Dataset Information

Metabolomic Prediction of Human Prostate Cancer Aggressiveness: Magnetic Resonance Spectroscopy of Histologically Benign Tissue.

ABSTRACT: 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.

SUBMITTER: Vandergrift LA

PROVIDER: S-EPMC5980000 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Metabolomic Prediction of Human Prostate Cancer Aggressiveness: Magnetic Resonance Spectroscopy of Histologically Benign Tissue.

Vandergrift Lindsey A LA Decelle Emily A EA Kurth Johannes J Wu Shulin S Fuss Taylor L TL DeFeo Elita M EM Halpern Elkan F EF Taupitz Matthias M McDougal W Scott WS Olumi Aria F AF Wu Chin-Lee CL Cheng Leo L LL

Scientific reports 20180326 1

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 ca ...[more]

PMID: 29581441

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Project description: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.

Project description:Medulloblastoma (MB) is the most common malignant brain tumor occurring in childhood and rarely found in adult. Based on transcriptome profile MB are currently classified into four major molecular groups reflecting a considerable biological heterogeneity: WNT-activated, SHH-activated, group 3 and group 4. Recently, DNA methylation profiling allowed the identification of additional subgroups within the four major molecular groups associated with different clinic-pathological and molecular features. Isocitrate Dehydrogenase-1 (IDH1) mutations have been described in several tumours, including gliomas, while in MB are exceptionally reported and not routinely investigated. By mean of magnetic resonance spectroscopy (MRS) we unequivocally assessed the presence the oncometabolite D-2-Hydroxyglutarate (2HG), a marker of IDH1 and IDH2 mutation, in a case of adult MB. Immunophenotypical work-up and methylation profiling assigned the diagnosis of MB, subclass SHH-A, and molecular testing revealed the presence of the non-canonical somatic IDH1(p.R132C) mutation and an additional GNAS mutation, also exceptionally described in MB. To our knowledge this is the first reported case of MB harboring both mutations together. Of note, tumour exhibited a heterogeneous phenotype with a tumour component displaying glial differentiation, with robust GFAP expression, and a component with conventional MB features and selective presence of GNAS mutation, suggesting coexistence of two different major tumour clones. These findings draw attention to the need of a deeper genetic characterization of MB in order to get insights into their biology and improve stratification and clinical management of the patients. Moreover, reported data underling the importance of performing MRS for the identification of IDH mutations in non-glial tumours. The use of throughput molecular profiling analysis and advanced medical imaging technology will certainly increase the frequency with which rare tumour entities will be identified. Whether they have any particular therapeutic implications or prognostic relevance requires further investigations.

Dataset Information

Metabolomic Prediction of Human Prostate Cancer Aggressiveness: Magnetic Resonance Spectroscopy of Histologically Benign Tissue.

Publications

Metabolomic Prediction of Human Prostate Cancer Aggressiveness: Magnetic Resonance Spectroscopy of Histologically Benign Tissue.

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