Reverse engineering of transcriptional networks using gene expression data enables identification of genes that underpin the development and progression of different cancers. Methods to this end have been available for over a decade and, with a critical mass of transcriptomic data in the oncology arena having been reached, they are ever more applicable. Extensive and complex networks can be distilled into a small set of key master transcriptional regulators (MTR), genes that are very highly connected and have been shown to be involved in processes of known importance in disease. Interpreting and validating the results of standardized bioinformatic methods is of crucial importance in determining the inherent value of MTRs. In this review, we briefly describe how MTRs are identified and focus on providing an overview of how MTRs can and have been validated for use in clinical decision making in malignant diseases, along with serving as tractable therapeutic targets. Cancer Res; 77(9); 2186–90. ©2017 AACR.
from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2plRvmL
via IFTTT
Εγγραφή σε:
Σχόλια ανάρτησης (Atom)
Δημοφιλείς αναρτήσεις
-
Purpose: The MHC-unrestricted activity of cytokine-induced killer (CIK) cells against chemo-surviving melanoma cancer stem cells (mCSC) was...
-
Induced overexpression of CD44 associated with resistance to apoptosis on DNA damage response in human head and neck squamous cell carc...
-
Abstract This paper addresses the hybrid consensus-based formation keeping problem for nonholonomic mobile robots in the presence of a nov...
Δεν υπάρχουν σχόλια:
Δημοσίευση σχολίου