L-Asparaginase (ASP) is well-known for its excellent efficacy in treating hematological malignancies. Unfortunately, the intrinsic shortcomings of ASP, namely high immunogenicity, severe toxicity, short half-life, and poor stability, restrict its clinical usage. Poly(ethylene glycol) conjugation (PEGylation) of ASP is an effective strategy to address these issues, but it is not ideal in clinical applications due to complex chemical synthesis procedures, reduced ASP activity after conjugation, and pre-existing anti-PEG antibodies in humans. Herein, the authors genetically engineered an elastin-like polypeptide (ELP)-fused ASP (ASP-ELP), a core-shell structured tetramer predicted by AlphaFold2, to overcome the limitations of ASP and PEG-ASP. Notably, the unique thermosensitivity of ASP-ELP enables the in situ formation of a sustained-release depot post-injection with zero-order release kinetics over a long time. The in vitro and in vivo studies reveal that ASP-ELP possesses increased activity retention, improved stability, extended half-life, mitigated immunogenicity, reduced toxicity, and enhanced efficacy compared to ASP and PEG-ASP. Indeed, ASP-ELP treatment in leukemia or lymphoma mouse models of cell line-derived xenograft (CDX) shows potent anti-cancer effects with significantly prolonged survival. The findings also indicate that artificial intelligence (AI)-assisted genetic engineering is instructive in designing protein-polypeptide conjugates and may pave the way to develop next-generation biologics to enhance cancer treatment.
Keywords: L-asparaginase; artificial intelligence; elastin-like polypeptide; hematological malignancies; immunogenicity.
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