AACR Annual Meeting 2025
AACR Annual Meeting 2025
Date: April 25-30, 2025
Location: Chicago, IL
Event Overview
Three PathFinder Lab members (Sung Hak Lee, Moonyoung Lee, Harim Chun) attended the premier international cancer research conference, participating in cutting-edge scientific sessions while presenting our laboratory's research contributions. The five-day program provided comprehensive exposure to the latest advances in cancer biology, therapeutics, and computational approaches.
Program Participation
Poster Presentations: Moonyoung Lee and Harim Chun showcased lab research findings
Plenary Sessions: Attended keynote presentations on oncogene targeting, genomic instability, and tumor microenvironment complexity
Scientific Sessions: Focused participation in spatial omics, AI-driven pathology, and multimodal cancer research tracks
Key Scientific Exposure
Lab members gained insights across multiple cutting-edge research areas:
Therapeutic Targeting - Novel drug development approaches and personalized treatment strategies
Spatial Technologies - Advanced methods for spatial analysis and cellular interaction mapping
AI Applications - Machine learning approaches for integrating histopathology with molecular data
Tumor Biology - Genomic instability mechanisms and microenvironment heterogeneity
Key Outcomes
Direct exposure to latest computational oncology methodologies relevant to our research
Opportunities with experiencing leading researchers in image analysis and spatial genomics
Validation of our research directions through alignment with cutting-edge conference presentations
Enhanced understanding of AI-driven biomarker discovery approaches
Impact
The conference participation significantly advanced our laboratory's awareness of current trends in computational cancer research and spatial analysis methodologies. The combination of poster presentations and comprehensive session attendance provided valuable opportunities for both showcasing our work and identifying future research directions. Insights gained from various AI-driven approaches will directly inform our ongoing pathology image analysis and genomics integration projects.
Date: April 25-30, 2025
Location: Chicago, IL
Event Overview
Three PathFinder Lab members (Sung Hak Lee, Moonyoung Lee, Harim Chun) attended the premier international cancer research conference, participating in cutting-edge scientific sessions while presenting our laboratory's research contributions. The five-day program provided comprehensive exposure to the latest advances in cancer biology, therapeutics, and computational approaches.
Program Participation
Poster Presentations: Moonyoung Lee and Harim Chun showcased lab research findings
Plenary Sessions: Attended keynote presentations on oncogene targeting, genomic instability, and tumor microenvironment complexity
Scientific Sessions: Focused participation in spatial omics, AI-driven pathology, and multimodal cancer research tracks
Key Scientific Exposure
Lab members gained insights across multiple cutting-edge research areas:
Therapeutic Targeting - Novel drug development approaches and personalized treatment strategies
Spatial Technologies - Advanced methods for spatial analysis and cellular interaction mapping
AI Applications - Machine learning approaches for integrating histopathology with molecular data
Tumor Biology - Genomic instability mechanisms and microenvironment heterogeneity
Key Outcomes
Direct exposure to latest computational oncology methodologies relevant to our research
Opportunities with experiencing leading researchers in image analysis and spatial genomics
Validation of our research directions through alignment with cutting-edge conference presentations
Enhanced understanding of AI-driven biomarker discovery approaches
Impact
The conference participation significantly advanced our laboratory's awareness of current trends in computational cancer research and spatial analysis methodologies. The combination of poster presentations and comprehensive session attendance provided valuable opportunities for both showcasing our work and identifying future research directions. Insights gained from various AI-driven approaches will directly inform our ongoing pathology image analysis and genomics integration projects.
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