Intracellular Signaling in Malignant Lymphoma Cells

Stanford University, Stanford CA

Investigators

Linked publications & trials

Abstract

Changes in intracellular protein levels, subcellular localization, or activation state are considered to be reflective[unreadable] of a cell's capabilities or functions. Some of these events are relatively transitory - such as some phosphorylation[unreadable] of proteins in cell signaling cascades. Some of the relevant cell populations are so rare as to[unreadable] make their isolation for standard biochemical analysis nearly impossible. Remodeling of such cell signaling[unreadable] mechanisms drives tumor proliferation and suppresses apoptosis, contributing to tumor survival despite intense[unreadable] therapy regimens. Therefore, to understand how signaling networks are remodeled in hematological[unreadable] tumors there is a need to measure complex populations of immune system cells and phenotype them not[unreadable] only for their cell lineage status but also for their relative activation state.[unreadable] The central hypothesis of these studies is that patients whose tumors share similar mechanisms of proliferative[unreadable] and anti-apoptotic signaling will respond similarly to a defined tumor cell killing regimen. Underlying this[unreadable] idea is the additional hypothesis that heritable differences among tumors will detectably modify tumor cell[unreadable] signaling networks. A long range goal in this project is to develop a predictive model of FL clinical outcome[unreadable] based on molecular mechanisms of signaling detected in heterogeneous tumor cell populations. In addressing[unreadable] this goal, we will a) construct a signaling taxonomy of FL, b) delineate remodeled signaling mechanisms[unreadable] in FL tumor cells, and c) correlate profiles of signaling in lymphoma with both heritable changes in tumors[unreadable] and clinical measures of disease aggressiveness. We will also test the hypothesis that cell by cell enumeration[unreadable] of signaling mechanisms will reveal the nature of the tumor - host interaction and distinguish tumor cell[unreadable] subsets whose presence and signaling state correlate with disease outcome.