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Published on: April 11, 2016
Precision Oncology Program (POP), an observational study using real-world data and imaging mass cytometry to explore
Laura Amanda Boos1, Christian Doerig2, Gabriele Gut1,3
1Department of Medical Oncology and Hematology, University Hospital Zurich, Zurich, Switzerland.
Introduction:
Precision oncology aims to provide individualised treatment recommendations based on patient-specific characteristics. In this rapidly evolving field with increasing numbers of biomarkers and potential therapeutic targets, there is a growing unmet need for evidence guiding these individualised treatment recommendations. The Precision Oncology Program (POP) harnesses real-world data (RWD) and imaging mass cytometry (IMC) to evaluate the feasibility and utility of integrating different data modalities to inform personalised treatment recommendations. This program uses patient-matched clinicogenomic data and spatial single-cell proteomics analysis to support profiling-driven decision-making for patients with cancer at the Molecular Tumor Board.
Methods And Analysis:
The collaborative POP project recruits patients across all tumour entities and stages at the Comprehensive Cancer Center Zurich (CCCZ). For patients in the POP, a clinically and molecularly matched cohort is identified within the nationwide (US-based) de-identified Flatiron Health-Foundation Medicine clinicogenomic database (CGDB). It assesses whether clinical, genomic and outcome data of the CGDB cohort can inform treatment recommendations. In addition, multiplexed imaging mass cytometry (IMC) is performed in formalin-fixed paraffin-embedded tissue to assess the potential impact of spatial proteomics on personalised treatment decisions. RWD and IMC information is reviewed in the Molecular Tumor Board to assess the potential impact of this information on therapy decisions. However, since this is an observational study, these additional recommendations remain nonprescriptive and will not be forwarded to the treating physician.
Ethics And Dissemination:
The study is registered at ClinicalTrials.gov (NCT06680726) and approved by the Canton of Zurich Ethics Committee (Project ID: 2022-02289). Project-specific informed consent is obtained from all participants. Deceased patients may also be included. In this case, a signed general consent form must be available. Data privacy is ensured by unique patient numbers for pseudo-anonymised data. Study findings will be disseminated through international peer-reviewed journals, conferences, and direct communication with participants and relevant organisations.
Trial Registration Number:
NCT06680726.
Insights
The Precision Oncology Program integrates real-world data and imaging mass cytometry to guide personalized cancer treatment. This approach aims to improve decision-making by combining clinicogenomic and spatial proteomic data for individual patient care.
Area of Science:
- Oncology
- Bioinformatics
- Proteomics
Background:
- Precision oncology requires robust evidence for individualized treatment recommendations.
- Increasing biomarkers and therapeutic targets create a need for integrated data approaches.
- The Precision Oncology Program (POP) addresses this by evaluating combined data modalities.
Purpose of the Study:
- To assess the feasibility and utility of integrating real-world data (RWD) and imaging mass cytometry (IMC) for personalized cancer treatment.
- To evaluate if patient-matched clinicogenomic data and spatial proteomics can inform treatment decisions at the Molecular Tumor Board.
- To leverage a nationwide de-identified clinicogenomic database for cohort matching and data analysis.
Main Methods:
- Recruitment of patients across all tumor types and stages at the Comprehensive Cancer Center Zurich.
- Identification of matched cohorts in the Flatiron Health-Foundation Medicine clinicogenomic database (CGDB).
- Performance of multiplexed imaging mass cytometry (IMC) on formalin-fixed paraffin-embedded tissues.
- Review of RWD and IMC data by the Molecular Tumor Board for potential impact on therapy decisions.
Main Results:
- The study is observational, and recommendations derived from RWD and IMC are non-prescriptive.
- The feasibility and utility of integrating clinicogenomic data and spatial proteomics are under evaluation.
- The potential impact of these integrated data modalities on personalized treatment decisions is being assessed.
Conclusions:
- The Precision Oncology Program demonstrates a novel approach to integrating diverse data sources for cancer treatment.
- This program aims to enhance profiling-driven decision-making in precision oncology.
- Findings will contribute to evidence generation for individualized cancer therapies.
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