NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics

Kumar, Deepak; Gupta, Ashish; Mandhani, Anil; Sankhwar, Satya Narayan

doi:10.1002/pros.23198

Cited by 52 publications

(36 citation statements)

References 35 publications

(56 reference statements)

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“…Kumar et al conducted two metabolomics studies using NMR spectroscopy to identify diagnostic PCa biomarkers in serum [21,22]. Both studies lacked independent validation cohorts, but some results of the first report were replicated in their second study.…”

Section: Resultsmentioning

confidence: 99%

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Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Kdadra¹,

Höckner²,

Leung

et al. 2019

Diagnostics

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Prostate cancer (PCa) diagnosis with current biomarkers is difficult and often results in unnecessary invasive procedures as well as over-diagnosis and over-treatment, highlighting the need for novel biomarkers. The aim of this review is to provide a summary of available metabolomics PCa biomarkers, particularly for clinically significant disease. A systematic search was conducted on PubMed for publications from July 2008 to July 2018 in accordance with PRISMA guidelines to report biomarkers with respect to their application in PCa diagnosis, progression, aggressiveness, recurrence, and treatment response. The vast majority of studies report biomarkers with the ability to distinguish malignant from benign prostate tissue with a few studies investigating biomarkers associated with disease progression, treatment response or tumour recurrence. In general, these studies report high dimensional datasets and the number of analysed metabolites often significantly exceeded the number of available samples. Hence, observed multivariate differences between case and control samples in the datasets might potentially also be associated with pre-analytical, technical, statistical and confounding factors. Giving the technical and methodological hurdles, there are nevertheless a number of metabolites and pathways repeatedly reported across various technical approaches, cohorts and sample types that appear to play a predominant role in PCa tumour biology, progression and recurrence.

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Section: Resultsmentioning

confidence: 99%

“…In their second study [22], the same authors profiled 210 fasted serum samples obtained from 65 HC, 70 BPH patients and 75 PCa patients. In contrast to their previous study, proteins and lipoproteins were removed using centrifugal filtration prior to NMR analysis.…”

Section: Resultsmentioning

confidence: 99%

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Kdadra¹,

Höckner²,

Leung

et al. 2019

Diagnostics

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“…Increased dimethylsulfone was the NMR measured metabolite with highest discriminatory power (AUC 0.74); however, using a panel of NMR and MS metabolites provided the best classification. Further, Kumar et al demonstrated the possibility to separate PCa from healthy controls, and PCa from both BPH and healthy controls, by NMR analysis of filtered serum, with classification accuracies ranging from 82 to 94%. In their cohort, dimethylsulfone was not quantified and they detected increased levels of sarcosine in PCa patients compared with both BPH and healthy controls.…”

Section: Cancer Detection and Diagnosismentioning

confidence: 99%

NMR‐based metabolomics of biofluids in cancer

et al. 2018

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This review describes the current status of NMR-based metabolomics of biofluids with respect to cancer risk assessment, detection, disease characterization, prognosis, and treatment monitoring. While the metabolism of cancer cells is altered compared with that of non-proliferating cells, the metabolome of blood and urine reflects the entire organism. We conclude that many studies show impressive associations between biofluid metabolomics and cancer progression, but translation to clinical practice is currently hindered by lack of validation, difficulties in biological interpretation, and non-standardized analytical procedures.

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“…15 1 H-nuclear magnetic resonance (NMR)-based metabolic profiling of filtered serum revealed that alanine, sarcosine, creatinine, glycine and citrate were able to discriminate PCa from BPH, exhibiting a high accuracy (88.3%) to differentiate PCa from BPH. 16 Serum metabolites showed promising capacity of analyzing molecular composition, however, they are an expensive and complex technology, which may introduce challenges for clinical application. 17 Numerous methods and techniques have been applied in PCa detection, such as computed tomography (CT)/positron emission tomography (PET) by 18 F-choline 18 and gallium-68 PSMA ligand Glu-urea-Lys(Ahx)-HBED-CC, 19 biopsy 20 and PSA screen.…”

Section: Introductionmentioning

confidence: 99%

Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4–10 ng/mL

Chen

Rong

Shao

et al. 2017

IJN

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The surface-enhanced Raman spectroscopy (SERS) of blood serum was investigated to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) in males with a prostate-specific antigen level of 4–10 ng/mL, so as to reduce unnecessary biopsies. A total of 240 SERS spectra from blood serum were acquired from 40 PCa subjects and 40 BPH subjects who had all received prostate biopsies and were given a pathological diagnosis. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms, were used to analyze the spectra data of serum from patients in control (CTR), PCa and BPH groups; results offered a sensitivity of 97.5%, a specificity of 100.0%, a precision of 100.0% and an accuracy of 99.2% for CTR; a sensitivity of 90.0%, a specificity of 97.5%, a precision of 94.7% and an accuracy of 98.3% for BPH; a sensitivity of 95.0%, a specificity of 93.8%, a precision of 88.4% and an accuracy of 94.2% for PCa. Similarly, this technique can significantly differentiate low- and high-risk PCa with an accuracy of 92.3%, a specificity of 95% and a sensitivity of 89.5%. The results suggest that analyzing blood serum using SERS combined with PCA–LDA diagnostic algorithms is a promising clinical tool for PCa diagnosis and assessment.

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NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics

Cited by 52 publications

References 35 publications

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

NMR‐based metabolomics of biofluids in cancer

Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4–10 ng/mL

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NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics

Cited by 52 publications

References 35 publications

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

Metabolomics Biomarkers of Prostate Cancer: A Systematic Review

NMR‐based metabolomics of biofluids in cancer

Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4&ndash;10 ng/mL

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Product

Resources

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Surface-enhanced Raman spectroscopy of serum accurately detects prostate cancer in patients with prostate-specific antigen levels of 4–10 ng/mL