(HealthDay News) — Subnetworks of interacting genes can predict the risk of disease progression requiring treatment in patients with chronic lymphocytic leukemia.
Han-Yu Chuang, PhD, from the University of California San Diego in La Jolla, and colleagues performed a subnetwork-based analysis of gene expression profiles to determine the risk of disease progression in 130 patients with chronic lymphocytic leukemia.
The researchers identified 38 prognostic subnetworks that predicted the likelihood of disease progression requiring treatment from the date the sample was collected; this prediction was then validated in two independent groups. The prognostic subnetworks were found to be more accurate than established markers. For patients classified at diagnosis as having aggressive disease there was reduced divergence in gene expression over time, compared to those with indolent disease. Levels of expression varied over time, but increased similarity was noted at later time points before therapy.
“As such, these results have implications for understanding cancer evolution and for the development of novel treatment strategies for patients with chronic lymphocytic leukemia,” Chuang and colleagues conclude.
Two authors were partially supported by grants from Pfizer and Agilent Labs. One author is an employee of Roche Molecular Systems and another is an employee of MLL Münchner Leukämielabor.