chapter  13
TAILORx: Rationale for the Study Design
ByJoseph A. Sparano
Pages 12

There have been substantial technical and analytical advances within the past

decade that have facilitated high-throughput analysis of clinical specimens, a

process that has been referred to as “molecular profiling.” This term, as applied

here, may refer to evaluating various “markers,” including genomic, proteomic,

and epigenomic expression patterns, or a combination of these patterns, in

clinical specimens. Technological advances have led to the ability to measure

thousands of markers with a variety of validated methods (1), and analytical

models have been developed that facilitate analysis of the voluminous amount of

data that are generated (2). The technology has also led to an ability to perform

“discovery-based research,” in which large volumes of data are generated and

analyzed without a specific hypothesis, in contrast to the traditional scientific

paradigm of “hypothesis-based research,” in which a limited number of genes or

proteins are based upon a specific hypothesis and rationale (3). Discovery-based

research and hypothesis-based research are not mutually exclusive; however,

profiling may also be used to test specific hypotheses that are based on sound,

scientific rationale. A series of studies have been reported over the past few

years that have utilized gene expression profiling to discover “molecular

markers,” which may identify (i) distinct molecular subtypes of breast cancer

(i.e., genotypic-phenotypic correlation), (ii) molecular signatures-associated

prognosis (i.e., prognostic factors), and (iii) molecular signatures that predict

the benefit from specific therapies (i.e., predictive factors) (4). When a

“molecular marker” is shown to perform more reliably than clinical features in

predicting prognosis or the benefit from a specific intervention, then there is

interest in further evaluating the utility of the marker in clinical practice (5).