Gene Editing Used to Enhance AML Antigen Targeting for CAR T-Cell Therapy

Video

Siddhartha Mukherjee, MD, discusses potential means of targeting chimeric antigen receptor T-cell therapy for patients with acute myeloid leukemia.

Siddhartha Mukherjee, MD, assistant professor of medicine at Columbia University Medical Center, discusses potential means of targeting chimeric antigen receptor (CAR) T-cell therapy for patients with acute myeloid leukemia (AML).

There are currently few CAR T-cell therapies for AML based on available antigen targets that have shown efficacy. According to Mukherjee, his company Vor Biopharma is investigating CD33 and CLL-1 antigens, which are highly expressed in AML cells but are also expressed in healthy CD34+ human hematopoietic stem cells.

In order to improve targeting of CAR T-cell therapy, investigators are researching the impact of deleting these antigens from healthy hematopoietic stem cells through multiplex editing. The investigators have demonstrated with in vivo models that gene-edited cells remain viable and persistent in the long term, so VCAR33-CLL1 multi-specific CAR T cells can be directed against AML cells without causing on-target, off-tumor cytopenic effects. Additionally, targeting multiple antigens could reduce the chance of tumor resistance.

Mukherjee says this is effectively bioengineering a unique tumor antigen. A trial of CAR T-cell therapy following this gene editing approach is now recruiting, and he hopes it will show efficacy and tolerability AML.

TRANSCRIPTION:

0:08 | In our trial, we delete an antigen from the donor cells, CD33 and maybe a couple of antigens we can delete, and then use the fact that now these normal cells don't have that antigen, while the AML cells have that antigen. We can now direct CAR T cells against AML cells. CD33 is 1 of them. There are 2 or 3 other antigens that we're working on. And all of a sudden now we’ve bioengineered a unique tumor cell antigen. That trial is also recruiting, and I think we're very excited about it. We, of course, don't have any data about it yet, but I'm optimistic that it will work.

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