Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler

Helga Bergholtz(Oslo University Hospital), Jodi M. Carter(Mayo Clinic), Alessandra Cesano(Essa Pharma (United States)), Maggie C.U. Cheang(Institute of Cancer Research), S. Church(Nanostring Technologies (United States)), Prajan Divakar(Nanostring Technologies (United States)), Christopher A. Fuhrman(Nanostring Technologies (United States)), Shom Goel(The University of Melbourne), Jingjing Gong(Nanostring Technologies (United States)), Jennifer L. Guerriero(Brigham and Women's Hospital), Margaret L. Hoang(Nanostring Technologies (United States)), E. Shelley Hwang(Duke University), Hellen Kuasne(McGill University Health Centre), Jinho Lee(Oregon Health & Science University), Yan Liang(Nanostring Technologies (United States)), Elizabeth A. Mittendorf(Brigham and Women's Hospital), Jessica Perez(Nanostring Technologies (United States)), Aleix Prat, Lajos Pusztai(Yale Cancer Center), Jason Reeves(Nanostring Technologies (United States)), Yasser Riazalhosseini(McGill Genome Centre), Jennifer K. Richer(University of Colorado Anschutz Medical Campus), Özgür Şahin(University of South Carolina), Hiromi Sato(Nanostring Technologies (United States)), Ilana Schlam(MedStar Washington Hospital Center), Thérese Sørlie(Oslo University Hospital), Daniel G. Stover(The Ohio State University), Sandra M. Swain(Georgetown University), Alexander Swarbrick(Garvan Institute of Medical Research), E. Aubrey Thompson(Mayo Clinic in Florida), Sara M. Tolaney(Harvard University), Sarah H. Warren(Nanostring Technologies (United States))
Cancers
September 4, 2021
Cited by 97Open Access
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Abstract

Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.


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