Tissue-type plasminogen activator (tPA) in breast cancer: relationship with clinicopathological parameters and prognostic significance.
ABSTRACT Tissue-type plasminogen activator (tPA) is a serine protease primarily involved in the intravascular dissolution of blood clots. High intratumoral tPA levels are associated with prognosis in several human tumors. In addition, tPA has been shown to be an estrogen-inducible protein in human breast cancer cell lines. The aim of the present study was to analyze the cytosolic tPA content in primary breast carcinomas and its potential clinical value.
tPA was measured by a solid-phase enzyme immunoassay in tumor cytosol samples obtained from 800 patients with breast cancer. The median follow-up period was of 49.2 months.
Cytosolic tPA levels ranged widely in breast carcinomas (median: 3.9; range: 0.1- 315.3 ng/mg protein). tPA levels were significantly lower in large tumors, as well as in those showing poor differentiation, estrogen (ER) or PgR-negativity, aneuploidy, or a high S-phase fraction. In addition, low tPA intratumoral levels were associated with a high probability of both shortened relapse-free and overall survival in all patients and in the subgroup with node-negative tumors. However, our results did not show any significant relationship between intratumoral tPA levels and prognosis in the different subgroups of patients, stratified according to the type of systemic adjuvant therapy received (chemotherapy, tamoxifen or chemotherapy plus sequential tamoxifen).
The results of the present investigation indicate that low intratumoral tPA levels are associated with aggressiveness and poor prognosis in breast cancer patients. However, the study suggests that tPA levels do not predict response to systemic adjuvant therapy.
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ABSTRACT: Recent studies on the pattern of gene expression in estrogen receptor positive and negative tumours have revealed profound differences according to receptor status. However, it remains unclear if these differences reflect phenotypic traits in addition to sensitivity to endocrine therapy. This paper describes the long-term pattern of disease recurrence among ca. 2,600 pre- and post-menopausal patients with primary breast cancer according to estrogen receptor status. The study was based on patients with an operable, invasive breast cancer entered in one of three controlled clinical trials conducted by the Stockholm Breast Cancer Group. We selected those 2,562 patients who had been randomly allocated between adjuvant tamoxifen and no adjuvant systemic therapy. These patients had a known estrogen receptor status. Tamoxifen reduced locoregional (8.8% vs. 12.4%, hazard ratio (HR), 0.66; 95% CI, 0.52-0.83; P = 0.001, distant recurrences (17.2% vs. 20.2%, HR, 0.81; CI, 0.68-0.97; P = 0.018, as well as breast cancer death (18.7% vs. 23.7%, HR, 0.78; CI, 0.67-0.92; P = 0.002). Among patients not allocated to tamoxifen there was no significant differences in term of neither locoregional (12.4% vs. 12.4%, HR, 1; CI, 0.72-1.41; P = 0.98), nor distant metastases (18.5% vs. 20.7%, HR, 1.11;CI, 0.85-1.45; P = 0.46) according to ER status. The pattern of metastases was not different in ER positive comparison with ER negative. The results showed that the mentioned substantial differences in terms of gene expression appeared mainly to be related to endocrine sensitivity and not to metastatic potential. However, a slight advantage during the first five years for the ER positive versus ER negative patients in terms of cumulative incidence of events, suggested that ER negativity in some cases is correlated with an increased tumour growth rate.Breast Cancer Research and Treatment 02/2008; 107(1):71-8. · 4.47 Impact Factor
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ABSTRACT: The PDGF (platelet-derived growth factor) family members are potent mitogens for cells of mesenchymal origin and serve as important regulators of cell migration, survival, apoptosis and transformation. Tumour-derived PDGF ligands are thought to function in both autocrine and paracrine manners, activating receptors on tumour and surrounding stromal cells. PDGF-C and -D are secreted as latent dimers, unlike PDGF-A and -B. Cleavage of the CUB domain from the PDGF-C and -D dimers is required for their biological activity. At present, little is known about the proteolytic processing of PDGF-C, the rate-limiting step in the regulation of PDGF-C activity. In the present study we show that the breast carcinoma cell line MCF7, engineered to overexpress PDGF-C, produces proteases capable of cleaving PDGF-C to its active form. Increased PDGF-C expression enhances cell proliferation, anchorage-independent cell growth and tumour cell motility by autocrine signalling. In addition, MCF7-produced PDGF-C induces fibroblast cell migration in a paracrine manner. Interestingly, PDGF-C enhances tumour cell invasion in the presence of fibroblasts, suggesting a role for tumour-derived PDGF-C in tumour-stromal interactions. In the present study, we identify tPA (tissue plasminogen activator) and matriptase as major proteases for processing of PDGF-C in MCF7 cells. In in vitro studies, we also show that uPA (urokinase-type plasminogen activator) is able to process PDGF-C. Furthermore, by site-directed mutagenesis, we identify the cleavage site for these proteases in PDGF-C. Lastly, we provide evidence suggesting a two-step proteolytic processing of PDGF-C involving creation of a hemidimer, followed by GFD-D (growth factor domain dimer) generation.Biochemical Journal 02/2012; 441(3):909-18. · 4.65 Impact Factor
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ABSTRACT: Glucocorticoid receptor (GR) activation can inhibit breast epithelial and cancer cells from undergoing programmed cell death in response to diverse apoptotic stimuli. Understanding the mechanisms underlying inappropriate cell survival mechanisms is important for treating breast cancer because if we can reverse these mechanisms, therapies designed to kill tumor cells are likely to be more effective. Recently, genome-wide DNA microarrays have provided a glimpse into the signals and interactions within regulatory pathways of the cell. These arrays enable simultaneous measurement of mRNA abundance of most, if not all, identified genes in a genome under different physiological conditions. Currently, two types of microarray experiments are frequently performed in laboratories. The first is a single time point microarray experiment, and the second is a time course microarray experiment. Single time point microarray experiments are effective in identifying genes regulated by a given treatment, e.g., direct target genes of a hormone treatment. However, because molecular pathways are dynamic processes that take place over time, single time point microarray experiments may not allow us to identify dynamic molecular pathways. This problem can be approached by performing a time course microarray experiment, which measures gene expression changes at various time points following a given treatment. In this chapter, we first describe how to identify target genes of a given treatment using a single time point microarray data analysis. We then present three alternate bioinformatics approaches to uncover molecular mechanisms from time course microarray data. Finally, we present a novel bioinformatics approach for analyzing time course microarray data in order to identify novel GR-mediated breast cancer cell survival pathways.12/2007: pages 165-183;