The health system will finally have a rational way to deploy its tools where they matter most.
Em Ribeirão Preto, pesquisadores da USP iniciaram um estudo que convida quinze mil pessoas a revelar, por meio de seu próprio DNA, o quanto a herança biológica as aproxima ou as afasta do câncer. A iniciativa, integrada ao Programa Nacional de Oncologia, não busca prever destinos individuais, mas construir uma linguagem genética capaz de orientar o sistema de saúde a agir com mais precisão e menos desperdício. É uma aposta antiga da medicina — conhecer para prevenir — agora traduzida em escala e algoritmos.
- O câncer continua sendo tratado como um problema coletivo uniforme, quando o risco, na prática, é profundamente desigual entre os indivíduos.
- Quinze mil moradores da região de Ribeirão Preto foram recrutados para fornecer material genético que será convertido em escores de predisposição hereditária.
- O escore poligênico não condena nem absolve — ele calibra probabilidades, permitindo que rastreamentos e intervenções sejam direcionados a quem mais precisa.
- O sistema público de saúde poderá, em até três anos, usar esses dados para redistribuir recursos preventivos com base em risco real, não em médias populacionais.
- A infraestrutura genética construída para o câncer abre caminho para prever riscos de outras doenças, multiplicando o valor dos dados coletados agora.
Em um centro de pesquisa da USP em Ribeirão Preto, cientistas começaram a analisar o material genético de quinze mil moradores da região com um objetivo preciso: calcular a predisposição hereditária de cada pessoa ao câncer. O instrumento central é o escore poligênico — uma soma matemática dos fatores genéticos que aumentam ou reduzem a probabilidade de desenvolver a doença.
O oncologista Leandro Colli, um dos coordenadores do estudo, descreve a iniciativa como uma questão de eficiência. O sistema de saúde, historicamente limitado em recursos, tende a distribuir prevenção de forma indiscriminada. Com os escores em mãos, seria possível concentrar rastreamentos, monitoramentos e aconselhamentos nas pessoas com maior risco real — e poupar esforços onde o risco é baixo.
Importante notar: o escore poligênico não é uma sentença. Ele não diz se alguém vai desenvolver câncer, mas indica se a biologia herdada torna isso mais ou menos provável do que a média. Essa distinção abre espaço para uma prevenção personalizada que, sem o dado genético, permaneceria fechada.
O estudo integra o Programa Nacional de Oncologia do Brasil e segue uma tendência já consolidada em outros países há mais de uma década. O que o diferencia é a escala — quinze mil participantes é uma amostra expressiva para o contexto brasileiro — e a promessa de resultados em até três anos.
Além do câncer, os pesquisadores vislumbram um horizonte mais amplo: a mesma infraestrutura genética poderá ser usada para prever riscos de outras doenças, transformando o banco de dados atual em uma plataforma de saúde preventiva de longo alcance. Para os quinze mil que cederam suas amostras, o estudo é uma espécie de contrato — sua informação genética, em troca da esperança de um sistema de saúde que um dia saberá, com mais precisão, como protegê-los.
At a university research center in Ribeirão Preto, scientists have begun the work of sorting people by their genetic likelihood of developing cancer. Fifteen thousand residents from the region have been recruited to give samples of their genetic material, which researchers will analyze to build what they call a polygenic score—essentially a mathematical sum of all the inherited factors that either push someone toward cancer or shield them from it.
The logic is straightforward, if ambitious. Once researchers understand who carries the highest genetic risk, public health officials can stop treating cancer prevention as a one-size-fits-all problem. Instead of spreading resources thin across an entire population, they can concentrate screening, monitoring, and preventive interventions on the people most likely to need them. Leandro Colli, an oncologist and one of the study's coordinators, frames it as a matter of efficiency: the health system will finally have a rational way to deploy its tools where they matter most.
The polygenic score itself is not a prediction of destiny. It does not tell you whether you will get cancer. It tells you whether your inherited biology makes cancer more or less probable than average. That distinction matters because it opens a door to prevention that would otherwise stay closed. Someone with a high score might benefit from earlier screening, lifestyle counseling, or closer monitoring. Someone with a low score might reasonably defer certain interventions. The public health system, Colli suggests, will be able to make smarter choices about where to invest its finite resources.
What makes this study part of something larger is that it is not new in principle. Other countries have been running similar genetic risk assessments for more than a decade. The research is integrated into Brazil's National Program for Oncological Care, a coordinated effort to improve how the country approaches cancer as a public health problem. The novelty here is scale and location: fifteen thousand people is a substantial sample, and the work is happening in Brazil, where such large-scale genetic studies are less common than in wealthier nations.
The researchers expect to have their polygenic scores ready within three years. That timeline matters because it suggests this is not a distant theoretical exercise. Within a few years, the health system could begin using these scores to reshape how it allocates preventive care. Colli also hints at a broader possibility: once the machinery is in place to predict cancer risk from genetics, the same approach could work for other diseases. The infrastructure built for cancer prevention might become a platform for predicting risk across multiple conditions, multiplying the value of the genetic data being collected now.
For the fifteen thousand people who have given their samples, the study represents a kind of bargain. They contribute their genetic information in exchange for the possibility that their health system will one day use that information to protect them more effectively. Whether that promise will be kept depends on what the researchers find, how the data is used, and whether the public health system has the will and resources to act on the scores once they exist. For now, the samples are being analyzed, the algorithms are being built, and the waiting begins.
Notable Quotes
The health system will be able to direct preventive care more efficiently to those with the highest likelihood of developing disease— Leandro Colli, oncologist and study coordinator
The same genetic scoring approach could eventually be used to predict risk for other diseases beyond cancer— Leandro Colli
The Hearth Conversation Another angle on the story
Why does a health system need to know who's at genetic risk for cancer before it can prevent it?
Because prevention is expensive, and resources are always limited. If you screen everyone equally, you waste money on people who will never get sick and miss opportunities to help people who will. A genetic score lets you focus on the people who actually need it.
But doesn't knowing your genetic risk create anxiety? What if someone learns they're high-risk and it changes how they see themselves?
That's a real concern, and it's why this matters—the score isn't destiny. It's probability. Someone with high genetic risk can still avoid cancer through lifestyle, and someone with low risk can still develop it. The score is just information that helps doctors and patients make smarter choices together.
Three years is a long time to wait for results. What happens to the fifteen thousand people in the meantime?
They go about their lives. The study is observational—researchers are analyzing their genetic material and building the scoring system. The real test comes after, when the health system has to decide whether to actually use these scores to change how it delivers care.
And if it works in Brazil, what then?
Then you have a model that other countries could adapt. And as Colli mentioned, the same genetic framework could predict risk for heart disease, diabetes, other conditions. You build the infrastructure once and use it many times over.