Analytical approaches relating genetic evolutionary pathways to prognostic factors.

Human solid tumors accumulate multiple genetic abnormalities as they progress to advanced stages. Multiparameter flow cytometry measurements of individual cells within each tumor may be useful in describing the genetic pathways taken by individual tumors during the course of their genetic evolution. In this paper, we analyzed correlated cell-by-cell measurements of cell DNA content, HER-2/neu protein content, and ras protein content obtained by multiparameter flow cytometry studies of primary breast cancers from 92 patients. These laboratory findings were correlated with established clinical prognostic factors for each patient at the time of diagnosis, using a stepwise multiple analysis of variance (MANOVA). The stepwise MANOVA successively splits a group of patients into two mutually exclusive dissimilar groups, selecting the clinical prognostic factor that is most effective in doing so. Using this criterion, formation of the first three groups that were judged most dissimilar on the cytometry parameters was based on the number of positive nodes at the time of diagnosis. We show that ploidy, HER-2/neu protein content, and ras protein content, as measured by multiple parameter flow cytometry, are correlated with nodal status and other known clinical prognostic factors. The cell-by-cell multiparameter data suggest that for some individual tumors there are multiple genetic evolutionary pathways. Multiple genetic evolutionary pathways are also suggested by the MANOVA analysis. Focusing on the identification and analysis of genetic evolutionary pathways within individual tumors and across patients appears to offer a promising approach for defining the prognosis of early cancers.