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Affinity purification mass spectrometry analysis of PD-1 uncovers SAP as a new checkpoint inhibitor.

ABSTRACT: Programmed cell death-1 (PD-1) is an essential inhibitory receptor in T cells. Antibodies targeting PD-1 elicit durable clinical responses in patients with multiple tumor indications. Nevertheless, a significant proportion of patients do not respond to anti-PD-1 treatment, and a better understanding of the signaling pathways downstream of PD-1 could provide biomarkers for those whose tumors respond and new therapeutic approaches for those whose tumors do not. We used affinity purification mass spectrometry to uncover multiple proteins associated with PD-1. Among these proteins, signaling lymphocytic activation molecule-associated protein (SAP) was functionally and mechanistically analyzed for its contribution to PD-1 inhibitory responses. Silencing of SAP augmented and overexpression blocked PD-1 function. T cells from patients with X-linked lymphoproliferative disease (XLP), who lack functional SAP, were hyperresponsive to PD-1 signaling, confirming its inhibitory role downstream of PD-1. Strikingly, signaling downstream of PD-1 in purified T cell subsets did not correlate with PD-1 surface expression but was inversely correlated with intracellular SAP levels. Mechanistically, SAP opposed PD-1 function by acting as a molecular shield of key tyrosine residues that are targets for the tyrosine phosphatase SHP2, which mediates PD-1 inhibitory properties. Our results identify SAP as an inhibitor of PD-1 function and SHP2 as a potential therapeutic target in patients with XLP.

SUBMITTER: Peled M

PROVIDER: S-EPMC5776966 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Affinity purification mass spectrometry analysis of PD-1 uncovers SAP as a new checkpoint inhibitor.

Peled Michael M Tocheva Anna S AS Sandigursky Sabina S Nayak Shruti S Philips Elliot A EA Nichols Kim E KE Strazza Marianne M Azoulay-Alfaguter Inbar I Askenazi Manor M Neel Benjamin G BG Pelzek Adam J AJ Ueberheide Beatrix B Mor Adam A

Proceedings of the National Academy of Sciences of the United States of America 20171227 3

Programmed cell death-1 (PD-1) is an essential inhibitory receptor in T cells. Antibodies targeting PD-1 elicit durable clinical responses in patients with multiple tumor indications. Nevertheless, a significant proportion of patients do not respond to anti-PD-1 treatment, and a better understanding of the signaling pathways downstream of PD-1 could provide biomarkers for those whose tumors respond and new therapeutic approaches for those whose tumors do not. We used affinity purification mass s ...[more]

PMID: 29282323

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Project description:BACKGROUND: Recent advances in molecular biology have led to the accumulation of large amounts of data on protein-protein interaction networks in different species. An important challenge for the analysis of these data is to extract functional modules such as protein complexes and biological processes from networks which are characterised by the present of a significant number of false positives. Various computational techniques have been applied in recent years. However, most of them treat protein interaction as binary. Co-complex relations derived from affinity purification/mass spectrometry (AP-MS) experiments have been largely ignored. METHODS: This paper presents a new algorithm for detecting protein complexes from AP-MS data. The algorithm intends to detect groups of prey proteins that are significantly co-associated with the same set of bait proteins. We first construct AP-MS data as a bipartite network, where one set of nodes consists of bait proteins and the other set is composed of prey proteins. We then calculate pair-wise similarities of bait proteins based on the number of their commonly shared neighbours. A hierarchical clustering algorithm is employed to cluster bait proteins based on the similarities and thus a set of 'seed' clusters is obtained. Starting from these 'seed' clusters, an expansion process is developed to identify prey proteins which are significantly associated with the same set of bait proteins. Then, a set of complete protein complexes is derived. In application to two real AP-MS datasets, we validate biological significance of predicted protein complexes by using curated protein complexes and well-characterized cellular component annotation from Gene Ontology (GO). Several statistical metrics have been applied for evaluation. RESULTS: Experimental results show that, the proposed algorithm achieves significant improvement in detecting protein complexes from AP-MS data. In comparison to the well-known MCL algorithm, our algorithm improves the accuracy rate by about 20% in detecting protein complexes in both networks and increases the F-Measure value by about 50% in Krogan_2006 network. Greater precision and better accuracy have been achieved and the identified complexes are demonstrated to match well with existing curated protein complexes. CONCLUSIONS: Our study highlights the significance of taking co-complex relations into account when extracting protein complexes from AP-MS data. The algorithm proposed in this paper can be easily extended to the analysis of other biological networks which can be conveniently represented by bipartite graphs such as drug-target networks.

Dataset Information

Affinity purification mass spectrometry analysis of PD-1 uncovers SAP as a new checkpoint inhibitor.

Publications

Affinity purification mass spectrometry analysis of PD-1 uncovers SAP as a new checkpoint inhibitor.

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