Back

Transmorphic phage-guided systemic delivery of TNFα gene for the treatment of human paediatric medulloblastoma

Al-Bahrani, M.; Waramit, S.; Suwan, K.; Asavarut, P.; Hajitou, A.

2022-10-18 microbiology
10.1101/2022.10.18.512650 bioRxiv
Show abstract

Medulloblastoma is the most common childhood brain tumor with an unfavorable prognosis and limited options of harmful treatments that are associated with devastating long-term side effects. Therefore, the development of safe, non-invasive and effective therapeutic approaches is required to save the quality of life of young medulloblastoma survivors. We postulated that therapeutic targeting is a solution. Thus, we used a recently designed tumor-targeted bacteriophage (phage)-derived particle, named transmorphic phage/AAV, TPA, to deliver a transgene expressing the tumor necrosis factor alpha (TNF) for targeted systemic therapy of medulloblastoma. This vector was engineered to display the double cyclic RGD4C peptide to selectively target tumors after intravenous administration. Furthermore, the lack of native phage tropism to mammalian cells warrants safe and selective systemic delivery to the tumor microenvironment. In vitro RGD4C.TPA.TNF treatment of human medulloblastoma cells generated efficient and selective TNF expression, subsequently triggering cell death. Combination with the chemotherapeutic drug cisplatin, used clinically against medulloblastoma, resulted in augmented effect through the enhancement of TNF gene expression. Systemic administration of RGD4C.TPA.TNF to mice bearing subcutaneous medulloblastoma xenografts resulted in selective tumor homing of these particles, and consequently targeted tumor expression of TNF, apoptosis, and destruction of the tumor vasculature. Thus, our RGD4C.TPA.TNF particle provides selective and efficient systemic delivery of TNF to medulloblastoma, yielding a potential TNF anti-medulloblastoma therapy while sparing healthy tissues from the systemic toxicity of this cytokine.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.