Cancer Research - Europa

Keywords | Urology | clinical analysis | anticancer therapy | prognonsis | microarray |
Drop-Top
Integration of DNA, RNA and protein
markers in a tool for the prognosis
and diagnosis of human disease
Summary
The management of patients with superfi cial bladder cancer
is diffi cult. No reliable means exists to determine whether
a tumour will progress towards an infi ltrative form, which
requires radical surgery (cystectomy), or whether it will
remain superfi cial, which requires only conservative surgery
(resection). In addition, no dependable marker exists to predict
whether a primary tumour will reappear or not during
the years following surgical resection, forcing patients to
undergo constant revisions that reduce their quality of life
and overburden health care systems.
Numerous markers of various types (genes, transcripts and
proteins) have been analyzed in bladder cancer studies.
Some of them have been found to harbor potential for
the prognosis (progression and recurrence) of superfi cial
tumours. However, analyses have often been limited to a single
type of marker or even to a single marker. To the best of
our knowledge, no study has attempted to integrate diff erent
types of markers for an increased predictive power.
The main scientifi c goal of Drop-Top is to identify a set of
markers with high predictive power for tumour progression
and recurrence. To this end, we propose to collect tumour
and urine samples from bladder cancer patients with
a detailed clinical record, to measure in them markers of
diff erent types, to fi nd statistically signifi cant correlations
between measurements and clinical records, and to select
a predictor set.
In addition, Drop-Top pursues an ambitious technological
challenge: the development of a prognosis microarray for
the detection of said predictor set. In order to achieve this
we propose to measure all three types of marker biomolecules
by means of a single type of probe: oligonucleotides.
Specifi cally, we propose to use short, long and aptamer oligonucleotides
for the detection of gene, transcript and
protein markers respectively.
Problem
Cancer is the second cause of death in the Western world
and its incidence is increasing due to the overall aging of the
population. Although advances in our understanding of the
mechanisms of tumour onset and progression have been
EARLY DETECTION, DIAGNOSIS AND PROGNOSIS
enormous, major impact on survival has been restricted to
haematopoietic malignancies, some pediatric tumours, and
very few solid tumours. Improvement in survival can be
attributed not only to advances in standard chemo- and
radio-therapy and to the recent implementation of targeteddrug
therapy, but also to advances in diagnosis and the
identifi cation of high-risk groups, which allow for earlier and
better treatment selection.
In contrast, the overall prognosis of the most common cancers,
such as lung, colon, prostate, breast and bladder
cancers remains poor, specially when the tumour cannot be
cured by surgery. One limitation is that the pathologist’s
interpretation of the tumour’s histological features remains
the ‘gold standard’. Recent advances in microarray technology
together with information derived from the sequencing
of the human genome have raised hopes that this situation
will change dramatically in the coming years. For these
hopes to be realized, it is essential to make appropriate use
of information, technology and clinical resources. We believe
that resources are often wasted because of inappropriate
approaches and inadequate collaboration between clinical,
academic and industrial partners.
Transcriptome analysis by DNA microarrays has been successfully
used for the identifi cation of biomarkers of tumour
progression. However, and due to the use of diff erent microarray
platforms and patient selection strategies, among
others, the biomarkers identifi ed for a given clinical condition
vary from study to study. Therefore, their application to
common clinical practice has not yet taken place, and
requires prospective studies. The Drop-Top proposal intends
to overcome the above limitations by a double approach:
• prospective validation of the information acquired
through retrospective studies. For this, a collaborative
multicentre eff ort is essential;
• integration of biomarkers from genome, transcriptome
and proteome analysis in a single predictor set. Even
though each of these three analyses by itself will likely
contribute, it is expected that the combination of biomarker
types will result in an enhanced predictive power.
This type of strategy has scarcely been used due to:
• the high cost of microarray technology;
• the need to have access to diff erent platforms for
the detection of diff erent biomolecules;
• the fragmentary nature of most of the published
work (multiple DNA, mRNA and protein markers
studied, but only individually and in most cases
weakly associated to disease phenotype);
• the lack of bioinformatics and biostatistics tools to
handle heterogeneous data;
• the limited amount of clinical and follow-up information
usually available. In addition, most of these studies
are performed without taking into consideration potential
bias in the patient population under study (i.e. large
tumour cases are more likely to be studied than small
tumour cases for sample availability reasons).
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