Lipid metabolism reprogramming in renal cell carcinoma

Identify CTBP1-DT as an immunological biomarker that promotes lipid synthesis and apoptosis resistance in KIRC

Recently, mounting evidence has highlighted the essential function of the C-terminal binding protein-1 divergent transcript (CTBP1-DT) in malignancies. However, its role in kidney renal clear cell carcinoma (KIRC) remains largely unknown. Our study aimed to identify the potential function of CTBP1-DT in KIRC. RT-qPCR, Kaplan-Meier survival analysis, Cox regression analysis, and nomogram analysis were utilized to determine the expression and effects of CTBP1-DT on survival. The subcellular localization of CTBP1-DT was determined using RNA fluorescence in situ hybridization (FISH). To investigate the functions of CTBP1-DT in regulating KIRC cell proliferation, migration, invasion, lipid synthesis, and apoptosis, we conducted CCK8, EdU, Transwell, and Oil Red O staining and cell apoptosis staining assays. The relationships between CTBP1-DT and the tumor microenvironment were investigated with multiple bioinformatics analysis algorithms and databases, including CYBERSORT, TIMER2, Spearman correlation test, tumor mutation burden (TMB), microsatellite instability (MSI), and immunophenoscore (IPS). According to our results, CTBP1-DT is a lncRNA located in the nucleus that is significantly upregulated in KIRC and is correlated with better clinical outcomes. Downregulating CTBP1-DT inhibited cell viability, migration, invasion, and lipid synthesis but triggered cell apoptosis. Additionally, we explored the potential effect of CTBP1-DT in regulating immune cell infiltration in KIRC and other malignancies. Furthermore, CTBP1-DT could be used to predict the effectiveness of targeted drugs and immune checkpoint inhibitors. In conclusion, we identified CTBP1-DT as a potential immunological biomarker and discovered the potential role of CTBP1-DT in regulating lipid synthesis and apoptosis resistance.

Exosome-related lncRNA score: A value-based individual treatment strategy for predicting the response to immunotherapy in clear cell renal cell carcinoma

BACKGROUND

Exosomes play a crucial role in intercellular communication in clear cell renal cell carcinoma (ccRCC), while the long non-coding RNAs (lncRNAs) are implicated in tumorigenesis and progression.

AIMS

The purpose of this study is to construction a exosomes-related lncRNA score and a ceRNA network to predict the response to immunotherapy and potential targeted drug in ccRCC.

METHODS

Data of ccRCC patients were obtained from the TCGA database. Pearson correlation analysis was used to identify eExosomes-related lncRNAs (ERLRs) from Top10 exosomes-related genes that have been screened. The entire cohort was randomly divided into a training cohort and a validation cohort in equal scale. LASSO regression and multivariate cox regression was used to construct the ERLRs-based score. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and drug susceptibility between the high- and low-risk groups were also investigated. Finally, the relevant ceRNA network was constructed by machine learning to analyze their potential targets in immunotherapy and drug use of ccRCC patients.

RESULTS

A score consisting of 4ERLRs was identified, and patients with higher ERLRs-based score tended to have a worse prognosis than those with lower ERLRs-based score. ROC curves and multivariate Cox regression analysis demonstrated that the score could be considered as a risk factor for prognosis in both training and validation cohorts. Moreover, patients with high scores are predisposed to experience poor overall survival, a larger prevalence of advanced stage (III-IV), a greater tumor mutational burden, a higher infiltration of immunosuppressive cells, and a greater likelihood of responding favorably to immunotherapy. The importance of EMX2OS was determined by mechanical learning, and the ceRNA network was constructed, and EMX2OS may be a potential therapeutic target, possibly exerting its function through the EMX2OS/hsa-miR-31-5p/TLN2 axis.

CONCLUSIONS

Based on machine learning, a novel ERLRs-based score was constructed for predicting the survival of ccRCC patients. The ERLRs-based score is a promising potential independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics. Meanwhile, we screened out key lncRNAEMX2OS and identified the EMX2OS/hsa-miR-31-5p/TLN2 axis, which may provide new clues for the targeted therapy of ccRCC.

Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer-driven tissue factors in shaping nutrient availability in these tumors.

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

Background

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

Methods

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

Results

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

Conclusions

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

Influence of Dietary Polyunsaturated Fatty Acid Intake on Potential Lipid Metabolite Diagnostic Markers in Renal Cell Carcinoma: A Case-Control Study

Non-invasive diagnostics are crucial for the timely detection of renal cell carcinoma (RCC), significantly improving survival rates. Despite advancements, specific lipid markers for RCC remain unidentified. We aimed to discover and validate potent plasma markers and their association with dietary fats. Using lipid metabolite quantification, machine-learning algorithms, and marker validation, we identified RCC diagnostic markers in studies involving 60 RCC and 167 healthy controls (HC), as well as 27 RCC and 74 HC, by analyzing their correlation with dietary fats. RCC was associated with altered metabolism in amino acids, glycerophospholipids, and glutathione. We validated seven markers (l-tryptophan, various lysophosphatidylcholines [LysoPCs], decanoylcarnitine, and l-glutamic acid), achieving a 96.9% AUC, effectively distinguishing RCC from HC. Decreased decanoylcarnitine, due to reduced carnitine palmitoyltransferase 1 (CPT1) activity, was identified as affecting RCC risk. High intake of polyunsaturated fatty acids (PUFAs) was negatively correlated with LysoPC (18:1) and LysoPC (18:2), influencing RCC risk. We validated seven potential markers for RCC diagnosis, highlighting the influence of high PUFA intake on LysoPC levels and its impact on RCC occurrence via CPT1 downregulation. These insights support the efficient and accurate diagnosis of RCC, thereby facilitating risk mitigation and improving patient outcomes.

MED15 is upregulated by HIF-2α and promotes proliferation and metastasis in clear cell renal cell carcinoma via activation of SREBP-dependent fatty acid synthesis

Emerging evidence has highlighted that dysregulation of lipid metabolism in clear cell renal cell carcinoma (ccRCC) is associated with tumor development and progression. HIF-2α plays an oncogenic role in ccRCC and is involved in abnormal lipid accumulation. However, the underlying mechanisms between these two phenomena remain unknown. Here, MED15 was demonstrated to be a dominant factor for HIF-2α-dependent lipid accumulation and tumor progression. HIF-2α promoted MED15 transcriptional activation by directly binding the MED15 promoter region, and MED15 overexpression significantly alleviated the lipid deposition inhibition and malignant tumor behavior phenotypes induced by HIF-2α knockdown. MED15 was upregulated in ccRCC and predicted poor prognosis. MED15 promoted lipid deposition and tumor progression in ccRCC. Mechanistic investigations demonstrated that MED15 acts as SREBP coactivator directly interacting with SREBPs to promote SREBP-dependent lipid biosynthesis enzyme expression, and promotes SREBP1 and SREBP2 activation through the PLK1/AKT axis. Overall, we describe a molecular regulatory network that links MED15 to lipid metabolism induced by the SREBP pathway and the classic HIF-2α pathway in ccRCC. Efforts to target MED15 or inhibit MED15 binding to SREBPs as a novel therapeutic strategy for ccRCC may be warranted.

Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer driven tissue factors in shaping nutrient availability in these tumors.

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

Background

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

Methods

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

Results

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

Conclusion

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

HIF2α Promotes Cancer Metastasis through TCF7L2-Dependent Fatty Acid Synthesis in ccRCC

Recent studies have highlighted the notable involvement of the crosstalk between hypoxia-inducible factor 2 alpha (HIF2α) and Wnt signaling components in tumorigenesis. However, the cellular function and precise regulatory mechanisms of HIF2α and Wnt signaling interactions in clear cell renal cell carcinoma (ccRCC) remain elusive. To analyze the correlation between HIF2α and Wnt signaling, we utilized the Cancer Genome Atlas - Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) public database, HIF2α RNA sequencing data, and conducted luciferase reporter assays. A Wnt-related gene set was employed to identify key regulators of Wnt signaling controlled by HIF2α in ccRCC. Furthermore, we assessed the biological effects of TCF7L2 on ccRCC metastasis and lipid metabolism in both in vivo and in vitro settings. Our outcomes confirm TCF7L2 as a key gene involved in HIF2α-mediated regulation of the canonical Wnt pathway. Functional studies demonstrate that TCF7L2 promotes metastasis in ccRCC. Mechanistic investigations reveal that HIF2α stabilizes TCF7L2 mRNA in a method based on m6A by transcriptionally regulating METTL3. Up-regulation of TCF7L2 enhances cellular fatty acid oxidation, which promotes histone acetylation. This facilitates the transcription of genes connected to epithelial-mesenchymal transition and ultimately enhances metastasis of ccRCC. These outcomes offer a novel understanding into the involvement of lipid metabolism in the signaling pathway regulation, offering valuable implications for targeted treatment in ccRCC.

Low expression of fatty acid oxidation related gene ACADM indicates poor prognosis of renal clear cell carcinoma and is related to tumor immune infiltration

This research aims to identify the key fatty acid beta-oxidation (FAO) genes that are altered in kidney renal clear cell carcinoma (KIRC) and to analyze the role of these genes in KIRC. The Gene Expression Omnibus (GEO) and FAO datasets were used to identify these key genes. Wilcoxon rank sum test was used to assess the levels of acyl-CoA dehydrogenase medium chain (ACADM) between KIRC and non-cancer samples. The logistic regression and Wilcoxon rank sum test were used to explore the association between ACADM and clinical features. The diagnostic performance of ACADM for KIRC was assessed using a diagnostic receiver operating characteristic (ROC) curve. The co-expressed genes of ACADM were identified in LinkedOmics database, and their function and pathway enrichment were analyzed. The correlation between ACADM expression level and immune infiltration was analyzed by Gene Set Variation Analysis (GSVA) method. Additionally, the proliferation, migration, and invasion abilities of KIRC cells were assessed after overexpressing ACADM. Following differential analysis and intersection, we identified six hub genes, including ACADM. We found that the expression level of ACADM was decreased in KIRC tissues and had a better diagnostic effect (AUC = 0.916). Survival analysis suggested that patients with decreased ACADM expression had a worse prognosis. According to correlation analysis, a variety of clinical features were associated with the expression level of ACADM. By analyzing the infiltration level of immune cells, we found that ACADM may be related to the enrichment of immune cells. Finally, ACADM overexpression inhibited proliferation, migration, and invasion of KIRC cells. In conclusion, our findings suggest that reduced ACADM expression in KIRC patients is indicative of poor prognosis. These results imply that ACADM may be a diagnostic and prognostic marker for individuals with KIRC, offering a reference for clinicians in diagnosis and treatment.

HIF-2α/LINC02609/APOL1-mediated lipid storage promotes endoplasmic reticulum homeostasis and regulates tumor progression in clear-cell renal cell carcinoma

BACKGROUND

The VHL-HIF pathway and lipid droplet accumulation are the main characteristics of clear cell renal cell carcinoma (ccRCC). However, the connection between the two features is largely unknown.

METHODS

We used transcriptional sequencing and TCGA database analysis to identify APOL1 as a novel therapeutic target for ccRCC. The oncogenic functions of APOL1 were investigated by cell proliferation, colony formation, migration and invasion assays in ccRCC cells in vitro and xenografts derived from ccRCC cells in vivo. Oil red O staining and quantification were used to detect lipid droplets. Chromatin immunoprecipitation (ChIP) assays and luciferase reporter assays were carried out to identify HIF-2α bound to the promoter of APOL1 and lncRNA LINC02609. RNA-FISH and luciferase reporter assays were performed to determine that LncRNA LINC02609 functions as a competing endogenous RNA to regulate APOL1 expression by sponging miR-149-5p.

FINDINGS

RNA-seq data revealed that HIF2α can regulate APOL1 and lncRNA LINC02609 expression. We also found that HIF-2α can bind to the promoter of APOL1 and lncRNA LINC02609 and transcriptionally regulate their expression directly. We further demonstrated that LncRNA LINC02609 functions as a competing endogenous RNA to regulate APOL1 expression by sponging miR-149-5p in ccRCC. Mechanistically, APOL1-dependent lipid storage is required for endoplasmic reticulum (ER) homeostasis and cell viability and metastasis in ccRCC. We also showed that high APOL1 expression correlated with worse clinical outcomes, and knockdown of APOL1 inhibited tumor cell lipid droplet formation, proliferation, metastasis and xenograft tumor formation abilities. Together, our studies identify that HIF2α can regulate the expression of the lipid metabolism related gene APOL1 by direct and indirect means, which are essential for ccRCC tumorigenesis.

INTERPRETATION

Based on the experimental data, in ccRCC, the HIF-2α/LINC02609/APOL1 axis can regulate the expression of APOL1, thus interfering with lipid storage, promoting endoplasmic reticulum homeostasis and regulating tumor progression in ccRCC. Together, our findings provide potential biomarkers and novel therapeutic targets for future studies in ccRCC.

Immunohistochemical expression of cytochrome P4A11 (CYP4A11), carbonic anhydrase 9 (CAIX) and Ki67 in renal cell carcinoma; diagnostic relevance and relations to clinicopathological parameters

BACKGROUND

Cytochrome P4A11 (CYP4A11) is a member of cytochrome p450 family, which is involved in arachidonic acid metabolism that participates in promoting malignant cell proliferation, progression, and angiogenetic capacity. Carbonic Anhydrase 9 (CAIX) is a transmembrane protein that plays an integral part in regulating hypoxia which affects cancer cell metabolism, proliferation and promotes metastasis. The aim of this study was to evaluate the immunohistochemical expression of CYP4A11, CAIX and ki67 in RCC subtypes in relation to clinicopathological parameters and to evaluate the diagnostic significance of CYP4A11 and CAIX in differentiating renal cell carcinoma (RCC) subtypes.

MATERIALS AND METHODS

one hundred primary RCC cases, collected from Pathology Department, Faculty of Medicine, Tanta University and from private laboratories, were evaluated for immunohistochemical expression of CYP4A11, CAIX and ki67.

RESULTS

CYP4A11 was expressed in 59% of RCC; with 91.7% sensitivity and 90% specificity in differentiating clear cell and non-clear cell subtypes. CAIX was expressed in 50% of RCC; with 95% sensitivity, 80% specificity. High expression of CYP4A11 was statistically positively associated with higher tumor grade, high expression of CAIX was statistically positively associated with lower tumor grade and absence of necrosis and high ki67 labeling index was significantly associated with clear cell subtype, larger tumor sizes, higher tumor grade, advanced tumor stage, fat invasion and vascular invasion.

CONCLUSIONS

CYP4A11 and CAIX can be used as diagnostic markers to differentiate clear cell RCC from other subtypes. CYP4A11 is more diagnostically accurate and specific than CAIX. High expression of CYP4A11, low CAIX expression and high ki67 labeling index were related to features of aggressive tumor behavior.

LncRNAs-circRNAs as Rising Epigenetic Binary Superstars in Regulating Lipid Metabolic Reprogramming of Cancers

As one of novel hallmarks of cancer, lipid metabolic reprogramming has recently been becoming fascinating and widely studied. Lipid metabolic reprogramming in cancer is shown to support carcinogenesis, progression, distal metastasis, and chemotherapy resistance by generating ATP, biosynthesizing macromolecules, and maintaining appropriate redox status. Notably, increasing evidence confirms that lipid metabolic reprogramming is under the control of dysregulated non-coding RNAs in cancer, especially lncRNAs and circRNAs. This review highlights the present research findings on the aberrantly expressed lncRNAs and circRNAs involved in the lipid metabolic reprogramming of cancer. Emphasis is placed on their regulatory targets in lipid metabolic reprogramming and associated mechanisms, including the clinical relevance in cancer through lipid metabolism modulation. Such insights will be pivotal in identifying new theranostic targets and treatment strategies for cancer patients afflicted with lipid metabolic reprogramming.

Targeting lipid biosynthesis on the basis of conventional treatments for clear cell renal cell carcinoma: A promising therapeutic approach

A variety of cancer cells exhibit dysregulated lipid metabolism, characterized by excessive intracellular lipid accumulation, and clear cell renal cell carcinoma (ccRCC) is the most typical disease with these characteristics. As the most common malignancy of all renal cell carcinomas (RCCs), ccRCC is typically characterized by a large accumulation of lipids and glycogen in the cytoplasm and a nucleus that is squeezed by the accumulated lipid droplets and localized to the marginal areas within the cytoplasm. This lipid accumulation has been found to be critically involved in the maintenance of malignant features observed in various cancers. Firstly, it maintains the persistent proliferative and metastasis properties of cancer cells. Secondly, it acts as a buffer against lipid peroxidation, preventing lipid peroxidation-induced ferroptosis. Moreover, lipids can diminish the sensitivity of cancer cells to radiotherapy. As ccRCC is a type of cancer with high lipid synthesis, targeting lipid synthesis-related genes in cancer cells may be a promising therapeutic modality for single treatment or in combination with radiotherapy, chemotherapy, and immunotherapy. This may revolutionize the choice of treatment modality for ccRCC patients. In this review, we concentrate on the current status and progress of research on lipid biosynthesis in ccRCC and the potential applications of targeting lipid synthesis to treat ccRCC. At last, we propose perspective and future research directions for targeting inhibition of lipid biosynthesis in combination with conventional therapeutic approaches for the treatment of ccRCC, which will help to evolve the therapeutic model.

Long non-coding RNA HIF1A-AS2 promotes carcinogenesis by enhancing Gli1-mediated HIF1α expression in clear cell renal cell carcinoma

BACKGROUND

The most common urologic tumor in humans with the highest incidence rate is clear cell renal cell carcinoma (ccRCC). Long non-coding RNAs (lncRNAs) act as regulatory factors in several tumors. Here, we studied ccRCC regulated by hypoxia-inducible factor 1α (HIF1α)-antisense RNA 2 (AS2) or HIF1A-AS2.

METHODS

We performed wound-healing, transwell, and CCK-8 assays by decreasing or increasing the HIF1A-AS2 expression in RCC cell lines. Western blotting and qRT-PCR were used to identify the expression of downstream genes of the HIF1A-AS2 pathway. Gli1 and HIF1A-AS2 relationship was assessed using RIP and RNA pull-down assays. Lastly, transcriptome sequencing was performed on kidney cancer cells that had been knocked down to find possible regulatory mechanisms.

RESULTS

Our results suggest that high expression of HIF1A-AS2 may promote RCC cell proliferation and Gli1 expression as a downstream factor. Furthermore, they have physical binding sites and together regulate HIF1α to encourage the development of ccRCC. HIF1A-AS2 lncRNA may offer a new molecular target for ccRCC treatment.

CONCLUSION

lncRNA HIF1A-AS2 affects ccRCC development by regulating HIF1a expression through Gli1.

Mechanisms of sunitinib resistance in renal cell carcinoma and associated opportunities for therapeutics

Sunitinib is the first-line drug for renal cell carcinoma (RCC) treatment. However, patients who received sunitinib treatment will ultimately develop drug resistance after 6-15 months, creating a huge obstacle to the current treatment of renal cell carcinoma. Therefore, it is urgent to clarify the mechanisms of sunitinib resistance and develop new strategies to overcome it. In this review, the mechanisms of sunitinib resistance in renal cell carcinoma have been summarized based on five topics: activation of bypass or alternative pathway, inadequate drug accumulation, tumour microenvironment, metabolic reprogramming and epigenetic regulation. Furthermore, present and potential biomarkers, as well as potential treatment strategies for overcoming sunitinib resistance in renal cell carcinoma, are also covered.

Lipid metabolism-related gene expression in the immune microenvironment predicts prognostic outcomes in renal cell carcinoma

Background

Rates of renal cell carcinoma (RCC) occurrence and mortality are steadily rising. In an effort to address this issue, the present bioinformatics study was developed with the goal of identifying major lipid metabolism biomarkers and immune infiltration characteristics associated with RCC cases.

Methods

The Cancer Genome Atlas (TCGA) and E-MTAB-1980 were used to obtain matched clinical and RNA expression data from patients diagnosed with RCC. A LASSO algorithm and multivariate Cox regression analyses were employed to design a prognostic risk model for these patients. The tumor immune microenvironment (TIME) in RCC patients was further interrogated through ESTIMATE, TIMER, and single-cell gene set enrichment analysis (ssGSEA) analyses. Gene Ontology (GO), KEGG, and GSEA enrichment approaches were further employed to gauge the mechanistic basis for the observed results. Differences in gene expression and associated functional changes were then validated through appropriate molecular biology assays.

Results

Through the approach detailed above, a risk model based on 8 genes associated with RCC patient overall survival and lipid metabolism was ultimately identified that was capable of aiding in the diagnosis of this cancer type. Poorer prognostic outcomes in the analyzed RCC patients were associated with higher immune scores, lower levels of tumor purity, greater immune cell infiltration, and higher relative immune status. In GO and KEGG enrichment analyses, genes that were differentially expressed between risk groups were primarily related to the immune response and substance metabolism. GSEA analyses additionally revealed that the most enriched factors in the high-risk group included the stable internal environment, peroxisomes, and fatty acid metabolism. Subsequent experimental validation in vitro and in vivo revealed that the most significantly differentially expressed gene identified herein, ALOX5, was capable of suppressing RCC tumor cell proliferation, invasivity, and migration.

Conclusion

In summary, a risk model was successfully established that was significantly related to RCC patient prognosis and TIME composition, offering a robust foundation for the development of novel targeted therapeutic agents and individualized treatment regimens. In both immunoassays and functional analyses, dysregulated lipid metabolism was associated with aberrant immunological activity and the reprogramming of fatty acid metabolic activity, contributing to poorer outcomes.

A prognostic risk model for programmed cell death and revealing TRIB3 as a promising apoptosis suppressor in renal cell carcinoma

Programmed cell death (PCD), a common modality of cell death, affects tumor development and acts as a target for tumor therapeutics. Many modalities of PCD regulate genesis, progression and metastasis of cancers, thus affecting the patients' prognosis, but the comprehensive molecular mechanisms of PCD in tumors are lacking, especially in renal cancer. Here, seventeen PRPCDGs were identified from 1257 genes associated with thirteen PCD modalities, which were highly differentially expressed and significantly affected patients' prognosis. Then, LASSO regression analysis of these PRPCDGs screened the 9-gene PRPCDGs risk signature in TCGA-KIRC database. The PRPCDGs risk signature was closely associated with the patients' prognosis and presented stable prediction efficacy for 5- and 7-year overall survival (OS) in three different cohorts of renal cancer. Immune cell infiltration, immune checkpoint expression and pathway enrichment (including GO, KEGG pathway, tumor-associated pathways and metabolism-associated pathways) were significantly different in the high- or low-PRPCDGs-risk group. Finally, we illustrated that TRIB3 might be a protumor factor responsible for the elevated proliferation and invasion capacities of renal cell carcinoma (RCC) cells. In summary, the PRPCDGs risk signature was developed and showed stable prediction efficacy for the prognosis of patients and that (such as TRIB3) could be a potential target for RCC management.

Serum uric acid and triglycerides in clear cell renal cell carcinoma: A restrospective cross-sectional study

The available evidence on the relationship between serum uric acid and triglycerides in clear cell renal cell carcinoma (ccRCC) is limited. The objective of this study is to investigate whether there is an independent association between serum uric acid and triglycerides in ccRCC, while adjusting for other variables. This cross-sectional study involved 1018 participants with ccRCC, who were admitted to a hospital in China from December 1st, 2013 to January 1st, 2023. The main independent variable investigated was serum uric acid, which was measured at baseline. The dependent variable was triglycerides. Covariates considered in this study included age, sex, body mass index, smoking status, hypertension, diabetes, coronary disease, High-density lipoprotein cholesterol, Low-density lipoprotein cholesterol, Total cholesterol, Blood urea nitrogen, and Creatinine. The study included 1018 participants with an average age of 56.92 ± 10.88 years old, and approximately 68% of them were male. The fully-adjusted linear regression analysis indicated a positive association between serum uric acid levels (100μmol/L) and triglyceride levels (mmol/L) after adjusting for confounding factors (β = 0.13, 95% CI [0.07, 0.18]). Furthermore, a smooth curve was constructed between serum uric acid and triglycerides based on the fully-adjusted model. In patients with ccRCC, there was a positive association between serum uric acid and triglycerides.

The m6A modification-mediated OGDHL exerts a tumor suppressor role in ccRCC by downregulating FASN to inhibit lipid synthesis and ERK signaling

Metabolic reprogramming is a hallmark of cancer, and the impact of lipid metabolism as a crucial aspect of metabolic reprogramming on clear cell renal cell carcinoma (ccRCC) progression has been established. However, the regulatory mechanisms underlying the relationship between metabolic abnormalities and ccRCC progression remain unclear. Therefore, this study aimed to identify key regulatory factors of metabolic reprogramming in ccRCC and provide potential therapeutic targets for ccRCC patients. Potential metabolic regulatory factors in ccRCC were screened using bioinformatics analysis. Public databases and patient samples were used to investigate the aberrant expression of Oxoglutarate dehydrogenase-like (OGDHL) in ccRCC. The function of OGDHL in ccRCC growth and metastasis was evaluated through in vitro and in vivo functional experiments. Mechanistic insights were obtained through luciferase reporter assays, chromatin immunoprecipitation, RNA methylation immunoprecipitation, and mutagenesis studies. OGDHL mRNA and protein levels were significantly downregulated in ccRCC tissues. Upregulation of OGDHL expression effectively inhibited ccRCC growth and metastasis both in vitro and in vivo. Furthermore, FTO-mediated OGDHL m6A demethylation suppressed its expression in ccRCC. Mechanistically, low levels of OGDHL promoted TFAP2A expression by inhibiting ubiquitination levels, which then bound to the FASN promoter region and transcriptionally activated FASN expression, thereby promoting lipid accumulation and ERK pathway activation. Our findings demonstrate the impact of OGDHL on ccRCC progression and highlight the role of the FTO/OGDHL/TFAP2A/FASN axis in regulating ccRCC lipid metabolism and progression, providing new targets for ccRCC therapy.

PHF8-GLUL axis in lipid deposition and tumor growth of clear cell renal cell carcinoma

For clear cell renal cell carcinoma (ccRCC), lipid deposition plays important roles in the development, metastasis, and drug resistance. However, the molecular mechanisms underlying lipid deposition in ccRCC remain largely unknown. By conducting an unbiased CRISPR-Cas9 screening, we identified the epigenetic regulator plant homeodomain finger protein 8 (PHF8) as an important regulator in ccRCC lipid deposition. Moreover, PHF8 is regulated by von Hippel-Lindau (VHL)/hypoxia-inducible factor (HIF) axis and essential for VHL deficiency-induced lipid deposition. PHF8 transcriptionally up-regulates glutamate-ammonia ligase (GLUL), which promotes the lipid deposition and ccRCC progression. Mechanistically, by forming a complex with c-MYC, PHF8 up-regulates TEA domain transcription factor 1 (TEAD1) in a histone demethylation-dependent manner. Subsequently, TEAD1 up-regulates GLUL transcriptionally. Pharmacological inhibition of GLUL by l-methionine sulfoximine not only repressed ccRCC lipid deposition and tumor growth but also enhanced the anticancer effects of everolimus. Thus, the PHF8-GLUL axis represents a potential therapeutic target for ccRCC treatment.

The novel role of LDHA/LDHB in the prognostic value and tumor-immune infiltration in clear cell renal cell carcinoma

Lactate dehydrogenase (LDH) is a crucial glycolytic enzyme which mediates the metabolic plasticity of cancer cells, however its clinical significance in renal cell carcinoma (RCC) is poorly understood. Herein, we examined the prognostic significance of the two primary components of LDH, i.e., LDHA and LDHB, in clear cell RCC (ccRCC) patients and further explored their association with immune infiltration in ccRCC. In this study, the expression levels of LDHA and LDHB were examined in ccRCC and adjacent normal tissues by Gene Expression Profiling Interactive Analysis 2 (GEPIA2), UALCAN, and western blotting (WB) analyses, and their prognostic values were estimated in 150 ccRCC and 30 adjacent normal tissues by immunohistochemistry (IHC) analysis. The relationship to immune infiltration of LDHA and LDHB genes was further investigated using tumor immune estimation resource 2 (TIMER2) and Tumor-Immune System Interactions and DrugBank (TISIDB) databases, respectively. Public databases and WB analyses demonstrated higher LDHA and lower LDHB in ccRCC than in non-tumor tissues. IHC analysis revealed that LDHA and LDHB expression profiles were significantly associated with tumor grade, stage, size, and overall survival (OS). Univariate survival analysis displayed that high grade, advanced stage, large tumor, metastasis, high LDHA, and low LDHB expression were significantly associated with a poorer OS, and multivariate analysis revealed tumor stage and LDHB were identified as independent predictors for OS in patients with ccRCC. Further TIMER2 and TISIDB analyses demonstrated that LDHA and LDHB expression was significantly related to multiple immune cells and immune inhibitors in over 500 ccRCC patients. These findings revealed that LDHB was an independent favorable predictor, and LDHA and LDHB correlated with tumor immune infiltrates in ccRCC patients, which indicated LDHA/LDHB could be implicated in the tumorigenesis of ccRCC and might be potential therapeutic targets for patients with ccRCC.

Sphingosine kinase 1 regulates lipid metabolism to promote progression of kidney renal clear cell carcinoma

PURPOSE

To detect the expression of sphingosine kinase 1 (SPHK1) in clear cell renal cell carcinoma (ccRCC) and explore its biological role in the occurrence and development of ccRCC through regulation of fatty acid metabolism.

METHODS

Using the Cancer Genome Atlas database, SPHK1 expression and its clinical significance were detected in clear cell renal cell carcinoma. Immunohistochemistry was performed to detect SPHK1 expression in RCC samples in our hospital. The connection between the SPHK1 levels and clinicopathological features of patients was assessed. Nile Red was used to detect fatty acids in cells. Cell Counting Kit-8 and 5-ethynyl-2'-deoxyuridine assays were performed to determine the effect of SPHK1 on renal cell viability and proliferation, respectively. Additionally, the effects of SPHK1 on the proliferation and metastasis of ccRCC were studied using wound healing and Transwell assays. Fatty acids were added exogenously in recovery experiments and western blotting was performed to determine the effect of SPHK1 on fatty acid metabolism in ccRCC. Finally, the effects of SPHK1 on tumor growth were investigated in a xenograft model.

RESULTS

Bioinformatics analysis revealed that SPHK1 expression was upregulated in kidney RCC. OverSPHK1 expression was associated with poor prognosis for ccRCC patients. High SPHK1 expression was detected in human ccRCC. SPHK1 expression was related to clinicopathological features, such as tumor size and Furman grade. Additionally, cell proliferation, migration, and invasion were inhibited in ccRCC cells with low SPHK1 expression. In rescue experiments, proliferation, migration, and invasion were restored. In vivo, reduced SPHK1 levels correlated with lower expression of fatty acid synthase, stearoyl-CoA desaturase 1, and acetyl CoA carboxylase, and slowed tumor growth.

CONCLUSIONS

SPHK1 is abnormally overexpressed in human ccRCC. Patients with ccRCC may benefit from treatments that target SPHK1, which may also serve as a prognostic indicator.

Metabolic reprogramming of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a malignancy that exhibits metabolic reprogramming as a result of genetic mutations. This reprogramming accommodates the energy and anabolic needs of the cancer cells, leading to changes in glucose, lipid, and bio-oxidative metabolism, and in some cases, the amino acid metabolism. Recent evidence suggests that ccRCC may be classified as a metabolic disease. The metabolic alterations provide potential targets for novel therapeutic interventions or biomarkers for monitoring tumor growth and prognosis. This literature review summarized recent discoveries of metabolic alterations in ccRCC, including changes in glucose, lipid, and amino acid metabolism. The development of metabolic drugs targeting these metabolic pathways was also discussed, such as HIF-2α inhibitors, fatty acid synthase (FAS) inhibitors, glutaminase (GLS) inhibitors, indoleamine 2,3-dioxygenase (IDO) inhibitors, and arginine depletion. Future trends in drug development are proposed, including the use of combination therapies and personalized medicine approaches. In conclusion, this review provides a comprehensive overview of the metabolic alterations in ccRCC and highlights the potential for developing new treatments for this disease.

Distinguishing Renal Cell Carcinoma From Normal Kidney Tissue Using Mass Spectrometry Imaging Combined With Machine Learning

PURPOSE

Accurately distinguishing renal cell carcinoma (RCC) from normal kidney tissue is critical for identifying positive surgical margins (PSMs) during partial and radical nephrectomy, which remains the primary intervention for localized RCC. Techniques that detect PSM with higher accuracy and faster turnaround time than intraoperative frozen section (IFS) analysis can help decrease reoperation rates, relieve patient anxiety and costs, and potentially improve patient outcomes.

MATERIALS AND METHODS

Here, we extended our combined desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and machine learning methodology to identify metabolite and lipid species from tissue surfaces that can distinguish normal tissues from clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) tissues.

RESULTS

From 24 normal and 40 renal cancer (23 ccRCC, 13 pRCC, and 4 chRCC) tissues, we developed a multinomial lasso classifier that selects 281 total analytes from over 27,000 detected molecular species that distinguishes all histological subtypes of RCC from normal kidney tissues with 84.5% accuracy. On the basis of independent test data reflecting distinct patient populations, the classifier achieves 85.4% and 91.2% accuracy on a Stanford test set (20 normal and 28 RCC) and a Baylor-UT Austin test set (16 normal and 41 RCC), respectively. The majority of the model's selected features show consistent trends across data sets affirming its stable performance, where the suppression of arachidonic acid metabolism is identified as a shared molecular feature of ccRCC and pRCC.

CONCLUSION

Together, these results indicate that signatures derived from DESI-MSI combined with machine learning may be used to rapidly determine surgical margin status with accuracies that meet or exceed those reported for IFS.

PI3K/AKT/mTOR Dysregulation and Reprogramming Metabolic Pathways in Renal Cancer: Crosstalk with the VHL/HIF Axis

Renal cell carcinoma (RCC) represents 85-95% of kidney cancers and is the most frequent type of renal cancer in adult patients. It accounts for 3% of all cancer cases and is in 7th place among the most frequent histological types of cancer. Clear cell renal cell carcinoma (ccRCC), accounts for 75% of RCCs and has the most kidney cancer-related deaths. One-third of the patients with ccRCC develop metastases. Renal cancer presents cellular alterations in sugars, lipids, amino acids, and nucleic acid metabolism. RCC is characterized by several metabolic dysregulations including oxygen sensing (VHL/HIF pathway), glucose transporters (GLUT 1 and GLUT 4) energy sensing, and energy nutrient sensing cascade. Metabolic reprogramming represents an important characteristic of the cancer cells to survive in nutrient and oxygen-deprived environments, to proliferate and metastasize in different body sites. The phosphoinositide 3-kinase-AKT-mammalian target of the rapamycin (PI3K/AKT/mTOR) signaling pathway is usually dysregulated in various cancer types including renal cancer. This molecular pathway is frequently correlated with tumor growth and survival. The main aim of this review is to present renal cancer types, dysregulation of PI3K/AKT/mTOR signaling pathway members, crosstalk with VHL/HIF axis, and carbohydrates, lipids, and amino acid alterations.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Solute carrier-related signature for assessing prognosis and immunity in patients with clear-cell renal cell carcinoma

Background

Clear-cell renal cell carcinoma (ccRCC) is the most common malignant kidney cancer. However, the tumor microenvironment and crosstalk involved in metabolic reprogramming in ccRCC are not well-understood.

Methods

We used The Cancer Genome Atlas to obtain ccRCC transcriptome data and clinical information. The E-MTAB-1980 cohort was used for external validation. The GENECARDS database contains the first 100 solute carrier (SLC)-related genes. The predictive value of SLC-related genes for ccRCC prognosis and treatment was assessed using univariate Cox regression analysis. An SLC-related predictive signature was developed through Lasso regression analysis and used to determine the risk profiles of patients with ccRCC. Patients in each cohort were separated into high- and low-risk groups based on their risk scores. The clinical importance of the signature was assessed through survival, immune microenvironment, drug sensitivity, and nomogram analyses using R software.

Results

SLC25A23, SLC25A42, SLC5A1, SLC3A1, SLC25A37, SLC5A6, SLCO5A1, and SCP2 comprised the signatures of the eight SLC-related genes. Patients with ccRCC were separated into high- and low-risk groups based on the risk value in the training and validation cohorts; the high-risk group had a significantly worse prognosis (p < 0.001). The risk score was an independent predictive indicator of ccRCC in the two cohorts according to univariate and multivariate Cox regression (p < 0.05). Analysis of the immune microenvironment showed that immune cell infiltration and immune checkpoint gene expression differed between the two groups (p < 0.05). Drug sensitivity analysis showed that compared to the low-risk group, the high-risk group was more sensitive to sunitinib, nilotinib, JNK-inhibitor-VIII, dasatinib, bosutinib, and bortezomib (p < 0.001). Survival analysis and receiver operating characteristic curves were validated using the E-MTAB-1980 cohort.

Conclusions

SLC-related genes have predictive relevance in ccRCC and play roles in the immunological milieu. Our results provide insight into metabolic reprogramming in ccRCC and identify promising treatment targets for ccRCC.

Preoperative serum low-density lipoprotein cholesterol is an independent prognostic factor in patients with renal cell carcinoma after nephrectomy

BACKGROUND

Little is known about the association between the preoperative low-density lipoprotein cholesterol (LDL-C) level and prognosis in patients with renal cell carcinoma (RCC) after nephrectomy, and its prognostic value needs to be elucidated.

METHODS

The clinical and follow-up data of 737 RCC patients who underwent nephrectomy were retrospectively analyzed. The optimal cut-off LDL-C level was determined using X-tile, and then patients were divided into low and high LDL-C groups. The association between LDL-C levels and survival of RCC patients was assessed using the Kaplan-Meier method and Cox regression analysis.

RESULTS

The optimal cut-off LDL-C level was 1.93 mmol/L, and patients were divided into the low (≤ 1.93 mmol/L) and high LDL-C (> 1.93 mmol/L) groups. The Kaplan-Meier analysis showed that patients in the low LDL-C group had significantly shorter overall survival (OS), cancer-specific survival (CSS) and recurrence-free survival (RFS) than those in the high LDL-C group (P = 0.001, P = 0.001, and P = 0.003, respectively). The COX univariate analysis showed that the preoperative LDL-C level was closely associated with OS, CSS, and RFS in RCC patients (P = 0.002, P = 0.003, and P = 0.005, respectively). The multivariate analysis showed that the preoperative LDL-C level was an independent factor for predicting survival (OS, CSS and RFS) in RCC patients after nephrectomy. The low preoperative LDL-C levels predicted worse OS (hazard ratio [HR]: 2.337; 95% confidence interval [CI]: 1.192-4.581; P = 0.013), CSS (HR: 3.347; 95% CI: 1.515-7.392; P = 0.003), and RFS (HR: 2.207; 95% CI: 1.178-4.132; P = 0.013).

CONCLUSIONS

The preoperative LDL-C level is an independent factor for the prognosis of RCC patients after nephrectomy, and low preoperative LDL-C levels predict worse survival (OS, CSS, and RFS).

Lipids as Targets for Renal Cell Carcinoma Therapy

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

ALKBH5 inhibits the SIRT3/ACC1 axis to regulate fatty acid metabolism via an m6A-IGF2BP1-dependent manner in cervical squamous cell carcinoma

Cervical cancer (CC) is the most common malignancy of the female reproductive system, among which cervical squamous cell carcinoma (CESC) is the most common type. The demethylase ALKBH5 has been previously revealed to be downregulated in CC tissue. N6 methyladenine (m6A) is the most common modification in eukaryotic RNAs and is involved in modulating tumour progression. Therefore, we attempted to clarify the ALKBH5 role and mechanism underlying CESC progression. In CESC, patient tissue and control tissue m6A levels were measured. Reverse transcription quantitative real-time polymerase chain reaction, western blotting and immunochemistry were used to measure ALKBH5 levels. A correlation between CESC patient survival and ALKBH5 levels was evaluated. Wound healing, transwell and colony formation assays were used to detect CESC cellular behaviours. Corresponding kits and BODIPY staining were used to detect CESC lipid metabolism. Bioinformatics, immunoprecipitation, RNA pulldown and RNA immunoprecipitation assays as well as half-life measurements were used to assess the association and mechanism of ALKBH5 with silent mating type information regulation 2 homologue 3 (SIRT3), acetyl-CoA carboxylase 1 (ACC1) and insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1). The m6A demethylase ALKBH5 was depleted in CESC tissue and cells, and a low level of ALKBH5 predicted an unfavourable prognosis in CESC patients. ALKBH5 overexpression suppressed CESC growth and lipid metabolism in vitro and CESC tumour growth in vivo, and ACC1 overexpression rescued these changes. ALKBH5 downregulated ACC1 levels in CESC cells by facilitating SIRT3 methylation to repress ACC1 deacetylation. ALKBH5 destabilized SIRT3 to downregulate SIRT3 levels in CESCs in an m6A-IGF2BP1-dependent manner. ALKBH5 demethylates and destabilizes SIRT3 in an m6A-IGF2BP1-dependent manner, repressing CESC growth, lipid metabolism and tumorigenesis by downregulating ACC1.

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.

Manipulation of Amino Acid Levels with Artificial Diets Induces a Marked Anticancer Activity in Mice with Renal Cell Carcinoma

Targeted therapies with antiangiogenic drugs (e.g., sunitinib) and immune checkpoint inhibitors (e.g., anti-PD-1 antibodies) are the standard of care for patients with metastatic renal cell carcinoma. Although these treatments improve patient survival, they are rarely curative. We previously hypothesized that advanced cancers might be treated without drugs by using artificial diets in which the levels of specific amino acids (AAs) are manipulated. In this work, after showing that AA manipulation induces selective anticancer activity in renal cell carcinoma cells in vitro, we screened 18 artificial diets for anticancer activity in a challenging animal model of renal cell carcinoma. The model was established by injecting murine renal cell carcinoma (Renca) cells into the peritoneum of immunocompetent BALB/cAnNRj mice. Mice survival was markedly improved when their normal diet was replaced with our artificial diets. Mice fed a diet lacking six AAs (diet T2) lived longer than mice treated with sunitinib or anti-PD-1 immunotherapy; several animals lived very long or were cured. Controlling the levels of several AAs (e.g., cysteine, methionine, and leucine) and lipids was important for the anticancer activity of the diets. Additional studies are needed to further evaluate the therapeutic potential and mechanism of action of this simple and inexpensive anticancer strategy.

Study on potential markers for diagnosis of renal cell carcinoma by serum untargeted metabolomics based on UPLC-MS/MS

Objective: Renal cell carcinoma (RCC) is the most common malignancy of the kidney. However, there is no reliable biomarker with high sensitivity and specificity for diagnosis and differential diagnosis. This study aims to analyze serum metabolite profile of patients with RCC and screen for potential diagnostic biomarkers. Methods: Forty-five healthy controls (HC), 40 patients with benign kidney tumor (BKT) and 46 patients with RCC were enrolled in this study. Serum metabolites were detected by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), and then subjected to multivariate statistical analysis, metabolic pathway analysis and diagnostic performance evaluation. Results: The changes of glycerophospholipid metabolism, phosphatidylinositol signaling system, glycerolipid metabolism, d-glutamine and d-glutamate metabolism, galactose metabolism, and folate biosynthesis were observed in RCC group. Two hundred and forty differential metabolites were screened between RCC and HC groups, and 64 differential metabolites were screened between RCC and BKT groups. Among them, 4 differential metabolites, including 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, lysophosphatidylcholine (LPC) 19:2, and γ-Aminobutyryl-lysine (an amino acid metabolite), were of high clinical value not only in the diagnosis of RCC (RCC group vs. HC group; AUC = 0.990, 0.916, 0.909, and 0.962; Sensitivity = 97.73%, 97.73%, 93.18%, and 86.36%; Specificity = 100.00%, 73.33%, 80.00%, and 95.56%), but also in the differential diagnosis of benign and malignant kidney tumors (RCC group vs. BKT group; AUC = 0.989, 0.941, 0.845 and 0.981; Sensitivity = 93.33%, 93.33%, 77.27% and 93.33%; Specificity = 100.00%, 84.21%, 78.38% and 92.11%). Conclusion: The occurrence of RCC may involve changes in multiple metabolic pathways. The 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, LPC 19:2 and γ-Aminobutyryl-lysine may be potential biomarkers for the diagnosis or differential diagnosis of RCC.

Dual-tracer positron emission tomography/computed tomography as an imaging probe of de novo lipogenesis in preclinical models of hepatocellular carcinoma

Background

De novo lipogenesis is upregulated in many cancers, and targeting it represents a metabolic approach to cancer treatment. However, the treatment response is unpredictable because lipogenic activity varies greatly among individual tumors, thereby necessitating the assessment of lipogenic activity before treatment. Here, we proposed an imaging probe, positron emission tomography/computed tomography (PET/CT) with dual tracers combining 11C-acetate and 18F-fluorodeoxyglucose (18F-FDG), to assess the lipogenic activity of hepatocellular carcinoma (HCC) and predict the response to lipogenesis-targeted therapy.

Methods

We investigated the association between 11C-acetate/18F-FDG uptake and de novo lipogenesis in three HCC cell lines (from well-differentiated to poorly differentiated: HepG2, Hep3B, and SkHep1) by examining the expression of lipogenic enzymes: acetyl-CoA synthetase 2 (ACSS2), fatty acid synthase (FASN), and ATP citrate lyase (ACLY). The glycolysis level was determined through glycolytic enzymes: pyruvate dehydrogenase expression (PDH). On the basis of the findings of dual-tracer PET/CT, we evaluated the treatment response to a lipase inhibitor (orlistat) in cell culture experiments and xenograft mice.

Results

Dual-tracer PET/CT revealed the lipogenic activity of various HCC cells, which was positively associated with 11C-acetate uptake and negatively associated with 18F-FDG uptake. This finding represents the negative association between 11C-acetate and 18F-FDG uptake. Because these two tracers revealed the lipogenic and glycolytic activity, respectively, which implies an antagonism between lipogenic metabolism and glucose metabolism in HCC. In addition, dual-tracer PET/CT not only revealed the lipogenic activity but also predicted the treatment response to lipogenesis-targeted therapy. For example, HepG2 xenografts with high 11C-acetate but low 18F-FDG uptake exhibited high lipogenic activity and responded well to orlistat treatment, whereas SkHep1 xenografts with low 11C-acetate but high 18F-FDG uptake exhibited lower lipogenic activity and poor response to orlistat.

Conclusion

The proposed non-invasive dual-tracer PET/CT imaging can reveal the lipogenesis and glycolysis status of HCC, thus providing an ideal imaging probe for predicting the therapeutic response of HCC to lipogenesis-targeted therapy.

Fatty acid desaturase 1 (FADS1) is a cancer marker for patient survival and a potential novel target for precision cancer treatment

Fatty Acid Desaturase-1 (FADS1) or delta 5 desaturase (D5D) is a rate-limiting enzyme involved in the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFAs), i.e., arachidonic acid (ARA) and eicosapentaenoic (EPA). These LC-PUFAs and their metabolites play essential and broad roles in cancer cell proliferation, metastasis, and tumor microenvironment. However, the role of FADS1 in cancers remains incompletely understood. Utilizing The Cancer Genome Atlas (TCGA) database, we explored the role of FADS1 across different cancer types using multiple bioinformatics and statistical tools. Moreover, we studied the impact of a FADS1 inhibitor (D5D-IN-326) on proliferation of multiple cancer cell lines. We identified that FADS1 gene is a predictor for cancer survival in multiple cancer types. Compared to normal tissue, the mRNA expression of FADS1 is significantly increased in primary tumors while even higher in metastatic and recurrent tumors. Mechanistically, pathway analysis demonstrated that FADS1 is associated with cholesterol biosynthesis and cell cycle control genes. Interestingly, FADS1 expression is higher when TP53 is mutated. Tumors with increased FADS1 expression also demonstrated an increased signatures of fibroblasts and macrophages infiltration among most cancer types. Our in vitro assays showed that D5D-IN-326 significantly inhibited cell proliferation of kidney, colon, breast, and lung cancer cell lines in a dose-dependent manner. Lastly, single nucleotide polymorphisms (SNPs) which are well-established expression quantitative trait loci (eQTLs) for FADS1 in normal human tissues are also significantly correlated with FADS1 expression in tumors of multiple tissue types, potentially serving as a marker to stratify cancer patients with high/low FADS1 expression in their tumor tissue. Our study suggests that FADS1 plays multiple roles in cancer biology and is potentially a novel target for precision cancer treatment.

Serum Eicosanoids Metabolomics Profile in a Mouse Model of Renal Cell Carcinoma: Predicting the Antitumor Efficacy of Anlotinib

Anlotinib (ANL) shows promising efficacy in patients with renal cell cancer (RCC). Here, for the first time, a serum eicosanoid metabolomics profile and pharmacodynamics in Renca syngeneic mice treated with ANL was performed and integrated using our previous HPLC-MS/MS method and multivariate statistical analysis. The tumor growth inhibition rates of ANL were 39% and 52% at low (3 mg/kg) and high (6 mg/kg) dose levels, without obvious toxicity. A total of 15 disturbed metabolites were observed between the normal group and the model group, and the intrinsic metabolic phenotype alterations had occurred due to the treatment of ANL. A total of eight potential metabolites from the refined partial least squares (PLS) model were considered as potential predictive biomarkers for the efficacy of ANL, and the DHA held the most outstanding sensitivity and specificity with an area under the receiver operating characteristic curve of 0.88. Collectively, the results of this exploratory study not only provide a powerful reference for understanding eicosanoid metabolic reprogramming of ANL but also offer an innovative perspective for the development of therapeutic targets and strategies, the discovery of predictive biomarkers, and the determination of effective tumor monitoring approaches.

Decrease of Intracellular Glutamine by STF-62247 Results in the Accumulation of Lipid Droplets in von Hippel-Lindau Deficient Cells

Kidney cancer is one of the top ten cancer diagnosed worldwide and its incidence has increased the last 20 years. Clear Cell Renal Cell Carcinoma (ccRCC) are characterized by mutations that inactivate the von Hippel-Lindau (VHL) tumor suppressor gene and evidence indicated alterations in metabolic pathways, particularly in glutamine metabolism. We previously identified a small molecule, STF-62247, which target VHL-deficient renal tumors by affecting late-stages of autophagy and lysosomal signaling. In this study, we investigated ccRCC metabolism in VHL-deficient and proficient cells exposed to the small molecule. Metabolomics profiling using 1H NMR demonstrated that STF-62247 increases levels of glucose, pyruvate, glycerol 3-phosphate while glutamate, asparagine, and glutathione significantly decreased. Diminution of glutamate and glutamine was further investigated using mass spectrometry, western blot analyses, enzymatic activities, and viability assays. We found that expression of SLC1A5 increases in VHL-deficient cells treated with STF-62247, possibly to stimulate glutamine uptake intracellularly to counteract the diminution of this amino acid. However, exogenous addition of glutamine was not able to rescue cell viability induced by the small molecule. Instead, our results showed that VHL-deficient cells utilize glutamine to produce fatty acid in response to STF-62247. Surprisingly, this occurs through oxidative phosphorylation in STF-treated cells while control cells use reductive carboxylation to sustain lipogenesis. We also demonstrated that STF-62247 stimulated expression of stearoyl-CoA desaturase (SCD1) and peripilin2 (PLIN2) to generate accumulation of lipid droplets in VHL-deficient cells. Moreover, the carnitine palmitoyltransferase 1A (CPT1A), which control the entry of fatty acid into mitochondria for β-oxidation, also increased in response to STF-62247. CPT1A overexpression in ccRCC is known to limit tumor growth. Together, our results demonstrated that STF-62247 modulates cellular metabolism of glutamine, an amino acid involved in the autophagy-lysosome process, to support lipogenesis, which could be implicated in the signaling driving to cell death.