Cancers (Sep 2021)

Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx<sup>®</sup> Digital Spatial Profiler

  • Helga Bergholtz,
  • Jodi M. Carter,
  • Alessandra Cesano,
  • Maggie Chon U Cheang,
  • Sarah E. Church,
  • Prajan Divakar,
  • Christopher A. Fuhrman,
  • Shom Goel,
  • Jingjing Gong,
  • Jennifer L. Guerriero,
  • Margaret L. Hoang,
  • E. Shelley Hwang,
  • Hellen Kuasne,
  • Jinho Lee,
  • Yan Liang,
  • Elizabeth A. Mittendorf,
  • Jessica Perez,
  • Aleix Prat,
  • Lajos Pusztai,
  • Jason W. Reeves,
  • Yasser Riazalhosseini,
  • Jennifer K. Richer,
  • Özgür Sahin,
  • Hiromi Sato,
  • Ilana Schlam,
  • Therese Sørlie,
  • Daniel G. Stover,
  • Sandra M. Swain,
  • Alexander Swarbrick,
  • E. Aubrey Thompson,
  • Sara M. Tolaney,
  • Sarah E. Warren,
  • on behalf of the GeoMx Breast Cancer Consortium

DOI
https://doi.org/10.3390/cancers13174456
Journal volume & issue
Vol. 13, no. 17
p. 4456

Abstract

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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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