Infrastructure for Developing Gastrointestinal Cancer Prognostic and Predictive Markers
One of the current difficulties in the management of GIC is the decision to treat and the
type of treatment to select. Tumour staging and histopathological assessment provides some
indication of the likely aggressiveness of a cancer and hence the need to treat; however
even within specific disease stages and histopathological types there is much variability in
disease outcomes and further sub-categorization is desirable. For the type of treatment to
select, there are currently no established criteria, despite the fact there is much
inter-individual variability in response rates and the occurrence of drug toxicity.
Currently this has also become an increasingly important issue as the numbers of available
regimens for GIC chemotherapy such as 5-FU, capecitabine, irinotecan, oxaliplatin,
gefitinib, erlotinib, cetuximab, and bevacuzimab either alone or in combination has recently
increased, making the treatment selection even more difficult. There is clearly a need for
additional prognostic (predictive of disease aggressiveness) and predictive (predictive of
likely response to treatment) indicators for GIC.
In over 10 years devoted to developing prognostic and predictive markers in different
laboratories and clinics in Australia, Singapore, Europe and USA, the PI has gained deep
experience in what it takes to run a successful program for the development of prognostic
and predictive markers (Soong et al. 1996, Soong et al. 2000, Mattison et al. 2002).
Firstly needed is a comprehensive database linking clinical, histopathological, treatment
and outcome characteristics of each case. This provides multiple functional endpoints to
understand the significance of the candidate marker and a complete overview of likely
influencing factors.
Secondly needed is a collection of samples linked to the database that are suitable for the
testing of candidate markers. In this regard, the types of samples analyzed are also
critical:
In the last few years, the distinction between prognostic and predictive markers has been
found to be increasingly important (Elsaleh et al. 2000). Some cancers may be aggressive
(poor prognosis) but respond well to treatment giving the appearance of good outcome, while
others may be relatively benign (good prognosis) but resistant to treatment, giving a poor
outcome. Without taking this into consideration, some markers considered to be markers of
poor prognosis may be actual markers of poor treatment response but good prognosis, and all
the other possible misleading permutations. The methods to clearly delineate prognostic and
predictive significance have now been defined: Prognostic significance for a marker is
determined by examining its associations with survival in patients without treatment.
Predictive significance is determined by comparing the survival of patients with treatment
against those without in patient subgroups with and without the candidate marker. The
significance of this is that to clearly develop prognostic and predictive markers,
investigators need a group of cases that has not received treatment. Since the mid-1990s,
chemotherapy became a mainstay for advanced GIC cancer and it is now considered unethical
not to treat, implying the only way to accurately assess a marker on its prognostic or
predictive significance is to analyze samples pre-mid 1990s with a recording of their
treatment status, and this can be obtained from archived fixed tissue collections.
The other sample consideration is that to integrate well into clinical practice, prognostic
and predictive markers preferably are analyzable on non-invasive samples and are able to be
proven in prospective analysis. The collection of minimally-inconveniencing blood samples
would serve this purpose, and to have sufficient sample size available for the validation of
future prognostic and predictive markers, it would be provident to begin collection as early
as possible.
Thirdly, to have sufficient statistical power and understand the complexity of the disease
from various angles of expertise in the management of GIC, cross-department and
-institutional collaboration is necessary.
These factors have gone into the proposal of the specific objectives of this current
protocol given above.
Observational
Time Perspective: Prospective
there is no primary outcome measures in this study
no time frame is provided
Dr Alex Chang, MD
Principal Investigator
JHS IMC
Singapore: Domain Specific Review Boards
JS0733
NCT00539318
August 2007
July 2009
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