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Patrícia Fraga

Bio: Patrícia Fraga is an academic researcher from Instituto de Medicina Molecular. The author has contributed to research in topics: Cancer & Cell. The author has co-authored 1 publications.

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TL;DR: In this article, the authors explored the development and characterization of three-dimensional (3D) models, named spheroids, of the most aggressive breast cancer subtypes (triple negative breast cancer-TNBC; and human-epidermal growth receptor-2-HER2+), using the liquid overlay technique with several selected cell lines.
Abstract: Breast cancer (BC) is the most commonly diagnosed cancer in women and one of the most common causes of cancer-related deaths. Despite intense research efforts, BC treatment still remains challenging. Improved drug development strategies are needed for impactful benefit to patients. Current preclinical studies rely mostly on cell-based screenings, using two-dimensional (2D) cell monolayers that do not mimic in vivo tumors properly. Herein, we explored the development and characterization of three-dimensional (3D) models, named spheroids, of the most aggressive BC subtypes (triple-negative breast cancer-TNBC; and human-epidermal growth receptor-2-HER2+), using the liquid overlay technique with several selected cell lines. In these cell line-derived spheroids, we studied cell density, proliferation, ultrastructure, apoptosis, reactive oxygen species (ROS) production, and cell permeabilization (live/dead). The results showed a formation of compact and homogeneous spheroids on day 7 after seeding 2000 cells/well for MDA-MB-231 and 5000 cells/well for BT-20 and BT-474. Next, we compared the efficacy of a model anticancer peptide (ACP) in cell monolayers and spheroids. Overall, the results demonstrated spheroids to be less sensitive to treatment than cell monolayers, revealing the need for more robust models in drug development.

5 citations


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TL;DR: In this article , a review of 3D in vitro cancer models for the efficacy evaluation of anticancer agents is presented, focusing on their potential contribution to replace, reduce and refine animal experimentations, highlighting their strength and weakness, and discussing possible perspectives to overcome current challenges.
Abstract: In the last decades three-dimensional (3D) in vitro cancer models have been proposed as a bridge between bidimensional (2D) cell cultures and in vivo animal models, the gold standards in the preclinical assessment of anticancer drug efficacy. 3D in vitro cancer models can be generated through a multitude of techniques, from both immortalized cancer cell lines and primary patient-derived tumor tissue. Among them, spheroids and organoids represent the most versatile and promising models, as they faithfully recapitulate the complexity and heterogeneity of human cancers. Although their recent applications include drug screening programs and personalized medicine, 3D in vitro cancer models have not yet been established as preclinical tools for studying anticancer drug efficacy and supporting preclinical-to-clinical translation, which remains mainly based on animal experimentation. In this review, we describe the state-of-the-art of 3D in vitro cancer models for the efficacy evaluation of anticancer agents, focusing on their potential contribution to replace, reduce and refine animal experimentations, highlighting their strength and weakness, and discussing possible perspectives to overcome current challenges.

3 citations

Journal ArticleDOI
TL;DR: This review attempts to summarize the most common 3D in vitro models used in breast cancer studies, including scaffold-free (spheroid and organoid), scaffolding-based, and chip-based models, particularly focused on the basic and translational application of these 3D models in drug screening and the tumor microenvironment in Breast cancer.
Abstract: Common models used in breast cancer studies, including two-dimensional (2D) cultures and animal models, do not precisely model all aspects of breast tumors. These models do not well simulate the cell-cell and cell-stromal interactions required for normal tumor growth in the body and lake tumor like microenvironment. Three-dimensional (3D) cell culture models are novel approaches to studying breast cancer. They do not have the restrictions of these conventional models and are able to recapitulate the structural architecture, complexity, and specific function of breast tumors and provide similar in vivo responses to therapeutic regimens. These models can be a link between former traditional 2D culture and in vivo models and are necessary for further studies in cancer. This review attempts to summarize the most common 3D in vitro models used in breast cancer studies, including scaffold-free (spheroid and organoid), scaffold-based, and chip-based models, particularly focused on the basic and translational application of these 3D models in drug screening and the tumor microenvironment in breast cancer.

3 citations

Journal ArticleDOI
TL;DR: In this paper , the potential of methoxy trityl groups, monomethoxy triityl (MMT), dimethoxy triethyltyll (DMT), and trimethoxy trithl (TMT) as acid-responsive substituents for designing anti-cancer cytidine analog prodrugs was investigated.

1 citations

Journal ArticleDOI
27 Apr 2023-Cancers
TL;DR: A comprehensive overview of the currently available 3D (3D) models of cervical cancer and their significance in pre-clinical and clinical studies is provided in this paper , where the authors emphasize the potential of 3D tumor models, such as spheroids from cervical cancer cell lines and patient-derived organoids, to evaluate novel therapies, particularly immunotherapies that target tumor cells and modulate the tumor microenvironment.
Abstract: Simple Summary Appropriate testing models are imperative to facilitate the discovery of effective personalized treatments against different cancers, including advanced cervical cancer. This review provides a comprehensive overview of the currently available three-dimensional (3D) models of cervical cancer and their significance in pre-clinical and clinical studies. The review emphasizes the potential of 3D tumor models, such as spheroids from cervical cancer cell lines and patient-derived organoids, to evaluate novel therapies, particularly immunotherapies that target tumor cells and modulate the tumor microenvironment. Notably, the cervical cancer field is underdeveloped regarding use of 3D tumor models, and there is an increasing need to develop appropriate models to address this clinical burden, which will aid in personalized treatment discovery. Abstract Cervical cancer is one of the most common malignant diseases in women worldwide. Despite the global introduction of a preventive vaccine against the leading cause of cervical cancer, human papillomavirus (HPV) infection, the incidence of this malignant disease is still very high, especially in economically challenged areas. New advances in cancer therapy, especially the rapid development and application of different immunotherapy strategies, have shown promising pre-clinical and clinical results. However, mortality from advanced stages of cervical cancer remains a significant concern. Precise and thorough evaluation of potential novel anti-cancer therapies in pre-clinical phases is indispensable for efficient development of new, more successful treatment options for cancer patients. Recently, 3D tumor models have become the gold standard in pre-clinical cancer research due to their capacity to better mimic the architecture and microenvironment of tumor tissue as compared to standard two-dimensional (2D) cell cultures. This review will focus on the application of spheroids and patient-derived organoids (PDOs) as tumor models to develop novel therapies against cervical cancer, with an emphasis on the immunotherapies that specifically target cancer cells and modulate the tumor microenvironment (TME).
Journal ArticleDOI
TL;DR: Using the van Deemter model, the efficiency of three stationary phase systems in the analysis of a mixture of synthetic peptides was evaluated: (i) monolithic, (ii) packed, and (iii) core-shell columns, and it was shown that the monolithic column is superior to the others, specifically using it, and additionally its efficiency was not significantly affected by increasing the flow as discussed by the authors .
Abstract: Using the van Deemter model, the efficiency of three stationary phase systems in the analysis of a mixture of synthetic peptides was evaluated: (i) monolithic, (ii) packed, and (iii) core–shell columns, and it was shown that the efficiency of the monolithic column is superior to the others, specifically using it, the lowest values of Hmin (0.03 and 0.1 mm) were obtained, and additionally its efficiency was not significantly affected by increasing the flow. Using the concept of the gradient retention factor (k*), a method for chromatographic separation of a peptide complex mixture was designed, implemented, and optimized and then transferred from a packed column to a monolithic one. The results showed that it was possible to separate all components of the mixture using both evaluated columns; moreover, the analysis time was reduced from 70 to 10 min, conserving the critical pair resolution (1.4), by the transfer method using the k* concept. The method developed was tested against a mixture of doping peptides, showing that this method is efficient for separating peptides of various natures. This investigation is very useful for the development of methods for the analysis of complex peptide mixtures since it provides a systematic approach that can be extrapolated to different types of columns and instrumentation.