
Proceedings Paper
Signal removal methods for highly multiplexed immunofluorescent staining using antibody conjugated oligonucleotidesFormat | Member Price | Non-Member Price |
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Paper Abstract
Successful cancer treatment continues to elude modern medicine and its arsenal of therapeutic strategies. Therapy resistance is driven by significant tumor heterogeneity, complex interactions between malignant, microenvironmental and immune cells and cross talk between signaling pathways. Advances in molecular characterization technologies such as next generation sequencing have helped unravel this network of interactions and have vastly affected how cancer is diagnosed and treated. However, the translation of complex genomic analyses to pathological diagnosis remains challenging using conventional immunofluorescence (IF) staining, which is typically limited to 2-5 antigens. Numerous strategies to increase distinct antigen detection on a single sample have been investigated, but all have deleterious effects on the tissue limiting the maximum number of biomarkers that can be imaged on a single sample and none can be seamlessly integrated into routine clinical workflows. To facilitate ready integration into clinical histopathology, we have developed a novel cyclic IF (cycIF) technology based on antibody conjugated oligonucleotides (Ab-oligos). In situ hybridization of complementary oligonucleotides (oligos) facilitates biomarker labeling for imaging on any conventional fluorescent microscope. We have validated a variety of oligo configurations and their respective signal removal strategies capable of diminishing fluorescent signal to levels of autofluorescence before subsequent staining cycles. Robust signal removal is performed without the employment of harsh conditions or reagents, maintaining tissue integrity and antigenicity for higher dimensionality immunostaining of a single sample. Our platform Ab-oligo cycIF technology uses conventional fluorophores and microscopes, allowing for dissemination to a broad audience and congruent integration into clinical histopathology workflows.
Paper Details
Date Published: 4 March 2019
PDF: 7 pages
Proc. SPIE 10881, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII, 108810X (4 March 2019); doi: 10.1117/12.2510573
Published in SPIE Proceedings Vol. 10881:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII
Daniel L. Farkas; Attila Tárnok; James F. Leary, Editor(s)
PDF: 7 pages
Proc. SPIE 10881, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII, 108810X (4 March 2019); doi: 10.1117/12.2510573
Show Author Affiliations
Nathan McMahon, Oregon Health & Science Univ. (United States)
Jocelyn Jones, Oregon Health & Science Univ. (United States)
Jennifer Eng, Oregon Health & Science Univ. (United States)
Sunjong Kwon, Oregon Health & Science Univ. (United States)
Young-Hwan Chang, Oregon Health & Science Univ. (United States)
Jocelyn Jones, Oregon Health & Science Univ. (United States)
Jennifer Eng, Oregon Health & Science Univ. (United States)
Sunjong Kwon, Oregon Health & Science Univ. (United States)
Young-Hwan Chang, Oregon Health & Science Univ. (United States)
Guillaume Thibault, Oregon Health & Science Univ. (United States)
Koei Chin, Oregon Health & Science Univ. (United States)
Michel Nederlof, Quantitative Imaging Systems (United States)
Joe Gray, Oregon Health & Science Univ. (United States)
Summer L. Gibbs, Oregon Health & Science Univ. (United States)
Koei Chin, Oregon Health & Science Univ. (United States)
Michel Nederlof, Quantitative Imaging Systems (United States)
Joe Gray, Oregon Health & Science Univ. (United States)
Summer L. Gibbs, Oregon Health & Science Univ. (United States)
Published in SPIE Proceedings Vol. 10881:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII
Daniel L. Farkas; Attila Tárnok; James F. Leary, Editor(s)
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