← BioTransfer GEO Dataset Finder
GEO series

Engineered cytokine/antibody fusion proteins improve delivery of IL-2 to pro-inflammatory cells and promote antitumor activity

GSE273415 Homo sapiens Expression profiling by high throughput sequencing 14 samples 2024/07/30 GPL24676
Summary
Progress in cytokine engineering is driving therapeutic translation by overcoming these proteins’ inherent limitations as drugs. The interleukin-2 (IL-2) cytokine harbors great promise as an immune stimulant for cancer treatment. However, the cytokine’s concurrent activation of both pro- inflammatory immune effector cells and anti-inflammatory regulatory T cells, toxicity at high doses, and short serum half-life limit clinical application. One promising approach to improve the selectivity, safety, and longevity of IL-2 is complexation with anti-IL-2 antibodies that bias the cytokine towards activation of immune effector cells. Although this strategy shows therapeutic potential in preclinical cancer models, clinical translation of a cytokine/antibody complex is complicated by challenges in formulating a multi-protein drug and concerns about complex stability. Here, we introduce a versatile approach to designing intramolecularly assembled single- agent fusion proteins (immunocytokines, ICs) comprising IL-2 and a biasing anti-IL-2 antibody that directs the cytokine’s activities towards immune effector cells. We establish the optimal IC construction and further engineer the cytokine/antibody affinity to improve immune biasing function. We demonstrate that our IC preferentially activates and expands immune effector cells, leading to superior antitumor activity compared to natural IL-2, both alone and in combination with immune checkpoint inhibitors. Moreover, therapeutic efficacy is observed without inducing toxicity, as measured by weight loss, pulmonary edema, cytokine secretion, and liver damage markers. This work presents a roadmap for the design and translation of cytokine/antibody fusion proteins.
Download
NCBI GEO page ↗ Paper (PMID 39115939) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.