Guideline

. 2021 Sep 4;13(17):4456.

doi: 10.3390/cancers13174456.

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

Helga Bergholtz¹, Jodi M Carter², Alessandra Cesano³, Maggie Chon U Cheang⁴, Sarah E Church⁵, Prajan Divakar⁵, Christopher A Fuhrman⁵, Shom Goel^{6

7}, Jingjing Gong⁵, Jennifer L Guerriero⁸, Margaret L Hoang⁵, E Shelley Hwang⁹, Hellen Kuasne¹⁰, Jinho Lee¹¹, Yan Liang⁵, Elizabeth A Mittendorf^{8

12

13}, Jessica Perez⁵, Aleix Prat¹⁴, Lajos Pusztai¹⁵, Jason W Reeves⁵, Yasser Riazalhosseini^{16

17}, Jennifer K Richer¹⁸, Özgür Sahin¹⁹, Hiromi Sato⁵, Ilana Schlam^{20

21}, Therese Sørlie^{1

22}, Daniel G Stover²³, Sandra M Swain^{24

25

26}, Alexander Swarbrick^{27

28}, E Aubrey Thompson²⁹, Sara M Tolaney^{13

30}, Sarah E Warren⁵, On Behalf Of The GeoMx Breast Cancer Consortium

Affiliations

¹ Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, 0450 Oslo, Norway.
² Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA.
³ ESSA Pharma Inc., South San Francisco, CA 94080, USA.
⁴ ICR Clinical Trials and Statistics Unit, Division of Clinical Studies, The Institute of Cancer Research, London SM2 5NG, UK.
⁵ NanoString® Technologies Inc., Seattle, WA 98109, USA.
⁶ Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
⁷ Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, VIC 3010, Australia.
⁸ Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA 02115, USA.
⁹ Duke Cancer Institute, Duke University, Durham, NC 27710, USA.
¹⁰ Rosalind and Morris Goodman Cancer Centre, McGill University, Montreal, QC H3A 0G4, Canada.
¹¹ Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA.
¹² Breast Oncology Program, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
¹³ Harvard Medical School, Boston, MA 02115, USA.
¹⁴ Translational Genomics and Targeted Therapies in Solid Tumors, August Pi i Sunyer Biomedical Research Institute, 08036 Barcelona, Spain.
¹⁵ Yale Cancer Center, Yale School of Medicine, New Haven, CT 06510, USA.
¹⁶ Department of Human Genetics, McGill University, Montreal, QC H3A 0G4, Canada.
¹⁷ McGill University Genome Centre, McGill University, Montreal, QC H3A 0G4, Canada.
¹⁸ Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
¹⁹ Department of Drug Discovery and Biomedical Sciences, University of South Carolina, Columbia, SC 29208, USA.
²⁰ MedStar Washington Hospital Center, Washington, DC 20010, USA.
²¹ Tufts Medical Center, Boston, MA 02111, USA.
²² Institute of Clinical Medicine, University of Oslo, 0315 Oslo, Norway.
²³ Ohio State University Comprehensive Cancer Center, Columbus, OH 43210, USA.
²⁴ Georgetown Lombardi Comprehensive Cancer Center, Washington, DC 20057, USA.
²⁵ Georgetown University Medical Center, Washington, DC 20057, USA.
²⁶ MedStar Health, Washington, DC 20057, USA.
²⁷ Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia.
²⁸ St Vincent's Clinical School, Faculty of Medicine, UNSW Sydney, Sydney NSW 2052, Australia.
²⁹ Department of Cancer Biology, Mayo Clinic Florida, Jacksonville, FL 32224, USA.
³⁰ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

PMID: 34503266
PMCID: PMC8431590
DOI: 10.3390/cancers13174456

Guideline

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

Helga Bergholtz et al. Cancers (Basel). 2021.

. 2021 Sep 4;13(17):4456.

doi: 10.3390/cancers13174456.

Authors

Affiliations

¹ Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, 0450 Oslo, Norway.
² Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA.
³ ESSA Pharma Inc., South San Francisco, CA 94080, USA.
⁴ ICR Clinical Trials and Statistics Unit, Division of Clinical Studies, The Institute of Cancer Research, London SM2 5NG, UK.
⁵ NanoString® Technologies Inc., Seattle, WA 98109, USA.
⁶ Peter MacCallum Cancer Centre, Melbourne, VIC 3000, Australia.
⁷ Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, VIC 3010, Australia.
⁸ Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA 02115, USA.
⁹ Duke Cancer Institute, Duke University, Durham, NC 27710, USA.
¹⁰ Rosalind and Morris Goodman Cancer Centre, McGill University, Montreal, QC H3A 0G4, Canada.
¹¹ Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA.
¹² Breast Oncology Program, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
¹³ Harvard Medical School, Boston, MA 02115, USA.
¹⁴ Translational Genomics and Targeted Therapies in Solid Tumors, August Pi i Sunyer Biomedical Research Institute, 08036 Barcelona, Spain.
¹⁵ Yale Cancer Center, Yale School of Medicine, New Haven, CT 06510, USA.
¹⁶ Department of Human Genetics, McGill University, Montreal, QC H3A 0G4, Canada.
¹⁷ McGill University Genome Centre, McGill University, Montreal, QC H3A 0G4, Canada.
¹⁸ Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
¹⁹ Department of Drug Discovery and Biomedical Sciences, University of South Carolina, Columbia, SC 29208, USA.
²⁰ MedStar Washington Hospital Center, Washington, DC 20010, USA.
²¹ Tufts Medical Center, Boston, MA 02111, USA.
²² Institute of Clinical Medicine, University of Oslo, 0315 Oslo, Norway.
²³ Ohio State University Comprehensive Cancer Center, Columbus, OH 43210, USA.
²⁴ Georgetown Lombardi Comprehensive Cancer Center, Washington, DC 20057, USA.
²⁵ Georgetown University Medical Center, Washington, DC 20057, USA.
²⁶ MedStar Health, Washington, DC 20057, USA.
²⁷ Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia.
²⁸ St Vincent's Clinical School, Faculty of Medicine, UNSW Sydney, Sydney NSW 2052, Australia.
²⁹ Department of Cancer Biology, Mayo Clinic Florida, Jacksonville, FL 32224, USA.
³⁰ Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA.

PMID: 34503266
PMCID: PMC8431590
DOI: 10.3390/cancers13174456

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.

Keywords: GeoMx; RNA and protein profiling; biomarker discovery; breast cancer; cancer transcriptome atlas; digital spatial profiler; spatial biology; tumor heterogeneity; tumor microenvironment; whole transcriptome atlas.

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Conflict of interest statement

A.C. is an employee of ESSA Pharma Inc., a consultant for NanoString Technologies Inc., Refuge Biotechnologies Inc., Bayer AG and Kiromic BioPharma Inc. and is on the scientific advisory board for Arch Oncology, Refuge Biotechnologies Inc. and IO Biotech ApS. M.C.U.C. has an advisory role of Veracyte and is co-inventor of the PAM50 bioclassifier patent with royalties paid by and research funding from NanoString Technologies Inc. S.E.C., P.D., C.A.F., J.G., M.L.H., Y.L., J.P., J.W.R., H.S., S.E.W. are employees of NanoString Technologies Inc., hold NanoString stock or stock options. S.G. receives research funding from Eli Lilly and G1 Therapeutics and honoraria for consulting from Eli Lilly, G1 Therapeutics, Pfizer and Novartis. J.L.G. is a consultant for GlaxoSmithKline (GSK), Codagenix, Verseau, Kymera and Array BioPharma and receives sponsored research support from GSK, Array BioPharma and Eli Lilly. E.A.M. is SAB for Exact Sciences, Merck and Roche/Genentech (compensated) and part of steering committee for Roche/Genentech and Bristol-Myers Squibb (uncompensated). A.P. has an advisory role and research funding from NanoString Technologies Inc. L.P. has received consulting fees and honoraria from Seagen, Pfizer, Astra Zeneca, Merck, Novartis, Bristol-Myers Squibb, Pfizer, Genentech, Eisai, Pieris, Immunomedics, Clovis, Syndax, H3Bio, Radius Health, Daiichi and institutional research funding from Seagen, AstraZeneca, Merck, Pfizer and Bristol Myers Squibb. O.S. is a co-founder of OncoCube Therapeutics LLC, founder and president of LoxiGen, Inc. and a grant recipient from Halozyme Therapeutics Inc. S.M.S. is consulting/honoraria for AstraZeneca, Daiichi Sankyo, Genentech/Hoffmann-La Roche, Lilly Pharmaceuticals, Exact Sciences, Athenex, Bejing Medical Award Foundation, third party writing (Genentech/Hoffman-la Roche), Independent Data Monitoring committee for AstraZeneca and research to institution Kailos Genetics. A.S. has received research support, consulting fees and conference travel support from NanoString Technologies Inc. S.M.T. receives institutional research funding from AstraZeneca, Lilly, Merck, Nektar, Novartis, Pfizer, Genentech/Roche, Immunomedics, Exelixis, Bristol-Myers Squibb, Eisai, Nanostring, Cyclacel, Odonate and Seattle Genetics and has served as an advisor/consultant to AstraZeneca, Lilly, Merck, Nektar, Novartis, Pfizer, Genentech/Roche, Immunomedics, Bristol-Myers Squibb, Eisai, Nanostring, Puma, Sanofi, Celldex, Paxman, Puma, Silverback Therapeutics, G1 Therapeutics, Gilead, AbbVie, Anthenex, OncoPep, Outcomes4Me, Kyowa Kirin Pharmaceuticals, Daiichi-Sankyo, Ellipsis and Samsung Bioepsis Inc. H.B., J.M.C., E.S.H., H.K., J.L., Y.R., J.K.R., I.S., T.S., D.G.S., E..AT.: No competing interests declared.

Figures

**Figure 1**
GeoMx workflow with NGS readout. The sequence of steps in the GeoMx workflow may be grouped into three phases: slide preparation (1), GeoMx instrument run (2–5) and readout (6). During slide preparation, a high-plex mixture of photocleavable oligo-linked probes (RNA shown) and morphology reagents are applied to the tissue section (1). Slides are loaded into the GeoMx instrument for a series of automated steps. After the researcher selects ROIs (2), the GeoMx instrument illuminates each area-of-illumination (AOI) with UV light to collect and deposit the photo-released oligos into a microtiter plate (3,4). Collection is repeated (5) to produce an AOI collection plate, where each well corresponds to a pool of photocleaved oligos from one AOI on the tissue. For NGS readout (6), each AOI (or well) is uniquely indexed during library preparation and can be pooled into one sequencing run.

**Figure 2**
Slide dimensions and tissue placement for GeoMx DSP study. Tissue sections must be placed in the digital scan area (shown in green), measuring, at maximum, 36.2 mm long by 14.6 mm wide in the center of the slide. The tissue sections should not overlap the slide gasket (shown in blue) or the tip calibration area (the triangular region to the left of the green scan area). The frosted/label end of the slide is on the right.

**Figure 3**
Representative images of non-invasive and invasive breast carcinoma based on histopathological subtypes. (A) Normal breast epithelium adjacent to invasive ductal carcinoma. (B) Ductal carcinoma in situ (DCIS) from concurrent invasive breast cancer. (C) Invasive ductal carcinoma (IDC). (D) Invasive lobular carcinomas (ILC). Hematoxylin and eosin (H&E) staining (upper panels). Morphology markers (middle and lower panels): PanCK (green), CD45 (red), smooth muscle actin (yellow) and DNA (blue). The boxed area is enlarged for better visualization. Scale bar: 200 μm.

**Figure 4**
Representative images of AOI segmentation strategies in breast cancer tissues. The IF image was collected with the following morphology markers: PanCK (green), CD3 (red), CD68 (yellow) and DNA (blue). The mask image shows the captured AOI in white for geometric, segment, cell-type specific, contour and complex (PanCK+ tumor segment, CD3 cell-specific segment in the PanCK- stroma, CD3 cell-specific segment in the PanCK+ tumor and everything else) masking. For contour and complex masking, 4 separate masks are shown in grayscale.

See this image and copyright information in PMC

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

Affiliations

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

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

Grants and funding

LinkOut - more resources

Full Text Sources

Miscellaneous