Present situation and future of genetic profiling for prognosis and treatment

Excerpt

Classification and staging systems are important in oncology to predict clinical behavior and determine prognosis. In addition, they may contribute to the selection of optimal treatment strategies. Much clinical and translational research over the past 30 years was directed at establishing or refining prognostic and predictive factors for breast cancer. Initially, tumor related factors such as size, grade, lymph node involvement, and hormone receptor status were considered in the determination of prognosis. Patient characteristics, such as age, menopausal status and performance status, also contributed to these estimates. Some factors such as estrogen receptor (ER) status were shown to be better predictive factors than prognostic factors. Thus, although ER-positive tumors have a slightly better prognosis during the early years of follow up than do ER-negative ones, the major application of ER status is to predict response to endocrine therapy. A variety of biochemical and molecular factors were reported to have prognostic or predictive ability over the past 20 years. These included cathepsin D, HER2, EGFR, p53, UPA, PAI, and many others. Of these, only HER2 was consistently validated as a prognostic factor, as well as a predictor of response to the monoclonal antibody trastuzumab (Herceptin). Developing, assessing, and discarding these various putative prognostic and/or predictive factors was the result of an enormous investment of time and effort of many scientists from many countries around the world. Considering that only one new prognostic/predictive factor was universally adopted over the past 25 years (HER2 status), it must be concluded that this is an enormously inefficient process. …