Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis.
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ABSTRACT:
SUBMITTER: Wettersten HI
PROVIDER: S-EPMC4470795 | biostudies-literature | 2015 Jun
REPOSITORIES: biostudies-literature
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Project description:Kidney cancer, or renal cell carcinoma (RCC), is a disease of increasing incidence that commonly is seen in the general practice of nephrology. Despite this state of affairs, this fascinating and highly morbid disease frequently is under-represented, or even absent, from the curriculum of nephrologists in training and generally is underemphasized in national nephrology meetings, both scientific as well as clinical. Although classic concepts in cancer research in general had led to the concept that cancer is a disease resulting from mutations in the control of growth-regulating pathways, reinforced by the discovery of oncogenes, more contemporary research, particularly in kidney cancer, has uncovered changes in metabolic pathways mediated by those same genes that control tumor energetics and biosynthesis. This adaptation of classic biochemical pathways to the tumor's advantage has been labeled metabolic reprogramming. For example, in the case of kidney cancer there exists a near-universal presence of von Hippel-Lindau tumor suppressor (pVHL) inactivation in the most common form, clear cell RCC (ccRCC), leading to activation of hypoxia-relevant and other metabolic pathways. Studies of this and other pathways in clear cell RCC (ccRCC) have been particularly revealing, leading to the concept that ccRCC can itself be considered a metabolic disease. For this reason, the relatively new method of metabolomics has become a useful technique in the study of ccRCC to tease out those pathways that have been reprogrammed by the tumor to its maximum survival advantage. Furthermore, identification of the nodes of such pathways can lead to novel areas for drug intervention in a disease for which such targets are seriously lacking. Further research and dissemination of these concepts, likely using omics techniques, will lead to clinical trials of therapeutics specifically targeted to tumor metabolism, rather than those generally toxic to all proliferating cells. Such novel agents are highly likely to be more effective than existing drugs and to have far fewer adverse effects. This review provides a general overview of the technique of metabolomics and then discusses how it and other omics techniques have been used to further our understanding of the basic biology of kidney cancer as well as to identify new therapeutic approaches.
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Project description:Kidney cancer is frequently metastatic on presentation at which point the disease is associated with a 95% mortality. Assessment of tumor grade on pathological examination is the most powerful means for prognostication as well as for stratification of patients into those who might respond to conventional or targeted therapy. Although there exist several grading systems in common use, all suffer from significant disparity among observers. In an attempt to objectify this process as well as to acquire grade-specific mechanistic information, we performed LC-MS/MS-based proteomics analysis on 50 clear cell kidney cancers equally distributed among normal tissues and Fuhrman grades 1-4. Initial experiments confirmed the utility of using archived formalin-fixed paraffin-embedded samples for LC-MS/MS-based proteomics analysis, and the LC-MS/MS findings were validated by extensive immunoblotting. We now show that changes among many biochemical processes and pathways are strongly grade-dependent with the glycolytic and amino acid synthetic pathways highly represented. In addition, proteins relating to acute phase and xenobiotic metabolism signaling are highly represented. Self-organized mapping of proteins with similar patterns of expression led to the creation of a heat map that will be useful in grade characterization as well as in future research relating to oncogenic mechanisms and targeted therapies for kidney cancer.
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Project description:The metabolic crosstalk between tumor cells and tumor-associated macrophages (TAMs) has emerged as a critical contributor to tumor development and progression. In breast cancer (BC), the abundance of immune-suppressive TAMs positively correlates with poor prognosis. However, little is known about how TAMs reprogram their metabolism in the BC microenvironment. In this work, we have assessed the metabolic and phenotypic impact of incubating THP-1-derived macrophages in conditioned media (CM) from two BC cell lines cultured in normoxia/hypoxia: MDA-MB-231 cells (highly metastatic, triple-negative BC), and MCF-7 cells (less aggressive, luminal BC). The resulting tumor-educated macrophages (TEM) displayed prominent differences in their metabolic activity and composition, compared to control cells (M0), as assessed by exo- and endometabolomics. In particular, TEM turned to the utilization of extracellular pyruvate, alanine, and branched chain keto acids (BCKA), while exhibiting alterations in metabolites associated with several intracellular pathways, including polyamines catabolism (MDA-TEM), collagen degradation (mainly MCF-TEM), adenosine accumulation (mainly MDA-TEM) and lipid metabolism. Interestingly, following a second-stage incubation in fresh RPMI medium, TEM still displayed several metabolic differences compared to M0, indicating persistent reprogramming. Overall, this work provided new insights into the metabolic plasticity of TEM, revealing potentially important nutritional exchanges and immunoregulatory metabolites in the BC TME.
| S-EPMC9954003 | biostudies-literature
Project description:BackgroundThe complex yet interrelated connections between cancer metabolism and oncogenic driver genes are relatively unexplored but have the potential to identify novel biomarkers and drug targets with prognostic and therapeutic value. The goal of this study was to identify global metabolic profiles of breast tumors isolated from multiple transgenic mouse models and to identify unique metabolic signatures driven by these oncogenes.MethodsUsing mass spectrometry (GC-MS, LC-MS/MS, and capillary zone electrophoresis (CZE)-MS platforms), we quantified and compared the levels of 374 metabolites in breast tissue from normal and transgenic mouse breast cancer models overexpressing a panel of oncogenes (PyMT, PyMT-DB, Wnt1, Neu, and C3-TAg). We also compared the mouse metabolomics data to published human metabolomics data already linked to clinical data.ResultsThrough analysis of our metabolomics data, we identified metabolic differences between normal and tumor breast tissues as well as metabolic differences unique to each initiating oncogene. We also quantified the metabolic profiles of the mammary fat pad versus mammary epithelium by CZE-MS/MS. However, the differences between the tissues did not account for the majority of the metabolic differences between the normal mammary gland and breast tumor tissues. Therefore, the differences between the cohorts were unlikely due to cellular heterogeneity. Of the mouse models used in this study, C3-TAg was the only cohort with a tumor metabolic signature composed of ten metabolites that had significant prognostic value in breast cancer patients. Gene expression analysis identified candidate genes that may contribute to the metabolic reprogramming.ConclusionsThis study identifies oncogene-induced metabolic reprogramming within mouse breast tumors and compares the results to that of human breast tumors, providing a unique look at the relationship between and clinical value of oncogene initiation and metabolism during breast cancer.
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Project description:Peroxidasin (PXDN), a human homolog of Drosophila PXDN, belongs to the family of heme peroxidases and has been found to promote oxidative stress in cardiovascular tissue, however, its role in prostate cancer has not been previously elucidated. We hypothesized that PXDN promotes prostate cancer progression via regulation of metabolic and oxidative stress pathways. We analyzed PXDN expression in prostate tissue by immunohistochemistry and found increased PXDN expression with prostate cancer progression as compared to normal tissue or cells. PXDN knockdown followed by proteomic analysis revealed an increase in oxidative stress, mitochondrial dysfunction and gluconeogenesis pathways. Additionally, Liquid Chromatography with tandem mass spectrometry (LC-MS/MS)-based metabolomics confirmed that PXDN knockdown induced global reprogramming associated with increased oxidative stress and decreased nucleotide biosynthesis. We further demonstrated that PXDN knockdown led to an increase in reactive oxygen species (ROS) associated with decreased cell viability and increased apoptosis. Finally, PXDN knockdown decreased colony formation on soft agar. Overall, the data suggest that PXDN promotes progression of prostate cancer by regulating the metabolome, more specifically, by inhibiting oxidative stress leading to decreased apoptosis. Therefore, PXDN may be a biomarker associated with prostate cancer and a potential therapeutic target.
| S-EPMC6627806 | biostudies-literature
Project description:In the age of bioinformatics and with the advent of high-powered computation over the past decade or so the landscape of biomedical research has become radically altered. Whereas a generation ago, investigators would study their "favorite" protein or gene and exhaustively catalog the role of this compound in their disease of interest, the appearance of omics has changed the face of medicine such that much of the cutting edge (and fundable!) medical research now evaluates the biology of the disease nearly in its entirety. Couple this with the realization that kidney cancer is a "metabolic disease" due to its multiple derangements in biochemical pathways [1, 2], and clear cell renal cell carcinoma (ccRCC) becomes ripe for data mining using multiple omics approaches.
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Project description:Biofilm formation plays a key role in many bacteria causing infections, which mostly accounts for high-frequency infectious recurrence and antibiotics resistance. In this study, we sought to compare modified metabolism of biofilm and planktonic populations with UTI89, a predominant agent of urinary tract infection, by combining mass spectrometry based untargeted and targeted metabolomics methods, as well as cytological visualization, which enable us to identify the driven metabolites and associated metabolic pathways underlying biofilm formation. Surprisingly, our finding revealed distinct differences in both phenotypic morphology and metabolism between two patterns. Furthermore, we identified and characterized 38 differential metabolites and associated three metabolic pathways involving glycerolipid metabolism, amino acid metabolism and carbohydrate metabolism that were altered mostly during biofilm formation. This discovery in metabolic phenotyping permitted biofilm formation shall provide us a novel insight into the dissociation of biofilm, which enable to develop novel biofilm based treatments against pathogen causing infections, with lower antibiotic resistance.
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Project description:BackgroundRenal cell carcinoma (RCC) is the sixth leading cause of cancer death and is responsible for 11,000 deaths per year in the US. Approximately one-third of patients present with disease which is already metastatic and for which there is currently no adequate treatment, and no biofluid screening tests exist for RCC. In this study, we have undertaken a comprehensive proteomic analysis and subsequently a pathway and network approach to identify biological processes involved in clear cell RCC (ccRCC). We have used these data to investigate urinary markers of RCC which could be applied to high-risk patients, or to those being followed for recurrence, for early diagnosis and treatment, thereby substantially reducing mortality of this disease.ResultsUsing 2-dimensional electrophoresis and mass spectrometric analysis, we identified 31 proteins which were differentially expressed with a high degree of significance in ccRCC as compared to adjacent non-malignant tissue, and we confirmed some of these by immunoblotting, immunohistochemistry, and comparison to published transcriptomic data. When evaluated by several pathway and biological process analysis programs, these proteins are demonstrated to be involved with a high degree of confidence (p values < 2.0 E-05) in glycolysis, propanoate metabolism, pyruvate metabolism, urea cycle and arginine/proline metabolism, as well as in the non-metabolic p53 and FAS pathways. In a pilot study using random urine samples from both ccRCC and control patients, we performed metabolic profiling and found that only sorbitol, a component of an alternative glycolysis pathway, is significantly elevated at 5.4-fold in RCC patients as compared to controls.ConclusionExtensive pathway and network analysis allowed for the discovery of highly significant pathways from a set of clear cell RCC samples. Knowledge of activation of these processes will lead to novel assays identifying their proteomic and/or metabolomic signatures in biofluids of patient at high risk for this disease; we provide pilot data for such a urinary bioassay. Furthermore, we demonstrate how the knowledge of networks, processes, and pathways altered in kidney cancer may be used to influence the choice of optimal therapy.
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Project description:The in situ metabolic profiling of the kidney is crucial to investigate the complex metabolic reprogramming underlying diabetic kidney disease (DKD) and to allow exploration of potential metabolic targets to improve kidney function. However, as the kidney is a highly heterogeneous organ, traditional metabolomic methods based on bulk analysis that produce an averaged measurement are inadequate. Herein, we employed an in situ metabolomics approach to discover alternations of DKD-associated metabolites and metabolic pathways. A series of histology-specific metabolic disturbances were discovered in situ using airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI). In combination with integrated metabolomics analysis, five dysfunctional metabolic pathways were identified and located in the kidneys of type-2 DKD mice simultaneously for the first time, including taurine metabolism, arginine and proline metabolism, histidine metabolism, biosynthesis of unsaturated fatty acids, and fatty acid degradation pathways. As crucial nodes of metabolic pathways, five dysregulated rate-limiting enzymes related to altered metabolic pathways were further identified. These findings reveal alternations from metabolites to enzymes at the molecular level in the progression of DKD and provide insights into DKD-associated metabolic reprogramming.
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