The Mu Lab at Yale School of Medicine

Transcript

• 00:04Lineage plasticity is a process
• 00:06which cancer cell can change
• 00:08their identity
• 00:09and become someone they are
• 00:11not before. Think about the
• 00:12whole concept of any anti
• 00:14cancer treatment. These kinds of
• 00:15cell have some identity, make
• 00:17them different from normal cells.
• 00:19Right? So we can target
• 00:20them by our anti cancer
• 00:22therapies.
• 00:26My lab, trying to answer
• 00:28three big questions.
• 00:29First is
• 00:30why cancer cell are able
• 00:32to escape the anti cancer
• 00:33therapy we designed for them,
• 00:34and how can we stop
• 00:35that? And second question is
• 00:38most of anti cancer therapy
• 00:39only work in a small
• 00:41proportion of patient. So we
• 00:43want to know, can we
• 00:44actually find a way to
• 00:45predict which patient responds to
• 00:47which therapy and match the
• 00:50perfect therapy for the perfect
• 00:51patient?
• 00:52And third is we try
• 00:53and develop new therapies for
• 00:55some cancer do not respond
• 00:57to any therapy exist right
• 00:59now. Now. So we are
• 01:00working very close to the
• 01:02physician colleagues at Yale and
• 01:04using all the cutting edge
• 01:05technology in my lab trying
• 01:07to solve these three big
• 01:08questions.
• 01:12This small rare clone has
• 01:14the ability to change it
• 01:15to some different cell it
• 01:16doesn't look like. But with
• 01:18special transatomic and single cell,
• 01:20first we can mapping them.
• 01:21We can know what you're
• 01:23actually changing to a new
• 01:24one. And with artificial intelligence,
• 01:26which AI do the best,
• 01:27is find a pattern. We
• 01:29do not what your identity
• 01:30is, but we can capture
• 01:32the pattern you change
• 01:34and then design three d
• 01:35cultured organoid.
• 01:37Organoid, you can think about
• 01:38is like a mini pseudotumor.
• 01:40We can generate those pseudotumor
• 01:42from a patient tumor, which
• 01:44means we can test a
• 01:45specific drug. Basically, we predict
• 01:48your next move and give
• 01:49you the drug already waiting
• 01:51there.
• 01:52This platform
• 01:53works close together.
• 01:55Basically,
• 01:55it's
• 01:56examine,
• 01:57prediction,
• 01:59and testing
• 02:00and will help us to
• 02:02solve the three big questions.
• 02:07If we can find all
• 02:08those rare cologne for not
• 02:11all the tumor, but every
• 02:12different patient,
• 02:13each of the rare cologne
• 02:15which cause their tumor may
• 02:16relapse in the future, and
• 02:17then we can design therapies
• 02:19to stop that before the
• 02:20tumor even relapses.
• 02:22And the second goal is
• 02:23use this precision medicine which
• 02:25based on AI algorithm prediction
• 02:27and those little pseudo tumor
• 02:29group platform.
• 02:30We can give each patient
• 02:32a very different treatment design
• 02:34based on AI prediction.
• 02:37And we'll have the most
• 02:38effective treatment before you even
• 02:40give the patient to help
• 02:41our physician colleagues.
• 02:44Right now, our lab is
• 02:45working on prostate cancer and
• 02:46also bladder cancer, and especially
• 02:48because we're in the urology
• 02:50department.
• 02:50But you can see the
• 02:52platform we built, the AI
• 02:53system, the special transatomic, and
• 02:55the pseudotumor,
• 02:56we can use the same
• 02:57platform to any different cancers.