Alberto Zambelli

Targeting triple negative breast cancer: Is p53 the answer?

Triple negative breast cancers, which are defined by lack of expression of estrogen, progesterone, or HER2 receptors, represent approximately 15% of all breast cancers, although they account for a much higher proportional of breast cancer mortality. This is due both to their innate aggressive biological characteristics, but also to lack of effective therapies. Conventional chemotherapy is currently the only treatment option, thus there is a critical need to find new and effective targeted therapies in this disease. While investigation of agents such as poly (ADP-ribose) polymerase (PARP) inhibitors and EGFR inhibitors continues, results from recent clinical trials indicate that these therapies are not as active in sporadic triple negative breast cancers as initially hoped. It is important therefore to consider other emerging therapeutic agents. Mutation in p53 is found in the vast majority of triple negative breast cancers, and as such is a target of particular interest. Within this review, several agents with potential activity against aberrant p53 signaling have been considered, as a novel approach to finding an effective targeted therapy for this aggressive breast cancer subtype.

Retinoids and breast cancer: From basic studies to the clinic and back again

All-trans retinoic acid (ATRA) is the most important active metabolite of vitamin A controlling segmentation in the developing organism and the homeostasis of various tissues in the adult. ATRA as well as natural and synthetic derivatives, collectively known as retinoids, are also promising agents in the treatment and chemoprevention of different types of neoplasia including breast cancer. The major aim of the present article is to review the basic knowledge acquired on the anti-tumor activity of classic retinoids, like ATRA, in mammary tumors, focusing on the underlying cellular and molecular mechanisms and the determinants of retinoid sensitivity/resistance. In the first part, an analysis of the large number of pre-clinical studies available is provided, stressing the point that this has resulted in a limited number of clinical trials. This is followed by an overview of the knowledge acquired on the role played by the retinoid nuclear receptors in the anti-tumor responses triggered by retinoids. The body of the article emphasizes the potential of ATRA and derivatives in modulating and in being influenced by some of the most relevant cellular pathways involved in the growth and progression of breast cancer. We review the studies centering on the cross-talk between retinoids and some of the growth-factor pathways which control the homeostasis of the mammary tumor cell. In addition, we consider the cross-talk with relevant intra-cellular second messenger pathways. The information provided lays the foundation for the development of rational and retinoid-based therapeutic strategies to be used for the management of breast cancer.

Cellular and molecular determinants of all-trans retinoic acid sensitivity in breast cancer: Luminal phenotype and RARα expression

Forty‐two cell lines recapitulating mammary carcinoma heterogeneity were profiled for all‐trans retinoic acid (ATRA) sensitivity. Luminal and ER+ (estrogen‐receptor‐positive) cell lines are generally sensitive to ATRA, while refractoriness/low sensitivity is associated with a Basal phenotype and HER2 positivity. Indeed, only 2 Basal cell lines (MDA‐MB157 and HCC‐1599) are highly sensitive to the retinoid. Sensitivity of HCC‐1599 cells is confirmed in xenotransplanted mice. Short‐term tissue‐slice cultures of surgical samples validate the cell‐line results and support the concept that a high proportion of Luminal/ER+ carcinomas are ATRA sensitive, while triple‐negative (Basal) and HER2‐positive tumors tend to be retinoid resistant. Pathway‐oriented analysis of the constitutive gene‐expression profiles in the cell lines identifies RARα as the member of the retinoid pathway directly associated with a Luminal phenotype, estrogen positivity and ATRA sensitivity. RARα3 is the major transcript in ATRA‐sensitive cells and tumors. Studies in selected cell lines with agonists/antagonists confirm that RARα is the principal mediator of ATRA responsiveness. RARα over‐expression sensitizes retinoid‐resistant MDA‐MB453 cells to ATRA anti‐proliferative action. Conversely, silencing of RARα in retinoid‐sensitive SKBR3 cells abrogates ATRA responsiveness. All this is paralleled by similar effects on ATRA‐dependent inhibition of cell motility, indicating that RARα may mediate also ATRA anti‐metastatic effects. We define gene sets of predictive potential which are associated with ATRA sensitivity in breast cancer cell lines and validate them in short‐term tissue cultures of Luminal/ER+ and triple‐negative tumors. In these last models, we determine the perturbations in the transcriptomic profiles afforded by ATRA. The study provides fundamental information for the development of retinoid‐based therapeutic strategies aimed at the stratified treatment of breast cancer subtypes.

Effectiveness of Trastuzumab in First-Line HER2+ Metastatic Breast Cancer After Failure in Adjuvant Setting: A Controlled Cohort Study

BACKGROUND The evidence supporting the use of trastuzumab (T) in a metastatic setting comes from studies that included (almost) only patients who never received prior T. We investigated the effectiveness of T as first-line therapy for metastatic breast cancer (mBC) in women previously treated with T in the adjuvant setting. MATERIALS AND METHODS By using record linkage of five administrative health care databases of Lombardy, Italy, we identified 2,046 women treated with T for early breast cancer (eBC) in 2006-2009, 96 of whom developed a metastasis and were retreated with T in first-line treatment for mBC (treatment group). We compared the overall survival (OS) of these women with that of 197 women treated with T in first-line treatment for mBC, who were treated with therapies other than T for early disease (control group). We computed Kaplan-Meier 2-year OS and used a proportional hazard model to estimate the multivariate hazard ratio (HR) of death in the intervention group compared with the control group, adjusted by age, use of endocrine therapy, and site of metastasis. RESULTS Two-year OS was 60.0% in the treatment group and 59.5% in the control group. The adjusted HR of death in the treatment group compared with the control group was 0.79 (95% confidence interval, 0.50-1.26). CONCLUSION Our data provide convincing evidence that the outcome of women receiving first-line T treatment for mBC after T failure in the adjuvant setting is comparable to that of women not receiving T for eBC. These data are of specific interest, given the unavailability of data from randomized clinical trials.

An ICT infrastructure to integrate clinical and molecular data in oncology research

BackgroundThe ONCO-i2b2 platform is a bioinformatics tool designed to integrate clinical and research data and support translational research in oncology. It is implemented by the University of Pavia and the IRCCS Fondazione Maugeri hospital (FSM), and grounded on the software developed by the Informatics for Integrating Biology and the Bedside (i2b2) research center. I2b2 has delivered an open source suite based on a data warehouse, which is efficiently interrogated to find sets of interesting patients through a query tool interface.MethodsOnco-i2b2 integrates data coming from multiple sources and allows the users to jointly query them. I2b2 data are then stored in a data warehouse, where facts are hierarchically structured as ontologies. Onco-i2b2 gathers data from the FSM pathology unit (PU) database and from the hospital biobank and merges them with the clinical information from the hospital information system.Our main effort was to provide a robust integrated research environment, giving a particular emphasis to the integration process and facing different challenges, consecutively listed: biospecimen samples privacy and anonymization; synchronization of the biobank database with the i2b2 data warehouse through a series of Extract, Transform, Load (ETL) operations; development and integration of a Natural Language Processing (NLP) module, to retrieve coded information, such as SNOMED terms and malignant tumors (TNM) classifications, and clinical tests results from unstructured medical records. Furthermore, we have developed an internal SNOMED ontology rested on the NCBO BioPortal web services.ResultsOnco-i2b2 manages data of more than 6,500 patients with breast cancer diagnosis collected between 2001 and 2011 (over 390 of them have at least one biological sample in the cancer biobank), more than 47,000 visits and 96,000 observations over 960 medical concepts.ConclusionsOnco-i2b2 is a concrete example of how integrated Information and Communication Technology architecture can be implemented to support translational research. The next steps of our project will involve the extension of its capabilities by implementing new plug-in devoted to bioinformatics data analysis as well as a temporal query module.

The ONCO-I2b2 project: integrating biobank information and clinical data to support translational research in oncology.

The University of Pavia and the IRCCS Fondazione Salvatore Maugeri of Pavia (FSM), has recently started an IT initiative to support clinical research in oncology, called ONCO-i2b2. ONCO-i2b2, funded by the Lombardia region, grounds on the software developed by the Informatics for Integrating Biology and the Bedside (i2b2) NIH project. Using i2b2 and new software modules purposely designed, data coming from multiple sources are integrated and jointly queried. The core of the integration process stands in retrieving and merging data from the biobank management software and from the FSM hospital information system. The integration process is based on a ontology of the problem domain and on open-source software integration modules. A Natural Language Processing module has been implemented, too. This module automatically extracts clinical information of oncology patients from unstructured medical records. The system currently manages more than two thousands patients and will be further implemented and improved in the next two years.

Temporal electronic phenotyping by mining careflows of breast cancer patients

In this work we present a careflow mining approach designed to analyze heterogeneous longitudinal data and to identify phenotypes in a patient cohort. The main idea underlying our approach is to combine methods derived from sequential pattern mining and temporal data mining to derive frequent healthcare histories (careflows) in a population of patients. This approach was applied to an integrated data repository containing clinical and administrative data of more than 4000 breast cancer patients. We used the mined histories to identify sub-cohorts of patients grouped according to healthcare activities pathways, then we characterized these sub-cohorts with clinical data. In this way, we were able to perform temporal electronic phenotyping of electronic health records (EHR) data.

A network-based data integration approach to support drug repurposing and multi-Target therapies in triple negative breast cancer

The integration of data and knowledge from heterogeneous sources can be a key success factor in drug design, drug repurposing and multi-target therapies. In this context, biological networks provide a useful instrument to highlight the relationships and to model the phenomena underlying therapeutic action in cancer. In our work, we applied network-based modeling within a novel bioinformatics pipeline to identify promising multi-target drugs. Given a certain tumor type/subtype, we derive a disease-specific Protein-Protein Interaction (PPI) network by combining different data-bases and knowledge repositories. Next, the application of suitable graph-based algorithms allows selecting a set of potentially interesting combinations of drug targets. A list of drug candidates is then extracted by applying a recent data fusion approach based on matrix tri-factorization. Available knowledge about selected drugs mechanisms of action is finally exploited to identify the most promising candidates for planning in vitro studies. We applied this approach to the case of Triple Negative Breast Cancer (TNBC), a subtype of breast cancer whose biology is poorly understood and that lacks of specific molecular targets. Our “in-silico” findings have been confirmed by a number of in vitro experiments, whose results demonstrated the ability of the method to select candidates for drug repurposing.

Trabectedin for the treatment of breast cancer

Introduction: Trabectedin is an anti-tumor compound registered in Europe and in several other countries, for the second-line treatment of soft tissue sarcoma (STS) and for ovarian cancer in combination with liposomal doxorubicin. Trabectedin inhibits cancer cell proliferation mainly affecting the transcription regulation. Trabectedin also acts as a modulator of tumor microenvironment by reducing the number of tumor associated macrophages (TAM). Because of its unique mechanism of action, trabectedin has the potential to act as antineoplastic agent also in several solid malignancies, including breast cancer (BC). Areas covered: This article reviews the preclinical and clinical data of trabectedin focusing on development in metastatic BC (mBC). Comments regarding the nature and the results of these trials are included. Expert opinion: Trabectedin is thought to have a crucial activity with defective DNA-repair machinery and also in modulating the tumor micro-environment and the immune-system of cancer patients. From the current available data, we recognize a potential activity of trabectedin in mBC and support the renewed efforts to better elucidate the value of trabectedin in this indication.

Long term survival of HER2-positive early breast cancer treated with trastuzumab-based adjuvant regimen: A large cohort study from clinical practice

Trastuzumab-based regimens for the adjuvant treatment of HER2-positive early breast cancer significantly prolonged overall survival (OS) and disease free survival (DFS) in large randomized trials, with sustained benefits at four-year follow-up. We assessed long-term survival estimates and predictors in a large cohort of Italian women with early breast cancer treated with trastuzumab in clinical practice. Through a record linkage between five regional healthcare databases, we identified women treated with trastuzumab for early breast cancer in Lombardy (2006-2009). DFS and OS were estimated using the Kaplan-Meier method, and independent predictors were assessed using proportional hazard models. 2046 women received trastuzumab in early breast cancer adjuvant setting. Overall, the proportion of patients surviving free of disease was 93.9% at one year, 85.8% at 2 years, 79.4% at 3 years, and 75.0% at 4 years. OS estimates were 98.7%, 95.4%, 91.5% and 89.4% at 1, 2, 3 and 4 years, respectively. Significant independent predictors of worse survival outcomes were age <40 or ≥70 years compared to age 40-69 years, positive nodal status, radical breast surgery, combination therapy with paclitaxel, having at least one comorbidity (i.e. diabetes, cardiovascular disease), and a trastuzumab-based regimen lasting less than six months. Long term survival rates of women treated with trastuzumab for early breast cancer in clinical practice were consistent with estimates from clinical trials testing the drug in the adjuvant setting.