1.

Discovering novel spatial biomarkers that are not readily detectable by traditional bulk profiling

Spatial proteomic characterization of the tumor and immune microenvironment reveals features associated with response to neoadjuvant HER2-targeted therapy

Katherine McNamara et al., Stanford University, Palo Alto, CA, USA

Used spatial proteomic analysis of biopsies from on-treatment HER2+ breast cancer patients to stratify responders v. non-responders early during a course of neoadjuvant HER2-targeted therapy. GeoMx analysis allowed unique segmentation of cell populations to provide insight into the effect of innate immune markers, ER status, and PAM50 subtype on treatment response.

Identification of cell type-specific RNA biomarker candidates in melanocytic tumors using GeoMx Digital Spatial Profiling

Maija Kiuru, MD, Ph.D., University of California, Davis, CA, USA

GeoMx Cancer Transcriptome Atlas analysis revealed microenvironment-specific expression of a novel cell-type specific biomarker, DAMP, in response to early melanoma development. This marker may allow for more sensitive detection of melanoma via patch biopsy.

Single-nucleus RNA-seq reveals distinct intratumoral transcriptomic heterogeneity in treatment-naïve and chemoradiotherapy-treated primary pancreatic ductal adenocarcinoma

William Hwang, MD, Ph.D., et al. et al., Broad Institute, Cambridge, MA, USA

GeoMx Cancer Transcriptome Atlas and Whole Transcriptome Atlas applications were used to profile tumor, fibroblast, and immune compartments in Pancreatic ductal adenocarcinoma (PDAC) samples from twelve patients. Differential gene expression was measured in tumor and fibroblast compartments between treatment groups and by levels of immune infiltration.

Spatial Profiling of the Immune Landscape of Solid Tumors Treated with Low Dose Radiation and Immunotherapy Using High Plex RNA Profiling with the GeoMx™ Platform

Krisztian Homicsko, MD, Ph.D., et al., Ludwig Institute for Cancer Research, Lausanne, Switzerland

This project interrogated gene expression changes associated with low-dose radiation immunogenic induction therapy in ovarian cancer. GeoMx Cancer Transcriptome Atlas analysis revealed a pretreatment microenvironment associated with favorable response to therapy, and allowed in depth analysis of needle core biopsies, providing important spatial information in samples that would not have been ideal for bulk transcriptomic assays.

Localizing and quantifying the immune contexture of human glioma with GeoMx™ high -plex RNA profiling

Troy McEachron, MD, et al., University of Southern California, Los Angeles, CA, USA

Combined single cell RNA sequencing with GeoMx Cancer Transcriptome Atlas analysis to characterize immune cell distribution in glioma samples. GeoMx DSP demonstrates that synchronizing digital pathology and bioinformatics provides layers of insight that conventional methods couldn’t.

2.

Spatial mapping of the whole transcriptome in FFPE tissue

Neural stem cell differentiation trajectories in the developing human brain revealed by whole-transcriptome in situ spatial profiling

Kenny Roberts, MD, Ph.D., et al. et al., Sanger Institute, Cambridge, UK

GeoMx DSP Whole Transcriptome Atlas was used to distinguish the transcriptomic profiles of neural stem cells, intermediate progenitors and neurons in the fetal human cerebral cortex at 14 and 19 post-conception weeks. This study examined cell type specific gene expression programs throughout the cortical germinal zones, subplate and the maturing cortical plate and identified spatiotemporal gene expression correlated with neural stem cell self-renewal and differentiation.

Single Cell Programs of Immune Activation in Human MSI vs MSS Colorectal Carcinoma

Jonathan Chen, MD, Ph.D., et al. et al., Broad Institute, Cambridge, MA, USA

GeoMx DSP Cancer Transcriptome Atlas and Whole Transcriptome Atlas were used to interrogate how tumor and microenvironment interactions vary spatially within colorectal cancers, allowing spatial mapping of signatures linked to single cell RNA sequencing. This study highlights the capacity of GeoMx to identify locations of specific cell populations distributed across tissues.

Measuring the Spatial Whole Transcriptome and High-Plex Proteins on FFPE samples from Glioblastoma Multiforme Immunotherapy Clinical Trials Using Digital Spatial Profiling

Yue Lu Ph.D., et al., Institute Systems Biology, Seattle, WA, USA

GeoMx Cancer Transcriptome Atlas analysis of glioblastoma multiforme (GBM) samples generated a high-resolution spatial map of the tumor microenvironment and provided the framework for creating a GBM tumor atlas. Use of whole transcriptome sequencing combined with spatial analysis provides the potential to discover the biology underpinning response to new immunotherapy treatment for glioblastoma.

3.

Phenotyping of single cells through spatial profiling algorithms

Mapping intratumoural heterogeneity of triple negative breast cancer through integrated single cell RNA-Sequencing and whole transcriptome Digital Spatial Profiling

Alex Swarbrick Ph.D. et al., Garvan Institute of Medical Research, Sydney, Australia

Primary, untreated, triple negative breast cancer (TNBC) was profiled using GeoMx DSP whole transcriptome. Segmentation was performed based on visual markers characterize immune and stromal cells in the invasive edge, tumor core, and distant stromal regions with the goal of discovering novel therapeutic targets in TNBC.

Updating immune cell deconvolution for the spatial genomics era

Danaher Ph.D. et al., NanoString Technologies, Seattle, WA USA

GeoMx DSP Cancer Transcriptome Atlas was used to estimate abundance of different immune cell types using novel computational methods. This allows researchers to study how immune cells interact spatially in different regions of a tissue.

Enabling pathway analysis of RNA expression in formalin-fixed paraffin embedded tissues with the GeoMx™ DSP Platform.

Boykin et al., NanoString Technologies, Seattle, WA USA

GeoMx Cancer Transcriptome Atlas, bulk RNA sequencing, and NanoString nCounter analysis was used to profile the same samples. This project demonstrates how GeoMx analysis can be expanded beyond single gene analysis to understand how biological pathways vary spatially in different regions of a tissue.