Precision Oncology and Bioinformatics

Making precision medicine a practical reality for patients

Researchers at Queen’s are pioneering new precision health informatics techniques to facilitate the advancement of personalised medicine and new cancer treatments.

The university’s research teams are developing novel integrated statistical and computational tools to analyse clinical and biological data to improve diagnosis, treatment selection, and overall patient outcomes.

Research Challenge

Cancer is one of the world’s most complex health challenges, with each patient’s genetic and molecular makeup influencing how their disease behaves and responds to treatment. Traditional cancer therapies often adopt a generalized approach, applying similar treatments to diverse patient populations. However, this “one-size-fits-all” model can lead to suboptimal results and unnecessary side effects. Researchers at Queen’s University are responding to the urgent need for precision medicine approaches that consider individual genetic variations to ensure more effective, targeted treatments.

In particular, bioinformatics — the use of statistical and computational tools to analyse biological data — is critical to realising the potential of precision medicine. Processing vast amounts of data from patients, clinical trials, and genomic studies is essential to identifying biomarkers (biological molecules found in blood or tissue) that can predict disease progression or treatment success.

Queen’s research teams are developing advanced statistical and computational algorithms and models that can harness these data complexities, improving our understanding of disease biology and enabling personalized cancer treatment. Before a new drug or treatment can be offered to cancer patients, it must be tested in the laboratory. Researchers can work with different types of laboratory models (pre-clinical models) that can act as a substitute for a tumour growing in the human body. Each type of model has its own advantages and limitations, and it can be difficult to decide which is the best model for each experiment or cancer type being studied.

Our Approach

Biomarker Discovery and Experimental Design for Personalised Treatment

Queen's has a world-leading biomarker discovery programme. Working closely with industry (Almac Diagnostics), the university's researchers have identified patterns in gene expression levels that assemble patients together into distinct groups, known as molecular subtypes. These subtypes and corresponding gene expression signatures, in breast, ovarian, prostate and colorectal cancers, can predict a patient’s likelihood of responding to specific treatments or their long-term outcome. This work is crucial for developing “precision” approaches, as the biomarkers (genes) discovered can help clinicians choose the best treatment plans while reducing unnecessary side effects.

The selection of the most appropriate pre-clinical model to study these subtypes and identify new treatments can be a complex issue. By measuring the activity of different genes in cancer models in the laboratory, Queen’s researchers can better understand how well a new drug works in a particular group of patients. Planning experiments in order to determine the effectiveness of new drugs or drug combinations, while minimising the use of essential resources, is crucial. In addition to biomarker discovery, Dr Blayney leads research into experimental design, helping researchers to choose the most appropriate model or set of experiments in order to accelerate biomarker discovery. By developing statistical and computational tools harnessing the vast array of patient data available, Dr Blayney has changed practice, both in industry and academic research settings, with the validation of a commonly-used ovarian cancer cell line as being gastro-intestinal in origin.

Dr Blayney has also introduced a computational tool which enables researchers to test multiple combinations of drugs at the same time, expediting the potential of translation into clinical trials.

Her focus on new statistical and computational methods for experimental design and biomarker discovery exemplifies Queen’s commitment to turning vast, complex datasets into actionable insights that directly impact patient care.

Dr. Blayney’s expertise in statistical and computational modelling, together with her collaboration with industrial partners, has played a critical role in advancing the discovery of new biomarkers and the new treatments.

These tools reduce the guesswork that often complicates cancer care, providing a clearer roadmap for patient-specific therapies that improve survival rates and quality of life.

“Our research at Queen’s University is not just about advancing computational models; it’s about giving clinicians the tools they need to deliver truly personalized care for cancer patients, with far-reaching benefits for healthcare systems and society as a whole.”

- Dr Jaine Blayney

What impact did it make?

Impact on Healthcare and Beyond

The work conducted at Queen’s is not only advancing the field of oncology but also transforming healthcare systems by making precision medicine more accessible and effective.

By developing tools that reduce the financial and emotional burdens of ineffective treatments, Queen’s research teams are helping to streamline healthcare delivery, making high-quality, personalised cancer care a reality. As these tools gain traction, Queen’s University is supporting a global shift toward precision oncology, promising broad-reaching benefits for cancer patients worldwide.