Overview of how the PE-CGS Network defined, implemented, and evaluated strategies to engage participants and communities in cancer genomic sequencing research, and how engagement optimization using scientific methods informed study practices.
0:00Welcome to Base by Base, the paper cast that brings genomics to you wherever you are. Thanks for listening, and don't forget to follow and rate us in your podcast app. So, you know, when we think about the whole genomic revolution, We usually picture this pristine high tech future, right?
0:15Oh yeah, like supercomputers, crunching DNA, targeted therapies, all of that. Exactly. We imagine these cures tailored to your exact biological makeup. But there is actually this staggering reality, hiding behind all that progress.
0:31historically, massive segments of the population have been completely left out of this revolution. Yeah, entirely left out. Right, due to geographical barriers or deep seated distrust. Or just research designs that completely ignore their lived experiences.
0:45And it creates a massive blind spot in the science. I mean, we are talking about entire communities being effectively excluded from the most advanced medical data pools on the planet. Which really forces us to ask a difficult question for this deep dive.
0:58What really happens when the very people who stand to benefit the most from genetic breakthroughs just decline to participate. Like, how could this change if scientists treated community engagement with the exact same rigor they apply to sequencing DNA?
1:13Because, you know, if your underlying data only reflects a narrow slice of humanity, Your precision medicine isn't actually precise for everyone else. It's just skewed Right. The algorithms and therapies are skewed from the ground up.
1:27Today we celebrate the work of Nora L. Crossno here and L.R. Schuster and their colleagues representing the PECGS Network, who have advanced our understanding of community and participant engagement in cancer genomics.
1:40Yeah, and this research was published in genetics and medicine, which is the official journal of the American College of Medical Genetics and Genomics. It provides a major platform for figuring out how we translate these genetic discoveries into health outcomes that actually reach everyone, you know, not just a select few.
1:56So let's set the stage here, to really understand why this research is so crucial. We have to rewind a bit to 2016. The National Cancer Institute launch the cancer moonshot with this incredibly ambitious stated goal to end cancer as we know it.
2:12The funding and the ambition for that were just unprecedented, but a major persistent gap quickly became really obvious to the scientific community. Understudied populations, specifically groups facing significant incidents and outcome disparities, or folks dealing with rare cancers, they simply weren't participating in these massive genomic research trials.
2:35Yeah, obviously, if they aren't participating, their genetic data isn't in the databases. The NCI recognize that this lack of representation fundamentally limits the development of evidence-based cancer control, prevention and intervention.
2:47You can't cure a disease across a whole population if you only study a tiny fraction of it. Exactly. So to address this foundational flaw, the NCI established the participant engagement in cancer genome sequencing network.
2:59Which we'll just call the PECGS network for short. Right, the PECGS network. Their mission was to bridge this gap and figure out how to successfully invite understudied populations into these vital research studies.
3:12Okay let's unpack this. Is this like building a state of the art, high-tech library, but placing it in a neighborhood where no one has a library card, and the books aren't even in their language? Yeah, I mean, that captures the structural problem perfectly.
3:26And the PECGS network realized that you can't just unlock the library doors and just sort of expect people to walk in. Engagement optimization isn't just opening the doors, is hiring a librarian who speaks the neighborhood's language, putting a community coffee shop in the lobby and, you know, actually asking the locals which books they want to read before you even stock the shots.
3:46Engagement optimization. It sounds very clinical, but it's really about applying hard science to the act of connecting with people. It is. It's the idea that engaging participants shouldn't just be an art or a gut feeling.
3:58It has to be an ongoing, scientifically rigorous process. But, I mean, looking at DNA is straightforward, right? You run a sample through a sequencer. How do you study the process of engagement across an entire research network?
4:12Well, the researchers focused on the network's 1st 3 years of activity. So that's from September 2020 to August 2023. And instead of looking at biological data, they looked at operational data across 5 distinct research centers.
4:26Operational data. Yeah, they used a mix of key inform interviews and extensive document reviews. Wait, like, they evaluated presentation slides and website posts? How does analyzing a PowerPoint deck actually translate to getting more people into a cancer trial?
4:42I know, it seems totally disconnected from hard biology, but they used a methodology called qualitative content analysis. They aren't just checking for typos. They are functionally mapping how a research team signals trust and accessibility.
4:54They look at research protocols, specific aims pages, social media posts, informed consent forms, all of it, searching for patterns and communication. So they're tracking the mechanism of connection. Exactly.
5:06How each center approaches different stages of a study. From the initial outreach, all the way to returning the genetic results to the patient. Wow, so they didn't just ask if the patients like the researchers, they brought real scientific methodology to bear on human interaction itself.
5:23What's fascinating here is that they applied the same rigorous methods we usually reserve for clinical trials. Really? Yeah, they use rapid cycle research. So conducting quick, incremental, scalable tests to see what communication works best.
5:37And they even used randomized controlled trials to test different engagement strategies against each other. Wait, they ran AB tests on how they treat people in a medical study? That is incredible. It really is.
5:48But before we get into tactics, we should probably define what the network agreed these terms actually mean. Yeah. Getting everyone on the same page was a major 1st step. They define engagement as the sustained, beneficial interaction between research teams and diverse individuals to inform research processes and improve outcomes.
6:05So it's an ongoing relationship. Not a one-off transaction where you just take their blood and leave. Exactly. And optimization is taking that relationship and applying scientific principles to analyze and act on the insights.
6:17You measure what's working and you iterate. So you're constantly improving. The paper breaks this down beautifully by looking at the 5 different research centers in the network, each focusing on different cancers and different understudy populations.
6:30Here's where it gets really interesting. Let's look at the specific tactics these centers used because this is where the theory hits reality. We'll start with the universe center, which focuses on American Indian adults with various types of cancer.
6:43If standard informed consent forms are essentially dense legal traps filled with intimidating medical jargon. Juniper must have had to completely tear down that framework to build trust with indigenous populations.
6:55Oh, they absolutely did. Juniper completely reimagined the informed consent process. They recognized that just using simpler vocabulary wasn't going to be enough. They needed to anchor the science directly to the community's cultural values.
7:09So what do they do? They actually brought in an indigenous artist to create visually enhanced informed consent documents. Wow. They integrated indigenous visual artwork directly into the legal and medical paperwork.
7:23Yes, using imagery like an eagle feather intertwined with a DNA stem. That's beautiful. Right. And in many American Indian cultures, the eagle feather represents strength and wisdom. By intertwining it with DNA.
7:36They visually communicate that participation in genomic research honors their inherent strength and contributes to collective wisdom. That is so powerful. They also used imagery of dragonflies and floral patterns, which symbolize hope, healing, and luck.
7:49And the researchers didn't just guess what might look nice to the community, right? No, not at all. They convened a tribal advisory committee made up of tribal leaders and cancer survivors. Oh, nice. This committee reviewed and approved all the design elements to ensure they authentically reflected indigenous ways of knowing.
8:06This approach acknowledges tribal sovereignty and respects cultural values, which, you know, historically have been completely violated in scientific research. Building that structural respect is the actual mechanism that generates profound trust.
8:18Exactly. So if Juniper completely tore down the visual framework of the consent process to build trust. The 2nd center, Count me in, had to do something similar with the actual verbal language. They focus on rare sarcomas, specifically osteosarcoma, and layomyosarcoma.
8:36Yeah, Count Me In provides a brilliant example of optimizing language based on direct community feedback. They conducted focus groups to understand how participants process the information they were receiving.
8:47Okay. Originally the researchers were using the standard clinical phrase for giving patients their genetic data back. They called it return of somatic results. Oh gosh. Imagine you're sitting in a clinical office dealing with a terrifying rare sarcoma diagnosis.
9:02A researcher hands you a paper that says, return of some attic results. You'd probably feel completely alienated. It sounds like a robot handy you receive. Yeah, and the focus groups confirmed that it was entirely alienating.
9:13So the center optimized. They changed the phrasing to shared learnings about your tumor. Shared learnings about your tumor. Wow. That subtle shift in language does more than just sound nice. It shifts the entire dynamic from a transactional data dump to a collaborative journey.
9:30Exactly. It tells the patient, we are learning this together. Validated by the community, that phrasing significantly warms the interaction. It makes the participant feel like a valued partner in the scientific process, not just a biological data source.
9:45So changing the language on a form builds trust. What if the barrier isn't the language, but the participant's immediate physical reality? That is exactly the puzzle the optimum center had to solve. Right.
9:58They focus on adults with lower grade glioma, which is a type of brain tumor. Yeah. Optimum recognized that to get people to participate in genomic research, you have to provide value to them outside of the research itself.
10:09You have to address their immediate daily realities. So what was their approach? To optimize recruitment and retention, they hosted bilingual webinars in English and Spanish. But these weren't webinars about DNA sequencing, were they?
10:21Not at all. They focused on topics the community desperately needed help with right now. things like navigating disability services, improving quality of life, and figuring out how to discuss genomic testing with their own healthcare providers.
10:35They essentially told the community, before we ask you for your genomic data, let us help you navigate the incredibly difficult reality of living with a brain tumor. Exactly. And they also posted all these recordings on their public website so anyone in the brain tumor community could access them, whether they join the study or not.
10:55Wow, that's amazing. Providing that kind of tangible immediate support demonstrates that the research center cares about the whole person. It is a masterclass in community building that really pays dividends when it comes time to actually ask for research participation.
11:09Absolutely. Moving from the lived reality of the patients to the messengers themselves. We look at the 4th center, kopec. They focus on colorectal cancer in Hispanic and Latino adults. Yeah, Kopek turned their attention heavily toward the people who serve as the bridge between the research institution and the local community.
11:25The community health educators. Right. The community health educators, these are the trusted local voices on the ground. Because, I mean, if the local educators don't understand the genomic science or can't communicate it effectively to their neighbors.
11:38The whole system breaks down before a patient ever meets a doctor. Exactly. To solve this, Kopeck developed an optimized highly specific training programs and toolkits for these educators. Okay. And these weren't just basic pamphlets.
11:51The toolkits included interactive modules, culturally tailored FAQ sheets, and even role-playing guides to help educators practice answering difficult questions about genomic data privacy and research intent.
12:04So they basically armed the local messengers with the best possible communication science. It did. And they used focus groups to evaluate the training itself, continually refining the toolkits. They treated the communication pipeline as a scientific variable that needs to be constantly tested and optimized.
12:21That's so smart Yeah, and moving forward. They plan to evaluate these educator toolkits using a randomized controlled trial to see which training methods actually yield the highest community engagement.
12:32Which brings us to the final critical moment of the research process. The moment the patient actually gets their results. The Fifth Center, WPECGS, works with black and African-American adults facing multiple myeloma and colorectal cancer.
12:47Right, and receiving complex genetic information can be incredibly confusing and anxiety inducing for anyone. For sure. It's not just finding out about mutation. It's learning information that could impact your family members or your insurance.
13:00WUPECGS, decided to rigorously test how to deliver this information better. They evaluated novel decision support tools. But what does a decision support tool actually look like in practice? Well, instead of just handing over a dense lab report, these tools act as interactive guides.
13:17They break down complex risk probabilities into clear visual graphics and allow patients to explore different medical scenarios at their own pace. Oh, that makes sense. That mechanically reduces the cognitive overload that causes what researchers call decisional regret.
13:32Yes. And decisional regret is that psychological burden a patient feels when they agree to a genetic test or receive the results, without truly understanding the life-altering implications of what they're looking at.
13:46Exactly. The WUPECGS center used randomized controlled trials to evaluate these tools. They wanted definitive proof of which communication methods actually reduced decisional regret and improved a patient's understanding of their own health.
13:59So no guessing. Right. They didn't rely on assumptions. They generated hard evidence on how to best support black and African-American patients through a highly complex medical moment. Stepping back to look at the whole PECTS network for a second.
14:12We are really witnessing a fundamental paradigm shift in clinical research. For decades, the biomedical model basically treated people as mere subjects. You extract their blood, you extract their data, and you send them on their way.
14:26What this paper demonstrates is a massive move toward treating patients as active essential partners. They aren't just the source of the data anymore. They are co-creators of the research process. The researchers are proving that when you integrate community voices through tribal advisory committees, multidisciplinary boards, or bilingual town halls, the quality of the research itself improves.
14:48Okay, but I have to play devil's advocate for a 2nd here. Does taking the time to make all these culturally specific tweaks, like creating new indigenous art for consent forms or hosting disability webinars.
15:02Does that slow down the actual hard science of finding cancer cures? Like, shouldn't scientists just be focusing all their time and budget on sequencing the DNA? You know, it's a really common assumption, but the evidence from this network shows that engagement optimization actually accelerates the science.
15:18Really? Accelerates it? Yes, without it, your science hits a wall. If you ignite cultural context, your cruel rates drop significantly because people simply won't sign up. Oh, right. And your dropout rates spike because participants feel unsupported.
15:32And most importantly, if only a specific homogeneous group of people stay in your study, your genomic data remains skewed, you end up spending 1000000000s of dollars on a high-tech cure that only works for a fraction of the population.
15:45Exactly. Bad engagement literally creates bad data. Optimization makes the data robust. It ensures that the genetic databases we build accurately reflect the true diversity of human biology. So the soft science of human engagement is exactly what makes the hard science of genomics viable.
16:04That's perfectly said, yes. Looking forward, what is the paper recommend for future studies based on these 1st 3 years of the network? They lay out a few critical recommendations. First, you have to build a robust infrastructure for engagement before you even start the science.
16:18Right. wait. Exactly. You cannot tack it on at the end as an afterthought. That means establishing bodies like a tribal advisory committee from day one and giving them actual influence over the study design.
16:30Give the community a real seat at the table. Yes. Second, you have to plan to measure engagement from the very beginning. You need to know what metrics you are tracking, like trust, decisional regret, or comprehension, and you have to track them consistently.
16:44Which naturally leads to their 3rd recommendation, right? Harmonization. Exactly. Moving forward, the field needs to actively engage community members in selecting harmonized constructs and measures. Because if every research center measures a concept like trust using a completely different survey, we can't really compare notes.
17:05Right. We need standardized, community approved ways to measure if our engagement is actually working across the board. Were there any major limitations to what they found? Obviously, this evaluation covers just the 1st 3 years of the network's formation.
17:17Yeah, the main limitation really is just time. We're seeing fantastic preliminary impacts on recruitment, retention, and the overall quality of the study designs. But the true long-term impact, whether these engagement optimizations actually lead to increased participant diversity in the final genomic databases, and ultimately, if they improve long-term cancer survival rates, well, that requires further evaluation as these massive studies conclude.
17:42So what does this all mean? If you had to distill this entire deep dive down for our listener? What is the core takeaway? The central insight is that engagement in genomics can no longer be an afterthought or a guessing game.
17:54It must be a scientifically rigorous, continuously optimized process that deeply respects and reflects the community its studies. It makes you wonder. If optimizing human engagement accelerates cancer research this much, What happens when we start applying these exact same metrics to AI development or public infrastructure?
18:12If the hard science only works when the soft science is optimized, we might need to rethink how we build almost everything. Definitely. What does this mean for the future of precision medicine when every community finally has a trusted seat at the table?
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