Abstract A043: A dynamic approach to functional precision medicine: Developing next-generation immunotherapy to overcome treatment resistance

Abstract Background: T-cell immune checkpoint inhibitor (ICI) therapies, such as anti-PD1 and anti-CTLA4, have revolutionized cancer treatment, offering durable responses for select patients. However, 75-85% of patients experience only transient responses or outright resistance. Enhancing the curative potential of ICIs has been a major focus for both academia and the biopharma industry over the past decade. Despite significant investments in drug discovery programs and clinical trials to develop new agents and novel combinations with ICI, most efforts have not succeeded in improving long-term response rates. Challenges: Our current approaches lack a precise understanding of which specific resistance mechanism of action (MOA) is operative in which specific subset of patients. Moreover, the application of precision based approaches to immune therapy is significantly limited by a static view of tumor-immune interactions or is overly reliant on preclinical models that fail to recapitulate the dynamic complexity of the human immune system. Hence, there remains a critical gap in understanding (1) how to identify patients, as early as possible, who will not benefit from their current therapies, (2) which druggable mechanisms underpin resistance in those patients and (3) how to match the right patients to the right therapeutics targeting specific resistance mechanisms. Insights: The immune system operates as a complex adaptive network, exhibiting non-linear responses to perturbations like ICI therapy. Notably, mechanisms driving resistance often emerge only after treatment initiation. This underscores the need for a dynamic precision medicine approach that accounts for the functional changes occurring in real-time during therapy. Approach: Our "Dynamic Precision™" approach leverages longitudinal clinical and molecular data from real-world cancer patients undergoing ICI treatment. By analyzing changes over time rather than static snapshots, we identify emergent signatures predictive of treatment resistance. This functional precision strategy uncovers dynamically regulated nodes within the immune system, offering new avenues for therapeutic intervention. Furthermore, these insights are linked with blood-based patient selection biomarkers, providing a minimally invasive method for patient stratification and monitoring. Conclusion: This dynamic approach to functional precision medicine bridges the gap between genomic insights and real-time adaptive responses in cancer therapy. By shifting from a static to a dynamic framework, we reveal novel, actionable targets for enhancing immunotherapy efficacy. We will present proof-of-concept data illustrating how this strategy refines precision treatment paradigms, ultimately contributing to the development of next-generation cancer therapies. Citation Format: Ronan O'Hagan, Lynda Chin. A dynamic approach to functional precision medicine: Developing next-generation immunotherapy to overcome treatment resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr A043.

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Journal
Cancer Research
Published
2025-03-11
DOI
https://doi.org/10.1158/1538-7445.genfunc25-a043
Primary Topic
Monoclonal and Polyclonal Antibodies Research
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article
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article

Abstract A043: A dynamic approach to functional precision medicine: Developing next-generation immunotherapy to overcome treatment resistance

Rónán C. O’Hagan, Lynda Chin
Cancer Research
Monoclonal and Polyclonal Antibodies Research
article

Abstract A043: A dynamic approach to functional precision medicine: Developing next-generation immunotherapy to overcome treatment resistance

Rónán C. O’Hagan, Lynda Chin
article en

Abstract

Abstract Background: T-cell immune checkpoint inhibitor (ICI) therapies, such as anti-PD1 and anti-CTLA4, have revolutionized cancer treatment, offering durable responses for select patients. However, 75-85% of patients experience only transient responses or outright resistance. Enhancing the curative potential of ICIs has been a major focus for both academia and the biopharma industry over the past decade. Despite significant investments in drug discovery programs and clinical trials to develop new agents and novel combinations with ICI, most efforts have not succeeded in improving long-term response rates. Challenges: Our current approaches lack a precise understanding of which specific resistance mechanism of action (MOA) is operative in which specific subset of patients. Moreover, the application of precision based approaches to immune therapy is significantly limited by a static view of tumor-immune interactions or is overly reliant on preclinical models that fail to recapitulate the dynamic complexity of the human immune system. Hence, there remains a critical gap in understanding (1) how to identify patients, as early as possible, who will not benefit from their current therapies, (2) which druggable mechanisms underpin resistance in those patients and (3) how to match the right patients to the right therapeutics targeting specific resistance mechanisms. Insights: The immune system operates as a complex adaptive network, exhibiting non-linear responses to perturbations like ICI therapy. Notably, mechanisms driving resistance often emerge only after treatment initiation. This underscores the need for a dynamic precision medicine approach that accounts for the functional changes occurring in real-time during therapy. Approach: Our "Dynamic Precision™" approach leverages longitudinal clinical and molecular data from real-world cancer patients undergoing ICI treatment. By analyzing changes over time rather than static snapshots, we identify emergent signatures predictive of treatment resistance. This functional precision strategy uncovers dynamically regulated nodes within the immune system, offering new avenues for therapeutic intervention. Furthermore, these insights are linked with blood-based patient selection biomarkers, providing a minimally invasive method for patient stratification and monitoring. Conclusion: This dynamic approach to functional precision medicine bridges the gap between genomic insights and real-time adaptive responses in cancer therapy. By shifting from a static to a dynamic framework, we reveal novel, actionable targets for enhancing immunotherapy efficacy. We will present proof-of-concept data illustrating how this strategy refines precision treatment paradigms, ultimately contributing to the development of next-generation cancer therapies. Citation Format: Ronan O'Hagan, Lynda Chin. A dynamic approach to functional precision medicine: Developing next-generation immunotherapy to overcome treatment resistance [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Functional and Genomic Precision Medicine in Cancer: Different Perspectives, Common Goals; 2025 Mar 11-13; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(5 Suppl):Abstract nr A043.

Cancer ResearchVol. 85(5_Supplement)
Houston Health and Human Services Department (US)
Openalex Percentile: Top 93%
Monoclonal and Polyclonal Antibodies Research
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