Scientists just cracked the hidden rules of cancer evolution

• Scientists have created a new way to predict how cancer cells evolve as they gain or lose entire chromosomes.
• These large chromosome changes can quickly reshape tumors, helping them grow, adapt to stress, and resist treatment.
• A new tool called ALFA-K reveals which chromosome changes help cancer cells thrive and which ones hold them back.
• The research shows how copying an entire genome can protect cancer cells from the damage caused by extreme chromosomal instability.
• The findings open the door to evolution-aware cancer treatments that anticipate how tumors change rather than reacting after resistance appears.

A New Way to Predict Cancer Evolution

Scientists at Moffitt Cancer Center have created a new method to forecast how cancer cells evolve as they gain or lose entire chromosomes. These large-scale genetic changes can give tumors an advantage, helping them grow faster, adapt to stress, and resist treatment.

The research, published in Nature Communications, introduces a computational tool called ALFA-K. It analyzes longitudinal, single-cell data to trace how cancer cells move through different chromosome combinations over time. By doing this, the method identifies which chromosome patterns are favored as tumors evolve.

The results challenge the idea that cancer evolution is driven by chance alone. Instead, the study shows that tumors follow measurable patterns shaped by chromosome makeup, evolutionary pressures, and treatment-related stress. This framework offers a new way to anticipate how cancers change and how they may respond to therapy.

Q&A with Noemi Andor, Ph.D., corresponding author and associate member in the Integrated Mathematical Oncology Program at Moffitt.

What problem were you trying to solve with this research, and why does it matter for understanding cancer?

Cancer evolves. As tumors grow, their cells constantly make mistakes when copying and dividing their DNA. Many of those mistakes involve gaining or losing whole chromosomes. This creates a mix of cancer cells with different chromosome combinations inside the same tumor.

The problem was that researchers had no reliable way to determine which of those combinations help cancer cells survive. The number of possible chromosome states is enormous, and most existing approaches could only capture snapshots in time or average behavior across many cells.

ALFA-K was developed to solve this problem by using longitudinal, single-cell data to reconstruct how cancer cells move through chromosome states over time and which states are favored by evolution. Without that understanding, cancer progression and treatment resistance can appear unpredictable. Our work shows they follow measurable rules.

Why are chromosome changes so important for tumor growth and treatment response?

Chromosomes contain hundreds or thousands of genes. When a cancer cell gains or loses a chromosome, it changes the dosage of many genes at once. This can immediately alter how the cell grows, divides or responds to stress.

These changes allow cancer cells to make large evolutionary jumps rather than small adjustments. They also create diversity within a tumor, which increases the chances that some cells survive treatment.

Importantly, the effects of these changes depend on a cell's existing chromosome makeup. The same chromosome change can be helpful in one context and harmful in another. This context dependence helps explain why cancer evolution has been so difficult to predict.

How is ALFA-K different from previous tools, and what does it allow researchers to do?

Before ALFA-K, chromosome changes were often assumed to have fixed effects. Researchers sometimes treated gaining or losing a chromosome as always beneficial or always harmful. Real cancer evolution is more complex.

ALFA-K tracks thousands of individual cells over time, accounting for ongoing chromosome instability and reconstructs local fitness landscapes. These landscapes describe how advantageous or harmful a chromosome change is given a cell's current chromosome configuration.

The tool also shows that the rate of chromosome errors matters. When chemotherapy increases chromosome mis-segregation, cancer cells move across these landscapes more quickly. Depending on the landscape's shape, this can push tumors toward chromosome states that are more tolerant of instability.

In this study, ALFA-K estimated the fitness of more than 270,000 distinct chromosome configurations. This made it possible to ask questions that were previously inaccessible.

What does whole-genome doubling mean, and why is it an important finding?

Whole-genome doubling occurs when a cell copies all of its chromosomes. Previous research showed that this can help cancer cells survive, but there was no way to measure how much protection it provides.

ALFA-K allows researchers to quantify that buffering effect. The method measures how much more tolerant genome-doubled cells are to chromosome mistakes compared with non-doubled cells.

This matters because buffering is not all or nothing. There is a threshold at which genome doubling becomes advantageous. By quantifying that threshold, ALFA-K turns genome doubling from a descriptive observation into a predictable evolutionary event.

How could this research eventually help guide cancer treatment?

ALFA-K shifts cancer research from describing what tumors look like to predicting how they will evolve.

In the future, this approach could help doctors interpret repeat biopsies, identify when a tumor is approaching a dangerous evolutionary transition and choose treatments that limit cancer's ability to explore harmful chromosome configurations.

The long-term goal is evolution-aware cancer therapy. This approach aims to anticipate how tumors will change rather than reacting after resistance has already emerged.

This study was supported by the National Cancer Institute (1R37CA266727-01A1, 1R21CA269415-01A1, 1R03CA259873-01A1).