Metabolic Pathways in Kidney Cancer: Current Therapies and Future Directions

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

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

Comprehensive proteogenomic characterization of rare kidney tumors

Non-clear cell renal cell carcinomas (non-ccRCCs) encompass diverse malignant and benign tumors. Refinement of differential diagnosis biomarkers, markers for early prognosis of aggressive disease, and therapeutic targets to complement immunotherapy are current clinical needs. Multi-omics analyses of 48 non-ccRCCs compared with 103 ccRCCs reveal proteogenomic, phosphorylation, glycosylation, and metabolic aberrations in RCC subtypes. RCCs with high genome instability display overexpression of IGF2BP3 and PYCR1. Integration of single-cell and bulk transcriptome data predicts diverse cell-of-origin and clarifies RCC subtype-specific proteogenomic signatures. Expression of biomarkers MAPRE3, ADGRF5, and GPNMB differentiates renal oncocytoma from chromophobe RCC, and PIGR and SOSTDC1 distinguish papillary RCC from MTSCC. This study expands our knowledge of proteogenomic signatures, biomarkers, and potential therapeutic targets in non-ccRCC.

Multi-omics and immunogenomics analysis revealed PFKFB3 as a targetable hallmark and mediates sunitinib resistance in papillary renal cell carcinoma: in silico study with laboratory verification

Glycolysis-related metabolic reprogramming is a central hallmark of human cancers, especially in renal cell carcinoma. However, the regulatory function of glycolytic signature in papillary RCC has not been well elucidated. In the present study, the glycolysis-immune predictive signature was constructed and validated using WGCNA, glycolysis-immune clustering analysis. PPI network of DEGs was constructed and visualized. Functional enrichments and patients' overall survival were analyzed. QRT-PCR experiments were performed to detect hub genes' expression and distribution, siRNA technology was used to silence targeted genes; cell proliferation and migration assays were applied to evaluate the biological function. Glucose concentration, lactate secretion, and ATP production were measured. Glycolysis-Immune Related Prognostic Index (GIRPI) was constructed and combined analyzed with single-cell RNA-seq. High-GIRPI signature predicted significantly poorer outcomes and relevant clinical features of pRCC patients. Moreover, GIRPI also participated in several pathways, which affected tumor immune microenvironment and provided potential therapeutic strategy. As a key glycolysis regulator, PFKFB3 could promote renal cancer cell proliferation and migration in vitro. Blocking of PFKFB3 by selective inhibitor PFK-015 or glycolytic inhibitor 2-DG significantly restrained renal cancer cells' neoplastic potential. PFK-015 and sunitinib could synergistically inhibit pRCC cells proliferation. Glycolysis-Immune Risk Signature is closely associated with pRCC prognosis, progression, immune infiltration, and therapeutic response. PFKFB3 may serve as a pivotal glycolysis regulator and mediates Sunitinib resistance in pRCC patients.

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

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

Bioinformatics analysis identifies GLUD1 as a prognostic indicator for clear cell renal cell carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is a common primary tumor of the kidney and is divided into three major subtypes, of which clear cell renal cell carcinoma (ccRCC) has the highest incidence. Glutamate dehydrogenase 1 (GLUD1) encodes glutamate dehydrogenase 1, which catalyzes the oxidative deamination of glutamate.

METHODS

We analyzed TCGA data using R language software and used multiple online databases to explore the relationship of GLUD1 with signaling pathways and drug sensitivity as well as GLUD1 protein expression and methylation.

RESULTS

The results showed that GLUD1 mRNA expression was reduced in tumor tissues and correlated with the progression of ccRCC. Univariate and multivariate Cox analysis showed that GLUD1 could be used as a prognostic marker for ccRCC. GLUD1 expression in ccRCC was associated with immune cells infiltration and multiple classical signaling pathways. In addition, GLUD1 mRNA expression was related to drug sensitivity.

CONCLUSIONS

These findings provide new ideas for finding new prognostic molecular markers and therapeutic targets for ccRCC.

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

hsa_circ_0003596, as a novel oncogene, regulates the malignant behavior of renal cell carcinoma by modulating glycolysis

BACKGROUND

This research was planned to analyze hsa_circ_0003596 (circCOL5A1) and glycolysis-focused mechanisms in renal cell carcinoma (RCC).

METHODS

circCOL5A1, miR-370-5p, and PRKCSH levels were determined in RCC tissues and selected cell lines by RT-qPCR and/or Western blot. RCC cells after corresponding transfection were tested by colony formation assay, EdU assay, Transwell assay, and flow cytometry to analyze cell proliferation, invasion, migration, and apoptosis. Meanwhile, glycolysis in cells was evaluated by measuring glucose consumption, lactic acid, and ATP production, as well as immunoblotting for HK2 and PKM2. In addition, circCOL5A1 knockdown was performed in animal experiments to observe tumor growth and glycolysis. Finally, the ceRNA network between circCOL5A1, miR-370-5p, and PRKCSH was studied by luciferase reporter assay and RIP experiment.

RESULTS

circCOL5A1 and PRKCSH were highly expressed and miR-370-5p was poorly expressed in RCC. circCOL5A1 knockdown depressed RCC proliferation, invasion, migration, and glycolysis, and enhanced apoptosis. circCOL5A1 competitively adsorbed miR-370-5p. Artificial upregulation of miR-370-5p saved the pro-tumor effect of circCOL5A1 on RCC cells, as evidenced by suppression of tumor malignancy and glycolysis. miR-370-5p targeted PRKCSH. PRKCSH overexpression contributed to a reversal of the anti-tumor effect of circCOL5A1 silencing. Silencing circCOL5A1 inhibited RCC tumor growth and glycolysis.

CONCLUSIONS

circCOL5A1 regulates the malignant behavior of RCC by modulating glycolysis.

Glycolysis-related biomarker TCIRG1 participates in regulation of renal cell carcinoma progression and tumor immune microenvironment by affecting aerobic glycolysis and AKT/mTOR signaling pathway

BACKGROUND

Renal cell carcinoma (RCC) is a hypermetabolic disease. Abnormal up-regulation of glycolytic signaling promotes tumor growth, and glycolytic metabolism is closely related to immunotherapy of renal cancer. The aim of the present study was to determine whether and how the glycolysis-related biomarker TCIRG1 affects aerobic glycolysis, the tumor microenvironment (TME) and malignant progression of clear cell renal cell carcinoma (ccRCC).

METHODS

Based on The Cancer Genome Atlas (TCGA, n = 533) and the glycolysis-related gene set from MSigDB, we identified the glycolysis-related gene TCIRG1 by bioinformatics analysis, analyzed its immunological properties in ccRCC and observed how it affected the biological function and glycolytic metabolism using online databases such as TIMER 2.0, UALCAN, LinkedOmics and in vitro experiments.

RESULTS

It was found that the expression of TCIRG1, was significantly increased in ccRCC tissue, and that high TCIRG1 expression was associated with poor overall survival (OS) and short progression-free interval (PFI). In addition, TCIRG1 expression was highly correlated with the infiltration immune cells, especially CD4+T cell Th1, CD8+T cell, NK cell, and M1 macrophage, and positively correlated with PDCD1, CTLA4 and other immunoinhibitors, CCL5, CXCR3 and other chemokines and chemokine receptors. More importantly, TCIRG1 may regulate aerobic glycolysis in ccRCC via the AKT/mTOR signaling pathway, thereby affecting the malignant progression of ccRCC cell lines.

CONCLUSIONS

Our results demonstrate that the glycolysis-related biomarker TCIRG1 is a tumor-promoting factor by affecting aerobic glycolysis and tumor immune microenvironment in ccRCC, and this finding may provide a new idea for the treatment of ccRCC by combination of metabolic intervention and immunotherapy.

The multi-omics analyses of acsl1 reveal its translational significance as a tumor microenvironmental and prognostic biomarker in clear cell renal cell carcinoma

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of kidney cancer. Dysregulation of long-chain acyl-CoA synthetase 1 (ACSL1) is strongly implicated in undesirable results in varieties of cancers. Nevertheless, the dysregulation and associated multi-omics characteristics of ACSL1 in ccRCC remain elusive.

METHODS

We probed the mRNA and protein profiles of ACSL1 in RCC using data from the Cancer Genome Atlas, Gene Expression Omnibus, the Human Protein Atlas (HPA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) and verified them in our patient cohort and RCC cell lines. Correlations between ACSL1 expression and clinicopathological features, epigenetic modification and immune microenvironment characteristics were analyzed to reveal the multi-omics profile associated with ACSL1.

RESULTS

ACSL1 was down-regulated in ccRCC tissues compared to adjacent normal tissues. Lower expression of ACSL1 was linked to unfavorable pathological parameters and prognosis. The dysregulation of ACSL1 was greatly ascribed to CpG island-associated methylation modification. The ACSL1 high-expression subgroup had enriched fatty acid metabolism-related pathways and high expression of ferroptosis-related genes. In contrast, the ACSL1 low-expression subgroup exhibited higher immune and microenvironment scores, elevated expression of immune checkpoints PDCD1, CTLA4, LAG3, and TIGIT, and higher TIDE scores. Using data from the GDSC database, we corroborated that down-regulation of ACSL1 was associated with higher sensitivity towards Erlotinib, Pazopanib, and PI3K-Akt-mTOR-targeted therapeutic strategies.

CONCLUSION

Taken together, our findings point to ACSL1 as a biomarker for prognostic prediction of ccRCC, identifying the tumor microenvironment (TME) phenotype, and even contributing to treatment decision-making in ccRCC patients.

The expression pattern of pyruvate dehydrogenase kinases predicts prognosis and correlates with immune exhaustion in clear cell renal cell carcinoma

Renal cancer cells constitute a paradigm of tumor cells with a glycolytic reprogramming which drives metabolic alterations favouring cell survival and transformation. We studied the expression and activity of pyruvate dehydrogenase kinases (PDK1-4), key enzymes of the energy metabolism, in renal cancer cells. We analysed the expression, subcellular distribution and clinicopathological correlations of PDK1-4 by immunohistochemistry of tumor tissue microarray samples from a cohort of 96 clear cell renal cell carcinoma (ccRCC) patients. Gene expression analysis was performed on whole tumor tissue sections of a subset of ccRCC samples. PDK2 and PDK3 protein expression in tumor cells correlated with lower patient overall survival, whereas PDK1 protein expression correlated with higher patient survival. Gene expression analysis revealed molecular association of PDK2 and PDK3 expression with PI3K signalling pathway, as well as with T cell infiltration and exhausted CD8 T cells. Inhibition of PDK by dichloroacetate in human renal cancer cell lines resulted in lower cell viability, which was accompanied by an increase in pAKT. Together, our findings suggest a differential role for PDK enzymes in ccRCC progression, and highlight PDK as actionable metabolic proteins in relation with PI3K signalling and exhausted CD8 T cells in ccRCC.

Endoplasmic Reticulum Stress in Renal Cell Carcinoma

The endoplasmic reticulum is an organelle exerting crucial functions in protein production, metabolism homeostasis and cell signaling. Endoplasmic reticulum stress occurs when cells are damaged and the capacity of this organelle to perform its normal functions is reduced. Subsequently, specific signaling cascades, together forming the so-called unfolded protein response, are activated and deeply impact cell fate. In normal renal cells, these molecular pathways strive to either resolve cell injury or activate cell death, depending on the extent of cell damage. Therefore, the activation of the endoplasmic reticulum stress pathway was suggested as an interesting therapeutic strategy for pathologies such as cancer. However, renal cancer cells are known to hijack these stress mechanisms and exploit them to their advantage in order to promote their survival through rewiring of their metabolism, activation of oxidative stress responses, autophagy, inhibition of apoptosis and senescence. Recent data strongly suggest that a certain threshold of endoplasmic reticulum stress activation needs to be attained in cancer cells in order to shift endoplasmic reticulum stress responses from a pro-survival to a pro-apoptotic outcome. Several endoplasmic reticulum stress pharmacological modulators of interest for therapeutic purposes are already available, but only a handful were tested in the case of renal carcinoma, and their effects in an in vivo setting remain poorly known. This review discusses the relevance of endoplasmic reticulum stress activation or suppression in renal cancer cell progression and the therapeutic potential of targeting this cellular process for this cancer.

A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes

MOTIVATION

Multilevel molecular profiling of tumors and the integrative analysis with clinical outcomes have enabled a deeper characterization of cancer treatment. Mediation analysis has emerged as a promising statistical tool to identify and quantify the intermediate mechanisms by which a gene affects an outcome. However, existing methods lack a unified approach to handle various types of outcome variables, making them unsuitable for high-throughput molecular profiling data with highly interconnected variables.

RESULTS

We develop a general mediation analysis framework for proteogenomic data that include multiple exposures, multivariate mediators on various scales of effects as appropriate for continuous, binary and survival outcomes. Our estimation method avoids imposing constraints on model parameters such as the rare disease assumption, while accommodating multiple exposures and high-dimensional mediators. We compare our approach to other methods in extensive simulation studies at a range of sample sizes, disease prevalence and number of false mediators. Using kidney renal clear cell carcinoma proteogenomic data, we identify genes that are mediated by proteins and the underlying mechanisms on various survival outcomes that capture short- and long-term disease-specific clinical characteristics.

AVAILABILITY AND IMPLEMENTATION

Software is made available in an R package (https://github.com/longjp/mediateR).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

SPTBN1 abrogates renal clear cell carcinoma progression via glycolysis reprogramming in a GPT2-dependent manner

BACKGROUND

Renal clear cell carcinoma (ccRCC) is the most prevalent tumors worldwide. Discovering effective biomarkers is essential to monitor the prognosis and provide alternative clinical options. SPTBN1 is implicated in various cancerous processes. However, its role in ccRCC remains unelucidated. This study intends to explore the biological function and mechanism of SPTBN1 in ccRCC.

METHODS

Single-cell and bulk RNA-seq, tissue microarray, real-time quantitative PCR, and western blotting were applied to verify the expression and predictive value of SPTBN1 in ccRCC. Gain or loss of functional ccRCC cell line models were constructed, and in vitro and in vivo assays were performed to elucidate its tumorigenic phenotypes. Actinomycin D experiment, RNA immunoprecipitation (RIP), specific inhibitors, and rescue experiments were carried out to define the molecular mechanisms.

RESULTS

SPTBN1 was down-regulated in ccRCC and knockdown of SPTBN1 displayed a remarkably oncogenic role both in vitro and in vivo; while overexpressing SPTBN1 reversed this effect. SPTBN1 mediated ccRCC progression via the pathway of glutamate pyruvate transaminase 2 (GPT2)-dependent glycolysis. The expression of GPT2 was significantly negatively correlated with that of SPTBN1. As an RNA binding protein SPTBN1, regulated the mRNA stability of GPT2.

CONCLUSION

Our research demonstrated that SPTBN1 is significantly down-regulated in ccRCC. SPTBN1 knockdown promotes ccRCC progression via activating GPT2-dependent glycolysis. SPTBN1 may serve as a therapeutic target for the treatment of ccRCC.

Glutamine metabolism in cancers: Targeting the oxidative homeostasis

Glutamine is the most abundant amino acid in blood and tissues, and the most important nutrient except for glucose in cancer cells. Over the past years, most studies have focused on the role of Gln metabolism in supporting energy metabolism rather than maintaining oxidative homeostasis. In fact, Gln is an important factor in maintaining oxidative homeostasis of cancer cells, especially in “Glutamine addicted” cancer cells. Here, this paper will review the recent scientific literature about the link between Gln metabolism and oxidative homeostasis, with an emphasis on the potential role of Gln metabolism in different cancers. Given that oxidative homeostasis is of critical importance in cancer, understanding the impacts of a Gln metabolism on oxidative homeostasis, gaining great insights into underlying molecular mechanisms, and developing effective therapeutic strategies are of great importance.

Derivation of prognostic contextual histopathological features from whole-slide images of tumours via graph deep learning

Methods of computational pathology applied to the analysis of whole-slide images (WSIs) do not typically consider histopathological features from the tumour microenvironment. Here, we show that a graph deep neural network that considers such contextual features in gigapixel-sized WSIs in a semi-supervised manner can provide interpretable prognostic biomarkers. We designed a neural-network model that leverages attention techniques to learn features of the heterogeneous tumour microenvironment from memory-efficient representations of aggregates of highly correlated image patches. We trained the model with WSIs of kidney, breast, lung and uterine cancers and validated it by predicting the prognosis of 3,950 patients with these four different types of cancer. We also show that the model provides interpretable contextual features of clear cell renal cell carcinoma that allowed for the risk-based retrospective stratification of 1,333 patients. Deep graph neural networks that derive contextual histopathological features from WSIs may aid diagnostic and prognostic tasks.

High-dimension to high-dimension screening for detecting genome-wide epigenetic and noncoding RNA regulators of gene expression

MOTIVATION

The advancement of high-throughput technology characterizes a wide variety of epigenetic modifications and noncoding RNAs across the genome involved in disease pathogenesis via regulating gene expression. The high dimensionality of both epigenetic/noncoding RNA and gene expression data make it challenging to identify the important regulators of genes. Conducting univariate test for each possible regulator-gene pair is subject to serious multiple comparison burden, and direct application of regularization methods to select regulator-gene pairs is computationally infeasible. Applying fast screening to reduce dimension first before regularization is more efficient and stable than applying regularization methods alone.

RESULTS

We propose a novel screening method based on robust partial correlation to detect epigenetic and noncoding RNA regulators of gene expression over the whole genome, a problem that includes both high-dimensional predictors and high-dimensional responses. Compared to existing screening methods, our method is conceptually innovative that it reduces the dimension of both predictor and response, and screens at both node (regulators or genes) and edge (regulator-gene pairs) levels. We develop data-driven procedures to determine the conditional sets and the optimal screening threshold, and implement a fast iterative algorithm. Simulations and applications to long noncoding RNA and microRNA regulation in Kidney cancer and DNA methylation regulation in Glioblastoma Multiforme illustrate the validity and advantage of our method.

AVAILABILITY AND IMPLEMENTATION

The R package, related source codes and real datasets used in this article are provided at https://github.com/kehongjie/rPCor.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PBRM1 deficiency oncogenic addiction is associated with activated AKT–mTOR signalling and aerobic glycolysis in clear cell renal cell carcinoma cells

The PBRM1 (PB1) gene which encodes the specific subunit BAF180 of the PBAF SWI/SNF complex, is highly mutated (~ 40%) in clear cell renal cell carcinoma (ccRCC). However, its functions and impact on cell signalling are still not fully understood. Aerobic glycolysis, also known as the ‘Warburg Effect’, is a hallmark of cancer, whether PB1 is involved in this metabolic shift in clear cell renal cell carcinoma remains unclear. Here, with established stable knockdown PB1 cell lines, we performed functional assays to access the effects on 786‐O and SN12C cells. Based on the RNA‐seq data, we selected some genes encoding key glycolytic enzymes, including PFKP, ENO1, PKM and LDHA, and examined the expression levels. The AKT–mTOR signalling pathway activity and expression of HIF1α were also analysed. Our data demonstrate that PB1 deficiency promotes the proliferation, migration, Xenograft growth of 786‐O and SN12C cells. Notably, knockdown of PB1 activates AKT–mTOR signalling and increases the expression of key glycolytic enzymes at both mRNA and protein levels. Furthermore, we provide evidence that deficient PB1 and hypoxic conditions exert a synergistic effect on HIF 1α expression and lactate production. Thus, our study provides novel insights into the roles of tumour suppressor PB1 and suggests that the AKT–mTOR signalling pathway, as well as glycolysis, is a potential drug target for ccRCC patients with deficient PB1.

Comprehensive Genomic Characterization of Tumor Microenvironment and Relevant Signature in Clear Cell Renal Cell Carcinoma

Purpose

To systematically investigate the characterization of tumor microenvironment (TME) in clear cell renal cell carcinoma (ccRCC), we performed a comprehensive analysis incorporating genomic alterations, cellular interactions, infiltrating immune cells, and risk signature.

Patients and Methods

Multi-omics data including RNA-seq, single-nucleotide variant (SNV) data, copy number variation (CNV) data, miRNA, and corresponding prognostic data were obtained from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. The CIBERSORT algorithm was utilized to identify prognostic TME subclusters, and TMEscore was further quantified. Moreover, the mutational landscape of TCGA-KIRC was explored. Lastly, TIDE resource was applied to assess the significance of TMEscore in predicting immunotherapeutic benefits.

Results

We analyzed the TME infiltration patterns from 621 ccRCC patients and identified 5 specific TME subclusters associated with clinical outcomes. Then, we found that TMEcluster5 was significantly related to favorable prognosis and enriched memory B-cell infiltration. Accordingly, we depicted the clustering landscape of TMEclusters, TMEscore levels, tumor mutation burden (TMB), tumor grades, purity, and ploidy in all patients. Lastly, TIDE was used to assess the efficiency of immune checkpoint blockers (ICBs) and found that the TMEscore has superior predictive significance to TMB, making it an essential independent prognostic biomarker and drug indicator for clinical use.

Conclusions

Our study depicted the clustering landscape of TMEclusters, TMEscore levels, TMB, tumor grades, purity, and ploidy in total ccRCC patients. The TMEscore was proved to have promising significance for predicting prognosis and ICB responses, in accordance with the goal of developing rationally individualized therapeutic interventions.

A novel diagnostic method: FT-IR, Raman and derivative spectroscopy fusion technology for the rapid diagnosis of renal cell carcinoma serum

This research innovatively combines FT-IR, Raman spectroscopy and their first-derivative spectroscopy to develop a rapid diagnosis method for renal cell carcinoma (RCC). After measuring the Raman spectra and FT-IR spectra of 45 cases of control subjects and 28 cases of RCC, the first derivative of the infrared spectra and the Raman spectra were calculated respectively. Principal component analysis (PCA) was used to extract the features of the infrared spectra, first-derivative infrared spectra, Raman spectra and first-derivative Raman spectra. Then the four feature matrices were merged as fused spectral feature matrices. The fused matrices were used as the input of AlexNet and MCNN. The fused spectral feature matrices were used as the input of AlexNet and MCNN. The adjusted AlexNet model performed better, and the classification accuracy of the fused spectral data is 93%. Compared with the classification results of infrared spectra (74%), Raman spectra (75%) and the fusion of infrared and Raman spectra (79%) combined with the adjusted AlexNet model, the classification result of the fusion of infrared spectra, Raman spectra and their first-derivative was significantly improved. The experimental results show that infrared spectroscopy, Raman spectroscopy and their first-derivative fusion technology combined with deep learning algorithms has great potential in the diagnosis of RCC.

Metabolomic Profiling in Renal Cell Carcinoma Patients: News and Views

BACKGROUND

We address novelty regarding metabolomic profiling in renal cell carcinoma (RCC) patients, in an attempt to postulate potential treatment strategies.

METHODS

A large-scale literature search in existing scientific websites focusing on the keywords "renal cell carcinoma", "clear cell histology", "papillary histology", "metabolomic profiling", and "therapeutics" was performed. Results: The PI3K/Akt signaling pathway is key in clear cell RCC metabolism and accordingly several drugs are presently available for routine use in clinical practice. Along this line, new treatment combinations against PI3K/Akt family members are currently under clinical investigation. On the other hand, new developed targets such as c-Met tyrosine kinase domain, glutathione (GSH) metabolism, and histone deacetylases enzymes (HDAC), as well as therapeutic strategies targeting them are currently being tested in clinical trials and here discussed.

CONCLUSIONS

In RCC patients, the PI3K/Akt signaling is still the most effective targetable pathway. Targeting other metabolic pathways such as c-Met, GSH, and HDAC appears to be a promising approach and deserve further insights.

HMGCS2 in metabolic pathways was associated with overall survival in hepatocellular carcinoma: A LASSO-derived study

This integrated bioinformatic study aimed to investigate potential prognostic candidates in hepatocellular carcinoma (HCC). In the GSE14520, GSE101685, and The Cancer Genome Atlas (TCGA) datasets, differentially expressed genes (DEGs) were identified and functional pathways of common DEGs were enriched. The least absolute shrinkage and selection operator (LASSO) model was used to screen the potential parameters associated with overall survival (OS) in HCC patients. Metabolic pathways were the most significantly enriched functional pathways of common DEGs in these three datasets. After LASSO model analysis, HMGCS2, UGP2, BCLC staging and TNM staging were screened as potential prognostic candidates for OS in HCC patients in GSE14520. HMGCS2 in the metabolic pathway was significantly downregulated in tumor tissues and peripheral blood mononuclear cells in HCC patients (all p < 0.05). Cox regression model indicated that HMGCS2 might be associate with OS in HCC patients in GSE14520 and in the TCGA (p = 0.029 and p = 0.05, respectively). Kaplan-Meier analysis demonstrated that HMGCS2 downregulation in tumors contributed to an unfavorable OS in HCC patients, both in GSE14520 and in the TCGA (p = 0.0001 and p = 0.0002, respectively). Additionally, HMGCS2 was significantly downregulated in HCC patients with high alpha-fetoprotein (AFP), main tumor size >5 cm, multinodular, advanced tumor staging including BCLC, TNM and CLIP (all p < 0.05). HMGCS2 was involved in metabolic pathways, and downregulated HMGCS2 in tumors was associated with unfavorable OS in HCC patients.

A HIF1α-GPD1 feedforward loop inhibits the progression of renal clear cell carcinoma via mitochondrial function and lipid metabolism

Background

Hypoxia signaling, especially the hypoxia inducible factor (HIF) pathway, is a major player in clear cell renal cell carcinoma (ccRCC), which is characterized by disorders in lipid and glycogen metabolism. However, the interaction between hypoxia and lipid metabolism in ccRCC progression is still poorly understood.

Methods

We used bioinformatic analysis and discovered that glycerol-3-phosphate dehydrogenase 1 (GPD1) may play a key role in hypoxia and lipid metabolism pathways in ccRCC. Tissue microarray, IHC staining, and survival analysis were performed to evaluate clinical function. In vitro and in vivo assays showed the biological effects of GPD1 in ccRCC progression.

Results

We found that the expression of GPD1 was downregulated in ccRCC tissues, and overexpression of GPD1 inhibited the progression of ccRCC both in vivo and in vitro. Furthermore, we demonstrated that hypoxia inducible factor-1α (HIF1α) directly regulates GPD1 at the transcriptional level, which leads to the inhibition of mitochondrial function and lipid metabolism. Additionally, GPD1 was shown to inhibit prolyl hydroxylase 3 (PHD3), which blocks prolyl-hydroxylation of HIF1α and subsequent proteasomal degradation, and thus reinforces the inhibition of mitochondrial function and phosphorylation of AMPK via suppressing glycerol-3-phosphate dehydrogenase 2 (GPD2).

Conclusions

This study not only demonstrated that HIF1α-GPD1 forms a positive feedforward loop inhibiting mitochondrial function and lipid metabolism in ccRCC, but also discovered a new mechanism for the molecular basis of HIF1α to inhibit tumor activity, thus providing novel insights into hypoxia-lipid-mediated ccRCC therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01996-6.

Metabolic reprogramming in renal cancer: Events of a metabolic disease

Recent studies have established that tumors can reprogram the pathways involved in nutrient uptake and metabolism to withstand the altered biosynthetic, bioenergetics and redox requirements of cancer cells. This phenomenon is called metabolic reprogramming, which is promoted by the loss of tumor suppressor genes and activation of oncogenes. Because of alterations and perturbations in multiple metabolic pathways, renal cell carcinoma (RCC) is sometimes termed as a "metabolic disease". The majority of metabolic reprogramming in renal cancer is caused by the inactivation of von Hippel-Lindau (VHL) gene and activation of the Ras-PI3K-AKT-mTOR pathway. Hypoxia-inducible factor (HIF) and Myc are other important players in the metabolic reprogramming of RCC. All types of RCCs are associated with reprogramming of glucose and fatty acid metabolism and the tricarboxylic acid (TCA) cycle. Metabolism of glutamine, tryptophan and arginine is also reprogrammed in renal cancer to favor tumor growth and oncogenesis. Together, understanding these modifications or reprogramming of the metabolic pathways in detail offer ample opportunities for the development of new therapeutic targets and strategies, discovery of biomarkers and identification of effective tumor detection methods.

Metabolic imaging with hyperpolarized 13 C pyruvate magnetic resonance imaging in patients with renal tumors-Initial experience

BACKGROUND

Optimal treatment selection for localized renal tumors is challenging because of their variable biologic behavior and limitations in the preoperative assessment of tumor aggressiveness. The authors investigated the emerging hyperpolarized (HP) ¹³ C magnetic resonance imaging (MRI) technique to noninvasively assess tumor lactate production, which is strongly associated with tumor aggressiveness.

METHODS

Eleven patients with renal tumors underwent HP ¹³ C pyruvate MRI before surgical resection. Tumor ¹³ C pyruvate and ¹³ C lactate images were acquired dynamically. Five patients underwent 2 scans on the same day to assess the intrapatient reproducibility of HP ¹³ C pyruvate MRI. Tumor metabolic data were compared with histopathology findings.

RESULTS

Eight patients had tumors with a sufficient metabolite signal-to-noise ratio for analysis; an insufficient tumor signal-to-noise ratio was noted in 2 patients, likely caused by poor tumor perfusion and, in 1 patient, because of technical errors. Of the 8 patients, 3 had high-grade clear cell renal cell carcinoma (ccRCC), 3 had low-grade ccRCC, and 2 had chromophobe RCC. There was a trend toward a higher lactate-to-pyruvate ratio in high-grade ccRCCs compared with low-grade ccRCCs. Both chromophobe RCCs had relatively high lactate-to-pyruvate ratios. Good reproducibility was noted across the 5 patients who underwent 2 HP ¹³ C pyruvate MRI scans on the same day.

CONCLUSIONS

The current results demonstrate the feasibility of HP ¹³ C pyruvate MRI for investigating the metabolic phenotype of localized renal tumors. The initial data indicate good reproducibility of metabolite measurements. In addition, the metabolic data indicate a trend toward differentiating low-grade and high-grade ccRCCs, the most common subtype of renal cancer.

LAY SUMMARY

Renal tumors are frequently discovered incidentally because of the increased use of medical imaging, but it is challenging to identify which aggressive tumors should be treated. A new metabolic imaging technique was applied to noninvasively predict renal tumor aggressiveness. The imaging results were compared with tumor samples taken during surgery and showed a trend toward differentiating between low-grade and high-grade clear cell renal cell carcinomas, which are the most common type of renal cancers.

Cancer Cells' Metabolism Dynamics in Renal Cell Carcinoma Patients' Outcome: Influence of GLUT-1-Related hsa-miR-144 and hsa-miR-186

Simple Summary

Renal cell carcinoma (RCC) is a metabolic associated cancer and the most common and lethal neoplasia in the adult kidney. This study aimed to understand the potential role of hsa-miR-144-5p and hsa-miR-186-3p (which target Glucose Transporter 1—GLUT-1) in clear cell RCC (ccRCC) glycolysis status, as well as their potential as biomarkers. A decrease of intracellular levels of these miRNAs and increase of their excretion was associated with an increase of GLUT-1’s levels and glycolysis’ markers. RCC patients presented higher plasmatic levels of hsa-miR-186-3p than healthy individuals and hsa-miR144-5p’s higher levels were associated with early clinical stages of RCC. Additionally, patients with low plasmatic levels of hsa-miR-144-5p and high plasmatic levels of hsa-miR-186-3p (high-risk group) showed a worse overall survival. Overall, these results indicate that circulating hsa-miR-144-5p and hsa-miR-186-3p may be potential biomarkers of ccRCC prognosis.

Abstract

The cancer cells’ metabolism is altered due to deregulation of key proteins, including glucose transporter 1 (GLUT-1), whose mRNA levels are influenced by microRNAs (miRNAs). Renal cell carcinoma (RCC) is the most common and lethal neoplasia in the adult kidney, mostly due to the lack of accurate diagnosis and follow-up biomarkers. Being a metabolic associated cancer, this study aimed to understand the hsa-miR-144-5p and hsa-miR-186-3p’s potential as biomarkers of clear cell RCC (ccRCC), establishing their role in its glycolysis status. Using three ccRCC lines, the intra- and extracellular levels of both miRNAs, GLUT-1’s mRNA expression and protein levels were assessed. Glucose consumption and lactate production were evaluated as glycolysis markers. A decrease of intracellular levels of these miRNAs and increase of their excretion was observed, associated with an increase of GLUT-1’s levels and glycolysis’ markers. Through a liquid biopsy approach, we found that RCC patients present higher plasmatic levels of hsa-miR-186-3p than healthy individuals. The Hsa-miR144-5p’s higher levels were associated with early clinical stages. When patients were stratified according to miRNAs plasmatic levels, low plasmatic levels of hsa-miR-144-5p and high plasmatic levels of hsa-miR-186-3p (high-risk group) showed the worst overall survival. Thus, circulating levels of these miRNAs may be potential biomarkers of ccRCC prognosis.

Downregulated METTL14 accumulates BPTF that reinforces super-enhancers and distal lung metastasis via glycolytic reprogramming in renal cell carcinoma

Background: Methyltransferase-like 14 (METTL14) participates in tumorigenesis in several malignancies, but how METTL14 mediates the metastasis of renal cell carcinoma (RCC) has never been reported. Methods: Western blotting, quantitative real-time PCR, and immunohistochemistry were used to determine the mRNA and protein levels of relevant genes. Methylated RNA immunoprecipitation sequencing and RNA sequencing were utilized to screen potential targets of METTL14. Chromatin immunoprecipitation sequencing and assay for transposase-accessible chromatin sequencing were performed to investigate epigenetic alterations. The biological roles and mechanisms of METTL14/BPTF in promoting lung metastasis were confirmed in vitro and in vivo using cell lines, patient samples, xenograft models, and organoids. Results: Utilizing the TCGA-KIRC and Ruijin-RCC datasets, we found low expression of METTL14 in mRCC samples, which predicted poor prognosis. METTL14 deficiency promoted RCC metastasis in vitro and in vivo. Mechanistically, METTL14-mediated m⁶A modification negatively regulated the mRNA stability of bromodomain PHD finger transcription factor (BPTF) and depended on BPTF to drive lung metastasis. Accumulated BPTF in METTL14-deficient cells remodeled the enhancer landscape to reinforce several oncogenic crosstalk. Particularly, BPTF constituted super-enhancers that activate downstream targets like enolase 2 and SRC proto-oncogene nonreceptor tyrosine kinase, leading to glycolytic reprogramming of METTL14^-/- cells. Finally, we determined the efficacy of the BPTF inhibitor AU1 in suppressing mRCC of patient-derived cells, mRCC-derived organoids (MDOs), and orthotopic xenograft models. Conclusions: Our study is the first to investigate the essential role of m⁶A modification and the METTL14/BPTF axis in the epigenetic and metabolic remodeling of mRCC, highlighting AU1 as a vital therapeutic candidate.

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.

Alternative Splicing and Cleavage of GLUT8

The GLUT (SLC2) family of membrane-associated transporters are described as glucose transporters. However, this family is divided into three classes and, though the regulated transporter activity of class I proteins is becoming better understood, class III protein functions continue to be obscure. We have cataloged the relative expression and splicing of SLC2 mRNA isomers in tumors and normal tissues, with a focus on breast tumors and cell lines. mRNA for the class III protein GLUT8 is the predominant SLC2 species expressed alongside GLUT1 in many tissues, but GLUT8 mRNA exists mostly as an untranslated splice form in tumors. We confirm that GLUT8 is not presented at the cell surface and does not transport glucose directly. However, we reveal a lysosome-dependent reaction that cleaves the GLUT8 protein and releases the carboxy-terminal peptide to a separate vesicle population. Given the localization of GLUT8 at a major metabolic hub (the late endosomal/lysosomal interface) and its regulated cleavage reaction, we evaluated TXNIP-mediated hexosamine homeostasis and speculate that GLUT8 may function as a sensory component of this reaction.

Beyond glycolysis: Hypoxia signaling as a master regulator of alternative metabolic pathways and the implications in clear cell renal cell carcinoma

The relationship between kidney cancer, specifically clear cell renal cell carcinoma (ccRCC), and the hypoxia signaling program has been extensively characterized. Its underlying role as the primary driver of the disease has led to the development of the most effective targeted therapies to date. Cellular responses to hypoxia or mutations affecting the von Hippel-Lindau (VHL) tumor suppressor gene stabilize the hypoxia inducible factor (HIF) transcription factors which then orchestrate elaborate downstream signaling events resulting in adaptations to key biological processes, such as reprogramming metabolism. The direct link of hypoxia signaling to glucose uptake and glycolysis has long been appreciated; however, the HIF family of proteins directly regulate many downstream targets, including other transcription factors with their own extensive networks. In this review, we will summarize our current understanding of how hypoxia signaling regulates other metabolic pathways and how this contributes to the development and progression of clear cell renal cell carcinomas.

Integrative -omics and HLA-ligandomics analysis to identify novel drug targets for ccRCC immunotherapy

Background

Clear cell renal cell carcinoma (ccRCC) is the dominant subtype of renal cancer. With currently available therapies, cure of advanced and metastatic ccRCC is achieved only in rare cases. Here, we developed a workflow integrating different -omics technologies to identify ccRCC-specific HLA-presented peptides as potential drug targets for ccRCC immunotherapy.

Methods

We analyzed HLA-presented peptides by MS-based ligandomics of 55 ccRCC tumors (cohort 1), paired non-tumor renal tissues, and 158 benign tissues from other organs. Pathways enriched in ccRCC compared to its cell type of origin were identified by transcriptome and gene set enrichment analyses in 51 tumor tissues of the same cohort. To retrieve a list of candidate targets with involvement in ccRCC pathogenesis, ccRCC-specific pathway genes were intersected with the source genes of tumor-exclusive peptides. The candidates were validated in an independent cohort from The Cancer Genome Atlas (TCGA KIRC, n = 452). DNA methylation (TCGA KIRC, n = 273), somatic mutations (TCGA KIRC, n = 392), and gene ontology (GO) and correlations with tumor metabolites (cohort 1, n = 30) and immune-oncological markers (cohort 1, n = 37) were analyzed to characterize regulatory and functional involvements. CD8⁺ T cell priming assays were used to identify immunogenic peptides. The candidate gene EGLN3 was functionally investigated in cell culture.

Results

A total of 34,226 HLA class I- and 19,325 class II-presented peptides were identified in ccRCC tissue, of which 443 class I and 203 class II peptides were ccRCC-specific and presented in ≥ 3 tumors. One hundred eighty-five of the 499 corresponding source genes were involved in pathways activated by ccRCC tumors. After validation in the independent cohort from TCGA, 113 final candidate genes remained. Candidates were involved in extracellular matrix organization, hypoxic signaling, immune processes, and others. Nine of the 12 peptides assessed by immunogenicity analysis were able to activate naïve CD8⁺ T cells, including peptides derived from EGLN3. Functional analysis of EGLN3 revealed possible tumor-promoting functions.

Conclusions

Integration of HLA ligandomics, transcriptomics, genetic, and epigenetic data leads to the identification of novel functionally relevant therapeutic targets for ccRCC immunotherapy. Validation of the identified targets is recommended to expand the treatment landscape of ccRCC.

A cluster of long non-coding RNAs exhibit diagnostic and prognostic values in renal cell carcinoma

Kidney cancer ranked in the top 10 for both men and women in the estimated numbers of new cancer cases in the United States in 2018. Targeted therapies have recently been administered to patients with clear cell renal cell carcinoma (ccRCC), but the overall survival of patients at the terminal stage of the disease has not been as good as expected. It is therefore necessary to uncover efficient biomarkers for early diagnosis, and to clarify the molecular mechanisms underlying ccRCC progression and metastasis. Increased evidence has shown that long non-coding RNAs (lncRNAs) play important roles during tumor progression. In this study, 10 candidate lncRNAs with diagnostic and prognostic values in ccRCC were identified: IGFL2-AS1, AC023043.1, AP000439.2, AC124854.1, AL355102.4, TMEM246-AS1, AL133467.3, ZNF582-AS1, LINC01510 and PSMG3-AS1. Enrichment analysis revealed metabolic and functional pathways, which may be closely associated with kidney cancer tumorigenesis. Six representative processes were summarized, namely glycolysis, amino acid metabolism, lipid synthesis, reductive carboxylation, nucleotide metabolism, transmembrane transport and signal transduction. In combination, the present results provided prognostic and diagnostic biomarkers for ccRCC and might pave the way for targeted intervention and molecular therapies in the future.

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.