The metabolic basis of kidney cancer

Comparative physiological, biochemical and transcriptomic analyses to reveal potential regulatory mechanisms in response to starvation stress in Cipangopaludina chinensis

Cipangopaludina chinensis, as a financially significant species in China, represents a gastropod in nature which frequently encounters starvation stress owing to its limited prey options. However, the underlying response mechanisms to combat starvation have not been investigated in depth. We collected C. chinensis under several times of starvation stress (0, 7, 30, and 60 days) for nutrient, biochemical characteristics and transcriptome analyses. The results showed that prolonged starvation stress (> 30 days) caused obvious fluctuations in the nutrient composition of snails, with dramatic reductions in body weight, survival and digestive enzyme activity (amylase, protease, and lipase), and markedly enhanced the antioxidant enzyme activities of the snails. Comparative transcriptome analyses revealed 3538 differentially expressed genes (DEGs), which were significantly associated with specific starvation stress-responsive pathways, including oxidative phosphorylation and alanine, aspartate, and glutamate metabolism. Then, we identified 40 candidate genes (e.g., HACD2, Cp1, CYP1A2, and GPX1) response to starvation stress through STEM and WGCNA analyses. RT-qPCR verified the accuracy and reliability of the high-throughput sequencing results. This study provides insights into snail overwintering survival and the potential regulatory mechanisms of snail adaptation to starvation stress.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Metabolic alterations in hereditary and sporadic renal cell carcinoma

Kidney cancer is the seventh leading cause of cancer in the world, and its incidence is on the rise. Renal cell carcinoma (RCC) is the most common form and is a heterogeneous disease comprising three major subtypes that vary in their histology, clinical course and driver mutations. These subtypes include clear cell RCC, papillary RCC and chromophobe RCC. Molecular analyses of hereditary and sporadic forms of RCC have revealed that this complex and deadly disease is characterized by metabolic pathway alterations in cancer cells that lead to deregulated oxygen and nutrient sensing, as well as impaired tricarboxylic acid cycle activity. These metabolic changes facilitate tumour growth and survival. Specifically, studies of the metabolic features of RCC have led to the discovery of oncometabolites - fumarate and succinate - that can promote tumorigenesis, moonlighting functions of enzymes, and substrate auxotrophy owing to the disruption of pathways that enable the production of arginine and cholesterol. These metabolic alterations within RCC can be exploited to identify new therapeutic targets and interventions, in combination with novel approaches that minimize the systemic toxicity of metabolic inhibitors and reduce the risk of drug resistance owing to metabolic plasticity.

Comparative analyses define differences between BHD-associated renal tumour and sporadic chromophobe renal cell carcinoma

BACKGROUND

Birt-Hogg-Dubé (BHD) syndrome, caused by germline alteration of folliculin (FLCN) gene, develops hybrid oncocytic/chromophobe tumour (HOCT) and chromophobe renal cell carcinoma (ChRCC), whereas sporadic ChRCC does not harbor FLCN alteration. To date, molecular characteristics of these similar histological types of tumours have been incompletely elucidated.

METHODS

To elucidate renal tumourigenesis of BHD-associated renal tumours and sporadic renal tumours, we conducted whole genome sequencing (WGS) and RNA-sequencing (RNA-seq) of sixteen BHD-associated renal tumours from nine unrelated BHD patients, twenty-one sporadic ChRCCs and seven sporadic oncocytomas. We then compared somatic mutation profiles with FLCN variants and RNA expression profiles between BHD-associated renal tumours and sporadic renal tumours.

FINDINGS

RNA-seq analysis revealed that BHD-associated renal tumours and sporadic renal tumours have totally different expression profiles. Sporadic ChRCCs were clustered into two distinct clusters characterized by L1CAM and FOXI1 expressions, molecular markers for renal tubule subclasses. Increased mitochondrial DNA (mtDNA) copy number with fewer variants was observed in BHD-associated renal tumours compared to sporadic ChRCCs. Cell-of-origin analysis using WGS data demonstrated that BHD-associated renal tumours and sporadic ChRCCs may arise from different cells of origin and second hit FLCN alterations may occur in early third decade of life in BHD patients.

INTERPRETATION

These data further our understanding of renal tumourigenesis of these two different types of renal tumours with similar histology.

FUNDING

This study was supported by JSPS KAKENHI Grants, RIKEN internal grant, and the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), Center for Cancer Research.

Clinical Characteristics of Molecularly Defined Renal Cell Carcinomas

Kidney tumors comprise a broad spectrum of different histopathological entities, with more than 0.4 million newly diagnosed cases each year, mostly in middle-aged and older men. Based on the description of the 2022 World Health Organization (WHO) classification of renal cell carcinoma (RCC), some new categories of tumor types have been added according to their specific molecular typing. However, studies on these types of RCC are still superficial, many types of these RCC currently lack accurate diagnostic standards in the clinic, and treatment protocols are largely consistent with the treatment guidelines for clear cell RCC (ccRCC), which might result in worse treatment outcomes for patients with these types of molecularly defined RCC. In this article, we conduct a narrative review of the literature published in the last 15 years on molecularly defined RCC. The purpose of this review is to summarize the clinical features and the current status of research on the detection and treatment of molecularly defined RCC.

A new glance at autophagolysosomal-dependent or -independent function of transcriptional factor EB in human cancer

Autophagy-lysosome system plays a variety of roles in human cancers. In addition to being implicated in metabolism, it is also involved in tumor immunity, remodeling the tumor microenvironment, vascular proliferation, and promoting tumor progression and metastasis. Transcriptional factor EB (TFEB) is a major regulator of the autophagy-lysosomal system. With the in-depth studies on TFEB, researchers have found that it promotes various cancer phenotypes by regulating the autophagolysosomal system, and even in an autophagy-independent way. In this review, we summarize the recent findings about TFEB in various types of cancer (melanoma, pancreatic ductal adenocarcinoma, renal cell carcinoma, colorectal cancer, breast cancer, prostate cancer, ovarian cancer and lung cancer), and shed some light on the mechanisms by which it may serve as a potential target for cancer treatment.

Epigenetic and transcriptomic characterization reveals progression markers and essential pathways in clear cell renal cell carcinoma

Identifying tumor-cell-specific markers and elucidating their epigenetic regulation and spatial heterogeneity provides mechanistic insights into cancer etiology. Here, we perform snRNA-seq and snATAC-seq in 34 and 28 human clear cell renal cell carcinoma (ccRCC) specimens, respectively, with matched bulk proteogenomics data. By identifying 20 tumor-specific markers through a multi-omics tiered approach, we reveal an association between higher ceruloplasmin (CP) expression and reduced survival. CP knockdown, combined with spatial transcriptomics, suggests a role for CP in regulating hyalinized stroma and tumor-stroma interactions in ccRCC. Intratumoral heterogeneity analysis portrays tumor cell-intrinsic inflammation and epithelial-mesenchymal transition (EMT) as two distinguishing features of tumor subpopulations. Finally, BAP1 mutations are associated with widespread reduction of chromatin accessibility, while PBRM1 mutations generally increase accessibility, with the former affecting five times more accessible peaks than the latter. These integrated analyses reveal the cellular architecture of ccRCC, providing insights into key markers and pathways in ccRCC tumorigenesis.

Emerging roles of TFE3 in metabolic regulation

TFE3 is a member of the MiT family of the bHLH-leucine zipper transcription factor. We previously focused on the role of TFE3 in autophagy and cancer. Recently, an increasing number of studies have revealed that TFE3 plays an important role in metabolic regulation. TFE3 participates in the metabolism of energy in the body by regulating pathways such as glucose and lipid metabolism, mitochondrial metabolism, and autophagy. This review summarizes and discusses the specific regulatory mechanisms of TFE3 in metabolism. We determined both the direct regulation of TFE3 on metabolically active cells, such as hepatocytes and skeletal muscle cells, and the indirect regulation of TFE3 through mitochondrial quality control and the autophagy-lysosome pathway. The role of TFE3 in tumor cell metabolism is also summarized in this review. Understanding the diverse roles of TFE3 in metabolic processes can provide new avenues for the treatment of some metabolism-related disorders.

Mitochondrial redox adaptations enable alternative aspartate synthesis in SDH-deficient cells

The oxidative tricarboxylic acid (TCA) cycle is a central mitochondrial pathway integrating catabolic conversions of NAD +to NADH and anabolic production of aspartate, a key amino acid for cell proliferation. Several TCA cycle components are implicated in tumorigenesis, including loss-of-function mutations in subunits of succinate dehydrogenase (SDH), also known as complex II of the electron transport chain (ETC), but mechanistic understanding of how proliferating cells tolerate the metabolic defects of SDH loss is still lacking. Here, we identify that SDH supports human cell proliferation through aspartate synthesis but, unlike other ETC impairments, the effects of SDH inhibition are not ameliorated by electron acceptor supplementation. Interestingly, we find aspartate production and cell proliferation are restored to SDH-impaired cells by concomitant inhibition of ETC complex I (CI). We determine that the benefits of CI inhibition in this context depend on decreasing mitochondrial NAD+/NADH, which drives SDH-independent aspartate production through pyruvate carboxylation and reductive carboxylation of glutamine. We also find that genetic loss or restoration of SDH selects for cells with concordant CI activity, establishing distinct modalities of mitochondrial metabolism for maintaining aspartate synthesis. These data therefore identify a metabolically beneficial mechanism for CI loss in proliferating cells and reveal how compartmentalized redox changes can impact cellular fitness.

Adjuvant Therapy for Renal Cell Carcinoma: End Points, Outcomes, and Risk Assessments

PURPOSE

Targeted tyrosine kinase inhibitors (TKIs) and immune-checkpoint inhibitors (ICIs) revolutionized the treatment of metastatic renal cell carcinoma (RCC). Efforts to translate these therapies into the adjuvant setting for local and locoregional RCC have been pursued over the past decade. We sought to provide an updated review of the literature regarding adjuvant therapy in RCC, as well as an analysis of patient characteristics that may portend the most favorable responses.

MATERIALS AND METHODS

Using PubMed, Google Scholar, and Wiley Online Library, we reviewed articles between 2000 and 2022. Search terms included "tyrosine kinase inhibitors," "adjuvant," "immunotherapy," and "renal cell carcinoma." The articles included were original and published in English. Information on clinical trials was collected from ClinicalTrials.gov, accessed in June 2022.

RESULTS

Landmark trials investigating adjuvant vascular endothelial growth factor (VEGF) inhibitors produced conflicting results, with only a single trial of sunitinib (S-TRAC) resulting in US Food and Drug Administration-approval on the basis of a slightly prolonged progression-free survival (PFS). Subsequent meta-analyses failed to show a benefit for adjuvant VEGF inhibitors. Several trials evaluating ICIs are currently ongoing, with pembrolizumab (KEYNOTE-564) earning US Food and Drug Administration-approval for a prolonged PFS, although overall survival data are not yet mature. Preliminary results from other adjuvant ICI trials have been conflicting.

CONCLUSION

There remains a lack of clear benefit for the use of adjuvant VEGF inhibitors in local and locoregional RCC. Adjuvant ICI investigations are ongoing, with promising results from KEYNOTE-564. It remains to be seen if PFS is an adequate surrogate end point for overall survival. Selection of patients at greatest risk for recurrence, and identification of those at greatest risk of rare but serious adverse events, may improve outcomes.

An Overview of Epigenetics in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) represents a heterogenous group of cancers with complex genetic background and histological varieties, which require various clinical therapies. Clear cell RCC represents the most common form of RCC that accounts for 3 out of 4 RCC cases. Screening methods for RCC lack sensitivity and specificity, and thus biomarkers that will allow early diagnosis are crucial. The impact of epigenetics in the development and progression of cancer, including RCC, is significant. Noncoding RNAs, histone modifications and DNA methylation represent fundamental epigenetic mechanisms and have been proved to be promising biomarkers. MicroRNAs have advantageous properties that facilitate early diagnosis of RCC, while their expression profiles have been assessed in renal cancer samples (tissue, blood, and urine). Current literature reports the up-regulation of mir122, mir1271 and mir15b in RCC specimens, which induces cell proliferation via FOXP-1 and PTEN genes. However, it should be noted that conflicting results are found in urine and serum patient samples. Moreover, promoters of at least 200 genes are methylated in renal cancers leading to epigenetic dysregulation. In this review, we analyze the vast plethora of studies that have evaluated the role of epigenetic mechanisms in RCC patients and their clinical importance.

Aberrant gene expression pattern in the glycolysis-cholesterol synthesis axis is linked with immune infiltration and prognosis in prostate cancer: A bioinformatics analysis

Aberrant lipid metabolism is an early event in tumorigenesis and has been found in a variety of tumor types, especially prostate cancer (PCa). Therefore, We hypothesize that PCa can be stratified into metabolic subgroups based on glycolytic and cholesterogenic related genes, and the different subgroups are closely related to the immune microenvironment. Bioinformatics analysis of genomic, transcriptomic, and clinical data from a comprehensive cohort of PCa patients was performed. Datasets included the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) dataset, GSE70768, our previously published PCa cohort. The unsupervised cluster analysis was employed to stratify PCa samples based on the expression of metabolic-related genes. Four molecular subtypes were identified, named Glycolytic, Cholesterogenic, Mixed, and Quiescent. Each metabolic subtype has specific features. Among the 4 subtypes, the cholesterogenic subtype exhibited better median survival, whereas patients with high expression of glycolytic genes showed the shortest survival. The mitochondrial pyruvate carriers (MPC) 1 exhibited expression difference between PCa metabolic subgroups, but not for MPCs 2. Glycolytic subtypes had lower immune cell scores, while Cholesterogenic subgroups had higher immune cell scores. Our results demonstrated that metabolic classifications based on specific glycolytic and cholesterol-producing pathways provide new biological insights into previously established subtypes and may guide develop personalized therapies for unique tumor metabolism characteristics.

Conditional Covalent Lethality Driven by Oncometabolite Accumulation

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is a cancer predisposition syndrome driven by mutation of the tumor suppressor fumarate hydratase (FH). Inactivation of FH causes accumulation of the electrophilic oncometabolite fumarate. In the absence of methods for reactivation, tumor suppressors can be targeted via identification of synthetic lethal interactions using genetic screens. Inspired by recent advances in chemoproteomic target identification, here, we test the hypothesis that the electrophilicity of the HLRCC metabolome may produce unique susceptibilities to covalent small molecules, a phenomenon we term conditional covalent lethality. Screening a panel of chemically diverse electrophiles, we identified a covalent ligand, MP-1, that exhibits FH-dependent cytotoxicity. Synthesis and structure-activity profiling identified key molecular determinants underlying the molecule's effects. Chemoproteomic profiling of cysteine reactivity together with clickable probes validated the ability of MP-1 to engage an array of functional cysteines, including one lying in the Zn-finger domain of the tRNA methyltransferase enzyme TRMT1. TRMT1 overexpression rescues tRNA methylation from inhibition by MP-1 and partially attenuates the covalent ligand's cytotoxicity. Our studies highlight the potential for covalent metabolites and small molecules to synergistically produce novel synthetic lethal interactions and raise the possibility of applying phenotypic screening with chemoproteomic target identification to identify new functional oncometabolite targets.

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

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

Genomic and Metabolic Hallmarks of SDH- and FH-deficient Renal Cell Carcinomas

BACKGROUND

Succinate dehydrogenase-deficient and fumarate hydratase-deficient renal cell carcinomas (SDHRCC and FHRCC) are rare kidney cancers driven by loss of TCA cycle enzymes.

OBJECTIVE

To define and compare the genomic and metabolomic hallmarks of SDHRCC and FHRCC.

DESIGN, SETTING, AND PARTICIPANTS

We analyzed SDHRCC and FHRCC tumors with either immunohistochemical evidence of loss of protein expression or genomically confirmed biallelic inactivation of SDHA/B/C/D/AF2 or FH.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Somatic alterations were identified using clinical pipelines, with allele-specific copy number alterations (CNAs) identified using FACETS. Mass spectrometry-based metabolomic profiling was performed on available SDHRCC and FHRCC tumors.

RESULTS AND LIMITATIONS

Tumors were analyzed for 42 patients (25 FHRCC, 17 SDHRCC). In the germline analysis, 16/17 SDHRCCs harbored a germline alteration in SDHB, whereas only 17/22 FHRCCs had pathogenic germline FH variants. SDHRCCs had a lower mutation burden (p = 0.02) and CNA burden (p = 0.0002) than FHRCCs. All SDHRCCs presented with deletion of chromosome 1p (overlapping SDHB), whereas FHRCCs demonstrated high but not ubiquitous loss of 1q (FH locus). Both SDHRCCs and FHRCCs exhibited significant idiopathic accumulation of the metabolite guanine. FHRCC tumors had elevated levels of urea cycle metabolites (argininosuccinate, citrulline, and fumarate), whereas SDHRCC tumors had elevation of numerous acylcarnitines. These characteristic metabolic changes allowed identification of a previously unrecognized SDH-deficient RCC.

CONCLUSIONS

Despite sharing similar genetic etiology, SDHRCC and FHRCC represent distinct molecular entities with unique genetic and metabolic abnormalities.

PATIENT SUMMARY

Kidney cancers driven by loss of the gene encoding either the succinate dehydrogenase or fumarate hydratase enzyme are rare. We sought to define and compare the genetic and metabolic features of these cancer entities.

Major heritable renal cell carcinoma syndromes: novel treatment options and future perspectives

PURPOSE OF REVIEW

To provide an overview of diagnosis, genetic abnormalities, clinical signs and treatment options for the major heritable renal cell carcinoma (RCC) syndromes.

RECENT FINDINGS

RCC in major hereditary syndromes are disorders which are typically autosomal dominant. They predispose patients to early onset of RCC and may exhibit other extrarenal manifestations. Early recognition of these diseases allows correct screening at appropriate ages as well as early detection of RCC. Moreover, expedient identification may optimize the management of extra renal manifestations as well as allow for genetic testing and screening of at-risk relatives.

SUMMARY

The risk of RCC in these major heritable syndromes is higher than sporadic disease. They occur at earlier age groups and can be multifocal or bilateral. Tumours are observed until at least 3 cm before any intervention, while nephron sparing surgery is widely considered as the treatment of choice except for hereditary leiomyomatosis with renal cell cancer, of which radical nephrectomy is treatment of choice. Intervention should be timeous as there is a highly reported incidence of early metastasis. Molecular therapies have been used in the setting of patients with metastasis, some of which show favourable outcomes.

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

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

Differential VHL mutation patterns in bilateral clear cell RCC distinguishes between independent primary tumors and contralateral metastatic disease

OBJECTIVE

To evaluate whether bilateral, multifocal clear cell renal cell carcinoma (ccRCC) patients can be differentiated by VHL mutation analysis into cases that represent either multiple independently arising primary tumors, or a single primary tumor which has spread ipsilaterally as well as to the contralateral kidney. The nature of kidney cancer multifocality outside of known hereditary syndromes is as yet poorly understood.

MATERIALS AND METHODS

DNA from multiple tumors per patient were evaluated for somatic VHL gene mutation and hypermethylation. A subset of tumors with shared VHL mutations were analyzed with targeted, next-generation sequencing assays.

RESULTS

This cohort contained 5 patients with multiple tumors that demonstrated a shared somatic VHL mutation consistent with metastatic spread including to the contralateral kidney. In several cases this was substantiated by additional shared somatic mutations in ccRCC-associated genes. In contrast, the remaining 14 patients with multiple tumors demonstrated unique, unshared VHL alterations in every analyzed tumor, consistent with independently arising kidney tumors. None of these latter patients showed any evidence of local spread or distant metastasis.

CONCLUSION

The spectrum of VHL alterations within evaluated bilateral, multifocal ccRCC tumors from a single patient can distinguish between multiple independent tumor growth and metastasis. This can be performed using currently available clinical genetic tests and will improve the accuracy of patient diagnosis and prognosis, as well as informing appropriate management.

Renal hypoxia-HIF-PHD-EPO signaling in transition metal nephrotoxicity: friend or foe?

The kidney is the main organ that senses changes in systemic oxygen tension, but it is also the key detoxification, transit and excretion site of transition metals (TMs). Pivotal to oxygen sensing are prolyl-hydroxylases (PHDs), which hydroxylate specific residues in hypoxia-inducible factors (HIFs), key transcription factors that orchestrate responses to hypoxia, such as induction of erythropoietin (EPO). The essential TM ion Fe is a key component and regulator of the hypoxia–PHD–HIF–EPO (HPHE) signaling axis, which governs erythropoiesis, angiogenesis, anaerobic metabolism, adaptation, survival and proliferation, and hence cell and body homeostasis. However, inadequate concentrations of essential TMs or entry of non-essential TMs in organisms cause toxicity and disrupt health. Non-essential TMs are toxic because they enter cells and displace essential TMs by ionic and molecular mimicry, e. g. in metalloproteins. Here, we review the molecular mechanisms of HPHE interactions with TMs (Fe, Co, Ni, Cd, Cr, and Pt) as well as their implications in renal physiology, pathophysiology and toxicology. Some TMs, such as Fe and Co, may activate renal HPHE signaling, which may be beneficial under some circumstances, for example, by mitigating renal injuries from other causes, but may also promote pathologies, such as renal cancer development and metastasis. Yet some other TMs appear to disrupt renal HPHE signaling, contributing to the complex picture of TM (nephro-)toxicity. Strikingly, despite a wealth of literature on the topic, current knowledge lacks a deeper molecular understanding of TM interaction with HPHE signaling, in particular in the kidney. This precludes rationale preventive and therapeutic approaches to TM nephrotoxicity, although recently activators of HPHE signaling have become available for therapy.

The genomic landscape of pediatric renal cell carcinomas

Pediatric renal cell carcinomas (RCC) differ from their adult counterparts not only in histologic subtypes but also in clinical characteristics and outcome. However, the underlying biology is still largely unclear. For this reason, we performed whole-exome and transcriptome sequencing analyses on a cohort of 25 pediatric RCC patients with various histologic subtypes, including 10 MiT family translocation (MiT) and 10 papillary RCCs. In this cohort of pediatric RCC, we find only limited genomic overlap with adult RCC, even within the same histologic subtype. Recurrent somatic mutations in genes not previously reported in RCC were detected, such as in CCDC168, PLEKHA1, VWF, and MAP3K9. Our papillary pediatric RCCs, which represent the largest cohort to date with comprehensive molecular profiling in this age group, appeared as a distinct genomic subtype differing in terms of gene mutations and gene expression patterns not only from MiT-RCC but also from their adult counterparts.

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WES and RNA-seq of 25 pediatric RCCs with various histologic subtypes

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Detected only limited genomic overlap with adult RCC

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Revealed recurrent somatic mutations in genes not previously reported in RCC

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Discovery of a CRK-PITPNA fusion gene in a pediatric papillary RCC

Toll-Like Receptors Serve as Biomarkers for Early Diagnosis and Prognosis Assessment of Kidney Renal Clear Cell Carcinoma by Influencing the Immune Microenvironment: Comprehensive Bioinformatics Analysis Combined With Experimental Validation

Background: Toll-like receptors (TLRs) are important initiators of innate and acquired immune responses. However, its role in kidney renal clear cell carcinoma (KIRC) remains unclear.

Methods: TLRs and their relationships with KIRC were studied in detail by ONCOMINE, UALCAN, GEPIA, cBioPortal, GeneMANIA, FunRich, LinkedOmics, TIMER and TRRUST. Moreover, we used clinical samples to verify the expressions of TLR3 and TLR4 in early stage of KIRC by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), flow cytometry (FC) and immunohistochemistry (IHC).

Results: The expression levels of TLRs in KIRC were generally different compared with adjacent normal tissues. Moreover, the expressions of TLR3 and TLR4 elevated significantly in the early stage of KIRC. Overexpressions of TLR1, TLR3, TLR4 and TLR8 in KIRC patients were associated with longer overall survival (OS), while inhibition of TLR9 expression was related to longer OS. Additionally, overexpressions of TLR1, TLR3 and TLR4 in KIRC patients were associated with longer disease free survival (DFS). There were general genetic alterations and obvious co-expression correlation of TLRs in KIRC. The PPI network between TLRs was rather complex, and the key gene connecting the TLRs interaction was MYD88. The GO analysis and KEGG pathway analysis indicated that TLRs were closely related to adaptive immunity, innate immunity and other immune-related processes. RELA, NFKB1, IRF8, IRF3 and HIF1A were key transcription factors regulating the expressions of TLRs. What’s more, the expression levels of all TLRs in KIRC were positively correlated with the infiltration levels of dendritic cells, macrophages, neutrophils, B cells, CD4⁺ T cells and CD8⁺ T cells. Finally, the results of RT-qPCR, FC and IHC confirmed that TLR3 and TLR4 were significantly elevated in the early stage of KIRC.

Conclusion: The occurrence and development of KIRC are closely related to TLRs, and TLRs have the potential to be early diagnostic biomarkers of KIRC and biomarkers for judging the prognosis and immune status of KIRC. This study may provide new insights into the selection of KIRC immunotherapy targets.

The prognostic significance of controlling nutritional status (CONUT) score for surgically treated renal cell cancer and upper urinary tract urothelial cancer: a systematic review and meta-analysis

In order to evaluate the predictive effect of the controlled nutritional status (CONUT) score on the prognosis of patients with renal cell carcinoma (RCC) and upper urinary tract urothelial carcinoma (UTUC), a meta-analysis was performed. This systematic review has been registered on PROSPERO, the registration ID is CRD42021251879. A systematic search of the published literature using PubMed, Web of Science, Cochrane Library, EMBASE, and MEDLINE was performed. The fields of "renal cell cancer," "upper tract urothelial cancer," and "controlling nutritional status" and other fields were used as search terms. STATA 16 software was used to carry out data merging and statistical analysis of binary variables, Q test and χ² tests were used to verify the heterogeneity between the included works of studies. Subgroup analysis and sensitivity analysis were used to explain the sources of heterogeneity between studies. Begg's test was used to assess publication bias between studies. From the first 542 studies retrieved, through strict inclusion and exclusion criteria, 7 studies finally met the requirements and were included in the meta-analysis. Pooled results indicated that high CONUT indicates worse over survival (OS) [HR = 1.70, 95% CI (1.43-2.03), P = 0.02], cancer-specific survival (CSS) [HR = 1.84, 95% CI (1.52-2.23), P = 0.01], recurrence-free survival (RFS) [HR = 1.60, 95% CI (1.26-2.03), P = 0.116], and disease-free survival (DFS) [HR = 1.47, 95% CI (1.20-1.81), P = 0.03]. Based on cancer type, cutoff value, region, and sample size, a subgroup analysis was performed. The results showed that OS and CSS were not affected by the above factors, and the high CONUT score before surgery predicted worse OS and CSS. In conclusion, this meta-analysis revealed that the preoperative CONUT score is a potential independent predictor of the postoperative prognosis of RCC/UTUC patients. A high CONUT predicts worse OS/CSS/DFS and RFS in patients.

MCT1 expression is independently related to shorter cancer-specific survival in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) has been considered a metabolic disease, with loss of von Hippel-Lindau (VHL) gene and consequent overexpression of hypoxia-inducible factor 1 alpha (HIF-1α), which is central for tumor development and progression. Among other effects, HIF-1α is involved in the metabolic reprogramming of cancer cells towards the Warburg effect involved in tumor cell proliferation, migration and survival. In this context, several proteins are expressed by cancer cells, including glucose and lactate transporters as well as different pH regulators. Among them, monocarboxylate transporters (MCTs) can be highlighted. Our aim is to comprehensively analyze the immunoexpression of MCT1, MCT2, MCT4, CD147, CD44, HIF-1α, GLUT1 and CAIX in ccRCC surgical specimens correlating with classical prognostic factors and survival of patients with long follow up. Surgical specimens from 207 patients with ccRCC who underwent radical or partial nephrectomy were used to build a tissue microarray. Immunostaining was categorized into absent/weak or moderate/strong and related to all classic ccRCC prognostic parameters. Kaplan-Meier curves were generated to assess overall and cancer-specific survival, and multivariate analysis was performed to identify independent prognostic factors of survival. Multivariate analysis showed that MCT1 together with tumor size and TNM staging, were independently related to cancer-specific survival. MCT1, CD147, CD44 and GLUT1 expression were significantly associated with poor prognostic factors. We show that MCT1 is an independent prognostic factor for cancer-specific survival in ccRCC justifying the use of new target therapies already being tested in clinical trials.

Decision-making in active surveillance in kidney cancer: current trends and future urine and tissue markers

Surveillance for small renal masses is a growing choice of management amongst physicians and patients. These decisions, however, can be difficult as patient factors and tumor factors may blur the line between continued surveillance and intervention. Currently, there are no biomarkers that are readily available to aid in the decision making for patients with known renal cell carcinoma; however, many show promise. We herein review the literature of the adjunct tools that are currently available for decision making in small renal masses, but also new potential biomarkers that can potentially be of use.

Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning

Clear cell renal cell carcinoma (ccRCC) is the most common histological type of kidney cancer and has high heterogeneity. Stratification of ccRCC is important since distinct subtypes differ in prognosis and treatment. Here, we applied a systems biology approach to stratify ccRCC into three molecular subtypes with different mRNA expression patterns and prognosis of patients. Further, we developed a set of biomarkers that could robustly classify the patients into each of the three subtypes and predict the prognosis of patients. Then, we reconstructed subtype-specific metabolic models and performed essential gene analysis to identify the potential drug targets. We identified four drug targets, including SOAT1, CRLS1, and ACACB, essential in all the three subtypes and GPD2, exclusively essential to subtype 1. Finally, we repositioned mitotane, an FDA-approved SOAT1 inhibitor, to treat ccRCC and showed that it decreased tumor cell viability and inhibited tumor cell growth based on in vitro experiments.

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Three consistent molecular ccRCC subtypes were found to guide patients' prognoses

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REOs-based biomarker was developed to robustly classify patients at individual level

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SOAT1 is identified as a common drug target for all ccRCC subtypes

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Mitotane was repositioned treatment of ccRCC via inhibiting SOAT1

Comparison of PD-L1 Scores in Primary Kidney Tumors Versus Accompanying Venous Tumor Thrombi: Retrospective, Comparative, Monocentric Study in Treatment-Naive Patients

Introduction

Renal cell carcinoma (RCC), an immunogenic tumor, is the most common form of kidney cancer worldwide. Immune checkpoint inhibitors (ICIs) play an important role in the treatment of metastatic RCC. Programmed death-ligand (PD-L1) has already been proposed as a possible prognosticator for ICIs effectiveness. To elucidate the feasible role of ICIs in neoadjuvant settings, we have assessed the most common PD-L1 expression modalities [tumor proportion score (TPS), combined positivity score (CPS) and inflammatory cell (IC) score] in primary tumors (PTs) and venous tumor thrombi (VTT) in first diagnosed, previously untreated RCC patients with accompanying VTT.

Methods

Between January 1999 and December 2016, 71 patients with a first diagnosed, untreated, locally advanced RCC (aRCC) (≥ pT3a) underwent surgery in Hanover Medical School (MHH). PD-L1 expression was examined separately in PTs and VTT using the CPS, IC score and TPS. We also considered the age at the time of the initial surgery and gender as probable influencing factors. By using a cutoff value of 1 (1%), PD-L1 expression levels in PTs and VTT were assessed to enable the determination of any frequency differences.

Results

Positive scores for PTs were shown by 54 (CPS), 53 (IC score) and 34 (TPS) patients, whereas in VTT, positive scores were evaluated for a total of 50 (CPS), 47 (IC-score) and 36 (TPS) patients. No statistically significant differences were obtained between the PD-L1 expression immunoscores for PTs and VTT. The covariates age at the time of the initial surgery and gender could not be statistically proven to influence the differences in PD-L1 expression between the VTT and PTs.

Conclusion

To the best of our knowledge, this research is the largest study to investigate PD-L1 expression in PTs and VTT in 71 cases. It could have relevance for the future development of neoadjuvant immunotherapy options, particularly in aRCC with VTT.

SWI/SNF-deficient neoplasms of the genitourinary tract

Since the discovery of association of SMARCB1 mutations with malignant rhabdoid tumors and renal medullary carcinoma, mutations in genes of the SWI/SNF chromatin remodeling complex have been increasingly identified across a diverse spectrum of neoplasms. As a group, SWI/SNF complex subunit mutations are now recognized to be the second most frequent type of mutations across tumors. SMARCB1 mutations were originally reported in malignant rhabdoid tumors of the kidney and thought to be pathognomonic for this tumor. However, more broadly, recognition of typical rhabdoid cytomorphology and SMARCB1 mutations beyond rhabdoid tumors has changed our understanding of the pathobiology of these tumors. While mutations of SWI/SNF complex are diagnostic of rhabdoid tumors and renal medullary carcinoma, their clinical relevance extends to potential prognostic and predictive utility in other tumors as well. Beyond SMARCB1, the PBRM1 and ARID1A genes are the most frequently altered members of the SWI/SNF complex in genitourinary neoplasms, especially in clear cell renal cell carcinoma and urothelial carcinoma. In this review, we provide an overview of alterations in the SWI/SNF complex encountered in genitourinary neoplasms and discuss their increasing clinical importance.

Monocarboxylate transporter 1 promotes proliferation and invasion of renal cancer cells by mediating acetate transport

One hallmark of renal cell carcinoma (RCC) is metabolic reprogramming, which involves elevation of glycolysis and upregulation of lipid metabolism. However, the mechanism of metabolic reprogramming is incompletely understood. Monocarboxylate transporter 1 (MCT1) promotes transport for lactate and pyruvate, which are crucial for cell metabolism. The aim of present study was to investigate the function of MCT1 on RCC development and its mechanism on metabolic reprogramming. The results showed that MCT1 messenger RNA and protein levels significantly increased in cancer tissues of ccRCC compared to normal tissue. MCT1 was further found to mainly located in the cell membrane of RCC. The knockdown of MCT1 by RNAi significantly inhibited proliferation and migration of 786-O and ACHN cells. MCT1 also induced the expressions of proliferation marker Ki-67 and invasion marker SNAI1. Moreover, we also showed that acetate treatment could upregulate the expression of MCT1, but not other MCT isoforms. On the other hand, MCT1 was involved in acetate transport and intracellular histone acetylation. In summary, this study revealed that MCT1 is abnormally high in ccRCC and promotes cancer development. The regulatory effect of MCT1 on cell proliferation and invasion maybe mediated by acetate transport.

Mitochondrial DNA alterations underlie an irreversible shift to aerobic glycolysis in fumarate hydratase-deficient renal cancer

Understanding the mechanisms of the Warburg shift to aerobic glycolysis is critical to defining the metabolic basis of cancer. Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is an aggressive cancer characterized by biallelic inactivation of the gene encoding the Krebs cycle enzyme fumarate hydratase, an early shift to aerobic glycolysis, and rapid metastasis. We observed impairment of the mitochondrial respiratory chain in tumors from patients with HLRCC. Biochemical and transcriptomic analyses revealed that respiratory chain dysfunction in the tumors was due to loss of expression of mitochondrial DNA (mtDNA)-encoded subunits of respiratory chain complexes, caused by a marked decrease in mtDNA content and increased mtDNA mutations. We demonstrated that accumulation of fumarate in HLRCC tumors inactivated the core factors responsible for replication and proofreading of mtDNA, leading to loss of respiratory chain components, thereby promoting the shift to aerobic glycolysis and disease progression in this prototypic model of glucose-dependent human cancer.

A pan-kidney cancer study identifies subtype specific perturbations on pathways with potential drivers in renal cell carcinoma

Background

Renal cell carcinoma (RCC) is a complex disease and is comprised of several histological subtypes, the most frequent of which are clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (PRCC) and chromophobe renal cell carcinoma (ChRCC). While lots of studies have been performed to investigate the molecular characterizations of different subtypes of RCC, our knowledge regarding the underlying mechanisms are still incomplete. As molecular alterations are eventually reflected on the pathway level to execute certain biological functions, characterizing the pathway perturbations is crucial for understanding tumorigenesis and development of RCC.

Methods

In this study, we investigated the pathway perturbations of various RCC subtype against normal tissue based on differential expressed genes within a certain pathway. We explored the potential upstream regulators of subtype-specific pathways with Ingenuity Pathway Analysis (IPA). We also evaluated the relationships between subtype-specific pathways and clinical outcome with survival analysis.

Results

In this study, we carried out a pathway-based analysis to explore the mechanisms of various RCC subtypes with TCGA RNA-seq data. Both commonly altered pathways and subtype-specific pathways were detected. To identify the distinctive characteristics of each subtype, we focused on subtype-specific perturbed pathways. Specifically, we observed that some of the altered pathways were regulated by several recurrent upstream regulators which presenting different expression patterns among distinct RCC subtypes. We also noticed that a large number of perturbed pathways were controlled by the subtype-specific upstream regulators. Moreover, we also evaluated the relationships between perturbed pathways and clinical outcome. Prognostic pathways were identified and their roles in tumor development and progression were inferred.

Conclusions

In summary, we evaluated the relationships among pathway perturbations, upstream regulators and clinical outcome for differential subtypes in RCC. We hypothesized that the alterations of common upstream regulators as well as subtype-specific upstream regulators work together to affect the downstream pathway perturbations and drive cancer initialization and prognosis. Our findings not only increase our understanding of the mechanisms of various RCC subtypes, but also provide targets for personalized therapeutic intervention.

cg04448376, cg24387542, cg08548498, and cg14621323 as a Novel Signature to Predict Prognosis in Kidney Renal Papillary Cell Carcinoma

INTRODUCTION

DNA methylation plays a vital role in prognosis prediction of cancers. In this study, we aimed to identify novel DNA methylation site biomarkers and create an efficient methylated site model for predicting survival in kidney renal papillary cell carcinoma (KIRP).

METHODS

DNA methylation and gene expression profile data were downloaded from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Differential methylated genes (DMGs) and differential expression genes (DEGs) were identified and then searched for the hub genes. Cox proportional hazards regression was applied to identify DNA methylated site biomarkers from the hub genes. Kaplan-Meier survival and ROC analyses were used to validate the effective prognostic ability of the methylation gene site biomarker. The biomarker sites were validated in the GEO cohorts. The GO and KEGG annotation was done to explore the biological function of DNA methylated site signature.

RESULTS

Nine DMGs with opposite expression patterns containing 47 methylated sites were identified. Finally, four methylated sites were identified using the hazard regression model (cg04448376, cg24387542, cg08548498, and cg14621323) located in UTY, LGALS9B, SLPI, and PFN3, respectively. These sites classified patients into high- and low-risk groups in the training cohort. The 5-year survival rates for patients with low-risk and high-risk scores were 97.5% and 75.9% (P < 0.001). The prognostic accuracy and signature methylation sites were validated in the test (TCGA, n = 87) and GEO cohorts (n = 14). Multivariate regression analysis showed that the signature was an independent prediction prognostic factor for KIRP. Based on this analysis, we developed methylated site signature nomogram that predicts an individual's risk of survival. Functional analysis suggested that these signature genes are involved in the biological processes of protein binding.

CONCLUSIONS

Our study demonstrated that the methylated gene site signature might be a powerful prognostic tool for evaluating survival rate and guiding tailored therapy for KIRP patients.

Integration of Survival and Binary Data for Variable Selection and Prediction: A Bayesian Approach

We consider the problem where the data consist of a survival time and a binary outcome measurement for each individual, as well as corresponding predictors. The goal is to select the common set of predictors which affect both the responses, and not just only one of them. In addition, we develop a survival prediction model based on data integration. This article is motivated by the Cancer Genomic Atlas (TCGA) databank, which is currently the largest genomics and transcriptomics database. The data contain cancer survival information along with cancer stages for each patient. Furthermore, it contains Reverse-phase Protein Array (RPPA) measurements for each individual, which are the predictors associated with these responses. The biological motivation is to identify the major actionable proteins associated with both survival outcomes and cancer stages. We develop a Bayesian hierarchical model to jointly model the survival time and the classification of the cancer stages. Moreover, to deal with the high dimensionality of the RPPA measurements, we use a shrinkage prior to identify significant proteins. Simulations and TCGA data analysis show that the joint integrated modeling approach improves survival prediction.

An ensemble of deep neural networks for kidney ultrasound image classification

BACKGROUND AND OBJECTIVE

Chronic kidney disease is a worldwide health issue which includes not only kidney failure but also complications of reduced kidney functionality. Cyst formation, nephrolithiasis or kidney stone, and renal cell carcinoma or kidney tumor are the common kidney disorders which affects the functionality of kidneys. These disorders are typically asymptomatic, therefore early and automatic diagnosis of kidney disorders are required to avoid serious complications.

METHODS

This paper proposes an automatic classification of B-mode kidney ultrasound images based on the ensemble of deep neural networks (DNNs) using transfer learning. The ultrasound images are usually affected by speckle noise and quality selection in the ultrasound image is based on perception-based image quality evaluator score. Three variant datasets are given to the pre-trained DNN models for feature extraction followed by support vector machine for classification. The ensembling of different pre-trained DNNs like ResNet-101, ShuffleNet, and MobileNet-v2 are combined and final predictions are done by using the majority voting technique. By combining the predictions from multiple DNNs the ensemble model shows better classification performance than the individual models. The presented method proved its superiority when compared to the conventional and DNN based classification methods. The developed ensemble model classifies the kidney ultrasound images into four classes, namely, normal, cyst, stone, and tumor.

RESULTS

To highlight effectiveness of the proposed approach, the ensemble based approach is compared with the existing state-of-the-art methods and tested in the variants of ultrasound images like in quality and noisy conditions. The presented method resulted in maximum classification accuracy of 96.54% in testing with quality images and 95.58% in testing with noisy images. The performance of the presented approach is evaluated based on accuracy, sensitivity, and selectivity.

CONCLUSIONS

From the experimental analysis, it is clear that the ensemble of DNNs classifies the majority of images correctly and results in maximum classification accuracy as compared to the existing methods. This automatic classification approach is a supporting tool for the radiologists and nephrologists for precise diagnosis of kidney diseases.

The Role of Metabolic Factors in Renal Cancers

An increasing number of evidence indicates that metabolic factors may play an important role in the development and progression of certain types of cancers, including renal cell carcinoma (RCC). This tumour is the most common kidney cancer which accounts for approximately 3–5% of malignant tumours in adults. Numerous studies indicated that concomitant diseases, including diabetes mellitus (DM) and hypertension, as well as obesity, insulin resistance, and lipid disorders, may also influence the prognosis and cancer-specific overall survival. However, the results of studies concerning the impact of metabolic factors on RCC are controversial. It appears that obesity increases the risk of RCC development; however, it may be a favourable factor in terms of prognosis. Obesity is closely related to insulin resistance and the development of diabetes mellitus type 2 (DM2T) since the adipocytes in visceral tissue secrete substances responsible for insulin resistance, e.g., free fatty acids. Interactions between insulin and insulin-like growth factor (IGF) system appear to be of key importance in the development and progression of RCC; however, the exact role of insulin and IGFs in RCC pathophysiology remains elusive. Studies indicated that diabetes increased the risk of RCC, but it might not alter cancer-related survival. The risk associated with a lipid profile is most mysterious, as numerous studies provided conflicting results. Even though large studies unravelling pathomechanisms involved in cancer growth are required to finally establish the impact of metabolic factors on the development, progression, and prognosis of renal cancers, it seems that the monitoring of health conditions, such as diabetes, low body mass index (BMI), and lipid disorders is of high importance in clear-cell RCC.

Targeting glycolysis with 2-deoxy-D-glucose sensitizes primary cell cultures of renal cell carcinoma to tyrosine kinase inhibitors

PURPOSE

To investigate the synergistic effect of glycolysis inhibition on therapy answer to tyrosine kinase inhibitors in renal carcinoma.

METHODS

Primary cell cultures from 33 renal tumors including clear cell RCC (ccRCC), papillary RCC and the rare subtype chromophobe RCC as well as two metastases of ccRCC were obtained and cultivated. The patient-derived cells were verified by immunohistochemistry. CcRCC cells were further examined by exon sequencing of the von Hippel-Lindau gene (VHL) and by RNA-sequencing. Next, cell cultures of all subtypes of RCC were exposed to increasing doses of various tyrosine kinase inhibitors (axitinib, cabozantinib and pazopanib) and the glycolysis inhibitor 2-deoxy-D-glucose, alone or combined. CellTiter-Glo^® Luminescence assay and Crystal Violet staining were used to assess the inhibition of glycolysis and the viability of the cultured primary cells.

RESULTS

The cells expressed characteristic tissue markers and, in case of ccRCC cultures, the VHL status of the tumor they derived from. An upregulation of HK1, PFKP and SLC2A1 was observed, while components of the respiratory chain were downregulated, confirming a metabolic shift towards aerobic glycolysis. The tumors displayed variable individual responses for the therapeutics. All subtypes of RCC were susceptible to cabozantinib treatment indicated by decreased proliferation. Adding 2-deoxy-D-glucose to tyrosine kinase inhibitors decreased ATP production and increased the susceptibility of ccRCC to pazopanib treatment.

CONCLUSION

This study presents a valuable tool to cultivate even uncommon and rare renal cancer subtypes and allows testing of targeted therapies as a personalized approach as well as testing new therapies such as glycolysis inhibition in an in vitro model.

Alterations in glycolytic/cholesterogenic gene expression in hepatocellular carcinoma

Metabolic reprogramming is a hallmark of tumors, including hepatocellular carcinoma (HCC). We used data from The Cancer Genome Atlas and the International Cancer Genome Consortium to assess the alterations in glycolytic and cholesterogenic genes in HCC and to determine their association with clinical features in HCC patients. Based on the gene expression profiles from these databases, we established four subtypes of HCC: cholesterogenic, glycolytic, mixed, and quiescent. The prognosis of the cholesterogenic subgroup was poorer than that of the glycolytic group. Tumors in the glycolytic group were more sensitive to chemotherapy. We also explored the relationships between these metabolic subtypes and previously established HCC subgroups. Glycolytic gene expression correlated strongly with poorer prognostic gene expression in the Hoshida classification of HCC. Whole-genome analyses indicated that aberrant amplification of TP53 and MYC in HCC were associated with abnormal anabolic cholesterol metabolism. The mRNA levels of mitochondrial pyruvate carriers 1 and 2 differed among the HCC metabolic subtypes. In a bioinformatics analysis we identified genomic characteristics of tumor metabolism that varied among different cancer types. These findings demonstrate that metabolic subtypes may be valuable prognostic indicators in HCC patients.

Identification of potential novel differentially-expressed genes and their role in invasion and migration in renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) remains one of the most common cancer types globally, and while it has been extensively studied, the molecular basis for its pathology remains incompletely understood. Herein, we profiled three previously published datasets (GSE66272, GSE100666, and GSE105261) in a single integrated analysis aimed at identifying disease-associated patterns of gene expression that may offer mechanistic insight into the drivers of this disease. We pooled expression data from 39 normal kidney samples and 39 kidney tumors, leading us to identify 310 differentially expressed genes (DEGs) that were linked to kidney cancer in all three analyzed datasets. Of these genes, 133 and 177 were up- and down-regulated, respectively, in cancer samples. We then incorporated these DEGs into a protein-protein interaction network with the STRING and Cytoscape tools, and we were able to identify signaling pathways significantly enriched for these DEGs. The relationship between DEG expression and ccRCC patient survival was further evaluated using a Kaplan-Meier approach, leading us to identify TIMP1 as an independent prognostic factor in ccRCC patients. When TIMP1 expression was disrupted in ccRCC cell lines, this impaired their migratory and invasive capabilities. In summary, we employed an integrative bioinformatics approach to identify ccRCC-related DEGs and associated signaling pathways. Together these findings offer novel insight into the mechanistic basis for ccRCC, potentially helping to identify novel therapeutic targets for the treatment of this deadly disease.

Discovery and validation of the prognostic value of the lncRNAs encoding snoRNAs in patients with clear cell renal cell carcinoma

Some lncRNAs can encode small nucleolar RNAs (snoRNAs), called small nucleolar RNA host genes (SNHGs), which have exerted certain predictive values for the prognosis of some cancer patients. In this study, using RNA-seq and survival data in TCGA-KIRC, we examined the expression profile of 20 SNHGs and explored their prognostic values in ccRCC. Results showed that SNHG1, GAS5, SNHG3-8, SNHG11, SNHG12, SNHG15-17, SNHG20, SNHG22 and SNHG25 were significantly upregulated in ccRCC tissues compared with adjacent normal tissues. After adjustment for confounding factors, the multivariate analysis confirmed that increased SNHG3 expression was independently associated with shorter OS, while increased SNHG15 expression was an independent predictor of shorter RFS. Using the methylation data, the methylation status of 2 CpG sites (cg07807470 and cg15161854) and 2 CpG sites (cg00953154 and cg16459265) were negatively correlated with SNHG3 and SNHG15 expression, respectively. Moreover, low methylation levels of the 4 CpG sites were significantly associated with shorter OS. Furthermore, we validated the expression patterns, methylation status and prognostic value of SNHG3 and SNHG15 using clinical ccRCC samples. Taken together, SNHG3 and SNHG15 might be valuable prognostic markers in ccRCC, and DNA hypomethylation might play an important role in elevated SNHG3 and SNHG15 transcription in ccRCC.

Oncometabolites in renal cancer

The study of cancer metabolism has evolved vastly beyond the remit of tumour proliferation and survival with the identification of the role of 'oncometabolites' in tumorigenesis. Simply defined, oncometabolites are conventional metabolites that, when aberrantly accumulated, have pro-oncogenic functions. Their discovery has led researchers to revisit the Warburg hypothesis, first postulated in the 1950s, of aberrant metabolism as an aetiological determinant of cancer. As such, the identification of oncometabolites and their utilization in diagnostics and prognostics, as novel therapeutic targets and as biomarkers of disease, are areas of considerable interest in oncology. To date, fumarate, succinate, L-2-hydroxyglutarate (L-2-HG) and D-2-hydroxyglutarate (D-2-HG) have been characterized as bona fide oncometabolites. Extensive metabolic reprogramming occurs during tumour initiation and progression in renal cell carcinoma (RCC) and three oncometabolites - fumarate, succinate and L-2-HG - have been implicated in this disease process. All of these oncometabolites inhibit a superfamily of enzymes known as α-ketoglutarate-dependent dioxygenases, leading to epigenetic dysregulation and induction of pseudohypoxic phenotypes, and also have specific pro-oncogenic capabilities. Oncometabolites could potentially be exploited for the development of novel targeted therapies and as biomarkers of disease.

Screening, identification and validation of CCND1 and PECAM1/CD31 for predicting prognosis in renal cell carcinoma patients

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers worldwide. Despite intense efforts to elucidate its pathogenesis, the molecular mechanisms and genetic characteristics of this cancer remain unknown. In this study, three expression profile data sets (GSE15641, GSE16441 and GSE66270) were integrated to identify candidate genes that could elucidate functional pathways in ccRCC. Expression data from 63 ccRCC tumors and 54 normal samples were pooled and analyzed. The GSE profiles shared 379 differentially expressed genes (DEGs), including 249 upregulated genes, and 130 downregulated genes. A protein-protein interaction network (PPI) was constructed and analyzed using STRING and Cytoscape. Functional and signaling pathways of the shared DEGs with significant p values were identified. Kaplan-Meier plots of integrated expression scores were used to analyze survival outcomes. These suggested that FN1, ICAM1, CXCR4, TYROBP, EGF, CAV1, CCND1 and PECAM1/CD31 were independent prognostic factors in ccRCC. Finally, to investigate early events in renal cancer, we screened for the hub genes CCND1 and PECAM1/CD31. In summary, integrated bioinformatics analysis identified candidate DEGs and pathways in ccRCC that could improve our understanding of the causes and underlying molecular events of ccRCC. These candidate genes and pathways could be therapeutic targets for ccRCC.

Three novel hub genes and their clinical significance in clear cell renal cell carcinoma

Purpose. To investigate the association of biomarkers correlated with clinical stages and survival of clear cell renal cell carcinoma (ccRCC).

Methods. The GSE36895 dataset was downloaded and differentially expressed or methylated genes were analyzed. Hub genes were identified with weighted gene co-expression network analysis (WGCNA) and protein-protein interaction network (PPI), and validated with TCGA database and our own tissues. The biological processes of hub genes were further explored by functional enrichment analysis. Survival analyses were also performed. The underlying mechanisms for ccRCC development were detected with Gene set enrichment analyses.

Results. A total of 1624 differentially expressed genes were analyzed by WGCNA and 6 co-expressed gene modules were identified. Three hub genes (EHHADH, ACADM and AGXT2) were met the criterion of both WGCNA and PPI networks analysis, which showed highest negative association with pathological T stage (r = - 0.45, p = 0.01) and tumor grade (r = - 0.45, p = 0.01). The downregulation of these hub genes was validated with using both TCGA database and samples harvested at our institute The biological processes that hub genes involved, such as metabolic process (p = 9.63E - 09), oxidation-reduction process (p = 1.05E - 08) and oxidoreductase activity (p = 1.72E - 04), were revealed. Survival analysis showed a higher expression or lower methylation of these hub genes, a longer survival of ccRCC patients. ccRCC samples with higher expression of hub genes were enriched in gene sets correlated with signaling like biosynthesis of unsaturated fatty acids, butanoate metabolism, and PPAR signaling pathway.

Conclusions. We identified three novel tumor suppressors associated with pathological T stage and overall survival of ccRCC. They might be potential as individualized therapeutic targets and diagnostic biomarkers for ccRCC.

Role of Positron Emission Tomography Imaging in Metabolically Active Renal Cell Carcinoma

PURPOSE OF REVIEW

The clinical role of fluorine-18 fluoro-2-deoxyglucose (FDG)-positron emission tomography (PET) in renal cell carcinoma (RCC) is still evolving. Use of FDG PET in RCC is currently not a standard investigation in the diagnosis and staging of RCC due to its renal excretion. This review focuses on the clinical role and current status of FDG PET and PET/CT in RCC.

RECENT FINDINGS

Studies investigating the role of FDG PET in localized RCC were largely disappointing. Several studies have demonstrated that the use of hybrid imaging PET/CT is feasible in evaluating the extra-renal disease. A current review of the literature determines PET/CT to be a valuable tool both in treatment decision-making and monitoring and in predicting the survival in recurrent and metastatic RCC. PET/CT might be a viable option in the evaluation of RCC, especially recurrent and metastatic disease. PET/CT has also shown to play a role in predicting survival and monitoring therapy response.

Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data

Accurate prognostic prediction using molecular information is a challenging area of research, which is essential to develop precision medicine. In this paper, we develop translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients. There are considerable statistical and computational challenges due to the large dimension of the problems. Furthermore, data are available for different tumor types; hence data integration for various tumors is desirable. Having censored survival outcomes escalates one more level of complexity in the inferential procedure. We develop Bayesian hierarchical survival models, which accommodate all the challenges mentioned here. We use the hierarchical Bayesian accelerated failure time model for survival regression. Furthermore, we assume sparse horseshoe prior distribution for the regression coefficients to identify the major proteomic drivers. We borrow strength across tumor groups by introducing a correlation structure among the prior distributions. The proposed methods have been used to analyze data from the recently curated "The Cancer Proteome Atlas" (TCPA), which contains reverse-phase protein arrays-based high-quality protein expression data as well as detailed clinical annotation, including survival times. Our simulation and the TCPA data analysis illustrate the efficacy of the proposed integrative model, which links different tumors with the correlated prior structures.

Metabolomics informs common patterns of molecular dysfunction across histologies of renal cell carcinoma

The last 30 years of research in renal cell carcinoma (RCC) has revealed that the vast majority of RCC histologies share a recurrent pattern of mutations to metabolic genes, including VHL, MTOR, ELOC, TSC1/2, FH, SDH, and mitochondrial DNA. This has prompted intense study of the consequences of these mutations on cellular metabolism and physiology in vivo by leveraging high-throughput technologies to measure small-molecule metabolites (i.e., metabolomics). The purpose of this review is to give a broad and integrated view on the discoveries made in RCC with metabolomics, and to give a basic understanding of the experimental design of metabolomic studies. Our discussion is organized around five concepts which synthesize discoveries from genomics and metabolomics into the molecular basis of RCC and transcend the different RCC histologies: (1) metabolic phenotypes unique to certain genotypes, (2) mitochondrial dysfunction, (3) the oxidative stress response, (4) epigenetics, and (5) therapy targeted to metabolism. We conclude by proposing several promising lines of investigation that intersect metabolism with emerging ideas in RCC biology.