Skip to main content

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

Publication ,  Journal Article
Bergholtz, H; Carter, JM; Cesano, A; Cheang, MCU; Church, SE; Divakar, P; Fuhrman, CA; Goel, S; Gong, J; Guerriero, JL; Hoang, ML; Hwang, ES ...
Published in: Cancers (Basel)
September 4, 2021

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.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Cancers (Basel)

DOI

ISSN

2072-6694

Publication Date

September 4, 2021

Volume

13

Issue

17

Location

Switzerland

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bergholtz, H., Carter, J. M., Cesano, A., Cheang, M. C. U., Church, S. E., Divakar, P., … On Behalf Of The GeoMx Breast Cancer Consortium, . (2021). Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler. Cancers (Basel), 13(17). https://doi.org/10.3390/cancers13174456
Bergholtz, Helga, Jodi M. Carter, Alessandra Cesano, Maggie Chon U. Cheang, Sarah E. Church, Prajan Divakar, Christopher A. Fuhrman, et al. “Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler.Cancers (Basel) 13, no. 17 (September 4, 2021). https://doi.org/10.3390/cancers13174456.
Bergholtz H, Carter JM, Cesano A, Cheang MCU, Church SE, Divakar P, et al. Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler. Cancers (Basel). 2021 Sep 4;13(17).
Bergholtz, Helga, et al. “Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler.Cancers (Basel), vol. 13, no. 17, Sept. 2021. Pubmed, doi:10.3390/cancers13174456.
Bergholtz H, Carter JM, Cesano A, Cheang MCU, Church SE, Divakar P, Fuhrman CA, Goel S, Gong J, Guerriero JL, Hoang ML, Hwang ES, Kuasne H, Lee J, Liang Y, Mittendorf EA, Perez J, Prat A, Pusztai L, Reeves JW, Riazalhosseini Y, Richer JK, Sahin Ö, Sato H, Schlam I, Sørlie T, Stover DG, Swain SM, Swarbrick A, Thompson EA, Tolaney SM, Warren SE, On Behalf Of The GeoMx Breast Cancer Consortium. Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler. Cancers (Basel). 2021 Sep 4;13(17).

Published In

Cancers (Basel)

DOI

ISSN

2072-6694

Publication Date

September 4, 2021

Volume

13

Issue

17

Location

Switzerland

Related Subject Headings

  • 3211 Oncology and carcinogenesis
  • 1112 Oncology and Carcinogenesis