Altered metabolic pathways in clear cell renal cell carcinoma: A meta-analysis and validation study focused on the deregulated genes and their associated networks

The dysfunctional immune response in renal cell carcinoma correlates with changes in the metabolic landscape of ccRCC during disease progression

Renal cell carcinoma is an immunogenic tumour with a prominent dysfunctional immune cell infiltrate, unable to control tumour growth. Although tyrosine kinase inhibitors and immunotherapy have improved the outlook for some patients, many individuals are non-responders or relapse despite treatment. The hostile metabolic environment in RCC affects the ability of T-cells to maintain their own metabolic programme constraining T-cell immunity in RCC. We investigated the phenotype, function and metabolic capability of RCC TILs correlating this with clinicopathological features of the tumour and metabolic environment at the different disease stages. Flow cytometric analysis of freshly isolated TILs showed the emergence of exhausted T-cells in advanced disease based on their PD-1high and CD39 expression and reduced production of inflammatory cytokines upon in vitro stimulation. Exhausted T-cells from advanced stage disease also displayed an overall phenotype of metabolic insufficiency, characterized by mitochondrial alterations and defects in glucose uptake. Nanostring nCounter cancer metabolism assay on RNA obtained from 30 ccRCC cases revealed significant over-expression of metabolic genes even at early stage disease (pT1-2), while at pT3-4 and the locally advanced thrombi stages, there was an overall decrease in differentially expressed metabolic genes. Notably, the gene PPARGC1A was the most significantly down-regulated gene from pT1-2 to pT3-4 RCC which correlated with loss of mitochondrial function in tumour-infiltrating T-cells evident at this tumour stage. Down-regulation of PPARGC1A into stage pT3-4 may be the 'tipping-point' in RCC disease progression, modulating immune activity in ccRCC and potentially reducing the efficacy of immunotherapies in RCC and poorer patient outcomes.

Prediction of Distant Metastases in Patients with Kidney Cancer Based on Gene Expression and Methylation Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common and aggressive histological type of cancer in this location. Distant metastases are present in approximately 30% of patients at the time of first examination. Therefore, the ability to predict the occurrence of metastases in patients at early stages of the disease is an urgent task aimed at personalized treatment. Samples of tumor and paired histologically normal kidney tissue from patients with metastatic and non-metastatic ccRCC were studied. Gene expression was analyzed using real-time PCR. The level of gene methylation was evaluated using bisulfite conversion followed by quantitative methylation-specific PCR. Two groups of genes were analyzed in this study. The first group includes genes whose expression is significantly reduced during metastasis: CA9, NDUFA4L2, EGLN3, and BHLHE41 (p < 0.001, ROC analysis). The second group includes microRNA genes: MIR125B-1, MIR137, MIR375, MIR193A, and MIR34B/C, whose increased methylation levels are associated with the development of distant metastases (p = 0.002 to <0.001, ROC analysis). Based on the data obtained, a combined panel of genes was formed to identify patients whose tumors have a high metastatic potential. The panel can estimate the probability of metastasis with an accuracy of up to 92%.

Differential Activation of NRF2 Signaling Pathway in Renal-Cell Carcinoma Caki Cell Lines

Renal-cell carcinoma (RCC) is a heterogeneous disease consisting of several subtypes based on specific genomic profiles and histological and clinical characteristics. The subtype with the highest prevalence is clear-cell RCC (ccRCC), next is papillary RCC (pRCC), and then chromophobe RCC (chRCC). The ccRCC cell lines are further subdivided into prognostic expression-based subtypes ccA or ccB. This heterogeneity necessitates the development, availability, and utilization of cell line models with the correct disease phenotypic characteristics for RCC research. In this study, we focused on characterizing proteomic differences between the Caki-1 and Caki-2 cell lines that are commonly used in ccRCC research. Both cells are primarily defined as human ccRCC cell lines. Caki-1 cell lines are metastatic, harboring wild-type VHL, whereas Caki-2 are considered as the primary ccRCC cell lines expressing wild-type von Hippel–Lindau protein (pVHL). Here, we performed a comprehensive comparative proteomic analysis of Caki-1 and Caki-2 cells using tandem mass-tag reagents together with liquid chromatography mass spectrometry (LC/MS) for the identification and quantitation of proteins in the two cell lines. Differential regulation of a subset of the proteins identified was validated using orthogonal methods including western blot, q-PCR, and immunofluorescence assays. Integrative bioinformatic analysis identifies the activation/inhibition of specific molecular pathways, upstream regulators, and causal networks that are uniquely regulated and associated with the two cell lines and RCC subtypes, and potentially the disease stage. Altogether, we have identified multiple molecular pathways, including NRF2 signaling, which is the most significantly activated pathway in Caki-2 versus Caki-1 cells. Some of the differentially regulated molecules and signaling pathways could serve as potential diagnostic and prognostic biomarkers and therapeutic targets amongst ccRCC subtypes.

Does the Urinary Proteome Reflect ccRCC Stage and Grade Progression?

Due its ability to provide a global snapshot of kidney physiology, urine has emerged as a highly promising, non-invasive source in the search for new molecular indicators of disease diagnosis, prognosis, and surveillance. In particular, proteomics represents an ideal strategy for the identification of urinary protein markers; thus, a urinomic approach could also represent a powerful tool in the investigation of the most common kidney cancer, which is clear cell Renal Cell Carcinoma (ccRCC). Currently, these tumors are classified after surgical removal using the TNM and nuclear grading systems and prognosis is usually predicted based upon staging. However, the aggressiveness and clinical outcomes of ccRCC remain heterogeneous within each stratified group, highlighting the need for novel molecular indicators that can predict the progression of these tumors. In our study, we explored the association between the urinary proteome and the ccRCC staging and grading classification. The urine proteome of 44 ccRCC patients with lesions of varying severity was analyzed via label-free proteomics. MS data revealed several proteins with altered abundance according to clinicopathological stratification. Specifically, we determined a panel of dysregulated proteins strictly related to stage and grade, suggesting the potential utility of MS-based urinomics as a complementary tool in the staging process of ccRCC.

METTL13 inhibits progression of clear cell renal cell carcinoma with repression on PI3K/AKT/mTOR/HIF-1α pathway and c-Myc expression

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the most common and aggressive type of renal malignancy. Methyltransferase like 13 (METTL13) functions as an oncogene in most of human cancers, but its function and mechanism in ccRCC remains unreported.

METHODS

qRT-PCR, western blotting and immunohistochemistry were used to detect METTL13's expression in tissues. The effects of METTL13 on ccRCC cells' growth and metastasis were determined by both functional experiments and animal experiments. Weighted gene co-expression network analysis (WGCNA) was performed to annotate METTL13's functions and co-immunoprecipitation (co-IP) was used to determine the interaction between METTL13 and c-Myc.

RESULTS

METTL13 was underexpressed in ccRCC tissues compared to normal kidney tissues and its low expression predicted poor prognosis for ccRCC patients. The in vitro studies showed that knockdown and overexpression of METTL13 respectively led to increase and decrease in ccRCC cells' proliferation, viability, migratory ability and invasiveness as well as epithelial-mesenchymal transition (EMT). The in vivo experiment demonstrated the inhibitory effect that METTL13 had on ccRCC cells' growth and metastasis. Bioinformatic analyses showed various biological functions and pathways METTL13 was involved in. In ccRCC cells, we observed that METTL13 could negatively regulate PI3K/AKT/mTOR/HIF-1α pathway and that it combined to c-Myc and inhibited c-Myc protein expression.

CONCLUSIONS

In general, our finding suggests that high expression of METTL13 is associated with favorable prognosis of ccRCC patients. Meanwhile, METTL13 can inhibit growth and metastasis of ccRCC cells with participation in multiple potential molecular mechanisms. Therefore, we suggest METTL13 can be a new diagnostic and therapeutic target for ccRCC in the future.

MicroRNA related prognosis biomarkers from high throughput sequencing data of kidney renal clear cell carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is the most common type of kidney cell carcinoma which has the worst overall survival rate. Almost 30% of patients with localized cancers eventually develop to metastases despite of early surgical treatment carried out. MicroRNAs (miRNAs) play a critical role in human cancer initiation, progression, and prognosis. The aim of our study was to identify potential prognosis biomarkers to predict overall survival of KIRC.

Methods

All data were downloaded from an open access database The Cancer Genome Atlas. DESeq2 package in R was used to screening the differential expression miRNAs (DEMs) and genes (DEGs). RegParallel and Survival packages in R was used to analysis their relationships with the KIRC patients. David version 6.8 and STRING version 11 were used to take the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis.

Results

We found 2 DEGs (TIMP3 and HMGCS1) and 3 DEMs (hsa-miR-21-5p, hsa-miR-223-3p, and hsa-miR-365a-3p) could be prognosis biomarkers for the prediction of KIRC patients. The constructed prognostic model based on those 2 DEGs could effectively predict the survival status of KIRC. And the constructed prognostic model based on those 3 DEMs could effectively predict the survival status of KIRC in 3-year and 5-year.

Conclusion

The current study provided novel insights into the miRNA related mRNA network in KIRC and those 2 DEGs biomarkers and 3 DEMs biomarkers may be independent prognostic signatures in predicting the survival of KIRC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-00932-z.

ABAT and ALDH6A1, regulated by transcription factor HNF4A, suppress tumorigenic capability in clear cell renal cell carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a malignancy characterized by metabolic reprogramming. ABAT and ALDH6A1 are metabolic enzymes. In this study, we aim to investigate the associations of ABAT and ALDH6A1 with the malignancy of ccRCC cells.

Methods

The gene expression levels of ABAT and ALDH6A1 in ccRCC were analyzed from gene expression microarray datasets and RNA sequencing data. Clinical information was analyzed from The Cancer Genome Atlas (TCGA) data. The distributions of ABAT and ALDH6A1 in ccRCC clinical tissues were screened by reverse transcription-quantitative polymerase chain reaction (RT-QPCR) and immunohistochemical assays. The effect of overexpression of ABAT or ALDH6A1 was measured by detecting the cell viability, migration ability, and the ratio of lactate and nicotinamide adenine dinucleotide phosphate (NADPH). Chromatin immunoprecipitation (ChIP) and luciferase reporter assays were carried out to investigate the transcript regulation of HNF4A in ABAT and ALDH6A1.

Results

Remarkable downregulated ABAT and ALDH6A1 expression levels were observed in ccRCC patients and low expression of ABAT and ALDH6A1 was correlated with poor survival. Overexpression of ABAT or ALDH6A1 significantly attenuated cell proliferation and migration, and impaired lactate production. In ABAT increased ccRCC cells, the ratio of NADPH/NADP+ was reduced. Finally, we demonstrated that ABAT and ALDH6A1 were directly regulated by a tumor suppressor, HNF4A.

Conclusions

These observations identified HNF4A-regulated low-expressed ABAT and ALDH6A1 as promising diagnostic and prognostic biomarkers for ccRCC.

The Genes-Candidates for Prognostic Markers of Metastasis by Expression Level in Clear Cell Renal Cell Cancer

The molecular prognostic markers of metastasis are important for personalized approaches to clear cell renal cell carcinoma (ccRCC) treatment but markers for practical use are still missing. To address this gap we studied the expression of ten genes—CA9, NDUFA4L2, VWF, IGFBP3, BHLHE41, EGLN3, SAA1, CSF1R, C1QA, and FN1—through RT-PCR, in 56 ccRCC patients without metastases and with metastases. All of these, excluding CSF1R, showed differential and increased (besides SAA1) expression in non-metastasis tumors. The gene expression levels in metastasis tumors were decreased, besides CSF1R, FN1 (not changed), and SAA1 (increased). There were significant associations of the differentially expressed genes with ccRCC metastasis by ROC analysis and the Fisher exact test. The association of the NDUFA4L2, VWF, EGLN3, SAA1, and C1QA expression with ccRCC metastasis is shown for the first time. The CA9, NDUFA4L2, BHLHE4, and EGLN3 were distinguished as the strongest candidates for ccRCC metastasis biomarkers. We used an approach that presupposed that the metastasis marker was the expression levels of any three genes from the selected panel and received sensitivity (88%) and specificity (73%) levels with a relative risk of RR > 3. In conclusion, a panel of selected genes—the candidates in biomarkers of ccRCC metastasis—was created for the first time. The results might shed some light on the ccRCC metastasis processes.

Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models

Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients.

Circulating adiponectin as a biomarker in renal cell carcinoma: a systematic review and meta-analysis

Context: Metabolic imbalance in renal cell carcinoma (RCC) can lead to abnormal adiponectin levels. Objective: To evaluate circulating adiponectin as a detection or predictive marker for RCC. Methods: A comprehensive literature search and meta-analysis was performed on studies reporting circulating adiponectin levels and RCC. The meta-analysis was performed using RevMan. Results: Seven studies compared the circulating adiponection levels between RCC cases and controls. Adiponectin level was significantly lower in RCC cases compared to controls at pre-diagnosis and pre-operative time-points. RCC stage, grade and subtype did not affect adiponectin levels. Conclusion: Low circulating adiponectin could be a predictive or risk factor for RCC.

Recognition of early and late stages of bladder cancer using metabolites and machine learning

INTRODUCTION

Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its rate of occurrence increases with age. The current method of BCa diagnosis includes a cystoscopy and biopsy. This process is expensive, unpleasant, and may have severe side effects. Recent growth in the power and accessibility of machine-learning software has allowed for the development of new, non-invasive diagnostic methods whose accuracy and sensitivity are uncompromising to function.

OBJECTIVES

The goal of this research was to elucidate the biomarkers including metabolites and corresponding genes for different stages of BCa, show their distinguishing and common features, and create a machine-learning model for classification of stages of BCa.

METHODS

Sets of metabolites for early and late stages, as well as common for both stages were analyzed using MetaboAnalyst and Ingenuity^® Pathway Analysis (IPA^®) software. Machine-learning methods were utilized in the development of a binary classifier for early- and late-stage metabolites of BCa. Metabolites were quantitatively characterized using EDragon 1.0 software. The two modeling methods used are Multilayer Perceptron (MLP) and Stochastic Gradient Descent (SGD) with a logistic regression loss function.

RESULTS

We explored metabolic pathways related to early-stage BCa (Galactose metabolism and Starch and sucrose metabolism) and to late-stage BCa (Glycine, serine, and threonine metabolism, Arginine and proline metabolism, Glycerophospholipid metabolism, and Galactose metabolism) as well as those common to both stages pathways. The central metabolite impacting the most cancerogenic genes (AKT, EGFR, MAPK3) in early stage is D-glucose, while late-stage BCa is characterized by significant fold changes in several metabolites: glycerol, choline, 13(S)-hydroxyoctadecadienoic acid, 2'-fucosyllactose. Insulin was also seen to play an important role in late stages of BCa. The best performing model was able to predict metabolite class with an accuracy of 82.54% and the area under precision-recall curve (PRC) of 0.84 on the training set. The same model was applied to three separate sets of metabolites obtained from public sources, one set of the late-stage metabolites and two sets of the early-stage metabolites. The model was better at predicting early-stage metabolites with accuracies of 72% (18/25) and 95% (19/20) on the early sets, and an accuracy of 65.45% (36/55) on the late-stage metabolite set.

CONCLUSION

By examining the biomarkers present in the urine samples of BCa patients as compared with normal patients, the biomarkers associated with this cancer can be pinpointed and lead to the elucidation of affected metabolic pathways that are specific to different stages of cancer. Development of machine-learning model including metabolites and their chemical descriptors made it possible to achieve considerable accuracy of prediction of stages of BCa.

Identification of a lncRNA‑associated competing endogenous RNA‑regulated network in clear cell renal cell carcinoma

Long noncoding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs) in the regulation of gene expression in various physiological and pathological processes. The present study aimed to explore the lncRNA-miRNA-mRNA interactions in clear cell renal cell carcinoma (ccRCC) using comprehensive bioinformatics analysis. RNA-seq data were downloaded from the TCGA Data Portal, and the differentially expressed lncRNAs (DElncRs), miRNAs (DEmiRs), and mRNAs (DEGs) between tumoral and control samples were identified using the edgeR package. The correlations between the DemiR/DElncR expression levels and clinical features were evaluated using nonparametric regression analysis. The Kaplan-Meier method was used to identify DElncRs associated with overall survival time. Then, the DElncR-DEmiR interaction pairs were predicted using miRcode and the starBase v2.0 database, and DEmiR-DEG pairs were predicted using the miRTarBase database. Then, a ceRNA-regulated network of ccRCC was constructed based on these interactions. Genes in the network were also assigned to functional categories in the KEGG pathway database. A total of 1,573 DEGs, 37 DelncRs, and 62 DEmiRs were identified. Moreover, several DElncRs were significantly associated with patient clinical variables; for example, TCL6 was significantly associated with tumor grade and AJCC pathological stage. Next, 38 pairs of DElncR-DEmiR interactions (13 DElncRs and 8 DEmiRs) were identified. Among the 8 DEmiRs that target DElncRs, six were found to target DEGs. Based on the identified DElncR-DEmiR interactions and DEmiR-DEG interactions, a ceRNA-regulated network comprising 203 nodes and 221 edges was constructed (with MIC >0.15 and MIC-p² >0.15). The novel lncRNAs, DGCR5, MYCNOS, and PART1 may participate in the progression of ccRCC through cytochrome P450-mediated drug metabolism.

The downregulated long noncoding RNA DHRS4-AS1 is protumoral and associated with the prognosis of clear cell renal cell carcinoma

BACKGROUND

Long noncoding RNAs (lncRNAs) have been identified as important factors in cancer biology and are deregulated in many cancers. The present study aimed to determine the expression and roles of lncRNA DHRS4-AS1 in the progression of clear cell renal cell carcinoma (ccRCC).

METHODS AND RESULTS

Using high-throughput RNA-sequencing data of ccRCC tumors from the Cancer Genome Atlas project, we identified lncRNA DHRS4-AS1 as significantly associated with ccRCC patients' overall survival. We confirmed the downregulation of DHRS4-AS1 in ccRCC by assessing its expression levels in a cohort of 52 tumor and paired non-tumor samples. In addition, we found that low DHRS4-AS1 expression was significantly associated with a high tumor node metastasis stage, lymph node metastasis, advanced pathological grade and poor prognosis. Furthermore, DHRS4-AS1 overexpression inhibited the progression of cell cycles of ccRCC in vitro. These data indicate that DHRS4-AS1 functions by preventing the proliferation and invasion, inhibiting the cell cycle progression and promoting the apoptosis of ccRCC cells.

CONCLUSION

Taken together, our findings identify the role of DHRS4-AS1 as a tumor inhibitor in ccRCC for the first time, demonstrating that DHRS4-AS1 is a potential prognostic biomarker that could potentially be applied in ccRCC therapy.

miR-199b-5p serves as a tumor suppressor in renal cell carcinoma

MicroRNA (miR)-199b-5p has been reported to have a critical role in various types of malignancy. However, the exact function miR-199b-5p in renal cancer remains to be fully elucidated. The present study aimed to detect the expression levels of miR-199b-5p in renal cell carcinoma (RCC) tissues and RCC cell lines, and investigated the effect of miR-199b-5p in vitro with Cell Counting Kit-8, MTT, scratch wound, Transwell and flow cytometric assays. The results demonstrated that the expression levels of miR-199b-5p were significantly downregulated in RCC tissues and cell lines compared with those in paired adjacent normal renal tissues and a reference cell line, respectively. Downregulation of miR-199b-5p by transfection with a synthetic inhibitor promoted cellular proliferation and migration, while reducing the apoptotic rate, indicating that miR-199b-5p may serve as a tumor suppressor in RCC. Further study is required to identify target genes of miR-199b-5p to elucidate the mechanisms underlying the role of miR-199b-5p in the occurrence and development of RCC.

Restoration of 5-hydroxymethylcytosine by ascorbate blocks kidney tumour growth

Loss of 5-hydroxymethylcytosine (5hmC) occurs frequently in a wide variety of tumours, including clear-cell renal cell carcinoma (ccRCC). It remains unknown, however, whether the restoration of 5hmC patterns in tumours could have therapeutic efficacy. Here, we used sodium L-ascorbate (vitamin C, AsANa) and the oxidation-resistant form L-ascorbic acid 2-phosphate sesquimagnesium (APM) for the restoration of 5hmC patterns in ccRCC cells. At physiological concentrations, both show anti-tumour efficacy during long-term treatment in vitro and in vivo Strikingly, global 5hmC patterns in ccRCC cells after treatment resemble those of normal kidney tissue, which is observed also in treated xenograft tumours, and in primary cells from a ccRCC patient. Further, RNA-seq data show that long-term treatment with vitamin C changes the transcriptome of ccRCC cells. Finally, APM treatment induces less non-specific cell damage and shows increased stability in mouse plasma compared to AsANa. Taken together, our study provides proof of concept for an epigenetic differentiation therapy of ccRCC with vitamin C, especially APM, at low doses by 5hmC reprogramming.

microRNA‑181a‑5p functions as an oncogene in renal cell carcinoma

Renal cell carcinoma (RCC) is one of the most common urinary tumors. Previous studies have demonstrated that microRNA (miR)‑181a‑5p has an important role in numerous types of cancer. However, the function of miR‑181a‑5p in RCC remains unknown. In the present study, the expression levels of miR‑181a‑5p in RCC tissues and cell lines were investigated using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) analysis. The results of the RT‑qPCR analyses suggested that the expression of miR‑181a‑5p was upregulated in RCC tissues and cells lines compared with adjacent normal renal tissues and normal renal cell lines. Furthermore, the effect of miR‑181a‑5p on cell proliferation, migration, invasion and apoptosis was investigated in the present study. Overexpression of miR‑181a‑5p was revealed to suppress the apoptosis of 786‑O and ACHN cells, in addition to enhancing the proliferation, migration and invasion abilities of 786‑O and ACHN cells in vitro, thus suggesting that miR‑181a‑5p may function as an oncogene in RCC. However, further studies are required to investigate the underlying mechanism of miR‑181a‑5p and its potential role as a biomarker for early detection and prognosis, in addition to as a therapeutic target in RCC.

Proteomics of liquid biopsies: Depicting RCC infiltration into the renal vein by MS analysis of urine and plasma

Liquid biopsies, as blood and urine, could offer an invaluable, easily accessible source of biomarkers, and evidences for elucidating the pathological processes. Only few studies integrated the proteomes driven by more than one biofluid. Furthermore, it is not clear which biofluid better mirrors the alterations triggered by disease. Venous infiltrating RCC(Renal Cell Carcinoma) could represent an advantageous model for exploring this aspect. Herein, we investigate how blood and urine "proteomically" reflect the changes occurring during RCC infiltration into renal vein(RV) by label-free nLC-ESI-MS/MS. We found 574 and 58 differentially expressed proteins(DEPs) in response to vascular involvement. To the augment of vascular involvement, the abundance of only three proteins in urine(UROM,RALA,CNDP1) and two in plasma(APOA1,K2C1) diminished while increased for twenty-six urinary proteins. 80 proteins were found both in urine and plasma, among which twenty-eight were DEPs. A huge overlap between the two biofluids was highlighted, as expected, being urine the filtrate of blood. However, this consistency decreases when RV-occlusion occurs suggesting alternative protein releases, and a loss of kidney architecture. Moreover, several proteomic and functional signatures were biofluid-specific. In conclusion, the complementarity between the specimens allowed to achieve a deeper level of molecular complexity of the RCC venous infiltration. SIGNIFICANCE: Although plasma and urine are strongly interconnected, only few proteomic studies investigated the complementarity of these fluids as bio-sources of information. Moreover, none of them was focused to their analysis and comparison in the context of vascular infiltration of renal cancer. Herein, new insights were gained regarding the impact into urinary and plasma proteome of the changes triggered by the ccRCC invasion into vascular system and renal vein. Furthermore, the integration of the information driven by the two liquid biopsies permits to unravel biological processes otherwise lost.

The platelet isoform of phosphofructokinase contributes to metabolic reprogramming and maintains cell proliferation in clear cell renal cell carcinoma

Metabolic alterations underlying clear cell renal cell carcinoma (ccRCC) progression include aerobic glycolysis, increased pentose phosphate pathway activity and reduced oxidative phosphorylation. Phosphofructokinase (PFK), a key enzyme of the glycolytic pathway, has L, M, and P isoforms with different tissue distributions. The mRNA level of the platelet isoform of phosphofructokinase (PFKP) is reported to be up-regulated in ccRCC patients. However, it remains unclear whether PFKP plays an important role in promoting aerobic glycolysis and macromolecular biosynthesis to support cell proliferation in ccRCC. Here we found that the up-regulated PFKP became the predominant isoform of PFK in human ccRCC. Suppression of PFKP not only impaired cell proliferation by inducing cell cycle arrest and apoptosis, but also led to decreased glycolysis, pentose phosphate pathway and nucleotide biosynthesis, accompanied by activated tricarboxylic acid cycle in ccRCC cells. Moreover, we found that p53 activation contributed to cell proliferation and metabolic defects induced by PFKP knockdown in ccRCC cells. Furthermore, suppression of PFKP led to reduced ccRCC tumor growth in vivo. Our data indicate that PFKP not only is required for metabolic reprogramming and maintaining cell proliferation, but also may provide us with a valid target for anti-renal cancer pharmaceutical agents.

Nicotinamide N-Methyltransferase in Health and Cancer

Over the past decade, the roles of nicotinamide N-methyltransferase and its product 1-methyl nicotinamide have emerged from playing merely minor roles in phase 2 xenobiotic metabolism as actors in some of the most important scenes of human life. In this review, the structures of the gene, messenger RNA, and protein are discussed, together with the role of the enzyme in many of the common cancers that afflict people today.

High expression of Aldolase A predicts poor survival in patients with clear-cell renal cell carcinoma

Background

Aldolase A (ALDOA) is a glycolytic enzyme that drives the glycolytic metabolic pathway in mammalian cells. The overexpression of ALDOA was observed in a variety of cancers including clear-cell renal cell carcinoma (ccRCC). However, little was known about the clinicopathological significance and prognostic value of ALDOA in ccRCC patients.

Methods

The expression of ALDOA was detected using immunohistochemical staining in 162 formalin-fixed, paraffin-embedded ccRCC sections. Prognostic outcomes correlated with ALDOA were examined using Kaplan–Meier analysis and the Cox proportional hazards model.

Results

In patients with ccRCC, increased cytoplasmic ALDOA expression was positively associated with tumor size (P=0.021), TNM stages (P=0.034), lymph node metastasis (P=0.020), and overall survival (OS) (P<0.001). Kaplan–Meier analysis showed that high cytoplasmic expression of ALDOA was associated with a statistically significant lower OS (P<0.001). Multivariate analysis demonstrated that ALDOA expression was an independent and significant prognostic factor (HR =3.561, 95% CI =1.715–7.396, P=0.001). ALDOA expression was not associated with significant prognostic deference in the subgroups of TNM stage I patients or pT1 patients.

Conclusion

Our results suggest that ALDOA expression is an independent prognostic factor for OS in patients with ccRCC.

A comprehensive analysis of cancer-driving mutations and genes in kidney cancer

An accumulation of driver mutations is important for cancer formation and progression, and leads to the disruption of genes and signaling pathways. The identification of driver mutations and genes has been the subject of numerous previous studies. The present study was performed to identify cancer-driving mutations and genes in renal cell carcinoma (RCC), prioritizing noncoding variants with a high functional impact, in order to analyze the most informative features. Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping version 2 (Polyphen2) and MutationAssessor were applied to predict deleterious mutations in the coding genome. OncodriveFM and OncodriveCLUST were used to detect potential driver genes and signaling pathways. The functional impact of noncoding variants was evaluated using Combined Annotation Dependent Depletion, FunSeq2 and Genome-Wide Annotation of Variants. Noncoding features were analyzed with respect to their enrichment of high-scoring variants. A total of 1,327 coding mutations in clear cell RCC, 258 in chromophobe RCC and 1,186 in papillary RCC were predicted to be deleterious by all three of MutationAssessor, Polyphen2 and SIFT. In total, 77 genes were positively selected by OncodriveFM and 1 by OncodriveCLUST, 45 of which were recurrently mutated genes. In addition, 10 signaling pathways were recurrently mutated and had a high functional impact bias (FM bias), and 31 novel signaling pathways with high FM bias were identified. Furthermore, noncoding regulatory features and conserved regions contained numerous high-scoring variants, and expression, replication time, GC content and recombination rate were positively correlated with the densities of high-scoring variants. In conclusion, the present study identified a list of cancer-driving genes and signaling pathways, features like regulatory elements, conserved regions, replication time, expression, GC content and recombination rate are major factors that affect the distribution of high-scoring non-coding mutations in kidney cancer.

Choosing the right cell line for renal cell cancer research

Cell lines are still a tool of choice for many fields of biomedical research, including oncology. Although cancer is a very complex disease, many discoveries have been made using monocultures of established cell lines. Therefore, the proper use of in vitro models is crucial to enhance our understanding of cancer. Therapeutics against renal cell cancer (RCC) are also screened with the use of cell lines. Multiple RCC in vitro cultures are available, allowing in vivo heterogeneity in the laboratory, but at the same time, these can be a source of errors. In this review, we tried to sum up the data on the RCC cell lines used currently. An increasing amount of data on RCC shed new light on the molecular background of the disease; however, it revealed how much still needs to be done. As new types of RCC are being distinguished, novel cell lines and the re-exploration of old ones seems to be indispensable to create effective in vitro tools for drug screening and more.

Low level of PDZ domain containing 1 (PDZK1) predicts poor clinical outcome in patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most lethal neoplasm of the urologic system. Clinical therapeutic effect varies greatly between individual ccRCC patients, so there is an urgent need to develop prognostic molecular biomarkers to help clinicians identify patients in need of early aggressive management. In this study, samples from primary ccRCC tumor and their corresponding nontumor adjacent tissues (n=18) were analyzed by quantitative proteomic assay. Proteins downregulated in tumors were studied by GO and KEGG pathways enrichment analyses. Six proteins were found both downregulated and annotated with cell proliferation in ccRCC patients. Of these proteins, PDZK1 and FABP1 were also involved in the lipid metabolism pathway. The downregulation of PDZK1 was further validated in TCGA_KIRC dataset (n=532) and independent set (n=202). PDZK1 could discriminate recurrence, metastasis and prognosis between ccRCC patients. Low level of PDZK1 in both mRNA and protein was associated with reduced overall survival (OS) and disease-free survival (DFS) in two independent sets. In univariate and multivariate analyses, PDZK1 was defined as an independent prognostic factor for both OS and DFS. These findings indicated that low level of PDZK1 could predict poor clinical outcome in patients with ccRCC.

Sequential pathogenesis of metastatic VHL mutant clear cell renal cell carcinoma: putting it together with a translational perspective

Clear cell renal cell carcinoma (ccRCC) accounts for ∼80% of all RCC, and biallelic Von Hippel-Lindau (VHL) gene defects occur in ∼75% of sporadic ccRCC. The etiopathogenesis of VHL mutant metastatic RCC, based on our understanding to date of molecular mechanisms involved, is a sequence of events which can be grouped under the following: (i) loss of VHL activity (germline/somatic mutation + inactivation of the wild-type copy); (ii) constitutive activation of the hypoxia-inducible factor (HIF) pathway due to loss of VHL activity and transcription of genes involved in angiogenesis, epithelial-mesenchymal transition, invasion, metastasis, survival, anaerobic glycolysis and pentose phosphate pathway; (iii) interactions of the HIF pathway with other oncogenic pathways; (iv) genome-wide epigenetic changes (potentially driven by an overactive HIF pathway) and the influence of epigenetics on various oncogenic, apoptotic, cell cycle regulatory and mismatch repair pathways (inhibition of multiple tumor suppressor genes); (v) immune evasion, at least partially caused by changes in the epigenome. These mechanisms interact throughout the pathogenesis and progression of disease, and also confer chemoresistance and radioresistance, making it one of the most difficult metastatic cancers to treat. This article puts together the sequential pathogenesis of VHL mutant ccRCC by elaborating these mechanisms and the interplay of oncogenic pathways, epigenetics, metabolism and immune evasion, with a perspective on potential therapeutic strategies. We reflect on the huge gap between our understanding of the molecular biology and currently accepted standard of care in metastatic ccRCC, and present ideas for better translational research involving therapeutic strategies with combinatorial drug approach, targeting different aspects of the pathogenesis.

Proteotranscriptomic Analysis Reveals Stage Specific Changes in the Molecular Landscape of Clear-Cell Renal Cell Carcinoma

Renal cell carcinoma comprises 2 to 3% of malignancies in adults with the most prevalent subtype being clear-cell RCC (ccRCC). This type of cancer is well characterized at the genomic and transcriptomic level and is associated with a loss of VHL that results in stabilization of HIF1. The current study focused on evaluating ccRCC stage dependent changes at the proteome level to provide insight into the molecular pathogenesis of ccRCC progression. To accomplish this, label-free proteomics was used to characterize matched tumor and normal-adjacent tissues from 84 patients with stage I to IV ccRCC. Using pooled samples 1551 proteins were identified, of which 290 were differentially abundant, while 783 proteins were identified using individual samples, with 344 being differentially abundant. These 344 differentially abundant proteins were enriched in metabolic pathways and further examination revealed metabolic dysfunction consistent with the Warburg effect. Additionally, the protein data indicated activation of ESRRA and ESRRG, and HIF1A, as well as inhibition of FOXA1, MAPK1 and WISP2. A subset analysis of complementary gene expression array data on 47 pairs of these same tissues indicated similar upstream changes, such as increased HIF1A activation with stage, though ESRRA and ESRRG activation and FOXA1 inhibition were not predicted from the transcriptomic data. The activation of ESRRA and ESRRG implied that HIF2A may also be activated during later stages of ccRCC, which was confirmed in the transcriptional analysis. This combined analysis highlights the importance of HIF1A and HIF2A in developing the ccRCC molecular phenotype as well as the potential involvement of ESRRA and ESRRG in driving these changes. In addition, cofilin-1, profilin-1, nicotinamide N-methyltransferase, and fructose-bisphosphate aldolase A were identified as candidate markers of late stage ccRCC. Utilization of data collected from heterogeneous biological domains strengthened the findings from each domain, demonstrating the complementary nature of such an analysis. Together these results highlight the importance of the VHL/HIF1A/HIF2A axis and provide a foundation and therapeutic targets for future studies. (Data are available via ProteomeXchange with identifier PXD003271 and MassIVE with identifier MSV000079511.)

Non-invasive differentiation of benign renal tumors from clear cell renal cell carcinomas using clinically translatable hyperpolarized 13C pyruvate magnetic resonance

Localized renal tumors are increasingly detected incidentally at imaging. Conventional imaging cannot reliably differentiate the 20% of these tumors that are benign from malignant renal cell carcinomas (RCCs), leading to unnecessary surgical resection and resulting morbidity associated with surgery. Here, we investigated hyperpolarized 13C pyruvate metabolism in live patient-derived renal tumor tissue slices using a novel magnetic resonance (MR) -compatible bioreactor platform. We demonstrated for the first time that clear cell RCCs (ccRCCs), which account for 70-80% of all RCCs, have increased lactate production as well as rapid lactate efflux compared to benign renal tumors. This difference is attributed to increased lactate dehydrogenase A and monocarboxylate transporter 4 expression in ccRCCs. This distinctive metabolic phenotype can be used to differentiate RCCs from benign renal tumors using clinically translatable hyperpolarized 13C pyruvate MR.

Transcriptome Sequencing (RNAseq) Enables Utilization of Formalin-Fixed, Paraffin-Embedded Biopsies with Clear Cell Renal Cell Carcinoma for Exploration of Disease Biology and Biomarker Development

Formalin-fixed, paraffin-embedded (FFPE) tissues are an underused resource for molecular analyses. This proof of concept study aimed to compare RNAseq results from FFPE biopsies with the corresponding RNAlater^® (Qiagen, Germany) stored samples from clear cell renal cell carcinoma (ccRCC) patients to investigate feasibility of RNAseq in archival tissue. From each of 16 patients undergoing partial or full nephrectomy, four core biopsies, such as two specimens with ccRCC and two specimens of adjacent normal tissue, were obtained with a 16g needle. One normal and one ccRCC tissue specimen per patient was stored either in FFPE or RNAlater^®. RNA sequencing libraries were generated applying the new Illumina TruSeq^® Access library preparation protocol. Comparative analysis was done using voom/Limma R-package. The analysis of the FFPE and RNAlater^® datasets yielded similar numbers of detected genes, differentially expressed transcripts and affected pathways. The FFPE and RNAlater datasets shared 80% (n = 1106) differentially expressed genes. The average expression and the log2 fold changes of these transcripts correlated with R² = 0.97, and R² = 0.96, respectively. Among transcripts with the highest fold changes in both datasets were carbonic anhydrase 9 (CA9), neuronal pentraxin-2 (NPTX2) and uromodulin (UMOD) that were confirmed by immunohistochemistry. IPA revealed the presence of gene signatures of cancer and nephrotoxicity, renal damage and immune response. To simulate the feasibility of clinical biomarker studies with FFPE samples, a classifier model was developed for the FFPE dataset: expression data for CA9 alone had an accuracy, specificity and sensitivity of 94%, respectively, and achieved similar performance in the RNAlater dataset. Transforming growth factor-ß1 (TGFB1)-regulated genes, epithelial to mesenchymal transition (EMT) and NOTCH signaling cascade may support novel therapeutic strategies. In conclusion, in this proof of concept study, RNAseq data obtained from FFPE kidney biopsies are comparable to data obtained from fresh stored material, thereby expanding the utility of archival tissue specimens.

Role of NADH Dehydrogenase (Ubiquinone) 1 Alpha Subcomplex 4-Like 2 in Clear Cell Renal Cell Carcinoma

PURPOSE

We delineated the functions of the hypoxia-inducible factor-1α (HIF1α) target NADH dehydrogenase (ubiquinone) 1 alpha subcomplex 4-like 2 (NDUFA4L2) in clear cell renal cell carcinoma (ccRCC) and characterized NDUFA4L2 as a novel molecular target for ccRCC treatment.

EXPERIMENTAL DESIGN

We evaluated normal kidney and ccRCC patient microarray and RNAseq data from Oncomine and The Cancer Genome Atlas for NDUFA4L2 mRNA levels and the clinical implications of high NDUFA4L2 expression. In addition, we examined normal kidney and ccRCC patient tissue samples, human ccRCC cell lines, and murine models of ccRCC for NDUFA4L2 mRNA and protein expression. Utilizing short hairpin RNA, we performed NDUFA4L2 knockdown experiments and analyzed the proliferation, clonogenicity, metabolite levels, cell structure, and autophagy in ccRCC cell lines in culture.

RESULTS

We found that NDUFA4L2 mRNA and protein are highly expressed in ccRCC samples but undetectable in normal kidney tissue samples, and that NDUFA4L2 mRNA expression correlates with tumor stage and lower overall survival. In addition, we demonstrated that NDUFA4L2 is an HIF1α target in ccRCC and that NDUFA4L2 knockdown has a profound antiproliferative effect, alters metabolic pathways, and causes major stress in cultured RCC cells.

CONCLUSIONS

Collectively, our data show that NDUFA4L2 is a novel molecular target for ccRCC treatment. Clin Cancer Res; 22(11); 2791-801. ©2016 AACR.

A Metabonomic Study of the Effect of Methanol Extract of Ginger on Raji Cells Using (1)HNMR Spectroscopy

Cancer is currently a major international health problem. The development of resistance to chemotherapy has resulted in the search for herbal drugs. Ginger is a medicinal plant with several clinical applications. Metabolomics is a simultaneous detection of all the metabolites by use of (1)HNMR or mass spectroscopy and interpretation by modeling software. The purpose of this study was to detect the altered metabolites of Raji cells in the presence of ginger extract in vitro. Cells were cultured in the presence and absence of methanolic ginger extract in RPMI medium. IC50 determined by MTT and lipophilic and hydrophilic extracts were prepared from control and treated groups which were analyzed by (1)HNMR. The IC50 was 1000 μg/mL. Modeling of spectra was carried out on the two groups using OSC-PLS with MATLAB software and the main metabolites detected. Further analysis was carried out using MetaboAnalyst database. The main metabolic pathways affected by the ginger extract were detected. Ginger extract was seen to effect the protein biosynthesis, amino acid, and carbohydrate metabolism and had a strong cytotoxic effect on Raji cells in vitro.

NY-ESO-1 as a potential immunotherapeutic target in renal cell carcinoma

Background: Novel immune therapies targeting tumor specific antigens are being developed. Our purpose was to determine expression of the cancer testes antigen NY-ESO-1 in renal cell carcinoma (RCC), as NY-ESO-1 targeting approaches, particularly adoptive cell therapy, have not been evaluated in this disease.

Methods: We employed tissue microarrays containing >300 unique RCC cases and adjacent benign renal tissue to determine NY-ESO-1 expression using a quantitative immunofluorescence method. In addition, we studied NY-ESO-1 expression in 35 matched primary and metastatic RCC specimens to assess concordance between different tumor sites.

Results: NY-ESO-1 was highly expressed in a subset of RCCs. Expression in primary RCC specimens was significantly higher than adjacent normal renal tissue (P<0.0001) and higher in clear cell carcinomas than papillary RCC (P<0.0001). Expression levels in metastatic specimens were higher than in matched primary samples (P=0.0018), and the correlation between the two sites was modest (χ²=3.5, p=0.06).

Conclusions: Aberrant NY-ESO-1 expression seen in clear cell RCC suggests that NY-ESO-1 targeting approaches should be studied in this disease. Expression is higher in metastatic sites, and discordance between primary and metastatic sites in some patients suggests that patient selection for these therapies should be based on expression in metastatic rather than nephrectomy specimens.

New miRNA profiles accurately distinguish renal cell carcinomas and upper tract urothelial carcinomas from the normal kidney

Background

Upper tract urothelial carcinomas (UT-UC) can invade the pelvicalyceal system making differential diagnosis of the various histologically distinct renal cell carcinoma (RCC) subtypes and UT-UC, difficult. Correct diagnosis is critical for determining appropriate surgery and post-surgical treatments. We aimed to identify microRNA (miRNA) signatures that can accurately distinguish the most prevalent RCC subtypes and UT-UC form the normal kidney.

Methods and Findings

miRNA profiling was performed on FFPE tissue sections from RCC and UT-UC and normal kidney and 434 miRNAs were significantly deregulated in cancerous vs. the normal tissue. Hierarchical clustering distinguished UT-UCs from RCCs and classified the various RCC subtypes among them. qRT-PCR validated the deregulated expression profile for the majority of the miRNAs and ROC analysis revealed their capability to discriminate between tumour and normal kidney. An independent cohort of freshly frozen RCC and UT-UC samples was used to validate the deregulated miRNAs with the best discriminatory ability (AUC>0.8, p<0.001). Many of them were located within cytogenetic regions that were previously reported to be significantly aberrated. miRNA targets were predicted using the miRWalk algorithm and ingenuity pathway analysis identified the canonical pathways and curated networks of the deregulated miRNAs. Using the miRWalk algorithm, we further identified the top anti-correlated mRNA/miRNA pairs, between the deregulated miRNAs from our study and the top co-deregulated mRNAs among 5 independent ccRCC GEO datasets. The AB8/13 undifferentiated podocyte cells were used for functional assays using luciferase reporter constructs and the developmental transcription factor TFCP2L1 was proved to be a true target of miR-489, which was the second most upregulated miRNA in ccRCC.

Conclusions

We identified novel miRNAs specific for each RCC subtype and UT-UC, we investigated their putative targets, the networks and pathways in which they participate and we functionally verified the true targets of the top deregulated miRNAs.