Researchers use multiplexed 3D imaging to perform molecular and morphological assessments of colorectal cancers CellPressNews harvardmed ColorectalCancer ColorectalTumor Tumor 3DImaging
By Pooja Toshniwal PahariaJan 24 2023Reviewed by Aimee Molineux In a recent study published in Cell, researchers used multiplexed and three-dimensional imaging with machine-based learning and spatial statistics to perform molecular and morphological assessments of colorectal cancers .
The images were segmented, and their fluorescence intensities were quantified for generating data at a singular-cell level on cellular type, state, and cell-cell interactions. Three-dimensional reconstructions of serial tissue sections were prepared and supervised by machine learning. Two approaches were used for analyzing tumor cells, i.e., a ‘bottoms-up’ approach and a ‘top-down’ approach.
Results Multiplexed analysis showed intermixed tumor morphologies and molecular gradients. Various cancer-characteristic cellular features were observed as large, interconnected structures. Three-dimensional TLS networks showed intra-TLS patterning variations. PD1 -PDL1 interactions were observed primarily between T lymphocytes and myeloid cells in the colorectal cancer cohort.
Immunological cells observed within the tumor comprised CD8+ and programmed cell death protein 1-expressing cytotoxic-type T lymphocytes, CD4-expressing helper-type T lymphocytes, CD68-expressing and/or CD163-expressing macrophages, and CD20-expressing B lymphocytes. In addition, subcategories like CD4+ FOXP3+ Tregs were observed.
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