Journal article
Alice Yu, Yuanyuan Li, Irene Li, M. Ozawa, Christine Yeh, Aaron E. Chiou, Winston L Trope, Jonathan Taylor, J. Shrager, S. Plevritis
Science advances, 2022
Science advances, 2022
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DOI
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APA
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Yu, A., Li, Y., Li, I., Ozawa, M., Yeh, C., Chiou, A. E., … Plevritis, S. (2022). Reconstructing codependent cellular cross-talk in lung adenocarcinoma using REMI. Science Advances.
Chicago/Turabian
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Yu, Alice, Yuanyuan Li, Irene Li, M. Ozawa, Christine Yeh, Aaron E. Chiou, Winston L Trope, Jonathan Taylor, J. Shrager, and S. Plevritis. “Reconstructing Codependent Cellular Cross-Talk in Lung Adenocarcinoma Using REMI.” Science advances (2022).
MLA
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Yu, Alice, et al. “Reconstructing Codependent Cellular Cross-Talk in Lung Adenocarcinoma Using REMI.” Science Advances, 2022.
BibTeX Click to copy
@article{alice2022a,
title = {Reconstructing codependent cellular cross-talk in lung adenocarcinoma using REMI},
year = {2022},
journal = {Science advances},
author = {Yu, Alice and Li, Yuanyuan and Li, Irene and Ozawa, M. and Yeh, Christine and Chiou, Aaron E. and Trope, Winston L and Taylor, Jonathan and Shrager, J. and Plevritis, S.}
}
Abstract
Cellular cross-talk in tissue microenvironments is fundamental to normal and pathological biological processes. Global assessment of cell-cell interactions (CCIs) is not yet technically feasible, but computational efforts to reconstruct these interactions have been proposed. Current computational approaches that identify CCI often make the simplifying assumption that pairwise interactions are independent of one another, which can lead to reduced accuracy. We present REMI (REgularized Microenvironment Interactome), a graph-based algorithm that predicts ligand-receptor (LR) interactions by accounting for LR dependencies on high-dimensional, small–sample size datasets. We apply REMI to reconstruct the human lung adenocarcinoma (LUAD) interactome from a bulk flow-sorted RNA sequencing dataset, then leverage single-cell transcriptomics data to increase the cell type resolution and identify LR prognostic signatures among tumor-stroma-immune subpopulations. We experimentally confirmed colocalization of CTGF:LRP6 among malignant cell subtypes as an interaction predicted to be associated with LUAD progression. Our work presents a computational approach to reconstruct interactomes and identify clinically relevant CCIs.
