Single-cell Multiomics Powers Biomarker Insights into AML

Myeloid diseases such as AML are highly diverse, with genetic and immunophenotypic changes driving clonal evolution, making response and relapse difficult to predict. Single-cell multiomics helps address this complexity, offering deeper insights into disease progression and treatment response to guide more informed therapeutic decisions.

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What if you could follow the evolution of AML to uncover biomarker insights?

The complexity of leukemia clonal architecture and the genotypic and immunophenotypic drifts during treatment explain why more than half of patients in remission could relapse. Using single-cell multiomics approaches, researchers can uncover the clonal and subclonal drivers of therapy resistance and relapse, and more precisely characterize patient tumor heterogeneity and evolution.

Key Benefits

Early delineation of subclones driving myeloid progression, therapy resistance, and relapse.

Single-cell characterization of SNVs, indels, CNVs, zygosity, and surface protein expression to unravel clonal heterogeneity.

More cost-effective and easier than combining bulk NGS and Flow, with sample multiplexing and automated data integration.

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Primary Applications

Clonal Heterogeneity

Disease characterization
Mutation acquisition
Clonal architecture and evolution from precursor to disease state

Therapy Resistance

Understand mechanisms of resistance
Differentiate non/responders
Identify and detect rare relapse clones

Disease Monitoring

Sensitive and specific measure of residual disease
Identify gene/surface protein targets for future therapeutic interventions

Tapestri Single-cell Myeloid Multiomics Solution

Get everything you need to conduct single-cell multiomics analysis of AML and other myeloid neoplasms in your lab with this fully-supported, all-in-one package.