Abstract 1885: Identification of the novel immune synapse-localized proteome for immuno-oncology using Microscoop®-induced targeted photo-biotinylation

Abstract Although numerous immune synapse (IS) protein species have been identified, many IS-localized protein species remain unknown. Understanding the proteome of the IS between a target cell and a lymphocyte is crucial for advancing immuno-oncology. However, the low abundance of ISs and the absence of a definitive enrichment marker have hindered efficient proteomic profiling. In this study, we utilized Microscoop®, an innovative system that integrates microscopy, machine learning, and photochemical labeling to enable precise and spatially specific enrichment of IS proteins, thereby facilitating proteomic discovery for the IS. We employed Raji B cells as antigen-presenting cells (APCs) and induced IS formation with Jurkat T cells. The system first employed immunofluorescence imaging of CD3, a common IS marker in Jurkat T cells, and utilized a convolutional neural network-based deep learning algorithm to recognize IS formation from CMTPX-stained Raji B cells. Our automated system successfully achieved spatially targeted biotin-tagging of proteins at ISs through multiple rounds of imaging, deep learning-driven pattern generation, and photochemical labeling. Subsequent streptavidin pull-down and mass spectrometry analysis enabled the identification of IS-specific proteins. Remarkably, our spatial proteomic approach led to the isolation and identification of hundreds of different species at the IS interface, including proteins associated with key components of T-cell receptor (TCR) signaling pathways such as the TCR/CD3 complex, Src and Tec family tyrosine kinases, and pivotal NF-kB signaling proteins. Additionally, we identified a significant enrichment of proteins not previously associated with the IS. Our study not only illuminates previously unknown aspects of immune regulation at the IS interface but also has significant implications for cancer research, particularly in understanding and manipulating immune responses for therapeutic purposes. Citation Format: Chantal Hoi Yin Cheung, Weng Man Chong, Chun-Kai Huang, Hsiao-Jen Chang, Chia-Wen Chung, Jung-Chi Liao, Joseph Breier. Identification of the novel immune synapse-localized proteome for immuno-oncology using Microscoop®-induced targeted photo-biotinylation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1885.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-1885
Primary Topic
Nanoplatforms for cancer theranostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 1885: Identification of the novel immune synapse-localized proteome for immuno-oncology using Microscoop®-induced targeted photo-biotinylation

Joseph M. Breier, Chia-Wen Chung, Jung‐Chi Liao, Hsiao-Jen Chang et al.
Cancer Research
Nanoplatforms for cancer theranostics
article

Abstract 1885: Identification of the novel immune synapse-localized proteome for immuno-oncology using Microscoop®-induced targeted photo-biotinylation

Joseph M. Breier, Chia-Wen Chung, Jung‐Chi Liao, Hsiao-Jen Chang, Weng Man Chong, Chantal Hoi Yin Cheung, Chun‐Kai Huang
article en

Abstract

Abstract Although numerous immune synapse (IS) protein species have been identified, many IS-localized protein species remain unknown. Understanding the proteome of the IS between a target cell and a lymphocyte is crucial for advancing immuno-oncology. However, the low abundance of ISs and the absence of a definitive enrichment marker have hindered efficient proteomic profiling. In this study, we utilized Microscoop®, an innovative system that integrates microscopy, machine learning, and photochemical labeling to enable precise and spatially specific enrichment of IS proteins, thereby facilitating proteomic discovery for the IS. We employed Raji B cells as antigen-presenting cells (APCs) and induced IS formation with Jurkat T cells. The system first employed immunofluorescence imaging of CD3, a common IS marker in Jurkat T cells, and utilized a convolutional neural network-based deep learning algorithm to recognize IS formation from CMTPX-stained Raji B cells. Our automated system successfully achieved spatially targeted biotin-tagging of proteins at ISs through multiple rounds of imaging, deep learning-driven pattern generation, and photochemical labeling. Subsequent streptavidin pull-down and mass spectrometry analysis enabled the identification of IS-specific proteins. Remarkably, our spatial proteomic approach led to the isolation and identification of hundreds of different species at the IS interface, including proteins associated with key components of T-cell receptor (TCR) signaling pathways such as the TCR/CD3 complex, Src and Tec family tyrosine kinases, and pivotal NF-kB signaling proteins. Additionally, we identified a significant enrichment of proteins not previously associated with the IS. Our study not only illuminates previously unknown aspects of immune regulation at the IS interface but also has significant implications for cancer research, particularly in understanding and manipulating immune responses for therapeutic purposes. Citation Format: Chantal Hoi Yin Cheung, Weng Man Chong, Chun-Kai Huang, Hsiao-Jen Chang, Chia-Wen Chung, Jung-Chi Liao, Joseph Breier. Identification of the novel immune synapse-localized proteome for immuno-oncology using Microscoop®-induced targeted photo-biotinylation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1885.

Cancer ResearchVol. 85(8_Supplement_1)
1Cellbio (United States) (US)
Openalex Percentile: Top 93%
Nanoplatforms for cancer theranostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.