SPECIAL EVENT: Single-Cell Spatial Transcriptomics + Proteomics!

About this Class

Please join us for this special event featuring three speakers on the topic of Single-Cell Spatial Transcriptomics.

George Zaki, Ph.D., Director, Applied Scientific Computing, BACS, The Frederick National Lab for Cancer Research, NCI/CBIIT

Analysis of SPAtial Single-Cell Datasets using SPAC:  From hypotheses to insights

SPAC is a modular, from raw tabular data to scientific insights, web-accessible toolkit for analyzing spatial, single-cell datasets derived from multiplex IF-stained, whole-slide images generated by different technologies, such as InSituPlex (Ultivue), Imaging cyTOF (Standard BioTools), and PhenoCycler (AKA CODEX) or Opal TSA (Akoya Biosciences). Researchers use SPAC to build and configure scalable, flexible, multistep analysis pipelines on the web and share them with collaborators using a single click.

 Noemi Kedei, M.D., Facility Head, Staff Scientist, Spatial Imaging Technology Resource (SpITR), NCI CCR OSTR

Generating Highly Multiplex Single Cell Level Protein Expression Data in Tissues

Formerly known as the Collaborative Protein Technology Resource (CPTR), the Spatial Imaging Technology Resource (SpITR) is an open core supported by the NCI CCR Office of Science and Technology Resources (OSTR) dedicated to establishing and implementing cutting-edge molecular profiling technologies to facilitate discovery, translational, and clinical research. Spatial technologies include Phenocycler Fusion/CODEX for highly multiplex protein detection at single cell resolution and Nanostring CosMx and GeoMx Digital Spatial Profiling (DSP) for protein and transcript detection at single cell and regional level.

 Lichun Ma Ph.D., Stadtman Investigator, Cancer Data Science Laboratory (CDSL), NCI CCR

Spatial Single-cell Dissection of Cellular Neighborhoods in Liver Cancer

Tumor heterogeneity is the observation that cancer cells can show distinct differences from patient to patient, from primary to secondary tumors, or even between cells within the same tumor. This phenomenon is a major barrier to effective cancer interventions. A better understanding of tumor heterogeneity is critical for improving cancer treatment. Using cutting-edge technology in single-cell and spatial ‘omics assays, my research program focuses on developing novel approaches to understanding tumor heterogeneity through the lens of cellular neighborhoods.