Metabolic reprogramming in clear cell renal cell carcinoma

Proteomics Characterization of Clear Cell Renal Cell Carcinoma

PURPOSE

To explore the tumor proteome of patients diagnosed with localized clear cell renal cancer (ccRCC) and treated with surgery.

MATERIAL AND METHODS

A total of 165 FFPE tumor samples from patients diagnosed with ccRCC were analyzed using DIA-proteomics. Proteomics ccRCC subtypes were defined using a consensus cluster algorithm (CCA) and characterized by a functional approach using probabilistic graphical models and survival analyses.

RESULTS

We identified and quantified 3091 proteins, including 2026 high-confidence proteins. Two proteomics subtypes of ccRCC (CC1 and CC2) were identified by CC using the high-confidence proteins only. Characterization of molecular differences between CC1 and CC2 was performed in two steps. First, we defined 514 proteins showing differential expression between the two subtypes using a significance analysis of microarrays analysis. Proteins overexpressed in CC1 were mainly related to translation and ribosome, while proteins overexpressed in CC2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. CC1 subtype is characterized by an increased expression of proteins related to glycolysis, mitochondria, translation, adhesion proteins related to cytoskeleton and actin, nucleosome, and spliceosome, while CC2 subtype showed higher expression of proteins involved in focal adhesion, extracellular matrix, and collagen organization.

CONCLUSIONS

ccRCC tumors can be classified in two different proteomics subtypes. CC1 and CC2 present specific proteomics profiles, reflecting alterations of different molecular pathways in each subtype. The knowledge generated in this type of studies could help in the development of new drugs targeting subtype-specific deregulated pathways.

Histone methyltransferase SETD2: An epigenetic driver in clear cell renal cell carcinoma

SET domain-containing 2 (SETD2) is a lysine methyltransferase that catalyzes histone H3 lysine36 trimethylation (H3K36me3) and has been revealed to play important roles in the regulation of transcriptional elongation, RNA splicing, and DNA damage repair. SETD2 mutations have been documented in several cancers, including clear cell renal cell carcinoma (ccRCC). SETD2 deficiency is associated with cancer occurrence and progression by regulating autophagy flux, general metabolic activity, and replication fork speed. Therefore, SETD2 is considered a potential epigenetic therapeutic target and is the subject of ongoing research on cancer-related diagnosis and treatment. This review presents an overview of the molecular functions of SETD2 in H3K36me3 regulation and its relationship with ccRCC, providing a theoretical basis for subsequent antitumor therapy based on SETD2 or H3K36me3 targets.

Treatment strategies for clear cell renal cell carcinoma: Past, present and future

Clear cell renal cell carcinoma (ccRCC) is the most prevalent histological subtype of kidney cancer, which is prone to metastasis, recurrence, and resistance to radiotherapy and chemotherapy. The burden it places on human health due to its refractory nature and rising incidence rate is substantial. Researchers have recently determined the ccRCC risk factors and optimized the clinical therapy based on the disease's underlying molecular mechanisms. In this paper, we review the established clinical therapies and novel potential therapeutic approaches for ccRCC, and we support the importance of investigating novel therapeutic options in the context of combining established therapies as a research hotspot, with the goal of providing diversified therapeutic options that promise to address the issue of drug resistance, with a view to the early realization of precision medicine and individualized treatment.

Prediction of the Prognosis of Clear Cell Renal Cell Carcinoma by Cuproptosis-Related lncRNA Signals Based on Machine Learning and Construction of ceRNA Network

Background

Clear cell renal cell carcinoma's (ccRCC) occurrence and development are strongly linked to the metabolic reprogramming of tumors, and thus far, neither its prognosis nor treatment has achieved satisfying clinical outcomes.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, respectively, provided us with information on the RNA expression of ccRCC patients and their clinical data. Cuproptosis-related genes (CRGS) were discovered in recent massive research. With the help of log-rank testing and univariate Cox analysis, the prognostic significance of CRGS was examined. Different cuproptosis subtypes were identified using consensus clustering analysis, and GSVA was used to further investigate the likely signaling pathways between various subtypes. Univariate Cox, least absolute shrinkage and selection operator (Lasso), random forest (RF), and multivariate stepwise Cox regression analysis were used to build prognostic models. After that, the models were verified by means of the C index, Kaplan-Meier (K-M) survival curves, and time-dependent receiver operating characteristic (ROC) curves. The association between prognostic models and the tumor immune microenvironment as well as the relationship between prognostic models and immunotherapy were next examined using ssGSEA and TIDE analysis. Four online prediction websites-Mircode, MiRDB, MiRTarBase, and TargetScan-were used to build a lncRNA-miRNA-mRNA ceRNA network.

Results

By consensus clustering, two subgroups of cuproptosis were identified that represented distinct prognostic and immunological microenvironments.

Conclusion

A prognostic risk model with 13 CR-lncRNAs was developed. The immune microenvironment and responsiveness to immunotherapy are substantially connected with the model, which may reliably predict the prognosis of patients with ccRCC.

Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma

Background

Mitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them.

Methods

Target genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC).

Results

We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes (CENPA, TIMP1, and MYCN) as potential therapeutic targets, of which MYCN is a novel biomarker. Additionally, the nomogram performed well in both TCGA (1-year AUC=0.862) and E-MTAB-1980 cohorts (1-year AUC=0.909).

Conclusions

Our model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.

Multi-Omics Approach Reveals Redox Homeostasis Reprogramming in Early-Stage Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a malignant tumor originating from proximal tubular epithelial cells, and despite extensive research efforts, its redox homeostasis characteristics and protein S-nitrosylation (or S-nitrosation) (SNO) modification remain largely undefined. This serves as a reminder that the aforementioned features demand a comprehensive inspection. We collected tumor samples and paracancerous normal samples from five patients with early-stage ccRCC (T1N0M0) for proteomic, SNO-proteome, and redox-targeted metabolic analyses. The localization and functional properties of SNO proteins in ccRCC tumors and paracancerous normal tissues were elucidated for the first time. Several highly useful ccRCC-associated SNO proteins were further identified. Metabolic reprogramming, redox homeostasis reprogramming, and tumorigenic alterations are the three major characteristics of early-stage ccRCC. Peroxidative damage caused by rapid proliferation coupled with an increased redox buffering capacity and the antioxidant pool is a major mode of redox homeostasis reprogramming. NADPH and NADP⁺, which were identified from redox species, are both effective biomarkers and promising therapeutic targets. According to our findings, SNO protein signatures and redox homeostasis reprogramming are valuable for understanding the pathogenesis of ccRCC and identifying novel topics that should be seriously considered for the diagnosis and precise therapy of ccRCC.

Higher TYROBP and lower SOX6 as predictive biomarkers for poor prognosis of clear cell renal cell carcinoma: A pilot study

BACKGROUND

Clear cell renal carcinoma (ccRCC) is the most common subtype of renal cancer, accounting for approximately 75% of all histological types of renal cancer, and is the leading cause of death from renal cancer. However, the molecular mechanism of tyrosine kinase binding protein (TYROBP) and sex-determining region Y Box-6 (SOX6) in the ccRCC was not precise.

METHODS

Bioinformatics analysis was performed to explore the hub role of TYROBP and SOX6 on the ccRCC. A total of 6 patients with clear cell renal cell carcinoma (ccRCC) were recruited. HE staining was performed to observe the pathology result of ccRCC. Immunohistochemistry and Immunofluorescence assay was made to detect the protein expression of TYROBP. Total RNA was extracted using TRIzol to examine the mRNA expression of TYROBP via the Real time quantitative polymerase chain reaction. The strong correlation between the expression of TYROBP and the survival time of ccRCC patients was performed by the BP neural network and support vector machine.

RESULTS

Compared with the control group, the expression of SOX6 was downregulated in the samples with ccRCC. However, the expression of TYROBP was higher in the samples with ccRCC than in the control group. Compared with the patients with high SOX6 expression, the patients with low SOX6 expression have a poor survival prognosis (HR=0.39, P < .05). However, the patients with high TYROBP expression have a shorter survival time than the patients with low TYROBP expression (HR=1.66, P < .05). The genes related with TYROBP and SOX6 are mainly enriched in the regulation of cell activation, leukocyte activation, negative regulation of cell activation, myeloid leukocyte activation, positive regulation of response to external stimulus, immune response-regulating signaling pathway. The interaction between TYROBP, SOX6, and kidney neoplasms was drawn, and the inference score of TYROBP and SOX6 on the kidney neoplasms was high.

CONCLUSION

In conclusion, TYROBP is highly expressed in renal clear cell carcinoma, and when this molecule is highly expressed, the survival prognosis of renal carcinoma is poor. TYROBP and SOX6 may be potential targets for diagnosing and treating renal clear cell carcinoma.

Dynamic partitioning of branched-chain amino acids-derived nitrogen supports renal cancer progression

Metabolic reprogramming is critical for tumor initiation and progression. However, the exact impact of specific metabolic changes on cancer progression is poorly understood. Here, we integrate multimodal analyses of primary and metastatic clonally-related clear cell renal cancer cells (ccRCC) grown in physiological media to identify key stage-specific metabolic vulnerabilities. We show that a VHL loss-dependent reprogramming of branched-chain amino acid catabolism sustains the de novo biosynthesis of aspartate and arginine enabling tumor cells with the flexibility of partitioning the nitrogen of the amino acids depending on their needs. Importantly, we identify the epigenetic reactivation of argininosuccinate synthase (ASS1), a urea cycle enzyme suppressed in primary ccRCC, as a crucial event for metastatic renal cancer cells to acquire the capability to generate arginine, invade in vitro and metastasize in vivo. Overall, our study uncovers a mechanism of metabolic flexibility occurring during ccRCC progression, paving the way for the development of novel stage-specific therapies.

A Novel Cuproptosis-Related Prognostic Model and the Hub Gene FDX1 Predict the Prognosis and Correlate with Immune Infiltration in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is a common malignancy of the urological system with poor prognosis. Cuproptosis is a recently discovered novel manner of cell death, and the hub gene FDX1 could promote cuproptosis. However, the potential roles of cuproptosis-related genes (CRGs) and FDX1 for predicting prognosis, the immune microenvironment, and therapeutic response have been poorly studied in ccRCC. In the present study, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data were downloaded. CRGs were subjected to prognosis analysis, and three of them were used to construct the prognostic model by least absolute shrinkage and selection operator (LASSO) regression. The CRGs prognostic model showed excellent performance. Moreover, based on the risk score of the model, the nomogram was developed to predict 1-year, 3-year, and 5-year survival. Furthermore, the hub gene of cuproptosis, FDX1, was an independent prognostic biomarker in multivariate Cox regression analysis. The pan-cancer analysis showed that FDX1 was significantly downregulated and closely related to prognosis in ccRCC among 33 cancer types. Lower FDX1 was also correlated with worse clinicopathologic features. The lower expression of FDX1 in ccRCC was verified in the external database and our own database, which may be caused by DNA methylation. We further demonstrated that the tumor mutational burden (TMB) and immune cell infiltration were related to the expression of FDX1. Immune response and drug sensitivity analysis revealed that immunotherapy or elesclomol may have a favorable treatment effect in the high FDX1 expression group and sunitinib or axitinib may work better in the low FDX1 expression group. In conclusion, we constructed a CRGs prognostic model and revealed that FDX1 could serve as a prognostic biomarker and predict therapeutic response in ccRCC. The study will provide a novel, precise, and individual treatment strategy for ccRCC patients.

Biochemical and clinical effects of RPS20 expression in renal clear cell carcinoma

Renal cell carcinoma (RCC) remains one of the most lethal urinary tumors in East Asia despite great advancements in treatment strategies in recent years. Ribosomal protein S20 (RPS20) is considered a new oncogene; however, little information is available on its expression, regulation and biological function in patients with RCC. In the present study, 43 pairs of human RCC and neighboring normal renal tissues were examined for protein expression and immunohistochemistry examination of RPS20. Lentiviral transduction was also employed to create RPS20 knockdown cell lines for downstream cellular experiments. MTT, flow cytometry, wound healing, colony formation and invasion assays were used to examine how RPS20 affected kidney renal clear cell carcinoma (KIRC) cell behavior. Western blotting was used to detect cycle‑related proteins (CDK4 and cyclin D1), Wnt‑related proteins (N‑cadherin and E‑cadherin) and signaling proteins [phosphorylated (p)‑AKT and p‑ERK]. The functions of RPS20 in vivo were examined in 786‑O cells with RPS20 knockdown. RPS20 was significantly overexpressed in tumor tissues compared with its expression in the corresponding normal tissues. RPS20 expression was linked to tumor stage, differentiation grade, tumor size and lymph node metastasis, and it had an independent prognostic value in KIRC. Since RCC cell proliferation, migration and invasion were suppressed when RPS20 was knocked down, the formation of renal tumors in vivo was markedly slowed down. In RPS20 knockdown cell lines, CDK4, cyclin D1 and E‑cadherin were downregulated, while N‑cadherin expression was increased. RPS20 was also observed to be involved in controlling the activation of the ERK and mTOR signaling pathways. In summary, the present study showed that RPS20 increased cell proliferation in RCC by activating the AKT‑mTOR and ERK‑MAPK signaling pathways, which suggests that RPS20 may be a therapeutic and prognostic target for RCC.

Hadh deficiency induced oligoasthenoteratozoospermia through the TNF-α/Bcl-2 pathway in male mice

The process of spermatogenesis is a complex and delicate process that is still not fully understood. In this study, we examined the role of fatty acid oxidase 3-hydroxy acyl CoA dehydrogenase (HADH) in maintaining normal spermatogenesis in mice. In male mice, ablation of the Hadh gene using CRISPR/Cas9 technology arrested spermatocyte meiosis, increased multinucleated giant germ cells and vacuoles in seminiferous tubules, and accompanied with acrosomal dysplasia. Hadh^-/- male mice showed the typical features of oligoasthenoteratozoospermia (OAT), including decreased sperm concentration and motility and increased sperm abnormalities. Next, we explored the molecular events in the testes of the mutant mice. We found fatty acids accumulated in the testis of Hadh^-/- mice. And also, inflammatory factors TNF-α, IL-1β, and IL-6 were significantly increased, apoptosis-related protein Bcl-2 was decreased, and Bax and cleaved-Caspase3 were increased in Hadh^-/- male mice testis. After using etanercept, a specific inhibitor of TNF-α, testis injury caused by Hadh knockout was significantly alleviated, the sperm quality and motility were improved, and germ cell apoptosis was reduced. So our study demonstrated that Hadh deletion caused an increase in fatty acids. The accumulated fatty acids further induced testicular inflammation and germ cell apoptosis through the TNF-α/Bcl-2 signaling pathway, finally resulting in OAT in the Hadh^-/- mice. Inhibiting TNF-α may be used as a new treatment approach for testicular inflammation and OAT.

Integrative analysis indicates the prognostic value of circadian rhythm disruption in liver cancer: Potential for therapeutic targeting

Circadian rhythms regulate various biological processes, such as cell division and metabolism. Circadian rhythm disruption (CRD) is often associated with malignant tumor progression and poor prognosis. However, the effect of CRD on liver cancer prognosis has not been systematically analyzed or fully elucidated. Here, we developed a method to quantify and assess intratumoral CRD in a single-cell transcriptomic analysis of liver cancer and systematically analyzed the role of CRD in tumor progression and prognosis. Furthermore, a LASSO-Cox regression model based on 14 CRD genes was used to predict overall patient survival across multiple datasets. We found that malignant cells with high CRD scores were enriched in specific metabolic pathways, such as fatty acid metabolism and the trichloroacetic acid cycle. Intercellular communication analysis suggested that CRD regulates chemokine-mediated interactions. With the bulk transcriptomic datasets, we determined that LiverCRD scores were significantly correlated with macrophage infiltration levels and could guide targeted immunotherapy and chemotherapy strategies. In addition, LiverCRD is also associated with the mutational landscape-for example, TP53 mutation frequency was higher in high-CRD samples. Finally, the 14-gene-based LASSO-Cox regression model could accurately predict overall patient survival across datasets. In conclusion, Our proposed analysis reflects the relationship between CRD and the immune environment in liver cancer, suggesting that CRD may serve as a potential prognostic indicator. Our results may help guide targeted anti-tumor strategies.

LTB4R Promotes the Occurrence and Progression of Clear Cell Renal Cell Carcinoma (ccRCC) by Regulating the AKT/mTOR Signaling Pathway

ccRCC is highly immunogenic, yet its underlying immune-related molecular mechanisms are unknown. Leukotriene B4 Receptor 1 (LTB4R), a novel immune-related gene associated in our previous research with the prognosis of ccRCC patients, has been found in many cancers; however, its potential mechanism in renal clear carcinoma is unclear. This study was conducted to investigate LTB4R's action mechanism in renal clear cell carcinoma. First, a CCK8 assay was performed to verify LTB4R's effect on the proliferation viability of renal clear cell carcinoma cells. Scratch and transwell assays verified LTB4R's effect on the migration and invasion ability of renal clear cell carcinoma cells. Flow cytometry validated LTB4R's effect on renal clear cell carcinoma cells' apoptosis and cell cycle. A Western blot assay was conducted to further investigate LTB4R's effect on apoptosis, cell cycle, EMT process, and AKT/mTOR signaling pathway in renal clear cell carcinoma at the protein level. In vitro experiments showed that LTB4R knockdown inhibited the proliferation, migration, and invasion of renal clear cell carcinoma cells and promoted their apoptosis, whereas LTB4R overexpression promoted the proliferation, migration, and invasion of renal clear cell carcinoma cells and inhibited their apoptosis. In addition, we found that LTB4R regulated the proliferation and apoptosis of renal clear cell carcinoma cells by regulating the AKT/mTOR signaling pathway's phosphorylation process. Furthermore, we verified some of these results using bioinformatic analysis. LTB4R plays an oncogenic role in renal clear cell carcinoma; it is expected to be a molecular target for renal clear cell carcinoma treatment and a predictive biomarker for prognosis.

Integrated Analysis of the Role of Enolase 2 in Clear Cell Renal Cell Carcinoma

Enolase 2 (ENO2) has increasingly been documented in multiple cancers in recent years. However, the role of ENO2 in clear cell renal carcinoma (ccRCC) has not been fully explored. In the present study, open-access data were downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the Human Protein Atlas (HPA) databases. All statistical analyses were performed in R and GraphPad Prism 8 softwares. Results showed that ENO2 was overexpressed in ccRCC tissues and cell lines and correlated with worse clinical features and prognosis. In vitro experiments indicated that the inhibition of ENO2 could hamper the malignant behaviors of ccRCC cells. Gene Set Enrichment Analysis showed that epithelial-mesenchymal transition, KRAS signaling, inflammatory response, angiogenesis, hypoxia, and WNT/β-catenin pathways were upregulated in the ENO2 high-expression group; whereas adipogenesis, DNA repair, and androgen response pathways were downregulated. Immune infiltration analysis indicated that patients with high ENO2 levels might have higher M2 macrophages and lower γβ T cells in the tumor microenvironment, which may account to some extent for the worse prognosis of ENO2. Moreover, it was found that patients with low and high ENO2 expression might be more sensitive to PD-1 therapy and CTLA-4 therapy, respectively. In addition, patients with high ENO2 expression showed lower sensitivity to common chemotherapy drugs for ccRCC, including axitinib, cisplatin, gemcitabine, pazopanib, sunitinib, and temsirolimus. Overall, these results suggest that ENO2 is a potential prognosis biomarker of ccRCC and could affect the malignant biological behavior of cancer cells, highlighting its value as a potential therapeutic target.

The Versatile Role of miR-21 in Renal Homeostasis and Diseases

MicroRNAs (miRNAs) are small, non-coding RNA species that control gene expression and confer robustness to biological processes. Over the last two decades, their important roles during kidney development, homeostasis and the treatment of diseases have been established, in particular during the onset and progression of various forms of acute and chronic renal disorders. In recent years, miR-21, one of the best-characterized miRNAs to date, has received much attention in renal physiology in particular given its high degree of conservation and expression in kidneys, as well as its potent pathogenic role in various debilitating renal diseases. This review summarizes the current knowledge on miR-21’s involvement in both renal homeostasis and diseases, in particular its double-edged-sword role in acute versus chronic kidney injuries. Finally, we also discuss the potential of miR-21 as a biomarker and therapeutic target in renal diseases.

Targeting Mitochondrial Metabolism to Reverse Radioresistance: An Alternative to Glucose Metabolism

Radiotherapy failure and poor tumor prognosis are primarily attributed to radioresistance. Improving the curative effect of radiotherapy and delaying cancer progression have become difficult problems for clinicians. Glucose metabolism has long been regarded as the main metabolic process by which tumor cells meet their bioenergetic and anabolic needs, with the complex interactions between the mitochondria and tumors being ignored. This misconception was not dispelled until the early 2000s; however, the cellular molecules and signaling pathways involved in radioresistance remain incompletely defined. In addition to being a key metabolic site that regulates tumorigenesis, mitochondria can influence the radiation effects of malignancies by controlling redox reactions, participating in oxidative phosphorylation, producing oncometabolites, and triggering apoptosis. Therefore, the mitochondria are promising targets for the development of novel anticancer drugs. In this review, we summarize the internal relationship and related mechanisms between mitochondrial metabolism and cancer radioresistance, thus exploring the possibility of targeting mitochondrial signaling pathways to reverse radiation insensitivity. We suggest that attention should be paid to the potential value of mitochondria in prolonging the survival of cancer patients.

A pan-cancer analysis of the role of hexokinase II (HK2) in human tumors

More and more evidence show that HK2 is closely related to tumors. But no pan-cancer analysis is available. This paper aimed to explore the potential roles of HK2 across thirty-three tumors based on the datasets of the cancer genome Atlas (TCGA) and gene expression omnibus. HK2 is highly expressed in most tumors and related to the progression of some tumors. HK2 expression was associated with the infiltration of T follicular helper cells for the TCGA tumors of uveal melanoma, breast invasive carcinoma (BRCA), breast invasive carcinoma-luminalA (BRCA-LumA), head and neck squamous cell carcinoma (HNSC), head and neck squamous cell carcinoma with HPV positive (HNSC-HPV⁺), and cancer-associated fibroblasts for the tumors of brain lower grade glioma and stomach adenocarcinoma. Our first pan-cancer study offers a relatively comprehensive understanding of the roles of HK2 in different tumors.

Integrated analysis of transcriptomics, proteomics and metabolomics data reveals the role of SLC39A1 in renal cell carcinoma

Purpose: Accumulating evidence suggests that solute carrier family 39 member 1 (SLC39A1) conceivably function as a tumor suppressor, but the underlying mechanism in renal cell carcinoma (RCC) is poorly understood. Methods: OSRC-2 renal cancer cells were first transfected with SLC39A1 overexpressed vectors and empty vectors and then used in transcriptomics, proteomics, and metabolomics integrated analyses. Results: SLC39A1 significantly altered several metabolisms at transcriptional, protein and metabolic levels, including purine and pyrimidine metabolism, amino acids and derivatives metabolism, lactose metabolism, and free fatty acid metabolism. Additionally, SLC39A1 could promote ferroptosis, and triggered significant crosstalk in PI3K-AKT signal pathway, cAMP signal pathway, and peroxisome proliferators-activated receptor (PPAR) signal pathway. Conclusion: We found SLC39A1 transfection impaired tumor metabolism and perturbed tumor metabolism-related pathways, which was a likely cause of the alteration in cell proliferation, migration, and cell cycle progression in RCC cells. These multi-omics analyses results provided both a macroscopic picture of molecular perturbation by SLC39A1 and novel insights into RCC tumorigenesis and development.

Lysosomal-Associated Transmembrane Protein 5 Promotes Proliferation, Migration, and Invasion of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most aggressive and deadly cancer of the urinary system and is regulated by multiple signaling pathways. However, the specific molecular mechanisms underlying ccRCC have not been fully studied or demonstrated. This study aimed to elucidate the function of lysosomal-associated transmembrane protein 5 (LAPTM5) in ccRCC cell lines and animal models and determine the potential underlying mechanisms. Our results demonstrated that LAPTM5 expression in patients with ccRCC was significantly higher in the tumor group than that in the adjacent nontumor group. Moreover, LAPTM5 promoted proliferation, migration, and invasion of ccRCC cells through the gain and loss of the function of LAPTM5 in 786-0 and Caki-1 cell lines. Similar results regarding LAPTM5 overexpression were obtained in BALB/c nude mice. In addition, LAPTM5 activated the Jun N-terminal kinase (JNK)/p38 signaling cascade by interacting with Ras-related C3 botulinum toxin substrate 1 (RAC1). Treatment with an RAC1 inhibitor eliminated the effects of LAPTM5 in ccRCC. In conclusion, these results indicate that LAPTM5 may be a new therapeutic target for ccRCC via activation of the RAC1-JNK/p38 axis.

SET domain containing 2 (SETD2) influences metabolism and alternative splicing during myogenesis

Epigenetic regulatory mechanisms are increasingly recognized as crucial determinants of cellular specification and differentiation. During muscle cell differentiation (myogenesis), extensive remodelling of histone acetylation and methylation occurs. Several of these histone modifications aid in the expression of muscle-specific genes and the silencing of genes that block lineage commitment. Therefore, the identification of new epigenetic regulatory mechanisms is of high interest. Still, the functional relevance of numerous histone modifications during myogenesis remain completely uncertain. In this study, we focus on the function of H3K36me3 and its epigenetic writer, SET domain containing 2 (SETD2), in the context of muscle cell differentiation. We first observed that SETD2 expression increases during myogenesis. Targeted depletion of SETD2 in undifferentiated (myoblasts) and differentiated (myotubes) muscle cells reduced H3K36me3 levels and induced profound changes in gene expression and slight alterations in alternative splicing, as determined by deep RNA-sequencing analysis. Enzymes that function in metabolic pathways were upregulated in response to SETD2 depletion. Furthermore, we demonstrated that upregulation of several glycolytic enzymes was associated with an increase in intracellular pyruvate levels in SETD2-depleted cells, indicating a novel role for SETD2 in metabolic programming during myogenesis. Together, our results provide new insight into the signalling pathways controlled by chromatin-modifying enzymes and their associated histone modifications during muscle cell differentiation.

Metabolic signatures of immune cells in chronic kidney disease

Immune cells play a key role in maintaining renal dynamic balance and dealing with renal injury. The physiological and pathological functions of immune cells are intricately connected to their metabolic characteristics. However, immunometabolism in chronic kidney disease (CKD) is not fully understood. Pathophysiologically, disruption of kidney immune cells homeostasis causes inflammation and tissue damage via triggering metabolic reprogramming. The diverse metabolic characteristics of immune cells at different stages of CKD are strongly associated with their different pathological effect. In this work, we reviewed the metabolic characteristics of immune cells (macrophages, natural killer cells, T cells, natural killer T cells and B cells) and several non-immune cells, as well as potential treatments targeting immunometabolism in CKD. We attempt to elaborate on the metabolic signatures of immune cells and their intimate correlation with non-immune cells in CKD.

Glutamine metabolism in cancers: Targeting the oxidative homeostasis

Glutamine is the most abundant amino acid in blood and tissues, and the most important nutrient except for glucose in cancer cells. Over the past years, most studies have focused on the role of Gln metabolism in supporting energy metabolism rather than maintaining oxidative homeostasis. In fact, Gln is an important factor in maintaining oxidative homeostasis of cancer cells, especially in “Glutamine addicted” cancer cells. Here, this paper will review the recent scientific literature about the link between Gln metabolism and oxidative homeostasis, with an emphasis on the potential role of Gln metabolism in different cancers. Given that oxidative homeostasis is of critical importance in cancer, understanding the impacts of a Gln metabolism on oxidative homeostasis, gaining great insights into underlying molecular mechanisms, and developing effective therapeutic strategies are of great importance.

Short-chain L-3-hydroxyacyl-CoA dehydrogenase: A novel vital oncogene or tumor suppressor gene in cancers

The reprogramming of cellular metabolism is frequently linked to tumorigenesis. Glucose, fatty acids, and amino acids are the specific substrates involved in how an organism maintains metabolic equilibrium. The HADH gene codes for the short-chain L-3-hydroxyacyl-CoA dehydrogenase (HADH), a crucial enzyme in fatty acid oxidation that catalyzes the third phase of fatty acid oxidation in mitochondria. Increasing data suggest that HADH is differentially expressed in various types of malignancies and is linked to cancer development and progression. The significance of HADH expression in tumors and its potential mechanisms of action in the onset and progression of certain cancers are summarized in this article. The possible roles of HADH as a target and/or biomarker for the detection and treatment of various malignancies is also described here.

A Potential Fatty Acid Metabolism-Related Gene Signature for Prognosis in Clear Cell Renal Cell Carcinoma

Simple Summary

Clear Cell Renal Cell Carcinoma (ccRCC) is the most common and aggressive subtype of renal cancer. Abnormal fatty acid metabolism (FAM) is reported to be strongly associated with multiple malignancies, yet there is limited research in ccRCC. In this manuscript, we reported the significant role of abnormal FAM in predicting the prognosis of ccRCC. Three independent clinical cohorts (TCGA, EMTAB and our clinical cohorts with prognostic profiles and gene expression data, including RNA-seq, microarray and RT-qPCR) were applied as training and two external validation cohorts. As a result, we successfully constructed and validated a novel FAM-related gene signature (FAMGS) and nomogram for the overall survival of patients with ccRCC. Additionally, our study further elucidated the potential immune relevance and molecular mechanisms of abnormal FAM and the signature. In conclusion, the novel FAMGS constructed in this study offered a promising prognostic tool in clinic and potential therapeutic targets for ccRCC patients.

Abstract

This study aims to explore the role of abnormal fatty acid metabolism (FAM) in ccRCC and construct a novel fatty acid metabolism-related gene signature (FAMGS) for prognosis. Three independent ccRCC cohorts, including The Cancer Genome Atlas, E-MTAB-1980 and our clinical cohort (including RNA-seq, microarray and RT-qPCR data), were applied as training and two independent validation cohorts. Firstly, FAM levels were found to be significantly decreased in ccRCC and correlated with degrees of malignancy, confirming the pivotal role of FAM in ccRCC. Applying the least absolute shrinkage and selection operator cox regression, we established a novel FAMGS for overall survival (OS). The FAMGS divided patients into low or high-risk groups in the training cohort and were successfully validated in both the EMTAB and our clinical validation cohorts. Additionally, the FAMGS serves as an independent risk factor for OS of ccRCC. Results of the immune cell abundance identifier (ImmuCellAI) algorithm and gene set variation analysis (GSVA) revealed that patients in the high-risk group have comprehensively impaired metabolism, including lipids, amino acids and tricarboxylic acid cycle-related pathways and a more immunosuppressive tumor microenvironment. In conclusion, our study constructed and validated a novel FAMGS, which may improve the risk stratification optimization and personalized management of ccRCC.

Role of copper ionophore–induced death in immune microenvironment and clinical prognosis of ccRCC: An integrated analysis

Background: Clear cell renal cell carcinoma (ccRCC) is a malignancy with a high incidence rate and poor prognosis worldwide. Copper ionophore–induced death (CID) plays an important role in cancer progression.

Methods: One training and three validation datasets were acquired from TCGA, GEO and ArrayExpress. K-means clustering was conducted to identify the CID subtypes. The ESTIMATE and CIBERSORT algorithms were employed to illustrate the immune microenvironment of ccRCC. LASSO Cox regression was applied to construct the CID feature-based prognostic model. The immunotherapy cohort was acquired from the literature to explore the potential risk scores for predicting immunotherapy responsiveness.

Results: Two CID-related cancer subtypes of ccRCC were identified that performed different immune microenvironment characteristics and prognosis. Based on the identified subtypes, we analyzed the biological heterogeneity and constructed a gene prognostic model. The prognostic model performed well in one training dataset, three validation datasets, and different clinical pathological groups. The prognostic model has a good potential for predicting cancer immune features and immunotherapy responsiveness.

Conclusion: CID plays an important role in the tumor microenvironment progression of ccRCC. The robust gene prognostic model developed can help predict cancer prognosis, immune features, and immunotherapy responsiveness.

A new CCCH-type zinc finger-related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma patients

Background: Clear cell renal cell carcinoma (ccRCC) is the main component of renal cell carcinoma (RCC), and advanced ccRCC frequently indicates a poor prognosis. The significance of the CCCH-type zinc finger (CTZF) gene in cancer has been increasingly demonstrated during the past few years. According to studies, targeted radical therapy for cancer treatment may be a revolutionary therapeutic approach. Both lncRNAs and CCCH-type zinc finger genes are essential in ccRCC. However, the predictive role of long non-coding RNA (lncRNA) associated with the CCCH-type zinc finger gene in ccRCC needs further elucidation. This study aims to predict patient prognosis and investigate the immunological profile of ccRCC patients using CCCH-type zinc finger-associated lncRNAs (CTZFLs).

Methods: From the Cancer Genome Atlas database, RNA-seq and corresponding clinical and prognostic data of ccRCC patients were downloaded. Univariate and multivariate Cox regression analyses were conducted to acquire CTZFLs for constructing prediction models. The risk model was verified using receiver operating characteristic curve analysis. The Kaplan-Meier method was used to analyze the overall survival (OS) of high-risk and low-risk groups. Multivariate Cox and stratified analyses were used to assess the prognostic value of the predictive feature in the entire cohort and different subgroups. In addition, the relationship between risk scores, immunological status, and treatment response was studied.

Results: We constructed a signature consisting of eight CTZFLs (LINC02100, AC002451.1, DBH-AS1, AC105105.3, AL357140.2, LINC00460, DLGAP1-AS2, AL162377.1). The results demonstrated that the prognosis of ccRCC patients was independently predicted by CTZFLs signature and that the prognosis of high-risk groups was poorer than that of the lower group. CTZFLs markers had the highest diagnostic adequacy compared to single clinicopathologic factors, and their AUC (area under the receiver operating characteristic curve) was 0.806. The overall survival of high-risk groups was shorter than that of low-risk groups when patients were divided into groups based on several clinicopathologic factors. There were substantial differences in immunological function, immune cell score, and immune checkpoint expression between high- and low-risk groups. Additionally, Four agents, including ABT737, WIKI4, afuresertib, and GNE 317, were more sensitive in the high-risk group.

Conclusion: The Eight-CTZFLs prognostic signature may be a helpful prognostic indicator and may help with medication selection for clear cell renal cell carcinoma.

Cuprotosis-related signature predicts overall survival in clear cell renal cell carcinoma

Background: Cuprotosis is a new form of programmed cell death induced by copper. We explored the correlation of cuprotosis with clear cell renal cell carcinoma (ccRCC) and constructed a cuprotosis-related signature to predict the prognosis of patients with ccRCC.

Methods: The clinical and transcriptomic data of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA), cBioPortal, and GEO databases, and cuprotosis-related gene sets were contained in the previous study. A cuprotosis-related signature was developed based on data from TCGA and verified by data from cBioPortal and GEO databases. The immune cell infiltrates and the corresponding signature risk scores were investigated. Two independent cohorts of clinical trials were analyzed to explore the correlation of the signature risk score with immune therapy response.

Results: A signature containing six cuprotosis-related genes was identified and can accurately predict the prognosis of ccRCC patients. Patients with downregulated copper-induced programmed death had a worse overall survival (hazard ratio: 1.90, 95% CI: 1.39–2.59, p < 0.001). The higher signature risk score was significantly associated with male gender (p = 0.026), higher tumor stage (p < 0.001), and higher histological grade (p < 0.001). Furthermore, the signature risk score was positively correlated with the infiltration of B cells, CD8⁺ T cells, NK cells, Tregs, and T cells, whereas it was negatively correlated with eosinophils, mast cells, and neutrophils. However, no correlation between cuprotosis and response to anti-PD-1 therapy was found.

Conclusion: We established a cuprotosis signature, which can predict the prognosis of patients with ccRCC. Cuprotosis was significantly correlated with immune cell infiltrates in ccRCC.

Cuproptosis-related gene FDX1 expression correlates with the prognosis and tumor immune microenvironment in clear cell renal cell carcinoma

Background

Cuproptosis, a newly discovered form of cell death, is regulated by protein lipoylation and is related to mitochondrial metabolism. However, further research is needed to determine how the cuproptosis-related gene ferredoxin 1 (FDX1) affects the tumor immune response and its prognostic significance in clear cell renal cell carcinoma (ccRCC).

Methods

The Cancer Genome Atlas was used to screen for FDX1 gene expression in ccRCC and healthy tissue samples. The results were validated using the Gene Expression Omnibus and the Human Protein Atlas. Multivariable analysis and Kaplan-Meier survival curves were used to examine the relationship between FDX1 gene expression, clinicopathological parameters, and overall survival (OS). The protein network containing FDX1 gene interaction was constructed using the online Search Tool for the Retrieval of Interacting Genes/Proteins. The relationship between FDX1 gene expression and immune cell infiltration in ccRCC was examined using Gene Ontology, gene set enrichment analysis (GSEA), and a single-sample GSEA. Using the Gene Expression Profiling Interactive Analysis and Tumor Immune Estimation Resource databases, we investigated the relationship between FDX1 gene expression, the degree of immune cell infiltration, and the corresponding gene marker sets.

Results

ccRCC samples had significantly (p < 0.05) lower FDX1 gene expression levels than normal tissue samples. Lower FDX1 gene expression levels were strongly associated with higher cancer grades and more advanced tumor-node-metastasis stages. The findings of multivariate and univariate analyses illustrated that the OS in ccRCC patients with low FDX1 expression is shorter than in patients with high FDX1 expression (p < 0.05). Ferredoxin reductase and CYP11A1 are key proteins interacting with the FDX1 gene, and ccRCC with an FDX1 enzyme defect was associated with a low number of invading immune cells and their corresponding marker.

Conclusion

In ccRCC, decreased FDX1 expression was linked to disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration.

A signature based on chromatin regulation and tumor microenvironment infiltration in clear cell renal cell carcinoma

Aims: This research aimed to construct a signature based on chromatin regulation in localized clear cell renal cell carcinoma (ccRCC). Materials & methods: Non-negative matrix factorization clustering was performed on 438 localized ccRCC cases. The immune infiltration was generated by the single-sample gene set enrichment analysis algorithm. Survival analyses were performed using the Kaplan-Meier method, and the significance of the differences was determined using the log-rank test. The risk score was constructed based on the expression of chromatin regulators to quantify chromatin modification. Results: A score system based on chromatin modification was established. The high-risk subtype was characterized by increased tumor mutation burden, whereas a low-risk score was characterized by an increase in chromatin regulator expression and better overall survival. Conclusion: This research has constructed a signature based on chromatin regulation in localized ccRCC.

A novel marker based on necroptosis-related long non-coding RNA for forecasting prognostic in patients with clear cell renal cell carcinoma

Background: The incidence of clear cell renal cell carcinoma (ccRCC) is high and has increased gradually in recent years. At present, due to the lack of effective prognostic indicators, the prognosis of ccRCC patients is greatly affected.Necroptosis is a type of cell death, and along with cell necrosis is considered a new cancer treatment strategy. The aim of this study was to construct a new marker for predicting the prognosis of ccRCC patients based on long non-coding RNA (nrlncRNAs) associated with necroptosis.

Methods: RNA sequence data and clinical information of ccRCC patients from the Cancer Genome Atlas database (TCGA) were downloaded. NrlncRNA was identified by Pearson correlation study. The differentially expressed nrlncRNA and nrlncRNA pairs were identified by univariate Cox regression and Lasso-Cox regression. Finally, a Kaplan-Meier survival study, Cox regression, clinicopathological features correlation study, and receiver operating characteristic (ROC) spectrum were used to evaluate the prediction ability of 25-nrlncrnas for markers. In addition, correlations between the risk values and sensitivity to tumor-infiltrating immune cells, immune checkpoint inhibitors, and targeted drugs were also investigated.

Results: In the current research, a novel marker of 25-nrlncRNAs pairs was developed to improve prognostic prediction in patients with ccRCC. Compared with clinicopathological features, nrlncRNAs had a higher diagnostic validity for markers, with the 1-year, 3-years, and 5-years operating characteristic regions being 0.902, 0.835, and 0.856, respectively, and compared with the stage of 0.868, an increase of 0.034. Cox regression and stratified survival studies showed that this marker could be an independent predictor of ccRCC patients. In addition, patients with different risk scores had significant differences in tumor-infiltrating immune cells, immune checkpoint, and semi-inhibitory concentration of targeted drugs. The feature could be used to evaluate the clinical efficacy of immunotherapy and targeted drug therapy.

Conclusion: 25-nrlncRNAs pair markers may help to evaluate the prognosis and molecular characteristics of ccRCC patients, which improve treatment methods and can be more used in clinical practice.

FDX1 expression predicts favourable prognosis in clear cell renal cell carcinoma identified by bioinformatics and tissue microarray analysis

Ferredoxin 1 (FDX1), an iron-sulphur protein, is responsible for electron transfer in a range of metabolic redox reactions. Clear cell renal cell carcinoma (ccRCC) is an aggressive cancer characterised by metabolic reprogramming, and FDX1 is a critical regulator of cuproptosis. However, the expression profile and prognostic value of FDX1 associated with clinicopathological features in ccRCC remain largely unelucidated. In this study, we integrated a series of public bioinformatic analysis to explore the mRNA and protein profiles of FDX1 across human cancers and cell lines and validated its expression and prognostic value, especially in ccRCC. In this study, FDX1 mRNA and protein expression were aberrantly downregulated and associated with ccRCC grade, stage, and nodal metastasis, whereas in adjacent non-tumour kidney tissue, it was abundantly expressed and cytoplasmically localised in renal tubular epithelial cells. Multivariate analysis indicated that low FDX1 expression contributed to unfavourable overall and disease-free survival. The functional enrichment of FDX1 co-expressed genes in ccRCC involved mainly mitochondrial dysfunction in various metabolic processes and biological oxidation, besides iron-sulphur cluster biogenesis. Furthermore, FDX1 modulates immunological infiltration to affect prognosis. Thus, FDX1 downregulation is mechanistically because of ccRCC tumourigenesis and is a promising prognostic biomarker to stratify patients with ccRCC.

Identification of subtypes of clear cell renal cell carcinoma and construction of a prognostic model based on fatty acid metabolism genes

Background: The effects of fatty acid metabolism in many tumors have been widely reported. Due to the diversity of lipid synthesis, uptake, and transformation in clear cell renal cell carcinoma (ccRCC) cells, many studies have shown that ccRCC is associated with fatty acid metabolism. The study aimed was to explore the impact of fatty acid metabolism genes on the prognosis and immunotherapy of ccRCC.

Methods: Two subtypes were distinguished by unsupervised clustering analysis based on the expression of 309 fatty acid metabolism genes. A prognostic model was constructed by lasso algorithm and multivariate COX regression analysis using fatty acid metabolism genes as the signatures. The tumor microenvironment between subtypes and between risk groups was further analyzed. The International Cancer Genome Consortium cohort was used for external validation of the model.

Results: The analysis showed that subtype B had a poorer prognosis and a higher degree of immune infiltration. The high-risk group had a poorer prognosis and higher tumor microenvironment scores. The nomogram could accurately predict patient survival.

Conclusion: Fatty acid metabolism may affect the prognosis and immune infiltration of patients with ccRCC. The analysis was performed to understand the potential role of fatty acid metabolism genes in the immune infiltration and prognosis of patients. These findings have implications for individualized treatment, prognosis, and immunization for patients with ccRCC.

A radiogenomics biomarker based on immunological heterogeneity for non-invasive prognosis of renal clear cell carcinoma

Background

Tumor immunological heterogeneity potentially influences the prognostic disparities among patients with clear cell renal cell carcinoma (ccRCC); however, there is a lack of macroscopic imaging tools that can be used to predict immune-related gene expression in ccRCC.

Methods

A novel non-invasive radiogenomics biomarker was constructed for immune-related gene expression in ccRCC. First, 520 ccRCC transcriptomic datasets from The Cancer Genome Atlas (TCGA) were analyzed using a non-negative matrix decomposition (NMF) clustering to identify immune-related molecular subtypes. Immune-related prognostic genes were analyzed through Cox regression and Gene Set Enrichment Analysis (GSEA). We then built a risk model based on an immune-related gene subset to predict prognosis in patients with ccRCC. CT images corresponding to the ccRCC patients in The Cancer Imaging Archive (TCIA) database were used to extract radiomic features. To stratify immune-related gene expression levels, extracted radiogenomics features were identified according to standard consecutive steps. A nomogram was built to combine radiogenomics and clinicopathological information through multivariate logistic regression to further enhance the radiogenomics model. Mann–Whitney U test and ROC curves were used to assess the effectiveness of the radiogenomics marker.

Results

NMF methods successfully clustered patients into diverse subtypes according to gene expression levels in the tumor microenvironment (TME). The relative abundance of 10 immune cell populations in each tissue was also analyzed. The immune-related genomic signature (consisting of eight genes) of the tumor was shown to be significantly associated with survival in patients with ccRCC in TCGA database. The immune-related genomic signature was delineated by grouping the signature expression as either low- or high-risk. Using TCIA database, we constructed a radiogenomics biomarker consisting of 11 radiomic features that were optimal predictors of immune-related gene signature expression levels, which demonstrated AUC (area under the ROC curve) values of 0.76 and 0.72 in the training and validation groups, respectively. The nomogram built by combining radiomics and clinical pathological information could further improve the predictive efficacy of the radiogenomics model (AUC = 0.81, 074).

Conclusions

The novel prognostic radiogenomics biomarker achieved excellent correlation with the immune-related gene expression status of patients with ccRCC and could successfully stratify the survival status of patients in TCGA database. It is anticipated that this work will assist in selecting precise clinical treatment strategies. This study may also lead to precise theranostics for patients with ccRCC in the future.

A metabolic reprogramming-related prognostic risk model for clear cell renal cell carcinoma: From construction to preliminary application

Metabolic reprogramming is one of the characteristics of clear cell renal cell carcinoma (ccRCC). Although some treatments associated with the metabolic reprogramming for ccRCC have been identified, remain still lacking. In this study, we identified the differentially expressed genes (DEGs) associated with clinical traits with a total of 965 samples via DEG analysis and weighted correlation network analysis (WGCNA), screened the prognostic metabolism-related genes, and constructed the risk score prognostic models. We took the intersection of DEGs with significant difference coexpression modules and received two groups of intersection genes that were connected with metabolism via functional enrichment analysis. Then we respectively screened prognostic metabolic-related genes from the genes of the two intersection groups and constructed the risk score prognostic models. Compared with the predicted effect of clinical grade and stage for ccRCC patients, finally, we selected the model constructed with genes of ABAT, ALDH6A1, CHDH, EPHX2, ETNK2, and FBP1. The risk scores of the prognostic model were significantly related to overall survival (OS) and could serve as an independent prognostic factor. The Kaplan-Meier analysis and ROC curves revealed that the model efficiently predicts prognosis in the TCGA-KIRC cohort and the validation cohort. Then we investigated the potential underlying mechanism and sensitive drugs between high- and low-risk groups. The six key genes were significantly linked with worse OS and were downregulated in ccRCC, we confirmed the results in clinical samples. These results demonstrated the efficacy and robustness of the risk score prognostic model, based on the characteristics of metabolic reprogramming in ccRCC, and the key genes used in constructing the model also could develop into targets of molecular therapy for ccRCC.

Development and validation of a novel necroptosis-related score to improve the outcomes of clear cell renal cell carcinoma

Necroptosis has been indicated as a key regulator of tumor progression. However, the prognostic regulatory role of necroptosis in clear cell renal cell carcinoma (ccRCC) needs to be further investigated. In this study, necroptosis-related subtypes were identified by mining the public cohort (n = 530) obtained from The Cancer Genome Atlas. By applying Principal Component Analysis (PCA), the necroptosis-related scores (N-Score) were developed to assess the prognosis procession of ccRCC. The results were further validated by an external clinical cohort (n = 116) obtained from the First Affiliated Hospital of Wenzhou Medical University. It has been found that N-Score could precisely distinguish the prognostic outcomes of patients as an independent risk factor (Hazard ratio = 4.990, 95% confidence interval (CI) = 2.007–12.403, p < 0.001). In addition, changes in N-Score were associated with differences in tumor mutational burden as well as immune infiltration characterization. Moreover, higher N-Scores were also correlated significantly molecular drug sensitivity and stronger immune checkpoint activity. Notably, the prognosis of ccRCC could be effectively guided by combining the N-Scores and external clinical indicators. In conclusion, N-Scores could be served as a robust and effective biomarker to improve the prognosis outcomes and targeted therapy of ccRCC.

Identification of an amino acid metabolism-associated gene signature predicting the prognosis and immune therapy response of clear cell renal cell carcinoma

Background

The upregulation of amino acid metabolism is an essential form of metabolic reprogramming in cancer. Here, we developed an amino acid metabolism signature to predict prognosis and anti-PD-1 therapy response in clear cell renal cell carcinoma (ccRCC).

Methods

According to the amino acid metabolism-associated gene sets contained in the Molecular Signature Database, consensus clustering was performed to divide patients into two clusters. An amino acid metabolism-associated signature was identified and verified. Immune cell infiltrates and their corresponding signature risk scores were investigated. Two independent cohorts of clinical trials were analyzed to explore the correspondence between the signature risk score and the immune therapy response.

Results

Two clusters with different amino acid metabolic levels were identified by consensus clustering. The patients in the two clusters differed in overall survival, progression-free survival, amino acid metabolic status, and tumor microenvironment. We identified a signature containing eight amino acid metabolism-associated genes that could accurately predict the prognosis of patients with ccRCC. The signature risk score was positively correlated with infiltration of M1 macrophages, CD8+ T cells, and regulatory T cells, whereas it was negatively correlated with infiltration of neutrophils, NK cells, and CD4+ T cells. Patients with lower risk scores had better overall survival but worse responses to nivolumab.

Conclusion

Amino acid metabolic status is closely correlated with tumor microenvironment, response to checkpoint blockade therapy, and prognosis in patients with ccRCC. The established amino acid metabolism-associated gene signature can predict both survival and anti-PD-1 therapy response in patients with ccRCC.

Transcriptional and metabolic remodeling in clear cell renal cell carcinoma caused by ATF4 activation and the integrated stress response (ISR)

Research has shown extensive metabolic remodeling in clear cell renal cell carcinoma (ccRCC), with increased glutathione (GSH) levels. We hypothesized that activating transcription factor-4 (ATF4) and the integrated stress response (ISR) induce a metabolic shift, including increased GSH accumulation, and that Vitamin A deficiency (VAD), found in ccRCCs, can also activate ATF4 signaling in the kidney. To determine the role of ATF4, we used publicly available RNA sequencing (RNA-seq) data sets from The Cancer Genomics Atlas. Subsequently, we performed RNA-seq and liquid chromatography-mass spectrometry-based metabolomics analysis of the murine TRAnsgenic Cancer of the Kidney (TRACK) model for early-stage ccRCC. To validate our findings, we generated RCC4 cell lines with ATF4 gene edits (ATF4-knockout [KO]) and subjected these cells to metabolic isotope tracing. Analysis of variance, the two-sided Student's t test, and gene set enrichment analysis were used (p < 0.05) to determine statistical significance. Here we show that most human ccRCC tumors exhibit activation of the transcription factor ATF4. Activation of ATF4 is concomitant with enrichment of the ATF4 gene set and elevated expression of ATF4 target genes ASNS, ALDH1L2, MTHFD2, DDIT3 (CHOP), DDIT4, TRIB3, EIF4EBP1, SLC7A11, and PPP1R15A (GADD34). Transcript profiling and metabolomics analyses show that activated hypoxia-inducible factor-1α (HIF1α) signaling in our TRACK ccRCC murine model also induces an ATF4-mediated ISR. Notably, both normoxic HIF1α signaling in TRACK kidneys and VAD in wild-type kidneys diminish amino acid levels, increase ASNS, TRIB3, and MTHFD2 messenger RNA levels, and increase levels of lipids and GSH. By metabolic isotope tracing in human RCC4 kidney cancer parental and ATF4 gene-edited (ATF4-KO) cell lines, we show that ATF4 increases GSH accumulation in part via activation of the mitochondrial one-carbon metabolism pathway. Our results demonstrate for the first time that activation of ATF4 enhances GSH accumulation, increases purine and pyrimidine biosynthesis, and contributes to transcriptional and metabolic remodeling in ccRCC. Moreover, constitutive HIF1α expressed only in murine kidney proximal tubules activates ATF4, leading to the metabolic changes associated with the ISR. Our data indicate that HIF1α can promote ccRCC via ATF4 activation. Moreover, lack of Vitamin A in the kidney recapitulates aspects of the ISR.

Characterizing the molecular heterogeneity of clear cell renal cell carcinoma subgroups classified by miRNA expression profile

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous disease that is associated with poor prognosis. Recent works have revealed the significant roles of miRNA in ccRCC initiation and progression. Comprehensive characterization of ccRCC based on the prognostic miRNAs would contribute to clinicians’ early detection and targeted treatment. Here, we performed unsupervised clustering using TCGA-retrieved prognostic miRNAs expression profiles. Two ccRCC subtypes were identified after assessing principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE), and consensus heatmaps. We found that the two subtypes are associated with distinct clinical features, overall survivals, and molecular characteristics. C1 cluster enriched patients in relatively early stage and have better prognosis while patients in C2 cluster have poor prognosis with relatively advanced state. Mechanistically, we found the differentially expressed genes (DEGs) between the indicated subgroups dominantly enriched in biological processes related to transmembrane transport activity. In addition, we also revealed a miRNA-centered DEGs regulatory network, which severed as essential regulators in both transmembrane transport activity control and ccRCC progression. Together, our work described the molecular heterogeneity among ccRCC cancers, provided potential targets served as effective biomarkers for ccRCC diagnosis and prognosis, and paved avenues to better understand miRNA-directed regulatory network in ccRCC progression.

FECH Expression Correlates with the Prognosis and Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is, by far, the most prevalent and fatal kind of kidney cancer. Ferrochelatase (FECH) is an enzyme that performs a significant function in the onset and progression of many distinct kinds of malignant tumors. Nevertheless, its predictive usefulness in renal clear cell carcinoma (RCC) has not yet been fully investigated.

Methods

FECH expression in ccRCC and healthy adjoining tissues was primarily screened utilizing data sourced from The Cancer Genome Atlas (TCGA) and subsequently validated using data from an independent cohort derived from the Gene Expression Omnibus (GEO) and the Human Protein Atlas HPA databases. The relationship among FECH expression, clinicopathological parameters, and overall survival (OS) was assessed utilizing multivariate analysis and Kaplan–Meier survival curves. Additionally, the protein networks with FECH interaction were constructed with the aid of the online Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Gene ontology (GO) analysis, and gene set enrichment analysis (GSEA) were conducted based on TCGA data, and a single-sample GSEA was utilized to explore the link between FECH expression and the infiltration status of immune cells in the tumor. The Gene Expression Profiling Interactive Analysis (GEPIA) and TIMER databases were utilized to investigate the relationships of FECH expression with the infiltrating immune cells and the matching gene marker sets.

Results

FECH expression was shown to be substantially lowered in ccRCC tumors as opposed to that observed in normal tissues (p < 0.05). Lower levels of FECH expression were shown to have a strong association with higher grades of cancer and more advanced TNM stages. The findings of multivariate and univariate analyses illustrated that the OS in patients with ccRCC with low FECH expression is shorter in contrast with that in the high FECH expression group (p < 0.05). It was discovered that CPOX and frataxin are key proteins that interact with FECH. ccRCC with FECH deficiency was linked to the lack of infiltrating immune cells and their respective marker sets, which included CD4+ T cells.

Conclusion

In ccRCC, decreased FECH expression was linked to disease progression, unfavorable prognosis, and impaired immune cell infiltration.

YTHDC1 is downregulated by the YY1/HDAC2 complex and controls the sensitivity of ccRCC to sunitinib by targeting the ANXA1-MAPK pathway

BACKGROUND

Tyrosine kinase inhibitors (TKIs) such as sunitinib are multitarget antiangiogenic agents in clear cell renal cell carcinoma (ccRCC). They are widely used in the treatment of advanced/metastatic renal cancer. However, resistance to TKIs is common in the clinic, particularly after long-term treatment. YTHDC1 is the main nuclear reader protein that binds with m6A to regulate the splicing, export and stability of mRNA. However, the specific role and corresponding mechanism of YTHDC1 in renal cancer cells are still unclear.

METHODS

The Cancer Genome Atlas (TCGA) dataset was used to study the expression of YTHDC1 in ccRCC. Cell counting kit-8 (CCK-8), wound healing, Transwell and xenograft assays were applied to explore the biological function of YTHDC1 in ccRCC. Western blot, quantitative real time PCR (RT‒qPCR), RNA immunoprecipitation PCR (RIP-qPCR), methylated RIP-qPCR (MeRIP-qPCR) and RNA sequencing (RNA-seq) analyses were applied to study the YY1/HDAC2/YTHDC1/ANXA1 axis in renal cancer cells. The CCK-8 assay and xenograft assay were used to study the role of YTHDC1 in determining the sensitivity of ccRCC to sunitinib.

RESULTS

Our results demonstrated that YTHDC1 is downregulated in ccRCC tissues compared with normal tissues. Low expression of YTHDC1 is associated with a poor prognosis in patients with ccRCC. Subsequently, we showed that YTHDC1 inhibits the progression of renal cancer cells via downregulation of the ANXA1/MAPK pathways. Moreover, we also showed that the YTHDC1/ANXA1 axis modulates the sensitivity of tyrosine kinase inhibitors. We then revealed that HDAC2 inhibitors resensitize ccRCC to tyrosine kinase inhibitors through the YY1/HDAC2 complex. We have identified a novel YY1/HDAC2/YTHDC1/ANXA1 axis modulating the progression and chemosensitivity of ccRCC.

CONCLUSION

We identified a novel YY1/HDAC2/YTHDC1/ANXA1 axis modulating the progression and chemosensitivity of ccRCC.

LAMTOR3 is a prognostic biomarker in kidney renal clear cell carcinoma

Objective

The objective of the study was to investigate the expression of LAMTOR3 in kidney renal clear cell carcinoma (KIRC) and its clinical significance.

Methods

The expression of LAMTOR3 in KIRC and its relationship with clinical features were analyzed using the UALCAN online database. The results were verified using KIRC gene chip data and clinical specimens. The prognosis of KIRC patients was analyzed with the GEPIA2 database. GO, KEGG, and GSEA analyses were conducted to analyze the possible molecular mechanism of LAMTOR3 in KIRC. Immunohistochemical (IHC) and hematoxylin and eosin (H&E) staining were used for histopathological detection.

Results

UALCAN database analysis showed that LAMTOR3 expression in KIRC was significantly lower than in normal kidney tissues and correlated with the clinical stage, pathological grade, and tumor genotype (p < .05). GSE53757 dataset analysis consistently showed that the expression of LAMTOR3 in KIRC was significantly lower than in normal kidney tissues (p < .01). GEPIA2 database analysis indicated that patients with low LAMTOR3 expression had poor overall and disease‐free survival rates. GSEA analysis suggested that LAMTOR3 positively regulated the citrate cycle and drug metabolism cytochrome P450 and negatively regulated folate biosynthesis and olfactory transduction. The expression of LAMTOR3 in KIRC was also significantly correlated with immune cell infiltration. Finally, IHC showed that LAMTOR3 expression in the KIRC tissues was lower than in the adjacent normal tissues.

Conclusion

LAMTOR3 expression is significantly lower in KIRC. LAMTOR3 may be a potential marker for KIRC diagnosis and therapy.

FBP1 /miR-24-1/enhancer axis activation blocks renal cell carcinoma progression via Warburg effect

Warburg effect is a pivotal hallmark of cancers and appears prevalently in renal cell carcinoma (RCC). FBP1 plays a negative role in Warburg effect as a rate-limiting enzyme in gluconeogenesis, yet its mechanism in RCC remains to be further characterized. Herein, we revealed that FBP1 was downregulated in RCC tissue samples and was related to the poor survival rate of RCC. Strikingly, miR-24-1 whose DNA locus is overlapped with enhancer region chr9:95084940-95087024 was closely linked with the depletion of FBP1 in RCC. Of note, miRNAs like miR-24-1 whose DNA loci are enriched with H3K27ac and H3K4me1 modifications are belonging to nuclear activating miRNAs (NamiRNAs), which surprisingly upregulate target genes in RCC through enhancer beyond the conventional role of repressing target gene expression. Moreover, miR-24-1 reactivated the expression of FBP1 to suppress Warburg effect in RCC cells, and subsequently inhibited proliferation and metastasis of RCC cells. In mechanism, the activating role of miR-24-1 was dependent on enhancer integrity by dual luciferase reporter assay and CRISPR/Cas9 system. Ultimately, animal assay in vivo validated the suppressive function of FBP1 on 786-O and ACHN cells. Collectively, the current study highlighted that activation of FBP1 by enhancer-overlapped miR-24-1 is capable of contributing to Warburg effect repression through which RCC progression is robustly blocked, providing an alternative mechanism for RCC development and as well implying a potential clue for RCC treatment strategy.

Comprehensive Analysis of HMCN1 Somatic Mutation in Clear Cell Renal Cell Carcinoma

Background: Renal cell carcinoma (RCC) is a common malignancy of the genitourinary system and clear cell renal cell carcinoma (ccRCC) is the most representative subtype. The morbidity and mortality of ccRCC have gradually risen during recent years; however, the pathogenesis and potential biomarkers remain unclear. The purpose of our study was to find out prognostic genes correlated with somatic mutation and the underlying mechanisms of HMCN1 mutation in ccRCC. Methods: Somatic mutation data of two ccRCC cohorts were acquired from TCGA and cBioPortal. Genes frequently mutated in both datasets were extracted, from which tumor mutation burden and survival analysis revealed three prognostic genes. Further comprehensive analysis of HMCN1 mutation was carried out to identify differentially expressed genes and apply functional annotations. The correlation of HMCN1 mutation and tumor immunity was also evaluated. Results: HMCN1, SYNE1, and BAP1 mutations were associated with both tumor mutation burden and clinical prognosis in ccRCC. Gene enrichment analysis suggested the effects of HMCN1 mutation on biological processes and pathways linked to energy metabolism. HMCN1 mutation was also correlated with anti-tumor immunity. There were several limitations in the sample size and cohort availability of the present computational study. Conclusions: The present results inferred that HMCN1 mutation might have an important clinical significance for ccRCC patients by regulating metabolism and the immune microenvironment.

Emerging roles of fatty acid metabolism in cancer and their targeted drug development

Metabolic reprogramming is now considered as one of hallmark of tumor cells and provides them with a selective survival/growth advantage to resist harsh micro-environmental stress. Fatty acid (FA) metabolism of tumor cells supports the biosynthetic needs and provides fuel sources for energy supply. Since FA metabolic reprogramming is a critical link in tumor metabolism, its various roles in tumors have attracted increasing interest. Herein, we review the mechanisms through which cancer cells rewire their FA metabolism with a focus on the pathway of FA metabolism and its targeting drug development. The failure and successful cases of targeting tumor FA metabolism are expected to bypass the metabolic vulnerability and improve the efficacy of targeted therapy.

A Fatty Acid Metabolism Signature Associated With Clinical Therapy in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma is one of the most common tumors in the urinary system, among which clear cell renal cell carcinoma is the most common subtype with poor prognosis. As one of the tumors closely related to lipid metabolism, the role of fatty acid metabolism in ccRCC was investigated to predict the prognosis and guide treatment strategies. RNA-seq and clinical information of patients with ccRCC and expression microarray of human renal cell carcinoma cell lines were obtained from TCGA and GEO databases. Fatty acid metabolism–related risk signature was established by the univariate Cox regression and LASSO analysis to predict patient prognosis and response to different treatment modalities. Using the fatty acid metabolism risk signature, the risk score for each sample in the TCGA cohort was calculated and divided into high-risk and low-risk groups, with the cutoff point being the median. Patients with higher risk scores had a poorer prognosis than those with lower risk scores. The response of each sample to immunotherapy was predicted from the “TIDE” algorithm, while the sensitivity of each sample to sunitinib was obtained using the “pRRophetic” R package. Patients with lower risk scores had higher expression of PD-L1 and better efficacy for sunitinib than those in the high-risk group and were less likely to develop drug resistance, while patients with high-risk scores had a strong response to the anti-CTLA4 antibody therapy. A nomogram was constructed by independent prognostic factors to predict the 1-, 3-, and 5-year survival. According to the calibration curves, the nomogram had an excellent ability to predict survival for patients with ccRCC. Therefore, the fatty acid metabolism risk signature we established can not only predict the survival of patients with ccRCC but also predict patient response to targeted therapy and immunotherapy to provide optimal treatment strategies for patients.

A Cluster of Metabolic-Related Genes Serve as Potential Prognostic Biomarkers for Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the most common type of renal cancer, characterized by the dysregulation of metabolic pathways. RCC is the second highest cause of death among patients with urologic cancers and those with cancer cell metastases have a 5-years survival rate of only 10–15%. Thus, reliable prognostic biomarkers are essential tools to predict RCC patient outcomes. This study identified differentially expressed genes (DEGs) in the gene expression omnibus (GEO) database that are associated with pre-and post-metastases in clear cell renal cell carcinoma (ccRCC) patients and intersected these with metabolism-related genes in the Kyoto encyclopedia of genes and genomes (KEGG) database to identify metabolism-related DEGs (DEMGs). GOplot and ggplot packages for gene ontology (GO) and KEGG pathway enrichment analysis of DEMGs with log (foldchange) (logFC) were used to identify metabolic pathways associated with DEMG. Upregulated risk genes and downregulated protective genes among the DEMGs and seven independent metabolic genes, RRM2, MTHFD2, AGXT2, ALDH6A1, GLDC, HOGA1, and ETNK2, were found using univariate and multivariate Cox regression analysis, intersection, and Lasso-Cox regression analysis to establish a metabolic risk score signature (MRSS). Kaplan-Meier survival curve of Overall Survival (OS) showed that the low-risk group had a significantly better prognosis than the high-risk group in both the training cohort (p < 0.001; HR = 2.73, 95% CI = 1.97–3.79) and the validation cohort (p = 0.001; HR = 2.84, 95% CI = 1.50–5.38). The nomogram combined with multiple clinical information and MRSS was more effective at predicting patient outcomes than a single independent prognostic factor. The impact of metabolism on ccRCC was also assessed, and seven metabolism-related genes were established and validated as biomarkers to predict patient outcomes effectively.

Targeting mitochondrial one-carbon enzyme MTHFD2 together with pemetrexed confers therapeutic advantages in lung adenocarcinoma

Metabolic remodeling is the fundamental molecular feature of malignant tumors. Cancer cells require sufficient energy supplies supporting their high proliferative rate. MTHFD2, a mitochondrial one-carbon metabolic enzyme, is dysregulated in several malignancies and may serve as a promising therapeutic candidate in cancer treatment. Here, our data confirmed that MTHFD2 gene and protein was upregulated in the cancerous tissues of LUAD patients and was correlated with a poor survival in LUAD. MTHFD2 was involved in lung cancer cell proliferation, migration, and apoptosis by mediating its downstream molecules, such as DNA helicases (MCM4 and MCM7), as well as ZEB1, Vimentin and SNAI1, which contributed to tumor cell growth and epithelial-to-mesenchymal transition (EMT) process. Moreover, we identified that miRNA-99a-3p appeared to be an upstream mediator directly regulating MTHFD2 and MCM4 expression. Moreover, specific inhibition of MTHFD2 functions by siRNA or a chemical compound, improved anti-tumor sensitivities induced by pemetrexed in LUAD. Taken together, our study revealed the underlying molecular mechanisms of MTHFD2 in regulating cell proliferation and identified a novel therapeutic strategy improving the treatment efficacies in LUAD.

Restoring the epigenetically silenced lncRNA COL18A1-AS1 represses ccRCC progression by lipid browning via miR-1286/KLF12 axis

Abnormal accumulation of lipids has been highlighted in the progression of clear cell renal cell carcinoma (ccRCC). However, the underlying mechanism remains unclear. Emerging evidence suggests long noncoding RNAs (lncRNAs) participate in the regulation of lipid metabolism. In this study, we found lncRNA COL18A1-AS1 was downregulated in ccRCC and that higher COL18A1-AS1 expression indicated better prognosis. Decreased COL18A1-AS1 expression was caused by DNA methylation at the CpG islands within its promoter. Restoring the epigenetically silenced COL18A1-AS1 repressed tumor progression, promoted lipid browning and consumption in vitro and in vivo. Mechanistically, COL18A1-AS1 could competitively bind miR-1286 to increase the expression of Krüppel-like factor 12 (KLF12). Downregulation of COL18A1-AS1 in ccRCC resulted in the low expression of KLF12. COL18A1-AS1/KLF12 positively regulated uncoupling protein 1 (UCP1)-mediated lipid browning, which promotes tumor cell "slimming" and inhibits tumor progression. When tumor cell "slimming" occurred, lipid droplets turned into tiny pieces, and lipids were consumed without producing ATP energy. Taken together, our findings on COL18A1-AS1-miR-1286/KLF12 axis revealed a potential mechanism of abnormal accumulation of lipids in ccRCC and could be a promising therapeutic target for ccRCC patients.

A Novel Biomarker, FKBP10, for Poor Prognosis Prediction in Patients with Clear Cell Renal Cell Carcinoma

Objective

To screen genes associated with poor prognosis of clear cell renal cell carcinoma (CcRCC) from the public databases HPA (Human Protein Atlas), UALCAN, and GEPIA (Gene Expression Profiling Interactive Analysis) and to investigate the expression of FKBP10 in CcRCC and the effect on prognosis of the patients and the biological behavior of CcRCC cells.

Methods

The tumor tissues and adjacent noncancerous tissues of 42 patients with CcRCC diagnosed and treated in our hospital were collected, and the general information of the patients was recorded. FKBP10 expression in the tissues was determined by qRT-PCR and western blot, and its relationship with general information and prognosis of patients was analyzed. Knockdown or overexpression experiments were carried out with the human proximal tubule epithelial cell line HK-2 and CcRCC cell lines Caki-1, 786-O, ACHN, and A498 to verify the relationship between FKBP10 expression and cell proliferation and adhesion ability using MTT assay and fibronectin adhesion assay, respectively. Western blot was utilized to examine the protein expression level of c-Myc, cyclin D1, and Bcl-2 in the cells.

Results

FKBP10 was highly expressed in CcRCC tissues and cells and was correlated with poor prognosis. In addition, FKBP10 expression was positively correlated with CcRCC tumor size and staging and negatively correlated with tumor differentiation. Moreover, knockdown of FKBP10 significantly inhibited the proliferation of CcRCC cells, notably declined the protein expression of c-Myc, cyclin D1, and Bcl-2, and promoted cell adhesion.

Conclusion

FKBP10 is highly expressed in CcRCC tissues and cells and is associated with poor prognosis in patients. FKBP10 participated in the occurrence and development of CcRCC by promoting cell proliferation and inhibiting apoptosis and adhesion.

Mitochondrial metabolic reprogramming by SIRT3 regulation ameliorates drug resistance in renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) alters metabolic signals frequently, leading to mitochondrial dysfunction, such as increase of glycolysis and accumulation of lipid. Sirtuin3 (SIRT3) is a key factor for the regulation of both mitochondrial integrity and function. SIRT3 is downregulated and contributes in both cancer development and progression in ccRCC. The aim of this study is to investigate SIRT3-regulated mitochondrial biogenesis in ccRCC. SIRT3 overexpression alone reduced glucose uptake rate and enhanced membrane potential in mitochondria. ccRCC with overexpressed SIRT3 further improved the lethal effects when combined with anticancer drugs (Resveratrol, Everolimus and Temsirolimus). Cell viability was markedly decreased in a dose-dependent manner when treated with resveratrol or mTOR inhibitors in SIRT3 overexpressing ccRCC. In conclusion, SIRT3 improved mitochondrial functions in ccRCC through metabolic reprogramming. Mitochondrial reprogramming by SIRT3 regulation improves the sensitivity to anticancer drugs. The combination of SIRT3 and resveratrol functioned synergistically lethal effect in ccRCC.