Walk through the labs at Moffitt Cancer Center in Tampa, Florida, during summer, and you'll witness an unusual sight: high school students clustered around computers, developing mathematical models that might reveal cancer's secrets. These aren't typical science fair projects—these teens are part of an innovative program that's training the next generation of scientists to fight cancer not just with medicines, but with mathematics.
The High School Internship Program in Integrated Mathematical Oncology (HIP IMO) represents a radical approach to cancer research education. By shattering traditional boundaries between biology and mathematics, this initiative gives students as young as 16 the opportunity to contribute directly to cutting-edge cancer research alongside leading scientists 4 .
What Is Mathematical Oncology?
When Numbers Meet Neoplasms
Traditional cancer research largely happens through biological experiments—testing drugs on cancer cells, analyzing genetic mutations, or conducting clinical trials. Mathematical oncology takes a different approach, using computational models and quantitative frameworks to understand and predict cancer behavior 5 .
Cracking Cancer's Evolutionary Code
Cancer isn't static—it evolves, adapting to treatments and developing resistance. Mathematical oncology can exploit these very evolutionary dynamics. For instance, Evolutionary Therapy approaches developed at Moffitt deliberately manipulate the competition between drug-sensitive and drug-resistant cancer cells 5 .
"Modern cancer research, and the wealth of data across multiple spatial and temporal scales, has created the need for researchers that are well versed in the life sciences and natural sciences," noted the founders of HIP IMO in their five-year review of the program 2 . This fusion of disciplines creates powerful new ways to combat cancer.
The Making of Teenage Scientists
A Summer of Immersion
Each summer, selected high school students embark on an eight-week intensive research experience at Moffitt's Integrated Mathematical Oncology department. The program runs parallel to the Hillsborough County school summer break, with students committing to full-weekday attendance from 10 a.m. to 4 p.m. 4 .
Under the guidance of dedicated mentors, these young researchers don't just observe—they lead their own research projects tailored to their interests and abilities. The experience includes participating in lab meetings, documenting findings in professional formats, and presenting results to the scientific community 4 .
HIP IMO Program at a Glance
| Duration | 8 weeks (June - August) |
| Daily Schedule | 10 a.m. - 4 p.m., weekdays |
| Key Deliverables | Research project, scientific presentation, 3-page paper |
| Scholarship | $1,000 award for participants |
| Eligibility | High school students aged 16+ (current year graduates ineligible) |
Real Science, Real Impact
Despite their youth, HIP IMO participants have contributed to legitimate scientific publications. Interns have co-authored papers in prestigious journals on topics ranging from intracellular temperature gradients to sociodemographic factors affecting immune responses in cancer 4 .
Publication 1
Explored how cytoplasmic convection currents create temperature variations inside cells—work that could reveal new aspects of cellular function in health and disease 4 .
Publication 2
Developed computational pipelines for analyzing digital images of cancer tissues, improving how researchers extract meaningful data from biological samples 4 .
Mathematics vs. Brain Cancer: A Case Study
The Glioblastoma Challenge
To understand how mathematical oncology works in practice, consider a recent Moffitt study on glioblastoma, the most aggressive type of brain tumor . Even with intensive treatment, this cancer almost always returns, making it a prime target for mathematical approaches.
An interdisciplinary team led by Moffitt's Dr. Noemi Andor and SDSU's Professor Parag Katira investigated why glioblastomas recur so predictably after surgery. Their groundbreaking research focused on ploidy—the number of chromosomes in cells—and how this characteristic affects tumor growth in different brain environments .
Building a Digital Twin of a Tumor
The researchers developed an innovative mathematical framework called the "Stochastic State-Space Model of the Brain" that combines patient scan data, medical images, and laboratory findings . This virtual model simulates how glioblastoma cells grow, move, and respond to treatments in the context of a specific patient's brain.
The model revealed a crucial discovery: cancer cells with different ploidy levels respond differently to oxygen and nutrient availability in various brain regions. This environmental pressure influences how quickly tumors regenerate after treatment .
| Research Finding | Scientific Significance |
|---|---|
| Ploidy-environment interaction | Tumors with different chromosome counts grow at different rates depending on their location in the brain |
| Metabolic flexibility | Some glioblastoma cells accelerate their switch to sugar-based metabolism more quickly than others |
| Oxygen dependence | The transition to sugar-based energy is influenced by oxygen availability |
| Tissue resource influence | Energy supply and cancer genome evolution appear tightly connected across different cancer types |
Implications for Future Treatments
This mathematical approach could help doctors predict tumor regrowth patterns and design more personalized treatment strategies . By understanding how cancer cells adapt to their environment and energy constraints, researchers might develop new approaches to slow tumor evolution and improve patient outcomes.
The Mathematical Oncologist's Toolkit
What does it take to become a mathematical oncologist? The field requires a diverse set of computational tools and approaches, many of which HIP IMO interns learn to apply to their research projects 5 .
| Research Tool | Primary Function | Research Applications |
|---|---|---|
| Ordinary Differential Equations (ODEs) | Model population dynamics over time | Tracking cancer cell growth and treatment response |
| Partial Differential Equations (PDEs) | Describe spatial-temporal processes | Modeling tumor invasion and metastasis patterns |
| Hybrid Cellular Automata | Simulate individual cell behaviors | Studying cellular interactions within tumor ecosystems |
| Game Theory | Analyze competitive and cooperative behaviors | Understanding treatment resistance evolution |
| Stochastic Models | Incorporate randomness and uncertainty | Predicting cancer evolution and heterogeneity |
| Machine Learning | Identify patterns in complex datasets | Discovering biomarkers from genomic or imaging data |
| Bayesian Models | Update predictions with new evidence | Personalizing treatment based on individual patient responses |
Tool Application Examples
ODEs in Treatment Modeling
Used to simulate how cancer cell populations change over time in response to chemotherapy drugs.
Game Theory in Resistance
Helps predict how cancer cells might evolve resistance strategies against targeted therapies.
ML in Diagnosis
Trains algorithms to recognize patterns in medical images for earlier and more accurate cancer detection.
Training Tomorrow's Interdisciplinary Scientists
From Classroom to Cancer Research
The HIP IMO program represents a visionary approach to science education. By exposing students to interdisciplinary research early, the program helps bridge the steep learning curve that typically separates disciplinary undergraduate education from interdisciplinary graduate research 2 .
Between 2015 and 2019, the program trained 59 students, many of whom have gone on to prestigious institutions including Columbia, Princeton, University of Chicago, and Duke 2 4 . This pipeline of young talent brings fresh perspectives to cancer research while preparing students for careers at the interface of quantitative and biological sciences.
A Model for the Future of Science Education
The program's success demonstrates the power of early interdisciplinary immersion. Traditional education occurs in "disciplinary silos," creating barriers to collaboration later in scientific careers. HIP IMO breaks down these barriers from the start, showing students how mathematical thinking can solve biological puzzles 2 .
The Future Is Quantitative
The intersection of mathematics and oncology represents a frontier in our fight against cancer. Programs like HIP IMO not only advance cancer research but cultivate the interdisciplinary thinkers needed to tackle complex diseases in the 21st century.
What begins as a summer internship for a high school student might evolve into a career dedicated to decoding cancer's mathematical secrets—eventually leading to more personalized, predictive, and effective cancer treatments for patients everywhere.
As these young mathematical oncologists prove, sometimes the most powerful weapons against cancer aren't found in medicine cabinets, but in the elegant language of mathematics and the boundless curiosity of bright young minds.