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Context and Aims: Breast cancer prognosis and predictive biomarkers development would allow sparing some patients from chemotherapy or identifying patients for whom chemotherapy would be indicated. In this context, in 2009, the French National Cancer Institute, a National Health and Science Agency dedicated to cancer, in collaboration with the French society of senology and breast pathology (SFSPM) published a report on the assessment of the prognostic and the predictive clinical validity of tissular biomarkers, uPA/PAI-1, Oncotype DX™ and MammaPrint(®), in breast cancer management. They concluded that only the uPA/PAI-1 prognosis value reached the highest level of evidence (LOE I according to Hayes 1998 classification). In 2012, it was decided to update this report since new data have emerged and because information disparities among clinicians have been identified. This article aims to present the main conclusions together with the levels of evidence associated with those conclusions., Methods: The updating process was based on literature published since 2009 appraisal and on multidisciplinary and independent experts' opinion. The levels of evidence (LOE) used are those of the classification defined by Simon in 2009 (updated Hayes 1998 classification): LOE IA and LOE IB: high level of evidence; LOE IIB and LOE IIC: intermediate level of evidence; LOE IIIC and LOE IV-VD: low level of evidence., Conclusions: Among patients without lymph-node involvement, uPA/PAI-1, invasion process biomarkers, reach the highest level of evidence for 10 years recurrence free survival prognosis (LOE IA according to Simon). The predictive value to anthracyclins chemotherapy remains to be confirmed. Oncotype DX™ and MammaPrint(®) prognosis and predictive value do not reach the LOE I level. This updating' process confirms the 2009 levels of evidence for all the three biomarkers prognosis value. Besides, concerning Oncotype DX™ and MammaPrint(®), new data do not allow to conclude neither to their complementary clinical information to other clinicopathological existing biomarkers nor to a favorable cost-efficiency ratio in therapeutic decision making and this because of the methodological weakness and uncertainty that are identified in the selected studies. Practically, beyond the prognosis and predictive biomarkers validity, the clinical utility of a new biomarker for chemotherapy indication depends on its clinical added information with regard to validated biomarkers (HR, HER2 and Ki67) and to clinicopathological parameters. Since they are the sole validated biomarkers of the invasion process, uPA/PAI-1 could complete clinical information of other clinicopathological factors and consequently could confer an added clinical value. However, data concerning the impact of this information on chemotherapy clinical indication are lacking., (Copyright © 2014. Published by Elsevier Masson SAS.)

Among the proteases involved in the tumor invasion process, components of the plasminogen activator system (plasminogen activator type-urokinase uPA, its membrane receptor uPAR and its two inhibitors PAI-1 and PAI-2) appear to define high risk patients in primary breast cancer. As individual analysis of each component of the plasminogen activator system does not reflect the complex interactions between the different components, we studied the prognostic impact of a dissemination risk index combining the four variables. We found that this index was the most powerful prognostic factor, particularly in node-negative patients.

It is now clearly established that proteolytic enzymes, and in particular plasminogen activator (uPA), play an important role in breaking down the extracellular matrix, which is considered to be a step in metastasis formation. Plasminogen activators are controlled at various levels. Two inhibitors, PAI-1 and PAI-2, have been identified, the latter being more specific for uPA. In attempts to determine their prognostic value, it is essential to investigate the relative importance of these parameters and their interactions. We used an immunoenzymatic method to assay uPA, PAI-1 and PAI-2 antigens in cytosols prepared from 314 primary breast tumors. The patients were followed up for a minimum of six years and all relevant clinical and laboratory findings had been recorded. Univariate analysis confirmed the poor outcome of patients whose tumors contained large amounts of uPA and PAI-1. In addition, low levels of PAI-2 correlated with shorter disease-free survival in the overall population (P = 0.02), post-menopausal women (P = 0.02) and women without lymph node involvement (P = 0.02). Multivariate analysis using the "Main Effects" Cox model identified node involvement, macroscopic tumor size and PAI-2 as significant variables. The "interactive" Cox model, taking into account interactions between uPA and its two inhibitors, identified a first subgroup with a very poor prognosis associating either high levels of PAI-1 with low levels of PAI-2 in the overall population as well as following stratification for axillary node negative disease, or high levels of uPA with low levels of PAI-2 in the group of menopausal women. We conclude that PAI-1 provides the same prognostic informations as uPA, and does not appear to play its role as an inhibitor. In contrast, PAI-2 increased the prognostic value of both uPA, particularly in post-menopausal women, as well as PAI-1 in a subgroup of axillary node negative patients.

Among the great many prognostic factors currently available in breast cancer, three classes of tissue biological parameters appear to be the most reliable in the establishment of a clinical decision flowchart, when they will have been technically and clinically validated: parameters of hormone dependence, tumour aggressiveness and invasion and parameters of proliferation. This article discusses the difficulties encountered in the evaluation of some of these parameters (hormone receptors by various methodological approaches, proteases, enzymes involved in cell proliferation), with emphasis on standardisation of techniques, development of quality controls, clinical validation and objective information of the medical and scientific communities.