Multiplexed spatially resolved tissue biomarkers for optimal use of PD-1 axis blockers and PARP inhibitors in cancer.
- Institution
- Yale University, CT
- Principal investigator
- Kurt A Schalper
- Funding
- $251K
- Duration
- 2025–2027
Moonbase score
Still being scored
Abstract
Project summary/abstract. Current predictive biomarkers for immune checkpoint blockers have multiple limitations, and selection of patients with the highest benefit potential for immunotherapy alone or in combination with other agents is an unmet need. Tumors harboring DNA repair defects display increased sensitivity to agents targeting such pathways such as PARP1/2 inhibitors. Predictive biomarkers for such therapies rely on DNA/genomic analysis that is limited by the dependency of tumor content in samples, lack of annotation of the variants' significance in multiple DNA repair genes, and the occurrence of DNA repair alterations due to non-genomic events. Notably, immunotherapies are active in patients with malignancies harboring DNA repair defects and the efficacy of PARP inhibitors requires adaptive anti-tumor immune responses in preclinical models. This has raised interest in combining these agents. Here and through 2 complementary aims, we will validate multiplex quantitative immunofluorescence (mQIF) assays for spatially resolved measurement of key immune metrics and homologous recombination-deficiency (HRD) proteins in conventional formalin-fixed paraffin-embedded tumor biopsies. These markers are non- redundant and complementary with existing biomarkers. In Aim 1 (UH2), we will analytically validate and standardize two mQIF assays for measurement of anti-tumor immune responses (Assay #1: DAPI/CK/PD- L1/CD8/CD20) and HRD metrics (Assay #2: DAPI/CK/H2AX/RAD51/BRCA1). In Aim 2 (UH3), we will determine the pharmacodynamic and predictive biomarker role of the mQIF assays measuring anti-tumor immune responses and HRD metrics in 3 independent clinical trials using PARP inhibitors and/or PD-1 axis blockers. Together, these studies have the potential to expand the repertoire of predictive biomarkers for novel anti-cancer treatments and positively impact patients' outcomes. We have assembled a team of investigators with complementary expertise and will access unique laboratory/technical and clinical trial resources to accomplish the proposed work. The use of advanced analytical controls, cross validation of results in multiple studies and rigorous statistical definitions will support the scientific quality and success of the study.
Research team
- Patricia M. LorussoPI
- Kurt A SchalperPI
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