Nathan P McMahon1, Jocelyn A Jones1, Sunjong Kwon1,2, Koei Chin1,2, Michel A Nederlof3, Joe W Gray1,4,2, Summer L Gibbs1,4,2. 1. Oregon Health and Science University, Biomedical Engineering Department, Portland, Oregon, United States. 2. Oregon Health and Science University, OHSU Center for Spatial Systems Biomedicine, Portland, Oregon, United States. 3. Quantitative Imaging, LLC, Pittsburgh, Pennsylvania, United States. 4. Oregon Health and Science University, Knight Cancer Institute, Portland, Oregon, United States.
Abstract
SIGNIFICANCE: Advanced genetic characterization has informed cancer heterogeneity and the challenge it poses to effective therapy; however, current methods lack spatial context, which is vital to successful cancer therapy. Conventional immunolabeling, commonplace in the clinic, can provide spatial context to protein expression. However, these techniques are spectrally limited, resulting in inadequate capacity to resolve the heterogenous cell subpopulations within a tumor. AIM: We developed and optimized oligonucleotide conjugated antibodies (Ab-oligo) to facilitate cyclic immunofluorescence (cyCIF), resulting in high-dimensional immunostaining. APPROACH: We employed a site-specific conjugation strategy to label antibodies with unique oligonucleotide sequences, which were hybridized in situ with their complementary oligonucleotide sequence tagged with a conventional fluorophore. Antibody concentration, imaging strand concentration, and configuration as well as signal removal strategies were optimized to generate maximal staining intensity using our Ab-oligo cyCIF strategy. RESULTS: We successfully generated 14 Ab-oligo conjugates and validated their antigen specificity, which was maintained in single color staining studies. With the validated antibodies, we generated up to 14-color imaging data sets of human breast cancer tissues. CONCLUSIONS: Herein, we demonstrated the utility of Ab-oligo cyCIF as a platform for highly multiplexed imaging, its utility to measure tumor heterogeneity, and its potential for future use in clinical histopathology.
SIGNIFICANCE: Advanced genetic characterization has informed cancer heterogeneity and the challenge it poses to effective therapy; however, current methods lack spatial context, which is vital to successful cancer therapy. Conventional immunolabeling, commonplace in the clinic, can provide spatial context to protein expression. However, these techniques are spectrally limited, resulting in inadequate capacity to resolve the heterogenous cell subpopulations within a tumor. AIM: We developed and optimized oligonucleotide conjugated antibodies (Ab-oligo) to facilitate cyclic immunofluorescence (cyCIF), resulting in high-dimensional immunostaining. APPROACH: We employed a site-specific conjugation strategy to label antibodies with unique oligonucleotide sequences, which were hybridized in situ with their complementary oligonucleotide sequence tagged with a conventional fluorophore. Antibody concentration, imaging strand concentration, and configuration as well as signal removal strategies were optimized to generate maximal staining intensity using our Ab-oligo cyCIF strategy. RESULTS: We successfully generated 14 Ab-oligo conjugates and validated their antigen specificity, which was maintained in single color staining studies. With the validated antibodies, we generated up to 14-color imaging data sets of humanbreast cancer tissues. CONCLUSIONS: Herein, we demonstrated the utility of Ab-oligo cyCIF as a platform for highly multiplexed imaging, its utility to measure tumor heterogeneity, and its potential for future use in clinical histopathology.
Entities:
Keywords:
cancer heterogeneity; cyclic immunostaining; multiplexed immunostaining; oligonucleotide conjugated antibody
Authors: Nathan P McMahon; Allison Solanki; Lei G Wang; Antonio R Montaño; Jocelyn A Jones; Kimberley S Samkoe; Kenneth M Tichauer; Summer L Gibbs Journal: Mol Imaging Biol Date: 2021-03-09 Impact factor: 3.488
Authors: Jocelyn A Jones; Nathan P McMahon; Ting Zheng; Jennifer Eng; Koei Chin; Sunjong Kwon; Michel A Nederlof; Joe W Gray; Summer L Gibbs Journal: Sci Rep Date: 2021-12-13 Impact factor: 4.379
Authors: Michael S Parappilly; Yuki Chin; Riley M Whalen; Ashley N Anderson; Trinity S Robinson; Luke Strgar; Thomas L Sutton; Patrick Conley; Christopher Klocke; Summer L Gibbs; Young Hwan Chang; Guanming Wu; Melissa H Wong; Alison H Skalet Journal: Cancers (Basel) Date: 2022-09-23 Impact factor: 6.575