Colorectal cancer is often diagnosed at an advanced stage when treatment options are limited. This underscores the need for simpler, less invasive diagnostic tools, particularly in the face of a still unexplained rise in cases among young adults. While it has long been known that gut microbiota plays a role in the development of colorectal cancer, translating these findings into clinical practice has proven challenging. This is because different strains of the same bacterial species can have opposite effects, with some promoting the disease and others having no effect.

"Instead of relying on the analysis of the various species composing the microbiota, which does not capture all meaningful differences, or of bacterial strains, which vary greatly from one individual to another, we focused on an intermediate level of the microbiota, the subspecies," explains Mirko Trajkovski, full professor in the Department of Cell Physiology and Metabolism and in the Diabetes Centre at the UNIGE Faculty of Medicine, who led this research. "The subspecies resolution is specific and can capture the differences in how bacteria function and contribute to diseases including cancer, while remaining general enough to detect these changes among different groups of individuals, populations, or countries."

With the help of machine learning

The first step was to analyse huge amounts of data. "As a bioinformatician, the challenge was to come up with an innovative approach for mass data analysis," recalls Matija Trickovic, PhD student in the laboratory of Mirko Trajkovski and first author of this study. "We successfully developed the first comprehensive catalogue of human gut microbiota subspecies, together with a precise and efficient method to use it both for research and in the clinic."

By combining this catalogue with existing clinical data, the scientists developed a model that can predict the presence of colorectal cancer solely based on the bacteria present in stool samples. "Although we were confident in our strategy, the results were striking," enthuses Matija Trickovic. "Our method detected 90% of cancer cases, a result very close to the 94% detection rate achieved by colonoscopies and better than all current non-invasive detection methods."

By integrating more clinical data, this model could become even more precise and match the accuracy of colonoscopy. It could become a routine screening tool and facilitate the early detection of colorectal cancer, which would then be confirmed by colonoscopy but only in a selected group of patients.

A new world of applications

A first clinical trial is being set up in collaboration with the Geneva University Hospitals (HUG) to determine more precisely the cancer stages and the lesions that can be detected. However, the applications go beyond colorectal cancer. By studying the differences between subspecies from the same bacterial species, researchers can now identify the mechanisms of action by which the gut microbiota influences human health. "The same method could soon be used to develop non-invasive diagnostic tools for a wide range of diseases, all based on a single microbiota analysis," concludes Mirko Trajkovski.

The findings, published on September 8 in Cancer Discovery, are the first to suggest that ecDNA rings containing cancer-driving genes often appear in the earliest stages of glioblastoma's development -- and in some cases, even before the tumour has fully formed. This early arrival may set the stage for the cancer's rapid growth, adaptability and resistance to treatment.

The study was led by Dr Benjamin Werner at Queen Mary University of London and Professor Paul Mischel at Stanford University, both part of Cancer Grand Challenges' team eDyNAmiC, as well as Professor Charlie Swanton at The Francis Crick Institute.

Tackling cancer's toughest challenges

Glioblastoma is one of the most challenging cancers to treat, with median survival remaining at around 14 months and little improvement in recent decades. New approaches for earlier detection and more effective treatment are urgently needed.

ecDNA is emerging as a potentially important player in many adult and paediatric cancers, including glioblastoma, but its role is complex and mysterious. The Cancer Grand Challenges initiative -- founded by Cancer Research UK and the National Cancer Institute in the US -- identified understanding ecDNA as one of the toughest challenges facing the field today. In 2022, they funded team eDyNAmiC -- a $25m international, cross-disciplinary consortium of experts in cancer, clinical research, evolutionary biology, computer science and mathematics -- to decipher ecDNA's role and identify ways to target it. The current study marks an important advance in team eDyNAmiC's work.

Excavating a tumor's past

In their new study, team eDyNAmiC and their collaborators integrated genomic and imaging data from patients with glioblastoma with advanced computational modelling of the evolution of ecDNAs in space and time.

"We studied the tumours much like an archaeologist would. Rather than taking a single sample, we excavated multiple sites around the tumour, allowing us to build computational models describing how they evolved. We simulated millions of different scenarios to reconstruct how the earliest ecDNAs emerged, spread, and drove tumour aggressiveness, giving us a clearer picture of the tumour's origins and progression," explains senior author Dr Benjamin Werner, a group leader at the Barts Cancer Institute, Queen Mary University of London.

The analysis revealed that most ecDNA rings contained EGFR, a potent cancer-driving gene. EGFR ecDNA appeared early in the cancer's evolution -- even before tumour formation in some patients. It also frequently gained extra changes, such as the EGFRvIII variant, that made the cancer more aggressive and resistant to therapies.

A window of opportunity

"These subtle mechanisms show that there may be a window of opportunity to detect and treat the disease between the first appearance of EGFR ecDNA and the emergence of these more aggressive variants," suggests Dr Magnus Haughey, a postdoctoral researcher in Dr Werner's group and one of the paper's lead authors. "If scientists can develop a reliable test to detect early EGFR ecDNA -- for example through a blood test -- it could enable them to intervene before the disease becomes harder to treat."

The study confirmed that ecDNA can carry more than one cancer gene at a time, each of which may uniquely shape how tumours evolve and respond to treatment. This highlights the potential value of tailoring treatments based on a tumour's ecDNA profile.

Yet many mysteries remain. The researchers now plan to study how different treatments affect the number and types of ecDNA in glioblastoma. Team eDyNAmiC will continue to investigate the role of ecDNAs across a range of cancer types to uncover further opportunities to diagnose cancers earlier, track their progress more precisely, and design smarter treatments.

Charlie Swanton, Deputy Clinical Director and head of the Cancer Evolution and Genome Instability Laboratory at The Francis Crick Institute and chief clinician at Cancer Research UK, says:

"These findings suggest that ecDNA is not just a passenger in glioblastoma, but an early and powerful driver of the disease. By tracing when and how ecDNA arises, we open up the possibility of detecting glioblastoma much earlier and intervening before it becomes so aggressive and resistant to therapy. I hope this might help to drive a new era in how we diagnose, track and treat this devastating cancer."

Paul Mischel, MD, the Fortinet Founders Professor and professor and vice chair of research in the pathology department at Stanford Medicine, says:

"These findings reveal an important new insight into the role of ecDNA in tumour development and progression. Previous work from our collaborative team and other researchers, has shown that ecDNA can arise early in tumor development, including at the stage of high-grade dysplasia, and it can also arise later to drive tumor progression and treatment resistance. The findings here show that in glioblastoma, there is an early event driven by ecDNA that could potentially be more actionable, raising the possibility that glioblastoma is another cancer for which earlier detection and intervention based upon ecDNA may be possible."

Director of Cancer Grand Challenges, Dr David Scott, says:

"This study exemplifies the bold, boundary-pushing science Cancer Grand Challenges was created to support. By unravelling the evolutionary history of ecDNA in glioblastoma, team eDyNAmiC is not only deepening our understanding of one of the most devastating cancers but also illuminating new paths for earlier detection and treatment. It's a powerful reminder that when we bring together diverse disciplines and global talent, we can begin to solve the toughest problems facing cancer research."