Suppressor of cytokine signaling-3 (SOCS-3) is one member of a family of intracellular inhibitors of signaling pathways initiated by cytokines that use, among others, the common receptor subunit gp130. The SH2 domain of SOCS-3 has been shown to be essential for this inhibitory activity, and we have used a quantitative binding analysis of SOCS-3 to synthetic phosphopeptides to map the potential sites of interaction of SOCS-3 with different components of the gp130 signaling pathway. The only high-affinity ligand found corresponded to the region of gp130 centered around phosphotyrosine-757 (pY757), previously shown to be a docking site for the tyrosine phosphatase SHP-2. By contrast, phosphopeptides corresponding to other regions within gp130, Janus kinase, or signal transducer and activator of transcription proteins bound to SOCS-3 with weak or undetectable affinity. The significance of pY757 in gp130 as a biologically relevant SOCS-3 docking site was investigated by using transfected 293T fibroblasts. Although SOCS-3 inhibited signaling in cells transfected with a chimeric receptor containing the wild-type gp130 intracellular domain, inhibition was considerably impaired for a receptor carrying a Y3 F point mutation at residue 757. Taken together, these data suggest that the mechanism by which SOCS-3 inhibits the gp130 signaling pathway depends on recruitment to the phosphorylated gp130 receptor, and that some of the negative regulatory roles previously attributed to the phosphatase SHP-2 might in fact be caused by the action of SOCS-3.
Metabolomics research often requires the use of multiple analytical platforms, batches of samples, and laboratories, any of which can introduce a component of unwanted variation. In addition, every experiment is subject to within-platform and other experimental variation, which often includes unwanted biological variation. Such variation must be removed in order to focus on the biological information of interest. We present a broadly applicable method for the removal of unwanted variation arising from various sources for the identification of differentially abundant metabolites and, hence, for the systematic integration of data on the same quantities from different sources. We illustrate the versatility and the performance of the approach in four applications, and we show that it has several advantages over the existing normalization methods.
The lung presents a highly oxidative environment, which is tolerated through engagement of tightly controlled stress response pathways. A critical stress response mediator is the transcription factor nuclear factor erythroid-2-related factor 2 (NFE2L2/NRF2), which is negatively regulated by Kelch-like ECH-associated protein 1 (KEAP1). Alterations in the KEAP1/NRF2 pathway have been identified in 23% of lung adenocarcinomas, suggesting that deregulation of the pathway is a major cancer driver. We demonstrate that inactivation of Keap1 and Pten in the mouse lung promotes adenocarcinoma formation. Notably, metabolites identified in the plasma of Keap1/Pten tumor-bearing mice indicate that tumorigenesis is associated with reprogramming of the pentose phosphate pathway. Furthermore, the immune milieu was dramatically changed by Keap1 and Pten deletion, and tumor regression was achieved utilizing immune checkpoint inhibition. Thus, our study highlights the ability to exploit both metabolic and immune characteristics in the detection and treatment of lung tumors harboring KEAP1/NRF2 pathway alterations.
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