Classic Hodgkin Lymphoma (cHL) is characterized by the presence of abnormal large cells known as Hodgkin Reed-Sternberg (HRS) cells. Curative intent chemotherapy has a 90% response rate, but for refractory patients, current immunotherapies remain insufficient. Ongoing research aims to enhance therapy and patient outcomes by focusing on the tumor microenvironment (TME), a complex environment that includes diverse non-malignant cells, including immune cells, which constitute a critical component of the TME. Utilizing multiplex analysis to comprehend these intricate interactions can pave the way for identifying novel strategies to combat cancer more effectively. CD30-targeted therapies and PD1/PDL1 inhibitors are under investigation clinically and could potentially benefit from adding checkpoint markers such as TIM-3 to enhance patient outcomes by addressing T-cell exhaustion. Such combination strategies will require assays and analysis strategies that can describe both spatial and multi-marker data. Multiplex immunofluorescence (mIF) is a valuable tool for analyzing spatial biology, patient selection, mechanism of action, pharmacodynamics and biomarker assays predictive of response. Describing the relationship between T cell exhaustion and response in cHL may guide the development of targeted treatments aimed at restoring the immune system's ability to recognize and eliminate cancer cells.
Twenty-five to thirty percent of cHL patients with advanced stages do not respond to standard therapies. To understand the mechanisms of resistance, we developed a mIF panel (CD4, CD8, CD30, PD-1, PD-L1, and TIM3) for formalin-fixed and paraffin-embedded cHL tissues on the OPAL Tyramide Signal Amplification system and the Leica Bond RX. A set of commercially sourced cHL whole tissue samples (n=5) were used to develop and validate the panel, with qualitative evaluations by a Hematopathologist affirming that the mIF and 3, 3'-diaminobenzidine (DAB) staining yielded comparable results. Subsequently, a cohort of cHL samples (n=34) were stained and underwent exploratory image (Halo) and data (Microsoft Excel and R Studio) analyses.
The image analysis strategy includes cell segmentation and phenotyping for all markers in the panel, identifying individual cell populations and multi-marker co-expressing cell populations. Additionally, spatial analysis describes the relationships between key phenotypes in the TME. The quantity of exhausted T cells, their average distance to HRS cells and the average count of exhausted T cells within different proximities of HRS cells will be presented.
The development of this mIF assay for cHL demonstrates its consistent application at a mid-scale level across a diverse patient population with varying medical backgrounds and treatment histories. This approach provides a deeper understanding of immune response diversity and cellular composition within cHL. Future deployment of the panel against clinical trial samples with outcomes and responses will yield further insights.
Riley-Burns:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Surace:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Lesley:AstraZeneca: Current Employment, Current equity holder in publicly-traded company; Amgen: Current equity holder in publicly-traded company. Kositsky:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Munugalavadla:Gilead Sciences: Current equity holder in publicly-traded company, Other: A family member is an employee and stockholder of Gilead Sciences.; AZN: Current equity holder in publicly-traded company, Other: Stock in publicly-traded company; AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Chiu:AstraZeneca: Current Employment. Auclair:AstraZeneca: Current Employment, Current equity holder in publicly-traded company. Palmer:AstraZeneca: Current Employment, Current equity holder in publicly-traded company.
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