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[New eBook] Choosing a single-cell method starts with one question: what do you need to measure? This field guide sorts the single-cell technology landscape by analyte rather than by supplier. It covers genomic, epigenomic, transcriptomic, proteomic, spatial, and multiomic methods. For each analyte class, it explains what is measured, how it is amplified or captured, and where its main limits are. It pays particular attention to the trade-off between throughput and per-cell completeness that shapes nearly every method. A decision framework then matches common research questions to the method families best suited to answer them, from clonal mutations and chromatin state to immunophenotype and gene editing outcomes. The guide ends with practical adoption considerations, including bioinformatics maturity, sample format, and workflow fit. It also includes a feature reference table comparing 19 method families and 20 primary references from the peer-reviewed literature. Get the guide here 👉 https://lnkd.in/g_TGikPT

Bulk VAF tells you a mutant clone is shrinking. It can’t tell you which cells are going, or whether normal hematopoiesis is coming back. See how single-cell DNA + protein profiling on the Tapestri Platform supported exploratory biomarker analysis in phase 1 trials of a first-in-class mutCALR antibody in ET and MF.

Bulk VAF tells you a mutant clone is shrinking. It can’t tell you which cells are going, or whether normal hematopoiesis is coming back. See how single-cell DNA + protein profiling on the Tapestri Platform supported exploratory biomarker analysis in phase 1 trials of a first-in-class mutCALR antibody in ET and MF.

Rare clones and off-target edits hide in bulk data. This free eBook shows how single-cell resolution catches what averages miss.

[Upcoming Webinar] The tumor microenvironment shapes how cancer cells grow, adapt, and respond to therapy. Yet most laboratory models, such as two-dimensional monolayer cultures, strip away the extracellular matrix and tissue architecture that define tumors in patients. Patient-derived scaffolds, decellularized tumor tissue that retains its native structure and composition, recreate in vivo-like growth conditions when repopulated with tumor cells of interest. In this live webinar, Dr. Anders Ståhlberg will present how his group has applied patient-derived scaffolds in breast cancer, colon cancer, and sarcoma to study the cellular and non-cellular tumor microenvironment. Molecular characterization of scaffolds and repopulated cells revealed cell-to-cell signaling and biological processes that drive tumor development. Single-cell triomics on Mission Bio's Tapestri platform, using a targeted approach, then measured DNA, RNA, and protein within the same cells, linking genotype directly to phenotype. In breast cancer cells grown in monolayers and in scaffolds, with and without chemotherapy, triomics reliably resolved distinct subpopulations across genetic, transcriptional, and protein biomarkers. Chemotherapy shifted these subpopulations and their biomarker expression, while scaffolds derived from different patients' tumors influenced cell heterogeneity and drug resistance in distinct ways, reflecting each tumor's unique microenvironment. Together, this approach can help reveal how the tumor microenvironment shapes cellular heterogeneity, phenotypes, and treatment response, and provide new insight into the mechanisms underlying tumor development and therapy resistance. Register here: https://lnkd.in/gtE4nnBz

Biology driving acute myeloid leukemia (AML) development isn't just gene mutations. Asif Javed showed that chromosomal gain, aka trisomy, can be a driver due to a cumulative sequence of these mutations. Join us live: https://lnkd.in/g5aS2mCj What you will learn: • Bulk sequencing across three independent cohorts of myeloid malignancies (1,650 cytogenetically normal and 229 trisomy patients) identified regulatory gene mutations associated with whole-chromosome gains, with ASXL1, SRSF2, STAG2, and EZH2 remaining significant after multiple-testing correction. • Single-cell DNA sequencing on Mission Bio's Tapestri platform profiled 51,092 cells across 16 AML patients to reconstruct clonal phylogenies, showing regulatory gene mutations typically arise before the chromosome gain. • In 71% of trisomy-positive cases, more than one regulatory mutation occurred before or within the same clonal branch as the chromosome gain supporting a cumulative mechanism rather than a single driver mutation. • CRISPR screen data and evolutionary simulation modeling support a model in which progressive disruption of transcription and chromatin regulation destabilizes chromosome segregation over time.