Optimizing therapeutic targets for breast cancer using boolean network models.

Studying gene regulatory networks associated with cancer provides valuable insights for therapeutic purposes, given that cancer is fundamentally a genetic disease. However, as the number of genes in the system increases, the complexity arising from the interconnections between network components grows exponentially. In this study, using Boolean logic to adjust the existing relationships between network components has facilitated simplifying the modeling process, enabling the generation of attractors that represent cell phenotypes based on breast cancer RNA-seq data.

Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid.

In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months.

Data-Driven Modeling of Breast Cancer Tumors Using Boolean Networks.

Cancer is a genomic disease involving various intertwined pathways with complex cross-communication links. Conceptually, this complex interconnected system forms a network, which allows one to model the dynamic behavior of the elements that characterize it to describe the entire system's development in its various evolutionary stages of carcinogenesis. Knowing the activation or inhibition status of the genes that make up the network during its temporal evolution is necessary for the rational intervention on the critical factors for controlling the system's dynamic evolution.

Flow Cytometry Immunophenotyping for Diagnostic Orientation and Classification of Pediatric Cancer Based on the EuroFlow Solid Tumor Orientation Tube (STOT).

Early diagnosis of pediatric cancer is key for adequate patient management and improved outcome. Although multiparameter flow cytometry (MFC) has proven of great utility in the diagnosis and classification of hematologic malignancies, its application to non-hematopoietic pediatric tumors remains limited. Here we designed and prospectively validated a new single eight-color antibody combination-solid tumor orientation tube, STOT-for diagnostic screening of pediatric cancer by MFC.

Tracking the Antibody Immunome in Sporadic Colorectal Cancer by Using Antigen Self-Assembled Protein Arrays.

Sporadic Colorectal Cancer (sCRC) is the third leading cause of cancer death in the Western world, and the sCRC patients presenting with synchronic metastasis have the poorest prognosis. Genetic alterations accumulated in sCRC tumor cells translate into mutated proteins and/or abnormal protein expression levels, which contribute to the development of sCRC. Then, the tumor-associated proteins (TAAs) might induce the production of auto-antibodies (aAb) via humoral immune response.

Age Distribution of Multiple Functionally Relevant Subsets of CD4+ T Cells in Human Blood Using a Standardized and Validated 14-Color EuroFlow Immune Monitoring Tube.

CD4+ T cells comprise multiple functionally distinct cell populations that play a key role in immunity. Despite blood monitoring of CD4+ T-cell subsets is of potential clinical utility, no standardized and validated approaches have been proposed so far. The aim of this study was to design and validate a single 14-color antibody combination for sensitive and reproducible flow cytometry monitoring of CD4+ T-cell populations in human blood to establish normal age-related reference values and evaluate the presence of potentially altered profiles in three distinct disease models-monoclonal B-cell lymphocytosis (MBL), systemic mastocytosis (SM), and common variable immunodeficiency (CVID).

Adverse perinatal outcomes for advanced maternal age: a cross-sectional study of Brazilian births.

Objectives: To investigate the risk of adverse perinatal outcomes in women aged ≥41 years relatively to those aged 21-34.

Methods: Approximately 8.5 million records of singleton births in Brazilian hospitals in the period 2004-2009 were investigated.

Serum tryptase monitoring in indolent systemic mastocytosis: association with disease features and patient outcome.

Background: Serum baseline tryptase (sBT) is a minor diagnostic criterion for systemic mastocytosis (SM) of undetermined prognostic impact. We monitored sBT levels in indolent SM (ISM) patients and investigated its utility for predicting disease behaviour and outcome.

Methods: In total 74 adult ISM patients who were followed for ≥48 months and received no cytoreductive therapy were retrospectively studied.

Harmonization of light scatter and fluorescence flow cytometry profiles obtained after staining peripheral blood leucocytes for cell surface-only versus intracellular antigens with the Fix & Perm reagent.

Staining for intracellular markers with the Fix & Perm reagent is associated with variations in the scatter properties of leucocytes, limiting automated analysis of flow cytometry (FCM) data. Here, we investigated those variables significantly contributing to changes in the light scatter, autofluorescence, and bcl2 staining characteristics of peripheral blood (PB) leucocytes, after fixation with Fix & Perm. Our major aim was to evaluate a new mathematical approach for automated harmonization of FCM data from datafiles corresponding to aliquots of a sample treated with cell-surface-only versus Fix & Perm intracellular staining techniques.

New decision support tool for treatment intensity choice in childhood acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL), the most common cancer in childhood, has its treatment modulated by the risk of relapse. An appropriate estimation of this risk is the most important factor for the definition of treatment strategy. In this paper, we build up a new decision support tool to improve treatment intensity choice in childhood ALL.

A multidimensional classification approach for the automated analysis of flow cytometry data.

We describe an automated multidimensional approach for the analysis of flow cytometry data based on pattern classification. Flow cytometry is a widely used technique both for research and clinical purposes where it has become essential for the diagnosis and follow up of a wide spectrum of diseases, such as HIV-infection and neoplastic disorders. Flow cytometry data sets are composed of quite a large number of observations that can be viewed as elements of a n-dimensional space.