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

The percentage abundance of sarcomatoid component has a prognostic role in grade 4 non-metastatic clear cell-renal carcinoma

PURPOSE

Sarcomatoid dedifferentiation represents one of the most aggressive features of clear cell renal cell carcinoma (ccRCC). In this study we evaluated whether grade 4-ccRCC subclassification based on the intratumoral abundance of sarcomatoid features could have a prognostic impact.

METHODS

A cohort of 212 patients with localized or locally advanced sarcomatoid ccRCC was identified. This population was stratified according to abundance of sarcomatoid features in low-sarcomatoid (LS = < 20% sarcomatoid component; n = 117) and high-sarcomatoid (HS = ≥ 20% sarcomatoid component; n = 95). Estimates of cancer-specific survival (CSS) and recurrence-free survival (RFS) were calculated according to the Kaplan-Meier method and compared with the log-rank test. Multivariable analysis was performed using the Cox proportional hazards regression model to identify the most significant variables for predicting CSS and RFS.

RESULTS

Kaplan-Meier survival curves stratified by abundance of sarcomatoid component, showed that CSS and RFS were significantly decreased in patients with sarcomatoid component ≥ 20% (both P < 0.0001). At multivariable analysis by Cox regression modeling, the abundance of sarcomatoid component was an independent adverse prognostic factor for CSS (P < 0.0001) and RFS (P < 0.0001).

CONCLUSION

ccRCC Subclassification based on the abundance of intratumoral sarcomatoid component has a clinical significance. Our study showed that ccRCC subclassification into HS versus LS groups had a prognostic impact in terms of CSS and RFS in non-metastatic ccRCC.

Disulfidptosis, a novel regulated cell death to predict survival and therapeutic response in kidney renal clear cell carcinoma

BACKGROUND

Metabolic regulation of cell death has become a potential therapeutic target for kidney renal clear cell carcinoma (KIRC), which is distinguished by notable heterogeneity and significant immune infiltration. Disulfidptosis, a recently identified form of cell death, has gained prominence in antitumor immunity. This research aims to investigate the correlation between disulfidptosis and prognosis of KIRC, while also exploring the possibility of predicting therapeutic response by disulfidptosis-associated genes (DAGs).

METHODS

We sourced clinical data and RNA sequence of KIRC from the Cancer Genome Atlas Database. Employing unsupervised clustering based on 23 DAGs, we further identified key differentially expressed genes (DEGs) between clusters to construct a DAG prognostic signature. A nomogram was developed and validated to predict clinical outcome of KIRC. Finally, we examined immune cell infiltration, tumor mutational burden, immunotherapy response, and sensitivity to drugs in high and low-risk groups.

RESULTS

Two distinct KIRC patient clusters were successfully stratified using the 23-DAG-related prognostic signature, comprising 11 key genes. This resulted in a robust risk model with strong predictive accuracy for overall survival. The nomogram, incorporating DAG-based risk scores, age, and pM stage, exhibited excellent predictive performance. The high-risk group displayed increased immune cell infiltration and tumor mutational burden, while the low-risk group showed heightened sensitivity to immunotherapies and targeted treatments.

CONCLUSION

This study established a robust DAG-based risk model for KIRC, highlighting its significant correlation with the immune landscape and therapeutic responses. Novel disulfidptosis-related biomarkers revealed distinct immune profiles, drug sensitivities, and immunotherapy potentials among KIRC patients.

LPCAT3 regulates the immune infiltration and prognosis of ccRCC patients by mediating ferroptosis and endoplasmic reticulum stress

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) accounts for 70% of renal cell carcinoma (RCC) cases. Although surgery remains the mainstay treatment, renal injury and high metastasis rates after nephrectomy dramatically reduce patient quality of life. Drugs that stimulate the immune system by targeting checkpoint pathways improve overall survival in patients with RCC. Here, we investigated the applicability of lysophosphatidylcholine acyltransferase 3 (LPCAT3) as a target for immunotherapy.

METHODS

In the present study, high LPCAT3 expression in ccRCC was identified using The Cancer Genome Atlas (TCGA) data and validated in two external cohorts from the Gene Expression Omnibus (GEO) database. qRT-PCR was performed to identify the mRNA level of LPCAT3 in tumors and adjacent normal tissues. And immunohistochemistry was used to evaluate the protein level of LPCAT3 between two groups of samples. Furthermore, gene set enrichment analysis was performed to explore the biological processes and pathways related to LPCAT3 expression. Key gene expression and correlation analyses were performed to determine the crosstalk among LPCAT3 expression, ferroptosis, and endoplasmic reticulum stress (ERS). Subsequently, CIBERSORT was used to analyze the immune infiltration status of patients with high and low LPCAT3 expression.

RESULTS

TCGA and GEO data revealed that LPCAT3 expression in ccRCC tumor tissues was higher than that in adjacent normal tissues; moreover, patients with high LPCAT3 expression had better survival outcomes. qRT-PCR and immunohistochemistry verified the high LPCAT3 expression in tumor tissue. Pathways related to ferroptosis and ERS were upregulated in patients with high LPCAT3 expression. Univariate and multivariate regression analyses revealed that low LPCAT3 levels represent an independent risk factor for ccRCC. LPCAT3 expression was positively correlated with M2 macrophage infiltration levels but negatively correlated with the memory B cell, CD8+ T cell, follicular helper T cell, regulatory T cell, activated natural killer cell, and activated memory CD4+ T cell infiltration levels.

CONCLUSIONS

LPCAT3was identified as a ccRCC biomarker and may regulate immune infiltration and prognosis in ccRCC by mediating ferroptosis and ERS. Thus, it has potential for exploitation as a prognostic and immune therapeutic target for patients with ccRCC.

FADS1, a lipid metabolism-related diagnostic biomarker in KIRC

BACKGROUND

Kidney renal clear cell carcinoma (KIRC), the predominant subtype of renal cell carcinoma, poses significant health risks. The rapid progression and resistance to targeted therapies highlight the need for new tumor markers and therapeutic targets. FADS1, part of the fatty acid desaturase family, regulates fatty acid synthesis and participates in lipid metabolism. However, its role in KIRC is not well-studied.

METHODS

The study utilized bioinformatics analysis through the TCGA database and other platforms to identify FADS1 expression levels in KIRC. Twenty pairs of KIRC clinical tissue samples were used for qPCR verification. Meanwhile, eight pairs of KIRC clinical tissue samples were used for Western blot verification. Conduct statistical evaluation, including Wilcoxon rank sum test and Kaplan-Meier analysis, to explore the correlation between FADS1 expression and clinical pathological features and immune infiltration. In addition, in vitro experiments were conducted to confirm the biological function of FADS1.

RESULTS

The findings indicated that FADS1 is highly expressed in KIRC and contributes to tumor development. FADS1's role in lipid metabolism leads to lipid accumulation within tumor cells, which may influence the occurrence and progression of KIRC. TIMER analysis revealed a correlation between FADS1 expression and the infiltration levels of various immune cells, indicating its potential role in modulating immune characteristics.

CONCLUSION

FADS1 could serve as a prognostic biomarker associated with immunity in KIRC, highlighting its potential as a diagnostic and therapeutic target. The study underscores the importance of further research into FADS1's role in lipid metabolism and immune infiltration to develop effective therapeutic strategies.

Identification of ferroptosis-related gene signatures as a novel prognostic model for clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC), a common type of renal cortical tumor, is the most prevalent subtype of renal malignancies within the urinary system and is associated with a low survival rate. Ferroptosis plays a crucial role in the process of renal carcinogenesis and holds potential for significant applications in patient prognosis. However, the clinical prognostic relevance of ferroptosis-related genes (FRGs) for ccRCC remains unclear. The identification of FRG signatures and the development of a novel prognostic model based on FRGs demonstrate important prognostic significance for ccRCC.

METHODS

Univariate cox screen was performed to screen for prognostic-related genes using ccRCC data from the The Cancer Genome Atlas (TCGA) database. And then an initial screen for prognostic genes was performed by taking intersections with the differential genes of the Gene Expression Omnibus (GEO) database datasets GSE213324 and GSE66271, as well as with the FRGs, and a multigene signature was constructed using least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. Subsequently, the model was evaluated using Kaplan-Meier (KM) survival curve analysis, receiver operating characteristic (ROC), nomogram, and decision curve analysis (DCA). Differences in tumor microenvironment and immune function were analyzed by single-sample gene set enrichment analysis (ssGSEA) and immune infiltration in patients in the high- and low-risk groups. The tumor immune dysfunction and exclusion (TIDE) assessed the immune checkpoint inhibitor (ICI) susceptibility in patients. The Gene Set Enrichment Analysis (GSEA) was performed for pathway enrichment analysis. Patient mutation data were downloaded and tumor mutation burden (TMB) were compared between patients in the high- and low-risk groups.

RESULTS

ADACSB, DPEP1, KIF20A, MT1G, PVT1 and TIMP1 were utilized to establish a novel prognostic signature. The KM curve analysis revealed that patients in the high-risk group exhibited a poorer prognosis. Additionally, the ROC results demonstrated that the model displayed favorable prognostic accuracy. Independent prognostic analyses indicated that the FRGs model could serve as an independent prognostic indicator. Furthermore, calibration curve of the nomogram illustrated enhanced precision in predicting survival rates for patients at 1, 3 and 5 years. Analysis of mutation data unveiled higher tumor mutation load among patients in the high-risk group, which correlated with an increase in risk score.

CONCLUSION

The FRGs model offers a novel approach for prognostic prediction of ccRCC patients and has the potential to provide personalized prognostic prediction and treatment for ccRCC patients.

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.

Transcriptomic and proteo-metabolic determinants of the grading system in clear cell renal cell carcinoma

BACKGROUND

Pathological grade is a morphological parameter of clear cell-renal cell carcinoma (ccRCC) and an independent predictor of cancer-specific survival. The aim of this study was to identify grade-dependent metabolic signatures and corresponding gene and protein expression changes that connect variations in cancer metabolism with nuclear grade, especially in high-grade tumors.

METHODS

Forty ccRCC samples were collected and stratified according to nuclear grade: 23 low-grade (LG = G1-G2) and 17 high-grade (HG = G3-G4) samples. In addition, 122 patients with sarcomatoid ccRCC (sRCC) were classified according to the abundance of sarcomatoid features as low sarcomatoid (LS; sarcomatoid component<20%; n = 67) or high sarcomatoid (HS; sarcomatoid component≥20%; n = 55). Untargeted metabolomic analysis was performed. To study the relative changes in gene and protein expression in HG vs. LG ccRCC, data from 4 different datasets were downloaded and stratified according to nuclear grade. Immunohistochemistry and immunofluorescence were used to evaluate protein expression. Cancer-specific survival (CSS) and progression-free survival (PFS) were calculated using Kaplan-Meier analysis. Multivariate analysis was performed using a Cox regression model.

RESULTS

The Warburg effect, in association with changes in Krebs cycle intermediates and related metabolites, was more prominent in HG ccRCC than in LG ccRCC. Additional alterations included metabolic reprogramming in the urea cycle and modulation of glutathione metabolism with the accumulation of reduced glutathione and carnitine derivatives in HG tumors, while the concentrations of long- and medium-chain fatty acids were greater in LG ccRCC. CSS and PFS were significantly decreased in patients with HS tumors. According to the multivariate analysis, the abundance of the sarcomatoid component was an adverse prognostic factor.

CONCLUSIONS

ccRCC is characterized by a particular grade-dependent metabolic reprogramming. Metabolic pathways and associated molecular alterations are grade-specific and could represent potential therapeutic targets, especially in HG tumors. sRCC subclassification based on the abundance of sarcomatoid components into HS vs. LS tumors have prognostic value.

FUT10 is related to the poor prognosis and immune infiltration in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC), is highly metastatic with unfavorable oncologic outcomes. The metastatic dissemination and underlying mechanisms of ccRCC remain insufficiently understood. The expression of fucosyltransferases (FUTs) has been explored in multiple cancer types, which affect survival of tumor cells and oncology progress. However, the role of fucosyltransferase 10 (FUT10), a member of the FUT family, is still unclear in ccRCC. We aimed to investigate the effects of FUT10 on the prognosis and immune infiltration of ccRCC via The Cancer Genome Atlas (TCGA) database.

Methods

The relationship between FUT10 expression and clinical-pathologic features was evaluated by Welch's t-test, Wilcoxon signed-rank test, Dunn's test, and logistic regression based on TCGA datasets. The FUT10 expression level was converted into a categorical variable by receiver operating characteristic (ROC) and the area under the curve (AUC). The factors associated with the prognosis were determined by Kaplan-Meier method. The function of FUT10 was identified by functional enrichment analysis, gene set enrichment analysis (GSEA), gene correlation analysis, and immune infiltration analysis. At last, we verified the FUT10 messenger RNA (mRNA) expression in ccRCC and adjacent kidney tissues by quantitative real-time polymerase chain reaction (qRT-PCR).

Results

Downregulated FUT10 expression in ccRCC was associated with the clinical stage (P<0.001), T stage (P<0.001), M stage (P<0.001), and overall survival (OS) event (P<0.001). The ROC curve suggested that FUT10 had a certain accuracy in the diagnostic ability in ccRCC (AUC =0.787). It was shown that patient survival was prolonged in the FUT10 high-expression group. Meanwhile, multivariate analysis displayed that FUT10 was an independent risk factor for ccRCC patients (P=0.003). Moreover, we uncovered that FUT10 was involved in the phenotype of the immune response, oxidative phosphorylation (OXPHOS), arachidonic acid (AA) metabolism, and primary immunodeficiency (PID) by function enrichment analysis and GSEA. In addition, in the high FUT10 expression group, natural killer (NK) CD56bright cells exhibited lower enrichment scores, and central memory T cells exhibited higher enrichment scores. Especially, ARL8B, a key factor in NK-mediated cytotoxicity, had a certain correlation with FUT10 (r=0.590, P<0.001). Compared to the normal kidney tissues, the FUT10 mRNA expression in the ccRCC was decreased (P=0.004).

Conclusions

FUT10 might be a promising immune therapy target and prognostic biomarker in ccRCC.

The prognostic and immune significance of SNHG3 in clear cell renal cell carcinoma

Background

Long non-coding RNA (lncRNA) small nucleolar RNA host gene 3 (SNHG3) has been reported to be involved in the pathological process of a variety of tumors, including clear cell renal cell carcinoma (ccRCC). However, whether SNHG3 can be used as a prognostic biomarker and its correlation with immune infiltration in ccRCC remain unclear, warranting further research. This study aims to explore the relationship between SNHG3 and immune infiltration in ccRCC and confirm the potential of SNHG3 to predict survival of ccRCC patients.

Methods

The Cancer Genome Atlas (TCGA) database was used to assess the expression of SNHG3 in ccRCC, evaluate clinicopathological characteristics, assess prognosis, and conduct functional enrichment analysis. The ccRCC microenvironment and immune infiltration were investigated using the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithms, respectively. We additionally investigated the relationships between SNHG3 and immunological checkpoints. Drug sensitivity of SNHG3 was investigated in R. The expression of SNHG3 was verified in the Gene Expression Omnibus (GEO) database, ccRCC cell lines, and tissues. Wound healing and Methylthiazolyldiphenyl-tetrazolium bromide (MTT) assays were used to evaluate tumor cell migration and proliferation. Fluorescence in situ hybridization (FISH) assay was conducted to localize SNHG3 in ccRCC cells.

Results

SNHG3 expression was significantly upregulated in ccRCC cells and tissues and associated with several clinicopathological features and poor prognosis of ccRCC patients. SNHG3 was correlated with immune cells infiltration in ccRCC and exhibited sensitivity to various targeted and chemotherapy drugs. Knockdown of SNHG3 significantly reduced the proliferation and migration of ccRCC. FISH results showed that SNHG3 was located in the cell nucleus.

Conclusions

Overall, this study demonstrates that SNHG3 is a prognostic biomarker correlated with immune infiltration in ccRCC.

Glycogen metabolism genes as a molecular signature for subtyping, prognostic prediction, and immunotherapy selection in clear cell renal cell carcinoma

Glycogen accumulation is a typical feature in clear cell renal cell carcinoma (ccRCC). It has been reported that glycogen metabolism-related genes can promote the progression of ccRCC, but its role in molecular typing, prognosis, immune infiltration, and immunotherapy response has rarely been reported. We applied an unsupervised clustering approach for molecular typing of ccRCC. The least absolute shrinkage and selection operator regression (LASSO) was used for prognostic model construction. The robustness of the model is evaluated by multicenter mutual verification. Weighted gene co-expression network analysis (WGCNA) was used to explore potential biological mechanisms. RT-qPCR was used to identify mRNA relative expression. We found ccRCC can be divided into two subtypes based on glycogen metabolism-related genes, and the prognosis of patients between the two subtypes is significantly different. Furthermore, we constructed a prognostic model for ccRCC patients based on glycogen metabolism-related genes using LASSO algorithm. We found that the model has a strong prognostic effect. Subsequently, we explored the underlying mechanisms through WGCNA and found that the model is associated with immune-related signaling pathways. Finally, we also found that this prognostic model can be used as a marker of response to immunotherapy in patients with advanced ccRCC. In conclusion, glycogen metabolism-related genes have critical value in molecular typing and prognosis evaluation of ccRCC.

Potential prognostic and immunologic significances of ADAM8 in clear cell renal cell carcinoma

BACKGROUND

A Disintegrin And Metalloproteinase 8 (ADAM8) has been implicated in the development and progression of several cancers. However, further studies are needed to determine the value of ADAM8 in ccRCC. The research aimed to investigate the prognostic and immunologic significance of ADAM8 in ccRCC from the perspective of bioinformatics.

METHODS

We analyzed the expression and prognosis of ADAM8 in ccRCC using The Cancer Genome Atlas and validated it with Gene Expression Omnibus and immunohistochemistry assay. Functional enrichment analysis was conducted to investigate the signaling pathways. And the relationship between ADAM8 and the tumor microenvironment was analyzed using the CIBERSORT algorithm. Furthermore, the study explored the response to immunotherapy of ccRCC by using The Cancer Immunome Atlas database data. Potential drugs for treating ccRCC were discovered using the Connectivity Map.

RESULTS

The expression of ADAM8 was significantly elevated in ccRCC tissues. CcRCC patients with higher levels of ADAM8 expression had poorer prognosis, and ADAM8 was shown to be an independent predictive risk factor for ccRCC. The functional enrichment analysis revealed relevant signaling pathways. Furthermore, we found that ADAM8 expression correlates strongly with the extent of immune cell infiltration and immunotherapy. Finally, 4 groups of potential drugs for the treatment of ccRCC were identified.

CONCLUSION

Our research found that ADAM8 could have a significant impact on the development, progression, immunotherapy and prognosis of patients with ccRCC, and may be a promising prognostic and immunotherapeutic target. The study provides a new insights that may be useful in helping to manage ccRCC.

Dual-energy CT iodine concentration as a biomarker for immunotherapy treatment response in metastatic melanoma and renal cell carcinoma patients

OBJECTIVE

To investigate the predictive value of tumor iodine concentration obtained with dual-energy CT (DECT) for treatment response in patients treated with immune checkpoint inhibitors (ICI).

MATERIALS AND METHODS

Retrospective single-center study of consecutive metastatic melanoma and renal cell carcinoma (RCC) patients undergoing first-line ICI treatment. The iodine concentration measurement time points include prior to initiation of therapy (baseline [BL]), after initiation (follow-up [FU1]), and either time point nearest to 12 months or at time of progression (final follow-up [FFU]). Target lesion DECT-based whole-volume tumor normalized iodine concentration average (NICave) and size measurements were obtained. Reference standard was individual lesion FFU status categorized as responders or nonresponders per RECIST 1.1. Logistic regression model assessed NICave change and FU1 lesion response as predictors of FFU lesion outcome. Model's performance was summarized with AUC. Intraclass correlation coefficient (ICC) summarized inter-rater agreement of NICave.

RESULTS

Forty-six patients were included (mean age 61 ± 11 years, 12 women; 16 melanoma). Sixty-four of 175 target lesions were confirmed nonresponders at FFU. In a multivariable model, lesion status at FU1 (odds ratio [OR]: 27.4, p < 0.001) and changes in NICave from BL to FU1 (OR: 2.42 per 1-SD increase, p = 0.019) were significant predictors of lesion status at FFU. The model's AUC was 0.86 (95% CI: 0.76-0.93). Inter-rater reliability of NICave was 0.98 (95% CI: 0.97-0.99).

CONCLUSIONS

Changes in iodine concentration from baseline to first follow-up improve identification of delayed responding metastatic melanoma and RCC lesions treated with immune checkpoint inhibitor, initially classified as nonresponders by size change.

KEY POINTS

Question How can pseudoprogression/delayed treatment response in metastatic renal cell carcinoma (RCC) and melanoma patients on first-line immune checkpoint inhibitors be accurately identified? Findings Combining iodine concentration change from Dual-energy CT (baseline to first follow-up) with RECIST-based lesion size change improved prediction of final lesion outcome. Clinical relevance DECT-based whole-volume tumor iodine concentration for target lesions is useful as a predictive imaging biomarker for distinguishing delayed response from true progression in patients with metastatic RCC and melanoma treated with first-line immune checkpoint inhibitors.

Bioinformatics analysis of mitochondrial metabolism-related genes demonstrates their importance in renal cell carcinoma

PURPOSE

Clear cell renal cell carcinoma (ccRCC) is resistant to radiotherapy and chemotherapy. Thus, it is necessary to find new diagnostic markers and therapeutic targets to increase the overall outcomes of ccRCC. Recent studies have shown that therapeutic methods that interfere with the energy transfer system can also positively affect the treatment process.

METHODS

The present study is focused on finding markers associated with mitochondrial metabolic pathways that affect the outcome of ccRCC. For this purpose, we investigated various aspects of the relationship between mitochondrial metabolism and ccRCC based on analysis of gene network connections and differentially expressed genes, through assessment of protein-protein interaction, mutations, and promoter methylation on the related genes. We also investigated gene interaction with miRNAs and immune infiltration analysis.

RESULTS

Through these steps, we provided a list of possible diagnostic markers and therapeutic targets for ccRCC.

CONCLUSION

The current study further proved the importance of mitochondrial metabolic pathways in the pathogenesis of ccRCC and provided a list of possible diagnostic markers and therapeutic targets from these pathways that can be used in ccRCC.

Prognostic value of B7-H3 expression in metastatic renal cell carcinoma and its impact on immunotherapy response

BACKGROUND

Renal cell carcinoma (RCC) is characterised by its immunogenic and proangiogenic nature and its resistance to conventional therapies. The advent of immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs) has significantly improved patient survival, but resistance to these treatments remains a challenge. B7-H3, a potential immune checkpoint, has been implicated in modulating the tumour microenvironment and immune escape mechanisms in RCC.

METHODS

Immunohistochemical analysis of B7-H3 expression was performed in 84 metastatic RCC patients. Tissue microarrays and separate sections of formalin-fixed paraffin-embedded tissue were used for immunohistochemical staining. Membranous staining of the tumor cells was scored and statistical analyses were performed to assess the correlation between B7-H3 expression and treatment outcome.

RESULTS

B7-H3 expression was absent in 31% of patients, while 33.3% had a score of 1+, 31% had 2+, and 4.8% had 3+. High B7-H3 expression correlated with poorer OS (20 months vs. 45 months, p = 0.012). In patients receiving nivolumab, those with high B7-H3 expression had shorter PFS (2 months vs. 8 months, p = 0.037) and OS (17 months vs. 51 months, p = 0.01). B7-H3 expression was the only factor significantly affecting PFS and OS in multivariate analysis.

CONCLUSION

High B7-H3 expression is associated with poorer survival outcomes and reduced response to nivolumab in metastatic RCC patients. B7-H3 may serve as a predictive biomarker for immunotherapy response. Future studies should explore targeting B7-H3 in combination with existing therapies to enhance treatment efficacy.

Developing hypoxia and lactate metabolism-related molecular subtypes and prognostic signature for clear cell renal cell carcinoma through integrating machine learning

BACKGROUND

The microenvironment of clear cell renal cell carcinoma (ccRCC) is characterized by hypoxia and increased lactate production. However, the impact of hypoxia and lactate metabolism on ccRCC remains incompletely understood. In this study, a new molecular subtype is developed based on hypoxia-related genes (HRGs) and lactate metabolism-related genes (LMRGs), aiming to create a tool that can predict the survival rate, immune microenvironment status, and responsiveness to treatment of ccRCC patients.

METHOD

We obtained RNA-seq data and clinical information of patients with ccRCC from TCGA and GEO. HRGs and LMRGs are sourced from the Molecular Signatures Database. Integrating 10 machine learning algorithms and 101 frameworks, we constructed a prognostic model related to hypoxia and lactate metabolism. Its accuracy and reliability are evaluated through constructing prognostic nomograms, drawing ROC curves, and validating with clinical datasets. Additionally, risk subgroups are evaluated based on functional enrichment, tumor mutational burden (TMB), immune cell infiltration degree, and immune checkpoint expression level. Finally, we evaluate the responsiveness of risk subgroups to immunotherapy and determine personalized drugs for specific risk subgroups.

RESULTS

85 valuable prognostic genes were screened out. Functional enrichment analysis shows that the group with high-risk hypoxia and lactate metabolism-related genes scores (HLMRGS) is mainly involved in the activation of immune-related activities, while the low risk HLMRGS group is more active in metabolic and tumor-related pathways. At the same time, differences in the cellular functional states in the tumor microenvironment between the high risk HLMRGS group and the low risk HLMRGS group were observed. Finally, potential drugs for specific risk subgroups were determined.

CONCLUSION

We have developed a novel prognostic signature that integrates hypoxia and lactate metabolism. It is expected to become an effective tool for prognosis prediction, immunotherapy and personalized medicine of ccRCC.

ATF4/NUPR1 axis promotes cancer cell survival and mediates immunosuppression in clear cell renal cell carcinoma

Cancer cells encounter unavoidable stress during tumor growth. The stress-induced transcription factor, activating transcription factor 4 (ATF4), has been reported to upregulate various adaptive genes involved in salvage pathways to alleviate stress and promote tumor progression. However, this effect is unknown in clear cell renal cell carcinoma (ccRCC). In this study, we found that ATF4 expression was remarkably upregulated in tumor tissues and associated with poor ccRCC outcomes. ATF4 depletion significantly impaired ccRCC cell proliferation, migration, and invasion in vitro and in vivo by inhibiting the AKT/mTOR and epithelial-mesenchymal transition (EMT)-related signaling pathway. RNA sequencing and functional studies identified nuclear protein 1 (NUPR1) as a key downstream target of ATF4 for repressing ferroptosis and promoting ccRCC cell survival. In addition, targeting ATF4 or pharmacological inhibition using NUPR1 inhibitor ZZW115 promoted antitumor immunity in syngeneic graft mouse models, represented by increased infiltration of CD4+ and CD8+ T cells. Furthermore, ZZW115 could improve the response to the PD-1 immune checkpoint blockade. The results demonstrate that the ATF4/NUPR1 signaling axis promotes ccRCC survival and facilitates tumor-mediated immunosuppression, providing a set of potential targets and prognostic indicators for ccRCC patients.

ZBP1 as a prognostic biomarker correlated with cell proliferation in clear cell renal cell carcinoma

Background

Z-DNA-binding protein 1 (ZBP1) is a critical Z-DNA- and Z-RNA-binding protein. However, its diagnostic and prognostic significance, as well as its functions in clear cell renal cell carcinoma (ccRCC), are not well understood.

Materials and methods

Paired and unpaired differential expression analyses of ZBP1 were performed in pan-cancer cells. Receiver operating characteristic (ROC) curves and survival analyses were used to evaluate the clinical significance of ZBP1. Functional enrichment and immune infiltration analyses were used to explore the mechanisms underlying ZBP1 expression. Western blotting, qRT-PCR, CCK-8, and colony formation assays were used to investigate the potential function of ZBP1 in ccRCC cells. Molecular docking was utilized to identify drugs targeting ZBP1.

Results

ZBP1 was highly expressed in ccRCC, demonstrating significant diagnostic and prognostic value. ZBP1 mRNA expression correlated with TNM stage, pathologic stage, and histologic grade. Functional enrichment analyses indicated that ZBP1 is involved in multiple immune processes. Moreover, ZBP1 mRNA expression was positively correlated with the infiltrating levels of T cells and cytotoxic cells, and negatively correlated with the infiltrating levels of mast cells and Th17 cells in ccRCC. Biological experiments confirmed that ZBP1 promotes ccRCC cell proliferation. Molecular docking studies identified rucaparib as a potential drug targeting ZBP1.

Conclusion

Our research findings suggest that targeting ZBP1 could represent a novel therapeutic approach to inhibit the progression of ccRCC.

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC.

Identification of a novel PANoptosis-related gene signature for predicting the prognosis in clear cell renal cell carcinoma

PANoptosis has been shown to play an important role in tumorigenesis and gain more attention. Yet, the prognostic significance of PANoptosis-related genes has not been investigated more in clear cell renal cell carcinoma (ccRCC). The aim of this research was designed to identify and create a signature of PANoptosis-related genes which was expected to predict prognosis of ccRCC more effectively. The transcriptome data and clinical information were collected from The Cancer Genome Atlas database and the Gene Expression Omnibus database. Optimal differentially expressed PANoptosis-related genes, which were closely associated with prognosis and employed to construct a risk score, were extracted by univariate Cox analysis, least absolute shrinkage and selection operator Cox regression and multivariate Cox analysis. We performed Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curves to complete this process. By adopting univariate and multivariate analysis, the constructed risk score was assessed to verify whether it could be taken as an independent contributor for prognosis. Moreover, we created a nomogram in order to predict overall survival (OS) of ccRCC. Five differentially expressed PANoptosis-related genes were screened out and used to construct a risk score. Our results showed that ccRCC patients with high risk score had a poor prognosis and shorter OS. The results of Kaplan-Meier curves and the area under the receiver operating characteristic curves of 1-, 3-, and 5-year OS indicated that the prediction performance was satisfactory. Additionally, the risk model could be taken as an independent prognostic factor in training and validation cohorts. The nomogram exhibited excellent reliability in predicting OS, which was validated by calibration curves. We identified 5 PANoptosis-related genes, which were used to construct a risk score and a nomogram for prognostic prediction with reliable predictive capability. The present study may provide new potential therapeutic targets and precise treatment strategies for ccRCC.

Comprehensive analysis of lncRNA-mediated ceRNA network in renal cell carcinoma based on GEO database

Renal cell carcinoma (RCC) ranks among the leading causes of cancer-related mortality. Despite extensive research, the precise etiology and progression of RCC remain incompletely elucidated. Long noncoding RNA (lncRNA) has been identified as competitive endogenous RNA (ceRNA) capable of binding to microRNA (miRNA) sites, thereby modulating the expression of messenger RNAs (mRNA) and target genes. This regulatory network is known to exert a pivotal influence on cancer initiation and progression. However, the specific role and functional significance of the lncRNA-miRNA-mRNA ceRNA network in RCC remain poorly understood. The RCC transcriptome data was obtained from the gene expression omnibus database. The identification of differentially expressed long noncoding RNAs (DElncRNAs), differentially expressed miRNAs, and differentially expressed mRNAs (DEmRNAs) between RCC and corresponding paracancer tissues was performed using the "Limma" package in R 4.3.1 software. We employed a weighted gene co-expression network analysis to identify the key DElncRNAs that are most relevant to RCC. Subsequently, we utilized the encyclopedia of RNA interactomes database to predict the interactions between these DElncRNAs and miRNAs, and the miRDB database to predict the interactions between miRNAs and mRNAs. Therefore, key DElncRNAs were obtained to verify the expression of their related genes in the The Cancer Genome Atlas database and to analyze the prognosis. The construction of RCC-specific lncRNA-miRNA-mRNA ceRNA network was carried out using Cytoscape 3.7.0. A total of 286 DElncRNAs, 56 differentially expressed miRNAs, and 2065 DEmRNAs were identified in RCC. Seven key DElncRNAs (GAS6 antisense RNA 1, myocardial infarction associated transcript, long intergenic nonprotein coding RNA 921, MMP25 antisense RNA 1, Chromosome 22 Open Reading Frame 34, MIR34A host gene, MIR4435-2 host gene) were identified using weighted gene co-expression network analysis and encyclopedia of RNA interactomes databases. Subsequently, a network diagram comprising 217 nodes and 463 edges was constructed based on these key DElncRNAs. The functional analysis of DEmRNAs in the ceRNA network was conducted using Kyoto Encyclopedia of Genes and Genomes and gene ontology. We constructed RCC-specific ceRNA networks and identified the crucial lncRNAs associated with RCC using bioinformatics analysis, which will help us further understand the pathogenesis of this disease.

Decreased PANK1 expression in kidney renal clear cell carcinoma: impact on cell apoptosis, invasion, migration, and epithelial-mesenchymal transition

OBJECTIVE

To investigate pantothenate kinases 1 (PANK1) expression in kidney renal clear cell carcinoma (KIRC) tissues, analyze its correlation with clinicopathological features and prognosis, and explore its impact on invasion, migration, and apoptosis in KIRC cells.

METHODS

GEPIA (gene expression profiling interactive analysis), UALCAN and LinkedOmics, were employed to analyze PANK1 expression in KIRC tissues and its correlation with clinical characteristics. Comparative analyses were performed between KIRC (Caki-1 and 786-O) and noncancerous renal cells (HK-2 and RPTEC). Transfection with PANK1 activation particles was conducted, followed by Wound healing, Transwell assay, Annexin V-fluorescein isothiocyanate/propidium iodide (Annexin V-FITC/PI) staining, quantitative reverse-transcription polymerase chain reaction (qRT-PCR), and Western blotting.

RESULTS

PANK1 was down-regulated in KIRC tissues and cells compared to normal tissues and noncancerous cells. Correlation analyses linked PANK1 expression with clinicopathological features in KIRC, with high PANK1 expression associated with a favorable outcome. High PANK1 expression correlated positively with E-cadherin (CDH1), tight junction protein 1 (TJP1), Fas cell surface death receptor (FAS), caspase-8 (CASP8), and CASP9, while showing a negative correlation with vimentin (VIM), snail family transcriptional repressor 1 (SNAIL1), twist family BHLH transcription factor 1 (TWIST1), and TWIST2. PANK1 overexpression increased CDH1, TJP1, FAS, CASP8, and CASP9 while downregulating SNAIL1, VIM, TWIST1, and TWIST2, inhibiting invasion and migration, and promoting apoptosis in KIRC cells.

CONCLUSION

PANK1 down-regulation in KIRC tissues correlated with clinicopathological features and prognosis. Its overexpression modulated epithelial-mesenchymal transition (EMT)-related gene, inhibited invasion, promoted apoptosis in KIRC cells, highlighting its role in disease progression and therapeutic potential.

Characterization of cuproptosis signature in clear cell renal cell carcinoma by single cell and spatial transcriptome analysis

Cuproptosis is a novel type to regulate cell death with copper-dependent manner, and has been reported to involve in the occurrence and development of various malignant tumors. However, the association between cuproptosis and the tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) remained unclear. To address this question, we integrated the single cell RNA sequencing (scRNA-seq) datasets of ccRCC across different stages, systematically examined the distinctive expression patterns of cuproptosis-related genes (CRGs) within the TME of ccRCC, and explored the crucial signatures using the spatial transcriptome sequencing (ST-seq) dataset. The cuproptosis activities reduced in cancer tissues along with the ccRCC development, and recovered after therapy. We identified HILPDA+ ccRCC1 subtype, characterized with hypoxia, as cuproptosis susceptible cells associated with a better prognosis. The main co-expression modules of HILPDA+ ccRCC1 subtype highlighted the role in anion transport, response to oxygen species and PD-L1-PD-1 pathway. Furthermore, the immunosuppressive cells might interact with HILPDA+ ccRCC1 subtype via HAVCR2-LGALS9, C3-C3AR1, HLA-A-CD8B and HLA-C-CD8A axises to shape the cuproptosis-related TME landscape. In summary, we anticipate that this study will offer valuable insights and potential strategies of cuproptosis for therapy of ccRCC.

Epigenetic modification of PHLDA2 is associated with tumor microenvironment and unfavorable outcome of immune checkpoint inhibitor-based therapies in clear cell renal cell carcinoma

BACKGROUND

A substantial proportion of patients with metastatic clear cell renal cell carcinoma (ccRCC) cannot derive benefit from immune checkpoint inhibitor (ICI) plus anti-angiogenic agent combination therapy, making identification of predictive biomarkers an urgent need. The members of pleckstrin homology-like domain family A (PHLDA) play critical roles in multiple cancers, whereas their roles in ccRCC remain unknown.

METHODS

Transcriptomic, clinical, genetic alteration and DNA methylation data were obtained for integrated analyses from TCGA database. RNA sequencing was performed on 117 primary tumors and 79 normal kidney tissues from our center. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis were performed to explore transcriptomic features. Data from three randomized controlled trials (RCT), including CheckMate025, IMmotion151, JAVELIN101, were obtained for validation.

RESULTS

Members of PHLDA family were dysregulated in pan-cancer. Elevated PHLDA2 expression was associated with adverse clinicopathologic parameters and worse prognosis in ccRCC. Aberrant DNA hypomethylation contributed to up-regulation of PHLDA2. An immunosuppressive microenvironment featured by high infiltrates of Tregs and cancer-associated fibroblasts, was observed in ccRCC with higher PHLDA2 expression. Utilizing data from three RCTs, the association of elevated PHLDA2 expression with poor therapeutic efficacy of ICI plus anti-angiogenic combination therapy was confirmed.

CONCLUSIONS

Our study revealed that elevated PHLDA2 expression regulated by DNA hypomethylation was correlated with poor prognosis and immunosuppressive microenvironment, and highlighted the role of PHLDA2 as a robust biomarker for predicting therapeutic efficacy of ICI plus anti-angiogenic agent combination therapy in ccRCC, which expand the dimension of precision medicine.

Establishment and validation of a novel disulfidptosis-related immune checkpoint gene signature in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal tumors and is associated with a unfavorable prognosis. Disulfidptosis is a recently identified form of cell death mediated by disulfide bonds. Numerous studies have highlighted the significance of immune checkpoint genes (ICGs) in ccRCC. Nevertheless, the involvement of disulfidptosis-related immune checkpoint genes (DRICGs) in ccRCC remains poorly understood.

METHODS

The mRNA expression profiles and clinicopathological data of ccRCC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases. The associations between disulfidptosis-related genes (DRGs) and immune checkpoint genes (ICGs) were assessed to identify DRICGs. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were conducted to construct a risk signature.

RESULTS

A total of 39 differentially expressed immune-related candidate genes were identified. A prognostic signature was constructed utilizing nine DRICGs (CD276, CD80, CD86, HLA-E, LAG3, PDCD1LG2, PVR, TIGIT, and TNFRSF4) and validated using GEO data. The risk model functioned as an independent prognostic indicator for ccRCC, while the associated nomogram provided a reliable scoring system for ccRCC. Gene set enrichment analysis indicated enrichment of phospholipase D, antigen processing and presentation, and ascorbate and aldarate metabolism-related signaling pathways in the high-risk group. Furthermore, the DRICGs exhibited correlations with the infiltration of various immune cells. It is noteworthy that patients with ccRCC categorized into distinct risk groups based on this model displayed varying sensitivities to potential therapeutic agents.

CONCLUSIONS

The novel DRICG-based risk signature is a reliable indicator for the prognosis of ccRCC patients. Moreover, it also aids in drug selection and correlates with the tumour immune microenvironment in ccRCC.

Towards effective CAIX-targeted radionuclide and checkpoint inhibition combination therapy for advanced clear cell renal cell carcinoma

Background: Immune checkpoint inhibitors (ICI) are routinely used in advanced clear cell renal cell carcinoma (ccRCC). However, a substantial group of patients does not respond to ICI therapy. Radiation is a promising approach to increase ICI response rates since it can generate anti-tumor immunity. Targeted radionuclide therapy (TRT) is a systemic radiation treatment, ideally suited for precision irradiation of metastasized cancer. Therefore, the aim of this study is to explore the potential of combined TRT, targeting carbonic anhydrase IX (CAIX) which is overexpressed in ccRCC, using [177Lu]Lu-DOTA-hG250, and ICI for the treatment of ccRCC. Methods: In this study, we evaluated the therapeutic and immunological action of [177Lu]Lu-DOTA-hG250 combined with aPD-1/a-CTLA-4 ICI. First, the biodistribution of [177Lu]Lu-DOTA-hG250 was investigated in BALB/cAnNRj mice bearing Renca-CAIX or CT26-CAIX tumors. Renca-CAIX and CT26-CAIX tumors are characterized by poor versus extensive T-cell infiltration and homogeneous versus heterogeneous PD-L1 expression, respectively. Tumor-absorbed radiation doses were estimated through dosimetry. Subsequently, [177Lu]Lu-DOTA-hG250 TRT efficacy with and without ICI was evaluated by monitoring tumor growth and survival. Therapy-induced changes in the tumor microenvironment were studied by collection of tumor tissue before and 5 or 8 days after treatment and analyzed by immunohistochemistry, flow cytometry, and RNA profiling. Results: Biodistribution studies showed high tumor uptake of [177Lu]Lu-DOTA-hG250 in both tumor models. Dose escalation therapy studies in Renca-CAIX tumor-bearing mice demonstrated dose-dependent anti-tumor efficacy of [177Lu]Lu-DOTA-hG250 and remarkable therapeutic synergy including complete remissions when a presumed subtherapeutic TRT dose (4 MBq, which had no significant efficacy as monotherapy) was combined with aPD-1+aCTLA-4. Similar results were obtained in the CT26-CAIX model for 4 MBq [177Lu]Lu-DOTA-hG250 + a-PD1. Ex vivo analyses of treated tumors revealed DNA damage, T-cell infiltration, and modulated immune signaling pathways in the TME after combination treatment. Conclusions: Subtherapeutic [177Lu]Lu-DOTA-hG250 combined with ICI showed superior therapeutic outcome and significantly altered the TME. Our results underline the importance of investigating this combination treatment for patients with advanced ccRCC in a clinical setting. Further investigations should focus on how the combination therapy should be optimally applied in the future.

What factors may affect the effect of ICI-combined therapy in patients with metastatic renal cell carcinoma? A meta-analysis

OBJECTIVE

The prognostic factors of ICI-including combined therapy in patients with metastatic renal cell carcinoma were analyzed by systematic review.

METHOD

We searched Web of Science, Cochrane, PubMed, CNKI, Wanfang and other databases for randomized controlled trials and clinical trials of combination therapy including ICIs in the treatment of metastatic renal cell carcinoma. The search time was from the establishment of the database to September 2023. Data were extracted and evaluated with RevMan 5.4 software.

RESULTS

Six studies were included, including 4723 patients. The results showed that ① in terms of progression-free survival, the factors of age < 65 years old, male sex, Canada and Western Europe, nephrectomy, different IMDC class, number of organs with metastases and PD-L1 expression ≥ 1% significantly prolonged PFS in patients with metastatic cancer treated by combination therapy including ICIs; ② in terms of overall survival rate, the factors of age < 65 years old, female sex, nephrectomy, different IMDC class and PD-L1 expression ≥ 1% significantly prolonged the OS of patients with metastatic cancer treated by combination therapy including ICIs.

CONCLUSIONS

Age, sex, region, nephrectomy, different IMDC class, number of organs with metastases and PD-L1 expression are independent factors influencing the efficacy of combination therapy including ICIs in the treatment of metastatic renal cell carcinoma. Systematic evaluation of baseline indicators of patients with metastatic renal cell carcinoma to predict clinical benefits can effectively improve the benefit rate of patients.

Diagnostic, predictive and prognostic molecular biomarkers in clear cell renal cell carcinoma: A retrospective study

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of kidney cancer. Many patients are diagnosed at advanced stages, making early detection crucial. Unfortunately, there are currently no noninvasive tests for ccRCC, emphasizing the need for new biomarkers. Additionally, ccRCC often develops resistance to treatments like radiotherapy and chemotherapy. Identifying biomarkers that predict treatment outcomes is vital for personalized care. The integration of artificial intelligence (AI), multi-omics analysis, and computational biology holds promise in bolstering detection precision and resilience, opening avenues for future investigations. The amalgamation of radiogenomics and biomaterial-basedimmunomodulation signifies a revolutionary breakthrough in diagnostic medicine. This review summarizes existing literature and highlights emerging biomarkers that enhance diagnostic, predictive, and prognostic capabilities for ccRCC, setting the stage for future clinical research.

The Evolving Landscape of Biomarkers for Immune Checkpoint Blockade in Genitourinary Cancers

In the past decade, immune checkpoint inhibitors (ICI) have been approved for treatment of genitourinary malignancies and have revolutionized the treatment landscape of these tumors. However, despite the remarkable success of these therapies in some GU malignancies, many patients' tumors do not respond to these therapies, and others may experience significant side effects, such as immune-related adverse events (iRAEs). Accordingly, biomarkers and improved prognostic tools are critically needed to help predict which patients will respond to ICI, predict and mitigate risk of developing immune-related adverse events, and inform personalized choice of therapy for each patient. Ongoing clinical and preclinical studies continue to provide an increasingly robust understanding of the mechanisms of the response to immunotherapy, which continue to inform biomarker development and validation. Herein, we provide a comprehensive review of biomarkers of the response to immunotherapy in GU tumors and their role in selection of therapy and disease monitoring.

Adjuvant therapy in renal cell carcinoma: Tyrosine kinase inhibitor versus immune checkpoint inhibitor

BACKGROUND

To date, no meta-analysis has been conducted to compare the effectiveness and safety of adjuvant tyrosine kinase inhibitors (TKIs) and adjuvant immunotherapies (IMTs) in renal cell carcinoma (RCC) patients using reconstructed individual patient data (IPD). This study aims to fill that gap by assessing the efficacy and safety profiles of these treatments in such patients.

METHODS

This study employed a systematic approach for identifying relevant literature from the PubMed and EMBASE databases. We included articles published in English from the inception of these databases until November 11, 2023, focusing specifically on appropriate phase III randomized controlled trials (RCTs). To reconstruct survival curves, we utilized a semiautomated tool, WebPlotDigitizer, in conjunction with a novel shiny application integrated with R software. For adverse events (AEs), the summary measures were incidences, expressed as a 95% confidence interval (CI), calculated using a random-effects model with a logit transformation.

RESULTS

The analysis included 8 RCTs with a total of 9119 patients. Compared to adjuvant TKIs, adjuvant IMTs showed a similar disease-free survival (DFS) (hazard ratio [HR] 1.03, 95% CI [0.98-1.09], P = .281). However, the overall survival (OS) rates between the 2 groups couldn't be directly compared due to unmatched control groups in the IMT and TKI studies. Against placebo, adjuvant IMTs demonstrated superior DFS (HR 0.82, 95% CI [0.71-0.94], P = .004) but comparable OS (HR 0.79, 95% CI [0.59-1.06], P = .120). Against placebo, adjuvant TKIs showed superior DFS (HR 0.85, 95% CI [0.79-0.92], P < .0001) and marginally better OS (HR 0.89, 95% CI [0.80-0.996], P = .042). Regarding severe AEs and discontinuation rates due to AEs, adjuvant IMTs had a significantly lower incidence of severe AEs (25% [320/1282] vs 59% [2192/3716], odds ratio [OR] 0.23, 95% CI [0.20-0.27], P < .0001) and a markedly better discontinuation rate (39% [499/1282] vs 52% [2068/4018], OR 0.60, 95% CI [0.53-0.68], P < .0001) compared to TKIs.

CONCLUSION

This paper presents a thorough analysis of DFS, OS, and treatment-related AEs across various groups in RCC patients, offering a valuable resource for clinicians in everyday practice. Our findings indicate that while adjuvant IMTs and adjuvant TKIs demonstrate similar DFS, IMTs are notably superior in terms of safety and compliance.

Prognostic impact and immunotherapeutic implications of NETosis-related prognostic model in clear cell renal cell carcinoma

BACKGROUND

The ramifications of necroptosis on the prognostication of clear cell renal cell carcinoma (ccRCC) remain inadequately expounded.

METHODS

A prognostic model delineating the facets of necroptosis in ccRCC was constructed, employing a compendium of algorithms. External validation was effectuated using the E-MTAB-1980 dataset. The exploration of immune infiltration scores was undertaken through the exploitation of multiple algorithms. Single-cell RNA sequencing data were procured from the GSE171306 dataset. Real-time quantitative PCR (RT-qPCR) was engaged to scrutinize the differential expression of SLC25A37 across cancer and paracancer tissues, as well as diverse cell lines. Assessments of proliferative and metastatic alterations in 769-P and 786-O cells were accomplished through Cell Counting Kit-8 (CCK8) and wound healing assays.

RESULTS

The necroptosis-related signature (NRS) emerges as a discerning metric, delineating patients' immune attributes, tumor mutation burden, immunotherapy response, and drug susceptibility. Single-cell RNA sequencing analysis unveils the marked enrichment of SLC25A37 in tumor cells. Concurrently, RT-qPCR discloses the overexpression of SLC25A37 in both ccRCC tissues and cell lines. SLC25A37 knockdown mitigates the proliferative and metastatic propensities of 769-P and 786-O cells, as evidenced by CCK8 and wound healing assays.

CONCLUSION

The NRS assumes a pivotal role in ascertaining the prognosis, tumor mutation burden, immunotherapy response, drug susceptibility, and immune cell infiltration features of ccRCC patients. SLC25A37 emerges as a putative player in immunosuppressive microenvironments, thereby providing a prospective avenue for the design of innovative immunotherapeutic targets for ccRCC.

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.

Deciphering anoikis resistance and identifying prognostic biomarkers in clear cell renal cell carcinoma epithelial cells

This study tackles the persistent prognostic and management challenges of clear cell renal cell carcinoma (ccRCC), despite advancements in multimodal therapies. Focusing on anoikis, a critical form of programmed cell death in tumor progression and metastasis, we investigated its resistance in cancer evolution. Using single-cell RNA sequencing from seven ccRCC patients, we assessed the impact of anoikis-related genes (ARGs) and identified differentially expressed genes (DEGs) in Anoikis-related epithelial subclusters (ARESs). Additionally, six ccRCC RNA microarray datasets from the GEO database were analyzed for robust DEGs. A novel risk prognostic model was developed through LASSO and multivariate Cox regression, validated using BEST, ULCAN, and RT-PCR. The study included functional enrichment, immune infiltration analysis in the tumor microenvironment (TME), and drug sensitivity assessments, leading to a predictive nomogram integrating clinical parameters. Results highlighted dynamic ARG expression patterns and enhanced intercellular interactions in ARESs, with significant KEGG pathway enrichment in MYC + Epithelial subclusters indicating enhanced anoikis resistance. Additionally, all ARESs were identified in the spatial context, and their locational relationships were explored. Three key prognostic genes-TIMP1, PECAM1, and CDKN1A-were identified, with the high-risk group showing greater immune infiltration and anoikis resistance, linked to poorer prognosis. This study offers a novel ccRCC risk signature, providing innovative approaches for patient management, prognosis, and personalized treatment.

Molecular subtypes of clear cell renal carcinoma based on PCD-related long non-coding RNAs expression: insights into the underlying mechanisms and therapeutic strategies

BACKGROUND

PCD-related long non-coding RNAs (PRLs) are rarely investigated in relation to clear cell renal carcinoma (ccRCC). As part of this study, we evaluated the immunological potential of PRL signatures as a biomarker for ccRCC prognosis and immunological function.

MATERIALS AND METHODS

Data were downloaded from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. A Pearson correlation analysis was conducted on the 27 PCD-associated genes to determine whether lncRNAs were significantly associated with PCD. Kaplan-Meier analysis, biological function identification, immune infiltration analysis, estimation of efficacy of immunotherapy and targeted drug screening, and exploration of the landscape of mutation status were conducted by analyzing the risk scores.

RESULTS

Seven PRLs, LINC02747, AP001636.3, AC022126.1, LINC02657, LINC02609, LINC02154, and ZNNT1, were used to divide patients with ccRCC into groups with high and low risk. High-risk patients had a worse prognosis than low-risk patients, according to the results, and the PRL signature showed promising predictive ability. More immune cells were clustered in the high-risk group, whereas the immune cell function of the low-risk group was significantly suppressed. The high-risk group was less sensitive to immunotherapy, whereas the low-risk group had positive responses to most drugs.

CONCLUSIONS

Collectively, we established and verified a PRL signature that could competently guide the prognostic survival and immunotherapy of ccRCC. In addition, molecular subtypes were determined for ccRCC based on PRL expression, which may help elucidate the underlying molecular mechanism of ccRCC and develop targeted 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.

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.

Circulating microRNA-155-3p levels predicts response to first line immunotherapy in patients with metastatic renal cell carcinoma

Predictive biomarkers of response to immune checkpoint-based therapies (ICI) remain a critically unmet need in the management of advanced renal cell carcinoma (RCC). The complex interplay of the tumour microenvironment (TME) and the circulating immune response has proven to be challenging to decipher. MicroRNAs have gained increasing attention for their role in post-transcriptional gene expression regulation, particularly because they can have immunomodulatory properties. We evaluated the presence of immune-specific extracellular vesicle (EV) microRNAs in the plasma of patients with metastatic RCC (mRCC) prior to initiation of ICI. We found significantly lower levels of microRNA155-3p (miR155) in responders to ICI, when compared to non-responders. This microRNA has unique immunomodulatory properties, thus providing potential biological rationale for our findings. Our results support further work in exploring microRNAs as potential biomarkers of response to immunotherapy.

Effect of CHST11, a novel biomarker, on the biological functionalities of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor, and the role of carbohydrate sulfotransferase 11 (CHST11) in this cancer remains unclear. Here, by using bioinformatics methods, we comprehensively analyzed the relationship between CHST11 and clinical significance, immune infiltration, functional enrichment, m6A methylation, and protein-protein interaction networks. We found that CHST11 expression was significantly higher in ccRCC samples than in normal tissues. Additionally, CHST11 levels correlated with the clinicopathological features of ccRCC patients and functioned as a prognostic factor for patient survival. Functional analysis revealed the involvement of CHST11 in metabolic pathways. Immune infiltration and m6A methylation analysis suggested the association of CHST11 with immune cell abundance in the tumor microenvironment and specific methylation patterns in ccRCC. The in vitro analysis of the clinical samples and ccRCC cell lines demonstrated that the overexpression of CHST11 promotes ccRCC cell proliferation, migration, and invasion, while its suppression has the opposite effect. Thus, CHST11 may play a remarkable role in the occurrence and progression of ccRCC. Functionally, CHST11 promotes the aggressiveness of ccRCC cells. These findings provide insights into the role of CHST11 in ccRCC progression.Registry and the Registration No. of the study/trial: No. 2021K034.

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.

The association between the triglyceride-glucose index and prognosis in postoperative renal cell carcinoma patients: a retrospective cohort study

Background

Insulin resistance has been proven to be associated with renal cell carcinoma (RCC). However, the prognostic value of the triglyceride-glucose (TyG) index, as a marker for insulin resistance (IR), is still unclear. Therefore, we conducted research to explore the prognostic value and the predictive performance of the TyG index in postoperative RCC patients.

Methods

A total of 651 postoperative RCC patients from January 2016 to June 2018 were enrolled in the final study. Their clinical and laboratory parameters were collected from medical records and through follow-up by phone. The triglyceride-glucose (TyG) index was calculated as follows: TyG = Ln[TG (mg/dl) × FBG (mg/dL)/2]. The overall survival (OS) and disease-free survival (DFS) were identified as the main outcomes.

Results

The TyG index is an independent prognostic factor for OS (HR = 2.340, 95% CI = 1.506 to 3.64, P < 0.001) and DFS (HR = 2.027, 95% CI = 1.347 to 3.051, P < 0.001) in postoperative RCC patients. Kaplan-Meier survival curves of the different TyG index levels showed statistically significant differences in terms of OS and DFS (log-rank test, P < 0.0001). Furthermore, the TyG index was significantly associated with RCC risk factors.

Conclusion

The TyG index is significantly associated with RCC survival. The mechanisms responsible for these results may contribute toward the improvement of RCC prognosis and immunotherapy efficacy and the development of new immunotherapeutic targets.

Knockdown of Antisense Noncoding Mitochondrial RNA Reduces Tumorigenicity of Patient-Derived Clear Cell Renal Carcinoma Cells in an Orthotopic Xenograft Mouse Model

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of renal cancer and its treatment is hindered by a resistance to targeted therapies, immunotherapies and combinations of both. We have reported that the knockdown of the antisense noncoding mitochondrial RNAs (ASncmtRNAs) with chemically modified antisense oligonucleotides induces proliferative arrest and apoptotic death in tumor cells from many human and mouse cancer types. These studies have been mostly performed in vitro and in vivo on commercially available cancer cell lines and have shown that in mouse models tumor growth is stunted by the treatment. The present work was performed on cells derived from primary and metastatic ccRCC tumors. We established primary cultures from primary and metastatic ccRCC tumors, which were subjected to knockdown of ASncmtRNAs in vitro and in vivo in an orthotopic xenograft model in NOD/SCID mice. We found that these primary ccRCC cells are affected in the same way as tumor cell lines and in the orthotopic model tumor growth was significantly reduced by the treatment. This study on patient-derived ccRCC tumor cells represents a model closer to actual patient ccRCC tumors and shows that knockdown of ASncmtRNAs poses a potential treatment option for these patients.

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.

The Expression of Alamandine Receptor MrgD in Clear Cell Renal Cell Carcinoma Is Associated with a Worse Prognosis and Unfavorable Response to Antiangiogenic Therapy

Renal cell carcinoma (RCC) ranks among the most prevalent malignancies in Western countries, marked by its notable heterogeneity, which contributes to an unpredictable clinical trajectory. The insufficiency of dependable biomarkers adds complexity to assessing this tumor progression. Imbalances of several components of the intrarenal renin-angiotensin system (iRAS) significantly impact patient prognoses and responses to first-line immunotherapies. In this study, we analyzed the immunohistochemical expression of the Mas-related G-protein-coupled receptor D (MrgD), which recognizes the novel RAS peptide alamandine (ALA), in a series of 87 clear cell renal cell (CCRCCs), 19 papillary (PRCC), 7 chromophobe (ChRCC) renal cell carcinomas, and 11 renal oncocytomas (RO). MrgD was expressed in all the renal tumor subtypes, with a higher mean staining intensity in the PRCCs, ChRCCs, and ROs. A high expression of MrgD at the tumor center and at the infiltrative front of CCRCC tissues was significantly associated with a high histological grade, large tumor diameter, local invasion, and locoregional node and distant metastasis. Patients with worse 5-year cancer-specific survival and a poorer response to antiangiogenic tyrosine-kinase inhibitors (TKIs) showed higher MrgD expression at the center of their primary tumors. These findings suggest a possible role of MrgD in renal carcinogenetic processes. Further studies are necessary to unveil its potential as a novel biomarker for CCRCC prognosis and response to frontline therapies.

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.

The Role of the Complement in Clear Cell Renal Carcinoma (ccRCC)-What Future Prospects Are There for Its Use in Clinical Practice?

In recent years, the first-line available therapeutic options for metastatic renal cell carcinoma (mRCC) have radically changed with the introduction into clinical practice of new immune checkpoint inhibitor (ICI)-based combinations. Many efforts are focusing on identifying novel prognostic and predictive markers in this setting. The complement system (CS) plays a central role in promoting the growth and progression of mRCC. In particular, mRCC has been defined as an "aggressive complement tumor", which encompasses a group of malignancies with poor prognosie and highly expressed complement components. Several preclinical and retrospective studies have demonstrated the negative prognostic role of the complement in mRCC; however, there is little evidence on its possible role as a predictor of the response to ICIs. The purpose of this review is to explore more deeply the physio-pathological role of the complement in the development of RCC and its possible future use in clinical practice as a prognostic and predictive factor.

MUC1 Drives the Progression and Chemoresistance of Clear Cell Renal Carcinomas

While the transmembrane glycoprotein mucin 1 (MUC1) is clustered at the apical borders of normal epithelial cells, with transformation and loss of polarity, MUC1 is found at high levels in the cytosol and is uniformly distributed over the entire surface of carcinoma cells, where it can promote tumor progression and adversely affects the response to therapy. Clear cell renal cell carcinoma (ccRCC), the main histotype of kidney cancer, is typically highly resistant to conventional and targeted therapies for reasons that remain largely unknown. In this context, we investigated whether MUC1 also plays a pivotal role in the cellular and molecular events driving ccRCC progression and chemoresistance. We showed, using loss- and gain-of-function approaches in ccRCC-derived cell lines, that MUC1 not only influences tumor progression but also induces a multi-drug-resistant profile reminiscent of the activation of ABC drug efflux transporters. Overall, our results suggest that targeting MUC1 may represent a novel therapeutic approach to limit ccRCC progression and improve drug sensitivity.

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.