Erratum: The potential value of cuprotosis (copper-induced cell death) in the therapy of clear cell renal cell carcinoma.

[This corrects the article on p. 3947 in vol. 12, PMID: 36119838.].

Evaluating the Role of Neddylation Modifications in Kidney Renal Clear Cell Carcinoma: An Integrated Approach Using Bioinformatics, MLN4924 Dosing Experiments, and RNA Sequencing.

BACKGROUND: Neddylation, a post-translational modification process, plays a crucial role in various human neoplasms. However, its connection with kidney renal clear cell carcinoma (KIRC) remains under-researched. METHODS: We validated the Gene Set Cancer Analysis Lite (GSCALite) platform against The Cancer Genome Atlas (TCGA) database, analyzing 33 cancer types and their link with 17 neddylation-related genes. This included examining copy number variations (CNVs), single nucleotide variations (SNVs), mRNA expression, cellular pathway involvement, and methylation. Using Gene Set Variation Analysis (GSVA), we categorized these genes into three clusters and examined their impact on KIRC patient prognosis, drug responses, immune infiltration, and oncogenic pathways. Afterward, our objective is to identify genes that exhibit overexpression in KIRC and are associated with an adverse prognosis. After pinpointing the specific target gene, we used the specific inhibitor MLN4924 to inhibit the neddylation pathway to conduct RNA sequencing and related in vitro experiments to verify and study the specificity and potential mechanisms related to the target. This approach is geared towards enhancing our understanding of the prognostic importance of neddylation modification in KIRC. RESULTS: We identified significant CNV, SNV, and methylation events in neddylation-related genes across various cancers, with notably higher expression levels observed in KIRC. Cluster analysis revealed a potential trade-off in the interactions among neddylation-related genes, where both high and low levels of gene expression are linked to adverse prognoses. This association is particularly pronounced concerning lymph node involvement, T stage classification, and Fustat score. Simultaneously, our research discovered that PSMB10 exhibits overexpression in KIRC when compared to normal tissues, negatively impacting patient prognosis. Through RNA sequencing and in vitro assays, we confirmed that the inhibition of neddylation modification could play a role in the regulation of various signaling pathways, thereby influencing the prognosis of KIRC. Moreover, our results underscore PSMB10 as a viable target for therapeutic intervention in KIRC, opening up novel pathways for the development of targeted treatment strategies. CONCLUSION: This study underscores the regulatory function and potential mechanism of neddylation modification on the phenotype of KIRC, identifying PSMB10 as a key regulatory target with a significant role in influencing the prognosis of KIRC.

Frontiers in sarcopenia: Advancements in diagnostics, molecular mechanisms, and therapeutic strategies.

The onset of sarcopenia is intimately linked with aging, posing significant implications not only for individual patient quality of life but also for the broader societal healthcare framework. Early and accurate identification of sarcopenia and a comprehensive understanding of its mechanistic underpinnings and therapeutic targets paramount to addressing this condition effectively. This review endeavors to present a cohesive overview of recent advancements in sarcopenia research and diagnosis. We initially delve into the contemporary diagnostic criteria, specifically referencing the European Working Group on Sarcopenia in Older People (EWGSOP) 2 and Asian Working Group on Sarcopenia (AWGS) 2019 benchmarks. Additionally, we elucidate comprehensive assessment techniques for muscle strength, quantity, and physical performance, highlighting tools such as grip strength, chair stand test, dual-energy X-ray Absorptiometry (DEXA), bioelectrical impedance analysis (BIA), gait speed, and short physical performance battery (SPPB), while also discussing their inherent advantages and limitations. Such diagnostic advancements pave the way for early identification and unequivocal diagnosis of sarcopenia. Proceeding further, we provide a deep-dive into sarcopenia's pathogenesis, offering a thorough examination of associated signaling pathways like the Myostatin, AMP-activated protein kinase (AMPK), insulin/IGF-1 Signaling (IIS), and the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways. Each pathway's role in sarcopenia mediation is detailed, underscoring potential therapeutic target avenues. From a mechanistic perspective, the review also underscores the pivotal role of mitochondrial dysfunction in sarcopenia, emphasizing elements such as mitochondrial oxidative overload, mitochondrial biogenesis, and mitophagy, and highlighting their therapeutic significance. At last, we capture recent strides made in sarcopenia treatment, ranging from nutritional and exercise interventions to potential pharmacological and supplementation strategies. In sum, this review meticulously synthesizes the latest scientific developments in sarcopenia, aiming to enhance diagnostic precision in clinical practice and provide comprehensive insights into refined mechanistic targets and innovative therapeutic interventions, ultimately contributing to optimized patient care and advancements in the field.

Deciphering the role of neddylation in tumor microenvironment modulation: common outcome of multiple signaling pathways.

Neddylation is a post-translational modification process, similar to ubiquitination, that controls several biological processes. Notably, it is often aberrantly activated in neoplasms and plays a critical role in the intricate dynamics of the tumor microenvironment (TME). This regulatory influence of neddylation permeates extensively and profoundly within the TME, affecting the behavior of tumor cells, immune cells, angiogenesis, and the extracellular matrix. Usually, neddylation promotes tumor progression towards increased malignancy. In this review, we highlight the latest understanding of the intricate molecular mechanisms that target neddylation to modulate the TME by affecting various signaling pathways. There is emerging evidence that the targeted disruption of the neddylation modification process, specifically the inhibition of cullin-RING ligases (CRLs) functionality, presents a promising avenue for targeted therapy. MLN4924, a small-molecule inhibitor of the neddylation pathway, precisely targets the neural precursor cell-expressed developmentally downregulated protein 8 activating enzyme (NAE). In recent years, significant advancements have been made in the field of neddylation modification therapy, particularly the integration of MLN4924 with chemotherapy or targeted therapy. This combined approach has demonstrated notable success in the treatment of a variety of hematological and solid tumors. Here, we investigated the inhibitory effects of MLN4924 on neddylation and summarized the current therapeutic outcomes of MLN4924 against various tumors. In conclusion, this review provides a comprehensive, up-to-date, and thorough overview of neddylation modifications, and offers insight into the critical importance of this cellular process in tumorigenesis.

[Retracted] Isoquercitrin inhibits bladder cancer progression in vitro and in vivo by regulating the PI3K/Akt and PKC signaling pathways.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that the agarose gel electrophoretic bands shown in Fig. 4A for PKC were strikingly similar to bands that had already appeared in another article written by different authors at different research institutes. Owing to the fact that the contentious data in the above article had already been published prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 36: 165­172, 2016; DOI: 10.3892/or.2016.4794].

Tumor Vaccines: Unleashing the Power of the Immune System to Fight Cancer.

This comprehensive review delves into the rapidly evolving arena of cancer vaccines. Initially, we examine the intricate constitution of the tumor microenvironment (TME), a dynamic factor that significantly influences tumor heterogeneity. Current research trends focusing on harnessing the TME for effective tumor vaccine treatments are also discussed. We then provide a detailed overview of the current state of research concerning tumor immunity and the mechanisms of tumor vaccines, describing the complex immunological processes involved. Furthermore, we conduct an exhaustive analysis of the contemporary research landscape of tumor vaccines, with a particular focus on peptide vaccines, DNA/RNA-based vaccines, viral-vector-based vaccines, dendritic-cell-based vaccines, and whole-cell-based vaccines. We analyze and summarize these categories of tumor vaccines, highlighting their individual advantages, limitations, and the factors influencing their effectiveness. In our survey of each category, we summarize commonly used tumor vaccines, aiming to provide readers with a more comprehensive understanding of the current state of tumor vaccine research. We then delve into an innovative strategy combining cancer vaccines with other therapies. By studying the effects of combining tumor vaccines with immune checkpoint inhibitors, radiotherapy, chemotherapy, targeted therapy, and oncolytic virotherapy, we establish that this approach can enhance overall treatment efficacy and offset the limitations of single-treatment approaches, offering patients more effective treatment options. Following this, we undertake a meticulous analysis of the entire process of personalized cancer vaccines, elucidating the intricate process from design, through research and production, to clinical application, thus helping readers gain a thorough understanding of its complexities. In conclusion, our exploration of tumor vaccines in this review aims to highlight their promising potential in cancer treatment. As research in this field continues to evolve, it undeniably holds immense promise for improving cancer patient outcomes.

Review and prospect of immune checkpoint blockade therapy represented by PD-1/PD-L1 in the treatment of clear cell renal cell carcinoma.

As a common tumor of the urinary system, the morbidity and mortality related to renal carcinoma, are increasing annually. Clear cell renal cell carcinoma (CCRCC) is the most common subtype of renal cell carcinoma, accounting for approximately 75% of the total number of patients with renal cell carcinoma. Currently, the clinical treatment of ccRCC involves targeted therapy, immunotherapy, and a combination of the two. In immunotherapy, PD-1/PD-L1 blocking of activated T cells to kill cancer cells is the most common treatment. However, as treatment progresses, some patients gradually develop resistance to immunotherapy. Meanwhile, other patients experience great side effects after immunotherapy, resulting in a survival status far lower than the expected survival rate. Based on these clinical problems, many researchers have been working on the improvement of tumor immunotherapy in recent years and have accumulated numerous research results. We hope to find a more suitable direction for future immunotherapy for ccRCC by combining these results and the latest research progress.

Analysis of genomes and transcriptomes of clear cell renal cell carcinomas identifies mutations and gene expression changes in the TGF-beta pathway.

The occurrence of clear cell renal cell carcinoma (ccRCC) is related to changes in the transforming growth factor-ß (TGF-ß) signaling pathway. In this study, we adopted an integrated approach to identify and verify the effects of changes in this pathway on ccRCC and provide a guide for identifying new therapeutic targets. We performed transcriptome analysis of 539 ccRCC cases from The Cancer Genome Atlas (TCGA) and divided the samples into different TGF-ß clusters according to unsupervised hierarchical clustering. We found that 76 of the 85 TGF-ß pathway genes were dysregulated, and 55 genes were either protective or risk factors affecting the prognosis of ccRCC. The survival time of patients with tumors with low TGF-ß scores was shorter than that of patients with tumors with high TGF-ß scores. The overall survival (OS) of patients with ccRCC with high TGF-ß scores was better than that of patients with low TGF-ß scores. The TGF-ß score correlated with the expression of key ccRCC and deacetylation genes. The sensitivity of tumor patients to targeted drugs differed between the high and low TGF-ß score groups. Therefore, a prognostic model based on the TGF-ß gene pathway can predict the prognosis of ccRCC patients. Grouping patients with ccRCC according to their TGF-ß score is of great significance for evaluating the prognosis of patients, selecting targeted drugs, and identifying new therapeutic targets.

The potential value of cuprotosis (copper-induced cell death) in the therapy of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) accounts for 75% of the total incidence of renal cancer, and every year the number of morbidity and mortality increases, posing a serious threat to public health. The current main treatment methods for kidney cancer include drug-targeted therapy and immunotherapy. Although there are many treatment options for kidney cancer, they all have limitations, including drug resistance, unsatisfied long-term benefits, and adverse effects. Therefore, it is crucial to identify more effective therapeutic targets. As a newly discovered mechanism of cell death, copper-induced cell death (cuprotosis) is closely related to changes in cell metabolism, particularly in copper metabolism. Current studies have shown that the key signaling pathway of cuprotosis, the FDX1 (Ferredoxin 1)-LIAS (Lipoic Acid Synthetase) axis, plays an important role in the regulation of cellular oxidative stress, which can directly affect cell survival via inducing or promoting cancer cell death. Therefore, we speculated that this regulatory cell death mechanism might serve as a potential therapeutic target for the clinical treatment of renal cancer. To test this, we first performed a pan-cancer analysis based on cuprotosis-related genomic and transcriptomic levels to reveal the expression of cuprotosis in cancer. Next, GSVA-clustering analysis was performed with data from the Cancer Genome Atlas (TCGA) cohort, and the cohort was divided into three clusters according to the gene enrichment levels of cuprotosis marker genes. In addition, we analyzed the potential of using cuprotosis in clinical treatment from multiple perspectives, including chemotherapeutic drug susceptibility test, immune target inhibition treatment responsiveness, and histone modification. Combining the results of multi-omics analysis, we focused on the feasibility of this novel regulatory cell death mechanism in ccRCC treatment and further constructed a prognostic model. Finally, we verified our results by integrating the patient's gene expression information and radiomics information. Our study provides new insights into the development and clinical application of targeting cuprotosis pathway.

Lipid metabolism in ferroptosis and ferroptosis-based cancer therapy.

Ferroptosis refers to iron-dependent, specialized, and regulated-necrosis mediated by lipid peroxidation, which is closely related to a variety of diseases, including cancer. Tumor cells undergo extensive changes in lipid metabolism, including lipid peroxidation and ferroptosis. Changes in lipid metabolism are critical for the regulation of ferroptosis and thus have important roles in cancer therapy. In this review, we introduce the characteristics of ferroptosis and briefly analyze the links between several metabolic mechanisms and ferroptosis. The effects of lipid peroxides, several signaling pathways, and the molecules and pathways involved in lipid metabolism on ferroptosis were extensively analyzed. Finally, our review highlights some ferroptosis-based treatments and presents some methods and examples of how these treatments can be combined with other treatments.

Potential Application of Pyroptosis in Kidney Renal Clear Cell Carcinoma Immunotherapy and Targeted Therapy.

Renal cell carcinoma (RCC) is a type of cancer with an increasing rate of morbidity and mortality and is a serious threat to human health. The treatment of RCC, especially kidney renal clear cell carcinoma (KIRC), has always been the focus of clinical treatment. Using The Cancer Genome Atlas (TCGA) database as a starting point, we explored the feasibility of applying the pyroptosis mechanism to KIRC treatment by searching for cancer markers associated with pyroptosis and cancer treatment signatures. The obtained samples were clustered using unsupervised clustering analysis to define the different KIRC subtypes with different pyroptosis expression levels. Based on this, a gene expression analysis was performed to explore the carcinogenic mechanism that is markedly related to pyroptosis. The Genomics of Drug Sensitivity in Cancer database and single sample gene set enrichment analysis (ssGSEA) algorithm were used to analyze the different treatment methods of the current prominent KIRC to determine whether pyroptosis plays a role. Finally, LASSO regression was used to screen for related genes and construct a model to predict patient prognosis. The expression levels of GSDME, CASP3, CASP4, CASP5, CHMP3, and CHMP4C were incorporated into the model construction. After verification, the prediction accuracy of the 3-, 5-, 7- and 10 years survival rates of our prognostic model were 0.66, 0.701, 0.719, and 0.728, respectively. Through the above analysis, we demonstrated the feasibility of pyroptosis in the clinical treatment of KIRC and provided novel ideas and suggestions for the clinical treatment of KIRC.

Development of a Novel Sphingolipid Signaling Pathway-Related Risk Assessment Model to Predict Prognosis in Kidney Renal Clear Cell Carcinoma.

This study aimed to explore underlying mechanisms by which sphingolipid-related genes play a role in kidney renal clear cell carcinoma (KIRC) and construct a new prognosis-related risk model. We used a variety of bioinformatics methods and databases to complete our exploration. Based on the TCGA database, we used multiple R-based extension packages for data transformation, processing, and statistical analyses. First, on analyzing the CNV, SNV, and mRNA expression of 29 sphingolipid-related genes in various types of cancers, we found that the vast majority were protective in KIRC. Subsequently, we performed cluster analysis of patients with KIRC using sphingolipid-related genes and successfully classified them into the following three clusters with significant prognostic differences: Cluster 1, Cluster 2, and Cluster 3. We performed differential analyses of transcription factor activity, drug sensitivity, immune cell infiltration, and classical oncogenes to elucidate the unique roles of sphingolipid-related genes in cancer, especially KIRC, and provide a reference for clinical treatment. After analyzing the risk rates of sphingolipid-related genes in KIRC, we successfully established a risk model composed of seven genes using LASSO regression analysis, including SPHK1, CERS5, PLPP1, SGMS1, SGMS2, SERINC1, and KDSR. Previous studies have suggested that these genes play important biological roles in sphingolipid metabolism. ROC curve analysis results showed that the risk model provided good prediction accuracy. Based on this risk model, we successfully classified patients with KIRC into high- and low-risk groups with significant prognostic differences. In addition, we performed correlation analyses combined with clinicopathological data and found a significant correlation between the risk model and patient's M, T, stage, grade, and fustat. Finally, we developed a nomogram that predicted the 5-, 7-, and 10-year survival in patients with KIRC. The model we constructed had strong predictive ability. In conclusion, we believe that this study provides valuable data and clues for future studies on sphingolipid-related genes in KIRC.

Application of Regulatory Cell Death in Cancer: Based on Targeted Therapy and Immunotherapy.

The development of cancer treatment methods is constantly changing. For common cancers, our treatment methods are still based on conventional treatment methods, such as chemotherapy, radiotherapy, and targeted drug therapy. Nevertheless, the emergence of tumor resistance has a negative impact on treatment. Regulated cell death is a gene-regulated mode of programmed cell death. After receiving specific signal transduction, cells change their physical and chemical properties and the extracellular microenvironment, resulting in structural destruction and decomposition. As research accumulates, we now know that by precisely inducing specific cell death patterns, we can treat cancer with less collateral damage than other treatments. Many newly discovered types of RCD are thought to be useful for cancer treatment. However, some experimental results suggest that some RCDs are not sensitive to cancer cell death, and some may even promote cancer progression. This review summarizes the discovered types of RCDs, reviews their clinical efficacy in cancer treatment, explores their anticancer mechanisms, and discusses the feasibility of some newly discovered RCDs for cancer treatment in combination with the immune and tumor microenvironment.

Using Genomic and Transcriptome Analyses to Identify the Role of the Oxidative Stress Pathway in Renal Clear Cell Carcinoma and Its Potential Therapeutic Significance.

Oxidative stress (OS) refers to endogenous and/or exogenous stimulation when the balance between oxidation and antioxidants in the body is disrupted, resulting in excessive production of free radicals. Excessive free radicals exert a series of negative effects on the body, which can result in the oxidation of and infliction of damage on biological molecules and further cause cell death and tissue damage, which are related to many pathological processes. Pathways related to OS have always been the focus of medical research. Several studies are being conducted to develop strategies to treat cancer by exploring the OS pathways. Therefore, this study is aimed at determining the correlation between the OS pathway and kidney renal clear cell carcinoma (KIRC) through bioinformatics analysis, at proving the effect of common anticancer drugs on the OS pathway, and at constructing a prognosis model of patients with KIRC based on several genes with the strongest correlation between the OS pathway and KIRC. We first collected and analyzed gene expression and clinical information of related patients through TCGA database. Then, we divided the samples into three clusters according to their gene expression levels obtained through cluster analysis. Using these three clusters, we performed GDSC drug analysis and GSEA analysis and examined the correlation among the OS pathway, histone modification, and immune cell infiltration. We also analyzed the response of anti-PD-1 and anti-CTLA-4 to the OS pathway. Thereafter, we used LASSO regression to select the most suitable nine genes, combined with the clinicopathological characteristics to establish the prognosis model of patients with KIRC, and verified the scientific precision of the model. Finally, tumor mutational burden was calculated to verify whether patients would benefit from immunotherapy. The results of this study may provide a reference for the establishment of treatment strategies for patients with KIRC.

Angiogenesis Pathway in Kidney Renal Clear Cell Carcinoma and Its Prognostic Value for Cancer Risk Prediction.

Angiogenesis, a process highly regulated by pro-angiogenic and anti-angiogenic factors, is disrupted and dysregulated in cancer. Despite the increased clinical use of angiogenesis inhibitors in cancer therapy, most molecularly targeted drugs have been less effective than expected. Therefore, an in-depth exploration of the angiogenesis pathway is warranted. In this study, the expression of angiogenesis-related genes in various cancers was explored using The Cancer Genome Atlas datasets, whereupon it was found that most of them were protective genes in the patients with kidney renal clear cell carcinoma (KIRC). We divided the samples from the KIRC dataset into three clusters according to the mRNA expression levels of these genes, with the enrichment scores being in the order of Cluster 2 (upregulated expression) > Cluster 3 (normal expression) > Cluster 1 (downregulated expression). The survival curves plotted for the three clusters revealed that the patients in Cluster 2 had the highest overall survival rates. Via a sensitivity analysis of the drugs listed on the Genomics of Drug Sensitivity in Cancer database, we generated IC50 estimates for 12 commonly used molecularly targeted drugs for KIRC in the three clusters, which can provide a more personalized treatment plan for the patients according to angiogenesis-related gene expression. Subsequently, we investigated the correlation between the angiogenesis pathway and classical cancer-related genes as well as that between the angiogenesis score and immune cell infiltration. Finally, we used the least absolute shrinkage and selection operator (LASSO)-Cox regression analysis to construct a risk score model for predicting the survival of patients with KIRC. According to the areas under the receiver operating characteristic (ROC) curves, this new survival model based on the angiogenesis-related genes had high prognostic prediction value. Our results should provide new avenues for the clinical diagnosis and treatment of patients with KIRC.

Identification of immunization-related new prognostic biomarkers for papillary renal cell carcinoma by integrated bioinformatics analysis.

BACKGROUND: Despite papillary renal cell carcinoma (pRCC) being the second most common type of kidney cancer, the underlying molecular mechanism remains unclear. Targeted therapies in the past have not been successful because of the lack of a clear understanding of the molecular mechanism. Hence, exploring the underlying mechanisms and seeking novel biomarkers for pursuing a precise prognostic biomarker and appropriate therapies are critical. MATERIAL AND METHODS: In our research, the differentially expressed genes (DEGs) were screened from the TCGA and GEO databases, and a total of 149 upregulated and 285 downregulated genes were sorted. This was followed by construction of functional enrichment and protein-protein interaction (PPI) network, and then the top 15 DEGs were selected for further analysis. The P4HB gene was chosen as our target gene by repetitively validating multiple datasets, and higher levels of P4HB expression predicted lower overall survival (OS) in patients with pRCC. RESULTS: We found that P4HB not only connects with immune cell infiltration and co-expression with PD-1, PD-L2, and CTLA-4, but also has a strong connection with the newly discovered hot gene, TOX. CONCLUSION: We speculate that P4HB is a novel gene involved in the progression of pRCC through immunomodulation.

A new prognostic risk model based on autophagy-related genes in kidney renal clear cell carcinoma.

This study aimed to explore the potential role of autophagy-related genes in kidney renal clear cell carcinoma (KIRC) and develop a new prognostic-related risk model. In our research, we used multiple bioinformatics methods to perform a pan-cancer analysis of the CNV, SNV, mRNA expression, and overall survival of autophagy-related genes, and displayed the results in the form of heat maps. We then performed cluster analysis and LASSO regression analysis on these autophagy-related genes in KIRC. In the cluster analysis, we successfully divided patients with KIRC into five clusters and found that there was a clear correlation between the classification and two clinicopathological features: tumor, and stage. In LASSO regression analysis, we used 13 genes to create a new prognostic-related risk model in KIRC. The model showed that the survival rate of patients with KIRC in the high-risk group was significantly lower than that in the low-risk group, and that there was a correlation between this grouping and the patients' metastasis, tumor, stage, grade, and fustat. The results of the ROC curve suggested that this model has good prediction accuracy. The results of multivariate Cox analysis show that the risk score of this model can be used as an independent risk factor for patients with KIRC. In summary, we believe that this research provides valuable data supporting future clinical treatment and scientific research.

A New Survival Model Based on ADAMTSs for Prognostic Prediction in Clear Cell Renal Cell Carcinoma.

The main purpose of this study was to explore the genetic variation, gene expression, and clinical significance of ADAMTSs (a disintegrin and metalloprotease domains with thrombospondin motifs) across cancer types. Analysis of data from the TCGA (The Cancer Genome Atlas) database showed that the ADAMTSs have extensive CNV (copy number variation) and SNV (single nucleotide variation) across cancer types. Compared with normal tissues, the methylation of ADAMTSs in cancer tissues is also significantly different, which affects the expression of ADAMTS gene and the prognosis of cancer patients. Through gene expression analysis, we found that ADAMTS family has significant changes in gene expression across cancer types and is closely related to the prognosis of carcinoma, especially in ccRCC (clear cell renal cell carcinoma). LASSO regression analysis was used to establish a prognostic model based on the ADAMTSs to judge the prognosis of patients with ccRCC. Multiple Cox regression analysis suggested that age, grade, stage, and risk score of the prognostic model of ccRCC were independent prognostic factors in patients with renal clear cell carcinoma. These findings indicate that the ADAMTSs-based survival model can accurately predict the prognosis of patients with ccRCC and suggest that ADAMTSs are a potential prognostic biomarker and therapeutic target in ccRCC.

The Uniqueness of Clear Cell Renal Cell Carcinoma: Summary of the Process and Abnormality of Glucose Metabolism and Lipid Metabolism in ccRCC.

Kidney cancer is a cancer with an increasing incidence in recent years. Clear cell renal cell carcinoma (ccRCC) accounts for up to 80% of all kidney cancers. The understanding of the pathogenesis, tumor progression, and metastasis of renal carcinoma is not yet perfect. Kidney cancer has some characteristics that distinguish it from other cancers, and the metabolic aspect is the most obvious. The specificity of glucose and lipid metabolism in kidney cancer cells has also led to its being studied as a metabolic disease. As the most common type of kidney cancer, ccRCC has many characteristics that represent the specificity of kidney cancer. There are features that we are very concerned about, including the presence of lipid droplets in cells and the obesity paradox. These two points are closely related to glucose metabolism and lipid metabolism. Therefore, we hope to explore whether metabolic changes affect the occurrence and development of kidney cancer by looking for evidence of changes on expression at the genomic and protein levels in glucose metabolism and lipid metabolism in ccRCC. We begin with the representative phenomenon of abnormal cancer metabolism: the Warburg effect, through the collection of popular metabolic pathways and related genes in the last decade, as well as some research hotspots, including the role of ferroptosis and glutamine in cancer, systematically elaborated the factors affecting the incidence and metastasis of kidney cancer. This review also identifies the similarities and differences between kidney cancer and other cancers in order to lay a theoretical foundation and provide a valid hypothesis for future research.

Genomic and Transcriptome Analysis to Identify the Role of the mTOR Pathway in Kidney Renal Clear Cell Carcinoma and Its Potential Therapeutic Significance.

The mTOR pathway, a major signaling pathway, regulates cell growth and protein synthesis by activating itself in response to upstream signals. Overactivation of the mTOR pathway may affect the occurrence and development of cancer, but no specific treatment has been proposed for targeting the mTOR pathway. In this study, we explored the expression of mTOR pathway genes in a variety of cancers and the potential compounds that target the mTOR pathway and focused on an abnormal type of cancer, kidney renal clear cell carcinoma (KIRC). Based on the mRNA expression of the mTOR pathway gene, we divided KIRC patient samples into three clusters. We explored possible therapeutic targets of the mTOR pathway in KIRC. We predicted the IC50 of some classical targeted drugs to analyze their correlation with the mTOR pathway. Subsequently, we investigated the correlation of the mTOR pathway with histone modification and immune infiltration, as well as the response to anti-PD-1 and anti-CTLA-4 therapy. Finally, we used a LASSO regression analysis to construct a model to predict the survival of patients with KIRC. This study shows that mTOR scores can be used as tools to study various treatments targeting the mTOR pathway and that we can predict the recovery of KIRC patients through the expression of mTOR pathway genes. These research results can provide a reference for future research on KIRC patient treatment strategies.