Deep-Context Tissue Analytics for Integrated Pathology Modeling in Tumors and Kidney Allografts
Personalized medicine increasingly relies on tissue pathology-based evaluation of prognostic and predictive biomarkers. Multiplex tissue biomarker assays, enabling identification of biological signals and their cellular sources in the deep context of tissue microenvironment become a critical chain in adoption of new generaon of immunity-modulating therapies for cancer and organ transplant management. Robust and affordable contextual tissue biomarker multiplexing has not been achieved.
Recent advance in molecular testing, high-resolution whole slide imaging in pathology, digital image analytics, and machine learning converge into new opportunities for tissue-based discovery and testing. Despite promising research ongoing, the disruptive technologies remain to be streamlined and translated into solutions implementable in clinical research and practice.
The aim of the proposed study is to develop novel tissue-based analytical assays for integrative modelling of kidney allograft and tumor pathology. It will employ novel imaging techniques of polychromatic polarization and ultraviolet sectioning excitation microscopy, combining their unique features for discovery of distinctive digital signatures of tissue components and pathology features. Biomarker measurements within this deep tissue context are expected to generate robust, integrated tissue-based pathology indicators. Multidimensional analysis along with machine learning and artificial intelligence will be used for feature extraction and tissue-based modeling of disease process.
The proposed project will engage an international team of researchers with unique sets of novel imaging and analytical technologies and expertise. The research will focus primarily on cancer and kidney allograft pathology to develop high dimensional and affordable tissue analytics; however, the advances in knowledge and technology will impact many areas of precision medicine with high-cost patient management.
The Aim of the study is to develop novel tissue-based analytical assays for integrated modelling of tumor and kidney allograft pathology
Objective 1. Explore tissue processing/data extraction approaches to discover unique digital signatures of tissue components and integrated pathology indicators.
Objective 2. Design and validate the “deep-context” tissue assays for selected analytical and clinical tasks to enable robust and affordable multidimensional modeling of tissue pathology.
Project start date: 2018-01-08
Project end date: 2021-10-07
Project team: prof. dr. A. Laurinavičius, Dr. A. Laurinavičienė, Dr. A. Rasmusson, Dr. B. Plancoulaine, Dr. R. Levenson, Dr. M. Shribak, Dr. KY. Jen.
Funding: funded by European Social Fund (2014-2020) under the measure No 09.3.3-LMT-K-712 „Strengthening the Skills and Capacities of Public Sector Researchers for Engaging in High Level R&D Activities“ activity „Strengthening of General Skills and Competences of Researchers Through Implementation of High Level R&D Projects“