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124<br />
Aim<br />
Drop-Top has two major objectives, one technological and<br />
one scientifi c. Regarding the former, we propose to develop<br />
a tool for multiparametric analyses (mRNA levels, large<br />
genetic rearrangements, genetic mutations, genetic polymorphisms,<br />
protein levels and post-translational modifi cations)<br />
of biological samples, to better predict tumour progression<br />
and recurrence (see Figure 1). The evaluation of such heterogeneous<br />
parameters will be performed on a single microarray:<br />
the triple microarray, an oligonucleotide microarray for<br />
simultaneous DNA, RNA and protein assessment). The triple<br />
microarray constitutes the test surface of a workstation that<br />
integrates technology for the hybridization, scanning and<br />
detection of biomarkers. Its simplicity should facilitate a wide<br />
implementation of this tool in the clinic.<br />
As scientifi c objective, we propose to identify a set of<br />
biomarkers with power for the prediction of clinical behaviour<br />
of bladder cancer. Selection of such set of biomarkers<br />
will be the end point of a fi ve-phase endeavour:<br />
• identifi cation of candidate biomarkers for bladder cancer<br />
progression and recurrence from the scientifi c<br />
literature and from existing data generated by two<br />
Drop-Top partners specialized in bladder cancer;<br />
• pre-selection of biomarkers on the basis of the strength<br />
of their association to tumour behaviour and on the scientifi<br />
c and technical quality of the study;<br />
• measurement and validation of said candidate biomarkers<br />
in a set of samples from patients with a detailed<br />
clinical record and follow-up;<br />
• application of bioinformatics and biostatistics tools for<br />
the identifi cation of a set of biomarkers with a strong<br />
association to tumour behaviour.<br />
Figure 1 | Triple microarray and Integrated station for improved multiparametric<br />
analyses of biological sample.<br />
The DroP-ToP strategy should be applicable to the study of<br />
any tumour type, and more generally to any disease with<br />
a genetic or gene-expression component. However, and as<br />
a proof of concept, we propose to apply it to bladder carcinoma<br />
because it represents a paradigm of the need for<br />
useful biomarkers in the clinical setting:<br />
• it is one of the best models of tumour progression;<br />
• its incidence ranks fi fth among all cancer types (the<br />
fourth most common in males and the ninth in females);<br />
• despite widely variable outcome, the diagnosis and<br />
prognosis tools used in the clinic are few and the same,<br />
and they are invasive even for asymptomatic patients<br />
(cystoscopy);<br />
• it is the most expensive cancer type, as it can recur many<br />
times after treatment;<br />
• its evolution is very diffi cult to predict, whereas the therapeutic<br />
approach for its two forms is completely diff erent:<br />
when invasive at the time of diagnosis, it has a poor<br />
prognosis and requires aggressive surgery (cystectomy);<br />
when non-invasive, prognosis is favourable and it only<br />
requires conservative surgery (resection);<br />
• its recurrence is also diffi cult to predict, which leads to<br />
unnecessary visits and cystoscopies for about 50 % of<br />
patients, whose tumours will never recur;<br />
• a number of highly promising biomarker candidates have<br />
already been identifi ed and reported in the literature.<br />
Expected results<br />
<strong>Cancer</strong> is the second leading cause of death worldwide. In<br />
the year 2002 there were 10 million new cases of cancer in<br />
the world, 6 million deaths and approximately 22 million<br />
people living with cancer worldwide. It is estimated that by<br />
year 2020 there will be 15 million new cases per year, and<br />
10 millions deaths. Bladder cancer is a highly common neoplasia,<br />
mainly among men, and its incidence is rising in several<br />
countries in Europe. Approximately 125 000 new cases with<br />
bladder cancer are diagnosed each year in the EU.<br />
Despite continued interest in the development of novel tests<br />
to better predict bladder cancer prognosis, there has been<br />
very limited progress. This is in part due to the fact that all<br />
tests developed until present are based on the detection of<br />
only one type of biomolecule (i.e. RNA, DNA or protein). Our<br />
approach is radically diff erent: from a systematic review of<br />
current knowledge on biomarkers of bladder cancer and<br />
existing research results of the participating academic partners,<br />
we propose to develop a microarray that can detect<br />
the 3 major types of molecules in human biological samples.<br />
This should provide a much more solid basis to identify<br />
molecular predictors of the disease.<br />
CANCER RESEARCH PROJECTS FUNDED UNDER THE SIXTH FRAMEWORK PROGRAMME