 Expression Affects the Immunoflogosis in Renal Cell Carcinoma Microenvironment through Complement System Activation and Immune Infiltrate Modulation

Mucin1 (MUC1), a glycoprotein associated with an aggressive cancer phenotype and chemoresistance, is aberrantly overexpressed in a subset of clear cell renal cell carcinoma (ccRCC). Recent studies suggest that MUC1 plays a role in modulating cancer cell metabolism, but its role in regulating immunoflogosis in the tumor microenvironment remains poorly understood. In a previous study, we showed that pentraxin-3 (PTX3) can affect the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system (C1q) and releasing proangiogenic factors (C3a, C5a). In this scenario, we evaluated the PTX3 expression and analyzed the potential role of complement system activation on tumor site and immune microenvironment modulation, stratifying samples in tumors with high (MUC1H) versus tumors with low MUC1 expression (MUC1L). We found that PTX3 tissue expression was significantly higher in MUC1H ccRCC. In addition, C1q deposition and the expressions of CD59, C3aR, and C5aR were extensively present in MUC1H ccRCC tissue samples and colocalized with PTX3. Finally, MUC1 expression was associated with an increased number of infiltrating mast cells, M2-macrophage, and IDO1+ cells, and a reduced number of CD8+ T cells. Taken together, our results suggest that expression of MUC1 can modulate the immunoflogosis in the ccRCC microenvironment by activating the classical pathway of the complement system and regulating the immune infiltrate, promoting an immune-silent microenvironment.

Lipids as Targets for Renal Cell Carcinoma Therapy

Kidney cancer is among the top ten most common cancers to date. Within the kidney, renal cell carcinoma (RCC) is the most common solid lesion occurring. While various risk factors are suspected, including unhealthy lifestyle, age, and ethnicity, genetic mutations seem to be a key risk factor. In particular, mutations in the von Hippel-Lindau gene (Vhl) have attracted a lot of interest since this gene regulates the hypoxia inducible transcription factors HIF-1α and HIF-2α, which in turn drive the transcription of many genes that are important for renal cancer growth and progression, including genes involved in lipid metabolism and signaling. Recent data suggest that HIF-1/2 are themselves regulated by bioactive lipids which make the connection between lipids and renal cancer obvious. This review will summarize the effects and contributions of the different classes of bioactive lipids, including sphingolipids, glycosphingolipids, eicosanoids, free fatty acids, cannabinoids, and cholesterol to renal carcinoma progression. Novel pharmacological strategies interfering with lipid signaling to treat renal cancer will be highlighted.

Renal Cell Carcinoma as a Metabolic Disease: An Update on Main Pathways, Potential Biomarkers, and Therapeutic Targets

Clear cell renal cell carcinoma (ccRCC) is the most frequent histological kidney cancer subtype. Over the last decade, significant progress has been made in identifying the genetic and metabolic alterations driving ccRCC development. In particular, an integrated approach using transcriptomics, metabolomics, and lipidomics has led to a better understanding of ccRCC as a metabolic disease. The metabolic profiling of this cancer could help define and predict its behavior in terms of aggressiveness, prognosis, and therapeutic responsiveness, and would be an innovative strategy for choosing the optimal therapy for a specific patient. This review article describes the current state-of-the-art in research on ccRCC metabolic pathways and potential therapeutic applications. In addition, the clinical implication of pharmacometabolomic intervention is analyzed, which represents a new field for novel stage-related and patient-tailored strategies according to the specific susceptibility to new classes of drugs.

Contemporary Clinical Definitions, Differential Diagnosis, and Novel Predictive Tools for Renal Cell Carcinoma

Despite significant progress regarding clinical detection/imaging evaluation modalities and genetic/molecular characterization of pathogenesis, advanced renal cell carcinoma (RCC) remains an incurable disease and overall RCC mortality has been steadily rising for decades. Concomitantly, clinical definitions have been greatly nuanced and refined. RCCs are currently viewed as a heterogeneous series of cancers, with the same anatomical origin, but fundamentally different metabolisms and clinical behaviors. Thus, RCC pathological diagnosis/subtyping guidelines have become increasingly intricate and cumbersome, routinely requiring ancillary studies, mainly immunohistochemistry. Meanwhile, RCC-associated-antigen targeted systemic therapy has been greatly diversified and emerging, novel clinical applications for RCC immunotherapy have already reported significant survival benefits, at least in the adjuvant setting. Even so, systemically disseminated RCCs still associate very poor clinical outcomes, with currently available therapeutic modalities only being able to prolong survival. In lack of a definitive cure for advanced RCCs, integration of the amounting scientific knowledge regarding RCC pathogenesis into RCC clinical management has been paramount for improving patient outcomes. The current review aims to offer an integrative perspective regarding contemporary RCC clinical definitions, proper RCC clinical work-up at initial diagnosis (semiology and multimodal imaging), RCC pathological evaluation, differential diagnosis/subtyping protocols, and novel clinical tools for RCC screening, risk stratification and therapeutic response prediction.

MUC1 Tissue Expression and Its Soluble Form CA15-3 Identify a Clear Cell Renal Cell Carcinoma with Distinct Metabolic Profile and Poor Clinical Outcome

An altered metabolism is involved in the development of clear cell renal carcinoma (ccRCC). MUC1 overexpression has been found to be associated with advanced disease and poor prognosis. In this study, we evaluated the metabolomic profile of human ccRCC, according to MUC1 expression, and integrated it with transcriptomic data. Moreover, we analyzed the role of MUC1 in sustaining ccRCC aggressiveness and the prognostic value of its soluble form CA15-3. Integrated metabolomic and transcriptomic analysis showed that MUC1-expressing ccRCC was characterized by metabolic reprogramming involving the glucose and lipid metabolism pathway. In addition, primary renal cancer cells treated with a small interfering RNA targeting MUC1 (siMUC1) migrated and proliferated at a slower rate than untreated cancer cells. After cisplatin treatment, the death rate of cancer cells treated with siMUC1 was significantly greater than that of untreated cells. Kaplan-Meier curves showed significant differences in CSS and PFS among groups of patients with high versus low levels of CA15-3. In a multivariate analysis, CA15-3 was an independent adverse prognostic factor for cancer-specific and progression-free survival. In conclusion, MUC1 expressing ccRCC is characterized by a particular metabolic reprogramming. The inhibition of MUC1 expression decreases cell motility and viability and improves cisplatin susceptibility, suggesting that this pathway can regulate de novo chemotherapy resistance in ccRCC.

Molecular signature of renal cell carcinoma by means of a multiplatform metabolomics analysis

Renal cell carcinoma (RCC) is a disease with no specific diagnostic method or treatment. Thus, the evaluation of novel diagnostic tools or treatment possibilities is essential. In this study, a multiplatform untargeted metabolomics analysis of urine was applied to search for a metabolic pattern specific for RCC, which could enable comprehensive assessment of its biochemical background. Thirty patients with diagnosed RCC and 29 healthy volunteers were involved in the first stage of the study. Initially, the utility of the application of the selected approach was checked for RCC with no differentiation for cancer subtypes. In the second stage, this approach was used to study clear cell renal cell carcinoma (ccRCC) in 38 ccRCC patients and 38 healthy volunteers. Three complementary analytical platforms were used: reversed-phase liquid chromatography coupled with time-of-flight mass spectrometry (RP-HPLC-TOF/MS), capillary electrophoresis coupled with time-of-flight mass spectrometry (CE-TOF/MS), and gas chromatography triple quadrupole mass spectrometry (GC-QqQ/MS). As a result of urine sample analyses, two panels of metabolites specific for RCC and ccRCC were selected. Disruptions in amino acid, lipid, purine, and pyrimidine metabolism, the TCA cycle and energetic processes were observed. The most interesting differences were observed for modified nucleosides. This is the first time that the levels of these compounds were found to be changed in RCC and ccRCC patients, providing a framework for further studies. Moreover, the application of the CE-MS technique enabled the determination of statistically significant changes in symmetric dimethylarginine (SDMA) in RCC.

•

Multiplatform untargeted metabolomics analysis was applied for selection of tentative diagnostic indicators of RCC.

•

LC-MS, GC-MS and CE-MS techniques were utilized for analysis of urine samples collected from RCC and ccRCC patients.

•

Alterations in amino acid, purine, and pyrimidine metabolism, as well as TCA cycle and energy processes, were observed.

Prognostic nutritional index as a prognostic factor for renal cell carcinoma: A systematic review and meta-analysis

Background

Prognostic nutritional index (PNI) is a simple parameter which reflects patient’s nutritional and inflammatory status and reported as a prognostic factor for renal cell carcinoma (RCC). Studies were included from database inception until February 2, 2022. The aim of this study is to evaluate prognostic value of PNI by meta-analysis of the diagnostic test accuracy in RCC.

Methods and findings

Studies were retrieved from PubMed, Cochrane, and EMBASE databases and assessed sensitivity, specificity, summary receiver operating characteristic curve (SROC) and area under curve (AUC). Totally, we identified 11 studies with a total of 7,296 patients were included to evaluate the prognostic value of PNI in RCC finally. They indicated a pooled sensitivity of 0.733 (95% CI, 0.651–0.802), specificity of 0.615 (95% CI, 0.528–0.695), diagnostic odds ratio (DOR) of 4.382 (95% CI, 3.148–6.101) and AUC of 0.72 (95% CI, 0.68–0.76). Heterogeneity was significant and univariate meta-regression revealed that metastasis and cut-off value of PNI might be the potential source of heterogeneity. Multivariate meta-regression analysis also demonstrated that metastasis might be the source of heterogeneity.

Conclusions

PNI demonstrated a good diagnostic accuracy as a prognostic factor for RCC and especially in case of metastatic RCC.

Methylation of PCDH17 and NEFH as prognostic biomarker for nonmetastatic RCC: A cohort study

DNA methylation makes up a main part of the molecular mechanism of cancer evolution and has shown promising results in the prognosis of renal cell cancer (RCC). In this study, we investigated the possible association of promoter methylation of PCDH17, NEFH, RASSF1A, and FHIT, genes with the prognosis of nonmetastatic RCC patients. Cancerous and normal adjacent tissues from surgical specimens of 41 patients with long follow-up were treated for DNA isolation and bisulfite conversion. The gene promoter methylation was determined with quantitative methylation-specific PCR (qMSP). Wilcoxon signed-rank test was used for paired methylation comparisons, while univariate linear regression and Mann-Whitney test were applied for associating methylation status with clinical and disease characteristics. Cox regression proportional hazards models and Kaplan-Meier plots were used for survival analyses in reference to methylation status. Paired comparisons showed tissue-specific hypermethylation for PCDH17 (P < .001), NEFH (P < .001), RASSF1A (P = .032), while a positive association of methylation in normal tissues with age was demonstrated for PCDH17 (P < .001), RASSF1A (P < .001), FHIT (P < .001). PCDH17 was more methylated in cases with clear cell RCC (P = .015) and high-grade tumor (P = .013), while NEFH methylation was higher in locally advanced cases (P = .032). PCDH17 hypermethylation in cancerous and normal tissues was linked to shorter disease-specific survival (DSS, P = .026, P = .004), disease-free survival (DFS, P = .004, P = .019) while NEFH hypermethylation in cancerous tissues was related to shorter DSS (P = .032). Increased methylation difference of NEFH was also associated with shorter DSS (P = .041) and DFS (P = .020), while the corresponding parameter for PCDH17 was associated with poor DFS (P = .014). Kaplan-Meier curves for hypermethylation in cancer tissues demonstrated different clinical courses for PCDH17 (P = .017), NEFH (P = .023) regarding DSS, and PCDH17 (P = .001) regarding DFS. Our study not only highlights the prognostic value of promoter methylation of PCDH17 and NEFH in cancer tissues but also is the first report of the prognostic value of methylation alterations in normal tissues. Our findings are the first report of the prognostic value of methylation alterations in normal tissues, which can contribute to improved assessment of recurrence risk.

GRAMD1A Is a Biomarker of Kidney Renal Clear Cell Carcinoma and Is Associated with Immune Infiltration in the Tumour Microenvironment

Background

GRAM structural domain-containing protein 1A (GRAMD1A) is upregulated in a variety of human cancer tissues and is closely associated with tumourigenesis and progression.

Methods

Patient RNA-sequencing data and clinicopathological information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The expression of GRAMD1A in kidney cancer cell lines and KIRC patients was analysed by quantitative polymerase chain reaction (qPCR). Receiver Operator Characteristic (ROC) curves, nomograms, Kaplan-Meier analysis, forest plots, and COX analysis were used to assess the diagnostic and prognostic value of GRAMD1A in KIRC, and gene set enrichment analysis (GSEA) was used to explore its potential signalling pathways. In addition, the Sangerbox website, Kaplan-Meier plotter database, and TISIDB and TIMER databases were used to further analyse the correlation of GRAMD1A with microsatellite instability (MSI), tumour mutational burden (TMB), immune checkpoint genes, and tumour-infiltrating lymphocytes (TILs).

Results

GRAMD1A was significantly highly expressed in KIRC and associated with shorter overall survival and relapse-free survival (P < 0.05). The AUC value of the ROC curve to identify KIRC and normal renal tissues was 0.942. Forest plot and COX analysis visualized that GRAMD1A could be an independent prognostic factor in KIRC patients (P < 0.01), and nomograms to determine the overall survival (OS) of KIRC patients also showed good efficacy (C-index: 0.776). Moreover, Spearman correlation analysis showed a positive correlation between GRAMD1A and MSI, TMB (P < 0.01). On the other hand, GRAMD1A was also found to be closely associated with immune checkpoint genes. Meanwhile, patients with KIRC with high GRAMD1A expression had a relatively low hazard ratio (HR) of death when B lymphocytes, natural killer T cells, CD4+ T lymphocytes, CD8+ T lymphocytes, and macrophages were enriched in the tumour microenvironment (TME), and a greater HR of death when regulatory T lymphocytes with tumour-specific immunosuppressive effects were significantly enriched. Last, GSEA shows that GRAMD1A is closely associated with the regulation of energy metabolism in KIRC.

Conclusions

GRAMD1A is a promising diagnostic and prognostic biomarker for patients with KIRC, and its biological function correlates to some extent with immune infiltration in TME.

Precision Medicine: An Optimal Approach to Patient Care in Renal Cell Carcinoma

Renal cell cancer (RCC) is a heterogeneous tumor that shows both intra- and inter-heterogeneity. Heterogeneity is displayed not only in different patients but also among RCC cells in the same tumor, which makes treatment difficult because of varying degrees of responses generated in RCC heterogeneous tumor cells even with targeted treatment. In that context, precision medicine (PM), in terms of individualized treatment catered for a specific patient or groups of patients, can shift the paradigm of treatment in the clinical management of RCC. Recent progress in the biochemical, molecular, and histological characteristics of RCC has thrown light on many deregulated pathways involved in the pathogenesis of RCC. As PM-based therapies are rapidly evolving and few are already in current clinical practice in oncology, one can expect that PM will expand its way toward the robust treatment of patients with RCC. This article provides a comprehensive background on recent strategies and breakthroughs of PM in oncology and provides an overview of the potential applicability of PM in RCC. The article also highlights the drawbacks of PM and provides a holistic approach that goes beyond the involvement of clinicians and encompasses appropriate legislative and administrative care imparted by the healthcare system and insurance providers. It is anticipated that combined efforts from all sectors involved will make PM accessible to RCC and other patients with cancer, making a tremendous positive leap on individualized treatment strategies. This will subsequently enhance the quality of life of patients.

Expression of GOT2 Is Epigenetically Regulated by DNA Methylation and Correlates with Immune Infiltrates in Clear-Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (KIRC) is the most common and highly malignant pathological type of kidney cancer, characterized by a profound metabolism dysregulation. As part of aspartate biosynthesis, mitochondrial GOT2 (glutamic-oxaloacetic transaminase 2) is essential for regulating cellular energy production and biosynthesis, linking multiple pathways. Nevertheless, the expression profile and prognostic significance of GOT2 in KIRC remain unclear. This study comprehensively analyzed the transcriptional levels, epigenetic regulation, correlation with immune infiltration, and prognosis of GOT2 in KIRC using rigorous bioinformatics analysis. We discovered that the expression levels of both mRNA and protein of GOT2 were remarkably decreased in KIRC tissues in comparison with normal tissues and were also significantly related to the clinical features and prognosis of KIRC. Remarkably, low GOT2 expression was positively associated with poorer overall survival (OS) and disease-free survival (DFS). Further analysis revealed that GOT2 downregulation is driven by DNA methylation in the promoter-related CpG islands. Finally, we also shed light on the influence of GOT2 expression in immune cell infiltration, suggesting that GOT2 may be a potential prognostic marker and therapeutic target for KIRC patients.

Overexpression CPT1A reduces lipid accumulation via PPARα/CD36 axis to suppress the cell proliferation in ccRCC

Clear cell renal carcinoma (ccRCC) is histologically defined by its cytoplasmic lipid deposits. Lipid metabolism disorder largely increases the risk of ccRCC. In this study, we aimed to investigate the biological functions and molecular mechanisms of carnitine palmitoyl transferase 1A (CPT1A) in ccRCC. Our results showed that CPT1A is decreased in ccRCC clinical samples and cell lines compared with that in normal samples. Lentivirus overexpressing CPT1A was used to investigate the neoplastic phenotypes of ccRCC, and the results showed that lipid accumulation and tumor growth are attenuated both and . In addition, CPT1A prevents cholesterol uptake and lipid accumulation by increasing the peroxisome proliferator-activated receptor α (PPARα) level through regulation of Class B scavenger receptor type 1 (SRB1) and cluster of differentiation 36 (CD36). Furthermore, PI3K/Akt signaling pathway promotes tumor cell proliferation in ccRCC, which is related to the enhanced expression of CD36. Functionally, weakened CPT1A expression is critical for lipid accumulation to promote ccRCC development. Collectively, our research unveiled a novel function of CPT1A in lipid metabolism via PPARα/CD36 axis, which provides a new theoretical explanation for the pathogenesis of ccRCC. Targeting CPT1A may be a potential therapeutic strategy to treat ccRCC.

Urine-Based Metabolomics and Machine Learning Reveals Metabolites Associated with Renal Cell Carcinoma Stage

Urine metabolomics profiling has potential for non-invasive RCC staging, in addition to providing metabolic insights into disease progression. In this study, we utilized liquid chromatography-mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and machine learning (ML) for the discovery of urine metabolites associated with RCC progression. Two machine learning questions were posed in the study: Binary classification into early RCC (stage I and II) and advanced RCC stages (stage III and IV), and RCC tumor size estimation through regression analysis. A total of 82 RCC patients with known tumor size and metabolomic measurements were used for the regression task, and 70 RCC patients with complete tumor-nodes-metastasis (TNM) staging information were used for the classification tasks under ten-fold cross-validation conditions. A voting ensemble regression model consisting of elastic net, ridge, and support vector regressor predicted RCC tumor size with a R² value of 0.58. A voting classifier model consisting of random forest, support vector machines, logistic regression, and adaptive boosting yielded an AUC of 0.96 and an accuracy of 87%. Some identified metabolites associated with renal cell carcinoma progression included 4-guanidinobutanoic acid, 7-aminomethyl-7-carbaguanine, 3-hydroxyanthranilic acid, lysyl-glycine, glycine, citrate, and pyruvate. Overall, we identified a urine metabolic phenotype associated with renal cell carcinoma stage, exploring the promise of a urine-based metabolomic assay for staging this disease.

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.