Research Focus: Single Cell Genomics characterization and analytics of large datasets from therapeutic cellular products using advanced bioinformatics tools

Osteoarthritis (OA) is the most common form of arthritis, affecting 32.5 million US adults and contributes to more than 27B in health care cost. CDC projects this number to reach 78 million by 2040. Knee OA carries 85% of this OA burden and Over 50% of people need knee replacement in their lifetime. Pain- both chronic and episodic results in poor quality of life. Pain in OA is likely the result of a complex interplay of factors including mechanical, inflammatory, systemic senescence and centralized pain pathways. Our work focusses on characterization of BMAC (Bone Marrow Aspirate Concentrate), SVF (Stromal Vascular Fraction) cells and UCT-MSCs which are currently potential therapeutic products for kneeOA with Single cell transcriptome analysis. Our datasets are from MILES (ClinicalTrials.gov Identifier: NCT03818737) clinical trial OA patients.
We generate these ScRNAseq datasets using 10x Genomics Chromium and Connect platforms and they are sequenced on Illumina Novaseq platform. This study is designed to understand the pathogenesis and progression of kneeOA disease compared to healthy population as well as how the transcriptomics data correlates to the variables like sex, age, and disease progression scores. In this process we hope to find biomarkers unique to diagnose and target for therapeutics of knee Osteoarthritis. For the data analysis process, we use different interfaces like R, Linux, Python and different software and statistical tools.
We hope this study will provide target cell types, genes and pathways that can be modulated to predict disease progression and help design therapies to control the pain and inflammation. Furthermore, this study will provide a robust reference database for the systemic inflammatory omics profile for future OA therapeutic research.

Relevant Publications:

• Medrano-Trochez, C., Chatterjee, P., Pradhan, P. et al. Single-cell RNA-seq of out-of-thaw mesenchymal stromal cells shows tissue-of-origin differences and inter-donor cell-cycle variations. Stem Cell Res Ther 12, 565 (2021) | https://doi.org/10.1186/s13287-021-02627-9
• Pallab Pradhan, Paramita Chatterjee, Hazel Y. Stevens, Chad Glen, Camila Medrano Trochez, Angela Jimenez, Linda Kippner, Wen Jun Seeto, Greg Gibson, Joanne Kutzberg, Theresa Kontanchek, Carolyn Yeago, Krishnendu Roy, Single-Cell Transcriptomic Attributes and Unbiased Computational Modeling for the Prediction of Immunomodulatory Potency of Mesenchymal Stromal Cells, bioRxiv 2020.09.12.294850; doi: https://doi.org/10.1101/2020.09.12.294850