A number of recent studies have reported on the use of biomarkers,
particularly blood-based ones, that offer the potential for screening
diseases such as cancer and HIV.
A biomarker can be a gene, a gene mutation, protein, other molecule
or clinical measurement that indicates a given disease state. Biomarkers
can be diagnostics (telling us of the presence of a given disease),
prognostic (telling us of the outcome for a patient with a particular
disease) and predictive (telling us of the response of an individual to a
given therapy). The latter has led to the rise of so-called
personalised or precision medicine.
Recent technologies developed since the sequencing of the human
genome allow scientists to profile samples using a patient’s whole
genome sequence, the expression of all of their genes, or by measuring
thousands of proteins. Before this technology was developed, single
biomarkers were often discovered by a chance observation, a hypothesis
based on existing molecular knowledge or by laborious screening.
Jolie has used biomarkers to make choices. Hot Gossip Italia, CC BY
PSA for prostate cancer and the CA125 protein for ovarian cancer are
two biomarkers currently used in this way. An elevated level of both of
these in the blood is taken as a signal of early-stage cancer and CA125
was one of the markers actress Angelina Jolie Pitt used in her decision to remove her ovaries and fallopian tubes.
A recent study
from University College London, published in the Journal of Clinical
Oncology, showed that elevated levels of the protein CA125 in blood
serum could diagnose advanced stages of ovarian cancer. The study
examined more than 200,000 post-menopausal women and a computer program
was then used to predict the risk of ovarian cancer based on factors
including age, the original level of the protein and how that level
changed over time.
The test was successful in diagnosing ovarian cancer in 86% of women
with invasive epithelial ovarian cancer and was hailed as the most
effective diagnostic tool for detecting cancer after the onset of
symptoms, compared to the conventional CA125 blood test and
trans-vaginal ultrasound, where the ovaries are scanned by ultrasound
through the wall of the vagina. These findings are extremely promising
and show the potential for using computer-based decision tools with
multiple features.
Using Single Markers
One of the limitations of using older approaches such as laborious
screening or hypotheses to discover biomarkers is that they may not be
the best marker to use and there may be other markers in the patient’s
profile which have greater accuracy, sensitivity and/or specificity (the
ability to correctly predict positive cases and to also predict
negative cases correctly).
More than one marker in the blood? Ink by Shutterstock
Another limitation is that a single marker, while clinically
appealing due to simplicity and low cost, may not capture the
variability of disease through the population, which lowers accuracy,
sensitivity and specificity.
This heterogeneity has been widely reported in breast cancer for example, where at least ten molecular subtypes
of disease, each having different outcomes and treatments, have been
hypothesised. Often scientists have sought to overcome the limitations
of such tests by retrospectively adding further biomarkers to the
existing test. Some tests, such as OncotypeDX for breast cancer, use
post-genomic data, where thousands of genes and/or proteins are measured
to produce a molecular profile of a sample to identify multiple markers
and thus capture more of the variability of the disease.
In the future it is likely that through activities such as the 100,000 Genomes Project,
and through molecular profiling projects, such as those being
undertaken in the John van Geest Cancer Research Centre at Nottingham
Trent University and other cancer research centres, more sophisticated
multi-marker tests will be developed.
Molecular profiling generates a vast amount of highly complex data,
with millions of potential biomarker variables – the analysis of which
is not a trivial undertaking. In order to develop an optimised
diagnostic test, this data needs to be analysed using appropriate
computer algorithms (the work of bioinformaticians) to develop highly
sensitive and specific diagnostic computer programs. Through this we
will be able to integrate an optimum set of biomarkers into computer
programs that aid in the clinical decision-making process. These
programs can then be disseminated through the internet, leading to more
widespread testing and validation.
The use of blood-based tests offers a great deal of potential for
non-invasive screening. However any test has to be trialled
prospectively in order to determine whether it truly screens all
positive cases. There has been much debate on the over-treatment of
cancers detected by screening – so-called false-positives, where cases
test positive for disease when in fact no disease is present, leading to
patients undergoing unnecessary and sometimes invasive treatments. This
debate will be fuelled further by blood-based diagnostic biomarkers.
The limitations of such processes need to be given careful consideration
before widespread use.
