Nanotechnology Accurately Predicts Prostate Cancer and Prognosis

The prostate-specific antigen (PSA) test was once the recommended screening tool for detecting prostate cancer (PCa), but there is now disagreement over the use of this test because it cannot predict which men with elevated PSA levels will actually develop an aggressive form of the disease.

Scientists at the Northwestern University (Evanston, IL, USA) and their colleagues at the Boston University Medical Center (Boston, MA, USA) studied patients who underwent their first surveillance biopsy 6 to12 months after enrollment. Progression was defined as any change in criteria 3, 4, or 5. Thirty-eight patients were randomly chosen from the database of patients adjudicated as progressors and non-progressors by the chief study urologist. Transrectal biopsies were obtained under three-dimensional ultrasound guidance. Hematoxylin and eosin (H&E) sections were reviewed by the study pathologist to direct the partial wave spectroscopic microscopy (PWS) analysis towards non-malignant tissue.

The teams described PWS marker disorder strength (Ld) as proportional to the mean and standard deviation of the spatial variations of the macromolecular density of the fundamental cellular building blocks (proteins, nucleic acids, lipids). Thus, Ld, colloquially, can be described as measuring the “clumpiness” of nanoscale structure. The scientists demonstrated that PWS is sensitive to structures from 20 to 200 nm through the spectral analysis of the interference spectra of light reflected from intracellular refractive index variations within microscopic spatiotemporal coherence volume, as opposed to typical light microscopy whose resolution is restricted 200 to 500 nm, the diffraction limit of light.

There was a profound increase in nano-architectural disorder between progressors and non-progressors. The Ld from future progressors was dramatically increased when compared to future non-progressors: 1 ± 0.065 versus 1.30 ± 0.0614, respectively. The area under the receiver operator characteristic curve (AUC) was 0.79, yielding a sensitivity of 88% and specificity of 72% for discriminating between progressors and non-progressors. This was not confounded by demographic factors such as age, smoking status, race, obesity, thus supporting the robustness of the approach.

The authors concluded that nano-architectural alterations occur in prostate cancer field carcinogenesis and can be exploited to predict prognosis of early stage PCa. This approach has promise in addressing the clinically vexing dilemma of management of low grade Gleason score 6 PCa and may provide a paradigm for dealing with the larger issue of cancer overdiagnosis. The study was published on February 23, 2015, in the journal Public Library of Science ONE.

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Northwestern University 
Boston University Medical Center