Abstract 7145: A spatial PK/PD framework predicts ADC response in solid tumors by integrating drug delivery, target engagement, and microenvironmental readiness

Abstract Background: Antibody-drug conjugates achieve their effect only when payload delivery, target accessibility, and microenvironmental readiness align within the tumor. Conventional biomarkers capture fragments of this biology, but not the spatial interplay that ultimately determines response. To address this gap, we conducted a translational spatial PK/PD study to determine whether high-resolution tissue mapping could predict early ADC activity in solid tumors. Methods: Tumor biopsies from patients and PDX models treated with a clinically relevant ADC were analyzed using an integrated spatial PK/PD workflow. Quantitative payload imaging by mass spectrometry imaging was combined with spatial proteomics and transcriptomics to map antigen distribution, stromal architecture, vascular organization, immune niches, and early pharmacodynamic activation. All data modalities were spatially registered and modeled using AI-based neighborhood analysis to generate a continuous delivery-engagement score for each tumor region. Importantly, pharmacodynamic readouts such as cleaved caspase-3 and γH2AX were evaluated in a blinded manner. Results: Across fourteen matched tumor samples, the analysis revealed a consistent pattern linking spatial drug behavior with early biological response. Regions showing strong spatial convergence between payload localization and antigen-rich tumor pockets exhibited significantly higher apoptotic signaling. Tumors displaying coherent payload influx along perfused vascular corridors were more likely to show downstream pharmacodynamic activation, regardless of their bulk target expression. In addition, microenvironments enriched for dendritic cells, CD8+ T cells, and interferon-responsive stromal states demonstrated enhanced sensitivity to the ADC even before radiographic change. When integrated into a unified spatial competency score, these features correctly classified early responses in eleven of fourteen samples. Conclusion: This study shows that a spatial PK/PD framework can predict ADC response by capturing the coordinated alignment of delivery, target engagement, and microenvironmental readiness within tissue. These findings provide a mechanistically grounded, clinically relevant approach for improving patient selection and advancing predictive biomarker strategies for next-generation ADCs. Citation Format: Corinne Ramos, Martha Baydoun, Sandra Delebecq, Amandine Gerstenberg, . A spatial PK/PD framework predicts ADC response in solid tumors by integrating drug delivery, target engagement, and microenvironmental readiness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7145.

Authors

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-7145
Primary Topic
HER2/EGFR in Cancer Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 7145: A spatial PK/PD framework predicts ADC response in solid tumors by integrating drug delivery, target engagement, and microenvironmental readiness

Amandine Gerstenberg, Sandra Delebecq, Martha Baydoun, Corinne Ramos
Cancer Research
HER2/EGFR in Cancer Research
article

Abstract 7145: A spatial PK/PD framework predicts ADC response in solid tumors by integrating drug delivery, target engagement, and microenvironmental readiness

Amandine Gerstenberg, Sandra Delebecq, Martha Baydoun, Corinne Ramos
article en

Abstract

Abstract Background: Antibody-drug conjugates achieve their effect only when payload delivery, target accessibility, and microenvironmental readiness align within the tumor. Conventional biomarkers capture fragments of this biology, but not the spatial interplay that ultimately determines response. To address this gap, we conducted a translational spatial PK/PD study to determine whether high-resolution tissue mapping could predict early ADC activity in solid tumors. Methods: Tumor biopsies from patients and PDX models treated with a clinically relevant ADC were analyzed using an integrated spatial PK/PD workflow. Quantitative payload imaging by mass spectrometry imaging was combined with spatial proteomics and transcriptomics to map antigen distribution, stromal architecture, vascular organization, immune niches, and early pharmacodynamic activation. All data modalities were spatially registered and modeled using AI-based neighborhood analysis to generate a continuous delivery-engagement score for each tumor region. Importantly, pharmacodynamic readouts such as cleaved caspase-3 and γH2AX were evaluated in a blinded manner. Results: Across fourteen matched tumor samples, the analysis revealed a consistent pattern linking spatial drug behavior with early biological response. Regions showing strong spatial convergence between payload localization and antigen-rich tumor pockets exhibited significantly higher apoptotic signaling. Tumors displaying coherent payload influx along perfused vascular corridors were more likely to show downstream pharmacodynamic activation, regardless of their bulk target expression. In addition, microenvironments enriched for dendritic cells, CD8+ T cells, and interferon-responsive stromal states demonstrated enhanced sensitivity to the ADC even before radiographic change. When integrated into a unified spatial competency score, these features correctly classified early responses in eleven of fourteen samples. Conclusion: This study shows that a spatial PK/PD framework can predict ADC response by capturing the coordinated alignment of delivery, target engagement, and microenvironmental readiness within tissue. These findings provide a mechanistically grounded, clinically relevant approach for improving patient selection and advancing predictive biomarker strategies for next-generation ADCs. Citation Format: Corinne Ramos, Martha Baydoun, Sandra Delebecq, Amandine Gerstenberg, . A spatial PK/PD framework predicts ADC response in solid tumors by integrating drug delivery, target engagement, and microenvironmental readiness [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7145.

Cancer ResearchVol. 86(7_Supplement)
Good health and well-being
Openalex Percentile: Top 8%
HER2/EGFR in Cancer Research
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.