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

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.

Serum and Urine Metabolic Fingerprints Characterize Renal Cell Carcinoma for Classification, Early Diagnosis, and Prognosis

Renal cell carcinoma (RCC) is a substantial pathology of the urinary system with a growing prevalence rate. However, current clinical methods have limitations for managing RCC due to the heterogeneity manifestations of the disease. Metabolic analyses are regarded as a preferred noninvasive approach in clinics, which can substantially benefit the characterization of RCC. This study constructs a nanoparticle-enhanced laser desorption ionization mass spectrometry (NELDI MS) to analyze metabolic fingerprints of renal tumors (n = 456) and healthy controls (n = 200). The classification models yielded the areas under curves (AUC) of 0.938 (95% confidence interval (CI), 0.884-0.967) for distinguishing renal tumors from healthy controls, 0.850 for differentiating malignant from benign tumors (95% CI, 0.821-0.915), and 0.925-0.932 for classifying subtypes of RCC (95% CI, 0.821-0.915). For the early stage of RCC subtypes, the averaged diagnostic sensitivity of 90.5% and specificity of 91.3% in the test set is achieved. Metabolic biomarkers are identified as the potential indicator for subtype diagnosis (p < 0.05). To validate the prognostic performance, a predictive model for RCC participants and achieve the prediction of disease (p = 0.003) is constructed. The study provides a promising prospect for applying metabolic analytical tools for RCC characterization.

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.

Differential effect of asparagine and glutamine removal on three adenocarcinoma cell lines

Asparagine and glutamine depletion operated by the drug Asparaginase (ASNase) has revolutionized therapy in pediatric patients affected by Acute Lymphoblastic Leukemia (ALL), bringing remissions to a remarkable 90 % of cases. However, the knowledge of the proproliferative role of asparagine in adult and solid tumors is still limited. We have here analyzed the effect of ASNase on three adenocarcinoma cell lines (A549, lung adenocarcinoma, MCF-7, breast cancer, and 786-O, kidney cancer). In contrast to MCF-7 cells, 786-O and A549 cells proved to be a relevant target for cell cycle perturbation by asparagine and glutamine shortage. Indeed, when the cell-cycle was analyzed by flow cytometry, A549 showed a canonical response to asparaginase, 786-O cells, instead, showed a reduction of the percentage of cells in the G1 phase and an increase of those in the S-phase. Despite an increased number of PCNA and RPA70 positive nuclear foci, BrdU and EdU incorporation was absent or strongly delayed in treated 786-O cells, thus indicating a readiness of replication forks unmatched by DNA synthesis. In 786-O asparagine synthetase was reduced following treatment and glutamine synthetase was totally absent. Interestingly, DNA synthesis could be recovered by adding Gln to the medium. MCF-7 cells showed no significant changes in the cell cycle phases, in DNA-bound PCNA and in total PCNA, but a significant increase in ASNS and GS mRNA and protein expression. The collected data suggest that the effect observed on 786-O cells following ASNase treatment could rely on mechanisms which differ from those well-known and described for leukemic blasts, consisting of a complete block in the G1/S transition in proliferating cells and on an increase on non-proliferative (G0) blasts.

IGF2BP2 inhibits invasion and migration of clear cell renal cell carcinoma via targeting Netrin-4 in an m6A-dependent manner

Clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma, often leads to a poor prognosis due to metastasis. The investigation of N6-methyladenosine (m6A) methylation, a crucial RNA modification, and its role in ccRCC, particularly through the m6A reader insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), revealed significant insights. We found that IGF2BP2 was notably downregulated in ccRCC, which correlated with tumor aggressiveness and poor prognosis. Thus, IGFBP2 has emerged as an independent prognostic factor of ccRCC. Moreover, a strong positive correlation was observed between the expression of IGF2BP2 and Netrin-4. Netrin-4 was also downregulated in ccRCC, and its lower levels were associated with increased malignancy and poor prognosis. Overexpression of IGF2BP2 and Netrin-4 suppressed the invasion and migration of ccRCC cells, while Netrin-4 knockdown reversed these effects in ccRCC cell lines. RNA immunoprecipitation (RIP)-quantitative polymerase chain reaction validated the robust enrichment of Netrin-4 mRNA in anti-IGF2BP2 antibody immunoprecipitates. MeRlP showed significantly increased Netrin4 m6A levels after lGF2BP2 overexpression. Moreover, we found that IGF2BP2 recognized and bound to the m6A site within the coding sequence of Netrin-4, enhancing its mRNA stability. Collectively, these results showed that IGF2BP2 plays a suppressive role in the invasion and migration of ccRCC cells by targeting Netrin-4 in an m6A-dependent manner. These findings underscore the potential of IGF2BP2/Netrin-4 as a promising prognostic biomarker and therapeutic target in patients with ccRCC metastasis.

Nc-RNA-mediated low expression of AZIN1 correlated with unfavorable prognosis in kidney renal clear cell carcinoma

OBJECTIVE

Kidney renal clear cell carcinoma (KIRC, ccRCC) is the most common type of renal cancer with high recurrence and mortality. It has long been recognized that Antizyme inhibitor 1 (AZIN1) serves as a pro-oncogenic molecule in multiple cancers. However, the clinicopathological features of AZIN1 in KIRC remain unexplored.

MATERIALS AND METHODS

The Cancer Genome Atlas (TCGA, TIMER, and GEPIA) were employed for pan-cancer expression and survival analysis of AZIN1, indicating the unique anti-tumor role of AZIN1 in KIRC. The expression and clinical characteristics of AZIN1 in KIRC were further proven via Human Protein Atlas and TCGA. single-sample GSEA was employed to investigate the immune infiltration of AZIN1. Then the downstream pathways were illustrated via the LinkedOmics, Metascape, and Cytoscape databases. The possible upper regulating noncoding RNAs (ncRNAs) were analyzed from five programs-TargetScan, StarBase, miRanda, PITA, and miRmap.

RESULTS

AZIN1 is downregulated in KIRC patients. Lower levels of AZIN1 were linked with unfavorable outcomes in KIRC patients. The AZIN1 expression was positively related to immune cell infiltration in KIRC. We also elucidated a possible upstream regulatory ncRNA of AZIN1 in KIRC namely STK4-AS1/AC068338.2-miR-106b-5p-AZIN1 axis as well as the downstream signaling pathways.

CONCLUSION

This study illustrated the unique anti-tumor role of AZIN1 in KIRC and provided potential value for guiding immunotherapy and targeted therapy.

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.

Redirecting Tumor Evolution with Nanocompiler Precision for Enhanced Therapeutic Outcomes

Precisely programming the highly plastic tumor expression profile to render it devoid of drug resistance and metastatic potential presents immense challenges. Here, a transformative nanocompiler designed to reprogram and stabilize the mutable state of tumor cells is introduced. This nanocompiler features a trio of components: 2-deoxy-d-glucose-modified lipid nanoparticles to inhibit glucose uptake, iron oxide nanoparticles to induce oxidative stress, and a deubiquitinase inhibitor to block adaptive protein profile changes in tumor cells. By specifically targeting the hypermetabolic nature of tumors, this approach disrupted their energy production, ultimately fostering a state of vulnerability and impeding their ability to adapt and resist. The results of this study indicate a substantial reduction in tumor growth and metastasis, thus demonstrating the potential of this strategy to manipulate tumor protein expression and fate. This proactive nanocompiler approach promises to steer cancer therapy toward more effective and lasting outcomes.

Metabolomic landscape of renal cell carcinoma in von Hippel-Lindau syndrome in a Chinese cohort

Von Hippel-Lindau (VHL) syndrome is a rare autosomal dominant disorder, where renal cell carcinoma (RCC) serves as a significant cause of mortality. We collected peripheral blood from 61 VHL-RCC patients and 31 healthy individuals, along with 19 paired RCC tumor and adjacent non-malignant samples. Using liquid chromatography-mass spectrometry, we identified 238 plasma and 241 tissue differentially abundant metabolites (DAMs), highlighting key pathways such as arginine and proline metabolism. The top 10 of the 23 DAMs, common to both plasma and tissue, were instrumental in constructing a high-performance diagnostic model. These DAMs demonstrated significant correlations with VHL gene mutation types. Cox regression analysis revealed that plasma levels of N2,N2-dimethylguanosine were associated with the timing of RCC onset in VHL patients, acting as an independent predictive factor. This study enhances diagnostic accuracy for this rare condition and opens new avenues for exploring metabolic mechanisms of the disease and potential therapeutic directions.

Metabolomics Reveals Tyrosine Kinase Inhibitor Resistance-Associated Metabolic Events in Human Metastatic Renal Cancer Cells

The development of resistance to tyrosine kinase inhibitors (TKIs) is a major cause of treatment failure in metastatic renal cell carcinoma (mRCC). A deeper understanding of the metabolic mechanisms associated with TKI resistance is critical for refining therapeutic strategies. In this study, we established resistance to sunitinib and pazopanib by exposing a parental Caki-1 cell line to increasing concentrations of sunitinib and pazopanib. The intracellular and extracellular metabolome of sunitinib- and pazopanib-resistant mRCC cells were investigated using a nuclear magnetic resonance (NMR)-based metabolomics approach. Data analysis included multivariate and univariate methods, as well as pathway and network analyses. Distinct metabolic signatures in sunitinib- and pazopanib-resistant RCC cells were found for the first time in this study. A common metabolic reprogramming pattern was observed in amino acid, glycerophospholipid, and nicotinate and nicotinamide metabolism. Sunitinib-resistant cells exhibited marked alterations in metabolites involved in antioxidant defence mechanisms, while pazopanib-resistant cells showed alterations in metabolites associated with energy pathways. Sunitinib-resistant RCC cells demonstrated an increased ability to proliferate, whereas pazopanib-resistant cells appeared to restructure their energy metabolism and undergo alterations in pathways associated with cell death. These findings provide potential targets for novel therapeutic strategies to overcome TKI resistance in mRCC through metabolic regulation.

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.

Unveiling the hidden role of disulfidptosis in kidney renal clear cell carcinoma: a prognostic signature for personalized treatment

The role of disulfidptosis in kidney renal clear cell carcinoma (KIRC) remains unknown. This study investigated disulfidptosis-related biomarkers for KIRC prognosis prediction and individualized treatment. KIRC patients were clustered by disulfidptosis profiles. Differential expression analysis, survival models, and machine learning were used to construct the disulfidptosis-related prognostic signature (DRPS). Characterizations of the tumor immune microenvironment, genetic drivers, drug sensitivity, and immunotherapy response were explored according to the DRPS risk stratification. Markers included in the signature were validated using single-cell, spatial transcriptomics, quantitative RT-qPCR, and immunohistochemistry. In the discovery cohort, we unveiled two clusters of KIRC patients that differed significantly in disulfidptosis regulator expressions and overall survival (OS). After multiple feature selection steps, a DRPS prognostic model with four features (CHAC1, COL7A1, FOXM1, SHOX2) was constructed and validated. Combined with clinical factors, the model demonstrated robust performance in the discovery and external validation cohorts (5-year AUC = 0.793 and 0.846, respectively). KIRC patients with high-risk scores are characterized by inferior OS, less tumor purity, and increased infiltrations of fibroblasts, M1 macrophages, and B cells. High-risk patients also have higher frequencies of BAP1 and AHNAK2 mutation. Besides, the correlation between the DRPS score and the chemotherapy-response signature indicated the potential effect of Gefitinib for high-risk patients. Among the signature genes, FOXM1 is highly expressed in cycling tumor cells and exhibits spatial aggregation, while others are expressed sparsely within tumor samples. The DRPS model enables improved clinical management and personalized KIRC therapy. The identified biomarkers and immune characteristics offer new mechanistic insight into disulfidptosis in KIRC.

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.

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.

TRIM26 inhibits clear cell renal cell carcinoma progression through destabilizing ETK and thus inactivation of AKT/mTOR signaling

BACKGROUND

Tripartite motif-containing 26 (TRIM26), a member of the TRIM protein family, exerts dual function in several types of cancer. Nevertheless, the precise role of TRIM26 in clear cell renal cell carcinoma (ccRCC) has not been investigated.

METHODS

The expression of TRIM26 in ccRCC tissues and cell lines were examined through the use of public resources and experimental validation. The impacts of TRIM26 on cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) process were determined via CCK-8, colony formation, EdU incorporation, wound healing, Transwell invasion, Western blot, and Immunofluorescence assays. RNA-seq followed by bioinformatic analyses were used to identify the downstream pathway of TRIM26. The interaction between TRIM26 and ETK was assessed by co-immunoprecipitation, qRT-PCR, Western blot, cycloheximide (CHX) chase, and in vivo ubiquitination assays.

RESULTS

We have shown that TRIM26 exhibits a downregulation in both ccRCC tissues and cell lines. Furthermore, this decreased expression of TRIM26 is closely linked to unfavorable overall survival and diseases-free survival outcomes among ccRCC patients. Gain- and loss-of-function experiments demonstrated that increasing the expression of TRIM26 suppressed the proliferation, migration, invasion, and EMT process of ccRCC cells. Conversely, reducing the expression of TRIM26 had the opposite effects. RNA sequencing, coupled with bioinformatic analysis, revealed a significant enrichment of the mTOR signaling pathway in the control group compared to the group with TRIM26 overexpression. This finding was then confirmed by a western blot assay. Subsequent examination revealed that TRMI26 had a direct interaction with ETK, a non-receptor tyrosine kinase. This interaction facilitated the ubiquitination and degradation of ETK, resulting in the deactivation of the AKT/mTOR signaling pathway in ccRCC. ETK overexpression counteracted the inhibitory effects of TRIM26 overexpression on cell proliferation, migration, and invasion.

CONCLUSION

Our results have shown a novel mechanism by which TRIM26 hinders the advancement of ccRCC by binding to and destabilizing ETK, thus leading to the deactivation of AKT/mTOR signaling. TRIM26 shows promise as both a therapeutic target and prognostic biomarker for ccRCC patients.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Identification of novel snoRNA-based biomarkers for clear cell renal cell carcinoma from urine-derived extracellular vesicles

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising.

METHODS

RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models.

RESULTS

An initial cluster analysis of RNA-seq expression data showed separation by the subjects' gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091).

CONCLUSIONS

Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

Background

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

Methods

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

Results

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

Conclusions

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

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

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

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

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

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.

VDRA downregulate β-catenin/Smad3 and DNA damage and repair associated with improved prognosis in ccRCC patients

The clear cell renal cell carcinoma (ccRCC) spotlighted the poorest survival, while chromophobe renal cell carcinoma (chRCC) was associated with the best survival. Earlier studies corroborated vitamin D receptor (VDR) was a promising molecular for improving the prognosis of RCC. In contrast to VDRA, the one of VDR isoforms, VDRB1 (VDR isoform B1) has an N-terminal extension of 50 amino acids and is less ligand-dependent. However, the functional differences between VDRA and VDRB1, and their roles in the prognosis of ccRCC and chRCC, have not been investigated. In the present study, we uncovered that the transcripts related to vitamin D pathway and cellular calcium signaling were effectively decreased in the context of ccRCC, yet failed to exert a comparable effect within chRCC. Specially, minimally levels of VDRA wherein kidneys of patients suffering from ccRCC predict shorter survival time. In addition, the protein expressions for β-catenin/Smad3 pathway and DNA damage and repair pathways were obviously impeded in VDRA-overexpressed ccRCC cells, yet this inhibitory effect was conspicuously absent in enable VDRB1 cells. Our results provide a new idea to improve the prognosis of ccRCC via VDRA upregulation.

Implications of MTHFD2 expression in renal cell carcinoma aggressiveness

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

Background

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

Methods

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

Results

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

Conclusions

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

Establishment and validation of a novel peroxisome-related gene prognostic risk model in kidney clear cell carcinoma

BACKGROUND

Kidney clear cell carcinoma (KIRC) is the most common subtype of renal cell carcinoma. Peroxisomes play a role in the regulation of tumorigenesis and cancer progression, yet the prognostic significance of peroxisome-related genes (PRGs) remains rarely studied. The study aimed to establish a novel prognostic risk model and identify potential biomarkers in KIRC.

METHODS

The significant prognostic PRGs were screened through differential and Cox regression analyses, and LASSO Cox regression analysis was performed to establish a prognostic risk model in the training cohort, which was validated internally in the testing and entire cohorts, and further assessed in the GSE22541 cohort. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the function and pathway differences between the high-risk and low-risk groups. The relationship between risk score and immune cell infiltration levels was evaluated in the CIBERSORT, ESTIMATE and TIMER databases. Finally, potential biomarkers were identified and validated from model genes, using immunohistochemistry.

RESULTS

Fourteen significant prognostic PRGs were identified using multiple analyses, and 9 genes (ABCD1, ACAD11, ACAT1, AGXT, DAO, EPHX2, FNDC5, HAO1, and HNGCLL1) were obtained to establish a prognostic model via LASSO Cox regression analysis. Combining the risk score with clinical factors to construct a nomogram, which provided support for personalized treatment protocols for KIRC patients. GO and KEGG analyses highlighted associations with substance metabolism, transport, and the PPAR signaling pathways. Tumor immune infiltration indicated immune suppression in the high-risk group, accompanied by higher tumor purity and the expression of 9 model genes was positively correlated with the level of immune cell infiltration. ACAT1 has superior prognostic capabilities in predicting the outcomes of KIRC patients.

CONCLUSIONS

The peroxisome-related prognostic risk model could better predict prognosis in KIRC patients.

Metabolomic profiling of human bladder tissue extracts

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Management of Pediatric Urolithiasis in an Italian Tertiary Referral Center: A Retrospective Analysis

Background and Objectives: In recent years, the prevalence of pediatric urolithiasis has increased in North America and Western countries, though it is endemic in developing countries. The aim of this study is to describe the experience of a tertiary pediatric referral center in the surgical management of pediatric urolithiasis. Materials and Methods: We retrospectively reviewed the experience of patients ≤ 16 years old affected by urinary stones who underwent surgery. Results: From April 2021 to September 2023, 31 pediatric patients underwent surgical procedures for stone diseases at our department: 13 preschool-aged (1-5 years) and 18 school-aged (6-16 years) children. During this period, 12 URSs, 17 RIRSs, and 2 PCNLs were recorded. Five patients had residual fragments at first, so three of them underwent a second endourological lithotripsy (2 RIRSs and 1 URS). Complete clearance was finally achieved in 27 patients. The stone composition was evaluated in 25 cases. Conclusions: Numerous innovations in the surgical treatment of pediatric urolithiasis have resulted from the development of smaller devices and new technology. Our results show how, in experienced centers, retrograde and percutaneous lithotripsy are safe and effective procedures for use in pediatric populations.

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

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

Disturbances in Nitric Oxide Cycle and Related Molecular Pathways in Clear Cell Renal Cell Carcinoma

It is important to note that maintaining adequate levels of nitric oxide (NO), the turnover, and the oxidation level of nitrogen are essential for the optimal progression of cellular processes, and alterations in the NO cycle indicate a crucial step in the onset and progression of multiple diseases. Cellular accumulation of NO and reactive nitrogen species in many types of tumour cells is expressed by an increased susceptibility to oxidative stress in the tumour microenvironment. Clear cell renal cell carcinoma (ccRCC) is a progressive metabolic disease in which tumour cells can adapt to metabolic reprogramming to enhance NO production in the tumour space. Understanding the factors governing NO biosynthesis metabolites in ccRCC represents a relevant, valuable approach to studying NO-based anticancer therapy. Exploring the molecular processes mediated by NO, related disturbances in molecular pathways, and NO-mediated signalling pathways in ccRCC could have significant therapeutic implications in managing and treating this condition.

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

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

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

A sialyltransferases-related gene signature serves as a potential predictor of prognosis and therapeutic response for bladder cancer

BACKGROUND

Aberrant glycosylation, catalyzed by the specific glycosyltransferase, is one of the dominant features of cancers. Among the glycosyltransferase subfamilies, sialyltransferases (SiaTs) are an essential part which has close linkages with tumor-associated events, such as tumor growth, metastasis and angiogenesis. Considering the relationship between SiaTs and cancer, the current study attempted to establish an effective prognostic model with SiaTs-related genes (SRGs) to predict patients' outcome and therapeutic responsiveness of bladder cancer.

METHODS

RNA-seq data, clinical information and genomic mutation data were downloaded (TCGA-BLCA and GSE13507 datasets). The comprehensive landscape of the 20 SiaTs was analyzed, and the differentially expressed SiaTs-related genes were screened with "DESeq2" R package. ConsensusClusterPlus was applied for clustering, following with survival analysis with Kaplan-Meier curve. The overall survival related SRGs were determined with univariate Cox proportional hazards regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate a SRGs-related prognostic model. The predictive value was estimated with Kaplan-Meier plot and the receiver operating characteristic (ROC) curve, which was further validated with the constructed nomogram and decision curve.

RESULTS

In bladder cancer tissues, 17 out of the 20 SiaTs were differentially expressed with CNV changes and somatic mutations. Two SiaTs_Clusters were determined based on the expression of the 20 SiaTs, and two gene_Clusters were identified based on the expression of differentially expressed genes between SiaTs_Clusters. The SRGs-related prognostic model was generated with 7 key genes (CD109, TEAD4, FN1, TM4SF1, CDCA7L, ATOH8 and GZMA), and the accuracy for outcome prediction was validated with ROC curve and a constructed nomogram. The SRGs-related prognostic signature could separate patients into high- and low-risk group, where the high-risk group showed poorer outcome, more abundant immune infiltration, and higher expression of immune checkpoint genes. In addition, the risk score derived from the SRGs-related prognostic model could be utilized as a predictor to evaluate the responsiveness of patients to the medical therapies.

CONCLUSIONS

The SRGs-related prognostic signature could potentially aid in the prediction of the survival outcome and therapy response for patients with bladder cancer, contributing to the development of personalized treatment and appropriate medical decisions.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Identification of KIFC1 as an independent prognostic marker in renal clear cell carcinoma correlates with tumor proliferation and immune infiltration

Renal clear cell carcinoma (ccRCC) is the world's most common form of cancer. Up to a third will develop metastases; the 5-year survival rate of the patients was only 14%. Practical prognostic markers remain to be discovered. Kinesin-like protein (KIFC1), a critical factor in maintaining the stability of the microtubule system, has significant prognostic value in some tumors. We analyzed the prognostic value, associated signaling pathways, and regulatory mechanisms of KIFC1 in ccRCC through bioinformatics and proteomics. Concretely, both mRNA and protein expression levels of KIFC1 were dramatically upregulated. KIFC1 is an independent prognostic factor for ccRCC. The expression of KIFC1 showed a significant positive correlation (Spearman coefficient > 0.7) with tumor proliferation-related pathways (tumor proliferation, G2/M checkpoint, and DNA replication) and tumor inflammation. Further, intratumoral immune cell analysis revealed that high expression of KIFC1 predicted more infiltration of CD8 + T and CD4 + T cells (p < 0.001). However, there was a significant positive relationship between CD8 + T cells and numerous immune checkpoint genes. CD8 + T cells in tumors from the KIFC1 high expression group were at the dysregulated state. High expression of KIFC1 may predict a poor immunotherapy outcome. By proteomics, we analyzed proteins interacting with KIFC1; spliceosome proteins had the most significant enrichment, indicating the new directions for KIFC1 investigation. In conclusion, our study identified KIFC1 as an independent prognostic factor in renal clear cell carcinoma, and the associated processes involved tumor proliferation and immune infiltration. KIFC1 had a close relationship with spliceosome proteins; it may be a new research direction.

A systematic review of robot-assisted partial nephrectomy outcomes for advanced indications: Large tumors (cT2-T3), solitary kidney, completely endophytic, hilar, recurrent, and multiple renal tumors

Objective

Robot-assisted partial nephrectomy (RAPN) has become widely used for treatment of renal cell carcinoma and it is expanding in the field of complex renal masses. The aim of this systematic review was to analyze outcomes of RAPN for completely endophytic renal masses, large tumors (cT2-T3), renal cell carcinoma in solitary kidney, recurrent tumors, completely endophytic and hilar masses, and simultaneous and multiple tumors.

Methods

A comprehensive search in the PubMed, Scopus, Web of Science, and Cochrane Central Register of Controlled Trials databases was performed in December 2022 for English language papers. The primary endpoint was to evaluate the role of RAPN in the setting of each category of complex renal masses considered. The secondary endpoint was to evaluate the surgical and functional outcomes.

Results

After screening 1250 records, 43 full-text manuscripts were selected, comprising over 8500 patients. Twelve and thirteen studies reported data for endophytic and hilar renal masses, respectively. Five and three studies reported outcomes for cT2-T3 and solitary kidney patients, respectively. Four studies focused on redo-RAPN for recurrent tumors. Two studies investigated simultaneous bilateral renal masses and five reports focused on multiple tumor excision in ipsilateral kidney.

Conclusion

Over the past decade, evidence supporting the use of RAPN for the most challenging nephron-sparing surgery indications has continuously grown. Although limitations remain including study design and lack of detailed long-term functional and oncological outcomes, the adoption of RAPN for the included advanced indications is associated with favorable surgical outcomes with good preservation of renal function without compromising the oncological result. Certainly, a higher likelihood of complication might be expected when facing extremely challenging cases. However, none of these indications should be considered per se an exclusion criterion for performing RAPN. Ultimately, a risk-adapted approach should be employed.

ENO2 as a Biomarker Regulating Energy Metabolism to Promote Tumor Progression in Clear Cell Renal Cell Carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common and metastatic type of renal cell carcinoma. Despite significant advancements, the current diagnostic biomarkers for ccRCC lack the desired specificity and sensitivity, necessitating the identification of novel biomarkers and elucidation of their underlying mechanisms.

METHODS

Three gene expression profile datasets were obtained from the GEO database, and differentially expressed genes (DEGs) were screened. Gene Ontology and KEGG pathway analysis were conducted in ccRCC. To clarify the diagnosis and prognostic role of ENO2, Kaplan-Meier analysis and Cox proportional hazards regression analysis were performed. Functional experiments were also carried out to verify the significant role of ENO2 in ccRCC. Finally, tumor mutational burden analysis was utilized to investigate the potential role of ENO2 in gene mutations in ccRCC.

RESULTS

The study showed that ENO2 is a potential biomarker for the diagnosis of ccRCC and can independently predict the clinical prognosis of ccRCC. Furthermore, we found that ENO2 can promote the occurrence and progression of ccRCC by affecting the glycolysis level of cells through the "Warburg effect".

CONCLUSIONS

These findings provide new theories for the occurrence and development of ccRCC and can help formulate new strategies for its diagnosis and treatment.