RESUMO
BACKGROUND: Renal cell carcinoma (RCC) is a metabolic disease, with subtypes exhibiting aberrations in different metabolic pathways. Metabolomics may offer greater sensitivity for revealing disease biology. We investigated the metabolomic profile of RCC using high-resolution magic angle spinning (HRMAS) proton magnetic resonance spectroscopy (1HMRS). METHODS: Surgical tissue samples were obtained from our frozen tissue bank, collected from radical or partial nephrectomy. Specimens were fresh-frozen, then stored at -80 °C until analysis. Tissue HRMAS-1HMRS was performed. A MatLab-based curve fitting program was used to process the spectra to produce relative intensities for 59 spectral regions of interest (ROIs). Comparisons of the metabolomic profiles of various RCC histologies and benign tumors, angiomyolipoma, and oncocytoma, were performed. False discovery rates (FDR) were used from the response screening to account for multiple testing; ROIs with FDR p < 0.05 were considered potential predictors of RCC. Wilcoxon rank sum test was used to compare median 1HMRS relative intensities for those metabolites that may differentiate between RCC and benign tumor. Logistic regression determined odds ratios for risk of malignancy based on the abundance of each metabolite. RESULTS: Thirty-eight RCC (16 clear cell, 11 papillary, 11 chromophobe), 10 oncocytomas, 7 angiomyolipomas, and 13 adjacent normal tissue specimens (matched pairs) were analyzed. Candidate metabolites for predictors of malignancy based on FDR p-values include histidine, phenylalanine, phosphocholine, serine, phosphocreatine, creatine, glycerophosphocholine, valine, glycine, myo-inositol, scyllo-inositol, taurine, glutamine, spermine, acetoacetate, and lactate. Higher levels of spermine, histidine, and phenylalanine at 3.15 to 3.13 parts per million (ppm) were associated with decreased risk of RCC (OR 4â¯×â¯10-5, 95% CI 7.42â¯×â¯10-8, 0.02), while 2.84 to 2.82 ppm increased the risk of malignant pathology (OR 7158.67, 95% CI 6.3, 8.3â¯×â¯106). The specific metabolites characterizing this region remain to be identified. Tumor stage did not affect metabolomic profile of malignant tumors, suggesting that metabolites are dependent on histologic subtype. CONCLUSIONS: HRMAS-1HMRS identified metabolites that may predict RCC. We demonstrated that those in the 3.14 to 3.13 ppm ROI were present in lower levels in RCC, while higher levels of metabolites in the 2.84 to 2.82 ppm ROI were associated with substantially increased risk of RCC. Further research in a larger population is required to validate these findings.
Assuntos
Carcinoma de Células Renais , Neoplasias Renais , Humanos , Carcinoma de Células Renais/diagnóstico , Carcinoma de Células Renais/patologia , Espectroscopia de Prótons por Ressonância Magnética , Histidina , Espermina , Espectroscopia de Ressonância Magnética/métodos , Neoplasias Renais/patologia , FenilalaninaRESUMO
Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. For its detection, serum prostate-specific antigen (PSA) screening is commonly used, despite its lack of specificity, high false positive rate, and inability to discriminate indolent from aggressive PCa. Following increases in serum PSA levels, clinicians often conduct prostate biopsies with or without advanced imaging. Nuclear magnetic resonance (NMR)-based metabolomics has proven to be promising for advancing early-detection and elucidation of disease progression, through the discovery and characterization of novel biomarkers. This retrospective study of urine-NMR samples, from prostate biopsy patients with and without PCa, identified several metabolites involved in energy metabolism, amino acid metabolism, and the hippuric acid pathway. Of note, lactate and hippurate-key metabolites involved in cellular proliferation and microbiome effects, respectively-were significantly altered, unveiling widespread metabolomic modifications associated with PCa development. These findings support urine metabolomics profiling as a promising strategy to identify new clinical biomarkers for PCa detection and diagnosis.
Assuntos
Antígeno Prostático Específico , Neoplasias da Próstata , Masculino , Humanos , Estudos Retrospectivos , Biomarcadores Tumorais , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/metabolismo , Neoplasias da Próstata/patologia , Espectroscopia de Ressonância Magnética , Metabolômica/métodosRESUMO
Currently, many prostate cancer patients, detected through the prostate specific antigen test, harbor organ-confined indolent disease that cannot be differentiated from aggressive cancer according to clinically and pathologically known measures. Spermine has been considered as an endogenous inhibitor for prostate-confined cancer growth and its expression has shown correlation with prostate cancer growth rates. If established clinically, measurements of spermine bio-synthesis rates in prostates may predict prostate cancer growth and patient outcomes. Using rat models, we tested the feasibility of quantifying spermine bio-synthesis rates with 13 C NMR. Male Copenhagen rats (10 weeks, n = 6) were injected with uniformly 13 C-labeled L-ornithine HCl, and were sacrificed in pairs at 10, 30, and 60 min after injection. Another two rats were injected with saline and sacrificed at 30 min as controls. Prostates were harvested and extracted with perchloric acid and the neutralized solutions were examined by 13 C NMR at 600 MHz. 13 C NMR revealed measurable ornithine, as well as putrescine-spermidine-spermine syntheses in rat prostates, allowing polyamine bio-synthetic and ornithine bio-catabolic rates to be calculated. Our study demonstrated the feasibility of 13 C NMR for measuring bio-synthesis rates of ornithine to spermine enzymatic reactions in rat prostates. The current study established a foundation upon which future investigations of protocols that differentiate prostate cancer growth rates according to the measure of ornithine to spermine bio-synthetic rates may be developed.
Assuntos
Neoplasias da Próstata , Espermina , Masculino , Ratos , Animais , Humanos , Espermina/metabolismo , Próstata , Poliaminas/metabolismo , Ornitina/metabolismo , Ornitina/farmacologiaRESUMO
PURPOSE: Recent research identified histone H3 K27M mutations to be associated with a dismal prognosis in pediatric diffuse midline glioma (pDMG); however, data on detailed MRI characteristics with respect to H3 K27 mutation status and molecular subgroups (H3.1 and H3.3 K27M mutations) are limited. METHODS: Standardized magnetic resonance imaging (MRI) parameters and epidemiologic data of 68 pDMG patients (age <18 years) were retrospectively reviewed and compared in a) H3 K27M mutant versus H3 K27 wildtype (WT) tumors and b) H3.1 versus H3.3 K27M mutant tumors. RESULTS: Intracranial gliomas (nâ¯= 58) showed heterogeneous phenotypes with isointense to hyperintense signal in T2-weighted images and frequent contrast enhancement. Hemorrhage and necrosis may be present. Comparing H3 K27M mutant to WT tumors, there were significant differences in the following parameters: i) tumor localization (pâ¯= 0.001), ii) T2 signal intensity (pâ¯= 0.021), and iii) T1 signal homogeneity (pâ¯= 0.02). No significant imaging differences were found in any parameter between H3.1 and H3.3 K27M mutant tumors; however, H3.1 mutant tumors occurred at a younger age (pâ¯= 0.004). Considering spinal gliomas (nâ¯= 10) there were no significant imaging differences between the analyzed molecular groups. CONCLUSION: With this study, we are the first to provide detailed MR imaging data on H3 K27M mutant pDMG with respect to molecular subgroup status in a large patient cohort. Our findings may support diagnosis and future targeted therapeutic trials of pDMG within the framework of the radiogenomics concept.
Assuntos
Neoplasias Encefálicas , Glioma , Adolescente , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/patologia , Criança , Glioma/diagnóstico por imagem , Glioma/genética , Glioma/patologia , Histonas/genética , Humanos , Imageamento por Ressonância Magnética , Estudos RetrospectivosRESUMO
The current high mortality of human lung cancer stems largely from the lack of feasible, early disease detection tools. An effective test with serum metabolomics predictive models able to suggest patients harboring disease could expedite triage patient to specialized imaging assessment. Here, using a training-validation-testing-cohort design, we establish our high-resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS)-based metabolomics predictive models to indicate lung cancer presence and patient survival using serum samples collected prior to their disease diagnoses. Studied serum samples were collected from 79 patients before (within 5.0 y) and at lung cancer diagnosis. Disease predictive models were established by comparing serum metabolomic patterns between our training cohorts: patients with lung cancer at time of diagnosis, and matched healthy controls. These predictive models were then applied to evaluate serum samples of our validation and testing cohorts, all collected from patients before their lung cancer diagnosis. Our study found that the predictive model yielded values for prior-to-detection serum samples to be intermediate between values for patients at time of diagnosis and for healthy controls; these intermediate values significantly differed from both groups, with an F1 score = 0.628 for cancer prediction. Furthermore, values from metabolomics predictive model measured from prior-to-diagnosis sera could significantly predict 5-y survival for patients with localized disease.
Assuntos
Detecção Precoce de Câncer/métodos , Neoplasias Pulmonares/diagnóstico , Espectroscopia de Ressonância Magnética , Metabolômica , Idoso , Feminino , Humanos , Neoplasias Pulmonares/sangue , Neoplasias Pulmonares/metabolismo , Masculino , Redes e Vias Metabólicas , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Reprodutibilidade dos TestesRESUMO
Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum.
Assuntos
Biomarcadores/sangue , Neoplasias Pulmonares/mortalidade , Neoplasias Pulmonares/patologia , Metabolômica/métodos , Idoso , Feminino , Glutamina/sangue , Glicina/sangue , Humanos , Neoplasias Pulmonares/metabolismo , Espectroscopia de Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Análise de Sobrevida , Valina/sangueRESUMO
Urinary tests have been used as noninvasive, cost-effective tools for screening, diagnosis and monitoring of diseases since ancient times. As we progress through the 21st century, modern analytical platforms have enabled effective measurement of metabolites, with promising results for both a deeper understanding of cancer pathophysiology and, ultimately, clinical translation. The first study to measure metabolomic urinary cancer biomarkers using NMR and mass spectrometry (MS) was published in 2006 and, since then, these techniques have been used to detect cancers of the urological system (kidney, prostate and bladder) and nonurological tumours including those of the breast, ovary, lung, liver, gastrointestinal tract, pancreas, bone and blood. This growing field warrants an assessment of the current status of research developments and recommendations to help systematize future research.
Assuntos
Biomarcadores Tumorais/urina , Metaboloma , Neoplasias/urina , Detecção Precoce de Câncer/métodos , Humanos , Neoplasias Hepáticas/diagnóstico , Neoplasias Hepáticas/metabolismo , Neoplasias Hepáticas/urina , Masculino , Metabolômica/métodos , Neoplasias/diagnóstico , Neoplasias/metabolismo , Guias de Prática Clínica como Assunto , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/metabolismo , Neoplasias da Próstata/urina , Neoplasias Urológicas/diagnóstico , Neoplasias Urológicas/metabolismo , Neoplasias Urológicas/urinaRESUMO
In this article, we review the state of the field of high resolution magic angle spinning MRS (HRMAS MRS)-based cancer metabolomics since its beginning in 2004; discuss the concept of cancer metabolomic fields, where metabolomic profiles measured from histologically benign tissues reflect patient cancer status; and report our HRMAS MRS metabolomic results, which characterize metabolomic fields in prostatectomy-removed cancerous prostates. Three-dimensional mapping of cancer lesions throughout each prostate enabled multiple benign tissue samples per organ to be classified based on distance from and extent of the closest cancer lesion as well as the Gleason score (GS) of the entire prostate. Cross-validated partial least squares-discriminant analysis separations were achieved between cancer and benign tissue, and between cancer tissue from prostates with high (≥4 + 3) and low (≤3 + 4) GS. Metabolomic field effects enabled histologically benign tissue adjacent to cancer to distinguish the GS and extent of the cancer lesion itself. Benign samples close to either low GS cancer or extensive cancer lesions could be distinguished from those far from cancer. Furthermore, a successfully cross-validated multivariate model for three benign tissue groups with varying distances from cancer lesions within one prostate indicates the scale of prostate cancer metabolomic fields. While these findings could, at present, be potentially useful in the prostate cancer clinic for analysis of biopsy or surgical specimens to complement current diagnostics, the confirmation of metabolomic fields should encourage further examination of cancer fields and can also enhance understanding of the metabolomic characteristics of cancer in myriad organ systems. Our results together with the success of HRMAS MRS-based cancer metabolomics presented in our literature review demonstrate the potential of cancer metabolomics to provide supplementary information for cancer diagnosis, staging, and patient prognostication.
Assuntos
Espectroscopia de Ressonância Magnética , Metabolômica , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/metabolismo , Idoso , Análise Discriminante , Humanos , Análise dos Mínimos Quadrados , Masculino , Pessoa de Meia-Idade , Gradação de Tumores , Análise de Componente Principal , Neoplasias da Próstata/patologia , Curva ROCRESUMO
PURPOSE: Epigenetic profiling has recently identified clinically and molecularly distinct subgroups of ependymoma. The 2016 World Health Organization (WHO) classification recognized supratentorial ependymomas (ST-EPN) with REL-associated protein/p65 (RELA) fusion as a clinicopathological entity. These tumors represent 70% of pediatric ST-EPN characterized by recurrent C11orf95-RELA fusion transcripts, which lead to pathological activation of the nuclear factor 'kappa-light-chain-enhancer' of activated B-cells (NF-κB) signaling pathway. Cyclin-dependent kinase inhibitor 2A (CDKN2A) inactivation has also been reported to correlate with poor prognosis. Here, we systematically describe magnetic resonance imaging (MRI) characteristics of RELA-fused ST-EPN, with respect to CDKN2A deletion status. METHODS: Our cohort of patients with ST-EPN (nâ¯= 57) was obtained from the database of the German Brain Tumor Reference Center of the German Society for Neuropathology and Neuroanatomy (DGNN), and tumors were diagnosed according to the 2016 WHO classification. Molecular characterization identified 47 RELA-fused tumors. We analyzed the preoperative MRI according to standardized criteria, and comparison was performed between CDKN2A altered (nâ¯= 21) and CDKN2A wild type (nâ¯= 26) tumors. RESULTS: The RELA-fused ST-EPN showed a spectrum of predominantly hemispheric tumors with cysts and necrosis. Statistical analysis on CDKN2A status revealed significant differences in terms of younger manifestation age (pâ¯=0.002) and more intratumoral hemorrhage in T2-weighted imaging (T2WI) (pâ¯=0.010) in wild type tumors; however, the location was not a parameter for differentiation. CONCLUSION: This study first provides comprehensive MRI data for RELA-fused ST-EPN as a distinct entity, with further interest on CDKN2A genomic status. Patient stratification by morphological MRI alone seems difficult at present. The results may support ongoing research in ST-EPN within the framework of the radiogenomics concept.
Assuntos
Ependimoma/diagnóstico por imagem , Neoplasias Supratentoriais/diagnóstico por imagem , Fator de Transcrição RelA/metabolismo , Adolescente , Criança , Pré-Escolar , Bases de Dados Factuais , Ependimoma/genética , Ependimoma/metabolismo , Ependimoma/patologia , Feminino , Deleção de Genes , Genes p16 , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Masculino , Gradação de Tumores , Proteínas de Fusão Oncogênica/metabolismo , Fenótipo , Neoplasias Supratentoriais/genética , Neoplasias Supratentoriais/metabolismo , Neoplasias Supratentoriais/patologiaRESUMO
Background: Recently, 3 molecular subgroups of atypical teratoid/rhabdoid tumor (ATRT) were identified, but little is known of their clinical and magnetic resonance imaging (MRI) characteristics. Methods: A total of 43 patients with known molecular subgroup status (ATRT-sonic hedgehog [SHH], n = 17; ATRT-tyrosine [TYR], n = 16; ATRT-myelocytomatosis oncogene [MYC], n = 10) were retrieved from the EU-RHAB Registry and analyzed for clinical and MRI features. Results: On MRI review, differences in preferential tumor location were confirmed, with ATRT-TYR being predominantly located infratentorially (P < 0.05). Peritumoral edema was more pronounced in ATRT-MYC compared with ATRT-SHH (P < 0.05) and ATRT-TYR (P < 0.05). Conversely, peripheral tumor cysts were found more frequently in ATRT-SHH (71%) and ATRT-TYR (94%) compared with ATRT-MYC (40%, P < 0.05). Contrast enhancement was absent in 29% of ATRT-SHH (0% of ATRT-TYR; 10% of ATRT-MYC; P < 0.05), and there was a trend toward strong contrast enhancement in ATRT-TYR and ATRT-MYC. We found the characteristic (bandlike) enhancement in 28% of ATRT as well as restricted diffusion in the majority of tumors. A midline/off-midline location in the posterior fossa was also not subgroup specific. Visible meningeal spread (M2) at diagnosis was rare throughout all subgroups. Conclusion: These exploratory findings suggest that MRI features vary across the 3 molecular subgroups of ATRT. Within future prospective trials, MRI may aid diagnosis and treatment stratification.
Assuntos
Proteínas Hedgehog/genética , Imageamento por Ressonância Magnética/métodos , Proteínas Proto-Oncogênicas c-myc/genética , Tumor Rabdoide/diagnóstico , Teratoma/diagnóstico , Tirosina/metabolismo , Biomarcadores Tumorais/análise , Pré-Escolar , Diagnóstico Diferencial , Feminino , Seguimentos , Humanos , Masculino , Prognóstico , Estudos Retrospectivos , Tumor Rabdoide/genética , Tumor Rabdoide/metabolismo , Teratoma/genética , Teratoma/metabolismoRESUMO
Prostate cancer alters cellular metabolism through events potentially preceding cancer morphological formation. Magnetic resonance spectroscopy (MRS)-based metabolomics of histologically-benign tissues from cancerous prostates can predict disease aggressiveness, offering clinically-translatable prognostic information. This retrospective study of 185 patients (2002-2009) included prostate tissues from prostatectomies (n = 365), benign prostatic hyperplasia (BPH) (n = 15), and biopsy cores from cancer-negative patients (n = 14). Tissues were measured with high resolution magic angle spinning (HRMAS) MRS, followed by quantitative histology using the Prognostic Grade Group (PGG) system. Metabolic profiles, measured solely from 338 of 365 histologically-benign tissues from cancerous prostates and divided into training-testing cohorts, could identify tumor grade and stage, and predict recurrence. Specifically, metabolic profiles: (1) show elevated myo-inositol, an endogenous tumor suppressor and potential mechanistic therapy target, in patients with highly-aggressive cancer, (2) identify a patient sub-group with less aggressive prostate cancer to avoid overtreatment if analysed at biopsy; and (3) subdivide the clinicopathologically indivisible PGG2 group into two distinct Kaplan-Meier recurrence groups, thereby identifying patients more at-risk for recurrence. Such findings, achievable by biopsy or prostatectomy tissue measurement, could inform treatment strategies. Metabolomics information can help transform a morphology-based diagnostic system by invoking cancer biology to improve evaluation of histologically-benign tissues in cancer environments.
Assuntos
Espectroscopia de Ressonância Magnética/métodos , Metabolômica/métodos , Neoplasias da Próstata/diagnóstico por imagem , Neoplasias da Próstata/patologia , Adulto , Idoso , Análise de Variância , Biomarcadores Tumorais/sangue , Biópsia , Progressão da Doença , Seguimentos , Humanos , Calicreínas/sangue , Estimativa de Kaplan-Meier , Masculino , Metaboloma , Pessoa de Meia-Idade , Recidiva Local de Neoplasia , Antígeno Prostático Específico/sangue , Prostatectomia , Hiperplasia Prostática/patologia , Neoplasias da Próstata/sangue , Estudos Retrospectivos , Estatísticas não ParamétricasRESUMO
BACKGROUND: Prostate cancer (PCa), the most common cancer and second leading cause of cancer death in American men, presents the clinical challenge of distinguishing between indolent and aggressive tumors for proper treatment. PCa presents significant alterations in metabolic pathways that can potentially be measured using techniques like mass spectrometry (MS) or MS imaging (MSI) and used to characterize PCa aggressiveness. MS quantifies metabolomic, proteomic, and lipidomic profiles of biological systems that can be further visualized for their spatial distributions through MSI. METHODS: PubMed was queried for all publications relating to MS and MSI in human PCa from April 2007 to April 2017. With the goal of reviewing the utility of MSI in diagnosis and prognostication of human PCa, MSI articles that reported investigations of PCa-specific metabolites or metabolites indicating PCa aggressiveness were selected for inclusion. Articles were included that covered MS and MSI principles, limitations, and applications in PCa. RESULTS: We identified nine key studies on MSI in intact human prostate tissue specimens that determined metabolites which could either differentiate between benign and malignant prostate tissue or indicate PCa aggressiveness. These MSI-detected biomarkers show promise in reliably identifying PCa and determining disease aggressiveness. CONCLUSIONS: MSI represents an innovative technique with the ability to interrogate cancer biomarkers in relation to tissue pathologies and investigate tumor aggressiveness. We propose MSI as a powerful adjuvant histopathology imaging tool for prostate tissue evaluations, where clinical translation of this ex vivo technique could make possible the use of MSI for personalized medicine in diagnosis and prognosis of PCa. Moreover, the knowledge provided from this technique can majorly contribute to the understanding of molecular pathogenesis of PCa and other malignant diseases.
Assuntos
Biomarcadores Tumorais/análise , Imagem Molecular/métodos , Neoplasias da Próstata/diagnóstico , Espectrometria de Massas por Ionização por Electrospray/métodos , Espectrometria de Massas por Ionização e Dessorção a Laser Assistida por Matriz/métodos , Biópsia , Humanos , Masculino , Metabolômica/métodos , Próstata/patologia , Neoplasias da Próstata/metabolismo , Neoplasias da Próstata/patologia , Proteômica/métodosRESUMO
High-resolution magic angle spinning (HRMAS) MRS is a powerful method for gaining insight into the physiological and pathological processes of cellular metabolism. Given its ability to obtain high-resolution spectra of non-liquid biological samples, while preserving tissue architecture for subsequent histopathological analysis, the technique has become invaluable for biochemical and biomedical studies. Using HRMAS MRS, alterations in measured metabolites, metabolic ratios, and metabolomic profiles present the possibility to improve identification and prognostication of various diseases and decipher the metabolomic impact of drug therapies. In this review, we evaluate HRMAS MRS results on human tissue specimens from malignancies and non-localized diseases reported in the literature since the inception of the technique in 1996. We present the diverse applications of the technique in understanding pathological processes of different anatomical origins, correlations with in vivo imaging, effectiveness of therapies, and progress in the HRMAS methodology.