Bioengineering Bacteria for GBM « Charlie Teo Foundation

Bioengineering Bacteria for GBM

Researcher name: A/Prof Tal Danino
Institution: Columbia University, U.S.
Grant Name: Research Rebels
Grant amount (AUD): $200k
Grant Awarded: 2024
Status: Ongoing

Meet the Researcher

A/Prof Tal Danino is a tenured Associate Professor in the Department of Biomedical Engineering at Columbia University. His lab focuses on engineering bacteria as a cancer therapy. Our Research team at the Charlie Teo Foundation proactively reached out to Tal to apply his novel methods to brain cancer.

What makes Tal unique is his multi-disciplinary scientific curiosity. He completed an ambitious triple major at UCLA in Chemistry, Mathematics and Physics, before going on to complete his PhD in Bioengineering. He did his post-doctoral research at the prestigious MIT before joining Columbia University in 2016, securing tenure in 2023.

Tal has created a culture of adventurous lab members who are ‘outsiders’ to the field of cancer research, offering unique expertise to treating GBM.

Tal is a celebrated scientist. His work has been published in high-impact journals including Nature, Science, and Nature Medicine. He has been featured by many media outlets including The New York Times,  WIRED and TEDx. He is the recipient of awards including the NSF CAREER Award, DoD Era of Hope Scholar Award, CRI Lloyd J Old STARs Award, Pershing Square-Sohn Prize and is a TED Fellow.

Not only this, Tal is an interdisciplinary artist transforming cancer cells from the laboratory into art works exhibited all around the world including in the U.S., Austria, South Korea, China, Norway and France.

This project is a game-changer because it uses a new field of science called synthetic biology to turn bacteria into a living medicine for GBM therapy. The project will test different types of engineered bacteria that have been shown to be safe and good at setting up home in tumours. The team has developed advanced genetic circuits in live bacteria, which will be tested in GBM models for the first time, potentially enabling safe and effective treatment in the brain by controlling how and when the bacteria deliver anti-cancer medicines to the tumour, grow, and interact with the immune system.

This project can help people with brain cancer by offering an out-of-the-box and potentially more effective treatment approach. By engineering bacteria to carry powerful anti-cancer molecules for GBM, the project aims to develop treatments that can get past the blood brain barrier and reach parts of the tumour that are usually out of reach for conventional therapies. This could lead to more effective treatments and better outcomes for patients with GBM. The use of engineered bacteria can have a big impact on the treatment of brain cancer by improving the effectiveness of the treatment and kick-starting the immune system in the local area. The project’s findings could also push forward the whole field of brain cancer research, paving the way for testing new types of engineered bacteria for GBM therapy that could ultimately help patients and fill the gaps in current GBM treatment options.

Glioblastoma multiforme (GBM) is a highly lethal adult brain cancer, with treatment hindered by the blood-brain barrier. Certain bacteria, like E. coli Nissle 1917, can bypass the blood-brain barrier and grow within necrotic tumour cores, offering a unique therapeutic opportunity. While these bacteria have shown safety and tumour colonization, their efficacy is limited, leading to a shift towards engineering bacteria to deliver therapeutic payloads. The Danino lab has previously engineered bacteria to express various therapeutic agents with significant efficacy across multiple cancer models. Preliminary data shows that bacteria can colonize GBM mouse models, leading to a proposal to engineer bacteria to deliver cytotoxic and immunotherapeutic payloads for GBM, while improving their safety and control systems.

The overarching aims of this grant includes:

Aim 1: Characterize engineered strains to reduce toxicity of bacteria in GBM models
Aim 2: Optimize therapeutic payloads and genetic circuitry for bacterial delivery in GBM models.