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Metabolomic Information Highly Useful for Predicting Future Prostate Cancer

Key findings

  • This study evaluated the diagnostic value of ex vivo nuclear magnetic resonance spectroscopy for detecting early prostate cancer by correlating metabolomic information with histopathology
  • Metabolite intensities and metabolomic profiles were significantly different between benign and malignant prostate tissue
  • Even more important, metabolomic information differentiated between samples of patients with histobenign prostate biopsies who received a prostate cancer diagnosis in the following years and those whose samples remained benign
  • The predictive power of metabolomic alterations in prostate biopsy samples could be very valuable for individualizing surveillance strategies and improving diagnostic and treatment strategies

A pressing challenge in prostate cancer (PCa) diagnostics is to precisely distinguish between highly aggressive and indolent tumors. High-resolution magic angle spinning (HRMAS) 1H nuclear magnetic resonance (NMR) spectroscopy has been investigated for this purpose, as tissue samples are spun at a 54.7° angle away from the direction of the spectrometer's static magnetic field, enabling ex vivo analysis at sufficient resolution.

Moreover, the tissue structure is preserved, allowing for subsequent histopathological and genetic evaluation of samples and, thus, analysis of correlations between tissue metabolites and pathology. The composition of the metabolome (the entirety of all measurable metabolites) changes dynamically as the body reacts to cancer, and specific metabolomic alterations are characteristic of malignant tumor cells.

Massachusetts General Hospital researchers observed metabolomic information differed substantially between patients with benign prostate biopsy samples, based on their risk for receiving a future PCa diagnosis. This suggests metabolomic information is highly valuable for early PCa detection and individualized surveillance. Leo Cheng, PhD, associate biophysicist in the Department of Pathology and the Department of Radiology, and colleagues report the findings in Cancers (Basel).

Methods

As part of a prospective study, the team obtained 441 prostate tissue samples from 351 patients at Mass General between April 2006 and October 2018. During each patient's biopsy, one or two additional tissue samples were taken for the study and scanned with HRMAS 1H NMR spectroscopy. Afterward, the samples were evaluated histopathologically.

Based on prespecified clinical and histopathological matching criteria, the researchers built three matched groups of 16 patients each:

  • Group 1—The NMR scanned biopsy was histobenign, but PCa was diagnosed before the end of the study period
  • Gr2—The biopsy was benign and the patient continued to be PCa-free
  • Gr3—The biopsy included cancer cells

Characterizing Samples

Peak intensity in several spectral regions significantly differentiated between benign, premalignant, and malignant tissue:

  • Region 23—Differentiation between Gr2 and Gr3. This region usually contains the signals of polyamines
  • Region 18—Differentiation between Gr2 and Gr1. Signals from the metabolites glycerophosphorylethanolamine (GPhE) and scyllo-inositol (SI) usually fall in this region. GPhE is involved in cell membrane metabolism, which is accelerated during carcinogenesis, and the same is thought to be true of SI. If GPhE and SI concentrations are already changed in the premalignant state of PCa, they could serve as indicators of early PCa development
  • Region 35—Differentiation between Gr1 and Gr3. This region usually contains the signal from glutamate, which tends to be elevated in PCa tissue. Thus, glutamate levels seem to change as early malignant alterations progress toward the formation of a more advanced solid tumor

Estimating Tumor Aggressiveness

Other study results suggested HRMAS 1H NMR spectroscopy might help to estimate tumor aggressiveness based on metabolic markers. The peak intensity in region 27 significantly differed between biopsy samples of patients whose highest Gleason score in the study period was 3+3=6 (low malignant) and those whose highest score was 3+4=7 (intermediate malignant). This finding has implications for surveillance and decisions about stage-adapted therapy.

Early PCa Detection

A principal components analysis of metabolites significantly differentiated Gr1, Gr2, and Gr3. This supports earlier research suggesting combinations of metabolite concentrations significantly differ between benign, premalignant, and malignant prostate tissue.

Furthermore, these metabolomic profiles seemed to be altered at a premalignant stage. They may be extremely valuable for identifying which patients with benign prostate samples are at high risk of future cancer development.

Looking Ahead

The predictive power of metabolomic risk profiles could help to individualize active surveillance strategies and improve PCa diagnostic and treatment strategies, contributing to a high level of personalized medicine. At present, high-resolution spectrometers aren't widely available, and the procedure is costly, but metabolomic information might someday supplement the current gold standard of histopathology.

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Related

Research conducted by Dr. Adam Feldman, Dr. Leo Cheng, and colleagues shows promising results for a non-invasive technique detecting metabolic signature between benign and cancerous prostate tissue.

Related

Douglas M. Dahl, MD, Chin-Lee Wu, MD, PhD, and colleagues found that in patients with smaller prostates (≤30 mL), transperineal multiparametric MRI-targeted biopsy alone does as well as the combination of targeted and conventional biopsy at detecting clinically significant cancer.