Characterizing Prostate Cancer By ex vivo MRS Signatures

Massachusetts General Hospital, Boston MA

Investigators

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Abstract

DESCRIPTION (provided by applicant): Serum prostate specific antigen testing improved early detection of prostate tumors, increased diagnosed prostate cancer (PCa) incidence, and shifted newly detected PCa treatment to earlier stages. These successes also generated controversies for effective management of earlier-stage PCa, chiefly: (1) the all-too-common false-negative biopsy finding through tissue sampling errors in asymptomatic patients who harbor small, heterogeneously distributed PCa; and (2) the uncertain malignant potential of most newly detected tumors, with PCa pathologies similar at biopsy but which PCa statistics indicate will trace drastically different disease paths. Greater sensitivity/specificity for PCa diagnostic and prognostic approaches would address both these urgent needs. Our original R01 studies used high resolution magic-angle-spinning proton magnetic resonance spectroscopy (HRMAS 1HMRS), which we developed to permit intact tissue analysis and correlation with pathology, in order to produce proof-of-concept PCa metabolic markers. We then developed PCa metabolomics and demonstrated that PCa metabolomic profiles improve accuracy in PCa detection, diagnosis, and characterization. Profile analyses of histologically-defined benign prostate tissue from PCa patients allowed us to identify PCa pathological stage and predict PCa recurrence by showing the existence of delocalized PCa metabolomic field-effects, or metabolomic fields. These PCa metabolomic fields: 1) yield measures of PCa signatures in histo-benign tissue and thus are likely to reduce histological sampling errors by indicating PCa presence for patients with false-negatives biopsies, and 2) have the capacity to predict PCa malignant potential for patients with positive biopsies. Thus PCa metabolomic fields are likely to contribute most significantly to the PCa clinic by distinguishing aggressive from indolent disease and informing treatment strategies through markers that support active surveillance for indolent tumors or suggest that the patient harbors an aggressive PCa and needs timely institution of adjuvant therapies. These significant outcomes from our original R01 studies comprise the basis for our renewal application, in which we propose: (1) to systematically investigate spatial distributions of PCa metabolites and metabolomic profiles localized at and delocalized beyond their pathological origins in PCa glands to precisely define PCa metabolomic field markers; (2) to use banked PCa tissue samples with known clinical outcomes to test PCa metabolomic profile predictions of PCa growth rate and biochemical recurrence and therapy response, as well as to analyze different pathological components associated with genetic profiles from these same samples via laser capture microdissection and real-time quantitative PCR; and (3) to establish, through longitudinal patient follow-up, the prognostic ability of PCa metabolites, metabolomic profiles, and metabolomic fields as metabolomic criteria that answer the ultimate challenges of the current PCa clinic by predicting PCa risk for biopsy-negative patients and the suitability of entering active surveillance for biopsy-positive patients.