to identify cancers of various classes not easily distinguishable using other conventional techniques (163,164).
Recently, this principle was applied to ovarian cancer using affymetrix GeneChip microarrays, Santa Clara, CA (41,165). A 115-gene signature was identified, which could predict poor overall survival and, which maintained independent prognostic value in multivariate analysis (41). Similarly, another study was able to differentiate low-grade from high-grade ovarian cancers based on gene-expression profiles and these profiles were also correlated to outcome (165). It was unclear whether the profile retained independent prognostic value when grade was present in the model. Another study identified gene profiles in clear cell carcinomas that distinguished these tumors from other poor prognosis tumors (33). Overall, these types of analyses are in their infancy, but based on work performed in other cancers and preliminary work in ovarian cancer the future is promising for these approaches. On the other hand, these techniques are much more time-consuming and difficult compared with the measurement of individual biomarkers using immunoassays. Moreover, it is unclear, at this point, whether these gene profiling techniques will necessarily yield superior predictive values compared with a well chosen combination of biomarkers.
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