Cholesterol and the development of clear-cell renal carcinoma

Novel scoring system incorporating lipoproteins to predict outcomes of epithelial ovarian cancer patients

OBJECTIVE

Epithelial ovarian cancer is the most lethal gynecological malignancy worldwide. While common prognostic factors are identified, the impact of serum lipoproteins remains controversial. This retrospective cohort study aims to investigate the association between specific lipoprotein levels and prognosis.

METHODS

Clinical data of 420 participants with epithelial ovarian cancer registered at Women's Hospital, School of Medicine, Zhejiang University, between January 2014 and April 2021 were included. Cox regression analyses and Kaplan-Meier methods were used to assess prognosis, estimated by hazard ratio (HR) with 95% confidence interval (CI). A novel prognostic model incorporating lipoproteins was developed for evaluating the prognosis. Meta-analysis was applied to assess the impact of low density lipoprotein cholesterol (LDL-C) on prognosis.

RESULTS

Among 420 patients, those in advanced stages exhibited higher low density lipoprotein cholesterol (LDL-C) (p=0.008) and lower high density lipoprotein cholesterol (HDL-C) levels (p<0.001), with no significant differences in total cholesterol or triglyceride levels. Elevated LDL-C level was significantly associated with worse overall survival (HR 1.72; 95% CI 1.15 to 2.58; p=0.010) and progression free survival (HR 1.94; 95% CI 1.46 to 2.58; p<0.001), whereas higher HDL-C level was linked to better overall survival (HR 0.56; 95% CI 0.37 to 0.85; p=0.004) and progression free survival (HR 0.61; 95% CI 0.46 to 0.81; p<0.001). A novel prognostic model, low density lipoprotein cholesterol-high density lipoprotein cholesterol-fibrinogen-lactate dehydrogenase-prealbumin-Fe-stage (LH-FLPFS), was established to enhance prognostic predictive efficacy. The meta-analysis further suggested that higher LDL-C level was associated with worse overall survival (HR 1.82; 95% CI 1.39 to 2.38; p<0.001).

CONCLUSIONS

In this study, preoperative LDL-C and HDL-C levels emerged as potential prognostic factors for ovarian cancer. Establishment of a novel prognostic model, LH-FLPFS, holds promise for significantly improving prognostic predictive efficacy.

Prediction model for ocular metastasis of breast cancer: machine learning model development and interpretation study

BACKGROUND

Breast cancer (BC) is caused by the uncontrolled proliferation of breast epithelial cells followed by malignant transformation, and it has the highest incidence among female malignant tumors. The metastasis of BC occurs through direct and lymphatic spread. Although ocular metastasis is relatively rare, it is a good indicator of a worse prognosis. We used machine learning (ML) to establish a model to analyze the risk factors of BC eye metastasis.

METHODS

The clinical data of 2225 patients with BC from 2003 to 2019 were collected and randomly classified into the training and test sets using a ratio of 7:3. Based on the presence or absence of eye metastasis, the patients with BC were classified into the ocular metastasis (OM) and non-ocular metastasis (NOM) groups. Univariate and multivariate logistic regression analyses and least absolute shrinkage and selection operator (LASSO) were conducted. We used six ML algorithms to establish a predictive BC model and used 10-fold cross-validation for internal verification. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the model. In addition, we established a web hazard calculator depending on the best-performing model to facilitate its clinical application. Shapley additive interpretation (SHAP) was used to determine the risk factors and the interpretability of the black box model.

RESULTS

Univariate logistic regression analysis showed that histopathology (other types), axillary lymph node metastasis (ALNM) (> 4), Ca2+, total cholesterol (TC), low-density lipoprotein (LDL), apolipoprotein A (ApoA), carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 125, CA153, CA199, alkaline phosphatase (ALP), and hemoglobin (Hb) were risk factors for BC eye metastasis. Multivariate logistic regression analysis showed that CA153, ApoA, and LDL were hazardous components for BC eye metastasis. LASSO showed that ALNM, LDL, CA125, Hb, ALP, and CA199 were the first six key variables that were useful for the diagnosis of ocular metastasis in breast cancer. Bootstrapped aggregation (BAG) demonstrated the discriminative ability (area under ROC curve [AUC] = 0.992, accuracy = 0.953, sensitivity = 0.987). Based on this, we applied the BAG machine learning model to build an online web computing system to help clinicians assist in determining the risk of BC eye metastasis. In addition, two typical cases are analyzed to determine the interpretability of the model.

CONCLUSION

We used ML to establish a risk prediction model for BC ocular metastasis, and BAG showed the greatest performance. The model can predict the risk of OM in patients with BC, facilitate early and timely diagnosis and treatment, and reduce the burden on society.

CT Characterization of Lipid Metabolism in Clear Cell Renal Cell Carcinoma: Relationship Between Liver Hounsfield Unit Values and Adipose Differentiation-Related Protein Gene Expression

Radiogenomics is an emerging field that links imaging features with molecular characteristics of diseases. In clear cell renal cell carcinoma (ccRCC), metabolic reprogramming leads to lipid accumulation, influenced by the adipose differentiation-related protein (ADFP). This study aimed to investigate whether hepatic and tumoral Hounsfield Unit (HU) values could serve as noninvasive radiogenomic biomarkers for ADFP expression in ccRCC. We analyzed CT images of 185 ccRCC patients, comparing lipid-associated HU values in the liver and tumor across ADFP expression statuses. Patients with low-grade ccRCC expressing ADFP showed significantly lower minimum HU values in both liver and tumor tissue, indicating greater lipid accumulation. Additionally, ADFP expression correlated negatively with abdominal adipose tissue compartments and positively with minimum tumoral HU values, linking systemic lipid metabolism to tumor biology. These findings suggest that hepatic and tumoral HU measurements may serve as noninvasive markers of lipid accumulation related to ADFP, providing insight into metabolic alterations in ccRCC. While promising, these results require validation in larger, controlled studies due to sample size and variability limitations. This approach could enhance the radiogenomic assessment of ccRCC, supporting noninvasive insights into tumor metabolism and progression.

Construction and experimental verification of a novel nine-glycosylation-related gene prognostic risk model for clear cell renal carcinoma

Objective

Patients with clear cell renal carcinoma (ccRCC) typically have poor prognosis. Glycosylation modification plays an important role in ccRCC. This study aimed to develop a novel signature for predicting ccRCC prognosis based on glycosylation-related genes (GRGs).

Methods

Differentially expressed GRGs (DE_GRGs) were identified using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus and used for constructing the risk model. The function of key genes was validated.

Results

Twenty-two DE_GRGs were intersected between GSE53757 and TCGA. Patients with ccRCC were divided into two clusters based on the expression profile of these DE_GRGs. Significant differences in the infiltration of 10 immune cell types were observed between two subclusters. Subsequently, the prognostic signatures of nine DE_GRGs (CHST9, COLGALT1, FUT3, FUT6, HS3ST2, POMGNT2, ST8SIA4, UGT3A1, and UGT8) were established. Patients in the high-risk group showed a poorer prognosis relative to the low-risk group. According to univariate and multivariate Cox regression analyses, the risk score, stage, and grade could be independent prognostic factors. A nomogram incorporating information on gender, age, risk group, TNM stage, and clinical stage showed accurate prediction in the survival probability. Except for CHST9, HS3ST2, and ST8SIA4, expression patterns of the remaining 6 DE_GRGs in Caki-1 and 786-O cells were confirmed by quantitative real-time PCR. FUT6 overexpression resulted in the inhibition of proliferation, migration, and invasion of ccRCC cells.

Conclusion

This study established a nine-DE_GRG-based prognostic signature, which independently predicted ccRCC prognosis. This finding emphasizes that GRGs are stratification factors for the precise prognosis of ccRCC.

Cholesterol Metabolism and Urinary System Tumors

Cancers of the urinary system account for 13.1% of new cancer cases and 7.9% of cancer-related deaths. Of them, renal cancer, bladder cancer, and prostate cancer are most prevalent and pose a substantial threat to human health and the quality of life. Prostate cancer is the most common malignant tumor in the male urinary system. It is the second most common type of malignant tumor in men, with lung cancer surpassing its incidence and mortality. Bladder cancer has one of the highest incidences and is sex-related, with men reporting a significantly higher incidence than women. Tumor development in the urinary system is associated with factors, such as smoking, obesity, high blood pressure, diet, occupational exposure, and genetics. The treatment strategies primarily involve surgery, radiation therapy, and chemotherapy. Cholesterol metabolism is a crucial physiological process associated with developing and progressing urinary system tumors. High cholesterol levels are closely associated with tumor occurrence, invasion, and metastasis. This warrants thoroughly investigating the role of cholesterol metabolism in urinary system tumors and identifying novel treatment methods for the prevention, early diagnosis, targeted treatment, and drug resistance of urinary system tumors.

Fatty acid metabolism-related lncRNAs are potential biomarkers for survival prediction in clear cell renal cell carcinoma

Metabolic reprogramming of energy is a newly recognized characteristic of cancer. In our current investigation, we examined the possible predictive importance of long noncoding RNAs (lncRNAs) associated to fatty acid metabolism in clear cell renal cell carcinoma (ccRCC). We conducted an analysis of the gene expression data obtained from patients diagnosed with ccRCC using the Cancer Genome Atlas (TCGA) database and the ArrayExpress database. We performed a screening to identify lncRNAs that are differentially expressed in fatty acid metabolism. Based on these findings, we developed a prognostic risk score model using these fatty acid metabolism-related lncRNAs. We then validated this model using Cox regression analysis, Kaplan-Meier survival analysis, and principal-component analysis (PCA). Furthermore, the prognostic risk score model was successfully validated using both the TCGA cohort and the E-MTAB-1980 cohort. We utilized gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to determine the correlation between fatty acid metabolism and the PPAR signaling pathway in patients with ccRCC at various clinical stages and prognoses. We have discovered compelling evidence of the interaction between immune cells in the tumor microenvironment and tumor cells, which leads to immune evasion and resistance to drugs. This was achieved by the utilization of advanced techniques such as the CIBERSORT method, ESTIMATE R package, ssGSEA algorithm, and TIMER database exploration. Ultimately, we have established a network of competing endogenous RNA (ceRNA) that is related to fatty acid metabolism. The findings of our study suggest that medicines focused on fatty acid metabolism could be clinically significant for individuals with ccRCC. The utilization of this risk model, which is centered around the lncRNAs associated with fatty acid metabolism, could potentially provide valuable prognostic information and hold immunotherapeutic implications for patients with ccRCC.

A Differential Transcriptional Regulome Approach to Unpack Cancer Biology: Insights on Renal Cell Carcinoma Subtypes

Cancer research calls for new approaches that account for the regulatory complexities of biology. We present, in this study, the differential transcriptional regulome (DIFFREG) approach for the identification and prioritization of key transcriptional regulators and apply it to the case of renal cell carcinoma (RCC) biology. Of note, RCC has a poor prognosis and the biomarker and drug discovery studies to date have tended to focus on gene expression independent from mutations and/or post-translational modifications. DIFFREG focuses on the differential regulation between transcription factors (TFs) and their target genes rather than differential gene expression and integrates transcriptome profiling with the human transcriptional regulatory network to analyze differential gene regulation between healthy and RCC cases. In this study, RNA-seq tissue samples (n = 1020) from the Cancer Genome Atlas (TCGA), including healthy and tumor subjects, were integrated with a comprehensive human TF-gene interactome dataset (1122603 interactions between 1289 TFs and 25177 genes). Comparative analysis of DIFFREG profiles, consisting of perturbed TF-gene interactions, from three common subtypes (clear cell RCC, papillary RCC and chromophobe RCC) revealed subtype-specific alterations, supporting the hypothesis that these signatures in the transcriptional regulome profiles may be considered potential biomarkers that may play an important role in elucidating the molecular mechanisms of RCC development and translating knowledge about the genetic basis of RCC into the clinic. In addition, these indicators may help oncologists make the best decisions for diagnosis and prognosis management.

A nomogram based on the preoperative neutrophil-to-lymphocyte ratio to distinguish sarcomatoid renal cell carcinoma from clear cell renal cell carcinoma

Objective

Our study aimed to assess the predictive value of the preoperative neutrophil-to-lymphocyte ratio(NLR) in distinguishing sarcomatoid renal cell carcinoma (SRCC) from clear cell renal cell carcinoma(CCRCC) and to developing a nomogram based on the preoperative NLR and other factors to distinguish SRCC from CCRCC.

Materials and methods

The database involved 280 patients, including 46 SRCC and 234 CCRCC. logistic analysis was conducted to select the variables associated with identifying SRCC preoperatively, and subgroup analysis was used to further validate the ability of NLR with preoperative identification of SRCC.In addition, The data were randomly separated into a training cohort(n=195) and a validation cohort(n=85). And an NLR-based nomogram was plotted based on the logistic analysis results. The nomogram was evaluated according to its discrimination, consistency, and clinical benefits.

Results

Multivariate analysis indicated that NLR, flank pain, tumor size, and total cholesterol(TC) were independent risk factors for identifying SRCC. The results of subgroup analysis showed that higher NLR was associated with a higher probability of SRCC in most subgroups. The area under the curve(AUC) of the training and validation cohorts were 0.801 and 0.738, respectively. The results of the calibration curve show high consistency between predicted and actual results. Decision Curve Analysis(DCA) showed clinical intervention based on the model was beneficial over most of the threshold risk range.

Conclusion

NLR is a potential indicator for preoperative differentiation of SRCC and CCRCC, and the predictive model constructed based on NLR has a good predictive ability. The new model could provide suggestions for the early identification of SRCC.

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.

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.

High VHL Expression Reverses Warburg Phenotype and Enhances Immunogenicity in Kidney Tumor Cells

Clear cell renal cell carcinoma (ccRCC) is a frequently occurring renal cancer. The Von Hippel-Lindau disease tumor suppressor VHL, a known tumor suppressor gene, is frequently mutated in about 50% of patients with ccRCC. However, it is unclear whether VHL influences the progression of ccRCC tumors expressing wild-type VHL. In the present study, we found that higher expression of VHL was correlated with the better disease-free survival (DFS) in ccRCC patients using The Cancer Genome Atlas (TCGA) datasets. We revealed that VHL overexpression in ccRCC cells inhibited epithelial-mesenchymal transition (EMT), sterol regulatory element-binding protein 1 (SREBP1)-regulated triglyceride synthesis, and cell proliferation. Proteomic analysis provided us a global view that VHL regulated four biological processes, including metabolism, immune regulation, apoptosis, and cell movement. Importantly, we found that VHL overexpression led to up-regulated expression of proteins associated with antigen processing and interferon-responsive proteins, thus rendering ccRCC cells more sensitive to interferon treatment. We defined an interferon-responsive signature (IRS) composed of ten interferon-responsive proteins, whose mRNA expression levels were positively correlated with DFS in ccRCC patients. Taken together, our results propose that the subset of ccRCC patients with high VHL expression benefit from immunotherapy.

CYP27A1 inhibits proliferation and migration of clear cell renal cell carcinoma via activation of LXRs/ABCA1

Cholesterol homeostasis plays an important role in the maintenance of normal body functions. CYP27A1 is a key enzyme known to regulate cholesterol homeostasis, which catalyzes the conversion of cholesterol to 27-HC and has been implicated in the occurrence and metastasis of various cancer types. The present study aimed to explore the regulatory role of CYP27A1 in the development of clear cell renal cell carcinoma (ccRCC). In particular, the effect of CYP27A1 on the proliferation and migration of ccRCC cells was investigated. The construction of a stable 786-O cell line overexpressing CYP27A1/pLVX was mediated by lentiviral infection. The proliferative capacity was assessed using MTT and colony formation. Wound healing assay was used to measure cell migration. Production of intracellular cholesterol and 27-HC was detected by enzyme-linked immunosorbent assay. The LXRs/ABCA1 pathway of cholesterol metabolism regulation was studied by RT-qPCR and Western blotting analysis after cells were treated with stimulation agents of 27-HC or T0901317 and inhibition agents of siRNA or GSK2033. The results revealed that overexpression of CYP27A1 could increase the intracellular production of 27-HC and inhibit the proliferation and migration of 786-O cells. And the treatment of 786-O cells with 27-HC induced a similar effect. CYP27A1/27HC mediated activation of the liver X receptors (LXRs) could up-regulate the expression of ATP-binding cassette transporter A1 (ABCA1), further resulting in the reduction of intracellular cholesterol contents. All of these findings indicated a regulatory role of CYP27A1 in the proliferation and migration of ccRCC, via activating LXRs/ABCA1 to regulate cholesterol homeostasis.

AUP1 regulates lipid metabolism and induces lipid accumulation to accelerate the progression of renal clear cell carcinoma

Lipid metabolic reprogramming is a prominent feature of clear cell renal cell carcinoma (ccRCC). Lipid accumulation affects cellular energy homeostasis, biofilm synthesis, lipid signal transduction, and phenotypic transformation in ccRCC. Herein, a prognostic‐related model was constructed, and the prognostic utility of AUP1, a lipid droplet–regulating very low–density lipoprotein assembly factor, in ccRCC was determined through multiparameter analysis. AUP1 expression was significantly higher in clinical samples than in normal tissues and was closely associated with the clinical stage. The inhibition of AUP1 expression impaired the proliferation, migration, and invasion of ACHN and A498 ccRCC cells in vitro and in vivo. RNA‐seq analysis revealed that AUP1 inhibition can significantly reduce the contents of intracellular triglyceride and cholesterol and regulate cell growth by cell cycle arrest, promoting apoptosis and reversing epithelial‐mesenchymal transition. AUP1 regulated the synthesis of cholesterol esters and fatty acids (FAs) in ccRCC cells by targeting sterol O‐acyltransferase 1 and partially promoted the progression of ccRCC. AUP1 also induced lipid accumulation in ccRCC by promoting the de novo synthesis of FAs (inhibiting protein kinase AMP‐activated catalytic subunit alpha 2), inhibiting the rate‐limiting enzyme of FA β oxidation (carnitine palmitoyltransferase 1A), regulating the key enzyme of lipolysis (monoglyceride lipase, MGLL), and inhibiting the lipid transporter StAR‐related lipid transfer domain containing 5 (STARD5). However, it did not affect the intracellular cholesterol synthesis pathway. The differential expression and prognostic significance of MGLL and STARD5 in ccRCC should be further studied. AUP1 may serve as a new and effective potential target and prognostic marker for ccRCC.

Lipid metabolism reprogramming in renal cell carcinoma

Metabolic reprogramming is recognized as a hallmark of cancer. Lipids are the essential biomolecules required for membrane biosynthesis, energy storage, and cell signaling. Altered lipid metabolism allows tumor cells to survive in the nutrient-deprived environment. However, lipid metabolism remodeling in renal cell carcinoma (RCC) has not received the same attention as in other cancers. RCC, the most common type of kidney cancer, is associated with almost 15,000 death in the USA annually. Being refractory to conventional chemotherapy agents and limited available targeted therapy options has made the treatment of metastatic RCC very challenging. In this article, we review recent findings that support the importance of synthesis and metabolism of cholesterol, free fatty acids (FFAs), and polyunsaturated fatty acids (PUFAs) in the carcinogenesis and biology of RCC. Delineating the detailed mechanisms underlying lipid reprogramming can help to better understand the pathophysiology of RCC and to design novel therapeutic strategies targeting this malignancy.

Involvement of LDL and ox-LDL in Cancer Development and Its Therapeutical Potential

Lipid metabolism disorder is related to an increased risk of tumorigenesis and is involved in the rapid growth of cancer cells as well as the formation of metastatic lesions. Epidemiological studies have demonstrated that low-density lipoprotein (LDL) and oxidized low-density lipoprotein (ox-LDL) are closely associated with breast cancer, colorectal cancer, pancreatic cancer, and other malignancies, suggesting that LDL and ox-LDL play important roles during the occurrence and development of cancers. LDL can deliver cholesterol into cancer cells after binding to LDL receptor (LDLR). Activation of PI3K/Akt/mTOR signaling pathway induces transcription of the sterol regulatory element-binding proteins (SREBPs), which subsequently promotes cholesterol uptake and synthesis to meet the demand of cancer cells. Ox-LDL binds to the lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) and cluster of differentiation 36 (CD36) to induce mutations, resulting in inflammation, cell proliferation, and metastasis of cancer. Classic lipid-lowering drugs, statins, have been shown to reduce LDL levels in certain types of cancer. As LDL and ox-LDL play complicated roles in cancers, the potential therapeutic effect of targeting lipid metabolism in cancer therapy warrants more investigation.

Predicting Clear Cell Renal Cell Carcinoma Survival Using Kurtosis of Cytoplasm in the Hematoxylin Channel from Histology Slides

Purpose

Grade-dependent decrease of lipid storage in clear cell renal cell carcinoma (ccRCC) leads to morphology changes in HE sections. This study investigated the role of cytoplasmic features in frozen sections of ccRCC on prognosis using the digital pathology approach.

Methods

We established an automatic pipeline that performed tumor region selection, stain vector normalization, nuclei segmentation, and feature extraction based on the pathologic data from Shanghai General Hospital and The Cancer Genome Atlas database. Extracted features were subjected to survival analysis.

Results

Kurtosis of the cytoplasm in the hematoxylin channel was correlated with progression-free survival (HR 0.10, 95% CI: 0.04–0.24, p=6.52^∗10⁻⁷) and overall survival (HR 0.11, 95% CI: 0.05–0.31, p=1.72^∗10⁻⁵) in ccRCC, which outperformed other texture features in this analysis. Multivariate Cox regression analysis revealed that low kurtosis of cytoplasm in the hematoxylin channel was an independent predictor for a shorter progression-free survival time (p=0.044) and overall survival time (p = 0.01). Kaplan–Meier survival analysis of progression-free survival and overall survival also showed a significantly worse prognosis in patients with low kurtosis of the cytoplasm in the hematoxylin channel (both p < 0.0001). Lower kurtosis of cytoplasm in the hematoxylin channel was associated with higher pathologic grade, less cholesterol ester, and more mitochondrial DNA content.

Conclusion

Kurtosis of the cytoplasm in the hematoxylin channel predicts survival in clear cell renal cell carcinoma.

SETD8 stabilized by USP17 epigenetically activates SREBP1 pathway to drive lipogenesis and oncogenesis of ccRCC

Recently, epigenetic modifications, including DNA methylation, histone modification and noncoding RNA (ncRNA)-associated gene silencing, have received increasing attention from the scientific community. Many studies have demonstrated that epigenetic regulation can render dynamic alterations in the transcriptional potential of a cell, which then affects the cell's biological function. The initiation and development of clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell cancer (RCC), is also closely related to genomic alterations by epigenetic modification. For ccRCC, lipid accumulation is one of the most typical characteristics. In other words, dysregulation of lipid uptake and synthesis occurs in ccRCC, which inversely promotes cancer proliferation and progression. However, the link among epigenetic alterations, lipid biosynthesis and renal cancer progression remains unclear. SETD8 is a histone methyltransferase and plays pivotal roles in cell cycle regulation and oncogenesis of various cancers, but its role in RCC is not well understood. In this study, we discovered that SETD8 was significantly overexpressed in RCC tumors, which was positively related to lipid storage and correlated with advanced tumor grade and stage and poor patient prognosis. Depletion of SETD8 by siRNAs or inhibitor UNC0379 diminished fatty acid (FA) de novo synthesis, cell proliferation and metastasis in ccRCC cells. Mechanistically, SETD8, which was posttranslationally stabilized by USP17, could transcriptionally modulate sterol regulatory element-binding protein 1 (SREBP1), a key transcription factor in fatty acid biosynthesis and lipogenesis, by monomethylating the 20th lysine of the H4 histone, elevating lipid biosynthesis and accumulation in RCC and further promoting cancer progression and metastasis. Taken together, the USP17/SETD8/SREBP1 signaling pathway plays a pivotal role in promoting RCC progression. SETD8 might be a novel biomarker and potential therapeutic target for treating RCC.

Diagnostic and prognostic value of ABC transporter family member ABCG1 gene in clear cell renal cell carcinoma

As the most common histologic subtype of renal cancer, clear cell renal cell carcinoma (ccRCC) poses a serious threat to public health. However, there are no specific molecular-targeted drugs for ccRCC at present. Human ATP-binding cassette (ABC) transporter family plays an important role in homeostasis maintenance. This study aimed to evaluate the potential diagnostic value of ABC genes in ccRCC. A total of 952 samples of ccRCC patients (707) and controls (245) from three different datasets were included for analysis. Receiver operating characteristic analysis and t-test were used to analyze the differential expression of ABC genes in ccRCC patients and control samples at mRNA level during screening and validations. The Cancer Genome Atlas (TCGA-ccRCC) dataset was utilized to investigate the correlation between ABC genes expression and prognostic value in ccRCC. We then investigated the interactions between ABCG1 and proteins in the Comparative Toxicogenomics Database (CTD). Finally, we found that ATP-binding cassette transporter G member 1 (ABCG1) was over-expressed in ccRCC patients compared with healthy samples at mRNA level. Cox regression analysis and Kaplan-Meier analysis showed that ccRCC patients with high ABCG1 expression had better overall survival (OS) than those patients with low expression (hazard ratio (HR) = 0.662, p = 0.007). This study demonstrated that ABCG1 is a potential diagnostic and prognostic biomarker in ccRCC and discussed the molecular mechanisms underlying the relationship between ccRCC and ABCG1, which might provide guidance for better management and treatment of ccRCC in the future.

Enzymes in the Cholesterol Synthesis Pathway: Interactomics in the Cancer Context

A global protein interactome ensures the maintenance of regulatory, signaling and structural processes in cells, but at the same time, aberrations in the repertoire of protein-protein interactions usually cause a disease onset. Many metabolic enzymes catalyze multistage transformation of cholesterol precursors in the cholesterol biosynthesis pathway. Cancer-associated deregulation of these enzymes through various molecular mechanisms results in pathological cholesterol accumulation (its precursors) which can be disease risk factors. This work is aimed at systematization and bioinformatic analysis of the available interactomics data on seventeen enzymes in the cholesterol pathway, encoded by HMGCR, MVK, PMVK, MVD, FDPS, FDFT1, SQLE, LSS, DHCR24, CYP51A1, TM7SF2, MSMO1, NSDHL, HSD17B7, EBP, SC5D, DHCR7 genes. The spectrum of 165 unique and 21 common protein partners that physically interact with target enzymes was selected from several interatomic resources. Among them there were 47 modifying proteins from different protein kinases/phosphatases and ubiquitin-protein ligases/deubiquitinases families. A literature search, enrichment and gene co-expression analysis showed that about a quarter of the identified protein partners was associated with cancer hallmarks and over-represented in cancer pathways. Our results allow to update the current fundamental view on protein-protein interactions and regulatory aspects of the cholesterol synthesis enzymes and annotate of their sub-interactomes in term of possible involvement in cancers that will contribute to prioritization of protein targets for future drug development.

LXR-Mediated Regulation of Marine-Derived Piericidins Aggravates High-Cholesterol Diet-Induced Cholesterol Metabolism Disorder in Mice

Reported as two antirenal cell carcinoma (RCC) drug candidates, marine-derived compounds piericidin A (PA) and glucopiericidin A (GPA) exhibit hepatotoxicity in renal carcinoma xenograft mice. Proteomics and transcriptomics reveal the hepatotoxicity related with cholesterol disposition since RCC is characterized by cholesterol accumulation. PA/GPA aggravate hepatotoxicity in high-cholesterol diet (HCD)-fed mice while exhibiting no toxicity in chow diet-fed mice. High cholesterol accumulation in liver is liver X receptor (LXR)-mediated cytochrome P450 family 7 subfamily a member 1 (CYP7A1) depression and low-density lipoprotein receptor (LDLR) activation. The farnesoid X nuclear receptor (FXR) is also depressed with a downregulated target gene OSTα. Different from PA directly combined with LXRα as an inhibitor, GPA exists as a prodrug in the liver and exerts toxic effects due to transformation into PA. Surface plasmon resonance (SPR) and docking results of 17 piericidins illustrate that glycosides exert no LXRα binding activity. A longer survival time of GPA-treated mice indicates that further exploration in anti-RCC drug research should focus on reducing glycosides transformed into PA and concentrating in the kidney tumor rather than the liver for lowering the risk of hepatotoxicity.

High SQLE Expression and Gene Amplification Correlates with Poor Prognosis in Head and Neck Squamous Cell Carcinoma

Objective

Squalene epoxidase (SQLE) is considered a metabolic oncogene, but its biological function and prognostic value in head and neck squamous cell carcinoma (HNSCC) remain unclear. We aimed to evaluate the role of SQLE in the occurrence and development of HNSCC through bioinformatics analysis, and validation experiments.

Methods

Transcriptomic, genomic, and clinical data from The Cancer Genome Atlas were used for pan-cancer analysis. SQLE expression in HNSCC was evaluated using Gene Expression Omnibus datasets and immunohistochemistry. The biological significance of SQLE in the tumor microenvironment (TME) of HNSCC was determined using TISCH, HuRI, LinkedOmics, and TIMER 2.0. The prognostic value of SQLE in HNSCC was analyzed using univariate Cox regression and Kaplan–Meier survival curves. Effect of SQLE on the Cal27 HNSCC cell line was evaluated using cell counting kit 8, wound healing, and EdU assays.

Results

SQLE was overexpressed and amplified in various cancers, including HNSCC. High SQLE expression promoted cell proliferation, associated with T stage in HNSCC patients. Copy number amplification and DNA demethylation contributed to high SQLE expression in HNSCC, which was associated with poor prognosis. SQLE was related to HNSCC TME, and its mRNA expression/copy number alterations were negatively correlated with the infiltration of CD8+ T cells, follicular helper T cells, and regulatory T cell infiltration and mast cell activation and positively correlated with the infiltration of M0 macrophages and resting mast cells in HNSCC.

Conclusion

SQLE was identified as a prognostic biomarker and a potential pharmaceutical target for HNSCC.

Apolipoprotein A1 is negatively associated with male papillary thyroid cancer patients: a cross-sectional study of single academic center in China

BACKGROUND

Papillary thyroid cancer (PTC) is the most common type of thyroid cancer and the incidence of PTC has continued to increase over the past decades. Many studies have shown that obesity is an independent risk factor for PTC and obese PTC patients tend to have a relative larger tumor size and higher grade of tumor stage. Obesity is associated with disordered lipid metabolism and the relationship between serum lipids and PTC remains unclear. Therefore, this study aimed to investigate the association between serum lipid level and PTC.

METHODS

We retrospectively analyzed 1018 PTC patients diagnosed and treated in our hospital, all these cases were first diagnosed with PTC and had complete clinical information including ultrasound reports before surgery, serum lipid (CHOL, TG, HDL-c, LDL-c, Apo-A1, Apo-B, Apo-E) results, surgical records and pathological reports.

RESULTS

None of these lipid markers were associated with tumor size in the whole cohort and in the female group. In the male group, on crude analysis, Apo-A1 showed a marginally association with tumor size, [OR = 0.158 (0.021-1.777)], p = 0.072. After adjusting for age and multifocality, Apo-A1 showed a significant association with tumor size [OR = 0.126 (0.016-0.974)], p = 0.047. This association become more apparent in a young male subgroup, [OR = 0.051 (0.005-0.497)], p = 0.009. CHOL, TG, HDL-c, LDL-c, Apo-B, Apo-E did not show significant association with tumor size. As for LNM, neither in the male group nor in the female group were found to be associated with any serum lipid biomarkers.

CONCLUSION

As PTC incidences continues to increase, our findings demonstrated a negatively association between PTC and apoA-1 in male PTC patients, which may contribute to further investigation concerning diagnosing and preventing this most common type of thyroid cancer.

The tumour microenvironment and metabolism in renal cell carcinoma targeted or immune therapy

Renal cell carcinoma (RCC) is one of the most common tumours of the urinary system, and is insidious and not susceptible to chemoradiotherapy. As the most common subtype of RCC (70-80% of cases), clear cell renal cell carcinoma (ccRCC) is characterized by the loss of von Hippel-Lindau and the accumulation of robust lipid and glycogen. For advanced RCC, molecular-targeted drugs, tyrosine kinase inhibitors (TKIs) and the immune checkpoint inhibitors (ICIs) have been increasingly recommended and investigated. Due to the existence of a highly dynamic, adaptive and heterogeneous tumour microenvironment (TME), and due to the glucose and lipid metabolism in RCC, this cancer may be accompanied by various types of resistance to TKIs and ICIs. With the increased production of lactate, nitric oxide, and other new by-products of metabolism, novel findings of the TME and key metabolic enzymes drived by HIF and other factors have been increasingly clarified in RCC carcinogenesis and therapy. However, there are few summaries of the TME and tumour metabolism for RCC progression and therapy. Here, we summarize and discuss the relationship of the important implicated characteristics of the TME as well as metabolic molecules and RCC carcinogenesis to provide prospects for future treatment strategies to overcome TME-related resistance in RCC.

Prognostic Effect of Preoperative Apolipoprotein B Level in Surgical Patients with Clear Cell Renal Cell Carcinoma

BACKGROUND

The aim of this study was to assess the prognostic value of the preoperative apolipoprotein B (ApoB) level in surgical patients with clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

The study included 307 ccRCC patients receiving radical or partial nephrectomy between 2003 and 2012 in our center. The correlations among the preoperative ApoB, clinicopathological parameters, and overall survival (OS) were evaluated.

RESULTS

A total of 193 males (62.9%) and 114 females (37.1%) with ccRCC who underwent radical or partial nephrectomy were enrolled in the present study. The OS at 5 years after the operation was 90.6% for all patients, 87.4% for the lower ApoB group, and 97.0% for the higher-ApoB group. The cause-specific survival (CSS) at 5 years after surgery was 90.2% for all patients, 86.7% for the lower-ApoB group, and 97.0% for the higher-ApoB group. A higher-ApoB level was related to a better OS and CSS in ccRCC patients (p = 0.001 and p < 0.001, respectively). In multivariate analysis, age >60 years (p = 0.008 and p = 0.023) and a lower Apo B level (p = 0.019 and p = 0.018) were independent prognostic factors for OS and CSS, respectively.

CONCLUSIONS

In the Apo apolipoprotein family, the preoperative ApoB level had an important clinical significance for predicting the prognosis and survival rate of ccRCC patients.

Comprehensive insights on pivotal prognostic signature involved in clear cell renal cell carcinoma microenvironment using the ESTIMATE algorithm

Emerging evidence has highlighted that the immune and stromal cells formed the majority of tumor microenvironment (TME) which are served as important roles in tumor progression. In our study, we aimed to screen vital prognostic signature associated with TME in clear cell renal cell carcinoma (ccRCC). We obtained total 611 samples from TCGA database consisting of transcriptome profiles and clinical data. ESTIMATE algorithm was applied to estimate the infiltrating fractions of immune/stromal cells. We found that the immune scores revealed more prognostic significance in overall survival and positive associations with risk clinical factors than stromal scores. We carried out differential expression analysis between Immunescore and stromalscore groups to obtain the 72 intersect genes. Protein to protein interaction (PPI) network and functional analysis was performed to indicate potential altered pathways. Additionally, we further conducted multivariate Cox analysis to identify 12 hub genes associated highly with TME of ccRCC using a stepwise regression procedure. Accordingly, risk score was constructed from the multivariate Cox results and Receiver Operating Characteristic (ROC) curve was used to assess the predictive value (AUC = 0.781). The ccRCC patients with high risk scores suffered poor survival outcomes than that with low risk scores. In the validation cohort from GSE53757, TNFSF13B, CASP5, and GJB6 correlated positively with tumor stages, while FREM1 negatively correlated with tumor stages. Importantly, we further observed that TNFSF13B, CASP5 and XCR1 showed the remarkable correlations with tumor‐infiltrating immune cells. Taken together, our research identified specific signatures that related to the infiltration of stromal and immune cells in TME of ccRCC using the transciptome profiles, which reached a comprehensive understanding of tumor microenvironment in ccRCC.

Uptake of HDL-cholesterol contributes to lipid accumulation in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC), which accounts for the majority of kidney cancer, is known to accumulate excess cholesterol. However, the mechanism and functional significance of the lipid accumulation for development of the cancer remains obscure. In this study, we analyzed 42 primary ccRCC samples, and determined that cholesterol levels of ~ 70% of the tumors were at least two-fold higher than that of benign kidney tissues. Compared to tumors without cholesterol accumulation, those containing excess cholesterol expressed higher levels of scavenger receptor BI (SR-B1), a receptor for uptake of HDL-associated cholesterol, but not genes involved in cholesterol synthesis and uptake of LDL-associated cholesterol. To further determine the roles of sterol accumulation for cancer development, we implanted ccRCC from patients into mouse kidneys using a mouse ccRCC xenograft model. Feeding mice with probucol, a compound lowing HDL-cholesterol, markedly reduced levels of cholesterol in tumors containing excess cholesterol. This treatment, however, did not affect growth of these tumors. Our study suggests that cholesterol overaccumulation in ccRCC is the consequence of increased uptake of HDL-cholesterol as a result of SR-B1 overexpression, but the lipid accumulation by itself may not play a significant role in progression of the cancer.

Gender- and cholesterol-specific predictive value of body mass index in renal cell carcinoma: A multicenter study

AIM

Recently, there have been some reports on preoperative body mass index (BMI) and total cholesterol (TC) as a prognostic predictor for patients with renal cell carcinoma (RCC) but the topic is controversial and still poorly understood. So we analyzed the effects of BMI and TC on the prognosis of RCC.

METHODS

Retrospective data from 1988 to 2015 were collected from eight centers with a total of 7,271 patients surgically treated for nonmetastatic RCC. Receiver operating characteristic curve analysis was analyzed and the highest Youden index was shown at 163.5 mg/dL. According to the Asian BMI criteria, patients were divided into normal BMI < 25 kg/m² and high BMI ≥ 25 kg/m² . Kaplan-Meier analysis, multivariate Cox regression model were performed to identify the overall survival (OS) and the recurrence-free survival (RFS).

RESULTS

Normal BMI and low TC group was associated with the shortest OS and RFS as compared to the other groups significantly. In the male patients, the results showed similar to the whole sample. But in the female, BMI had no effect on both OS and RFS. On multivariate Cox regression analysis, low TC was an independent predictor for OS in both genders. However, normal BMI was a significant prognostic factor in the males only.

CONCLUSION

Preoperative BMI and TC are good predictive factors for both OS and RFS significantly in RCC patients. Also, TC was an independent predictor for OS in all RCC patients; however, BMI was a significant predictor in males only.

The glutathione redox system is essential to prevent ferroptosis caused by impaired lipid metabolism in clear cell renal cell carcinoma

Metabolic reprogramming is a prominent feature of clear cell renal cell carcinoma (ccRCC). Here we investigated metabolic dependencies in a panel of ccRCC cell lines using nutrient depletion, functional RNAi screening and inhibitor treatment. We found that ccRCC cells are highly sensitive to the depletion of glutamine or cystine, two amino acids required for glutathione (GSH) synthesis. Moreover, silencing of enzymes of the GSH biosynthesis pathway or glutathione peroxidases, which depend on GSH for the removal of cellular hydroperoxides, selectively reduced viability of ccRCC cells but did not affect the growth of non-malignant renal epithelial cells. Inhibition of GSH synthesis triggered ferroptosis, an iron-dependent form of cell death associated with enhanced lipid peroxidation. VHL is a major tumour suppressor in ccRCC and loss of VHL leads to stabilisation of hypoxia inducible factors HIF-1α and HIF-2α. Restoration of functional VHL via exogenous expression of pVHL reverted ccRCC cells to an oxidative metabolism and rendered them insensitive to the induction of ferroptosis. VHL reconstituted cells also exhibited reduced lipid storage and higher expression of genes associated with oxidiative phosphorylation and fatty acid metabolism. Importantly, inhibition of β-oxidation or mitochondrial ATP-synthesis restored ferroptosis sensitivity in VHL reconstituted cells. We also found that inhibition of GSH synthesis blocked tumour growth in a MYC-dependent mouse model of renal cancer. Together, our data suggest that reduced fatty acid metabolism due to inhibition of β-oxidation renders renal cancer cells highly dependent on the GSH/GPX pathway to prevent lipid peroxidation and ferroptotic cell death.

Cholesterol promotes the migration and invasion of renal carcinoma cells by regulating the KLF5/miR-27a/FBXW7 pathway

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal subtype of renal cell carcinoma. Accumulation of cholesterol and cholesterol ester is a remarkable feature of ccRCC. However, the effect of cholesterol on ccRCC remains unknown. Out results showed that cholesterol treatment significantly promoted cells migration and invasion in ccRCC. Mechanism analysis indicated that cholesterol induced KLF5 expression. KLF5 positively regulated the transcription of miR-27a, increasing miR-27a expression. MiR-27a directly targeted FBXW7 by binding to its 3'UTR, reducing FBXW7 expression. FBXW7 silencing further increased the expression of KLF5 and miR-27a, and promoted cells migration and invasion. These results suggested that cholesterol accelerated ccRCC cells migration and invasion by regulating KLF5/miR-27a/FBXW7 axis.

Metabolic reprogramming of the tumor microenvironment by p62 and its partners

The concerted metabolic reprogramming across cancer and normal cellular compartments of the tumor microenvironment can favor tumorigenesis by increasing the survival and proliferating capacities of transformed cells. p62 has emerged as a critical signaling adaptor, beyond its role in autophagy, by playing an intricate context-dependent role in metabolic reprogramming of the cell types of the tumor and stroma, which shapes the tumor microenvironment to control tumor progression. Focusing on metabolic adaptations, we review the cellular processes upstream and downstream of p62 that regulate how distinct cell types adapt to the challenging and evolving environmental conditions during tumor initiation and progression. In addition, we describe partners of p62 that, in a collaborative or independent manner, can also rewire cell metabolism. Finally, we discuss the potential therapeutic implications of targeting p62 in cancer, considering its multifaceted roles in diverse cell types of the tumor microenvironment.

Lysosomal acid lipase promotes cholesterol ester metabolism and drives clear cell renal cell carcinoma progression

OBJECTIVES

Clear cell renal cell carcinoma (ccRCC) is characterized histologically by accumulation of cholesterol esters, cholesterol and other neutral lipids. Lysosomal acid lipase (LAL) is a critical enzyme involved in the cholesterol ester metabolism. Here, we sought to determine whether LAL could orchestrate metabolism of cholesterol esters in order to promote ccRCC progression.

MATERIALS AND METHODS

Quantitative reverse-transcription PCR and western blots were conducted to assess the expression of LAL in human ccRCC tissues. We analysed the relationship between LAL levels and patient survival using tissue microarrays. We used cell proliferation assays, colony formation assays, cell death assays, metabolic assays and xenograft tumour models to evaluate the biological function and underlying mechanisms.

RESULTS

LAL was up-regulated in ccRCC tissue. Tissue microarray analysis revealed higher levels of LAL in advanced grades of ccRCC, and high LAL expression indicated lower patient survival. Suppressing LAL expression not only blocked the utilization of cholesterol esters but also impaired proliferation and cellular survival. Furthermore, immunohistochemistry staining showed that LAL expression was correlated with Akt phosphorylation. Suppressing LAL expression decreased the phosphorylation level of Akt and Src and reduced the level of 14,15-epoxyeicosatrienoic acids in ccRCC cells. Supplement of 14,15-epoxyeicosatrienoic acids rescued proliferation in vitro and in vivo.

CONCLUSIONS

LAL promoted cell proliferation and survival via metabolism of epoxyeicosatrienoic acids and activation of the Src/Akt pathway.

A computational method using differential gene expression to predict altered metabolism of multicellular organisms

Altered metabolism is often identified as a cause or an effect of physiology and pathogenesis. But it is difficult to predict the metabolic flux distributions of multicellular organisms due to the lack of an explicit metabolic objective function. Here we present a computational method which can successfully describe the differences in metabolism between two different conditions on a large scale. By integrating gene expression data with an existing comprehensive reconstruction of the global human metabolic network, we qualitatively predicted significantly differential fluxes without prior knowledge or the rate of metabolite uptake and secretion. Therefore, this method can be applied for both microorganisms and multicellular organisms. Different from traditional enrichment analysis methods and constraint-based models, we consider conditions and interactions within the metabolic network simultaneously. To apply the proposed method, we predicted altered fluxes for E. coli strains and clear cell renal cell carcinoma, while the E. coli strains are growing aerobically in a chemostat with different dilution rates and clear cell renal cell carcinoma is compared with normal kidney cells. Then we map the significantly differential reactions to metabolic subsystems defined in the original metabolic network for ccRCC to observe the altered metabolism. In contrast with existing studies, our results show a high accuracy of the E. coli experiment and a more reasonable prediction of the ccRCC experiment. The method presented here provides a computational approach for the genome-wide study of altered metabolism under pairs of conditions for both microorganisms and multicellular organisms.

Rational Targeting of Cellular Cholesterol in Diffuse Large B-Cell Lymphoma (DLBCL) Enabled by Functional Lipoprotein Nanoparticles: A Therapeutic Strategy Dependent on Cell of Origin

Cancer cells have altered metabolism and, in some cases, an increased demand for cholesterol. It is important to identify novel, rational treatments based on biology, and cellular cholesterol metabolism as a potential target for cancer is an innovative approach. Toward this end, we focused on diffuse large B-cell lymphoma (DLBCL) as a model because there is differential cholesterol biosynthesis driven by B-cell receptor (BCR) signaling in germinal center (GC) versus activated B-cell (ABC) DLBCL. To specifically target cellular cholesterol homeostasis, we employed high-density lipoprotein-like nanoparticles (HDL NP) that can generally reduce cellular cholesterol by targeting and blocking cholesterol uptake through the high-affinity HDL receptor, scavenger receptor type B-1 (SCARB1). As we previously reported, GC DLBCL are exquisitely sensitive to HDL NP as monotherapy, while ABC DLBCL are less sensitive. Herein, we report that enhanced BCR signaling and resultant de novo cholesterol synthesis in ABC DLBCL drastically reduces the ability of HDL NPs to reduce cellular cholesterol and induce cell death. Therefore, we combined HDL NP with the BCR signaling inhibitor ibrutinib and the SYK inhibitor R406. By targeting both cellular cholesterol uptake and BCR-associated de novo cholesterol synthesis, we achieved cellular cholesterol reduction and induced apoptosis in otherwise resistant ABC DLBCL cell lines. These results in lymphoma demonstrate that reduction of cellular cholesterol is a powerful mechanism to induce apoptosis. Cells rich in cholesterol require HDL NP therapy to reduce uptake and molecularly targeted agents that inhibit upstream pathways that stimulate de novo cholesterol synthesis, thus, providing a new paradigm for rationally targeting cholesterol metabolism as therapy for cancer.

Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI

BACKGROUND

Dysregulated lipid and glucose metabolism in clear cell renal cell carcinoma (ccRCC) has been implicated in disease progression, and whole tumor tissue-based assessment of these changes is challenged by the tumor heterogeneity. We studied a noninvasive quantitative MRI method that predicts metabolic alterations in the whole tumor.

METHODS

We applied Dixon-based MRI for in vivo quantification of lipid accumulation (fat fraction [FF]) in targeted regions of interest of 45 primary ccRCCs and correlated these MRI measures to mass spectrometry-based lipidomics and metabolomics of anatomically colocalized tissue samples isolated from the same tumor after surgery.

RESULTS

In vivo tumor FF showed statistically significant (P < 0.0001) positive correlation with histologic fat content (Spearman correlation coefficient, ρ = 0.79), spectrometric triglycerides (ρ = 0.56) and cholesterol (ρ = 0.47); it showed negative correlation with free fatty acids (ρ = -0.44) and phospholipids (ρ = -0.65). We observed both inter- and intratumoral heterogeneity in lipid accumulation within the same tumor grade, whereas most aggressive tumors (International Society of Urological Pathology [ISUP] grade 4) exhibited reduced lipid accumulation. Cellular metabolites in tumors were altered compared with adjacent renal parenchyma.

CONCLUSION

Our results support the use of noninvasive quantitative Dixon-based MRI as a biomarker of reprogrammed lipid metabolism in ccRCC, which may serve as a predictor of tumor aggressiveness before surgical intervention.

FUNDING

NIH R01CA154475 (YZ, MF, PK, IP), NIH P50CA196516 (IP, JB, RJD, JAC, PK), Welch Foundation I-1832 (JY), and NIH P01HL020948 (JGM).

Hypoxia-inducible factor 1α activates insulin-induced gene 2 (Insig-2) transcription for degradation of 3-hydroxy-3-methylglutaryl (HMG)-CoA reductase in the liver

Cholesterol synthesis is a highly oxygen-consuming process. As such, oxygen deprivation (hypoxia) limits cholesterol synthesis through incompletely understood mechanisms mediated by the oxygen-sensitive transcription factor hypoxia-inducible factor 1α (HIF-1α). We show here that HIF-1α links pathways for oxygen sensing and feedback control of cholesterol synthesis in human fibroblasts by directly activating transcription of the INSIG-2 gene. Insig-2 is one of two endoplasmic reticulum membrane proteins that inhibit cholesterol synthesis by mediating sterol-induced ubiquitination and subsequent endoplasmic reticulum-associated degradation of the rate-limiting enzyme in the pathway, HMG-CoA reductase (HMGCR). Consistent with the results in cultured cells, hepatic levels of Insig-2 mRNA were enhanced in mouse models of hypoxia. Moreover, pharmacologic stabilization of HIF-1α in the liver stimulated HMGCR degradation via a reaction that requires the protein's prior ubiquitination and the presence of the Insig-2 protein. In summary, our results show that HIF-1α activates INSIG-2 transcription, leading to accumulation of Insig-2 protein, which binds to HMGCR and triggers its accelerated ubiquitination and degradation. These results indicate that HIF-mediated induction of Insig-2 and degradation of HMGCR are physiologically relevant events that guard against wasteful oxygen consumption and inappropriate cell growth during hypoxia.

Intratumor Heterogeneity in Primary Kidney Cancer Revealed by Metabolic Profiling of Multiple Spatially Separated Samples within Tumors

Metabolic alteration constitutes a hallmark of cancer. Glycolysis and antioxidant pathways in kidney cancer are elevated, with frequent mutation of the VHL gene. Intratumor genetic heterogeneity has been recently demonstrated in kidney cancer. However, intratumor metabolic heterogeneity has not been investigated. Here, we used global metabolomics analysis and tissue slice tracer studies to demonstrate that different portions of a human primary kidney tumor possess different metabolic characteristics and drug sensitivity. Pyruvate levels were elevated and pyruvate metabolism was altered in some tumor sections. These observations indicated that pyruvate metabolism may constitute a possible vulnerability of kidney cancer; indeed, pyruvate stimulated the growth of primary kidney cancer cells and pharmacological inhibition of pyruvate transporters slowed the growth of patient-derived kidney tumors in mice. These findings deepen our understanding of the intratumor metabolic heterogeneity of kidney cancer and may inform novel therapeutic approaches in human kidney cancer.

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Human primary kidney tumors harbor intratumor metabolic heterogeneity.

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Some tumor portions have high pyruvate levels with low glycolysis metabolites.

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Different pyruvate metabolic pathways are present in a tumor and represent a potential vulnerability

Understanding the features of cancer can lead to effective cancer therapy. One of the reasons why anti-cancer drugs have limited efficacy is the existence of intratumor heterogeneity. Intratumor heterogeneity is usually revealed by diverse genetic alterations. In this study, we studied metabolic features to comprehend intratumor heterogeneity. In human primary kidney tumors, some portions contained high levels of upper-glycolysis metabolites; however, other portions contained high pyruvate levels. Difference in pyruvate metabolism was observed in a tumor. Additional studies suggested that pyruvate metabolism represented a vulnerability in kidney cancer.

Mice lacking lipid droplet-associated hydrolase, a gene linked to human prostate cancer, have normal cholesterol ester metabolism

Variations in the gene LDAH (C2ORF43), which encodes lipid droplet-associated hydrolase (LDAH), are among few loci associated with human prostate cancer. Homologs of LDAH have been identified as proteins of lipid droplets (LDs). LDs are cellular organelles that store neutral lipids, such as triacylglycerols and sterol esters, as precursors for membrane components and as reservoirs of metabolic energy. LDAH is reported to hydrolyze cholesterol esters and to be important in macrophage cholesterol ester metabolism. Here, we confirm that LDAH is localized to LDs in several model systems. We generated a murine model in which Ldah is disrupted but found no evidence for a major function of LDAH in cholesterol ester or triacylglycerol metabolism in vivo, nor a role in energy or glucose metabolism. Our data suggest that LDAH is not a major cholesterol ester hydrolase, and an alternative metabolic function may be responsible for its possible effect on development of prostate cancer.

Renal Carcinogenesis, Tumor Heterogeneity, and Reactive Oxygen Species: Tactics Evolved

SIGNIFICANCE

The number of kidney cancers is growing 3-5% each year due to unknown etiologies. Intra- and inter-tumor mediators increase oxidative stress and drive tumor heterogeneity. Recent Advances: Technology advancement in state-of-the-art instrumentation and methodologies allows researchers to detect and characterize global landscaping modifications in genes, proteins, and pathophysiology patterns at the single-cell level.

CRITICAL ISSUES

We postulate that the sources of reactive oxygen species (ROS) and their activation within subcellular compartments will change over a timeline of tumor evolvement and contribute to tumor heterogeneity. Therefore, the complexity of intracellular changes within a tumor and ROS-induced tumor heterogeneity coupled to the advancement of detecting these events globally are limited at the level of data collection, organization, and interpretation using software algorithms and bioinformatics.

FUTURE DIRECTIONS

Integrative and collaborative research, combining the power of numbers with careful experimental design, protocol development, and data interpretation, will translate cancer biology and therapeutics to a heightened level or leave the abundant raw data as stagnant and underutilized. Antioxid. Redox Signal. 25, 685-701.

Glioblastomas with copy number gains in EGFR and RNF139 show increased expressions of carbonic anhydrase genes transformed by ENO1

Background

Prominence of glycolysis in glioblastomas may be non-specific or a feature of oncogene-related subgroups (i.e. amplified EGFR, etc.). Relationships between amplified oncogenes and expressions of metabolic genes associated with glycolysis, directly or indirectly via pH, were therefore investigated.

Methods

Using multiplex ligation-dependent probe amplification, copy numbers (CN) of 78 oncogenes were quantified in 24 glioblastomas. Related expressions of metabolic genes encoding lactate dehydrogenases (LDHA, LDHC), carbonic anhydrases (CA3, CA12), monocarboxylate transporters (SLC16A3 or MCT4, SLC16A4 or MCT5), ATP citrate lyase (ACLY), glycogen synthase1 (GYS1), hypoxia inducible factor-1A (HIF1A), and enolase1 (ENO1) were determined in 22 by RT-qPCR. To obtain supra-glycolytic levels and adjust for heterogeneity, concurrent ENO1 expression was used to mathematically transform the expression levels of metabolic genes already normalized with delta-delta crossing threshold methodology.

Results

Positive correlations with EGFR occurred for all metabolic genes. Significant differences (Wilcoxon Rank Sum) for oncogene CN gains in tumors of at least 2.00-fold versus less than 2.00-fold occurred for EGFR with CA3's expression (p < 0.03) and for RNF139 with CA12 (p < 0.004). Increased CN of XIAP associated negatively. Tumors with less than 2.00-fold CN gains differed from those with gains for XIAP with CA12 (p < 0.05). Male gender associated with CA12 (p < 0.05).

Conclusions

Glioblastomas with CN increases in EGFR had elevated CA3 expression. Similarly, tumors with RNF149 CN gains had elevated CA12 expression.

General significance

In larger studies, subgroups of glioblastomas may emerge according to oncogene-related effects on glycolysis, such as control of pH via effects on carbonic anhydrases, with prognostic and treatment implications.

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PCR of glioblastomas show oncogene copy numbers relate to metabolic gene expressions.

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ENO1(ENOLASE1) transformations yielded “supra-glycolytic” metabolic gene expressions.

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EGFR, RNF139, and XIAP associated with expressions of two carbonic anhydrase genes.

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Male gender associated (+) with the transformed expression of carbonic anhydrase 12.

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Oncogene amplifications may aid control of pH to protect glycolysis in glioblastomas.

Lipid rafts, KCa/ClCa/Ca2+ channel complexes and EGFR signaling: Novel targets to reduce tumor development by lipids?

Membrane lipid rafts are distinct plasma membrane nanodomains that are enriched with cholesterol, sphingolipids and gangliosides, with occasional presence of saturated fatty acids and phospholipids containing saturated acyl chains. It is well known that they organize receptors (such as Epithelial Growth Factor Receptor), ion channels and their downstream acting molecules to regulate intracellular signaling pathways. Among them are Ca2+ signaling pathways, which are modified in tumor cells and inhibited upon membrane raft disruption. In addition to protein components, lipids from rafts also contribute to the organization and function of Ca2+ signaling microdomains. This article aims to focus on the lipid raft KCa/ClCa/Ca2+ channel complexes that regulate Ca2+ and EGFR signaling in cancer cells, and discusses the potential modification of these complexes by lipids as a novel therapeutic approach in tumor development. This article is part of a Special Issue entitled: Membrane channels and transporters in cancers.

The UPS and downs of cholesterol homeostasis

An emerging theme in the regulation of cholesterol homeostasis is the role of the ubiquitin proteasome system (UPS), through which proteins are ubiquitylated and then degraded in response to specific signals. The UPS controls all aspects of cholesterol metabolism including its synthesis, uptake, and efflux. We review here recent work uncovering the ubiquitylation and degradation of key players in cholesterol homeostasis. This includes the low-density lipoprotein (LDL) receptor, transcription factors (sterol regulatory element binding proteins and liver X receptors), flux-controlling enzymes in cholesterol synthesis (3-hydroxy-3-methylglutaryl-CoA reductase and squalene monooxygenase), and cholesterol exporters (ATP-binding cassette transporters ABCA1 and ABCG1). We explore which E3 ligases are involved, and identify areas deserving of further research.

Dysregulated D-dopachrome tautomerase, a hypoxia-inducible factor-dependent gene, cooperates with macrophage migration inhibitory factor in renal tumorigenesis

Clear cell renal cell carcinomas (ccRCCs) are characterized by biallelic loss of the von Hippel-Lindau tumor suppressor and subsequent constitutive activation of the hypoxia-inducible factors, whose transcriptional programs dictate major phenotypic attributes of kidney tumors. We recently described a role for the macrophage migration inhibitory factor (MIF) in ccRCC as an autocrine-signaling molecule with elevated expression in tumor tissues and in the circulation of patients that has potent tumor cell survival effects. MIF is a pleiotropic cytokine implicated in a variety of diseases and cancers and is the target of both small molecule and antibody-based therapies currently in clinical trials. Recent work by others has described D-dopachrome tautomerase (DDT) as a functional homologue of MIF with a similar genomic structure and expression patterns. Thus, we sought to determine a role for DDT in renal cancer. We find that DDT expression mirrors MIF expression in ccRCC tumor sections with high correlation and that, mechanistically, DDT is a novel hypoxia-inducible gene and direct target of HIF1α and HIF2α. Functionally, DDT and MIF demonstrate a significant overlap in controlling cell survival, tumor formation, and tumor and endothelial cell migration. However, DDT inhibition consistently displayed more severe effects on most phenotypes. Accordingly, although dual inhibition of DDT and MIF demonstrated additive effects in vitro, DDT plays a dominant role in tumor growth in vivo. Together, our findings identify DDT as a functionally redundant but more potent cytokine to MIF in cancer and suggest that current attempts to inhibit MIF signaling may fail because of DDT compensation.