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Speaker 1: Hi Katie, Hi Brian. Well, I'm a little sad today

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Speaker 1: because you know, summer is my favorite season, and sadly

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Speaker 1: it's drawing to an end, and I'm not ready to

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Speaker 1: accept that. So I'm coming out to l A, to

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Speaker 1: the land of Sunshine, California. Here I come. Are you

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Speaker 1: coming to uh to visit me? Of course I plan

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Speaker 1: to see while I'm in town, but also Ellie, my

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Speaker 1: daughter who lives in Los Angeles. But the real reason

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Speaker 1: I'm coming, as much as I love you and Ellie

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Speaker 1: my daughter, is to support a cause that's very near

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Speaker 1: and dear to my heart and one that I really

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Speaker 1: haven't talked about that much on this podcast until today.

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Speaker 1: That is That's right in this episode, ladies and gentlemen,

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Speaker 1: I hope you're going to be excited about this because

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Speaker 1: it's something that I'm so passionate about. We'll be diving

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Speaker 1: into cancer and cancer research. Many of you might remember

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Speaker 1: or that I lost my extraordinary first husband, Jay Monahan,

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Speaker 1: to colon cancer twenty years ago, if you can believe that,

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Speaker 1: right before his forty second birthday. I was the co

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Speaker 1: anchor of the Today Show and many viewers lived the

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Speaker 1: experience almost along with me. And just a few years later,

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Speaker 1: I lost my sister Emily two pancreatic cancer when she

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Speaker 1: was fifty four in a rising star and politics uh

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Speaker 1: to tremendous losses for me and my family and Jay's family.

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Speaker 1: But what people might not realize, Katie, is that you

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Speaker 1: actually turned those tragedies into something more positive because you

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Speaker 1: co founded with eight other women this extraordinary organization called

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Speaker 1: Stand Up to Cancer. And I was blown away to

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Speaker 1: learn that you've raised nearly half a billion dollars since

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Speaker 1: it was founded ten years ago. You know, I couldn't

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Speaker 1: just rest on my laurels when it came to colin

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Speaker 1: oscophees Brian. I felt that so many cans sers deserved

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Speaker 1: our attention, and the ladies at Stand Up to Cancer

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Speaker 1: and the entire organization, because after all, it does take

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Speaker 1: a village, will not rest until more money is raised.

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Speaker 1: And the day after this episode drops, I'll be in

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Speaker 1: l A to mark the ten year anniversary of Stand

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Speaker 1: Up to Cancer and the live telecast that we've been

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Speaker 1: having every other year since its inceptions, So if you'd

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Speaker 1: like to tune in, the telecast will be broadcast on

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Speaker 1: seventy broadcast and cable networks as well as streaming platforms

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Speaker 1: and online So honestly, if you're anywhere near a screen

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Speaker 1: or even a phone, you are not going to be

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Speaker 1: able to avoid this telecast on Friday Night, and just

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Speaker 1: as an additional sweetener for people. In addition to these

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Speaker 1: extraordinary stories an amazing sinus, the telecast is also going

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Speaker 1: to feature a lot of star power, including the likes

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Speaker 1: of Bradley Cooper and Reese Weatherspoon and ma Hershela Ali.

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Speaker 1: I should probably explain, Brian to our listeners how Stand

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Speaker 1: Up to Cancer puts the dollars it raises to work.

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Speaker 1: Our goal is to really accelerate groundbreaking, promising cancer research

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Speaker 1: and mandate we don't encourage, we require collaboration instead of competition.

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Speaker 1: So we have set up dream teams of scientists who

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Speaker 1: are focused on various cancers like pancreatic cancer or nanotechnology.

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Speaker 1: Epigenetics have become quite the scientific researcher, right, Brian, and

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Speaker 1: these dream teams are basically a scientific task force and

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Speaker 1: the ideas to get them uh these top researchers from

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Speaker 1: different institutions to work together so they can develop new

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Speaker 1: approaches and new treatments for this terrible disease that claims

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Speaker 1: far too many lives every single year. And later in

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Speaker 1: the show, we're going to hear from a top oncologist

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Speaker 1: who has contributed enormously to Stand Up to Cancers research efforts.

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Speaker 1: He answers a lot of your questions and mind Katie

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Speaker 1: about the future of cancer research, the most promising therapies, now,

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Speaker 1: what you should do if you're diagnosed with cancer, etcetera, etcetera,

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Speaker 1: And he will give us the big picture. Bill Nelson,

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Speaker 1: I have a little crush on Bill. Don't tell him,

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Speaker 1: by the way, Brian. But another person I have a

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Speaker 1: little crush on is Matthew McConaughey. He's been such an

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Speaker 1: important supporter of Stand Up to Cancer and we're so

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Speaker 1: lucky to have so many celebrities stand with us. And

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Speaker 1: that's because, what can I say, Brian, stars, they're just

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Speaker 1: like us, they too have been affected by cancer. So

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Speaker 1: I recently chatted with Matthew about why this work has

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Speaker 1: become so important to him and how it's affected him personally.

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Speaker 1: Tell me why you wanted to get involved with Stand

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Speaker 1: Up to Cancer? Um, I think I was involved in

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Speaker 1: Stand Up to Cancer actually before cancer affected people very

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Speaker 1: close to me. So Lisa Boston asked me to be

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Speaker 1: involved in two thousand fifteen with the whole campaign, and

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Speaker 1: I said yes. And then shortly after that, I believe

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Speaker 1: is when it actually cancer did affect some people in

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Speaker 1: my near circumference, very very good friend of mine, one

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Speaker 1: of my best friends of twenty years um got cancer,

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Speaker 1: and then um someone in my family got it. And

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Speaker 1: you know when it happened. Uh want it scary too?

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Speaker 1: You want to go, well, I need. I want to

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Speaker 1: get all the information I can. You know what experts

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Speaker 1: can help me, can help. Then It's amazing how when

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Speaker 1: a cancer diagnosis affects someone you know and love, or

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Speaker 1: even yourself, it's you're suddenly immersed in this new world

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Speaker 1: of terms and sort of science and drugs and alternative

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Speaker 1: therapies and approaches. It can be so overwhelming, can it? Yes?

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Speaker 1: And I think it's hard, especially if you're going through

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Speaker 1: it you're self sometimes. I know, in the case of

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Speaker 1: my husband, when he was diagnosed, as smart as he was,

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Speaker 1: he didn't really want to know. He didn't want to

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Speaker 1: see the research for the science and his statistics. He didn't,

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Speaker 1: so you did, and then you helped shepherd and guide

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Speaker 1: him from there. Okay, yes, And I think that's the case.

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Speaker 1: I think some patients want to know and some patients don't.

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Speaker 1: And did you feel like you needed to be that

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Speaker 1: sort of explorer and you needed to really understand it

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Speaker 1: so you could help the people you love? That That's

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Speaker 1: exactly I felt like I was the one who needed

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Speaker 1: to do the expiration. I was the one who needs

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Speaker 1: to get the access to the expert, get the knowledge,

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Speaker 1: gather it as much and fore and wide as I could,

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Speaker 1: and then sit down and go over options, and go

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Speaker 1: over practicalities, and go over long shots and go over repercussion.

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Speaker 1: And you do this. This is you know, it goes

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Speaker 1: to that question this makes in life? But there may

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Speaker 1: be more pain than you have that question quality of

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Speaker 1: life versus quantity Along the way and um, different questions arise,

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Speaker 1: And I was I've been in a position where I

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Speaker 1: was the hunter and gatherer of the information and went

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Speaker 1: to stand up to cancer to find out so much

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Speaker 1: of that information. And then, as you know, it's up

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Speaker 1: to the individual has it. It's there there. It becomes

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Speaker 1: down to that personal choice, which is, you know, not

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Speaker 1: ours unless we're the unless we're the one to make,

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Speaker 1: which is, what do you want to do, and there's

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Speaker 1: many there's many signposts along the way. Here's where we are,

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Speaker 1: here's the new here's a new evolution in the disease.

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Speaker 1: What do you want to do, Here's what we can do,

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Speaker 1: what would you like to do? In some cases, there's

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Speaker 1: not a lot that can be done, and it's very

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Speaker 1: difficult in this day and age when there's so many

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Speaker 1: you know, medications and science has taken us so far

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Speaker 1: that many of these cancers continue to be so vaccine. Yeah,

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Speaker 1: I mean, look, there's obviously there's not a magic pill. Um,

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Speaker 1: there's not that major break that says we've figured it out,

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Speaker 1: we know how to cure all these many types of cancer. Um.

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Speaker 1: And so that's frustrating, um, but it's a reality. And

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Speaker 1: as you know, you gotta get on with the reality

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Speaker 1: that we if we the people's shepherding and helping out

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Speaker 1: those with cancer, if we get over the frustrated, it's

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Speaker 1: no help to the to the to the to the

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Speaker 1: victim or the one with cancer. So I just I

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Speaker 1: just personally try to take a very practical approach and say,

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Speaker 1: let me keep pounding on trying to do the homework.

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Speaker 1: Let me personally talk to that their doctor along the

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Speaker 1: way and get let me can give me the straight

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Speaker 1: nuts emotionally along the way. What what are we really

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Speaker 1: talking about? What's the you know what? Give me percentages?

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Speaker 1: Where are we? And let's be real. And both of

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Speaker 1: both the people that my friend and the family member

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Speaker 1: that I worked wanted to know the straight stuff. One

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Speaker 1: of them towards the end didn't want to know it anymore.

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Speaker 1: So not I don't want to hear anymore. Just let

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Speaker 1: me enjoy in my ignorance right now. I don't want

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Speaker 1: to hear anymore the stats for me. The other one

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Speaker 1: wanted to know the whole way, the whole way until

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Speaker 1: until they actually ended up they did move on. I

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Speaker 1: was gonna ask you about the outcome for both of

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Speaker 1: these people. We'll both have moved on. They're no longer

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Speaker 1: with us in this life on this earth. Um. Besides,

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Speaker 1: as you know, with just the disease of cancer, there's

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Speaker 1: a lot of personal want to needs that anyone on

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Speaker 1: the way out once or doesn't want, um do they

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Speaker 1: it was there are things incomplete in their life for

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Speaker 1: their relationships that were incomplete that they just want to have.

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Speaker 1: Let me just finish that off. Then there's the question

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Speaker 1: of you know, how much pain do you want to

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Speaker 1: go through? Is more time I'm worth more pain? Or no,

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Speaker 1: I want to fight it till the end. I'll go

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Speaker 1: through whatever pain because I may be able to break

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Speaker 1: through it. How long did you keep fighting on that?

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Speaker 1: How long do you go? You know what is too

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Speaker 1: much pain? Let me, let let me, let me, let

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Speaker 1: me fade out? UM. And then you know you're waiting

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Speaker 1: every day and you think something else might come off

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Speaker 1: and there is a new break through and the hey,

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Speaker 1: we could try this, and then you try all you

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Speaker 1: can and so many people have survived, Like I said,

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Speaker 1: fifteen and a half million survivors running around living their

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Speaker 1: life now UM. And I think less cases now in

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Speaker 1: the United States, and it used to be UM. So

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Speaker 1: you hope, you know that you're that the person you're

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Speaker 1: shepherding is going to be one of those fifteen and

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Speaker 1: a half million, or the next, the next one. UM.

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Speaker 1: At the same time, I mean this, it's it's the

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Speaker 1: son of a bitch man. This thing, it's a beast,

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Speaker 1: and we don't have it last so yet. But you know,

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Speaker 1: it's like I said at the beginning, and it's helpful

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Speaker 1: to whoever as it and it's helpful to ever of

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Speaker 1: us is helping do the homework and shepherd our love

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Speaker 1: to one out to know that someplace like Stand Up

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Speaker 1: to Cancer is a place. It's going to get you

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Speaker 1: all the information you can get, so you don't have

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Speaker 1: a black hole there once in case they do move on.

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Speaker 1: Oh should I? Would I? And could I have? That's

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Speaker 1: the way I felt with my husband. You know, I

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Speaker 1: wanted to make sure I did everything I possibly could.

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Speaker 1: So this was before Stand Up to Cancer even existed,

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Speaker 1: but I was calling pharmaceutical companies in Israel. I was

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Speaker 1: doing so much research and calling universities and organizations and

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Speaker 1: hoping that we could manage his disease long enough that

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Speaker 1: another thing, another breakthrough would occur. And I think that's

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Speaker 1: how you operate when you're trying to help someone you

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Speaker 1: love with you were operating like that. At the same

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Speaker 1: time this, Your husband was like, I don't want to

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Speaker 1: I don't want to know anymore. Don't tell me about it, kay,

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Speaker 1: Do you do the do the homework for me? Let me?

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Speaker 1: Was he saying, just tell me where to go, but

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Speaker 1: I don't want to know all of them? He didn't

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Speaker 1: really say it specifically, But I also shielded him from

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Speaker 1: a lot, which now I have some regrets about because

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Speaker 1: I think I didn't want to tell him how bad

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Speaker 1: it was, because he was so advanced when he was diagnosed.

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Speaker 1: You know, he had stage four calling cancer and he

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Speaker 1: had tumors all over his liver and it was just

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Speaker 1: so bleak that I made the choice of feeling that

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Speaker 1: I didn't want to ruin whatever time he had left.

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Speaker 1: But that really wasn't my decision to make, so now

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Speaker 1: I feel bad about it. Maybe it was, I don't know.

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Speaker 1: I know when you played ron Woodriff and Dallas Buyer's Club,

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Speaker 1: the HIV positive person who told I was told you

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Speaker 1: at thirty days, which was such an unbelievable, extraordinary performance.

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Speaker 1: I know you won an Academy Award for that, but

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Speaker 1: you actually channeled a little bit of int of yours

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Speaker 1: who you saw dying of cancer. Oh yeah, yeah, yes, yeah,

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Speaker 1: that would be a third that was that was pre

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Speaker 1: two thousand and fifteen. Yes, indeed, it was a good

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Speaker 1: friend of mine who slowly can't got the best of him.

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Speaker 1: Um and he was one of those fighters. He was

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Speaker 1: one of those you know, uh till the bitter in teeth,

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Speaker 1: non growling streaming como gritting to youth, I'm going to

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Speaker 1: make it, which is what he he gnawed at the situation,

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Speaker 1: did not want to go gently into this good night

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Speaker 1: going to fade out at all, um, And he didn't

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Speaker 1: until his his body broke down enough where his willpower

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Speaker 1: couldn't overcome it. But you used him in a way,

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Speaker 1: the image of him to model a little bit from performance.

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Speaker 1: I don't know how literal that would that was. It

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Speaker 1: was just somebody, uh in my life and a friend

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Speaker 1: who had come and he had always been a fighter

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Speaker 1: when before he was sick, and then afterwards I just

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Speaker 1: remember there's that he was. You know, he was like

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Speaker 1: a like a coyote and he just like if if

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Speaker 1: he was stuck, he was willing to no off his

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Speaker 1: leg to get out of the trap. He was willing

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Speaker 1: to do to do anything. And so he went pretty quickly,

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Speaker 1: you know, like he I saw him very shortly before

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Speaker 1: he moved on, and he still had as much fighting

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Speaker 1: him as he did you know, eight months earlier. Um,

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Speaker 1: But it was it was more his willpower to say no, no, no,

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Speaker 1: I'm not going, and if I do go, it's going

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Speaker 1: to be on the last drop of of life that

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Speaker 1: I have. Is there something about stand Up to Cancer

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Speaker 1: and the way it's sort of operating and focusing on

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Speaker 1: collaboration versus competition and really trying to change how cancer

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Speaker 1: research is on that made you want to support this

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Speaker 1: organization because there are a lot of groups doing great

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Speaker 1: work when it comes to cancer. I mean, look all

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Speaker 1: medicine and medicine should not, nor has ever invented to

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Speaker 1: become a competition. And we know rightfully so that it's

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Speaker 1: also a big business, which makes it a competition in places.

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Speaker 1: Um Uh, you know it's it's like it's like teaching,

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Speaker 1: you know what I mean. It's like if you have

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Speaker 1: a if you have a good idea, a good class,

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Speaker 1: scale it out, share it for free. Come on, what's

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Speaker 1: the end goal? Um? So the collaboration that Stand Up

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Speaker 1: uses is how it ought to be. Um, I wouldn't be.

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Speaker 1: You know, there are some people that, yes, compete, they

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Speaker 1: still do some good work, but it shouldn't be a

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Speaker 1: private club. You know that that somebody who's not in

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Speaker 1: that club does not have access to the expertise that

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Speaker 1: they could offer. So, you know, and we don't have it.

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Speaker 1: It's not figured out yet, So we need a lot

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Speaker 1: more collaboration. No one's got that, Like I said, no

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Speaker 1: one's got the magic pill, you know, So let's go

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Speaker 1: far and wide because all you know, all bets are

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Speaker 1: still on the table for what's the best way and

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Speaker 1: how to handle and diagnose and treat different type of

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Speaker 1: cancers are For so long, research was siloed and people

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Speaker 1: did not share their knowledge or test results or tissue samples.

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Speaker 1: And the thought is, if we do collaborateive scientists share

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Speaker 1: what they're doing, then if two heads are better than one,

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Speaker 1: ten heads are better than two, and we can get

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Speaker 1: treatments to patients in a much faster at a much

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Speaker 1: faster rate. That's just common sense, you know. I know

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Speaker 1: that your most famous line from your very first movie,

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Speaker 1: which I rewatched days and dazed and confused. This morning

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Speaker 1: we watched some clips. It's a good way to start today.

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Speaker 1: You just got to keep living, man. Is that is

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Speaker 1: that your message to people who are fighting cancer? Too? Sure?

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Speaker 1: I mean, that's that's a line that that is universal.

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Speaker 1: You had a specific to everybody. They can imply to

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Speaker 1: their own lives however they want to um. It was

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Speaker 1: inspired because my father moved on and it was about

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Speaker 1: how I was how I was dealing with my relationship

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Speaker 1: with him, and he had just moved on. So that

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Speaker 1: was five days into your shooting. That five days into

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Speaker 1: shooting Day's Confuse was my first acting job. My father

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Speaker 1: moved on and uh I went home for that weekend,

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Speaker 1: spent the weekend. We had to wake and the whole

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Speaker 1: family should get you back there to work. Um, nothing

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Speaker 1: you can do here, go back to it. And I

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Speaker 1: think it was like the first night we were back.

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Speaker 1: It was seen on the football field and I had

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Speaker 1: been obviously, you know, doing some soul searching with how

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Speaker 1: to what it all meant. Physically was gone, but they

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Speaker 1: just keep living. Came from well you still keep someone

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Speaker 1: spirit alive even though maybe physically they're not here, not personally,

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Speaker 1: you know. For me, just keep living. I applied to

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Speaker 1: many parts of my life, and I think everyone can

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Speaker 1: apply it in their own different way. It's just keep living. Mean,

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Speaker 1: I want to like that friend of mine that's going,

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Speaker 1: I want to live as long I want to live.

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Speaker 1: I'll take quantity over quality. I don't care how much

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Speaker 1: pain them in. I want to live longer. For some

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Speaker 1: it is others that just keep living choice Maybe you

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Speaker 1: know what enough of the pain right now. I'm I'm

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Speaker 1: I'm I'm ready. I'm talking about quality of life. And

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Speaker 1: I don't want to take the pain that I'm in

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Speaker 1: right now for another however, many weeks, days, months. I

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Speaker 1: don't want the quantity. I don't want more quantity. I'm

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Speaker 1: good right now, And that's up to each individual to say.

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Speaker 1: And it's also, as you know, it's it's a conversation

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Speaker 1: that we need to have with our friends and loved

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Speaker 1: ones before they're so sick, before they're in that much pain,

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Speaker 1: to have it, you know, and at a time where

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Speaker 1: there is lucid as possible as a society, we have

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Speaker 1: such hard time talking about death. Yeah, and yet it's

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Speaker 1: one of the things, one of the guarantees, you know.

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Speaker 1: I wish we didn't have such a hard time talking

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Speaker 1: about it. I think sometimes talking about it it feels

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Speaker 1: like a concession to some people, you know, I've got

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Speaker 1: to I've got a woman very close to me who

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Speaker 1: who um beat three types of cancer and didn't tell

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Speaker 1: didn't tell me she had it until her third one

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Speaker 1: and never went to doctors, And what were you doing

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Speaker 1: for what she was taking to aspirin? But her attitude

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Speaker 1: and her mental makeup had so much to do where

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Speaker 1: they're making it. Um, she was actually stayed in denial.

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Speaker 1: So I think talking about death or even sometimes people

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Speaker 1: going to see a doctor to concede and go I

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Speaker 1: need to get some help can make sometimes make our

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Speaker 1: our our our immune and innate reaction be like, oh

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Speaker 1: now I've now I'm a victim. Now I'm now I'm

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Speaker 1: conceding that death is out there, and I think something

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Speaker 1: that feels on people feel weak about that. But um,

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Speaker 1: I think it's good if we can talk about it

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Speaker 1: up front as early as possible, because it's happening one

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Speaker 1: day or another. It's happening. Well, as somebody involved with

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Speaker 1: Stand Up to cancer, I can't tell you how much

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Speaker 1: we appreciate your lending your name and celebrity to this

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Speaker 1: because I think it inspires other people and makes them

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Speaker 1: want to get involved. And if they see someone they

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Speaker 1: admire and like kind of standing up for stand up,

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Speaker 1: hopefully they'll follow suits. So thank you for doing that. Well,

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Speaker 1: I've got a personal investment in it people in my

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Speaker 1: own life. So who does that? You know? One and

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Speaker 1: two men one in three women will be diagnosed in

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Speaker 1: their lifetimes, So like it or not. There's very few

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Speaker 1: people escape it, so thank you, thank you for doing it.

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Speaker 1: My pleasure. That wraps things up with a one and

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Speaker 1: only Matthew McConaughey, folks, and we're going to take a

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Speaker 1: quick break and we'll be back with our second guest,

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Speaker 1: Dr Bill Nelson, from the Sydney Kimmel Comprehensive Cancer Center

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Speaker 1: at Johns Hopkins University in Baltimore. We're back, you know, Brian.

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Speaker 1: As much as I appreciate celebrities like Matthew McConaughey who

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Speaker 1: lend their star support to this cause, some of the

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Speaker 1: real heroes in this fight, I'm sure Matthew would agree,

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Speaker 1: are the scientists and doctors and clinicians who are working

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Speaker 1: day in and day out to find new ways to

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Speaker 1: help patients fighting cancer. I disagree. No'm for our second

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Speaker 1: and final chapter today, we're going to talk with one

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Speaker 1: of these heroes, Dr Bill Nelson. As you mentioned, he's

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Speaker 1: nationally recognized as a physician and scientist, and he specializes

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Speaker 1: in treating and researching prostate cancer. In fact, he discovered

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Speaker 1: the most common genome alteration in prostate cancer, which has

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Speaker 1: led to more diagnostic tests for the disease. Talk about impressive.

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Speaker 1: He's the director of the Sydney Kimmel Brands of Cancer

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Speaker 1: Center at Johns Hopkins and he is also on the

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Speaker 1: Stand Up to Cancer Scientific Advisory Committee. So in our

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Speaker 1: conversation with Dr Nelson, we dig into his work fighting

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Speaker 1: all kinds of cancer and we talked about why the

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Speaker 1: approach of Stand Up to Cancer is so unique and

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Speaker 1: has already yielded so many promising therapies. Bill, let's talk

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Speaker 1: about the model of Stand Up to Cancer and from

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Speaker 1: a scientist perspective, how is it different and why in

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Speaker 1: your view is it a positive thing? Well, I think

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Speaker 1: that the thing that attracted so much of the scientific

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Speaker 1: and cancer research community initially was its ambition. These women

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Speaker 1: had gotten together, as you know, and they wanted to

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Speaker 1: do something bold, and they wanted to do something big.

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Speaker 1: And their thought was that if everyone could come together

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Speaker 1: in dream teams we called them, in which case you

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Speaker 1: had everybody who could help on a particular cancer problem,

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Speaker 1: they could focus on this problem, get considerable investment of

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Speaker 1: resources over a short period of time, that they could

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Speaker 1: make a huge difference quickly, Dr Nelson, Bill, if I

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Speaker 1: might before stand Up to Cancer, what did the world

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Speaker 1: of cancer research look like, why was there this need

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Speaker 1: to create dream teams and collaborate. Well, you had very

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Speaker 1: dedicated people trying to make an impact on the cancer field.

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Speaker 1: They were very competitive, and some of that was good

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Speaker 1: in trying to outsmart or be cleverer than cancer than

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Speaker 1: one might compete with someone else working on the same

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Speaker 1: type of thing. And he didn't share information, didn't share

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Speaker 1: data until you delivered a publication into the medical literature.

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Speaker 1: That often was months months after the discovery was made.

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Speaker 1: And I think what became clear around the time stand

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Speaker 1: Up to Cancer as people were starting to work together,

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Speaker 1: not just to not compete with each other, but we

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Speaker 1: were starting to bring together areas of deep expertise uh

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Speaker 1: medical oncology, structural biology, chemistry, cell biology, engineering, all these things,

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Speaker 1: bringing more all together to ask much more impactful questions

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Speaker 1: about what cancer is and how it might be better treated.

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Speaker 1: On one level, you were collaborating with different kinds of

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Speaker 1: scientists and different kind of experts bringing their expertise together.

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Speaker 1: But in terms of institutions and medical establishments and biotech firms,

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Speaker 1: it was very very proprietary, wasn't it. Bill, Certainly in

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Speaker 1: the biotechnology industries proprietary because they're trying to build a

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Speaker 1: product to outcompete the next company. But there was a

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Speaker 1: lot of that ongoing, I think at our nations in

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Speaker 1: the world's leading cancer center, so they could say we're

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Speaker 1: the place that discovered this important thing. So it was

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Speaker 1: very political in a way, very much so yes, and

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Speaker 1: politics are everywhere to see that, Brian, and so initial

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Speaker 1: I know a lot of the scientists were a little

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Speaker 1: bit nervous about this whole new paradigm, thinking we're not

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Speaker 1: going to share our valuable research, our blood, sweat and tears.

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Speaker 1: If we're at such and such a hospital or institution,

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Speaker 1: we're not going to share it with the people, you

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Speaker 1: know on the other side of the country. What was

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00:25:20,040 --> 00:25:24,359
Speaker 1: the reaction initially? Like, I think it had ripened a

430
00:25:24,400 --> 00:25:27,280
Speaker 1: bit so that the idea was very timely, And I

431
00:25:27,280 --> 00:25:30,439
Speaker 1: think you're right. I think innately, I think scientists were

432
00:25:30,440 --> 00:25:33,000
Speaker 1: a little bit nervous. What am I gonna share? Well,

433
00:25:33,040 --> 00:25:35,800
Speaker 1: I share a little bit, but not the most important

434
00:25:35,840 --> 00:25:38,960
Speaker 1: part or what have you. I think what started to

435
00:25:39,000 --> 00:25:42,240
Speaker 1: happen though, is that some of the collaborative kinds of

436
00:25:42,400 --> 00:25:46,280
Speaker 1: research we're getting answers that weren't that people just weren't

437
00:25:46,320 --> 00:25:48,160
Speaker 1: getting when they're working on their own late at night

438
00:25:48,240 --> 00:25:50,520
Speaker 1: and you know, in a dark laboratory. And I think

439
00:25:50,600 --> 00:25:53,880
Speaker 1: people saw that this should work, although I think they

440
00:25:53,880 --> 00:25:55,840
Speaker 1: were a little nervous about taking it on. I think

441
00:25:55,840 --> 00:25:58,719
Speaker 1: that's a fair view. And so basically, what stand up

442
00:25:58,760 --> 00:26:02,000
Speaker 1: set is you're not getting our money unless you work together,

443
00:26:02,080 --> 00:26:04,919
Speaker 1: unless you play nice. Well they did say that, and

444
00:26:04,960 --> 00:26:07,840
Speaker 1: the other side was that, you know, it was very

445
00:26:07,840 --> 00:26:09,720
Speaker 1: clear from the get go that the stand Up to

446
00:26:09,800 --> 00:26:14,359
Speaker 1: Cancer enterprise reached the general public in very, very much

447
00:26:14,720 --> 00:26:18,080
Speaker 1: broader and more important ways. And remember, all along we

448
00:26:18,080 --> 00:26:21,280
Speaker 1: were concerned in all of cancer research that not enough

449
00:26:21,400 --> 00:26:24,480
Speaker 1: of the cancer patients were participating in clinical trials and

450
00:26:24,520 --> 00:26:27,280
Speaker 1: the like. And here was a magic kind of a

451
00:26:27,440 --> 00:26:30,480
Speaker 1: time where cancer researchers were going to come together, but

452
00:26:30,600 --> 00:26:33,879
Speaker 1: the entertainment industry and the TV news industry was going

453
00:26:33,920 --> 00:26:36,720
Speaker 1: to come together and tell everybody the story of cancer.

454
00:26:36,800 --> 00:26:40,520
Speaker 1: So those two things together it was faded to work.

455
00:26:40,560 --> 00:26:45,160
Speaker 1: And it has worked incredibly well. So after the initial resistance,

456
00:26:45,240 --> 00:26:49,239
Speaker 1: there was excitement. And I think my impression Bill is

457
00:26:49,359 --> 00:26:52,760
Speaker 1: once the scientists started working together and collaborating and getting

458
00:26:52,760 --> 00:26:56,600
Speaker 1: to know each other and sharing their results and tissue

459
00:26:56,640 --> 00:27:00,800
Speaker 1: samples and all sorts of things. They felt incredibly energized

460
00:27:01,040 --> 00:27:04,399
Speaker 1: by this, didn't they. Well, you've watched each year as

461
00:27:04,440 --> 00:27:06,879
Speaker 1: we come to the Scientific Summit, and you watch the

462
00:27:07,600 --> 00:27:11,360
Speaker 1: culture of how people interact the scientists, and I think

463
00:27:11,359 --> 00:27:14,080
Speaker 1: that's exactly right. I can think of two scientists from

464
00:27:14,080 --> 00:27:17,199
Speaker 1: my own field cancer up in genetics, Peter Jones and

465
00:27:17,320 --> 00:27:19,359
Speaker 1: Steve Bale, and they're a leader of a dream team.

466
00:27:19,600 --> 00:27:22,880
Speaker 1: These were arch rivals throughout most of my career in science.

467
00:27:23,119 --> 00:27:26,439
Speaker 1: They vacation together now so they not only begin to

468
00:27:26,480 --> 00:27:29,159
Speaker 1: see things together and how they might work together, but

469
00:27:29,400 --> 00:27:31,520
Speaker 1: the whole culture of science, I think has changed. And

470
00:27:31,520 --> 00:27:34,280
Speaker 1: you watched it year to year coming to the Scientific Summing.

471
00:27:34,400 --> 00:27:37,520
Speaker 1: It's actually been a really moving thing to witness because

472
00:27:37,680 --> 00:27:39,800
Speaker 1: I've always said, if two heads are better than one,

473
00:27:39,840 --> 00:27:43,520
Speaker 1: ten heads are better than two, And why not pool

474
00:27:43,680 --> 00:27:49,920
Speaker 1: your incredible science and hard work and intelligence intellect and

475
00:27:50,560 --> 00:27:55,439
Speaker 1: just help patience instead of helping the scientists. Ego With

476
00:27:55,480 --> 00:28:00,119
Speaker 1: all due respect, Bill, Yeah, no, at some point I

477
00:28:00,200 --> 00:28:02,400
Speaker 1: hope that people leave some of their ego at the door.

478
00:28:02,480 --> 00:28:04,240
Speaker 1: We want them to have enough of an ego to

479
00:28:04,320 --> 00:28:08,080
Speaker 1: be bold enough to have a new idea and build

480
00:28:08,080 --> 00:28:10,679
Speaker 1: that idea up into something important if it's the answer,

481
00:28:11,040 --> 00:28:14,280
Speaker 1: but other than that, it's just in the way. I agree. So, Bill,

482
00:28:14,320 --> 00:28:16,600
Speaker 1: I want to ask you a few questions about cancer

483
00:28:16,680 --> 00:28:19,119
Speaker 1: that may seem very obvious to you into Katie, but

484
00:28:19,240 --> 00:28:22,760
Speaker 1: to civilians like me, I think your expertise will be

485
00:28:22,840 --> 00:28:26,480
Speaker 1: very helpful. So I keep hearing a lot about immunotherapy,

486
00:28:26,600 --> 00:28:30,200
Speaker 1: and basically, here's what I know. Immunotherapy trains your body's

487
00:28:30,240 --> 00:28:34,520
Speaker 1: immune system to attack the cancer, which it won't do

488
00:28:34,640 --> 00:28:38,680
Speaker 1: on its own in many cases. Can you explain where

489
00:28:38,720 --> 00:28:43,200
Speaker 1: immunotherapy is and why it's so important? Yeah, well, I

490
00:28:43,200 --> 00:28:45,960
Speaker 1: think you You've got to beat on on the immune system.

491
00:28:46,000 --> 00:28:50,440
Speaker 1: The immune system is remarkable. It's capable, generally of distinguishing

492
00:28:50,560 --> 00:28:54,320
Speaker 1: threats of the body, whether they're bacteria or viruses or

493
00:28:54,480 --> 00:28:58,800
Speaker 1: fungi or somebody's kidney that's been transplanted into you. They

494
00:28:58,840 --> 00:29:01,600
Speaker 1: can distinguish that from the normal cells in the body.

495
00:29:01,960 --> 00:29:04,680
Speaker 1: And I think for a long time scientists wondered whether

496
00:29:04,720 --> 00:29:08,560
Speaker 1: the immune system could also see cancer cells as different

497
00:29:08,600 --> 00:29:11,360
Speaker 1: from normal cells. I think at this point we're pretty

498
00:29:11,400 --> 00:29:14,400
Speaker 1: well convinced that they absolutely can. So the question then became,

499
00:29:15,040 --> 00:29:18,040
Speaker 1: if the immune system can see the cancer recognize that

500
00:29:18,080 --> 00:29:21,120
Speaker 1: it's not normal. Why can't it mount an attack and

501
00:29:21,160 --> 00:29:23,320
Speaker 1: destroy the cancer the way it would try and destroy,

502
00:29:23,440 --> 00:29:27,080
Speaker 1: you know, bacteria or viruses or the like. And for

503
00:29:27,160 --> 00:29:31,080
Speaker 1: some of them, it looks like the cancer is sneaky.

504
00:29:31,240 --> 00:29:33,480
Speaker 1: It holds up what I think of as the talk

505
00:29:33,520 --> 00:29:35,920
Speaker 1: to the hand response. The immune cell shows up and

506
00:29:35,960 --> 00:29:38,840
Speaker 1: it holds it at bay. The importance of that is

507
00:29:38,880 --> 00:29:41,960
Speaker 1: that that can be defeated with a new series of drugs.

508
00:29:41,960 --> 00:29:45,160
Speaker 1: Are five of them now FDA approved called immune checkpoint

509
00:29:45,160 --> 00:29:48,680
Speaker 1: in immercial six. I guess um that stops that response,

510
00:29:48,840 --> 00:29:53,200
Speaker 1: unleashes the immune system, and for many people, the immune

511
00:29:53,200 --> 00:29:55,520
Speaker 1: system can destroy the cancer. It looks like it can

512
00:29:55,600 --> 00:29:58,400
Speaker 1: keep it at bay for a very long time. We're

513
00:29:58,440 --> 00:30:01,840
Speaker 1: beginning to wonder whether these people are cured. Truly remarkable,

514
00:30:01,960 --> 00:30:04,920
Speaker 1: It is so exciting, and cancer is such a wildly

515
00:30:05,360 --> 00:30:09,960
Speaker 1: vicious opponent. And I think Brian, for so long, even

516
00:30:10,000 --> 00:30:13,280
Speaker 1: if you turbo charge the immune system, the cancer cells

517
00:30:13,400 --> 00:30:16,680
Speaker 1: or something something within the cells or outside the cells

518
00:30:17,040 --> 00:30:20,760
Speaker 1: could figure out a way around it. Right to Bill's point,

519
00:30:20,840 --> 00:30:24,560
Speaker 1: they would set up these blockades or his his metaphor

520
00:30:24,600 --> 00:30:27,120
Speaker 1: the talk to the hand thing, but they can remove

521
00:30:27,160 --> 00:30:30,760
Speaker 1: the blockades, turbo charge the immune system and let it

522
00:30:30,880 --> 00:30:35,000
Speaker 1: do its job, and we're seeing some very exciting developments

523
00:30:35,000 --> 00:30:37,680
Speaker 1: in this field of cancer research. When it comes to

524
00:30:37,760 --> 00:30:41,280
Speaker 1: this really relatively new approach, which a lot of scientists

525
00:30:41,320 --> 00:30:43,920
Speaker 1: used to mock. Actually right, well, I think the people

526
00:30:43,920 --> 00:30:46,320
Speaker 1: who worked on immano therapy for a long time were

527
00:30:47,800 --> 00:30:50,320
Speaker 1: it wasn't working very well, and I think that many

528
00:30:50,360 --> 00:30:53,880
Speaker 1: of their colleagues reminded them that on occasion. But yeah,

529
00:30:53,960 --> 00:30:57,480
Speaker 1: now this these new immane checkpoint inhibitors are are just stunning,

530
00:30:57,600 --> 00:31:01,440
Speaker 1: and of course now the challenges. They work incredibly well

531
00:31:01,480 --> 00:31:04,080
Speaker 1: for a fraction of the people with many different types

532
00:31:04,120 --> 00:31:07,000
Speaker 1: of cancers that get treated, they don't work at all

533
00:31:07,080 --> 00:31:09,280
Speaker 1: for some other folks, and we need to know why

534
00:31:09,320 --> 00:31:12,000
Speaker 1: that's the case, because the what we assume is if

535
00:31:12,040 --> 00:31:15,000
Speaker 1: we can figure out why, perhaps we can can energize

536
00:31:15,000 --> 00:31:17,280
Speaker 1: the immune system and these people to work as effectively

537
00:31:17,320 --> 00:31:18,960
Speaker 1: it does in the others. You also have to be

538
00:31:19,000 --> 00:31:22,400
Speaker 1: careful Bill right about turbocharging the immune system too much,

539
00:31:22,480 --> 00:31:25,760
Speaker 1: because if the immune system Brian I always I love

540
00:31:25,840 --> 00:31:27,840
Speaker 1: to talk about this stuff and Brian doesn't know a

541
00:31:27,880 --> 00:31:30,480
Speaker 1: lot about it, But if the immune system is too

542
00:31:30,480 --> 00:31:35,040
Speaker 1: powerful that, of course, can can have some very adverse

543
00:31:35,080 --> 00:31:38,240
Speaker 1: effects on the patient. The use of these immune checkpoint

544
00:31:38,280 --> 00:31:41,640
Speaker 1: inhibitors does walk a tight rope of immunity a little bit,

545
00:31:42,040 --> 00:31:44,360
Speaker 1: and when the immune system gets too repped up, as

546
00:31:44,440 --> 00:31:49,680
Speaker 1: as Katie was saying, you get itis inflammation of in

547
00:31:49,760 --> 00:31:52,600
Speaker 1: almost any organ you can name, whether it's colitis and

548
00:31:52,640 --> 00:31:54,800
Speaker 1: the call and numinitis and the lungs. Those are some

549
00:31:54,840 --> 00:31:58,000
Speaker 1: of the more catastrophic ones. And so what's happened as

550
00:31:58,040 --> 00:32:01,160
Speaker 1: the physicians learned to use these drugs better and better

551
00:32:01,160 --> 00:32:03,920
Speaker 1: and more and more safely, they're far more attuned to

552
00:32:04,040 --> 00:32:06,360
Speaker 1: minor side effects. You know, a little bit of a

553
00:32:06,440 --> 00:32:08,720
Speaker 1: cough means a lot when you're on one of these drugs,

554
00:32:08,800 --> 00:32:12,000
Speaker 1: you get you evaluated very quickly. The thing that's exciting

555
00:32:12,040 --> 00:32:16,240
Speaker 1: is it looks like you can slow down the autoimmune attack,

556
00:32:16,320 --> 00:32:18,960
Speaker 1: the attack on the long or the colon or something

557
00:32:19,600 --> 00:32:24,160
Speaker 1: reasonably effectively without undermining the effect on the cancer very much.

558
00:32:24,200 --> 00:32:27,960
Speaker 1: And that's very promising. But that's how that that medicine

559
00:32:27,960 --> 00:32:31,360
Speaker 1: of that field is shaping up for our listeners. Which

560
00:32:31,360 --> 00:32:35,400
Speaker 1: are the cancers that are now most responsive to immunotherapies,

561
00:32:35,520 --> 00:32:38,720
Speaker 1: and which are the ones that have been the most challenging. Well,

562
00:32:38,720 --> 00:32:41,760
Speaker 1: there's three to to think a lot about one or melanomas,

563
00:32:41,800 --> 00:32:45,320
Speaker 1: and melanoma's the response rates are the highest. That the

564
00:32:45,400 --> 00:32:48,560
Speaker 1: fraction of people with melanoma that benefit from immune checkpoint

565
00:32:48,560 --> 00:32:52,960
Speaker 1: inhibited treatment is the highest. UH non small cell lung cancer.

566
00:32:53,000 --> 00:32:54,720
Speaker 1: We call it one of the kinds of lung cancers

567
00:32:54,760 --> 00:32:59,080
Speaker 1: respond extremely well. And the other one are cancers that

568
00:32:59,120 --> 00:33:02,520
Speaker 1: arise in the sting of an inherited deficiency in DNA

569
00:33:02,560 --> 00:33:06,600
Speaker 1: mismatch APPARENTSIMES. That's a bunch of science gobbledegook to say

570
00:33:06,640 --> 00:33:11,080
Speaker 1: there's an inherited syndrome where people develop cancers, often calling cancer,

571
00:33:11,160 --> 00:33:14,360
Speaker 1: but some others as well, And the reason they do

572
00:33:14,520 --> 00:33:19,120
Speaker 1: is that they get more and more acquired defects and genes.

573
00:33:19,120 --> 00:33:22,480
Speaker 1: Acquired defects and genes underlie cancer generally, but they get

574
00:33:22,520 --> 00:33:25,120
Speaker 1: many many of them, and the immune system can see

575
00:33:25,160 --> 00:33:29,240
Speaker 1: these cancers far more easily, it appears, and so taking

576
00:33:29,280 --> 00:33:33,160
Speaker 1: down this checkpoint barrier looks like it unleashes the immune system.

577
00:33:33,200 --> 00:33:35,880
Speaker 1: After these types of cancers, and these sample many, many

578
00:33:35,920 --> 00:33:39,200
Speaker 1: different kinds of cancer types. Not to be self serving,

579
00:33:39,240 --> 00:33:41,840
Speaker 1: but stand up to cancer is raised close to half

580
00:33:41,880 --> 00:33:46,920
Speaker 1: a billion. Yes, that's billion with a B, folks dollars,

581
00:33:47,040 --> 00:33:50,480
Speaker 1: and much of that money goes to support scientific research

582
00:33:50,960 --> 00:33:54,000
Speaker 1: and build It's a little different in terms of how

583
00:33:54,440 --> 00:33:58,920
Speaker 1: you all and the Scientific Advisory Committee determine where that

584
00:33:59,040 --> 00:34:03,080
Speaker 1: money goes. Can you explain that quickly for us? But

585
00:34:03,240 --> 00:34:05,520
Speaker 1: we when we look for the dream teams, we have

586
00:34:06,040 --> 00:34:08,680
Speaker 1: teams come together and and we help them even before

587
00:34:08,719 --> 00:34:10,960
Speaker 1: they apply, and we say, don't leave anyone out who

588
00:34:10,960 --> 00:34:13,600
Speaker 1: can be helpful. That's the secret to a great dream team.

589
00:34:13,640 --> 00:34:17,240
Speaker 1: They'll then propose a series of bold ideas, will review

590
00:34:17,560 --> 00:34:20,359
Speaker 1: what they have written, will give them some advice on

591
00:34:20,440 --> 00:34:24,439
Speaker 1: improving it, will invite them to come give an oral

592
00:34:24,520 --> 00:34:28,040
Speaker 1: presentation in front of a whole committee of scientists, try

593
00:34:28,040 --> 00:34:30,520
Speaker 1: and pick the ones that we think we should go after.

594
00:34:30,880 --> 00:34:35,680
Speaker 1: And then after the funding is awarded, the Scientific Oversight

595
00:34:35,719 --> 00:34:38,560
Speaker 1: Group continues to watch over these dream teams. We sit

596
00:34:38,600 --> 00:34:41,200
Speaker 1: with them every six months and hear their progress. We

597
00:34:41,320 --> 00:34:45,400
Speaker 1: hear where they've gotten stuck. Um we help them um

598
00:34:45,560 --> 00:34:49,520
Speaker 1: overcome obstacles. Early on, those obstacles were getting the culture

599
00:34:49,600 --> 00:34:51,120
Speaker 1: right to work as a team. We had to do

600
00:34:51,160 --> 00:34:53,520
Speaker 1: a lot of work there. That's not such an issue anymore.

601
00:34:53,560 --> 00:34:55,439
Speaker 1: They tend to work pretty well as a team now,

602
00:34:56,000 --> 00:34:58,680
Speaker 1: and then we bring back what they've learned report up

603
00:34:58,680 --> 00:35:02,040
Speaker 1: to the the women who founded Stand Up to Cancer,

604
00:35:02,080 --> 00:35:04,040
Speaker 1: so we can say this is where it's working, this

605
00:35:04,120 --> 00:35:06,600
Speaker 1: is what's not working. And what you all do with

606
00:35:06,600 --> 00:35:08,640
Speaker 1: that information is you use it to tell a story

607
00:35:08,760 --> 00:35:12,040
Speaker 1: and go raise more funds. There's also a time frame,

608
00:35:12,440 --> 00:35:16,239
Speaker 1: which I think is really important because patients are desperate

609
00:35:16,480 --> 00:35:20,120
Speaker 1: and I think you know people are desperate to come

610
00:35:20,200 --> 00:35:24,120
Speaker 1: up with better treatments, if not a cure, but at

611
00:35:24,160 --> 00:35:27,319
Speaker 1: least treatments that can keep the cancer at bay. So

612
00:35:27,560 --> 00:35:31,160
Speaker 1: you tell these scientists they have to really put their

613
00:35:31,160 --> 00:35:33,799
Speaker 1: foot on the gas pedal. Right, The support is for

614
00:35:33,920 --> 00:35:36,240
Speaker 1: three years. We want them to be in the clinic

615
00:35:36,280 --> 00:35:38,759
Speaker 1: helping people. And if they're in the middle of a

616
00:35:38,800 --> 00:35:41,640
Speaker 1: clinical trial and it's ongoing, the three year clock comes up,

617
00:35:41,680 --> 00:35:44,080
Speaker 1: we'll continue that clinical trial, but we want them to,

618
00:35:44,880 --> 00:35:47,040
Speaker 1: as you say, put the pedal to the metal, get

619
00:35:47,040 --> 00:35:50,880
Speaker 1: the idea translated. We call it into a clinical trial

620
00:35:51,080 --> 00:35:53,560
Speaker 1: so that people can benefit directly. Because time is of

621
00:35:53,600 --> 00:35:56,839
Speaker 1: the essence for these cancer patients and their families. When

622
00:35:56,880 --> 00:35:59,520
Speaker 1: you've heard those three words, you have cancer. Time means

623
00:35:59,640 --> 00:36:03,719
Speaker 1: completly different, meaning so and and when people hear that

624
00:36:03,920 --> 00:36:06,360
Speaker 1: you have cancer. I mean, this may seem like a

625
00:36:06,400 --> 00:36:09,799
Speaker 1: simple question, but what are the best next steps? How

626
00:36:09,800 --> 00:36:12,480
Speaker 1: do you figure out? You know, where can I get

627
00:36:12,560 --> 00:36:14,840
Speaker 1: the right treatment? How can I afford the right treatment?

628
00:36:14,880 --> 00:36:16,719
Speaker 1: Should I listen to this advice? Should I get a

629
00:36:16,760 --> 00:36:19,440
Speaker 1: second opinion? Etcetera? How can I make sure that my

630
00:36:19,520 --> 00:36:23,040
Speaker 1: treatment is benefiting from the breakthroughs that are happening with

631
00:36:23,360 --> 00:36:26,360
Speaker 1: stand up to cancer? Well? I think I think anyone

632
00:36:26,400 --> 00:36:29,560
Speaker 1: who's heard the words you have cancer as a diagnos

633
00:36:29,560 --> 00:36:32,680
Speaker 1: with a diagnosis of cancer will work with their loved ones,

634
00:36:33,040 --> 00:36:35,560
Speaker 1: They'll go seek medical help. I think the idea of

635
00:36:35,560 --> 00:36:38,319
Speaker 1: getting a second opinion is just sound advice generally for

636
00:36:38,360 --> 00:36:41,399
Speaker 1: anything anyone tells you. In medicine, one of the things

637
00:36:41,480 --> 00:36:45,600
Speaker 1: that's really helpful is the where the clinical trials are.

638
00:36:45,680 --> 00:36:49,080
Speaker 1: One thing about clinical research and cancer medicine is it's

639
00:36:49,160 --> 00:36:52,239
Speaker 1: innately the state of the art or better. That's what

640
00:36:52,320 --> 00:36:54,560
Speaker 1: you get with a clinical trial. You also get a

641
00:36:54,680 --> 00:36:57,799
Speaker 1: number of people second guessing the physicians decisions. You have

642
00:36:58,640 --> 00:37:01,360
Speaker 1: the process of doing clinical research, you have a number

643
00:37:01,400 --> 00:37:04,040
Speaker 1: of people watching to make sure the correct medical decisions

644
00:37:04,040 --> 00:37:07,200
Speaker 1: have made. So people like me believe the highest quality

645
00:37:07,280 --> 00:37:11,160
Speaker 1: cancer care is associated with cancer clinical trials. So looking

646
00:37:11,200 --> 00:37:14,640
Speaker 1: for are there opportunities to participate in clinical search? Are

647
00:37:14,680 --> 00:37:16,920
Speaker 1: you a candidate to be part of a clinical trial?

648
00:37:17,280 --> 00:37:19,879
Speaker 1: Is a good way to learn more about cancer and

649
00:37:20,160 --> 00:37:23,000
Speaker 1: to start making your own decisions with the help of

650
00:37:23,040 --> 00:37:26,279
Speaker 1: your physician. Getting back to how the research grants for

651
00:37:26,640 --> 00:37:30,239
Speaker 1: are awarded, I know that one of our goals is

652
00:37:30,320 --> 00:37:34,040
Speaker 1: to fund young researchers who have out of the box ideas,

653
00:37:34,800 --> 00:37:40,040
Speaker 1: because that's important for a number of reasons. First of all,

654
00:37:40,080 --> 00:37:43,080
Speaker 1: there's a serious brain drain, right A lot of scientists

655
00:37:43,120 --> 00:37:45,719
Speaker 1: come here and then they leave the country because they

656
00:37:45,760 --> 00:37:48,120
Speaker 1: want to get more financial support. So we want to

657
00:37:48,120 --> 00:37:52,880
Speaker 1: really encourage young scientists to stay in this country. And secondarily,

658
00:37:53,280 --> 00:37:57,160
Speaker 1: some of these ideas are too unconventional to be funded

659
00:37:57,200 --> 00:38:00,680
Speaker 1: in more traditional ways. Correct, that's right. We have I

660
00:38:00,719 --> 00:38:04,480
Speaker 1: think now forty six or maybe even fifty innovative research

661
00:38:04,560 --> 00:38:07,440
Speaker 1: grant awardees that that's what we call these young researchers,

662
00:38:07,440 --> 00:38:10,440
Speaker 1: and they're just they're just playing remarkable as as you know,

663
00:38:10,560 --> 00:38:13,560
Speaker 1: the late Laura Ziskin had a particular place in her

664
00:38:13,600 --> 00:38:16,440
Speaker 1: heart for this program. She got to know while she

665
00:38:16,520 --> 00:38:19,320
Speaker 1: was alive, everyone who was in this program very personally

666
00:38:19,320 --> 00:38:21,600
Speaker 1: would go to their posters at the summit, ask them

667
00:38:21,640 --> 00:38:24,800
Speaker 1: exactly what they're up to. And this is the best

668
00:38:24,880 --> 00:38:26,640
Speaker 1: that we have in the country who show up and

669
00:38:26,680 --> 00:38:29,479
Speaker 1: apply for these things, and uh, if there are any

670
00:38:29,600 --> 00:38:31,920
Speaker 1: reflection on what the world of cancer is gonna look

671
00:38:31,960 --> 00:38:33,200
Speaker 1: like in a few years, we're going to be in

672
00:38:33,239 --> 00:38:35,640
Speaker 1: good shape. They're incredibly talent a group of people. It's

673
00:38:35,719 --> 00:38:39,680
Speaker 1: very exciting and incredibly gratifying to see them. Brian, I

674
00:38:39,680 --> 00:38:42,319
Speaker 1: I think they're sort of like the Brian Goldsmiths of

675
00:38:42,360 --> 00:38:47,040
Speaker 1: the science world. Oh my god, that's not true. I

676
00:38:47,040 --> 00:38:49,319
Speaker 1: hope they're way better. I think of all the people

677
00:38:49,360 --> 00:38:53,399
Speaker 1: with cancer I'm making Brian blush. Hey, Brian, let's talk

678
00:38:53,440 --> 00:38:56,040
Speaker 1: a little to Bill about his background. What's a nice

679
00:38:56,080 --> 00:38:59,359
Speaker 1: guy like you doing in a field like this. Give

680
00:38:59,440 --> 00:39:01,919
Speaker 1: us a quick thumbnail sketch of your CV and why

681
00:39:01,960 --> 00:39:05,000
Speaker 1: you decided to become a cancer scientist, and a damn

682
00:39:05,040 --> 00:39:08,200
Speaker 1: good one at that, Bill, Thank you. I was not

683
00:39:08,360 --> 00:39:11,279
Speaker 1: someone interested in a pre medical education. I went to

684
00:39:11,360 --> 00:39:13,960
Speaker 1: college mostly to kick soccer balls and get an education.

685
00:39:14,120 --> 00:39:15,840
Speaker 1: I thought i'd kick soccer balls for a couple of

686
00:39:15,880 --> 00:39:17,600
Speaker 1: years and be a lawyer or something. I didn't have

687
00:39:17,920 --> 00:39:22,120
Speaker 1: very definitive plans. I managed to find myself without a job,

688
00:39:22,239 --> 00:39:24,920
Speaker 1: and uh I went to work for someone who brought

689
00:39:24,920 --> 00:39:27,719
Speaker 1: his kids to soccer camps and stuff. And uh I

690
00:39:27,800 --> 00:39:31,279
Speaker 1: had majored in chemistry and sort of quantum mechanics because

691
00:39:31,280 --> 00:39:34,759
Speaker 1: I thought it was interesting. Didn't take any biology to

692
00:39:34,840 --> 00:39:38,640
Speaker 1: Yale College up the street from my safety school, Safety School,

693
00:39:39,160 --> 00:39:43,600
Speaker 1: and uh I can remember this person, Joe McGuire was

694
00:39:43,680 --> 00:39:46,000
Speaker 1: the person ran the lab, and he was doing a

695
00:39:46,040 --> 00:39:49,840
Speaker 1: clinical research on the first uses of retinoids and children

696
00:39:49,880 --> 00:39:52,719
Speaker 1: with scaling skin disorders. Called it the o C so

697
00:39:52,760 --> 00:39:55,319
Speaker 1: they looked kind of funny. And the kids were, you know,

698
00:39:55,400 --> 00:39:58,200
Speaker 1: twelve thirteen year olds, and uh same kind of kids

699
00:39:58,239 --> 00:40:00,880
Speaker 1: would come to soccer camps and and I can remember

700
00:40:00,920 --> 00:40:03,000
Speaker 1: scraping skin off of them to do stuff in the

701
00:40:03,080 --> 00:40:06,600
Speaker 1: laboratory and and talking to them, and I was incredibly

702
00:40:06,640 --> 00:40:10,160
Speaker 1: impressed with how much they knew about clinical research. They

703
00:40:10,160 --> 00:40:13,160
Speaker 1: thought perhaps this new drug might help them, but it

704
00:40:13,239 --> 00:40:16,920
Speaker 1: was more likely not because they've tried things before. But

705
00:40:17,120 --> 00:40:19,560
Speaker 1: even if it didn't work, they were pretty convinced that

706
00:40:20,239 --> 00:40:22,560
Speaker 1: the next set of children with the same disorders would

707
00:40:22,560 --> 00:40:25,400
Speaker 1: be benefited. And I was very moved by that. And

708
00:40:25,440 --> 00:40:28,719
Speaker 1: I can remember taking this one boy and his mom

709
00:40:28,800 --> 00:40:30,719
Speaker 1: up to the laboratory, trying to show him what I

710
00:40:30,760 --> 00:40:33,720
Speaker 1: was doing, giving my best lay explanation, and I looked

711
00:40:33,719 --> 00:40:35,680
Speaker 1: at them at some point realized they had no earthly

712
00:40:35,719 --> 00:40:38,240
Speaker 1: idea what I was talking about, but they cared deeply

713
00:40:38,320 --> 00:40:41,320
Speaker 1: that this much activity was being expended on their behalf.

714
00:40:41,360 --> 00:40:43,600
Speaker 1: And I remember at that point I said, sign me up.

715
00:40:43,600 --> 00:40:44,960
Speaker 1: This is what I want to do. I want to

716
00:40:45,040 --> 00:40:48,359
Speaker 1: do something that brings new treatments to people. And uh

717
00:40:48,640 --> 00:40:50,279
Speaker 1: remember Joe said, well then you're gonna have to go

718
00:40:50,320 --> 00:40:53,080
Speaker 1: to medical school, which I didn't have the right curriculum for,

719
00:40:53,680 --> 00:40:56,640
Speaker 1: but Johns Hopkins took a risk on me. I ended

720
00:40:56,719 --> 00:40:59,560
Speaker 1: up and I was never going to do anything other

721
00:40:59,600 --> 00:41:01,160
Speaker 1: than cance. So I think it's the one where you

722
00:41:01,160 --> 00:41:04,959
Speaker 1: can make the biggest difference by coming up with something new. Well,

723
00:41:05,000 --> 00:41:08,319
Speaker 1: we're glad you did so, thank you. You're a leader

724
00:41:08,320 --> 00:41:12,120
Speaker 1: in what's known as translational research. Can you translate that

725
00:41:12,200 --> 00:41:17,160
Speaker 1: from me? Can you translate translational research? Yeah? No, So

726
00:41:17,200 --> 00:41:20,080
Speaker 1: translational research is the the idea that you can make

727
00:41:20,120 --> 00:41:23,680
Speaker 1: discoveries about biologic processes and the like, but to get

728
00:41:23,680 --> 00:41:27,440
Speaker 1: them into a clinical setting, to translate them from science,

729
00:41:27,480 --> 00:41:30,520
Speaker 1: if you will, to medicine. Um is what we think

730
00:41:30,520 --> 00:41:33,160
Speaker 1: of as translational research. So we try and take the

731
00:41:33,200 --> 00:41:37,080
Speaker 1: best ideas that arise out of how cells work, how

732
00:41:37,160 --> 00:41:40,520
Speaker 1: tissues work, and turn them into new opportunities to build

733
00:41:41,160 --> 00:41:45,359
Speaker 1: approaches to treatment, early detection, screening, prevention, and like you know,

734
00:41:45,440 --> 00:41:49,040
Speaker 1: one of the other exciting things about I think the

735
00:41:49,080 --> 00:41:52,440
Speaker 1: world of cancer research right now is I think you

736
00:41:52,520 --> 00:41:56,960
Speaker 1: mentioned it earlier, this confluence or convergence of all these

737
00:41:57,200 --> 00:41:59,920
Speaker 1: experts in different fields. And I think one of the

738
00:42:00,160 --> 00:42:02,799
Speaker 1: most important game changers, it seems to me, and you

739
00:42:02,880 --> 00:42:06,880
Speaker 1: correct me if I'm wrong, Bill, is data and how

740
00:42:07,000 --> 00:42:11,640
Speaker 1: data is going to impact cancer research. Now, we hear

741
00:42:11,680 --> 00:42:15,360
Speaker 1: that all the time, but can you explain in practical

742
00:42:15,480 --> 00:42:19,719
Speaker 1: terms what data can do for you as a scientist

743
00:42:19,840 --> 00:42:23,479
Speaker 1: and for patients everywhere? Well, there's all kinds of data

744
00:42:23,520 --> 00:42:26,000
Speaker 1: that you could perhaps bring together to help people more

745
00:42:26,000 --> 00:42:29,600
Speaker 1: and more in medicine. But think of cancer for a second, right,

746
00:42:29,680 --> 00:42:33,680
Speaker 1: All cancers are disorders of acquired defects and genes, which

747
00:42:33,680 --> 00:42:35,960
Speaker 1: means we're talking DNA like c S, I on the

748
00:42:36,000 --> 00:42:41,320
Speaker 1: television show three billion basis of DNA. That's the code

749
00:42:41,320 --> 00:42:44,839
Speaker 1: of DNA in every cell in the body. Think about this,

750
00:42:45,520 --> 00:42:49,359
Speaker 1: Human beings are nine nine point nine percent identical at

751
00:42:49,360 --> 00:42:51,760
Speaker 1: the DNA sequence level. And depending on who you're sitting

752
00:42:51,760 --> 00:42:53,280
Speaker 1: next to, that may or may not be a scary

753
00:42:53,280 --> 00:42:56,960
Speaker 1: thought was gonna say, But it does say there's a

754
00:42:56,960 --> 00:43:00,719
Speaker 1: lot more in common between people then we might think politically.

755
00:43:00,920 --> 00:43:04,359
Speaker 1: But that also means there's three million differences between any

756
00:43:04,440 --> 00:43:08,239
Speaker 1: two individuals. We now have the ability to look at

757
00:43:08,280 --> 00:43:11,760
Speaker 1: all the disorders, all the acquired defects in all the genes,

758
00:43:12,239 --> 00:43:15,560
Speaker 1: three billions of bases at a time, huge numbers. And

759
00:43:15,600 --> 00:43:20,200
Speaker 1: this starts to fill up computers, over taxes, microprocessors and

760
00:43:20,239 --> 00:43:22,680
Speaker 1: the like. And that's just to think about one particular

761
00:43:22,719 --> 00:43:26,360
Speaker 1: cancer case. What if we thought about all the breast cancer,

762
00:43:26,440 --> 00:43:28,920
Speaker 1: can we classify it in a way that's perhaps different

763
00:43:29,000 --> 00:43:31,520
Speaker 1: than before, which would say, this woman might not need

764
00:43:31,680 --> 00:43:34,440
Speaker 1: chemotherapy after surgery something that's been in the news of it,

765
00:43:34,880 --> 00:43:37,880
Speaker 1: or this woman might benefit from it, or this woman

766
00:43:37,960 --> 00:43:41,920
Speaker 1: might benefit from trastuzumab percepttion, and this woman might not.

767
00:43:42,320 --> 00:43:45,240
Speaker 1: As we're beginning to make these choices, we're using huge

768
00:43:45,239 --> 00:43:49,000
Speaker 1: amounts of data computers in different ways, and then you're

769
00:43:49,040 --> 00:43:51,880
Speaker 1: write data science itself is what this is becoming. So

770
00:43:51,960 --> 00:43:55,760
Speaker 1: it's it's it's really the not only the collection of data,

771
00:43:55,920 --> 00:43:59,480
Speaker 1: in other words, the information about all these individual cases,

772
00:44:00,040 --> 00:44:03,920
Speaker 1: but how it is organized and how scientists can compare

773
00:44:04,840 --> 00:44:09,480
Speaker 1: uh situations and outcomes and then come up with better recommendations.

774
00:44:09,880 --> 00:44:12,520
Speaker 1: Is that the right to think of it? Absolutely, that's

775
00:44:12,560 --> 00:44:14,799
Speaker 1: exactly right. And one of the challenges, of course is

776
00:44:15,520 --> 00:44:19,040
Speaker 1: as there are electronic health records now throughout the country

777
00:44:19,040 --> 00:44:23,280
Speaker 1: that most of us have somewhere, they have largely been launched,

778
00:44:23,360 --> 00:44:26,239
Speaker 1: if you will, for building purposes, building in compliance, not

779
00:44:26,360 --> 00:44:29,759
Speaker 1: to necessarily maintain the kind of information you'd love to

780
00:44:29,920 --> 00:44:33,280
Speaker 1: use to see whether a treatment worked for everyone who've

781
00:44:33,280 --> 00:44:36,279
Speaker 1: had this life experience and this DNA and put them

782
00:44:36,280 --> 00:44:39,280
Speaker 1: all together. That's what's gonna happen. I think everyone's convinced.

783
00:44:39,320 --> 00:44:41,040
Speaker 1: But it's been a little bit slower than we'd like

784
00:44:41,080 --> 00:44:44,080
Speaker 1: to see. But when it does happen, how will it

785
00:44:44,239 --> 00:44:47,759
Speaker 1: change the face of cancer research and treatment? Oh? I

786
00:44:47,760 --> 00:44:50,200
Speaker 1: think it's going to change it immensely. I think once

787
00:44:50,200 --> 00:44:53,719
Speaker 1: you realize that although we're all very similar we're all different. No,

788
00:44:53,840 --> 00:44:56,080
Speaker 1: two cancers are going to be exactly the life because

789
00:44:56,120 --> 00:44:59,560
Speaker 1: cancer is different in everyone's individual biology. That's right, And

790
00:44:59,600 --> 00:45:02,200
Speaker 1: so we're gonna give the right treatment at the right

791
00:45:02,239 --> 00:45:04,520
Speaker 1: time to the right person at the right does all

792
00:45:04,560 --> 00:45:06,839
Speaker 1: that's going You're going to have the information at your

793
00:45:06,880 --> 00:45:12,680
Speaker 1: fingertips to see sort of quantify, right, what treatment is

794
00:45:12,680 --> 00:45:15,640
Speaker 1: the most efficacious. I always like to use word efficacious.

795
00:45:15,680 --> 00:45:17,400
Speaker 1: I feel like it makes me sound smart. What do

796
00:45:17,400 --> 00:45:19,919
Speaker 1: you think instead of effective? Yeah, it makes you sound

797
00:45:19,920 --> 00:45:22,600
Speaker 1: a little flowering. Why do you scided to say efficactions

798
00:45:22,719 --> 00:45:24,759
Speaker 1: versus effect? I don't know. I'm stuck on whether or

799
00:45:24,800 --> 00:45:29,160
Speaker 1: not it works. You know, can I can? I kind

800
00:45:29,160 --> 00:45:32,600
Speaker 1: of related to that, which is, artificial intelligence has become

801
00:45:33,200 --> 00:45:38,040
Speaker 1: such a buzz phrase um in the world in general

802
00:45:38,160 --> 00:45:41,880
Speaker 1: and in science and particular. How is AI going to

803
00:45:42,080 --> 00:45:46,000
Speaker 1: change cancer research? Your treatment? Well, it is a perfect

804
00:45:46,000 --> 00:45:49,239
Speaker 1: way to go with this big data type discussion, right, So,

805
00:45:49,520 --> 00:45:55,040
Speaker 1: artificial intelligence particularly can seek and see patterns, and if

806
00:45:55,080 --> 00:45:58,319
Speaker 1: the data are collected in a high quality quantitative way,

807
00:45:58,360 --> 00:46:01,000
Speaker 1: as Katie was talking about, the better inputs are going

808
00:46:01,040 --> 00:46:05,319
Speaker 1: to drive the better artificial intelligence algorithms and insights. So

809
00:46:05,440 --> 00:46:08,680
Speaker 1: AI is basically just means it's like it can analyze

810
00:46:08,680 --> 00:46:13,000
Speaker 1: the data and organize the data and interpret the data right,

811
00:46:13,080 --> 00:46:15,200
Speaker 1: that's right, and it sees patterns. So I think the

812
00:46:15,239 --> 00:46:17,440
Speaker 1: first place you're gonna see big hits from AI and

813
00:46:17,480 --> 00:46:22,160
Speaker 1: medicine are in looking at images like mammograms or CT

814
00:46:22,320 --> 00:46:24,480
Speaker 1: scans as they call them, And the other is in

815
00:46:24,880 --> 00:46:28,040
Speaker 1: helping pathologists look at slides, and I think they'll see

816
00:46:28,080 --> 00:46:31,760
Speaker 1: these patterns. I suspect in the end that the AI

817
00:46:31,880 --> 00:46:34,279
Speaker 1: tool will be one that works with a doctor rather

818
00:46:34,320 --> 00:46:38,160
Speaker 1: than replaces one. They'll drive the pathologists eyes to a

819
00:46:38,160 --> 00:46:42,200
Speaker 1: particular part of the slide, saying in their artificial intelligence algorithm,

820
00:46:42,239 --> 00:46:45,120
Speaker 1: this looks suspicious to us, of the pathologist will examine

821
00:46:45,120 --> 00:46:47,520
Speaker 1: and says, yes, that's suspicious because it's a cancer, and

822
00:46:47,880 --> 00:46:49,719
Speaker 1: you'll go And I think that's where you're gonna see

823
00:46:49,719 --> 00:46:52,080
Speaker 1: the earliest hits. You're just gonna have many more tools

824
00:46:52,080 --> 00:46:55,279
Speaker 1: in your tool kit to help patients. Which is so

825
00:46:55,360 --> 00:46:59,600
Speaker 1: exciting is somebody who's husband died of calling cancer in

826
00:46:59,600 --> 00:47:01,759
Speaker 1: this span and of nine months, a new sister died

827
00:47:01,800 --> 00:47:04,960
Speaker 1: of pancreatic cancer in less than two years. You know

828
00:47:05,080 --> 00:47:08,680
Speaker 1: the idea of that being available is so moving and

829
00:47:08,920 --> 00:47:11,960
Speaker 1: heartening to me though. It's incredible, and that wasn't that

830
00:47:12,080 --> 00:47:14,640
Speaker 1: long ago. And so the idea that things are moving

831
00:47:14,680 --> 00:47:17,359
Speaker 1: now finally the way they need to be, faster and

832
00:47:17,400 --> 00:47:19,799
Speaker 1: faster helping more and more people, that's what we all want.

833
00:47:20,000 --> 00:47:22,160
Speaker 1: And you know, stand Up has funded a lot of

834
00:47:22,200 --> 00:47:25,520
Speaker 1: breakthroughs and I just want to give you all a

835
00:47:25,600 --> 00:47:29,440
Speaker 1: hat tip for that, um And and also it gives

836
00:47:29,480 --> 00:47:32,719
Speaker 1: me great pride to know that we have helped facilitate

837
00:47:32,800 --> 00:47:36,399
Speaker 1: some of these breakthroughs. Um. Can you just tick them

838
00:47:36,400 --> 00:47:39,879
Speaker 1: off real quickly, Bill, Just in the last ten years

839
00:47:39,920 --> 00:47:42,560
Speaker 1: have been incredible things that have happened as a result

840
00:47:42,600 --> 00:47:44,920
Speaker 1: of Stand Up to Cancer and these dream teams. Five

841
00:47:45,080 --> 00:47:48,120
Speaker 1: new cancer treatments approved by the Food and Drug Administration,

842
00:47:48,160 --> 00:47:50,520
Speaker 1: which means they're out there and people with cancer can

843
00:47:50,560 --> 00:47:54,319
Speaker 1: benefit from them. New targeted treatments for breast cancer and

844
00:47:54,320 --> 00:47:57,800
Speaker 1: ovarian cancer. A new chemotherapy like drug for pancreatic cancer.

845
00:47:58,320 --> 00:48:01,879
Speaker 1: New bionic T cells called car T cells for leukemia.

846
00:48:02,040 --> 00:48:04,040
Speaker 1: When they work, they work so well they make people

847
00:48:04,160 --> 00:48:06,920
Speaker 1: very sex So there's new strategies to how stop that

848
00:48:07,200 --> 00:48:09,920
Speaker 1: particular side effect. All of this out there, all of

849
00:48:09,920 --> 00:48:13,160
Speaker 1: this available today, uh. And ten years after standard to

850
00:48:13,200 --> 00:48:16,600
Speaker 1: cancer started. Well, it's really exciting, but of course it's

851
00:48:16,640 --> 00:48:20,160
Speaker 1: not enough. I can't tell you how many direct messages

852
00:48:20,280 --> 00:48:24,520
Speaker 1: I get through Instagram or through other means with people

853
00:48:24,600 --> 00:48:28,200
Speaker 1: just desperate bill for some kind of treatment, young people,

854
00:48:28,400 --> 00:48:32,560
Speaker 1: old people, all ages. And of course we just lost

855
00:48:32,640 --> 00:48:37,120
Speaker 1: to I think American heroes from cancer, John McCain from

856
00:48:37,120 --> 00:48:41,400
Speaker 1: glioblastoma I think nine years to the day after Teddy

857
00:48:41,480 --> 00:48:45,560
Speaker 1: Kennedy died of the same thing, and Aretha Franklin from

858
00:48:45,600 --> 00:48:50,040
Speaker 1: pancreatic cancer. So what do you if you had a

859
00:48:50,120 --> 00:48:54,680
Speaker 1: magic wand what would you like to see happen? Obviously

860
00:48:54,760 --> 00:48:57,719
Speaker 1: we'd like to cure all cancers and make them history.

861
00:48:57,760 --> 00:49:00,880
Speaker 1: But what do you see having in the future to

862
00:49:00,920 --> 00:49:06,160
Speaker 1: help the people who, sadly and tragically are not being helped. Well,

863
00:49:06,160 --> 00:49:08,600
Speaker 1: I think we do need to cure everyone with cancer,

864
00:49:08,719 --> 00:49:11,919
Speaker 1: and I think we're going to slowly but surely get

865
00:49:11,960 --> 00:49:14,560
Speaker 1: to there. And uh, and by that I don't mean

866
00:49:14,640 --> 00:49:18,200
Speaker 1: too slowly. I think we're finally moving quickly enough that

867
00:49:18,239 --> 00:49:21,560
Speaker 1: you're starting to see people benefit who historically you didn't

868
00:49:21,600 --> 00:49:25,960
Speaker 1: think of as benefiting very much. But those two are

869
00:49:26,000 --> 00:49:28,720
Speaker 1: ones that we just don't do well enough against brain tumors.

870
00:49:28,719 --> 00:49:33,240
Speaker 1: As you mentioned, whether it's Bo Biden or John McCain

871
00:49:33,400 --> 00:49:36,360
Speaker 1: or Teddy Kennedy or anybody who knows somebody with a

872
00:49:36,400 --> 00:49:39,000
Speaker 1: malignant brain tumor, we just don't do well enough against

873
00:49:39,000 --> 00:49:41,400
Speaker 1: that cancer. We need to work harder and get some

874
00:49:41,440 --> 00:49:45,839
Speaker 1: new insights pancreatic cancer. It's just starting to get a

875
00:49:45,840 --> 00:49:48,239
Speaker 1: little bit brighter, I think, but this is still a

876
00:49:48,280 --> 00:49:52,279
Speaker 1: cancer that's growing in incidents in our country as some

877
00:49:52,360 --> 00:49:55,360
Speaker 1: of other cancers are receding. So we're gonna have to

878
00:49:55,440 --> 00:49:58,120
Speaker 1: struggle with some cancers that we're not doing very well with.

879
00:49:58,680 --> 00:50:02,440
Speaker 1: Another more subtle channel into which I'm I'm hopeful about,

880
00:50:02,560 --> 00:50:05,880
Speaker 1: is that you know, most cancers arise, like percent of

881
00:50:05,880 --> 00:50:08,719
Speaker 1: them arising people over the age of sixty. The good

882
00:50:08,760 --> 00:50:12,200
Speaker 1: news is that we have people aging into their sixties, seventies,

883
00:50:12,280 --> 00:50:14,640
Speaker 1: I know, seventies and New twenty five or something. But

884
00:50:14,680 --> 00:50:17,400
Speaker 1: we have people aging into their sixties and seventies and

885
00:50:17,440 --> 00:50:19,239
Speaker 1: a much more healthy states. So of course we're going

886
00:50:19,280 --> 00:50:21,880
Speaker 1: to treat their cancer. But by the same token, we're

887
00:50:21,880 --> 00:50:24,759
Speaker 1: gonna want different kinds of cancer treatments, ones that they

888
00:50:24,760 --> 00:50:27,160
Speaker 1: can take, that's a pill that they can still continue

889
00:50:27,160 --> 00:50:30,440
Speaker 1: to work or or whatnot. And the that's starting to

890
00:50:30,480 --> 00:50:33,960
Speaker 1: happen to the cancer treatments just aren't is difficult to

891
00:50:34,000 --> 00:50:36,600
Speaker 1: get through as they once were. And Bill, you're you're

892
00:50:36,640 --> 00:50:40,080
Speaker 1: the director of the Kimmel Cancer Center at Johns Hopkins.

893
00:50:40,160 --> 00:50:42,799
Speaker 1: You study all aspects of cancer. And we've been talking

894
00:50:42,840 --> 00:50:45,200
Speaker 1: a lot about research and treatment, but can we just

895
00:50:45,200 --> 00:50:48,279
Speaker 1: talk for a second about prevention. What do we know

896
00:50:48,680 --> 00:50:51,399
Speaker 1: about things that those of us who are lucky enough

897
00:50:51,480 --> 00:50:53,239
Speaker 1: not to have had cancer, at least not to have

898
00:50:53,280 --> 00:50:57,240
Speaker 1: had cancer yet, what can we do to prevent cancer

899
00:50:57,320 --> 00:51:00,560
Speaker 1: in terms of you know, diet or lifestyle or anything

900
00:51:00,600 --> 00:51:03,279
Speaker 1: like that. Well, there's some straight off the bat that

901
00:51:03,360 --> 00:51:06,680
Speaker 1: people should just do. One is a vaccination against the

902
00:51:06,800 --> 00:51:12,000
Speaker 1: human papalomavirus HPV. Vaccination. Everyone, boys, girls, everyone should be vaccinated.

903
00:51:12,040 --> 00:51:15,239
Speaker 1: It stops at least three different kinds of cancers, and

904
00:51:15,320 --> 00:51:18,520
Speaker 1: it definitely works, and people should get it done. Smoking

905
00:51:18,520 --> 00:51:21,560
Speaker 1: cessation is one of the reasons lung cancer mortality has

906
00:51:21,600 --> 00:51:27,040
Speaker 1: been declining. Immercifully, Smoking effects all cancers. Smoking affects many cancers.

907
00:51:27,080 --> 00:51:29,440
Speaker 1: That's right, and there's no question we've got to stamp

908
00:51:29,440 --> 00:51:32,640
Speaker 1: out smoking. Justice. It seems to be working better and

909
00:51:32,680 --> 00:51:35,759
Speaker 1: better in this country. We see smoking pop up in

910
00:51:35,800 --> 00:51:37,360
Speaker 1: other parts of the globe. This is going to be

911
00:51:37,400 --> 00:51:41,239
Speaker 1: a global challenge. And a diet and exercise. Having a

912
00:51:41,239 --> 00:51:45,960
Speaker 1: healthier diet, healthier weight, and exercise probably is a general

913
00:51:46,000 --> 00:51:49,040
Speaker 1: preventative agent for many kinds of cancers, particularly those that

914
00:51:49,080 --> 00:51:51,759
Speaker 1: are common in the Western world. And those three things

915
00:51:51,800 --> 00:51:53,680
Speaker 1: people can just do on their own. They can get

916
00:51:53,680 --> 00:51:58,719
Speaker 1: those things done. There are increasingly some strategies using early detection.

917
00:51:59,160 --> 00:52:02,279
Speaker 1: Katie Kirk is shown us our own early detection strategies

918
00:52:02,320 --> 00:52:06,560
Speaker 1: periodically on television. UM. But there's early detection kind of

919
00:52:06,560 --> 00:52:09,399
Speaker 1: strategies and screening. And the other of course is there

920
00:52:09,440 --> 00:52:12,080
Speaker 1: are some medicines out that help prevent breast cancer, and

921
00:52:12,120 --> 00:52:14,480
Speaker 1: we need to discover more of those types of medicines

922
00:52:14,520 --> 00:52:17,960
Speaker 1: that help prevent other cancers. Well, we talk about early detection,

923
00:52:18,200 --> 00:52:21,320
Speaker 1: and now one of the exciting things that I've recently

924
00:52:21,400 --> 00:52:26,120
Speaker 1: learned is on the horizon potentially very very early stages

925
00:52:26,640 --> 00:52:29,920
Speaker 1: new ways of detecting cancer. I was at this Michael

926
00:52:29,960 --> 00:52:34,400
Speaker 1: Milken Institute panel over the weekend and they were talking

927
00:52:34,440 --> 00:52:40,080
Speaker 1: about potentially working on a breathalyzer for lung cancer and

928
00:52:40,120 --> 00:52:43,000
Speaker 1: coaling cancer and it Please Whenever I say these things,

929
00:52:43,080 --> 00:52:45,279
Speaker 1: I worry that people will say, oh, we'll wait to

930
00:52:45,360 --> 00:52:47,600
Speaker 1: get screen when they come up with the breathalyzer. Do

931
00:52:47,680 --> 00:52:50,280
Speaker 1: not wait, ladies and gentlemen. In fact, if you're forty

932
00:52:50,360 --> 00:52:53,319
Speaker 1: five are over, the American Cancer Society just lower the

933
00:52:53,360 --> 00:52:59,239
Speaker 1: age for a baseline screening colonoscopy or baseline screening for

934
00:52:59,400 --> 00:53:03,000
Speaker 1: coaling can are tot so please please, please get screen.

935
00:53:03,440 --> 00:53:05,680
Speaker 1: But it's it was so interesting to me. They were

936
00:53:05,760 --> 00:53:10,080
Speaker 1: kind of comparing how dogs can sniff out like diabetes.

937
00:53:10,160 --> 00:53:14,960
Speaker 1: Now it's so crazy, but so wild and cool too.

938
00:53:15,000 --> 00:53:17,960
Speaker 1: I mean, what do you think about that? Yes, I've

939
00:53:18,000 --> 00:53:20,400
Speaker 1: heard a little bit about this from Jonathan Simon's at

940
00:53:20,400 --> 00:53:22,839
Speaker 1: the Process Cancer Foundation works with Michael Milk, and he's

941
00:53:22,880 --> 00:53:25,399
Speaker 1: my my roommates. I get to hear a lot about

942
00:53:26,200 --> 00:53:28,000
Speaker 1: you guys. Must be really fun when you go out

943
00:53:28,040 --> 00:53:31,720
Speaker 1: for a beer. Yeah, we're exactly not exciting even slightly

944
00:53:32,320 --> 00:53:35,160
Speaker 1: like those two old guys in the Muppet television programs.

945
00:53:35,680 --> 00:53:38,200
Speaker 1: But no, they can train dogs to sniff out of

946
00:53:38,280 --> 00:53:42,200
Speaker 1: rioted diseases. These presumably are compounds, chemical compounds that are

947
00:53:42,320 --> 00:53:45,960
Speaker 1: very volatile dogs have. I forget what it is fifty

948
00:53:46,000 --> 00:53:48,600
Speaker 1: two a hundred times the number of odorant receptors in

949
00:53:48,640 --> 00:53:50,880
Speaker 1: their nose as human, so they can smell things better.

950
00:53:51,560 --> 00:53:53,880
Speaker 1: And I think the answer is what exactly are they smelling?

951
00:53:53,880 --> 00:53:56,120
Speaker 1: If they can sniff out cancer and other diseases, and

952
00:53:56,160 --> 00:53:58,880
Speaker 1: can we develop ways to measure them? And then the

953
00:53:58,920 --> 00:54:01,560
Speaker 1: next question is, as that gets you any earlier or

954
00:54:01,600 --> 00:54:05,399
Speaker 1: any more specific than colonoscopy or a DNA based test

955
00:54:05,520 --> 00:54:08,080
Speaker 1: or something like that, do you think that cancer will

956
00:54:08,440 --> 00:54:11,440
Speaker 1: one day soon? And if you could you even predict

957
00:54:11,480 --> 00:54:18,000
Speaker 1: when be a be a disease of the past. Yeah,

958
00:54:18,080 --> 00:54:21,279
Speaker 1: that's a great question. I think we'll be grappling with

959
00:54:21,360 --> 00:54:24,279
Speaker 1: it for quite a while. And I think, uh, one

960
00:54:24,320 --> 00:54:27,360
Speaker 1: of the reasons is that every time one cell divides

961
00:54:27,440 --> 00:54:31,200
Speaker 1: to become two of those three billion base pairs, it

962
00:54:31,239 --> 00:54:33,600
Speaker 1: makes a bunch of mistakes, thousands of them. Most of

963
00:54:33,600 --> 00:54:37,120
Speaker 1: them get fixed, but about five to ten sneak through.

964
00:54:37,920 --> 00:54:42,000
Speaker 1: And as long as that happens, then cancer will hopefully

965
00:54:42,000 --> 00:54:44,760
Speaker 1: be a rare disease. But I think we'll still still

966
00:54:44,800 --> 00:54:47,879
Speaker 1: likely have cancer to deal with. Well, we are going

967
00:54:47,960 --> 00:54:51,480
Speaker 1: to be dropping this episode, as they say in the BIZ,

968
00:54:51,560 --> 00:54:55,200
Speaker 1: one day before our fifth biennial stand up to cancer

969
00:54:55,280 --> 00:54:58,359
Speaker 1: telecasts that's every two years, and I'm very excited. I'm

970
00:54:58,360 --> 00:55:00,480
Speaker 1: going to be going out to l a Brian. I

971
00:55:00,480 --> 00:55:03,360
Speaker 1: hope he'll come this year with your lovely bride, Claire,

972
00:55:04,000 --> 00:55:08,160
Speaker 1: and and we have a lot of big, boldface names

973
00:55:08,200 --> 00:55:13,080
Speaker 1: like me Herschela Ali from Moonlight and Kathy Bates who

974
00:55:13,200 --> 00:55:16,920
Speaker 1: herself as a cancer survivor. Jennifer Garner, he's so cute.

975
00:55:16,960 --> 00:55:19,480
Speaker 1: I'm actually excited to meet her. I guess I've met her,

976
00:55:19,520 --> 00:55:21,439
Speaker 1: but I've seen her in a long time. Tony Hale,

977
00:55:21,880 --> 00:55:25,640
Speaker 1: at Helms ken Jong, whose wife is a breast cancer survivor,

978
00:55:25,800 --> 00:55:31,000
Speaker 1: Matthew McConaughey, Marley Mattlin who I love, Trevor Noah, we

979
00:55:31,040 --> 00:55:36,040
Speaker 1: have Reese Witherspoon, Keith Irvin, David Spade, Brian Goldsmith, Katie Curic,

980
00:55:36,400 --> 00:55:40,239
Speaker 1: Bill Nelson. Actually, one of my favorite moments in our

981
00:55:40,280 --> 00:55:43,680
Speaker 1: past telecast, Briant, is when we brought all the scientists

982
00:55:43,680 --> 00:55:46,399
Speaker 1: on stage, because truly, and you've heard me say this

983
00:55:46,680 --> 00:55:49,120
Speaker 1: time and time again, but me, me, my listeners haven't

984
00:55:49,719 --> 00:55:54,560
Speaker 1: Cancer researchers and scientists are my heroes. They are so

985
00:55:54,840 --> 00:56:02,200
Speaker 1: extraordinarily dedicated and committed and super smart, scary, smart, and

986
00:56:02,280 --> 00:56:05,440
Speaker 1: I feel like they don't get enough accolades in our

987
00:56:05,480 --> 00:56:09,839
Speaker 1: current culture. So to be able to celebrate everything you

988
00:56:09,920 --> 00:56:13,880
Speaker 1: all do is such a thrill for me, and I

989
00:56:13,960 --> 00:56:17,120
Speaker 1: hope that we'll be able to celebrate you all this

990
00:56:17,200 --> 00:56:19,520
Speaker 1: year as well. I'm sure we're going to be giving

991
00:56:19,520 --> 00:56:21,600
Speaker 1: you a big round of applause. I don't think your

992
00:56:21,640 --> 00:56:25,040
Speaker 1: band is playing Bill this year. And during our telecast,

993
00:56:25,160 --> 00:56:27,319
Speaker 1: you do play in a in a band I do,

994
00:56:27,400 --> 00:56:29,600
Speaker 1: and it's a it's a blast that no question tell

995
00:56:29,680 --> 00:56:33,160
Speaker 1: us about that is that a cancer band. Actually the

996
00:56:33,200 --> 00:56:36,640
Speaker 1: woman who fronts the band is a breast cancer survivor, actually,

997
00:56:36,680 --> 00:56:39,560
Speaker 1: and uh, and we were able to help her and uh,

998
00:56:40,000 --> 00:56:42,400
Speaker 1: and she's very public about her case, talks about it,

999
00:56:42,440 --> 00:56:45,120
Speaker 1: and it's it's wonderful to see. There's a lot of uh.

1000
00:56:45,640 --> 00:56:48,319
Speaker 1: I'm sure that's why so many musical artists contribute. There's

1001
00:56:48,360 --> 00:56:50,399
Speaker 1: a lot of people in the music business been very

1002
00:56:50,400 --> 00:56:52,560
Speaker 1: deeply touched by cancer and want to get back. It's

1003
00:56:52,600 --> 00:56:55,000
Speaker 1: really no surprise, Bill, when you consider that one in

1004
00:56:55,080 --> 00:56:58,320
Speaker 1: three Americans will be diagnosed with some kind of cancer

1005
00:56:58,560 --> 00:57:01,160
Speaker 1: during the course of their lifetime. Times that so many

1006
00:57:01,239 --> 00:57:05,160
Speaker 1: people want to participate in stand up to cancer. And

1007
00:57:05,200 --> 00:57:07,560
Speaker 1: I also want to say how grateful we are to

1008
00:57:07,640 --> 00:57:12,400
Speaker 1: all the people who are so generous with their their time, attention,

1009
00:57:12,440 --> 00:57:16,360
Speaker 1: and energy, and that they're willing to spend Friday night,

1010
00:57:16,800 --> 00:57:19,600
Speaker 1: uh talking about this disease. And this year we're going

1011
00:57:19,640 --> 00:57:23,080
Speaker 1: to be celebrating all the victories that we've seen. You know,

1012
00:57:23,200 --> 00:57:26,200
Speaker 1: sometimes this is such a heavy subject and it's so

1013
00:57:26,240 --> 00:57:29,360
Speaker 1: sad for so many people, but there are also so

1014
00:57:29,440 --> 00:57:33,520
Speaker 1: many survivors out there, and on this telecast, I think

1015
00:57:33,560 --> 00:57:37,280
Speaker 1: we're going to talk about the hope that all this

1016
00:57:37,440 --> 00:57:41,480
Speaker 1: research is ushering in for so many families, and it's

1017
00:57:41,480 --> 00:57:43,920
Speaker 1: going to happen. It's it's happening more and more. One

1018
00:57:43,920 --> 00:57:46,360
Speaker 1: of the biggest groups growing in the United States now,

1019
00:57:46,360 --> 00:57:50,640
Speaker 1: our cancer survivors fourteen sixteen, eighteen million or whatever the

1020
00:57:50,680 --> 00:57:52,480
Speaker 1: last number I saw. It's great to see and I

1021
00:57:52,520 --> 00:57:54,720
Speaker 1: hope people will get involved. You know, when I lost

1022
00:57:54,760 --> 00:57:58,440
Speaker 1: my husband and also my sister, I found being proactive

1023
00:57:58,880 --> 00:58:03,360
Speaker 1: and carrying a out something bigger than yourself and wanting

1024
00:58:03,400 --> 00:58:07,880
Speaker 1: to help other people was so cathartic for me and

1025
00:58:08,080 --> 00:58:12,320
Speaker 1: in fact, John McCain I posted on my Instagram a

1026
00:58:12,480 --> 00:58:17,320
Speaker 1: quote by John McCain. He said, if you find faults

1027
00:58:17,360 --> 00:58:20,000
Speaker 1: with our country, make it a better one. And then

1028
00:58:20,000 --> 00:58:22,520
Speaker 1: he goes on to ways that you can do things,

1029
00:58:22,680 --> 00:58:26,280
Speaker 1: and he says, our country will be better and you

1030
00:58:26,320 --> 00:58:29,680
Speaker 1: will be happier because nothing brings greater happiness in life

1031
00:58:29,880 --> 00:58:33,919
Speaker 1: than to serve a cause greater than yourself. So when

1032
00:58:33,960 --> 00:58:37,720
Speaker 1: people ask me what can I do? I always say,

1033
00:58:37,840 --> 00:58:42,360
Speaker 1: do anything. Make a small contribution of five dollars, get

1034
00:58:42,400 --> 00:58:46,320
Speaker 1: your kids to have elimonade stand you know, maybe get

1035
00:58:46,360 --> 00:58:50,040
Speaker 1: involved in a local cancer charity that gives support to

1036
00:58:50,200 --> 00:58:53,400
Speaker 1: patients who need it, who need even a drive to

1037
00:58:53,440 --> 00:58:56,560
Speaker 1: the doctor to get their chemo treatments. There's so many

1038
00:58:56,600 --> 00:58:59,800
Speaker 1: things that you can do, and I think the feeling

1039
00:58:59,840 --> 00:59:06,080
Speaker 1: of powerlessness that is so overwhelming during a cancer diagnosis

1040
00:59:06,160 --> 00:59:12,000
Speaker 1: or a cancer experience can be really offset by doing

1041
00:59:12,080 --> 00:59:15,240
Speaker 1: something proactive. So for all of you listening out there

1042
00:59:15,280 --> 00:59:18,040
Speaker 1: who have been touched by cancer and affected by it

1043
00:59:18,400 --> 00:59:21,840
Speaker 1: or are dealing with it right now, UM, we would

1044
00:59:21,920 --> 00:59:24,600
Speaker 1: so welcome your involvement with Stand Up to Cancer, and

1045
00:59:24,640 --> 00:59:27,280
Speaker 1: you can go to our website and learn the myriad

1046
00:59:27,320 --> 00:59:29,920
Speaker 1: of ways that you can get involved. Can you tell

1047
00:59:30,000 --> 00:59:33,920
Speaker 1: him a little passionate about this? Well, as you know

1048
00:59:34,480 --> 00:59:37,480
Speaker 1: and you mentioned this. I think all the physicians and

1049
00:59:37,480 --> 00:59:40,360
Speaker 1: scientists that work on cancer are passionate as well and

1050
00:59:40,760 --> 00:59:44,080
Speaker 1: cannot be more thankful to you and the women who

1051
00:59:44,120 --> 00:59:46,680
Speaker 1: run Stand Up to Cancer that both raise funds for

1052
00:59:46,760 --> 00:59:49,960
Speaker 1: the combat this disease and then increase the awareness of

1053
00:59:50,000 --> 00:59:53,919
Speaker 1: it so that everybody does better. It's it's it's really something. Well.

1054
00:59:54,120 --> 00:59:55,800
Speaker 1: I always say it's going to be the first line

1055
00:59:55,800 --> 00:59:59,320
Speaker 1: in my obituary, but hopefully that won't be written anytime,

1056
00:59:59,400 --> 01:00:03,520
Speaker 1: reels Bill Nelson. I'm bad happy you note. Thank you

1057
01:00:03,600 --> 01:00:06,120
Speaker 1: so much, Bill again for everything you do, for coming

1058
01:00:06,200 --> 01:00:08,919
Speaker 1: here and being on our podcast. Brian, you want to say,

1059
01:00:09,000 --> 01:00:11,840
Speaker 1: by the Bill to Bill, really appreciate your taking the

1060
01:00:11,960 --> 01:00:15,960
Speaker 1: time and educating us about cancer and the future of cancer.

1061
01:00:16,080 --> 01:00:18,440
Speaker 1: And I'm more optimistic than I was before we had

1062
01:00:18,480 --> 01:00:21,240
Speaker 1: this conversation. Well, Suber, You're both are welcome and thank

1063
01:00:21,240 --> 01:00:26,800
Speaker 1: you for having me. That wraps things up for us

1064
01:00:26,840 --> 01:00:29,160
Speaker 1: for today. Everyone. If you'd like to learn more about

1065
01:00:29,240 --> 01:00:32,240
Speaker 1: Stand Up to Cancer, or get involved, or even make

1066
01:00:32,240 --> 01:00:35,400
Speaker 1: a small contribution, please head to stand Up to Cancer

1067
01:00:35,720 --> 01:00:38,160
Speaker 1: dot org. Every couple of years around this time I

1068
01:00:38,200 --> 01:00:41,320
Speaker 1: make a contribution. I'm really glad that I have and

1069
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Speaker 1: I'd encourage everyone to do the same. Whether it's five

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01:00:44,040 --> 01:00:47,040
Speaker 1: dollars or five thousand dollars, you should give whatever you

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01:00:47,080 --> 01:00:50,160
Speaker 1: can because I can't imagine a better cause. Thank you, Brian,

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Speaker 1: and thanks as usual to our production team, Gianna Palmer,

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Speaker 1: our producer, Nor Richie, our assistant producer, and Jared O'Connell,

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01:00:57,200 --> 01:01:00,440
Speaker 1: who mixes and engineers the show. And beth A mas

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01:01:00,640 --> 01:01:03,479
Speaker 1: is a rock star in her own right here here.

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01:01:03,680 --> 01:01:07,439
Speaker 1: Special thanks this week to Jon Asanti for his production help,

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01:01:07,800 --> 01:01:11,360
Speaker 1: as well as Andy Kristen's and Jordan Duffy for engineering.

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Speaker 1: And a big thank you this week to Kathleen lab

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Speaker 1: my friend and colleague since nineteen Excuse me, I am

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01:01:18,840 --> 01:01:21,480
Speaker 1: so sorry. Kathleen and I not only went to the

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01:01:21,560 --> 01:01:24,840
Speaker 1: University of Virginia together, but she is a huge and

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01:01:24,920 --> 01:01:28,160
Speaker 1: important force behind Stand Up to Cancer and I feel

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01:01:28,200 --> 01:01:30,520
Speaker 1: so honored to be able to work with her after

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01:01:30,600 --> 01:01:33,280
Speaker 1: all these years. As always, a big thank you to

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01:01:33,400 --> 01:01:36,120
Speaker 1: Mark Phillips for our theme music. Brian and I are

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01:01:36,160 --> 01:01:40,760
Speaker 1: the show's executive producers. For better or for worse, Remember

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01:01:40,800 --> 01:01:43,560
Speaker 1: we love hearing from you over at comments at correct

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01:01:43,640 --> 01:01:46,600
Speaker 1: podcast dot com. We'll take questions. Guest ideas and of

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01:01:46,640 --> 01:01:49,760
Speaker 1: course feedback. You can also leave us a message at

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01:01:49,880 --> 01:01:53,120
Speaker 1: nine two to four, four, six, three seven. I'm on

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01:01:53,200 --> 01:01:57,160
Speaker 1: social media a lot under Katie Kirk. By the way,

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01:01:57,200 --> 01:02:00,120
Speaker 1: just follow me on Instagram. I'm a story make and

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01:02:00,240 --> 01:02:04,240
Speaker 1: full and Brian sends Twitter missives from the handle at

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01:02:04,360 --> 01:02:07,560
Speaker 1: Goldsmith b And if you've listened this far and you

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01:02:07,680 --> 01:02:10,800
Speaker 1: like the if one of you out there is listening

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01:02:10,840 --> 01:02:14,160
Speaker 1: this far, God help you, please know that we'd also

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01:02:14,200 --> 01:02:17,160
Speaker 1: appreciate it if you'd rate and review us on Apple Podcast.

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01:02:17,280 --> 01:02:20,080
Speaker 1: It helps more people to find the show. And don't

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01:02:20,080 --> 01:02:23,040
Speaker 1: forget to subscribe as well as always, thank you so

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01:02:23,120 --> 01:02:25,520
Speaker 1: much for listening, and we'll talk to you next week.