Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Robust antitumor activity of a de novo interleukin-21 mimic

ABSTRACT: Robust antitumor activity of a de novo interleukin-21 mimic

PROVIDER: PRJNA1078872 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Robust antitumor activity of a de novo interleukin-21 mimic

Project description:A long-standing goal of cancer immunotherapy is to activate cytotoxic antitumor T cells across a broad range of affinities and dampen suppressive regulatory T (Treg) cell responses, but current approaches achieve these goals with limited success. Here, we report a de novo IL-21 mimic, 21h10, designed to have augmented stability and high signaling potency in both humans and mice. In multiple animal models, 21h10 showed robust antitumor activity, exceeding that of native IL-21 for murine melanoma, inducing a rapid regression of murine adenocarcinoma, and exhibiting potent activity in an orthotopic pancreatic cancer model that is refractory to conventional immunotherapies. In the tumor microenvironment, 21h10 induced highly cytotoxic antitumor T cells from clonotypes with a range of affinities for endogenous tumor antigens, driving high expression of interferon- (IFN- ) and granzyme B compared to native IL-21, while in the CD4+ T cell compartment, the frequency of IFN- + Th1 cells was increased while Foxp3+ Treg cells were reduced. Thus, 21h10 is a highly active IL-21 mimic with human-mouse cross-reactivity that potentiates low-affinity antitumor responses and has considerable translational potential.

2025-01-01 | GSE256289 | GEO

Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity

Project description:Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity

| PRJNA785881 | ENA

Robust de novo pathway enrichment with KeyPathwayMiner 5.

Project description:Identifying functional modules or novel active pathways, recently termed de novo pathway enrichment, is a computational systems biology challenge that has gained much attention during the last decade. Given a large biological interaction network, KeyPathwayMiner extracts connected subnetworks that are enriched for differentially active entities from a series of molecular profiles encoded as binary indicator matrices. Since interaction networks constantly evolve, an important question is how robust the extracted results are when the network is modified. We enable users to study this effect through several network perturbation techniques and over a range of perturbation degrees. In addition, users may now provide a gold-standard set to determine how enriched extracted pathways are with relevant genes compared to randomized versions of the original network.

| S-EPMC4965696 | biostudies-literature

Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity III

Project description:Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity III

| PRJNA794186 | ENA

Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity II

Project description:Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity II

| PRJNA794177 | ENA

Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity IV

Project description:Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity IV

| PRJNA794187 | ENA

Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity V

Project description:Interleukin-10/CSF1R fusion protein rejuvenates the exhausted T cells for executing antitumor activity V

| PRJNA794196 | ENA

Hybrid Sequencing Facilitates Robust <i>De Novo</i> Plasmid Assembly.

Project description:Despite the wide use of plasmids in research and clinical production, the verification of plasmid sequences is a bottleneck that is too often overlooked in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had frequent issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most consistent assembly generation. Although Sanger sequencing can be used to verify specific regions, it requires a reference sequence to design primers, emphasizing the need for accurate de novo plasmid assembly tools. Some GC-rich and repetitive regions were difficult to resolve using any methods, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

| S-EPMC10996661 | biostudies-literature

microarray Analysis of MKN-45 cell lines after 48 hours post-transfection of miR-125b mimic (50nM) and mimic control.

Project description:We demonstrate that miR-125b, a key node in this microRNA regulatory network, is upregulated in gastric cancer (GC) and associated with poor overall survival through an integrated analysis of microRNA and mRNA profiling of GC revealed a mRNA-regulatory network.So we have employed whole genome microarray expression profiling as a discovery platform to compare the transcriptome profiling of human gastric cells (MKN-45) after 48 hours post-transfection of miR-125b mimic (50nM) and mimic control.Pathway analysis shows that the predicted targets of miR-125b are highly involved in apoptosis/program death pathway，and the robust apoptosis genes, BIK and CASP6 are validated as the directed targets of miR-125b.

2021-02-25 | GSE145959 | GEO

Lactate dehydrogenase inhibition synergizes with IL-21 to promote CD8+ T cell stemness and antitumor immunity

Project description:Interleukin (IL)-2 and IL-21 dichotomously shape CD8+ T cell differentiation. IL-2 drives terminal differentiation, generating cells that are poorly effective against tumors, whereas IL-21 promotes stem cell memory T cells (TSCM) and antitumor responses. Here we investigated the role of metabolic programming in the developmental differences induced by these cytokines. IL-2 promoted effector-like metabolism and aerobic glycolysis, robustly inducing lactate dehydrogenase (LDH) and lactate production, whereas IL-21 maintained a metabolically quiescent state dependent on oxidative phosphorylation. LDH inhibition rewired IL-2–induced effects, promoting pyruvate entry into the tricarboxylic acid cycle and inhibiting terminal effector and exhaustion programs, including mRNA expression of members of the NR4A family of nuclear receptors, as well as Prdm1 and Xbp1. While deletion of Ldha prevented development of cells with antitumor effector function, transient LDH inhibition enhanced the generation of memory cells capable of triggering robust antitumor responses after adoptive transfer. LDH inhibition did not significantly affect IL-21–induced metabolism but caused major transcriptomic changes, including the suppression of IL-21–induced exhaustion markers LAG3, PD1, 2B4, and TIM3. LDH inhibition combined with IL-21 increased the formation of TSCM cells, resulting in more profound antitumor responses and prolonged host survival. These findings indicate a pivotal role for LDH in modulating cytokine-mediated T cell differentiation and underscore the therapeutic potential of transiently inhibiting LDH during adoptive T cell-based immunotherapy, with an unanticipated cooperative antitumor effect of LDH inhibition and IL-21.

2020-02-13 | GSE143903 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data