Poster

Powerful insights with single-cell multi-omics: Co-detecting both genotype and phenotype from the same cell
Modern medicine has given rise to an array of treatment options for diseases, such as acute myeloid leukemia (AML). Cancer is a heterogeneous mixture of cells with varied states, and the best treatment options for an individual patient requires an understanding of the disease state at the cellular level. A single-cell multi-omics approach is the only way to achieve full resolution of the disease at the cellular level, revealing the interplay between genotype and phenotype. The Tapestri Platform enables comprehensive identification of cell subpopulations through single-cell multi-omics profiling. The platform discerned single nucleotide variants (SNVs), copy number variations (CNVs), and cell surface protein expression in single cells from a mixture of AML cell lines and an AML research sample. The results demonstrate that subpopulations are not consistently defined by one genetic or phenotypic factor alone, but by multiple parameters and are irretrievable by bulk sequencing methods. The multi-omics data generated by the Tapestri Platform is consistent with gold-standard techniques currently used for traditional omics analysis of AML samples.
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Single-cell multiomic clonal tracking in myeloma identifies SMM clones that progress to MM and low frequency MM clones with resistance features enabling more precise application of targeted therapies
Adam Sciambi
EHA (2024)

Single-Cell MRD Assessment in AML Reveals Clonal Diversity and Genotype–Phenotype Discordance Missed by Bulk Methods
Adam Sciambi, Daniel Mendoza, Kathryn Thompson, Lan W. Beppu, Benjamin Geller, Indira Krishnan, Lubna Nousheen, Shu Wang, Charlie Murphy, Jerald P. Radich, and Todd E. Druley
(2025)

Comprehensive On-and Off-target Confirmation Using Integrated rhAmpSeq and Targeted DNA Sequencing Single-Cell Technology
Indira Krishnan, Shu Wang, Saurabh Gulati
ASGCT 2025 (2025)

High Throughput Single-cell Assessment of Genome Integrity and Toxicity Events Associated With Edited Cells
Chieh-Yuan (Alex) Li; Saurabh Parikh; Saurabh Gulati; Donjo Ban; Nechama Kalter; Michael Rosenburg; Qawer Ayaz; Joanne Nguyen; Benjamin Miltz; Yang Li1; Madhumita Shrikhande; Edward Szekeres; Ayal Hendel; Benjamin Schroeder; Shu Wang
ESGCT 2024 (2024)