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Summary Cellular immunotherapies are rapidly gaining clinical importance, yet predictive platforms for modeling their mode of action are lacking. Here, we developed a dynamic immuno-organoid 3D imaging-transcriptomics platform; BEHAV3D, to unravel the behavioral and underlying molecular mechanisms of solid tumor targeting. Applied to an emerging cancer metabolome-sensing immunotherapy: TEGs, we first demonstrate targeting of multiple breast cancer subtypes. Live-tracking of over 120,000 TEGs revealed a diverse behavioral landscape and identified a ‘super engager’ cluster with serial killing capability. Inference of single-cell behavior with transcriptomics identified the gene signature of ‘super engager’ killer TEGs, which contained 27 genes with no previously described T cell function. Furthermore, guided by a dynamic type 1 interferon (IFN-I) signaling module induced by high TEG-sensitive organoids, we show that IFN-I can prime resistant organoids for TEG-mediated killing. Thus, BEHAV3D characterizes behavioral-phenotypic heterogeneity of cellular immunotherapies and holds promise for improving solid tumor-targeting in a patient-specific manner.
<p>PDF file - 131KB, Wnt target genes and probesets (S1). ER target genes and probesets (S2). Used datasets (S3). Variation in predicted probability of pathway activity between and within cell lines, assessed on dataset E-MTAB-37 (S4). Gene set enrichment analysis results on normal colon samples versus colon adenoma from GSE8671 (S5).</p>
List of DRA (http://trace.ddbj.nig.ac.jp/dra/index_e.html) accession numbers of the FANTOM5 samples, sequences and genomic coordinations. Files are in tab-delimited format, which includes * Library ID * FFID * BioSamples accession number * DRA experiment accession number * DRA run accession numbers * DRA analysis accession number for genomic coordination (BAM file) * DRA analysis accession number for CTSS (BED file) * Experiment method (CAGE/RNA-Seq/sRNA-Seq)