Improving prediction of prostate cancer recurrence using chemical imaging.

ABSTRACT: Precise Outcome prediction is crucial to providing optimal cancer care across the spectrum of solid cancers. Clinically-useful tools to predict risk of adverse events (metastases, recurrence), however, remain deficient. Here, we report an approach to predict the risk of prostate cancer recurrence, at the time of initial diagnosis, using a combination of emerging chemical imaging, a diagnostic protocol that focuses simultaneously on the tumor and its microenvironment, and data analysis of frequent patterns in molecular expression. Fourier transform infrared (FT-IR) spectroscopic imaging was employed to record the structure and molecular content from tumors prostatectomy. We analyzed data from a patient cohort that is mid-grade dominant - which is the largest cohort of patients in the modern

SUBMITTER: Kwak JT 

PROVIDER: S-EPMC4348620 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature