BACKGROUND: Individual assessment of the prognosis of patients with breast cancer is crucial for the selection of risk-adapted adjuvant therapy and in follow-up. Parameters from DNA flow-cytometry have been shown to provide significant prognostic information, but published results are in conflict and there are only a few investigations with long-term follow-up. The aim of this study is to clarify the impact of tumor DNA data on the clinical course of stage I and stage II breast cancer patients. PATIENTS AND METHODS: Several flow-cytometry DNA analyses were performed on tumor samples derived from 191 breast cancer patients entered in a controlled clinical trial after a median follow-up of more than 10 years. In addition to DNA index (DNI) and the percentage of cells in S phase (SPF), an index, designated aneuploidy fraction (AF), was determined. It ascertains the percentage of aneuploid cells out of all cells in the DNA flow-cytometry histogram, and its reproducibility has been tested by measurements of AF in two different samples of the same tumor. Univariate analyses and, in the 122 patients for whom complete information was available, a Cox model, were performed to investigate the individual prognostic impact of flow-cytometry parameters compared with established clinical factors. RESULTS: AF proved to be a very valuable prognostic indicator both in univariate and multivariate analyses, whereas DNI and SPF failed to provide independent prognostic information. The combination of AF and lymph node status clearly identifies different prognostic subgroups in operable breast cancer. CONCLUSIONS: Routine evaluation of patients with breast cancer should include tumor DNA flow-cytometry. Aneuploidy fraction is a valuable tool in assessing an individual patient's prognosis and thus can help in the choice of the appropriate adjuvant treatment strategy. Whether it, rather than DNI and SPF should be used, as we found, needs to be validated in a larger prospective investigation.
BACKGROUND: Individual assessment of the prognosis of patients with breast cancer is crucial for the selection of risk-adapted adjuvant therapy and in follow-up. Parameters from DNA flow-cytometry have been shown to provide significant prognostic information, but published results are in conflict and there are only a few investigations with long-term follow-up. The aim of this study is to clarify the impact of tumor DNA data on the clinical course of stage I and stage II breast cancerpatients. PATIENTS AND METHODS: Several flow-cytometry DNA analyses were performed on tumor samples derived from 191 breast cancerpatients entered in a controlled clinical trial after a median follow-up of more than 10 years. In addition to DNA index (DNI) and the percentage of cells in S phase (SPF), an index, designated aneuploidy fraction (AF), was determined. It ascertains the percentage of aneuploid cells out of all cells in the DNA flow-cytometry histogram, and its reproducibility has been tested by measurements of AF in two different samples of the same tumor. Univariate analyses and, in the 122 patients for whom complete information was available, a Cox model, were performed to investigate the individual prognostic impact of flow-cytometry parameters compared with established clinical factors. RESULTS:AF proved to be a very valuable prognostic indicator both in univariate and multivariate analyses, whereas DNI and SPF failed to provide independent prognostic information. The combination of AF and lymph node status clearly identifies different prognostic subgroups in operable breast cancer. CONCLUSIONS: Routine evaluation of patients with breast cancer should include tumor DNA flow-cytometry. Aneuploidy fraction is a valuable tool in assessing an individual patient's prognosis and thus can help in the choice of the appropriate adjuvant treatment strategy. Whether it, rather than DNI and SPF should be used, as we found, needs to be validated in a larger prospective investigation.
Authors: Ubaldo E Martinez-Outschoorn; Renee M Balliet; Dayana B Rivadeneira; Barbara Chiavarina; Stephanos Pavlides; Chenguang Wang; Diana Whitaker-Menezes; Kristin M Daumer; Zhao Lin; Agnieszka K Witkiewicz; Neal Flomenberg; Anthony Howell; Richard G Pestell; Erik S Knudsen; Federica Sotgia; Michael P Lisanti Journal: Cell Cycle Date: 2010-08-28 Impact factor: 4.534
Authors: M Fiegl; C Tueni; T Schenk; R Jakesz; M Gnant; A Reiner; M Rudas; H Pirc-Danoewinata; C Marosi; H Huber Journal: Br J Cancer Date: 1995-07 Impact factor: 7.640