Tumor Genetics vs. Family Genetics in Lung Cancer: What Is the Difference

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Tumor Genetics vs. Family Genetics in Lung Cancer: What is the Difference? from Patient Empowerment Network on Vimeo.

What do lung cancer patients need to know about genetic testing? Dr. Lecia Sequist explains the two types of genetic testing and how the test results are used to create optimal treatment plans for personalized care.

Dr. Sequist is program director of Cancer Early Detection & Diagnostics at Massachusetts General Hospital and also The Landry Family Professor of Medicine at Harvard Medical School.

[ACT]IVATION TIP:

“…if you’ve been diagnosed with cancer, you should talk to your doctor about whether you should get genetic testing, either of your cancer cells or of your familial genetic background. And sometimes the answer will be yes to both those. But know that there are two different types of genetic testing.”

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Transcript:

Lisa Hatfield:

Dr. Sequist, can you please explain what genetic testing is for cancer patients?

Dr. Lecia Sequist:

Yeah. This can be a really complicated area, so I’m so glad you asked me this question. I think genetic testing basically is looking at the genes. So inside each cell in our body, there are…there’s DNA, which is the genes, and the DNA is kind of like an instruction manual for your cells, and like any instruction manual it has different pages, it has different chapters and individual words. And when they’re doing genetic testing, they’re looking to see if any of those chapters or pages or words have a typo or maybe were deleted, sometimes a whole page or a whole chapter is deleted, or sometimes a chapter is picked out of where it’s supposed to go and shoved in another part of the book. And looking for these different kinds of mistakes or edits in the genes is what genetic testing does. But we can do genetic testing on different parts. When you’re talking about a patient who has cancer, there’s basically two different areas that can be tested genetically. One is the patient’s healthy body, the genes they were born with, that they inherited from their parents, that they’ve had their whole life or they could pass on to their children if they have children. And so that type of genetics is called the germline genetics, but it basically is the type of genes you can get from your parents or pass on to your children.

If you have been diagnosed with cancer, there’s a separate set of DNA, set of genetic testing, which is done on the cancer cells. And a lot of times those genes have not been with you your whole life, they just came up at the time that the first cancer cell appeared in your body. And they may be different than the germline genes you inherited from your parents. And so depends on the type of cancer that you have, there are some types of cancer where it is very common to look at the germline cancer gene…sorry, the germline genes to see if you have a predisposition for cancer. This is done a lot of times in breast and ovarian cancer and sometimes with colon cancer, where we know there are genes that can run in families that can predispose people to getting cancer. And the reason that’s done, if you’re diagnosed with cancer and they wanna check your familial genes, it’s because they wanna know if other people in your family might be at risk for the same type of cancer. Does this have implications for how your sister should be treated medically or your child?

Separately for lung cancer, for example, which I treat, we’re usually doing genetic testing on the cancer, and we’re looking at what’s making that cancer cell tick. Are there treatments, are there different drugs or therapies that we can give that will kill the cancer based on the genes that are in the cancer? And so that tumor cancer genetic testing is often called genotyping or it’s testing the somatic, which just means the cancer cells, the somatic genetic testing. But it’s complicated, and I think people, rightfully so, get confused about all these different types of genetic testing. I guess my activation tip for this question would be, if you’ve been diagnosed with cancer, you should talk to your doctor about whether you should get genetic testing, either of your cancer cells or of your familial genetic background. And sometimes the answer will be yes to both those. But know that there are two different types of genetic testing. 

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What Steps Can BIPOC Lung Cancer Patients Take to Guard Against Care Disparities?

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What Steps Can BIPOC Lung Cancer Patients Take to Guard Against Care Disparities? from Patient Empowerment Network on Vimeo.

How can BIPOC lung cancer patients or other underrepresented  patients help guard against care disparities? Expert Dr. Lecia Sequist shares advice for non-small cell lung cancer (NSCLC) patients to help ensure they receive optimal treatment with the most advanced treatments available.

Dr. Sequist is program director of Cancer Early Detection & Diagnostics at Massachusetts General Hospital and also The Landry Family Professor of Medicine at Harvard Medical School.

[ACT]IVATION TIP:

“You don’t have to ask permission to get a second opinion, you can just make an appointment with a different oncologist or go to an oncologist if you haven’t seen one before. Because lung cancer is changing and treatments are more successful, and we all have to do more as a community to make sure that those treatments are offered to everyone.”

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 Tumor Genetics vs. Family Genetics in Lung Cancer: What is the Difference

Tumor Genetics vs. Family Genetics in Lung Cancer: What is the Difference

Transcript:

Lisa Hatfield:

So, Dr. Sequist, we know that there are significant disparities in the treatment and the outcomes of minority patients who have non-small cell lung cancer. How can patients avoid these discrepancies in the timeliness of their diagnosis, because that can be an important factor in their outcome?

Dr. Lecia Sequist:

Yeah. I think lung cancer has changed a lot, but in the last 10 years, and there are better treatments than there used to be, and there’s a lot more treatments than there used to be, but not all doctors are aware of these new developments. And I think some doctors still have a kind of an old-fashioned nihilistic view about lung cancer, which can be very negative, which is that lung cancer can’t be treated effectively and patients are just going to do very poorly. That’s not true anymore. It may have been true 20, 30 years ago, unfortunately. But with treatments today, lung cancer patients can live longer, be cured more often and have better quality of life than with some of the older treatments.

And I think in the ideal world, the responsibility really should be on the physicians to make sure that they’re offering those treatments to patients, but in the real world, that doesn’t always happen. And so I think something that patients can do to empower themselves is also to ask their physicians if there’s anything else that can be done or if they should see a second opinion. If you’re feeling like your doctor is not offering you really many options or is being kind of nihilistic, having a very negative picture of what might happen to you with your cancer, then I would just get a second opinion. You don’t have to ask permission to get a second opinion, you can just make an appointment with a different oncologist or go to an oncologist if you haven’t seen one before. Because lung cancer is changing and treatments are more successful, and we all have to do more as a community to make sure that those treatments are offered to everyone. But until that day comes, I think patients also need to feel empowered to ask for other treatments and other opinions. 

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Can Artificial Intelligence and Machine Learning Help Advance Screening for Lung Cancer?

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Can Artificial Intelligence and Machine Learning Help Advance Screening for Lung Cancer? from Patient Empowerment Network on Vimeo.

How will lung cancer personalized medicine be improved with advanced technologies? Expert Dr. Lecia Sequist explains how artificial intelligence and machine learning help advance screening for lung cancer and shares advice for patients.

Dr. Sequist is program director of Cancer Early Detection & Diagnostics at Massachusetts General Hospital and also The Landry Family Professor of Medicine at Harvard Medical School.

[ACT]IVATION TIP:

“… if you are 50 and you have smoked in the past, I would urge you to talk to your doctor about whether you can access lung cancer screening. But if you’re younger or you haven’t smoked in the past, you can’t access lung cancer screening right now. And we’re hoping to change that with AI that can really help figure out who is at risk of this disease.”

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Transcript:

Lisa Hatfield:

Dr. Sequist, technology is advancing at such a fast pace, and we’re hearing words like artificial intelligence and machine learning. And I just read an article about a team that you’ve been working with that is developing or has developed an AI model that can detect future lung cancer risk. I believe it’s based on CT scans. Can you speak to that a little bit more and also talk a little bit more about where you see this AI technology taking cancer research and predicting cancer and also any challenges that we might face with AI and machine learning in healthcare?

Dr. Lecia Sequist:

Yeah. AI seems to be everywhere. You turn on the news or you look at your phone, and it’s talking about AI. And some of it seems scary, and Hollywood doesn’t help because there’s lots of movies about computers or robots kind of taking over the human race. And I think we have to separate Hollywood from real life. Artificial intelligence or machine learning, it’s a very general term. It can mean a lot of different things depending on what the context is. But it’s basically just a tool for understanding patterns. And we all understand patterns in our own life or our own house. I personally know that my dog is going to want to, as soon as we wake up in the morning, is going to want to go outside and then is going to want to have some food, and there are different patterns that you know in your daily life that you recognize, and you can anticipate what’s going to happen next.

AI is a tool that helps us anticipate what’s going to happen next for patterns that are way more complex than, yeah, your dog’s going to want to go outside and eat some food. So computers can sometimes pick up patterns that the human brain can’t really pick up, because they’re just too complicated. And that’s what we’ve found in our research. One of the vaccine things about lung cancer and trying to figure out how we can prevent lung cancer or find it at the earliest stage when it’s most curable is that it’s very hard to know who’s at risk. We know that lung cancer is one of the most common cancers out there, but knowing who is truly at risk and separating one person from the next is not so simple.

In the past, it’s mainly been, you know, determined by whether or not you ever smoke cigarettes. And it’s true that cigarette smoking is one risk factor for lung cancer, but it’s not the only one. And we don’t fully understand what all the risk factors might be, but we know that there are people who have smoked a lot in their life and never get lung cancer. And on the flip side, we know that there’s people who have never smoked or who maybe quit 30, 40 years ago and will still get lung cancer. And how do we know who’s at risk? That’s what we tried to solve with our research that I worked on with my colleagues at Mass General Hospital where I work and also at MIT, Massachusetts Institute of Technology, which is just down the road from us. And so we brought together our medical knowledge and our computer knowledge and tried to come up with a way to predict for any given individual person, are they at risk for lung cancer.

By looking at their lungs and not looking at the lungs the way a human radiologist sort of says, okay, there’s the right lung, there’s the left lung, and they’re looking for things that already exist like a tumor or a mass. The computer looks at a different type of pattern that human eyes and brains can’t really recognize and has learned the pattern, because we trained the computer with thousands and tens of thousands of scans where we knew this person went on to develop cancer and this one didn’t. And the computer learned the pattern of risk. And so using an X-ray or a CAT scan to predict future risk is something a little different. In medicine, we usually use an X-ray to say, okay, what’s happening now? Why does this patient have a fever? Why is this patient bleeding? And using an X-ray or a CAT scan in this case to predict the future is kind of a new thought for doctors. But we think that it could be a really valuable tool to help us understand who’s at risk for many different kinds of diseases. We happen to look at lung cancer, but I think you could use this idea for other diseases too.

Lisa Hatfield:

So will this AI model become mainstream anytime soon if a patient wants to access that? Or is it only being used for research purposes?

Dr. Lecia Sequist:

Well, we do before we start to offer anything mainstream or as part of routine care, we really need to understand how it can be used to help patients. So we are running some clinical trials right now to try and understand, is this a tool that could be used, for example, to give someone access to lung cancer screening? Because right now, if you want to have lung cancer screening, which is a very effective screening test to try and find cancer in people who feel completely well, trying to find cancer at the earliest stage before it has spread, can we give people access to lung cancer screening by using this AI test? Right now and if you want to get lung cancer screening, you have to be 50 or older, and you have to have smoked in the past. And if that fits your, if you are 50 and you have smoked in the past, I would urge you to talk to your doctor about whether you can access lung cancer screening. But if you’re younger or you haven’t smoked in the past, you can’t access lung cancer screening right now. And we’re hoping to change that with AI that can really help figure out who is at risk of this disease.

Lisa Hatfield:

Thank you. I’m excited to see where this goes in the future. 

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