An atlas to improve prostate cancer therapies

The project led by Jean-Philippe Theurillat of the Università della Svizzera italiana is the first NRP 79 project to have concluded its research phase. It delivers a systematic way to measure how closely different lab models match real patient tumours. "Researchers currently face a difficult situation," explains Theurillat, "because lack of data makes the choice of cell model more a matter of faith than an informed decision." His team set out to change that.

Decades of model development, but little comparison

Over the past decades, many different methods for growing human cells in the lab have been developed, with the hope of reducing or replacing animal experiments. In recent years, organoid cultures – small, three-dimensional cell structures – have been widely promoted as the most advanced method. However, none of these approaches had ever been systematically compared to real human tumours. As a result, researchers have largely chosen their lab models based on habit or assumption rather than solid evidence.

Gene expression as a benchmark

The research team addressed this blind spot. Using gene expression profiling – a method that reads which genes are active in a cell – they compared prostate cancer cells grown under different lab conditions with tumour samples from real patients. They then used artificial intelligence to identify which lab conditions best match what happens in human tumours. Throughout the process, the team prioritised cost-effective and manageable protocols suitable for everyday laboratory use.

A freely accessible tool for all researchers

The centrepiece of the project is the Prostate Cancer Atlas: a cloud-based tool that allows researchers to upload their own data and see how closely their lab model resembles human tumour tissue – and which disease stage it most closely matches. To date, the atlas has attracted over 400 regular users from academia and industry. It currently integrates 1,365 samples, with an update to nearly 3000 samples planned for autumn 2025.

The Prostate Cancer Atlas gives researchers in academia and industry a concrete, evidence-based way to evaluate the strengths and limitations of their lab models. It also allows them to spot patterns in their experimental data that reflect real processes in disease progression or resistance to hormone therapy. From a 3R perspective, this is significant: Rather than choosing a model based on convention, researchers can now make more informed decisions – and better understand how their lab results relate to what happens in real patients.

The approach is not limited to prostate cancer – it is broadly applicable and can be transferred to other disease models (e.g. breast cancer or lung cancer). The team around Theurillat is also part of Can-Map, an EU infrastructure grant application with partners from six European countries, aiming to scale the atlas concept to breast, prostate, colorectal, and lung cancer.