Identifying markers to predict a patient's response to therapy
In his first job as a research assistant to Professor Bernard Stewart, Dr Daniel Catchpoole was introduced to childhood cancer research. Like many scientists, Daniel is drawn by the thrill of discovery but when the mother of a cancer patient asks 'why?' it turns the academic pursuit into a human reality.
For Daniel it's not so much that cancer research is important to
him, it's just important. "When a mother of a child who died of a
brain tumour looks you in the eye and says 'we know he didn't have
a chance and the doctors did their best; we just want to know how
the tumour got there' it is up to the researcher to answer her
questions. Not the clinician, nurse or social worker," says
Daniel.
While the answers to the hows and whys of cancer are still being
sought, the answers to how best to treat cancer patients
individually are becoming realities. Daniel's research into
identifying markers that may predict a patient's response to
therapy means we are one step closer to personalised medicine.
"Personalised medicine is one of the goals of the cancer
research effort. That is, by treating each patient with the right
drug and the right dose it will provide them with the greatest
benefit in the management of their disease. It is our belief that
to truly personalise medicine we need to learn how to view patients
as individuals rather than in cohorts," explains Daniel.
"Most studies currently undertaken take groups of patients with
similar clinical criteria and attempt to identify common biological
attributes within those groups. Our approach is to explore, map,
mine and make sense of the vast amount of biological
information we can now gather for patients and their tumours so as
to allow a patient to patient comparison."
Daniel's approach means that a model can be built whereby each
patient within a cohort can be compared to each other on the basis
of biological similarity, rather than clinical presentation. This
will answer one of the key questions which confront clinicians -
whether the patient they are treating will respond to the therapy
they are administering.
"Patients which cluster together can then be compared with
respect to prior treatment strategy, outcome and medical
complications. Clinicians will then be able to use this information
to inform their treatment strategies for new patients who fall into
this cluster."
All medical advancement, even the
development of the humble band aid, has been the result of someone
doing research.
Traditionally, researchers group patients together who have
common clinical symptoms, pathology results or response to
treatment and attempt to identify biological and/or genetic defects
which will characterise the entire group. However, many human
diseases, especially cancer, are complex with a range of symptoms,
pathological results and genetic backgrounds seen in patients. The
complexity of human biology precludes researchers from simply
discovering a single consistent defect which is common for an
entire disease subgroup.
"Our study aims to apply data analysis techniques to genetic,
genomic and proteomic data to improve patient diagnosis, direct
clinical management approaches, lead to personalised treatment
strategies and eventually improve treatment outcomes for cancer
patients."
But it all has to start somewhere. As Daniel says, "All medical
advancement, even the development of the humble band aid, has been
the result of someone doing research."
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