Dataset Information

Defining key signaling nodes and therapeutic biomarkers in NF1-mutant cancers.

ABSTRACT: NF1 encodes a RAS GTPase-activating protein. Accordingly, aberrant RAS activation underlies the pathogenesis of NF1-mutant cancers. Nevertheless, it is unclear which RAS pathway components represent optimal therapeutic targets. Here, we identify mTORC1 as the key PI3K effector in NF1-mutant nervous system malignancies and conversely show that mTORC2 and AKT are dispensable. However, we find that tumor regression requires sustained inhibition of both mTORC1 and MEK. Transcriptional profiling studies were therefore used to establish a signature of effective mTORC1-MEK inhibition in vivo. We unexpectedly found that the glucose transporter GLUT1 was potently suppressed, but only when both pathways were inhibited. Moreover, unlike VHL- and LKB1-mutant cancers, reduction of (18)F-FDG uptake required the suppression of both mTORC1 and MEK. Together, these studies identify optimal and suboptimal therapeutic targets in NF1-mutant malignancies and define a noninvasive means of measuring combined mTORC1-MEK inhibition in vivo, which can be readily incorporated into clinical trials.This work demonstrates that mTORC1 and MEK are key therapeutic targets in NF1-mutant cancers and establishes a noninvasive biomarker of effective, combined target inhibition that can be evaluated in clinical trials.

SUBMITTER: Malone CF

PROVIDER: S-EPMC4446704 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Defining key signaling nodes and therapeutic biomarkers in NF1-mutant cancers.

Malone Clare F CF Fromm Jody A JA Maertens Ophélia O DeRaedt Thomas T Ingraham Rachel R Cichowski Karen K

Cancer discovery 20140609 9

<h4>Unlabelled</h4>NF1 encodes a RAS GTPase-activating protein. Accordingly, aberrant RAS activation underlies the pathogenesis of NF1-mutant cancers. Nevertheless, it is unclear which RAS pathway components represent optimal therapeutic targets. Here, we identify mTORC1 as the key PI3K effector in NF1-mutant nervous system malignancies and conversely show that mTORC2 and AKT are dispensable. However, we find that tumor regression requires sustained inhibition of both mTORC1 and MEK. Transcripti ...[more]

PMID: 24913553

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Project description:Network science holds great promise for expanding our understanding of the human brain in health, disease, development, and aging. Network analyses are quickly becoming the method of choice for analyzing functional MRI data. However, many technical issues have yet to be confronted in order to optimize results. One particular issue that remains controversial in functional brain network analyses is the definition of a network node. In functional brain networks a node represents some predefined collection of brain tissue, and an edge measures the functional connectivity between pairs of nodes. The characteristics of a node, chosen by the researcher, vary considerably in the literature. This manuscript reviews the current state of the art based on published manuscripts and highlights the strengths and weaknesses of three main methods for defining nodes. Voxel-wise networks are constructed by assigning a node to each, equally sized brain area (voxel). The fMRI time-series recorded from each voxel is then used to create the functional network. Anatomical methods utilize atlases to define the nodes based on brain structure. The fMRI time-series from all voxels within the anatomical area are averaged and subsequently used to generate the network. Functional activation methods rely on data from traditional fMRI activation studies, often from databases, to identify network nodes. Such methods identify the peaks or centers of mass from activation maps to determine the location of the nodes. Small (~10-20 millimeter diameter) spheres located at the coordinates of the activation foci are then applied to the data being used in the network analysis. The fMRI time-series from all voxels in the sphere are then averaged, and the resultant time series is used to generate the network. We attempt to clarify the discussion and move the study of complex brain networks forward. While the "correct" method to be used remains an open, possibly unsolvable question that deserves extensive debate and research, we argue that the best method available at the current time is the voxel-wise method.

Dataset Information

Defining key signaling nodes and therapeutic biomarkers in NF1-mutant cancers.

Publications

Defining key signaling nodes and therapeutic biomarkers in NF1-mutant cancers.

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