2022
DOI: 10.2139/ssrn.4283169
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A Target Discovery Pipeline Identified ILT3 as a Target for Immunotherapy of Multiple Myeloma

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Cited by 2 publications
(5 citation statements)
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“…Finding differentially expressed proteins between FL and MCL [95] MCL Identification of molecular signatures that differentiate MCL from B cells of the different compartments [96] Identification of proteomic biomarkers to distinguish MCL [97] Searching for specific proteomic biomarkers overexpressed in MCL tumor biopsies [98] Identification of tyrosine-phosphorylated proteins [99] Provision of insights into the dynamics of the disease and response to treatment [99] Evaluation of resistance to antinucleoside drugs [100] Discovery of neo-antigen peptides that mediate the killing of autologous lymphoma cells by circulating CD4 T cells [101] Characterization of the action mechanism of the MDM2-antagonist nutlin-3a [102] Discovery of the mechanisms involved in the pathogenesis of ocular adnexa extranodal MZL [103] Identification of biomarkers for the diagnosis of primary Sjögren's syndrome/MALT and prediction of progression [104] Establishment of the role of ID3 in regulating cell proliferation [105] MZL Study of the pharmacokinetics of umbralisib [106] BL Analysis of differentially expressed proteins between endemic and sporadic BL variants and EBV + and EBV − BL cell lines [107] Prediction of MGUS progression for an early diagnosis of MM [108] Analysis of the tumor microenvironment to identify determinants of durable responses to BCMA CAR T therapy [109] Quantification of surface proteins to identify immunotherapy targets and biomarkers associated with resistance and response to treatment [109] MM Identification of cell surface targets for immune-based therapies [110] Flow Cytometry CLL Design of panels for rapid disease diagnosis and progression assessment [111,112] Comparison of residual normal B cell profiles between CLL and MBL [113] B-ALL Evaluation of neuropilin-1/CD304 as minimal residual disease and prognostic marker [114] DLBCL Assessment of the absolute counts of B cells, T cells, and Treg cells for the prognostication of newly diagnosed DLBCL patients [115] Evaluation of the monocytic population distribution as an independent prognostic factor [116] DLBCL & FL Usage of aneuploidy and cell cycle indexing as tools for differentiating between CD10 + DLBCL and FL [117] DLBCL & BL Identification of cell markers to differentiate between BL and CD10 + DLBCL [118] MZL Distinguishing IgG4-related ophthalmic disease, idiopathic orbital inflammatio...…”
Section: Discovery Of Predictive Indicators Of Histological Transform...mentioning
confidence: 99%
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“…Finding differentially expressed proteins between FL and MCL [95] MCL Identification of molecular signatures that differentiate MCL from B cells of the different compartments [96] Identification of proteomic biomarkers to distinguish MCL [97] Searching for specific proteomic biomarkers overexpressed in MCL tumor biopsies [98] Identification of tyrosine-phosphorylated proteins [99] Provision of insights into the dynamics of the disease and response to treatment [99] Evaluation of resistance to antinucleoside drugs [100] Discovery of neo-antigen peptides that mediate the killing of autologous lymphoma cells by circulating CD4 T cells [101] Characterization of the action mechanism of the MDM2-antagonist nutlin-3a [102] Discovery of the mechanisms involved in the pathogenesis of ocular adnexa extranodal MZL [103] Identification of biomarkers for the diagnosis of primary Sjögren's syndrome/MALT and prediction of progression [104] Establishment of the role of ID3 in regulating cell proliferation [105] MZL Study of the pharmacokinetics of umbralisib [106] BL Analysis of differentially expressed proteins between endemic and sporadic BL variants and EBV + and EBV − BL cell lines [107] Prediction of MGUS progression for an early diagnosis of MM [108] Analysis of the tumor microenvironment to identify determinants of durable responses to BCMA CAR T therapy [109] Quantification of surface proteins to identify immunotherapy targets and biomarkers associated with resistance and response to treatment [109] MM Identification of cell surface targets for immune-based therapies [110] Flow Cytometry CLL Design of panels for rapid disease diagnosis and progression assessment [111,112] Comparison of residual normal B cell profiles between CLL and MBL [113] B-ALL Evaluation of neuropilin-1/CD304 as minimal residual disease and prognostic marker [114] DLBCL Assessment of the absolute counts of B cells, T cells, and Treg cells for the prognostication of newly diagnosed DLBCL patients [115] Evaluation of the monocytic population distribution as an independent prognostic factor [116] DLBCL & FL Usage of aneuploidy and cell cycle indexing as tools for differentiating between CD10 + DLBCL and FL [117] DLBCL & BL Identification of cell markers to differentiate between BL and CD10 + DLBCL [118] MZL Distinguishing IgG4-related ophthalmic disease, idiopathic orbital inflammatio...…”
Section: Discovery Of Predictive Indicators Of Histological Transform...mentioning
confidence: 99%
“…Noteworthy targets identified included ILT3, SEMA4A, CCR1, IL12RB1, FCRL3, and LRRC8D. A bispecific T cell engager targeting ILT3 in MM cells was developed, demonstrating potent killing effects [110].…”
Section: Proteomics Studies On Multiple Myeloma (Mm)mentioning
confidence: 99%
“…ITAM-mediated signalling propagates the nuclear translocation of nuclear factor (NF)-kB and nuclear factor of activated T cells (NFAT), phosphoinositide (PI) 3-kinase (PI3K) activation, which activates membrane-bound serine/threonine-specific protein kinases (AKT and BTK), as well as interacting with Ras to activate the Ras/Raf pathway. As a result, ligation of LILRAs propagates the proliferation, maturation and survival of immune cells (217, 218) (185,190) CLL, AML (119,185,191,192), multiple myeloma (193) (Figure 3). The signalling mechanisms of LILRA1 and LILRA6 remain to be identified, although the structural similarity with the other LILRAs suggests that they also signal though FceRIg.…”
Section: Lilr Signallingmentioning
confidence: 99%
“…Frontiers in Immunology frontiersin.org [191][192][193][194][195][196]290). LILRB4 has been associated with tumour immuneevasion with lower expression correlating with higher sensitivity to killing by NK cells in gastric cancer (120).…”
Section: Histological Analysis Of Breast Cancer Biopsies Revealed Lil...mentioning
confidence: 99%
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