RELEVANCE OF MULTIPLE BIOLOGICAL PARAMETERS IN BREAST-CANCER PROGNOSIS

A multitude of clinical, pathological and biological parameters have b een reliably associated with prognosis in breast cancer patients. Rece ntly much interest has been engendered by multifactorial computing met hods attempting to produce higher prognostic accuracy as well as being of clinical utility for treatment selection. Clinical, pathological a nd a number of more recent biological parameters were evaluated retros pectively in a population of 196 breast cancer patients who had been t reated with first line surgery and followed for a median of 7.3 years. Clinical tumour size, menopausal status, type of treatment as well as tumour grade, pathological tumour size, node invasion, the presence o f vascular emboli and steroid hormone receptor status were evaluated t ogether with gene amplification (by Southern blot) of c-erbB2/neu, c-m yc and int-2/FGF3 as well as overexpression (by immunohistochemistry, IHC) of c-erbB2/neu, EGF receptor, CSF-1 and CSF-1 receptor. The prese nce and abundance of inflammatory cell infiltrates (T, B cells and mon ocytes) were also evaluated by IHC. The risk of cancer related death a s tested in univariate and multivariate analyses was consistently high er in patients with positive axillary nodes and in those whose tumours showed evidence of int-2/FGF3 gene amplification, of overexpression o f c-erbB2/neu at the cellular membrane, of vascular invasion by tumour cells and of abundant CD45RO+ T cells infiltrates. A prognostic score was calculated for each patient by computing the prognostic index ass ociated with each of these five parameters and risk profiles were esta blished by order of increasing risk. Survival curves drawn for three g roups of high, intermediate or lowest risk showed a highly significant poorer survival for the highest risk group. The model we present, alt hough far from the complexity of a 'neural network' analysis, does dis criminate effectively between low, moderate and high risk groups. Futu re prospective studies should test these independent prognostic marker s together with more recently established markers in an attempt to det ermine not only the most predictive but also the most cost-effective ' prognostikit' for breast cancer patients. Such a molecular prognostic index will allow the evaluation of current therapies in the light of s pecific molecular alterations and may aid the design of new therapeuti c approaches geared to the genetic profile of a given tumour.