Thekkelnaycke M. Rajendiran

Metabolomic Profiles Delineate Potential Role for Sarcosine in Prostate Cancer Progression

Multiple, complex molecular events characterize cancer development and progression. Deciphering the molecular networks that distinguish organ-confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumours, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we profiled more than 1,126 metabolites across 262 clinical samples related to prostate cancer (42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer and metastatic disease. Sarcosine, an N-methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly increased during prostate cancer progression to metastasis and can be detected non-invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine-N-methyl transferase, the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity.

K⁺ efflux is the common trigger of NLRP3 inflammasome activation by bacterial toxins and particulate matter.

The NLRP3 inflammasome is an important component of the innate immune system. However, its mechanism of activation remains largely unknown. We show that NLRP3 activators including bacterial pore-forming toxins, nigericin, ATP, and particulate matter caused mitochondrial perturbation or the opening of a large membrane pore, but this was not required for NLRP3 activation. Furthermore, reactive oxygen species generation or a change in cell volume was not necessary for NLRP3 activation. Instead, the only common activity induced by all NLRP3 agonists was the permeation of the cell membrane to K⁺ and Na⁺. Notably, reduction of the intracellular K⁺ concentration was sufficient to activate NLRP3, whereas an increase in intracellular Na⁺ modulated but was not strictly required for inflammasome activation. These results provide a unifying model for the activation of the NLRP3 inflammasome in which a drop in cytosolic K⁺ is the common step that is necessary and sufficient for caspase-1 activation.

Magic angle spinning NMR-based metabolic profiling of head and neck squamous cell carcinoma tissues

High-resolution magic-angle spinning (HR-MAS) proton NMR spectroscopy is used to explore the metabolic signatures of head and neck squamous cell carcinoma (HNSCC) which included matched normal adjacent tissue (NAT) and tumor originating from tongue, lip, larynx and oral cavity, and associated lymph-node metastatic (LN-Met) tissues. A total of 43 tissues (18 NAT, 18 Tumor and 7 LN-Met) from 22 HNSCC patients were analyzed. Principal Component Analysis of NMR data showed a clear classification between NAT and tumor tissues, however, LN-Met tissues were classified among tumor. A partial least-squares discriminant analysis model generated from NMR metabolic profiles was used to differentiate normal from tumor samples (Q(2) > 0.80, Receiver Operator Characteristic area under the curve >0.86, using 7-fold cross validation). HNSCC and LN-Met tissues showed elevated levels of lactate, amino acids including leucine, isoleucine, valine, alanine, glutamine, glutamate, aspartate, glycine, phenylalanine and tyrosine, choline containing compounds, creatine, taurine, glutathione, and decreased levels of triglycerides. These elevated metabolites were associated with highly active glycolysis, increased amino acids influx (anaplerosis) into the TCA cycle, altered energy metabolism, membrane choline phospholipid metabolism, and oxidative and osmotic defense mechanisms. Moreover, decreased levels of triglycerides may indicate lipolysis followed by β-oxidation of fatty acids that may exist to deliver bioenergy for rapid tumor cell proliferation and growth.

Delineating Metabolic Signatures of Head and Neck Squamous Cell Carcinoma: Phospholipase A2, a Potential Therapeutic Target

A better understanding of molecular pathways involved in malignant transformation of head and neck squamous cell carcinoma (HNSCC) is essential for the development of novel and efficient anti-cancer drugs. To delineate the global metabolism of HNSCC, we report (1)H NMR-based metabolic profiling of HNSCC cells from five different patients that were derived from various sites of the upper aerodigestive tract, including the floor of mouth, tongue and larynx. Primary cultures of normal human oral keratinocytes (NHOK) from three different donors were used for comparison. (1)H NMR spectra of polar and non-polar extracts of cells were used to identify more than thirty-five metabolites. Principal component analysis performed on the NMR data revealed a clear classification of NHOK and HNSCC cells. HNSCC cells exhibited significantly altered levels of various metabolites that clearly revealed dysregulation in multiple metabolic events, including Warburg effect, oxidative phosphorylation, energy metabolism, TCA cycle anaplerotic flux, glutaminolysis, hexosamine pathway, osmo-regulatory and anti-oxidant mechanism. In addition, significant alterations in the ratios of phosphatidylcholine/lysophosphatidylcholine and phosphocholine/glycerophosphocholine, and elevated arachidonic acid observed in HNSCC cells reveal an altered membrane choline phospholipid metabolism (MCPM). Furthermore, significantly increased activity of phospholipase A(2) (PLA(2)), particularly cytosolic PLA(2) (cPLA(2)) observed in all the HNSCC cells confirm an altered MCPM. In summary, the metabolomic findings presented here can be useful to further elucidate the biological aspects that lead to HNSCC, and also provide a rational basis for monitoring molecular mechanisms in response to chemotherapy. Moreover, cPLA(2) may serve as a potential therapeutic target for anti-cancer therapy of HNSCC.

HR-MAS NMR tissue metabolomic signatures cross-validated by mass spectrometry distinguish bladder cancer from benign disease.

Effective diagnosis and surveillance of bladder cancer (BCa) is currently challenged by detection methods that are of poor sensitivity, particularly for low-grade tumors, resulting in unnecessary invasive procedures and economic burden. We performed HR-MAS NMR-based global metabolomic profiling and applied unsupervised principal component analysis (PCA) and hierarchical clustering performed on NMR data set of bladder-derived tissues and identified metabolic signatures that differentiate BCa from benign disease. A partial least-squares discriminant analysis (PLS-DA) model (leave-one-out cross-validation) was used as a diagnostic model to distinguish benign and BCa tissues. Receiver operating characteristic curve generated either from PC1 loadings of PCA or from predicted Y-values resulted in an area under curve of 0.97. Relative quantification of more than 15 tissue metabolites derived from HR-MAS NMR showed significant differences (P < 0.001) between benign and BCa samples. Noticeably, striking metabolic signatures were observed even for early stage BCa tissues (Ta-T1), demonstrating the sensitivity in detecting BCa. With the goal of cross-validating metabolic signatures derived from HR-MAS NMR, we utilized the same tissue samples to analyze 8 metabolites through gas chromatography-mass spectrometry (GC-MS)-targeted analysis, which undoubtedly complements HR-MAS NMR-derived metabolomic information. Cross-validation through GC-MS clearly demonstrates the utility of a straightforward, nondestructive, and rapid HR-MAS NMR technique for clinical diagnosis of BCa with even greater sensitivity. In addition to its utility as a diagnostic tool, these studies will lead to a better understanding of aberrant metabolic pathways in cancer as well as the design and implementation of personalized cancer therapy through metabolic modulation.

18F-Choline PET/MRI: The Additional Value of PET for MRI-Guided Transrectal Prostate Biopsies

We assessed the value of fusion 18F-fluoromethylcholine (18F-choline) PET/MRI for image-guided (targeted) prostate biopsies to detect significant prostate cancer (Gleason ≥ 3 + 4) compared with standard (systematic 12-core) biopsies. Methods: Within an ongoing prospective clinical trial, hybrid 18F-choline PET/CT and multiparametric 3T MRI (mpMRI) of the pelvis were performed in 36 subjects with a rising prostate-specific antigen for known (n = 15) or suspected (n = 21) prostate cancer before a prostate biopsy procedure. PET and T2-weighted MR volumes of the prostate were spatially registered using commercially available software. Biopsy targets were selected on the basis of visual appearance on MRI and graded as low, intermediate, or high risk for significant disease. Volumes of interest were defined for MR-identified lesions. 18F-choline uptake measures were obtained from the MR target and a mirrored background volume of interest. The biopsy procedure was performed after registration of real-time transrectal ultrasound with T2-weighted MR and included image-guided cores plus standard cores. Histologic results were determined from standard and targeted biopsy cores as well as prostatectomy specimens (n = 10). Results: Fifteen subjects were ultimately identified with Gleason ≥ 3 + 4 prostate cancer, of which targeted biopsy identified significantly more (n = 12) than standard biopsies (n = 5; P = 0.002). A total of 52 lesions were identified by mpMRI (19 low, 18 intermediate, 15 high risk), and mpMRI-assigned risk was a strong predictor of final pathology (area under the curve = 0.81; P < 0.001). When the mean 18F-choline target-to-background ratio was used, the addition of 18F-choline to mpMRI significantly improved the prediction of Gleason ≥ 3 + 4 cancers over mpMRI alone (area under the curve = 0.92; P < 0.001). Conclusion: Fusion PET/MRI transrectal ultrasound image registration for targeted prostate biopsies is clinically feasible and accurate. The addition of 18F-choline PET to mpMRI improves the identification of significant prostate cancer.

MetaboID: a graphical user interface package for assignment of 1H NMR spectra of bodyfluids and tissues.

Nuclear magnetic resonance based measurements of small molecule mixtures continues to be confronted with the challenge of spectral assignment. While multi-dimensional experiments are capable of addressing this challenge, the imposed time constraint becomes prohibitive, particularly with the large sample sets commonly encountered in metabolomic studies. Thus, one-dimensional spectral assignment is routinely performed, guided by two-dimensional experiments on a selected sample subset; however, a publicly available graphical interface for aiding in this process is currently unavailable. We have collected spectral information for 360 unique compounds from publicly available databases including chemical shift lists and authentic full resolution spectra, supplemented with spectral information for 25 compounds collected in-house at a proton NMR frequency of 900 MHz. This library serves as the basis for MetaboID, a Matlab-based user interface designed to aid in the one-dimensional spectral assignment process. The tools of MetaboID were built to guide resonance assignment in order of increasing confidence, starting from cursory compound searches based on chemical shift positions to analysis of authentic spike experiments. Together, these tools streamline the often repetitive task of spectral assignment. The overarching goal of the integrated toolbox of MetaboID is to centralize the one dimensional spectral assignment process, from providing access to large chemical shift libraries to providing a straightforward, intuitive means of spectral comparison. Such a toolbox is expected to be attractive to both experienced and new metabolomic researchers as well as general complex mixture analysts.

Re: Florian Jentzmik, Carsten Stephan, Kurt Miller, et al. Sarcosine in Urine after Digital Rectal Examination Fails as a Marker in Prostate Cancer Detection and Identification of Aggressive Tumours. Eur Urol 2010;58:12–8

In the paper published by Jentzmik et al. [1], the authors address the importance of urine-derived sarcosine based on public interest in our report [2], which describes elevated levels of the metabolite in urine of biopsy-proven prostate cancer (PCa) patients. We found especially elevated sarcosine levels in tumor specimens from patients with metastatic PCa, compared with organ-confined tumors. In their paper [1], the authors have examined urine supernatants collected after digital rectal examination (DRE) from 139 patients with prostate-specific antigen (PSA) levels between 2 and 20 ng/ml. These patients included 106 patients with PCa and 33 individuals with no evidence of malignancy (NEM), as assessed by biopsy. A total of 99 patients in this cohort had PSA levels between 0 and 10 ng/ml.

Lipidomic Signature of Progression of Chronic Kidney Disease in the Chronic Renal Insufficiency Cohort

Introduction Human studies report conflicting results on the predictive power of serum lipids on the progression of chronic kidney disease. We aimed to systematically identify the lipids that predict progression to end-stage kidney disease. Methods From the Chronic Renal Insufficiency Cohort, 79 patients with chronic kidney disease stages 2 to 3 who progressed to end-stage kidney disease over 6 years of follow-up were selected and frequency matched by age, sex, race, and diabetes with 121 nonprogressors with less than 25% decline in estimated glomerular filtration rate during the follow-up. The patients were randomly divided into training and test sets. We applied liquid chromatography-mass spectrometry-based lipidomics on visit year 1 samples. Results We identified 510 lipids, of which the top 10 coincided with false discovery threshold of 0.058 in the training set. From the top 10 lipids, the abundance of diacylglycerols and cholesteryl esters was lower, but that of phosphatidic acid 44:4 and monoacylglycerol 16:0 was significantly higher in progressors. Using logistic regression models, a multimarker panel consisting of diacylglycerols and monoacylglycerol independently predicted progression. The c-statistic of the multimarker panel added to the base model consisting of estimated glomerular filtration rate and urine protein-to-creatinine ratio as compared with that of the base model was 0.92 (95% confidence interval: 0.88–0.97) and 0.83 (95% confidence interval: 0.76–0.90, P < 0.01), respectively, an observation that was validated in the test subset. Discussion We conclude that a distinct panel of lipids may improve prediction of progression of chronic kidney disease beyond estimated glomerular filtration rate and urine protein-to-creatinine ratio when added to the base model.

Impaired β-Oxidation and Altered Complex Lipid Fatty Acid Partitioning with Advancing CKD

Studies of lipids in CKD, including ESRD, have been limited to measures of conventional lipid profiles. We aimed to systematically identify 17 different lipid classes and associate the abundance thereof with alterations in acylcarnitines, a metric of β-oxidation, across stages of CKD. From the Clinical Phenotyping Resource and Biobank Core (CPROBE) cohort of 1235 adults, we selected a panel of 214 participants: 36 with stage 1 or 2 CKD, 99 with stage 3 CKD, 61 with stage 4 CKD, and 18 with stage 5 CKD. Among participants, 110 were men (51.4%), 64 were black (29.9%), and 150 were white (70.1%), and the mean (SD) age was 60 (16) years old. We measured plasma lipids and acylcarnitines using liquid chromatography-mass spectrometry. Overall, we identified 330 different lipids across 17 different classes. Compared with earlier stages, stage 5 CKD associated with a higher abundance of saturated C16-C20 free fatty acids (FFAs) and long polyunsaturated complex lipids. Long-chain-to-intermediate-chain acylcarnitine ratio, a marker of efficiency of β-oxidation, exhibited a graded decrease from stage 2 to 5 CKD (P<0.001). Additionally, multiple linear regression revealed that the long-chain-to-intermediate-chain acylcarnitine ratio inversely associated with polyunsaturated long complex lipid subclasses and the C16-C20 FFAs but directly associated with short complex lipids with fewer double bonds. We conclude that increased abundance of saturated C16-C20 FFAs coupled with impaired β-oxidation of FFAs and inverse partitioning into complex lipids may be mechanisms underpinning lipid metabolism changes that typify advancing CKD.