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Label-free biomedical imaging represents a range of powerful technologies used to visualize natural sources of biological contrast. Label-free techniques such as autofluorescence and fluorescence lifetime imaging measure contrast produced by various cellular products and provide high sensitivity for detecting tissue changes that occur with disease onset. However, a major limitation of these modalities, and many label-free modalities broadly, is the lack of robust validation methods that confirm signal specificity. Moreover, existing approaches are limited to assessing correlations and fail to provide mechanistic information into pathological events. Spatially resolved gene sequencing methods (e.g., spatial transcriptomics) are a powerful tool to gain detailed biological insight into tissue properties by creating 2-D maps of variations in gene expression that influence tissue properties. Thus, these techniques represent an avenue for validation of label-free imaging markers through the examination of how label-free image features correspond to gene expression. Toward this aim, we performed autofluorescence and fluorescence lifetime imaging on tissue specimens from four patients presenting with pancreatic neuroendocrine tumors. We then performed spatial transcriptome sequencing on serial tissue sections to measure transcriptome-wide signatures. We assessed imaging biomarkers related to cellular metabolism, vasculature, and extracellular matrix properties. After registering the label-free images to the transcriptomic signatures, we performed k-means clustering, and assessed the correlation between imaging markers and differentially expressed genes associated with tissue properties of interest. Specifically, we aimed to examine correlations between gene expression and established optical biomarkers (e.g., optical redox ratio), along with identifying other potential connections between label-free optics and cellular genetics. The results show that spatial transcriptomics can be used as an effective validation tool for label-free imaging markers, while simultaneously providing additional biological insight to improve the specificity of imaging studies.
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