Oncological Pathology and Bioinformatics
RESEARCH
The research lines of the PO&B group focus on the study of the tumor microenvironment through digital image analysis and mathematical modeling.
The immune response is one of the components of the tumor microenvironment that has been shown to play an important role in the evolution of cancer patients.
Changes in the type and quantity of immune cells in the tumor microenvironment have been linked to differences in disease functionality. Our team has studied these changes by developing new computer-assisted image analysis algorithms capable of providing more precise and reproducible automated quantification of immune biomarkers with immunohistochemical and fluorescence staining.
The PO&B group has been recognized as a URV group since 2016, emerging since 2009 and consolidated since 2014 by the Agency for the Management of University and Research Grants (AGAUR). In addition, its members coordinate the IISPV transversal platform for histological, pathological and digitalization studies.
During all these years, the group has had different projects financed jointly with national collaborators (University Rovira i Virgili [URV] of Tarragona; University of Castilla-La Mancha; Hospital Universitari Puerta del Mar of Cadiz; University of Las Palmas de Gran Canaria) and international (Nalecz Institute of Biocybernetics and Biomedical Engineering in Warsaw, Poland; Université de Caen, France).
The group works with the strategic objective of improving the administration of current cancer treatments and detecting new therapeutic targets in breast cancer and lymphomas in order to reduce the risk of relapse and improve patient survival.
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The group's lines of research are the following:
1
Histological studies
Evaluation of different immune populations to the primary tumor and to GLA using histological staining techniques of immunohistochemistry and hematoxylin-eosin. These stains are performed on slides which are subsequently scanned to obtain digital images that are analyzed using artificial intelligence (AI) algorithms. The stains are performed on biopsies of the same patients where the genetic material has been extracted, so that we can compare the results obtained through histological studies with those obtained from genetic analyses.
2
Genetic analyses
Study of gene expression differences in the immune domain in GLA between different subgroups of patients using gene expression microarrays and RT-qPCR. The genetic material is obtained from biopsies of patients with a minimum of 10 years of follow-up. Subsequently, these differences in the domain of the primary tumor will also be evaluated.
3
Translational research in hematological diseases
Evaluation of diagnostic and treatment protocols. The objective of this line of research is to expand the existing prior knowledge of blood diseases, of new procedures suitable for their diagnosis and, very especially, of new treatments that allow the cure or at least prolong the life of people suffering from a hematological disease, whether neoplastic or not.
4
Artificial intelligence algorithms
Development of image analysis procedures based on machine and deep-learning to quantify, locate and evaluate the spatial distribution of different immune populations using immunohistochemical and hematoxylin-eosin staining. Annotations are being made on the digital images of each of the markers in order to develop the algorithms.
5
Computational modeling
Development of mathematical and artificial intelligence models with three different approaches:
1. Prediction of axillary metastasis at diagnosis using machine learning algorithms, integrating clinicopathological and immune response data.
2. Develop network-based models to analyze the interactions between the different components of the tumor and lymph node microenvironments.
3. Develop an agent-based model built from the spatial representation of the components and interactions defined by the network-based models, with the aim of simulating the migration of tumor cells from the tumor microenvironment to the axillary lymph nodes.
This will allow us to understand the mechanisms underlying axillary metastasis, the role played by immune cells in it, and identify new biomarker candidates.
6
Innovation in TMA
Tissue microarrays (TMAs) allow multiple histological samples to be evaluated on a single slide, thus reducing the number of materials, antibodies and reagents. In this sense, a new solution for the production of TMAs is being developed known as TMAtech Mold, which offers a wide variety of silicone molds available in a faster, more economical and personalized way than any of the existing alternatives, depending on each need, whether for researchers, pathologists or technicians.
