Iacobucci, I. et al. Modeling and targeting of erythroleukemia by hematopoietic genome editing. Blood 137.12, 1628-1640 (2021).
In this paper, researchers at St. Jude Children’s Research Hospital used the ICELL8 Single-Cell System’s SMART-Seq chemistry together with combinatorial genome editing to characterize acute erythroid leukemia (AEL)—a rare, aggressive form of acute myeloid leukemia (AML) associated with poor prognosis, uncertain genetic basis, and controversy surrounding the diagnosis. The group's preclinical models illustrate that combinatorial mutation patterns are associated with drug sensitivity in erythroleukemia, with implications to advance cancer therapeutics.
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Meers, M. P. et al. Multifactorial chromatin regulatory landscapes at single cell resolution. bioRxiv 2021.07.08.451691 (2021).
In this study, researchers at the Fred Hutchinson Cancer Research Center developed the Multiple Target Identification by Tagmentation (MulTI-Tag) method on the ICELL8 Single-Cell System. This multifactorial profiling approach can detect and compare distinct chromatin-associated proteins within the same sample, and is optimized to retain high sensitivity and specificity for multiple chromatin targets within the same cell. The sequencing result obtained by the MulTI-Tag method can be used for comprehensive cell type characterization, as well as the discovery of novel histone associations related to gene regulation development and disease.
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Tirier, S. M. et al. Pheno-seq - linking 3D phenotypes of clonal tumor spheroids to gene expression. bioRxiv 311472 (2018).
For this study, researchers at the German Cancer Research Center (DKFZ) leveraged the ICELL8 Single-Cell System for a high-throughput pheno-seq workflow. The system enabled the automated dispensing and confocal imaging of recovered spheroids in barcoded ICELL8 nanowell chips. The custom-developed workflow illustrates the open nature of the ICELL8 workflow for which modified image analysis and lysis procedures were developed to accommodate pheno-seq analysis. They were able to successfully demonstrate the correlation of morphological characteristics with the transcriptional profiles, noting that profiling single-spheroids increases sensitivity compared to single-cell analysis of tumor cells (identification of key transcripts missed by scRNA-seq).
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