p53, cathepsin D, Bcl-2 are joint prognostic indicators of breast cancer metastatic spreading

Guerra et al. BMC Cancer (2016) 16:649 DOI 10.1186/s12885-016-2713-3 RESEARCH ARTICLE Open Access p53, cathepsin D, Bcl-2 are joint prognostic indicators of breast cancer metastatic spreading Emanuela Guerra1, Alessia Cimadamore1, Pasquale Simeone1, Giovanna Vacca1, Rossano Lattanzio1,2, Gerardo Botti3, Valentina Gatta4, Marco D’Aurora4, Barbara Simionati5, Mauro Piantelli1,2 and Saverio Alberti1,6* Abstract Background: Traditional prognostic indicators of breast cancer, i.e. lymph node diffusion, tumor size, grading and estrogen receptor expression, are inadequate predictors of metastatic relapse. Thus, additional prognostic parameters appear urgently needed. Individual oncogenic determinants have largely failed in this endeavour. Only a few individual tumor growth drivers, e.g. mutated p53, Her-2, E-cadherin, Trops, did reach some prognostic/predictive power in clinical settings. As multiple factors are required to drive solid tumor progression, clusters of such determinants were expected to become stronger indicators of tumor aggressiveness and malignant progression than individual parameters. To identify such prognostic clusters, we went on to coordinately analyse molecular and histopathological determinants of tumor progression of post-menopausal breast cancers in the framework of a multi-institutional case series/case-control study. Methods: A multi-institutional series of 217 breast cancer cases was analyzed. Twenty six cases (12 %) showed disease relapse during follow-up. Relapsed cases were matched with a set of control patients by tumor diameter, pathological stage, tumor histotype, age, hormone receptors and grading. Histopathological and molecular determinants of tumor development and aggressiveness were then analyzed in relapsed versus non-relapsed cases. Stepwise analyses and model structure fitness assessments were carried out to identify clusters of molecular alterations with differential impact on metastatic relapse. Results: p53, Bcl-2 and cathepsin D were shown to be coordinately associated with unique levels of relative risk for disease relapse. As many Ras downstream targets, among them matrix metalloproteases, are synergistically upregulated by mutated p53, whole-exon sequence analyses were performed for TP53, Ki-RAS and Ha-RAS, and findings were correlated with clinical phenotypes. Notably, TP53 insertion/deletion mutations were only detected in relapsed cases. Correspondingly, Ha-RAS missense oncogenic mutations were only found in a subgroup of relapsing tumors. Conclusions: We have identified clusters of specific molecular alterations that greatly improve prognostic assessment with respect to singularly-analysed indicators. The combined analysis of these multiple tumor-relapse risk factors promises to become a powerful approach to identify patients subgroups with unfavourable disease outcome. (Continued on next page) * Correspondence: 1 Unit of Cancer Pathology, CeSI-MeT, University of Chieti, Chieti, Italy 6 Department of Neurosciences, Imaging and Clinical Sciences, University ‘G. D’Annunzio’, Chieti, Italy Full list of author information is available at the end of the article © 2016 The Author(s). Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Guerra et al. BMC Cancer (2016) 16:649 Page 2 of 15 (Continued from previous page) Keywords: Breast cancer, Metastatic relapse, Prognostic indicators, TP53, Bcl-2, Cathepsin D, RAS Abbreviations: CI, Confidence interval; CV, Cross-validation; Fab, Fragment antigen-binding; FFPE, Formalin-fixed paraffin-embedded; HR, Hazard ratio; IHC, Immunohistochemistry; PCR, Polymerase chain reaction; PK, Proteinase K; PLS-DA, Partial least squares discriminant analysis; TMA, Tissue micro-array; VIP, Variable importance in the projection Background Breast cancer (BC) is the most frequent malignancy in women with 800 cases out of 100,000 people, four-times as many as the second most frequent one, i.e. colorectal cancer [1]. Histopathology classification of BC according to tumor grade, stage, histotype, lymph node invasion and hormonal receptor status [2] is broadly used to draw correlations with survival. However, this classification performs poorly in predicting differential biological aggressiveness of tumors with identical grade and stage. As an example, patients with the best prognosis, i.e. bearing small size tumors, expressing estrogen receptors and without lymph node invasion, experience early tumor relapse in 10-20 % of the cases [3, 4]. Cases that relapse do not detectably differ from those that do not, as far as conventional prognostic parameters are concerned. Determinants of tumor biological history are expected to add to traditional prognostic classification algorithms [5, 6]. Individual oncogenic determinants, e.g. p53, Her2, E-cadherin, BRCA-1, Trops, have indeed been shown to add to prognostic and predictive procedures [5, 7– 11]. However, they largely failed to outperform traditional prognostic indicators. Tumor development depends on the accumulation of several specific genetic and epi-genetic changes [12–14]. Thus, the analysis of individual oncogenic factors is unlikely to suffice in defining the biological nature and aggressiveness of a tumor [15]. Major control pathways or clusters of drivers of cell growth, apoptosis or invasion are, on the other hand, expected to associate with tumor aggressiveness and overall malignancy much more strongly than individual factors. In this work we went on to test this model. Histopathology and oncogenicallyactivated determinants of tumor progression of BC were analyzed in the framework of a case-control study. The results obtained were evaluated by means of statistical analyses able to detect significant interactions of biological determinants connected with tumor relapse. This showed that correlated p53, Bcl-2 and cathepsin D specifically associate with unprecedented high levels of relative risk for local invasion and metastatic relapse. As matrix metalloproteases, which play a key role in local invasion and distant cancer spreading, were shown to be a transactivation target for mutant p53, in cooperation with oncogenic Ras, exon sequence analysis was performed for TP53 and RAS genes, and findings were coordinately analyzed with the immunohistochemistry (IHC) data and clinical phenotypes. Methods Breast cancer case series A multi-institutional case series of BC patients was collected from the National Cancer Instit (...truncated)