Deterministic mechanoporation of cells en masse to cure cancer

What if you could cure cancer by re-engineering patients' cells to better target and destroy their own tumors? With the advent of powerful new cellular engineering technologies, this is no longer the stuff of science fiction.

In the past few years, these technologies have enabled the development of revolutionary engineered cell therapies for treating cancer, such as CAR-T cell cancer immunotherapies for leukemia and lymphoma. They have also enabled development of treatments for rare genetic disorders, such as HSC gene therapies for "Bubble Boy disease" and beta thalassemia. Researchers worldwide are working at fever pitch to develop similar therapies for a large number of other deadly and debilitating illnesses.

But there's a catch: with the cost of these so-called "living drugs" ranging from a few hundred thousand dollars to nearly $2 million dollars, it's unclear whether they'll be sufficiently accessible to all those in need.

Now, in a watershed advance, engineers at the University of California, Riverside, in collaboration with researchers at City of Hope National Medical Center, have invented a device that holds potential for mass-producing engineered cells at lower cost, a tipping point for these lifesaving therapies.

In a new paper in the journal Nano Letters, a team of researchers led by Masaru Rao, an associate professor of mechanical engineering in the Marlan and Rosemary Bourns College of Engineering, describes a novel microfluidic device technology capable of addressing one of the most costly steps in the engineered cell therapy manufacturing process, namely gene delivery.

This technology, which the authors call deterministic mechanoporation, or DMP, uses fluid flow to pull each cell in a large population onto its own tiny needle. The flow is then reversed to release the cells from the needles, leaving a singular and precisely defined pore within each cell that allows for gene delivery.

This simple, but elegant nanomechanical poration approach provides significant advantages relative to existing gene delivery techniques. For example, since viral vectors make up a large fraction of the overall manufacturing cost of current cell therapies, their elimination through the use of DMP holds potential for considerable cost reduction."

Masaru Rao, associate professor of mechanical engineering in the Marlan and Rosemary Bourns College of Engineering

DMP's unique single-site poration mechanism is key, since it minimizes damage to the cell, while producing a well-defined pathway for introducing genes. This provides opportunity for achieving both high delivery efficiency and cellular viability, which is difficult to achieve using other non-viral delivery techniques, such as electroporation.

"In fact, in our paper we show that DMP can engineer primary human T cells, the same kind of cells used in CAR-T therapies, with efficiencies that exceed a state-of-the-art electroporation tool by more than four-fold," said Rao.

The DMP technology has been patented by UC Riverside and recently licensed to a new startup company that Rao has spun out of his lab, Basilard BioTech. The company is seeking to develop the technology, which it has branded SoloPore, as a disruptive new solution for engineering ex vivo cell and gene therapies for cancer specifically, as well as genetic disorders and degenerative diseases more broadly.

Journal reference:

Dixit, H.G., et al. (2019) Massively-Parallelized, Deterministic Mechanoporation for Intracellular Delivery. Nano Letters.


The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
New urine-based test holds great promise for early detection and prevention of cervical cancer