Algorithm Exposes Cells Driving Aggressive Tumor Growth

The first computer algorithm capable of identifying which tumour cells are driving aggressive cancer growth has been developed by Cancer Research UK-funded scientists from UCL and The Francis Crick Institute.

The innovative algorithm, called SPRINTER*, analyses individual cells within a tumour to identify those that are growing the most rapidly.

The technology could eventually help clinicians to detect fast-growing cancer cells in early-stage tumours and predict how a patient’s cancer might progress.

The researchers detailed their work in a new study published in Nature Genetics.

Dr Simone Zaccaria, senior author of the study from UCL Cancer Institute, said: “The importance of having access to sophisticated computational algorithms in this work cannot be overstated. It helped us to process large amounts of complex data quickly and accurately, uncovering patterns in cell growth which would be impossible to spot manually.

“Future progress in cancer research hinges on the use of cutting-edge technologies to pave the way for more precise interventions and better patient outcomes.”

Developing new targeted cancer treatments is challenging because tumours consist of diverse and complex populations of cancer cells. This means that different cells within the same tumour can respond differently to treatments, evolve resistance, or adapt in unexpected ways.

Dr Zaccaria and his team wanted to find a way to differentiate between these cell populations by identifying which were the fastest growing and therefore the most likely to impact a patient’s prognosis.

The team used SPRINTER to analyse nearly 15,000 cancer cells from a patient with non-small cell lung cancer, the most common type of lung cancer.

This allowed the team to compare cells from both the patient’s primary tumour and tumours that had spread to other parts of the body as the cancer developed.

SPRINTER revealed that the cells that were growing the fastest were responsible for spreading the cancer to other parts of the body, and that these cells were also responsible for seeding additional secondary tumours (rather than all secondary tumours originating from the primary tumour).

It also showed that these cells shed more of their DNA into the bloodstream, also known as circulating tumour DNA (ctDNA). This presents an opportunity to develop blood tests which could identify the aggressive cells which drive a patient’s tumour with a simple and minimally invasive procedure.

Executive Director of Research and Innovation at Cancer Research UK, Dr Iain Foulkes, said: “This research is another crucial step in our efforts to improve the outlook for people affected by lung cancer, while also providing valuable insights into the fundamental biology of all cancers. From uncovering the causes of lung cancer to pioneering drugs to treat it and campaigning for change, Cancer Research UK is powering progress for people impacted by the disease.”

The researchers hope that these findings will lay the foundations for further clinical studies, bringing the insights gained from SPRINTER into real-world cancer treatment. The possibility of detecting aggressive cancer cell populations early and monitoring them over time offers a new avenue for more proactive and personalised cancer care.

The patient who participated in this study was also enrolled in the Cancer Research UK funded TRACERx and PEACE studies, which work in tandem to track the evolution of lung cancer from when a patient is diagnosed to their death.

Professor Charles Swanton, Cancer Research UK’s chief clinician from UCL Cancer Institute and the Francis Crick Institute, said: “This research demonstrates the profound impact of pioneering studies like TRACERx and PEACE on our understanding of cancer. By leveraging cutting-edge technologies and bringing together some of the brightest minds in cancer research, these studies are unravelling the complexities of cancer progression and evolution.”

Reference: Lucas O, Ward S, Zaidi R, et al. Characterizing the evolutionary dynamics of cancer proliferation in single-cell clones with SPRINTER. Nat Genet. 2024. doi: 10.1038/s41588-024-01989-z

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