Unlocking Longevity: Lessons from Oncology
By Dr. Marwan Ghosn, Founder of In Good Health Clinic
At the forefront of healthcare innovation, oncology has transformed how we approach disease risk and prevention. With tools like genetic analysis, polygenic risk scores (PRS), and artificial intelligence (AI), cancer care has shifted from a reactive approach to one that emphasizes precision and prevention. However, these advancements don’t just revolutionize cancer care—they are now being applied to chronic metabolic and age-related conditions, such as heart disease and diabetes1.
With these innovative tools, the potential to unlock healthier, longer lives for everyone is becoming within reach. Let’s explore how translating these cutting-edge insights into actionable steps for patients can inspire a new era of preventive care.
How Oncology Became a Pioneer in Prevention
When it comes to understanding disease risk, oncology leads the way. Thanks to next-generation sequencing (NGS), healthcare providers can now analyze a person’s DNA and RNA to predict their chances of developing specific cancers.
This isn’t just theoretical—it’s practical. For instance, testing for BRCA1 and BRCA2 mutations enables women at higher risk of breast or ovarian cancer to take preventive action, ranging from lifestyle changes to preventive surgeries. Moreover, in oncology, NGS is not only used to assess disease risk but also to predict treatment responses based on various genomic profiles, guiding personalized treatment plans.
AI has taken this progress even further. By analyzing vast amounts of data, AI provides highly accurate risk predictions and tailors interventions to each patient2. The result? A more personalized approach to care that spans prevention, diagnosis, and treatment, subsequently improving outcomes and reducing overall disease burden. For example, AI in oncology can assist in early cancer detection by analyzing medical images, like CT scans or MRIs, to identify tumors or abnormalities, enabling earlier and more accurate diagnoses.
These are just a few examples of how oncology is driving the transformation in healthcare through the use of advanced technologies in both preventive and predictive medicine. What’s especially inspiring is how this shift—from reactive treatment to proactive prevention— has also been applied to redefine healthcare practices in other medical fields. Traditional methods often fall short in identifying risks for certain diseases. For example:
7 out of 10 women diagnosed with breast cancer have no family history of the disease.
1 in 4 people with coronary artery disease remain undetected through clinical risk evaluations alone.
These gaps underscore the need for advanced tools like NGS and AI-driven models3. By offering deeper insights into genetic and lifestyle risks, these technologies empower patients to take preventive action long before symptoms appear.
Expanding Oncology’s Tools to Aging and Chronic Conditions
Disease risk isn’t just about genetics—it’s multifactorial. Poor eating habits, hormonal changes, and environmental exposures all work alongside genetic predispositions to shape our health.
Advanced technologies now integrate these elements—genetics, epigenetics, and lifestyle factors—into comprehensive risk assessments, overall providing a more personalized picture of an individual’s health trajectory.
This holistic approach is transforming how we understand and manage chronic conditions.
The principles of precision care in oncology are now being applied to other health conditions, especially those linked to aging. Chronic conditions such as heart disease, diabetes, and others, share common biological pathways with cancer, including inflammation and oxidative stress. Leveraging similar tools—like PRS and AI—enables more effective prediction and management of these risks3.
Take heart disease, with NGS, healthcare providers can identify individuals predisposed to cardiovascular issues5. Instead of waiting for symptoms, targeted prevention strategies—such as dietary changes, exercise programs, or medication—can be implemented5. For example, familial hypercholesterolemia (FH) is a genetic condition caused by changes in the APOB, LDLR, and PCSK9 genes, which lead to very high cholesterol levels early in life. Without treatment, people with FH have a much higher chance of developing atherosclerotic cardiovascular disease (ASCVD), sometimes as early as in their 40s. However, with early and effective cholesterol-lowering medications, this risk can be greatly reduced. This shows how genetic testing can pinpoint those at risk, allowing for early action to prevent serious health issues later on.6
AI is also making strides in managing conditions like diabetes, which affects millions globally. By combining genetic data with patient medical histories, AI can identify risks early and recommend tailored interventions that range from dietary to lifestyle.
Why Early Prevention Matters More as We Age
Aging isn’t just about adding years to life—it also amplifies genetic risks for chronic conditions. One major culprit is “inflammaging,” a low-grade chronic inflammation that has been linked to diseases such as cancer and heart disease. This is where oncology’s focus on early intervention proves invaluable.
By identifying risks tied to inflammation, patients can adopt lifestyle changes that tackle multiple issues simultaneously.
For example, an anti-inflammatory diet or a tailored exercise routine can reduce cancer risks while improving heart and metabolic health. By helping patients embrace these holistic approaches, healthcare professionals can ensure individuals age with vitality.
Building a Roadmap for Longevity
The ultimate goal of these advancements is clear: helping people live longer, healthier lives. By combining the power of genetic insights, PRS, and AI, healthcare providers can design personalized health plans that address multiple risks simultaneously. For aging populations, this shift means focusing on prevention rather than waiting for problems to arise. Advanced health programs informed by these cutting-edge tools can help individuals adopt healthier habits and better manage their unique risks. This is the future of healthcare—tailoring health solutions to the unique needs of each individual.
Personalized health solutions are particularly crucial for patients with hidden or multifactorial risks.
Advanced tools such as PRS and AI create actionable roadmaps for prevention by addressing risks that often remain invisible in clinical evaluations. Whether it’s identifying prediabetes, mitigating inflammation, or catching early signs of coronary artery disease, these technologies empower patients to make informed choices.
- Cardiovascular disease: Advanced genetic tests enable the reclassification of patients at intermediate risk by traditional methods. Depending on their genetic profile, these patients may be identified as having a high risk of coronary artery disease, allowing for earlier and more effective interventions.
- Type 2 diabetes: By identifying high-risk patients through genetic and metabolic markers, tailored nutritional or pharmacological approaches can prevent the development of type 2 diabetes, improving outcomes and reducing long-term complications.
- Breast cancer: Specialized genetic tests can detect the polygenic risk of breast cancer in women without hereditary mutations, offering new insights for those at risk of sporadic cases and enabling earlier preventive measures.
- Prostate cancer: Genetic testing provides critical tools for identifying individuals at high risk of prostate cancer, surpassing the limitations of traditional screening methods and supporting earlier detection and intervention.
Closing Thoughts
Multifactorial risk assessments that combine genetics, lifestyle, and environmental data represent the next frontier of precision medicine. Some health indicators are undetectable through symptoms or traditional tests. Tools like PRS and AI are helping bridge these gaps1, creating a healthcare system that prioritizes prevention and longevity6.
The fusion of oncology and preventive medicine is reshaping healthcare. What began as a mission to better understand and treat cancer has evolved into a powerful blueprint for addressing aging and chronic diseases4.
By integrating the latest advances in genetic research and AI, healthcare professionals can empower patients to take charge of their health and embrace the opportunities for healthier, longer lives.
References:
1. Jin, J., & Kim, J. (2024). Multi-omics and Artificial Intelligence Technology for Elucidating Disease Pathophysiology. Preprints.org.
2. Henry, E. (2024). Utilizing Electronic Health Records for Predictive Modeling of Cancer Risk. ResearchGate.
3. Yurkovich, J. T., Evans, S. J., & Rappaport, N. (2024). The Transition from Genomics to Phenomics in Personalized Population Health. Nature Reviews Genetics.
4. Patrinos, G. P., & Meybodi, H. A. (2024). Introduction to the Future of Medicine. Springer.
5. Verma, M., & Senapati, S. (2024). Integrating Polygenic Risk Scores (PRS) for Personalized Diabetes Care: Advancing Clinical Practice with Tailored Pharmacological Approaches. Diabetes Therapy.
6. Hood, L., & Price, N. (2023). The Age of Scientific Wellness: Why the Future of Medicine Is Personalized, Predictive, Data-Rich, and in Your Hands. Books.Google.
7. Grzymski, J.J., Elhanan, G., Morales Rosado, J.A. et al. Population genetic screening efficiently identifies carriers of autosomal dominant diseases. Nat Med 26, 1235–1239 (2020). https://doi.org/10.1038/s41591-020-0982-5
