The Diverse Genomic Landscape of Clinically Low-risk Prostate Cancer.

Background: Among men with clinically low-risk prostate cancer, we have previously documented heterogeneity in terms of clinical characteristics and genomic risk scores.

Objective: To further study the underlying tumor biology of this patient population, by interrogating broader patterns of gene expression among men with clinically low-risk tumors.

Design, Setting, And Participants: Prostate biopsies from 427 patients considered potentially suitable for active surveillance underwent central pathology review and genome-wide expression profiling.

Development and Validation of a Novel Integrated Clinical-Genomic Risk Group Classification for Localized Prostate Cancer.

Purpose It is clinically challenging to integrate genomic-classifier results that report a numeric risk of recurrence into treatment recommendations for localized prostate cancer, which are founded in the framework of risk groups. We aimed to develop a novel clinical-genomic risk grouping system that can readily be incorporated into treatment guidelines for localized prostate cancer. Materials and Methods Two multicenter cohorts (n = 991) were used for training and validation of the clinical-genomic risk groups, and two additional cohorts (n = 5,937) were used for reclassification analyses.

Ability of a Genomic Classifier to Predict Metastasis and Prostate Cancer-specific Mortality after Radiation or Surgery based on Needle Biopsy Specimens.

Background: Decipher is a validated genomic classifier developed to determine the biological potential for metastasis after radical prostatectomy (RP).

Objective: To evaluate the ability of biopsy Decipher to predict metastasis and Prostate cancer-specific mortality (PCSM) in primarily intermediate- to high-risk patients treated with RP or radiation therapy (RT).

Design, Setting, And Participants: Two hundred and thirty-five patients treated with either RP (n=105) or RT±androgen deprivation therapy (n=130) with available genomic expression profiles generated from diagnostic biopsy specimens from seven tertiary referral centers.

Gene expression profiling-based prediction of response of colon carcinoma cells to 5-fluorouracil and camptothecin.

5-Fluorouracil (5-FU) is the most common chemotherapeutic agent used in the treatment of colorectal cancer, yet objective response rates are low. Recently, camptothecin (CPT) has emerged as an effective alternative therapy. Decisive means to determine treatment, based on the likelihood of response to each of these agents, could greatly enhance the management of this disease.

Application of gene expression profiling to colon cell maturation, transformation and chemoprevention.

Methods for high-throughput analysis of profiles of gene expression that assay thousands of genes simultaneously are powerful approaches for understanding and classifying cell and tissue phenotype. This includes analysis of normal pathways of cell maturation and their perturbation in transformation, the sensitivity and mechanism of response of normal and tumor cells to physiological and pharmacological agents, and modulation of tumor risk and progression by nutritional factors. However, the complex data generated by such approaches raise difficulties in analysis.

A gene expression profile that defines colon cell maturation in vitro.

Colonic epithelial cells undergo cell cycle arrest, lineage specific differentiation, and apoptosis, as they migrate along the crypt axis toward the lumenal surface. The Caco-2 colon carcinoma cell line models many of these phenotypic changes, in vitro. We used this model system and cDNA microarray analysis to characterize the genetic reprogramming that accompanies colon cell differentiation.