Oncology
Improving outcomes through cancer profiling
In this Q&A, Dr. Kelm explains why functional cancer profiling has the potential to transform patient outcomes on a global scale.
Q. Can you explain what functional cancer profiling is and why it could represent a breakthrough moment for oncology? A. Functional cancer profiling is an approach that directly measures how a patient’s live tumour cells respond to a wide range of drugs and drug combinations in the laboratory. Instead of predicting treatment response based only on genetic or molecular markers, functional profiling evaluates the actual biological behaviour of the cancer — how it lives, grows, and reacts when exposed to therapy. This is a significant shift from conventional genomic or molecular profiling. While genomic testing identifies mutations or biomarkers that might suggest sensitivity or resistance to a therapy, it cannot always predict how complex tumour ecosystems will respond in reality. Tumours are dynamic, heterogeneous systems influenced by both genetic and non-genetic factors, such as the tumour microenvironment and cell–cell interactions. Functional profiling captures all of these influences, producing a more comprehensive and clinically relevant view of drug sensitivity. In practical terms, this means we can test a wide variety of clinically relevant drugs and
combinations ex vivo on a patient’s own cancer cells before deciding on a treatment. The results can reveal unexpected sensitivities — even to drugs not typically considered for that cancer type — and help avoid ineffective or toxic therapies. This represents a potential breakthrough moment for oncology because it brings true functional precision medicine into reach. By complementing genomics with real-time functional data, we can personalise therapy based not just on what the tumour is, but on what it does. This approach could significantly improve response rates, reduce trial-and-error treatment, and accelerate the development of novel drug combinations.
Q Despite significant advances in cancer research, many oncologists still rely on trial and error to identify effective therapies. Why do you think that remains the case today? A. The persistence of the “trial-and-error” approach is not simply due to a lack of scientific tools – it is also a reflection of entrenched clinical and systemic practices. Traditionally, oncologists prescribe therapies based on established guidelines and population-level
evidence. In this framework, the oncologist is not personally accountable for the success or failure of a particular drug selection, and reimbursement schemes are specifically designed around these standardised pathways. As a result, the process is both familiar and administratively straightforward, even if it does not guarantee optimal outcomes for the individual patient. Functional precision oncology challenges this model. By testing a patient’s live tumour cells against a wide range of drugs, each patient essentially becomes a unique, individualised clinical trial. This approach aligns with a value-based care paradigm, where the focus is on achieving the best outcome for each patient, rather than following broad treatment algorithms. While early clinical studies of functional profiling have shown highly promising results, integrating this approach into standard practice is disruptive. It requires rethinking not only clinical decision-making but also regulatory and reimbursement frameworks that have long favoured traditional trial-and-error prescribing. In essence, functional cancer profiling offers
the potential to move oncology from a system driven by standardised protocols to one guided by patient-specific evidence, which could fundamentally reshape both treatment and the economics of cancer care.
Q. How does functional precision oncology differ from the genetic and molecular profiling approaches currently used to guide treatment decisions? A. Genetic and molecular profiling aim to identify mutations, gene expression changes, or biomarkers in a tumour that may suggest sensitivity or resistance to particular therapies. These approaches have undeniably transformed oncology by enabling targeted therapies when a clear actionable genetic alteration is present. However, their predictive power is indirect:
they tell us what the tumour is (its genotype or molecular state), but not always how it will behave when exposed to a given therapy. In many clinical contexts, two patients harbouring the “same” biomarker or mutation will show
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