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Paul Calabresi, MD Memorial Lectureship: Lymphocytes as a 'Living Drug' for the Treatment of Cancer

May 31, 2023
  • 00:00On behalf of myself and Doctor Weiner and
  • 00:04the the team here at Yale Cancer Center,
  • 00:07it's really my honor to introduce our
  • 00:0915th Calabresi Memorial Lecture and I
  • 00:12think I've been here for about 12 of
  • 00:15them in honor of Doctor Paul Calabresi.
  • 00:18We always are proud to welcome the Calabresi
  • 00:21family with us in person or online.
  • 00:25We have actually in the front
  • 00:27row Judge Guido Calbresi,
  • 00:29and I'll have him say a few words at
  • 00:32some point and just received a week ago
  • 00:34with the honor and another Yale degree.
  • 00:37He's already had several and you
  • 00:40know Paul's younger brother and I've
  • 00:42been very fortunate to know Guido
  • 00:43for a long time as well.
  • 00:44We also have Steven Calabresi on his way
  • 00:48from Rhode Island and we have several
  • 00:50other Calbresi family online and we're
  • 00:52really honored to have Steven Rosenberg.
  • 00:55This year's Cal Brazi lecturer and
  • 00:57we've been Vince and I have been
  • 00:59trying to get Steven for years and the
  • 01:02offer of doing it virtually was fine
  • 01:04because that this is such timely work.
  • 01:06It's the type of work that we
  • 01:08want to build here at Yale.
  • 01:10We actually have Mario Snow here who's
  • 01:12will show up at some point, Steve.
  • 01:13So we're really happy you're here.
  • 01:15But let me say a few words about Paul.
  • 01:18Paul Cal Brazi is often referred
  • 01:20to as the father of oncology
  • 01:22and as influence here at Yale.
  • 01:24Remains to this day.
  • 01:25He's a former faculty member
  • 01:27of Yale School of Medicine.
  • 01:29In fact,
  • 01:30he I believe he held one of the jobs I hold.
  • 01:32He built medical oncology at a time when I
  • 01:34don't think it really was medical oncology.
  • 01:36So he really, he really built the field.
  • 01:39He was internationally recognized for
  • 01:41the pharmacology of anti cancer agents.
  • 01:44And if you walk through the B wing,
  • 01:45you still feel his influence,
  • 01:47the people he worked with,
  • 01:47the people he recruited.
  • 01:49And he also serves as the director of
  • 01:51Yale Cancer Centers Advisory Board.
  • 01:53Until 2003.
  • 01:56Unfortunately,
  • 01:56he himself passed away from cancer,
  • 01:59showing us how while we're making progress,
  • 02:02we still have so much more we need to do.
  • 02:05I have a good fortune to meet Paul.
  • 02:07I hate to say it, 43 years ago.
  • 02:09I don't think I'll talk about
  • 02:11that too much here.
  • 02:12But his son Peter was my
  • 02:14freshman roommate at Yale,
  • 02:16and I met Peter and.
  • 02:18What better for someone who wanted
  • 02:19to be a doctor to have as a roommate,
  • 02:21you know, the father of oncology.
  • 02:23It was very nice.
  • 02:24They didn't like me at first too much.
  • 02:26But I've the family has warmed up to
  • 02:27me over the years and actually I've I I
  • 02:30was looking through some photos last night.
  • 02:32You know it was an error without iPhone,
  • 02:33so it's hard to find photos like it is now.
  • 02:35But I've spent many memorable times
  • 02:37with the Cal Brazi family over the
  • 02:40Yale Paul was an advisor, a mentor,
  • 02:43and a really good friend to me.
  • 02:46Actually Vince and I, I still we know we
  • 02:48we helped him with his disease as well.
  • 02:50And having this job here means so much to me.
  • 02:53One of the reasons I I'm back at
  • 02:55Yale is Paul had always told me
  • 02:57Yale is a great place for you.
  • 02:59I think you'd be happy there.
  • 03:01So joining us today we have Guido Calbresi
  • 03:04as I mentioned Doctor Calgary's brother,
  • 03:06his wife Anne I believe is online.
  • 03:08I talked about Steven, Paul's son.
  • 03:11His wife Mimi and Paul's daughter
  • 03:13Janice and son Peter are online.
  • 03:16So this is a very special grand rounds.
  • 03:19We have a plaque for you, Steve.
  • 03:22I don't know if it arrived yet.
  • 03:23It has to get to NCI security.
  • 03:25But what I'm going to do now is I'm
  • 03:27going to turn it over to Vince De Vita
  • 03:28who needs a little introduction here,
  • 03:30but certainly another father of oncology
  • 03:33and actually Paul's good friend.
  • 03:35And I'm going to let Vince come up,
  • 03:37introduce the you Steven,
  • 03:38and then we'll do a quick photo
  • 03:39with you in the background.
  • 03:41We'll figure out how to do a
  • 03:42hybrid photo and then we'll give
  • 03:43the time to you for your talk.
  • 03:45Vince.
  • 03:58Yeah, My welcome to the Calabresi family.
  • 04:01It's always a pleasure to see
  • 04:03you here and reminisce about my
  • 04:06old friend and my mentor, Paul.
  • 04:08I'm sure he's up there looking
  • 04:10down saying this is great.
  • 04:14And it's a real pleasure to
  • 04:16introduce my longtime friend
  • 04:17and colleague Steve Rosenberg.
  • 04:19I met Steve in 1974 when
  • 04:23he arrived fully formed.
  • 04:25As the new chief of the surgery brands
  • 04:27right out of his training program,
  • 04:29this caused quite a stir because
  • 04:32the old administration of surgeons
  • 04:35were oldfashioned and their motto
  • 04:37was if you can't go wide, go deep.
  • 04:39And and Steve was a thinking surgeon,
  • 04:42which immediately changed the
  • 04:44ability to collaborate and to
  • 04:46consult with the surgery department.
  • 04:47It was a fun time for the he also came
  • 04:52with his passion for immunotherapy.
  • 04:54And in the book he was to write a
  • 04:59lot later he describes the the source
  • 05:02of his passion in immunotherapy.
  • 05:04It was a patient he operated on in 1968
  • 05:07who came in with right up a quadrant pain,
  • 05:10had a non visualizing gallbladder,
  • 05:12was all set to go to operation.
  • 05:14And Steve reviewed his old charts and he had
  • 05:17come in 12 years earlier with belly pain.
  • 05:20He was operated on a big masses of
  • 05:22tumor with metastasis to the liver.
  • 05:25And here he was 12 years
  • 05:26later he was supposed to die.
  • 05:27Few months later he was 12
  • 05:29years later he was fine.
  • 05:30Steve thought this was a powerful expression
  • 05:33of the immunotherapy and he wanted to
  • 05:36find out how we could harness this
  • 05:38work. And since then, with
  • 05:42fierce intensity, he has worked in
  • 05:45the immunotherapy field and he has
  • 05:49unwavering focus and stayed on this.
  • 05:52Doing work in vitro and then in
  • 05:54animals and then repeating the animal
  • 05:56studies in humans to the point where
  • 05:58he's become the lead investigator
  • 06:00in the world in immunotherapy,
  • 06:03having either discovered or developed
  • 06:05all of the things that have been
  • 06:08done in immunotherapy that are now
  • 06:10making us very excited in the clinic.
  • 06:13And since we're talking about
  • 06:15fathers of programs,
  • 06:16I would sort of view Steve as the
  • 06:18father of the immunotherapy of cancer.
  • 06:21He got his bachelor's degree and
  • 06:24his MD degree from Johns Hopkins.
  • 06:26He's got his PhD from biophysics
  • 06:29from Harvard,
  • 06:31and he spent his time in Boston at the
  • 06:33Peter Ben Brigham getting a surgical
  • 06:36training under the famous Brandy Moore.
  • 06:38And then during that time he'd spent two
  • 06:41years coming to the clinical associate
  • 06:43at the National Cancer Institute.
  • 06:45I also started as a clinical associate.
  • 06:47We used to refer to ourselves
  • 06:49as the Yellow Berets.
  • 06:51Because it was a Vietnam War
  • 06:53and we got our military credit
  • 06:56without any of the gunfire.
  • 06:59Steve may forgive me for not
  • 07:01going over his honors and awards.
  • 07:03They're just too many.
  • 07:05I stopped counting 80.
  • 07:08And finally,
  • 07:09I've been working with Steve on
  • 07:11the textbook answer Principles of
  • 07:13Practice of Oncology for 42 years.
  • 07:16He and I are two of the three editors,
  • 07:19and it has been quite an experience.
  • 07:21The reason the book has risen to the
  • 07:24most popular Kansas text in the world is
  • 07:27of the fierce competitiveness amongst
  • 07:30the editors in preparing the book,
  • 07:33making sure that we each,
  • 07:35the other guy,
  • 07:36was doing all the things he had to do.
  • 07:38And of all the editors,
  • 07:40Steve was the most competitive and not
  • 07:43just a little story about to illustrate that.
  • 07:46The publishers took us away,
  • 07:49reached new addition a one week
  • 07:52before to set the table of contents
  • 07:55and pick the authors and invite
  • 07:57them and at the end the second week.
  • 07:59And so we work very hard during those days,
  • 08:02getting up at 7:00 in the morning
  • 08:04work until five and at the end
  • 08:06of the day we would, you know,
  • 08:08do our exercise and relax.
  • 08:10And Sam Helman,
  • 08:12at that time you played tennis.
  • 08:15I jogged and Steve, not so much.
  • 08:18Steve wasn't really into exercise
  • 08:21or healthy diet at the time.
  • 08:23So much to my surprise at the
  • 08:25end of one day when he said you
  • 08:27mind if I jog with you?
  • 08:29And so I said no with a
  • 08:31little smile on my face.
  • 08:32Off we went,
  • 08:33me and my running shorts
  • 08:34and my New Balance shoes.
  • 08:36Steve and his khaki pants and tennis
  • 08:39or sneakers more than and we started
  • 08:42running and after a little while I.
  • 08:45Ratcheted it up and Steve ratcheted it up.
  • 08:48And a little while I did some more
  • 08:50and Steve ratcheted up some more and
  • 08:53pretty soon we were sprinting as
  • 08:55fast as we could with our heads down,
  • 08:57not to some specified gold,
  • 09:00but clearly to see who
  • 09:03would collapse first.
  • 09:04And Steve Rosenberg.
  • 09:07The the unconditioned Steve Rosenberg.
  • 09:11Collapsed about four seconds
  • 09:14before the conditioned.
  • 09:15Vince Devita.
  • 09:18And I tell you, ladies and gentlemen,
  • 09:20that's the last time I beat
  • 09:22Steve Rosenberg at anything.
  • 09:25His talk today is entitled The Lymphocyte,
  • 09:28the Living Drug for the Treatment
  • 09:31of Cancer Doctor Rosenberg.
  • 09:38Well, this is a unique pleasure
  • 09:41for me for several reasons.
  • 09:46It's a pleasure to honor Paul
  • 09:50Calabresi and his family.
  • 09:52Paul a giant in the field of medical
  • 09:56oncology, but also to present
  • 10:01in front of Vince De Vita who.
  • 10:04Has played such an important role in
  • 10:06my ability to do a lot of this work.
  • 10:09Vince is a true giant in the
  • 10:12field of of oncology and his
  • 10:15contributions are known to to you all.
  • 10:20But when I started working at the NCI
  • 10:23trying to develop immunotherapies
  • 10:25for treatment of cancer,
  • 10:27there was not a lot of enthusiasm for it.
  • 10:29But as I initially began to get results.
  • 10:33I remember going to Vince De Vita and saying,
  • 10:36look, I think there's something here
  • 10:39and I'm going to need more resources.
  • 10:42And in a a remarkably generous way,
  • 10:46I was given by Vince De Vita
  • 10:50probably over the objection of many,
  • 10:52I know over the objection of some others,
  • 10:55was given the space and money and
  • 10:57resources to conduct the kinds of
  • 10:59studies that I'll be talking about today.
  • 11:01And it made a huge difference.
  • 11:03To me, we became friends for the past
  • 11:0847 years we worked in a textbook,
  • 11:11Vince's the soul of that textbook and
  • 11:15has led the the process for now through
  • 11:191212 generations of the of the book.
  • 11:22And so to be here to honor Paul Calabresi,
  • 11:25to honor Vince De Vita.
  • 11:28Doctor Weiner,
  • 11:29thank you so much for the invitation to
  • 11:32to come and deliver these remarks today.
  • 11:37So I'll be talking about lymphocytes as a
  • 11:40living drug for the treatment of cancer,
  • 11:42The use of lymphocytes in much the same
  • 11:44way that we might use chemotherapy or other
  • 11:47targeted agents to administer the to the
  • 11:50patient to try to impact on the on the tumor.
  • 11:54And I'll be talking about this
  • 11:56particular kind of immunotherapy and
  • 11:59that is cell transfer immunotherapy
  • 12:02that has many advantages.
  • 12:04One, if we're going to use a
  • 12:05lymphocyte as a drug,
  • 12:06we can grow lymphocytes easily to
  • 12:0810 of the 11 cells or more and
  • 12:11administer very high large numbers
  • 12:13of highly selected cells because we
  • 12:16have the reagent in the test tube.
  • 12:19We can potentially identify the exact
  • 12:21subpopulations and effector functions that
  • 12:24are required for the cancer regression.
  • 12:26And 3rd and very importantly,
  • 12:28we can manipulate the host prior
  • 12:30to the cell transfer in a way that
  • 12:33you cannot do with other forms of
  • 12:35immunotherapy because the cells to be
  • 12:37used are outside the body and we can
  • 12:40therefore alter the microenvironment
  • 12:43of the tumor in ways that will enable.
  • 12:48Immune cells to enter into those
  • 12:51tumors and destroy them.
  • 12:53And so it's the cell therapy that
  • 12:56I'm going to emphasize this morning.
  • 13:03Now cells carry a conventional T cell
  • 13:05receptor and the entire function of
  • 13:08the lymphocyte is dependent on that T
  • 13:10cell receptor to recognize its antigen.
  • 13:13Which in conventional forms for CD8
  • 13:15or CD4 cells, is a processed peptide
  • 13:18coming from inside the cell and put
  • 13:21on the patient's own MHC molecule.
  • 13:24But a little over a decade ago,
  • 13:26chimeric antigen receptors were described
  • 13:31and at the Weitzman Institute.
  • 13:34And that converts A lymphocyte into the
  • 13:37recognition of an antibody not based
  • 13:40on the conventional T cell receptor.
  • 13:42But by making a single chain of
  • 13:45the heavy and light chains of an
  • 13:47antibody and connecting it to
  • 13:50intracellular signaling domains,
  • 13:51we can then use that lymphocyte to
  • 13:55become recognition based on an antibody
  • 13:59rather than on a T cell receptor.
  • 14:02It can recognize cell surface
  • 14:04molecules based on this antibody.
  • 14:07Recognition.
  • 14:07And so it provides us with a whole
  • 14:10other way to identify, identify targets.
  • 14:15And I'd like to spend just a moment on
  • 14:17CAR T cells because although they've
  • 14:19had substantial activity in the
  • 14:21treatment of the hematologic cancers,
  • 14:23they have not had activity against
  • 14:26the solid tumors.
  • 14:28And what's the reason for that?
  • 14:29Well, CAR T cells require the use of
  • 14:32monoclonal antibodies that recognize
  • 14:33molecules on the cell surface.
  • 14:35And they were described by Kohler
  • 14:38and Milstein over 45 years ago.
  • 14:40And despite extraordinary work,
  • 14:41there's not been found a monoclonal
  • 14:44antibody that can distinguish A
  • 14:46malignant from a normal cell.
  • 14:49The antibodies can have a lot of
  • 14:50influence by reacting with cells.
  • 14:51Surface molecules that can affect cell
  • 14:54signaling can affect cell growth.
  • 14:56But we do not have antibodies
  • 14:58that are unique to a cancer.
  • 15:03And that's a problem,
  • 15:04because it's just as easy to kill
  • 15:07a normal cell as a cancer cell,
  • 15:09and we've seen deaths due to
  • 15:11the application of cells that
  • 15:13do not clearly distinguish
  • 15:15between a tumor in a normal cell.
  • 15:17Normal cells are highly,
  • 15:20exquisitely sensitive to.
  • 15:23The expression of monoclonal
  • 15:25antibodies and using ones that
  • 15:27can attack normal cells have
  • 15:29major clinical toxicities and
  • 15:32thus the limitation of cars for
  • 15:35solid tumors is substantial,
  • 15:37and there are as yet now no
  • 15:41known CAR T cell treatments that
  • 15:43are capable of treating in a
  • 15:46reproducible fashion malignant cells.
  • 15:50They are, however.
  • 15:52Potentially very valuable for the
  • 15:55treatment of humanologic malignancies.
  • 15:56And back in 2009, we reported the
  • 16:00first patient to be treated with a
  • 16:03cell therapy that finally got approved
  • 16:05by the Food and Drug Administration.
  • 16:06The only cell therapy now approved and
  • 16:09I'll just spend a moment talking about it.
  • 16:12We had developed models showing we could
  • 16:16treat syngenetic tumors by targeting CD19.
  • 16:19A molecule on virtually all B
  • 16:21cells and B cell malignancies.
  • 16:23We saw a patient with an aggressive
  • 16:26lymphoma in the way it behaved as
  • 16:28you can as you'll see his Xrays,
  • 16:30he's had multiple chemotherapies,
  • 16:33vaccines, checkpoint modulators,
  • 16:35more chemotherapy and finally came to
  • 16:37us in May in 2009 for treatment with.
  • 16:40His own T cells that were genetically
  • 16:43modified with a chimeric antigen receptor
  • 16:46that could recognize CD19 and this is
  • 16:49what his X-ray look like when we treated him.
  • 16:53You can see large masses directed
  • 16:56by these yellow arrows in his
  • 16:59media stymum in his axilla.
  • 17:01Large mediastinal mass, huge spleens,
  • 17:04lymph nodes surrounding
  • 17:05his vena cava and aorta,
  • 17:07huge iliac vessels.
  • 17:09We treated him.
  • 17:11All of his tumor disappeared over
  • 17:15the course of a few months and he
  • 17:17remains disease free to the present.
  • 17:20To the present time.
  • 17:23He had bone marrow replaced which also
  • 17:28disappeared. But you pay the price
  • 17:32because normal cells can also be killed
  • 17:34and B cells disappeared at a time when
  • 17:37normal T cells and natural killer cells
  • 17:39were returning over the course of the
  • 17:42week and 1/2 after the cell infusion.
  • 17:44It took eight or nine months for the
  • 17:47precursors that were not destroyed to to
  • 17:49restore B cells in the in the patient.
  • 17:52But patients can be can survive
  • 17:54for long periods of time in the
  • 17:57absence of any of any B cells.
  • 18:01Well, we treated the 1st 10 patients,
  • 18:03six of them responded.
  • 18:05Five of them are still responding to
  • 18:07the present day over 10 years later.
  • 18:10And in the surgery branch we
  • 18:12received these kinds of results.
  • 18:14We had objective responses by 47 percent.
  • 18:1742% are ongoing and have never recurred out,
  • 18:21with median survivals now beyond eight years.
  • 18:26A good friend of mine, Ari Beldegrand,
  • 18:28had been in my lab 20 years earlier.
  • 18:31We had remained friends and he heard
  • 18:33about some of these responses and after
  • 18:36we had had six complete responders,
  • 18:37he contacted me and said he
  • 18:39wanted to start a company,
  • 18:41Kite Pharma, who went on to do a
  • 18:44multiinstitutional study that almost
  • 18:46exactly reproduced our our results.
  • 18:49We began interacting with Kite
  • 18:51in 2012 through a. A.
  • 18:54A research agreement.
  • 18:56A research and development agreement.
  • 18:59A crater to transfer our technology
  • 19:02to Kite Pharma.
  • 19:03Five years later, they received FDA approval,
  • 19:06along with Novartis,
  • 19:08who had begun working on this a year later.
  • 19:10And in October 2017, Kite,
  • 19:13who has started to do this from nothing,
  • 19:15was told to Gilead Sciences for $11.9
  • 19:18billion and it's now widely available.
  • 19:20This treatment is now widely available
  • 19:23through the United States and Europe
  • 19:24and now beginning in Asia as well.
  • 19:28I think a very proud example of how
  • 19:30findings in an academic and a government
  • 19:33institution can then get translated
  • 19:35to help to help people in in need.
  • 19:41This remains,
  • 19:42however,
  • 19:42the only T cell treatment that
  • 19:45has been approved by the FDA,
  • 19:47although there were several others
  • 19:49that have shown effectiveness
  • 19:50against multiple myeloma that
  • 19:52are have actually just very
  • 19:55recently been been approved.
  • 20:02So here's the problem of
  • 20:04oncology in the United States,
  • 20:06there are about 600,000 cases.
  • 20:09The solid cancers, epithelial cancers
  • 20:12comprise about 90% of all cancers
  • 20:15that cause death in this country,
  • 20:18about 10% of the humanologic cancers.
  • 20:21And the devastating impact of this,
  • 20:23as you can see,
  • 20:24is that one in every two or three
  • 20:26Americans of us will develop an
  • 20:27invasive cancer during our life,
  • 20:29and unless we can find
  • 20:30better ways to treat it,
  • 20:31about one in five will
  • 20:33die of the of the cancer.
  • 20:38And so the major challenge
  • 20:40confronting cancer immunotherapy
  • 20:41today is the development of effective
  • 20:44immunotherapies for patients with
  • 20:46metastatic epithelial solid cancers
  • 20:48that cannot be cured by any available
  • 20:50treatment and result in 90% of all.
  • 20:53Of all cancer deaths,
  • 20:55the checkpoint modulators have had
  • 20:58major impact on some solid tumors like
  • 21:01Melanoma renal cell cancer patients
  • 21:03that have mismatched repair genes.
  • 21:05But the overwhelming majority of
  • 21:08patients with the solid epithelial
  • 21:10cancers do not respond with only
  • 21:12single digit levels of response to the
  • 21:15combined use of checkpoint inhibitors.
  • 21:20So how can we attack these solid
  • 21:22epithelial cancers and I'll talk
  • 21:24mainly about them and but here's a
  • 21:27general cartoon of how we do this.
  • 21:29We excise A tumor.
  • 21:30If you follow me along clockwise,
  • 21:32we follow it excise A tumor.
  • 21:34We grow cells to try to identify cells
  • 21:36with anti tumor activity if we can,
  • 21:39we grow them selectively to large numbers.
  • 21:42We generally infuse 5 * 10 to
  • 21:44the 10th 10 to the 11 cells
  • 21:46and reinfuse them following A.
  • 21:48Non myeloblade of lymphoid depleting
  • 21:51regimen with cyclophosphonine or
  • 21:53fludarabine that will eliminate
  • 21:55T cells for about 8 days before
  • 21:59they normally normally recover.
  • 22:01I'm going to talk primarily
  • 22:03about the epithelial cancers,
  • 22:04but we learned a lot from Melanoma,
  • 22:06so let me spend a moment.
  • 22:07With this lesson,
  • 22:08we treated 192 patients with metastatic
  • 22:11Melanoma with some of these results
  • 22:14that I first showed Vince Stavita
  • 22:16when we had our first lymphocyte
  • 22:18transfer that mediated aggression
  • 22:19of a Melanoma patient in 1988.
  • 22:22As you can see,
  • 22:24we've treated that we did treat
  • 22:25192 patients with their own cells,
  • 22:28their own tumor infiltrating lymphocytes
  • 22:30that we would grow out of the tumor.
  • 22:33Those cells are a sink for
  • 22:35tumor reactive cells.
  • 22:36You can see our objective response
  • 22:38rate by classic recess criteria,
  • 22:39which is the criteria I'll use throughout
  • 22:41this talk with 56% with a quarter
  • 22:44of patients having complete regressions,
  • 22:46only two patients that ever had a
  • 22:49complete regression ever gone on to recur.
  • 22:51The rest of the main disease free
  • 22:53and of these 48 complete responders,
  • 22:56only two patients required
  • 22:57more than a single treatment.
  • 22:59The cells are alive,
  • 23:00they can divide up to 10,000
  • 23:02fold in the first two weeks
  • 23:04after they've been administered.
  • 23:05And that's they patrol the body,
  • 23:07they find,
  • 23:08they find deposits wherever they
  • 23:11wherever the circulation exists.
  • 23:16Well here are our results
  • 23:18in those the overall.
  • 23:19Survival race, progression free
  • 23:22survival race or were about 37%,
  • 23:27but notice the complete responders
  • 23:30very rarely ever recur.
  • 23:32Somehow adoptive cell therapy
  • 23:34appears to eliminate the last
  • 23:36Melanoma cell and so the rest of
  • 23:38the presentation will be on trying
  • 23:40to find factors that we can use
  • 23:42to treat not only Melanoma but
  • 23:45the solid epithelial cancers.
  • 23:46And the first question?
  • 23:47That we'll discuss or what are the
  • 23:50characteristics of the cells that
  • 23:52mediated cancer regression in vivo,
  • 23:56especially to these patients
  • 23:57with Melanoma that have undergone
  • 23:59durable complete regressions.
  • 24:01And to do that we used a high dimensional
  • 24:04single cell transcriptome analysis of
  • 24:06up to 10,000 cells per per patient,
  • 24:09a single very elegant single cell
  • 24:12analysis available 10X from alumina.
  • 24:18Well, because we had a group of patients
  • 24:21that could respond and not respond,
  • 24:23we utilize the single cell
  • 24:26approach to identify the
  • 24:28transcriptome analysis of patients,
  • 24:31comparing responders from non responders.
  • 24:34Because for the first time we had a
  • 24:36group of immunotherapy patients that
  • 24:38were showing this distinction and
  • 24:40when we break all of the lymphocytes.
  • 24:42And their transcriptome analysis
  • 24:44using this these UMAP,
  • 24:46UMAP or typically analysis
  • 24:48using a near neighbor analysis,
  • 24:51you can identify 22 different kinds of
  • 24:54lymphocytes based on their transcriptome,
  • 24:57the messages that they that
  • 25:00they express into proteins.
  • 25:02And there turned out to be one
  • 25:05cluster that seemed to differentiate
  • 25:07responders from non responders.
  • 25:09And when we looked at the transcriptomic
  • 25:12analysis it turned out that only
  • 25:14that cluster cluster number one
  • 25:16could distinguish responding
  • 25:17from non responding patients.
  • 25:19If we looked at the expressed genes
  • 25:22in each of the other 21 clusters,
  • 25:25the responders and the non responders
  • 25:28were virtually identical except in this
  • 25:30cluster that was largely non responders.
  • 25:33It was only cluster number ones
  • 25:36transcriptome that could distinguish.
  • 25:39Responders from non responders and it
  • 25:41turned out that cluster one was highly
  • 25:44enriched in stem like lymphocytes
  • 25:46that do not express CD39 and CD69,
  • 25:50two molecules of lymphocyte
  • 25:53activation and differentiation.
  • 25:57Well,
  • 25:57it appeared therefore that maybe these
  • 26:00CD3969 stem like lymphocytes were
  • 26:02the ones that were most responsible.
  • 26:04For the Melanoma regressions,
  • 26:06because when we looked at the survival
  • 26:09of patients receiving either very
  • 26:11high or low total numbers of cells,
  • 26:14there was no statistical difference
  • 26:16in the outcome of those patients.
  • 26:18But if we now looked at patients
  • 26:21that got either high or low
  • 26:22double negative CD6939,
  • 26:25double negative stem like cells.
  • 26:27There was a highly significant difference
  • 26:30between the cells that were respond,
  • 26:32the patients that were responding to
  • 26:34not responding based on the number
  • 26:37of these double navigative cells
  • 26:38that they that they received highly
  • 26:42statistically significant well.
  • 26:45When we looked at the properties of
  • 26:46these cells, they were true stem cells.
  • 26:48If you divide a lymphocyte
  • 26:51population of till and facts based
  • 26:53on CD39 and 69 expection,
  • 26:55the double positive cells.
  • 26:57When isolated and grow will only
  • 26:59reconstitute themselves double positive.
  • 27:01But when you take the double negative
  • 27:05cells they reconstitute themselves
  • 27:07whereas the double positive cells do not.
  • 27:09They are true stem like cells
  • 27:11when you take cells in one of
  • 27:14our trials targeting Nye cell,
  • 27:16one antigen you can see.
  • 27:19In red,
  • 27:20the double negative cells from the
  • 27:22infusion continued to sustain themselves
  • 27:24as they grew in vitro and were re
  • 27:27stimulated one time after another,
  • 27:29whereas the double positive cells
  • 27:34disappeared as they grew.
  • 27:35They were not stem like,
  • 27:37they could not reproduce their
  • 27:39themselves with their own.
  • 27:41Native reactivities and in fact if
  • 27:43you look at the actual transcriptomes,
  • 27:45it is a stem like markers like K
  • 27:50LF2TCF7CD62L that were expressed
  • 27:53in the response associated culture.
  • 27:56And if you then took this back to the
  • 27:58mouse models that we had initially
  • 28:00studied female mouse model of Melanoma,
  • 28:04you can see that in fact.
  • 28:07These cells when implanted and allowed
  • 28:09to grow for 10 days before treatment
  • 28:11started peripheral blood, they grew.
  • 28:13If you gave double positive cells,
  • 28:15they had some weak reactivity.
  • 28:18But if you gave double negative cells at
  • 28:20two different concentrations including this
  • 28:22very low concentration of 500,000 cells,
  • 28:25the double negative cells could
  • 28:27mediate dramatic anti tumor effects
  • 28:29compared to the bulk populations
  • 28:31and so we could thus identify.
  • 28:34These stem like cells that had a profound
  • 28:38reactivity and published that about two
  • 28:42years ago and have been utilizing it.
  • 28:46We'll talk about some of the
  • 28:47results in the epithelial cancers.
  • 28:49But very recently and in this
  • 28:51unpublished data,
  • 28:52we found that we could actually
  • 28:54make the double positive cells that
  • 28:56were fairly weak work much better if
  • 28:58we could give them a vaccine that
  • 29:00was targeting the same antigens
  • 29:02that the cells were targeting.
  • 29:04And you can see here if we take the
  • 29:06double positive cells which are the most
  • 29:08exhausted of the cells and give them,
  • 29:10they do have some reactivity
  • 29:12compared to the control.
  • 29:14But when you give the double positive,
  • 29:16the double neck,
  • 29:17these double positive cells
  • 29:19in conjunction with a vaccine,
  • 29:20you can now make them very active
  • 29:22and take even 1 centimeter tumors,
  • 29:2520% of the total.
  • 29:285% of the total body weight of the
  • 29:30mouse to disappear completely and
  • 29:33that's something that we're now clinical
  • 29:35trial that we're now initiating.
  • 29:50So we know the kind of cell we want to use.
  • 29:52But what did the till actually recognize
  • 29:55that enables the in vivo control in the
  • 29:58last Melanoma cell And the fact that we
  • 30:00have seen specific regression of cancer
  • 30:02in the absence of any on target but off
  • 30:05tumor toxicities led us to believe.
  • 30:08That we were targeting something completely
  • 30:10unique to cancers and those were the
  • 30:13targets of cancer mutations that we
  • 30:15suspected were the CAR targets of the till.
  • 30:18And so again, to identify the target,
  • 30:21we have to identify this small peptide
  • 30:23that comes from an intracellular
  • 30:24molecule or a molecule that's been
  • 30:26ingested by the cell that can then
  • 30:28be presented to the T cell receptor.
  • 30:32And so about five years ago,
  • 30:33we developed this particular
  • 30:35blueprint for the identification.
  • 30:37Of cells that were recognized by Till
  • 30:40that could mediate tumor regressions.
  • 30:42And what do we do?
  • 30:43If you follow me counterclockwise,
  • 30:45we excise A tumor,
  • 30:47isolate the TILL and extract DNA&RNA from
  • 30:52that till and do whole exome sequencing
  • 30:55so that we could identify every cancer
  • 30:58mutation that was present in that cell.
  • 31:00And we do RN A/C to identify
  • 31:02all the mRNA molecules as well.
  • 31:05We then take those.
  • 31:08Cancer mutations as 25 more molecules
  • 31:11and either as peptides or as mini
  • 31:14genes put together in a tandem
  • 31:16structure to form a tandem mini
  • 31:18gene and put it into a patient's
  • 31:21own antigen presenting cell.
  • 31:23Now that antigen presenting cell
  • 31:24contains all of the MHC molecules of
  • 31:27the patient and if any of these cancer
  • 31:29mutations can then be presented.
  • 31:33On the antigen presenting cell and
  • 31:36recognized by the T cell receptor
  • 31:38of till that forms a signal in
  • 31:41the lymphocyte that enables us to
  • 31:43identify it because of upregulation
  • 31:45of activation markers and we could
  • 31:48then grow those cells selectively.
  • 31:50So again the key is to make a 25 more
  • 31:52peptide with the mutation in the middle
  • 31:55so that any peptide that could be
  • 31:58presented on the MHC surface is concluded.
  • 32:01It could either be the last.
  • 32:03Amino acid of the peptide that's presented,
  • 32:05or the first one,
  • 32:06but it has to be in this 25.
  • 32:08And the advantage of this is there's no
  • 32:10need to do any predicted peptide binding.
  • 32:14Every candidate peptide and all
  • 32:15MHC loci are included in the screen
  • 32:18because both have to be recognized
  • 32:20the peptide on the MHC and there's
  • 32:22no tumor cell lines necessary.
  • 32:23And as you know,
  • 32:24it's very hard to grow tumor cell
  • 32:26lines for most of the epithelial
  • 32:28epithelial cancers.
  • 32:32This can be done within about
  • 32:34two to three weeks,
  • 32:35takes 10 days to do the
  • 32:39to identify all of the
  • 32:40cancer mutation sequences,
  • 32:41another few days to do the
  • 32:44bioinformatic informatic analyses.
  • 32:45And so one has all this information available
  • 32:48within two weeks of the tumor resection.
  • 32:51Well, we started in Melanoma
  • 32:54and evaluated 86 patients.
  • 32:56Those tumors have more mutations
  • 32:58in most 556 as a median.
  • 33:01We screened every mutation that was
  • 33:04expressed that was expressed in RN A/C
  • 33:0715,000 mutations in these 86 patients
  • 33:09to see if any could be recognized by
  • 33:12the patient's own autologous T cell.
  • 33:14So we looked at 218 immunogenic
  • 33:18epitopes 85% of patients could recognize
  • 33:20their own tumor cells based on.
  • 33:22Recognition of these mutations.
  • 33:25Interestingly,
  • 33:25only 1.4% of the mutations could
  • 33:28be recognized because they had it
  • 33:30been cleaved and also presented
  • 33:32on the Mac molecule.
  • 33:33Of that particular patient,
  • 33:3692% were CD8 cells rather than CD Fours.
  • 33:39And our first surprise every
  • 33:42NEO antigen that we recognized,
  • 33:44all 218 were unique to the
  • 33:47individual patient.
  • 33:48Patient's cancer and recognized
  • 33:50by that patient,
  • 33:51none were shared between 2 Melanoma patients.
  • 33:55Well,
  • 33:55we then did this for 130
  • 33:57consecutive gastrointestinal cancers
  • 33:59screened over 15,000.
  • 34:00Of the expressed mutations,
  • 34:031.3% were recognized interestingly
  • 34:05half by CD8 and CD4 cells.
  • 34:08And for the first time we found
  • 34:10an antigen that was recognized
  • 34:11in more than one patient.
  • 34:13It was a KRAS mutation restricted by a
  • 34:16fairly unusual CW8O2 Class 1 molecule.
  • 34:20The other hundred 209 epitopes
  • 34:22that were found were all unique to
  • 34:25the individual individual patient.
  • 34:30True in breast cancer that
  • 34:32we just published last year,
  • 34:3343 consecutive patients 100 immunogenic
  • 34:37epitopes 2.1% were recognized of the
  • 34:40mutations recognized half by mainly by
  • 34:43CD Fours and all were absolutely unique.
  • 34:46And here is an updated as of last September
  • 34:50study of 205 consecutive patients and
  • 34:52note we're talking about the GI cancers,
  • 34:55breast cancer, lung cancer, Gastro,
  • 34:57Gu cancers like ovarian and prostate.
  • 35:00And across the board as you can see
  • 35:04about 70 to 80% of the patients contain
  • 35:08T cells that would recognize their own.
  • 35:13Neo antigens their own cancer mutations that
  • 35:16were presented on their autologous cancer
  • 35:19cells and of this 363 neo antigens we found,
  • 35:23we only found this one K Ras that was
  • 35:26recognized by more than one patient found on
  • 35:29this particular on this particular screen.
  • 35:33Now an advantage of targeting mutations is
  • 35:35its applicability to target multiple cancer.
  • 35:38Types, because we're targeting mutations
  • 35:40and most cancers have mutations,
  • 35:42some more than others.
  • 35:43But let me show you examples of what we've
  • 35:47been able to see an individual patients.
  • 35:51Most do not respond.
  • 35:52I'll show you the overall results soon,
  • 35:55but here are examples of individual
  • 35:58cancers that can respond.
  • 36:00Interestingly, the first patient that
  • 36:02responded to T cells that were unique,
  • 36:04that were identified as uniquely
  • 36:06responsive to our own mutation,
  • 36:08it was under a B2 mutation,
  • 36:10was a 4045 year old woman
  • 36:13with a clangiocarcinoma.
  • 36:14Bile duct cancer had undergone A hepatectomy,
  • 36:17multiple chemotherapy regimens,
  • 36:18developed lung and liver metastases.
  • 36:21We treated her with unselected till
  • 36:23much as we did in Melanoma that does
  • 36:25not work for the epithelial cancers.
  • 36:30Unselected till do work in Melanoma,
  • 36:34but you have to select the
  • 36:36specific ones which are much
  • 36:37rarer in the epithelial cancers.
  • 36:40We gave her those,
  • 36:40she didn't respond. However,
  • 36:42when we use our Tandeminy gene approach,
  • 36:44she had 26 mutations.
  • 36:45We could found that her B2IP
  • 36:47mutation that she recognized it
  • 36:51contained almost 90% the infusion
  • 36:54bag of cells recognized as mutation.
  • 36:57And she underwent a complete
  • 36:59regression of all of her cancer.
  • 37:01You can see her lung cancers
  • 37:06gone. She had three liver metastatic
  • 37:10deposits that disappeared and
  • 37:13she remains now disease free.
  • 37:16Almost 10 years, 10 years later,
  • 37:20this woman who had a metastatic
  • 37:22breast cancer, had been through seven
  • 37:24different treatments for her metastatic
  • 37:27disease to multiple groups, chest,
  • 37:29wall, bone, multiple nodal groups.
  • 37:32She came to us, received cells for treatment.
  • 37:36She received four different what
  • 37:38appeared to be random somatic mutations.
  • 37:40There's no driver function involved in these.
  • 37:45And there was redundancy in the T cell
  • 37:48receptors that we used to treat her.
  • 37:51But by treating these four now random
  • 37:54somatic mutations, she underwent a
  • 37:56complete regression of this lesion
  • 37:57beginning to grow through the cell wall.
  • 37:59You can see multiple liver metastases.
  • 38:01She had many more which disappeared.
  • 38:03And she's over five years later now
  • 38:06completely disease, disease free.
  • 38:07This patient with a metastatic cervical
  • 38:10cancer that was very aggressive and
  • 38:13fungating into her into her vagina.
  • 38:15Underwent resection radiation
  • 38:19therapy and cisplatin chemotherapy.
  • 38:22Underwent our hysterectomy
  • 38:23and excision of both ovaries.
  • 38:26She developed liver, lymph node,
  • 38:28intra abdominal Mets including one
  • 38:30that was obstructing her ureter.
  • 38:31Came to us for treatment with our own till.
  • 38:34You can see these lymph nodes
  • 38:36which disappeared.
  • 38:36This chest wall lesion disappearing
  • 38:39this one as well.
  • 38:40This node was obstructing her ureter.
  • 38:42We put in a urinary catheter.
  • 38:45A a ureteral catheter.
  • 38:46When our tumor went away we
  • 38:48could take it out.
  • 38:49She remains disease free.
  • 38:51Now over seven years later this patient
  • 38:55with colorectal cancer was the one
  • 38:57in which we found the KRS receptor.
  • 38:59It had a colectomy was invading her
  • 39:02bladder she so it was very aggressive.
  • 39:04We resected 2 lung metastasis.
  • 39:06She had seven others treated her and.
  • 39:09Almost all of our tumors disappeared.
  • 39:12She had seven lesions,
  • 39:14six of which disappeared.
  • 39:16This one did not disappear and continued
  • 39:20to grow and where we resected it.
  • 39:22We learned that in fact,
  • 39:24by looking at copy number
  • 39:26analysis of the chromosomes,
  • 39:27she had lost one chromosome from chromosome 6
  • 39:30and that chromosome and codes MHC molecules,
  • 39:33including her restricting element.
  • 39:35Therefore,
  • 39:35that tumor could escape.
  • 39:37And when we then went on to
  • 39:41resect her that one lesion,
  • 39:44she has not occurred since and remains
  • 39:47disease free over six years later.
  • 39:49We can see responses in pancreatic cancer
  • 39:52as you can see this very dramatic.
  • 39:54Response which I show you.
  • 39:56It was a very recent patient
  • 39:59who had what appeared to be
  • 40:00almost a complete regression of
  • 40:02multiple liver methass disease.
  • 40:03But unfortunately within three
  • 40:05months this patient didn't recur.
  • 40:07And when we biopsied one of the lesions,
  • 40:09he had lost expression of his target
  • 40:12molecule which turned out to be
  • 40:14P53 and a molecule that we'll hear
  • 40:17about in a few moments longer.
  • 40:21Well, we've now treated a little over
  • 40:24100 patients with epithelial cancers.
  • 40:26Again, it's the ducts in these
  • 40:28organs that provide the source of
  • 40:30mutations that are turning over
  • 40:32constantly and as mistakes are made,
  • 40:34mutations appear and those
  • 40:36are the ones we're targeting.
  • 40:39If you use bulk till in patients with
  • 40:42epithelial cancers who are chemo,
  • 40:44fract, chemo refractory,
  • 40:45we do not see responses in 21 patients,
  • 40:48but when we started to select these till.
  • 40:52And treated 81 patients,
  • 40:5517% of them have responded.
  • 40:57I've shown you some of them.
  • 40:58These are all patients
  • 41:00that are chemo refractory.
  • 41:02Many had had checkpoint modulators
  • 41:03which do not work in these
  • 41:05tumors and had not responded and.
  • 41:09We have a long ways to go,
  • 41:11but these 17 patients at least
  • 41:14show us that this is possible as
  • 41:16we continue to refine and learn
  • 41:19how to treat these patients.
  • 41:20For the refractory epithelial cancers,
  • 41:24well, there were two hypotheses
  • 41:25that come from this.
  • 41:26First,
  • 41:27it appears to be the recognition
  • 41:29of random somatic mutations.
  • 41:30It's a final common pathway that
  • 41:32explains cancer aggression for most,
  • 41:34if not all immuno therapies.
  • 41:37We finally understand what a cancer
  • 41:40antigen is and as we now look at the
  • 41:43variety of chemother of immunotherapies,
  • 41:45it's now been shown for anti C2A4,
  • 41:47we're studying it fertil tumor
  • 41:50infiltrating lymphocytes as well.
  • 41:52What is a cancer antigen?
  • 41:54It's any intracellular protein
  • 41:56that could potentially be a cancer
  • 41:58antigen if it's mutated and processed
  • 42:01intracellulally to a peptide that
  • 42:04combined to the autologous MHC molecule.
  • 42:06About one in every seventy of these
  • 42:09mutated NEO epitopes are NEO antigens
  • 42:12and there's good news and bad news.
  • 42:14The bad news is that this will have to
  • 42:16be a very highly personalized treatment
  • 42:18after over taking a patient's own cells.
  • 42:21We're targeting A mutation that's
  • 42:24unique to his own tumor and will
  • 42:27therefore be complex to administer.
  • 42:30The good news is that virtually all
  • 42:32cancer patients are potentially eligible
  • 42:34because they all have mutations.
  • 42:36And some more than others.
  • 42:38So the opportunity does exist to
  • 42:41further deliver this treatment and
  • 42:44the complexity will be difficult.
  • 42:46But then again,
  • 42:47I heard that in the early days of
  • 42:49our development of CAR T cells,
  • 42:50several groups came through large
  • 42:52pharmaceutical companies saying,
  • 42:53hey, if we had this disease,
  • 42:55we'd come to you,
  • 42:56but we don't see how to make money doing it.
  • 42:58But I have every confidence that if
  • 42:59we can figure out ways to make it
  • 43:01work and large numbers of patients,
  • 43:03the genius of American industry
  • 43:04will figure out a way to deliver it.
  • 43:08Well there are two main approaches
  • 43:10to using lymphos type transfer
  • 43:11and we've talked about expanding
  • 43:13naturally occurring anti cancer cells.
  • 43:15But because now it becomes so readily usable
  • 43:18to easy to identify T cell receptors,
  • 43:21we can actually identify T cell
  • 43:24receptors into autologous lymphocytes
  • 43:26and expand normal cells and convert
  • 43:28them into anti tumor anti tumor T cells.
  • 43:35We've talked about these non mutated
  • 43:37proteins that are not on normal tissues,
  • 43:40CD19, the unique somatic mutations,
  • 43:43but there are mutations in cancer
  • 43:46driver oncogenes or tumor suppressors
  • 43:48that can be shared among patients.
  • 43:52It's remarkable now that so many different
  • 43:54cancer genomes have been sequenced,
  • 43:56how few of these actually exist that are
  • 43:59shared Far and away the most common are KK,
  • 44:02RASS and P53.
  • 44:04KRS expressing 30% of all cancers,
  • 44:0770% of pancreatic cancer,
  • 44:09it's P53 and half of all cancers.
  • 44:12And so we've made efforts to
  • 44:15identify TCRS from patients that
  • 44:17contain these mutations to find T
  • 44:19cell receptors by doing a highly
  • 44:22directed screening using very high
  • 44:24concentrations of these molecules or by
  • 44:27especially by in vitro sensitization.
  • 44:30To identify T cells,
  • 44:32to identify that very tiny number
  • 44:34that do exist in patients that
  • 44:37can recognize K Ras in P53.
  • 44:41And we published about a year and a half
  • 44:44ago a library of T cell receptors that
  • 44:47are CD8 and CD4 that can recognize K Ras,
  • 44:51the common K Ras hotspot mutations.
  • 44:55Over 80% of OK Ras mutations
  • 44:58occur at three different hotspots,
  • 45:00GG12DG12V and G6 and the 60 oneth
  • 45:06amino acid almost all of them.
  • 45:09However the great majority are
  • 45:10at this K12 and 13 position and
  • 45:13you can see for a variety now of
  • 45:16restriction elements we can identify.
  • 45:19T cell receptors and publish the
  • 45:22sequences of them that can recognize
  • 45:26tumors mutations based on the
  • 45:30recognition of K Ras mutations and a
  • 45:35similar library now of mutations in
  • 45:38K Ras can be recognized by CD4 cells
  • 45:40using a variety of different Class 2
  • 45:43restriction elements And if you look at.
  • 45:46The two libraries that we've now developed,
  • 45:4833% of all patients with K Ras mutations
  • 45:51can potentially be eligible for treatment.
  • 45:54These T cell receptors if we
  • 45:57can learn to use them well,
  • 45:59that led us to the issue of,
  • 46:01well,
  • 46:02what kinds of receptors do we really
  • 46:04want because we can find dozens of
  • 46:07redundant muceptors recognizing the
  • 46:09same exact molecules and there are
  • 46:11a variety of tests that one can
  • 46:13use to test these receptors lytic.
  • 46:15Function, cytokine secretion,
  • 46:16the avidity,
  • 46:17the affinity catch bond techniques.
  • 46:20And so we've gone to try to understand
  • 46:23what T cells do we need so that
  • 46:25we can select the right ones among
  • 46:28the redundant number.
  • 46:29And this brings us back to that patient
  • 46:32with KRAS who was treated with four
  • 46:35different receptors all that recognized KRAS,
  • 46:37you can look here at their.
  • 46:40Avidity,
  • 46:40that is they all recognize about
  • 46:43the same concentration of peptide.
  • 46:45But one of these receptors disappeared
  • 46:49immediately upon infusion and this
  • 46:51was a majority receptor given.
  • 46:54Where are three of these receptors
  • 46:56persisted well out beyond the year?
  • 46:58Here are measurements out to 290 days.
  • 47:01There was something very different
  • 47:03about this receptor compared to these.
  • 47:06What was the difference?
  • 47:08The avidity was the same.
  • 47:11We looked at a variety of criteria,
  • 47:16especially surface plasmon resistance,
  • 47:18to measure the exact KD,
  • 47:21the association constant of that receptor.
  • 47:23What we did is identify the receptor,
  • 47:25clone it, purified it,
  • 47:27and put it into human cells that were
  • 47:30then used to treat the human tumor
  • 47:33and immunosuppressed mice and Notices
  • 47:361 receptor had the highest affinity.
  • 47:39And was the least active in treating mice.
  • 47:44If you look now at this highest
  • 47:47affinity receptor using a mouse,
  • 47:48a human receptor to treat a human tumor
  • 47:51in a highly immunosuppressed mouse,
  • 47:53it was these lower affinity receptors
  • 47:56which were the most effective.
  • 47:59And so it appears that it's not only the
  • 48:01fitness state of the lymphocyte itself,
  • 48:03but the quality of its receptor
  • 48:05that play a role in anti tumor.
  • 48:08Effectiveness well knowing the
  • 48:13receptor that was developed by Eric Tran who
  • 48:16was a fellow in the laboratory who about
  • 48:19the three years ago moved to Portland.
  • 48:22With Eric, we use this receptor that had
  • 48:25the low affinity that seemed to have
  • 48:28that sweet spot of the recognition to
  • 48:30treat a patient with pancreatic cancer.
  • 48:31It was published in the New England Journal.
  • 48:36What about six months ago and you can
  • 48:41see the regression that was reported
  • 48:45with follow up out to six months
  • 48:48of multiple lung metastases which
  • 48:50shrank in that patient to perform
  • 48:53a substantial partial regression.
  • 48:54We have additional follow up now
  • 48:57that patient did recur at one year
  • 48:59but spent one year disease free
  • 49:01of his pancreatic cancer and we
  • 49:04recently just four months ago.
  • 49:06Treated a patient with pancreatic
  • 49:08cancer utilizing a different set
  • 49:10of key res receptors restricted by
  • 49:12a eleven O 1 which is a class 1MHC
  • 49:16molecule and you can see here this
  • 49:19liver metastases which is almost
  • 49:22disappeared by three months this large
  • 49:25one smaller and by three months almost gone.
  • 49:28We're continuing to follow this
  • 49:30patient but this is an approach.
  • 49:32Using T cell receptors into normal
  • 49:34cells that can potentially be effective,
  • 49:37Peter Kim in the Surgery Branch
  • 49:41a fellow has developed a library
  • 49:44mainly using in vitro sensitization
  • 49:47to target P53 molecules.
  • 49:49This was published about six months ago
  • 49:54in Clinical Clinical Cancer Immunology
  • 49:57Research and again these receptors.
  • 50:00Now with some common Class 1 molecules,
  • 50:04O2,
  • 50:04O1 can potentially treat about 5
  • 50:071/2% of all patients with K Ras
  • 50:09mutations and again 50% of all cancer
  • 50:12patients have K Ras mutations.
  • 50:15Well, we could again identify the
  • 50:18T cell receptors that were most
  • 50:20common in recognizing P53 and
  • 50:25recognizing tumors that contain P53.
  • 50:29We isolated those T cell.
  • 50:31Receptors that you uniquely recognize
  • 50:34P53 recognizing tumors and again
  • 50:39studied each one of these 5-6 receptors
  • 50:43that we could find to see which
  • 50:45were most effective and one of them
  • 50:49was more effective than the rest.
  • 50:52Although at high concentrations many
  • 50:54others began to work as well in terms
  • 50:57of cursing in the regression of a
  • 50:59human tumor in a in a in a mouse.
  • 51:01Using human receptors at 27 cells,
  • 51:04you could see many,
  • 51:05several of the receptors were active.
  • 51:08But when you went down to 1/5 of
  • 51:10that a 2E6A tiny number of cells,
  • 51:12this one receptor was most effective
  • 51:14and it was the receptor with
  • 51:16an intermediate affinity.
  • 51:18And so as we continue these experiments,
  • 51:20we're beginning to learn which
  • 51:22kind of receptors we we need.
  • 51:24Well,
  • 51:24having identified that a patient who came in.
  • 51:28With breast cancer,
  • 51:29we've been through multiple chemotherapies
  • 51:32with the highly advanced disease was
  • 51:35treated with our own cells that were
  • 51:38transduced with a high affinity.
  • 51:42Excuse me,
  • 51:42a high avidity but not a high
  • 51:45affinity T cell receptor.
  • 51:47She had very aggressive disease including
  • 51:49a pericardium that was replaced by tumor.
  • 51:52We know that because a week before
  • 51:54we treated her we had to perform a
  • 51:56pericardial window to release fluid
  • 51:58from inside the pericardium and all
  • 51:59of the biopsies here were positive.
  • 52:01She had pleural effusions.
  • 52:02She had tumor covering her her breast
  • 52:06and extending into the into the other breast.
  • 52:09She was treated with our own cells that.
  • 52:12Had been transduced to express
  • 52:14an anti P53 receptor,
  • 52:16this 175 H receptor that I just mentioned.
  • 52:19Every one of these nodules is a
  • 52:22separate tumor deposit at a large
  • 52:24necrotic lesion in our breasts.
  • 52:26All of this, everything visible.
  • 52:30Disappeared and you can see here
  • 52:33at the 60 days the way this breast
  • 52:35looked at six months.
  • 52:37However,
  • 52:37she did recur with a nodule that we
  • 52:41biopsied that had an LOHA loss of
  • 52:44heterozygosity at her MHC locust which
  • 52:46enabled this and other lesions to
  • 52:49escape and so she did recur at six months.
  • 52:58So we can use T cell
  • 53:00receptors to treat patients.
  • 53:01And I'll finish with this very
  • 53:04latest finding we just published
  • 53:05about six months ago in the science
  • 53:08and are beginning to exploit.
  • 53:10And that is a very rapid method to
  • 53:13identify cancer reactive T cell
  • 53:15receptors directly from a resected
  • 53:17tumor without having to do all of the
  • 53:20testing to see what they recognize.
  • 53:22So how do we do this?
  • 53:25We use a single cell transcriptome
  • 53:27analysis of lymphocytes
  • 53:29from freshly resected tumor.
  • 53:33In this analysis,
  • 53:34each cell is bar coded with
  • 53:36an individual DNA sequence and
  • 53:38when that individual cell is
  • 53:40sequenced and you can sequence up
  • 53:42to 10,000 cells at a given time,
  • 53:44the transcriptome all the messenger
  • 53:47RN A's can be analyzed and the T
  • 53:50cell resequence identified and each.
  • 53:53Identified in an individual cell
  • 53:57and so we did that.
  • 54:00And if you then break those lymphocytes
  • 54:03into all of the different clusters,
  • 54:06what you can do is the following
  • 54:10because we have the transcriptome
  • 54:15sequence for every individual cell.
  • 54:20And we've identified the T cell
  • 54:22receptors in that patient that
  • 54:23can recognize the tumor because
  • 54:25every time we identify a cell and
  • 54:27all the patients I've showed you,
  • 54:29we can very easily then get to the T
  • 54:32cell receptor using PCR techniques
  • 54:33to clone it out only takes about
  • 54:36the about two weeks if we look
  • 54:38at this cluster and look at the T
  • 54:41cell receptor sequences that we've
  • 54:43identified for this rectal cancer
  • 54:45patient and see what cells they're in.
  • 54:49They quite astonishingly all appear
  • 54:51in a single transcriptome culture
  • 54:56was true for this breast cancer patient.
  • 54:58In this cluster, we take nine cancer
  • 55:01patients from many different histologies.
  • 55:03You can see they all fit in these
  • 55:06clusters and So what that enables us
  • 55:11to do is identify the gene signature.
  • 55:16Of cells in that cluster because
  • 55:18we know the whole transcriptome,
  • 55:19all the MRN A's expressed and could
  • 55:23identify and report on a gene signature
  • 55:26which we published in Science led
  • 55:28interestingly by a B cell antigen CX, CL13.
  • 55:32And when we take now an
  • 55:35unknown patient cluster,
  • 55:37look for that transcriptome sequencing
  • 55:39that we look for those T cell receptors.
  • 55:42Sequences that fit this gene
  • 55:46signature we could then identify.
  • 55:49For unknown samples,
  • 55:51we could identify cells that
  • 55:52contain that gene signature.
  • 55:54And because the cells are bar coded,
  • 55:55we can immediately get to the T
  • 55:58cell receptor sequence and know that
  • 55:59within a few weeks of the resection.
  • 56:02And when we test each of the TC
  • 56:03R's in that signature right now
  • 56:05and we're trying to define that
  • 56:07signature of the CDH cells.
  • 56:10CD62 percent of all of the T cell
  • 56:13receptors that are present in
  • 56:14that cluster are tumor reactive
  • 56:15and we can identify within weeks.
  • 56:17And CD4 cells it's not quite as good
  • 56:20as about 1/3 of the T cell receptors.
  • 56:22Thus anti tumor T cell receptors
  • 56:24can be quickly identified without
  • 56:27extensive screening.
  • 56:28And use for cell therapy and we haven't
  • 56:32haven't published much of this yet
  • 56:34but but in fact are working hard now
  • 56:37to try to improve our ability to use
  • 56:39T cell receptors for for treatment.
  • 56:46Well, I might conclude with this final,
  • 56:49this final slide and leave you with
  • 56:52these few general conclusions.
  • 56:54Cell transfer therapy can mediate
  • 56:56durable regression in patients with
  • 56:58metastatic cancer refractory to
  • 57:00all other treatments that T cells
  • 57:03recognize unique somatic mutations
  • 57:05and common cancers that identification
  • 57:07and targeting these mutations unique
  • 57:10to each cancer or sometimes shared
  • 57:11mutations such as K, RASM, P53.
  • 57:14Have the potential to extend cell
  • 57:16therapy to patients with the common
  • 57:19epithelial cancers using either
  • 57:21these naturally occurring or T
  • 57:23cell receptor transduced cells.
  • 57:25And finally gene signatures can be
  • 57:28generified generated to identify anti
  • 57:31tumor T cell receptors in fresh tumors
  • 57:34as well as identify the phenotype
  • 57:37of lymphocytes that can improve
  • 57:40functions in eliminating tumor in vivo.
  • 57:44Well, I thank you for your very kind,
  • 57:46kind attention.
  • 57:54Thanks, Steve.
  • 57:55That was inspiring and certainly I know
  • 57:59there were a good number of questions.
  • 58:00I know Diane Krauss has a few online.
  • 58:02But as is our tradition
  • 58:03at the Cal Brazi lecture,
  • 58:05we will often turn to Judge
  • 58:06Cal Brazi or Steven to please
  • 58:08ask the first question.
  • 58:15Doctor Colleridge Son or I'm a law
  • 58:18professor Doctor But I wondered,
  • 58:21would the you're talking about have
  • 58:23any applicability to glioma brain
  • 58:27cancer which I know of especially
  • 58:30hard to treat and which may
  • 58:32become much more common
  • 58:34in the future?
  • 58:35Because there is does seem to be
  • 58:37some evidence that cell phone use.
  • 58:39Increases the risk of coming
  • 58:41down with brain cancer.
  • 58:43So I just wondered, is this applicable
  • 58:45to gliola brain, Brain cancers
  • 58:50plus brain cancers.
  • 58:51Glioblastoma is the most aggressive form of
  • 58:55of the brain cancers do express mutations.
  • 58:58We have identified mutations
  • 59:00in glioblastomas. In fact,
  • 59:02we published a paper on that by
  • 59:05VED Leiko who is a fellow in the
  • 59:07in the surgery branch.
  • 59:09Of a mutation in a glioblastoma,
  • 59:11but we have not treated any glioblastoma
  • 59:15patients with these uniquely reactive cells.
  • 59:19We have treated glioblastomas with CAR
  • 59:21T cells targeting a shared mutation.
  • 59:24And so no responses again because
  • 59:27of the the weakness of of cars
  • 59:30and the potential danger that.
  • 59:32Their tumors might express normal
  • 59:34antigens and in a separate
  • 59:35study that I won't go into,
  • 59:37we actually saw substantial toxicities by
  • 59:40targeting a shared antigen and glioblastomas.
  • 59:43But using this new the new cancer antigens
  • 59:48that result from cancer mutations,
  • 59:50I think should be tried in glioblastoma.
  • 59:52But we have not begun those studies yet
  • 59:55and are concentrating on the more common.
  • 59:58Well, common epithelial cancers.
  • 59:59But it's a wonderful,
  • 01:00:01wonderful idea and something that I
  • 01:00:03hope to to get to in a serious way soon.
  • 01:00:08Question. I wonder if we can unmute
  • 01:00:10her so she can ask it herself.
  • 01:00:13While we're doing that, I'll just ask
  • 01:00:14a question from an anonymous attendee.
  • 01:00:16I have a patient with one of
  • 01:00:18the targetable Rasmutations
  • 01:00:19with the appropriate actual a.
  • 01:00:20What can I do for them?
  • 01:00:21How do I send them
  • 01:00:22to you? We're actively seeking,
  • 01:00:24we're actively seeking those
  • 01:00:26patients. And if you e-mail me
  • 01:00:30sar@nih.gov, I'll see that you get
  • 01:00:32contacted immediately about about that
  • 01:00:34patient to evaluate the eligibility of
  • 01:00:36that patient for our studies. Yeah,
  • 01:00:39I'm guessing that was Diane Kraus.
  • 01:00:40So that Eric would see that he has
  • 01:00:41to put more resource into this
  • 01:00:42so that we'll keep them here.
  • 01:00:43He's he's laughing. OK Diane,
  • 01:00:45are you able to ask your question
  • 01:00:46online or do you want me to
  • 01:00:47read it for you? I can ask it. I can ask
  • 01:00:50my question was why?
  • 01:00:52The selected till work when the
  • 01:00:54bulk till do not for some of
  • 01:00:56these patients with solid tumors,
  • 01:00:58is it a matter of the large dose of
  • 01:01:00the effective till or potentially
  • 01:01:02inhibition by other till that
  • 01:01:04aren't targeting the cancer.
  • 01:01:08We have evidence for both and I think
  • 01:01:11both are important in the animal models
  • 01:01:13in the number of cells you give is very
  • 01:01:16highly related to its effectiveness.
  • 01:01:19In the human, although we generally
  • 01:01:21give us very large numbers of cells,
  • 01:01:24even within the numbers of cells we give,
  • 01:01:26which generally are between 10
  • 01:01:27of the 10 and 10 of the 11,
  • 01:01:29we do see an influence of the
  • 01:01:31number of cells in the likelihood
  • 01:01:34of having complete regressions.
  • 01:01:35And we just published that about
  • 01:01:38a year and a half ago.
  • 01:01:40But we have evidence in animal models.
  • 01:01:43That the normal cells that
  • 01:01:45you give can inhibit.
  • 01:01:46Now if you're giving normal
  • 01:01:49cells that contain T regulatory
  • 01:01:51cells that would be hurtful,
  • 01:01:53but also these other cells that you
  • 01:01:55give that are non tumor reactive
  • 01:01:57compete for the cytokines that are
  • 01:01:59result of the lympho depletion.
  • 01:02:01When you lympho deplete,
  • 01:02:03you increase circulating levels of I
  • 01:02:05L15IL7 which normally do not circulate and.
  • 01:02:10Those circulating cytokines then can
  • 01:02:13impact on the cells we administer and
  • 01:02:15if we're administering normal cells
  • 01:02:16they compete with the good ones.
  • 01:02:18So you've hit your your your question
  • 01:02:22actually hit on the exactly the
  • 01:02:24right answer that you mentioned.
  • 01:02:25You need the right cells and
  • 01:02:27none of the wrong cells.
  • 01:02:29I know we're
  • 01:02:31little over but just two more
  • 01:02:32questions because some of your
  • 01:02:33old friends Mario Snow is online
  • 01:02:34and would like to ask a question.
  • 01:02:36Mario you should have come
  • 01:02:37here in person Mario.
  • 01:02:38Mario. I'm sorry, Steve,
  • 01:02:41I'm just curious for all the
  • 01:02:43reactive TCR's that you found
  • 01:02:44in the epithelium malignancies,
  • 01:02:46are those internally differentiated cells,
  • 01:02:48are there any in the stem cell
  • 01:02:50pool that you say work well and is
  • 01:02:52that different between epithelium
  • 01:02:53malignancies and Melanoma?
  • 01:02:57We can find them easily in Melanoma and
  • 01:02:59they are very difficult to find in,
  • 01:03:02in the epithelial cancers because the.
  • 01:03:07Incidence of those cells are likely
  • 01:03:09100,000 fold less in our measurements
  • 01:03:11in the epithelial cancers than in the
  • 01:03:14melanomas because we generally try
  • 01:03:16to find them in circulating cells.
  • 01:03:18But they do exist,
  • 01:03:20they just very hard to identify.
  • 01:03:21And my suspicion as we continue
  • 01:03:23to study and find better ways to
  • 01:03:25identify tiny numbers of them,
  • 01:03:27we will find them in the in the
  • 01:03:29patients that did that did respond.
  • 01:03:33But it's a particular delight to to
  • 01:03:36hear Mario, who worked closely with
  • 01:03:38us for for several years, as are
  • 01:03:41several others of your of your fellows.
  • 01:03:44We we now have Nick Clement on our on our
  • 01:03:50staff, and it reminds me to say that in fact.
  • 01:03:58Especially all of this work,
  • 01:03:59except for the first five to seven years,
  • 01:04:02was actually done not by me,
  • 01:04:04with my own hands in the lab,
  • 01:04:06but by fellows who come to
  • 01:04:07the surgery branch to train.
  • 01:04:09Fellows like Nick Lemon,
  • 01:04:11like like Mario,
  • 01:04:14who come to the NCI to gain experience
  • 01:04:16in doing clinical and laboratory
  • 01:04:18research for two to three years.
  • 01:04:21And I owe them a great debt, as I do to.
  • 01:04:24Mario, for all the contributions
  • 01:04:26he made when he was here,
  • 01:04:28when he was here with us, you
  • 01:04:29know, Steve, that might be a good way to end.
  • 01:04:31We're going to move into the other
  • 01:04:32room with some of our fellows to talk
  • 01:04:34with you and with the judge and others.
  • 01:04:36Let me just say in hearing you say
  • 01:04:38that the Paul Calabresi I knew would
  • 01:04:40have loved this lecture because it was
  • 01:04:43innovative and it was patient focused.
  • 01:04:45You're bringing new therapies to clinic
  • 01:04:47and Guido's going to say a word,
  • 01:04:48but the fact that you mentored,
  • 01:04:50that was what Paul is all about.
  • 01:04:51And I'm going to go the final word.
  • 01:04:53Judge Guido Calbresi.
  • 01:04:53And then we'll retire to the other room.
  • 01:04:56Judge of
  • 01:05:05course, one people who
  • 01:05:08developed chemotherapy first,
  • 01:05:10he said there was no doubt that
  • 01:05:12where one went was not with
  • 01:05:14chemotherapy but with immune.
  • 01:05:17And he said that was where
  • 01:05:19it would have to be.
  • 01:05:21And that's why I'm particularly
  • 01:05:23delighted to a very.
  • 01:05:26Well, on that note, thank you all.
  • 01:05:28Thank you, Steve.
  • 01:05:28We'll retire and we'll be 5
  • 01:05:29minutes and we'll get you back.
  • 01:05:30Thank you, everyone.