Cell . . . A hisst itwasher of immunoglobulin super-family interactions.

Cell membrane is an important biological contact surface between cytoplasm and extracellular environment. Cell surface receptors are regulators of intercellular communication and communication between cells and external environment.recent studies have predicted that more than 3000 genes in the human genome encode membrane proteins [1], and cell surface receptors play an important role in physiological and pathological signals.because of its function and easy contact on cell membrane, cell surface receptor family is the best target for protein targeted therapy.many studies have provided basic insights into the complex protein interaction network between model organisms or pathogens and hosts, even involving the study of protein interaction in human body.however, there is still a lack of research on the interaction of cell surface proteins.on June 25, 2020, Nadia Martinez Martin from Genentech, USA, published an article in cell magazine, the immunoglobin superfamily receptor definitions cancer related networks associated with clinical The extracellular interaction network of 445 members of the immunoglobulin superfamily (IgSF) was studied by using the previously developed high-throughput detection technology of receptor ligand interaction in human single transmembrane (STM) protein library [2].557 highly reliable interactions were identified, of which 82% were new discoveries. More than 60 receptor ligand interactions were identified by orthogonal experiments.at the same time, it revealed the status of cell type specific interaction and receptor ligand interaction imbalance in tumor.in a group of cancer patients treated with anti-PD-L1, the IgSF interaction omics study was evaluated and found that the interacting proteins were related to the function of CD8 + T-effector cells, and the protein interaction characteristics were highly correlated with the response to treatment.to explore the interaction between IgSF and STM receptors, researchers constructed a STM receptor library containing 445 human proteins, 365 of which contained at least one IgSF domain.using PD-1 / PDCD1 and PD-L2 / pdcd1lg2 as positive control, the sensitivity and stability of the platform were verified.after experiments and calculations, 577 interactions with high confidence were predicted among 440 unique IgSF and STM proteins, forming the "IgSF interaction group".if the "node" represents the extracellular protein and the "edge" represents the interaction between them, then the IgSF interaction group network has an average of 2-3 neighbors per node, which indicates that the network is composed of modular components with dense internal connections and sparse but related interconnections. TheIgSF interaction group included 105 known protein interaction pairs and 472 unreported interactions.comprehensive analysis of gene expression and IgSF interaction groups in healthy tissues verified the hypothesis that "modules with close functional connection are more likely to co express". It was found that the global tissue expression correlation coefficient of protein pairs with interaction was significantly higher than that of protein pairs without interaction.according to the functional module analysis of IgSF interaction group, a considerable number of tight junction modules such as connexin receptor and semaphorin / plexin family were observed.further analysis showed that the expression correlation of interacting protein pairs increased significantly, which was driven by selective interaction and / or selected interaction in specific tissue environment. in the first 5%, many known protein pairs are mainly related to specific tissues; many newly identified protein pairs also show strong tissue-dependent correlation. experiments such as tetramer and immunocoprecipitation were used to verify that the interaction predicted by IgSF can occur at the cellular level. surface plasmon resonance (SPR) was used to verify the protein-protein interactions, including EphA3 and PD-L1, ceacam4 and PD-L2 interactions. it is worth noting that the antibody atezolizumab, which blocks the PD-1 / PD-L1 axis, has a competitive relationship with EphA3. subsequently, the PTPR family centered modules were studied. PTPR family is the largest expression receptor protein tyrosine phosphatase family. IgSF interaction group showed that PTPR family members and four different nervous system related protein families had close connection. the ptprd, ptprs and ptprf family members were expressed on the cell surface, and the binding of slitrk3 with ptprd, ptprs, lfrn5, IL1RAP and ptprd, ptprs, ptprf were detected. this interaction has been verified by SPR and immunoprecipitation. genetic mutation of ptprd protein in tumor is very common, so will it affect the interaction network? Fourteen kinds of extracellular domain mutations were collected, including protein tyrosine phosphatase domain, immunoglobulin (Ig) and fibronectin domain (FN). The mutation of FN domain had no significant effect on ptprd interaction, while Ig domain mutation had a significant effect. interestingly, the binding to ilrap family members was almost unaffected by mutations, except for mutations in the Ig1 and ig2 domains; almost all mutations affected lrrc4b binding. moreover, specific mutations in tumors selectively affect the binding of ptprd to specific family members. in tumors, more than 90% of IgSF genes were differentially expressed, and the gene expression of interaction proteins was correlated. for example, interaction proteins such as PTPR family members are down-regulated in almost all tumors, while interaction proteins such as CTLA4 / CD80 and PD-1 / PD-L1 are up-regulated. finally, the researchers studied the correlation between the newly identified receptor ligand interaction network and the treatment results of tumor immune checkpoint. the IgSF interaction group was detected in 298 patients with metastatic urothelial carcinoma treated with anti-PD-L1 blocking antibody atezolizumab, and the transcriptome was analyzed. There was a strong correlation between the subsets of the IgSF interaction group and the immunothermal, cold or immune rejection phenotypes of the tumor (according to the characteristics of CD8 + T-effector cells and TGF - β). for example, PD-1 / PD-L1, CTLA4 / CD80, CD28 / CD86, CD47 / Sirpa, PD-L1 / EphA3, PD-L2 / ceacam4, lilrb4 / cntfr, LILRB1 / EDAR, LILRB1 / IL6R are associated with immunothermal tumors; cell adhesion molecule family is mainly associated with immune cold tumors. in addition, about 80 protein interactions were associated with improvement or aggravation of clinical outcomes, such as CD80 / PD-1 interaction, lrrc4b interaction with specific butylalanine member, and patient response to atezolizumab, while semaphorin / plexin and specific ptprd modulator were associated with poor response. in predicting clinical outcomes, gene pairs encoding interacting proteins showed synergistic effects. For example, compared with efnb1 itself, the co expression of efnb1, ecv2, aqpep and ephb6 had a higher correlation with non responders; the coexpression of efnb1 / ecv2 was significantly correlated with poor prognosis. in general, this study provides a platform for the omics study of IgSF interaction, and reveals the correlation between IgSF interaction group and tumor treatment and prognosis. research provides an important resource to promote biological discovery, as well as a framework for understanding the role of cell surface proteins in homeostasis and disease process, and provides relevant information for the development of therapeutic methods. [br / > the original link: references 1. Thul, P.J., akeson, L., Wiking, M., mahdysian, D., D., geladaki, A., AIT blal, H., ALM, t, T., aSpend, A., A., bjo ̈ rk, L., breckels, L.M., L.M., et al. (2017), a subcellular map of the human protein, science 356, eaalal3321.2. Martinez Martin, N., N., marcmandalli, J., Huang, C.S., Arthur, R, Martin Martin Martin, N., N., N., marcmandalli, J., Huang, C.S., Arthur, R, R, R, C.S., etc., et al C.P., Perotti, M, Fo- glierini, M., Ho, H., Dosey, A.M., Shriver, S., Payandeh, J., et al. (2018). An Un- biased Screen for Human Cytomegalovirus Identifies Neuropilin-2 as a Central Viral Receptor. Cell 174, 1158–1171.