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A Multivariate Cell-Based Liquid Biopsy for Lung Nodule Risk Stratification: Analytical Validation and Early Clinical Evaluation

ABSTRACT: A Multivariate Cell-Based Liquid Biopsy for Lung Nodule Risk Stratification: Analytical Validation and Early Clinical Evaluation

PROVIDER: PRJNA1152596 | ENA |

REPOSITORIES: ENA

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Project description:(ACUP Abstract) Evaluating the effect of negative pressure therapy on wound healing. The current study will physically and systematically characterize the wound site through the healing process, and provide valuable new information on how bacteria interacts with Granufoam, Surgicel, Owen's Rayon, Fibrin Glue, and the wound site during the healing process, and may lead to the development of new materials and dressings to be used for wound healing applications. (Manuscript Abstract) Wound therapies are capable of modulating the complex molecular signaling profile of tissue regeneration. However traditional, bulk tissue analysis results in nonspecific expressional profiles and diluted signaling that lacks temporal-spatial information. In this study, an acute incisional porcine wound model was developed in the context of negative pressure wound therapy (NPWT). Dressing materials were inserted into wounds with or without NPWT exposure and evaluated over 8-hours. Upon wound explantation, tissue was stratified and dissected into the epidermis, dermis, or subcutaneous layer, or left undissected as a bulk sample and all groups processed for RNAseq. RNAseq of stratified layers provided spatial localization of expressional changes within defined tissue regions, including angiogenesis, inflammation, and matrix remodeling. Different expressional profiles were observed between individual tissue layers relative to each other within a single wound group and between each individual layer relative to bulk analysis. Tissue stratification identified unique differentially expressed genes within specific layers of tissue that were hidden during bulk analysis, as well as amplification of weak signals and/or inversion of signaling between two layers of the same wound, suggesting that two layers of skin can cancel out signaling within bulk analytical approaches. The unique wound stratification and spatial RNAseq approach in this study provides a new methodology to observe expressional patterns more precisely within tissue that may have otherwise not been detectable. Together these experimental data offer novel insight into early expressional patterns and genomic profiles, within and between tissue layers, in wound healing pathways that could potentially help guide clinical decisions and improve wound outcomes.

Dataset Information

A Multivariate Cell-Based Liquid Biopsy for Lung Nodule Risk Stratification: Analytical Validation and Early Clinical Evaluation

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