Microenvironmental reorganization in brain tumors following radiotherapy and recurrence revealed by hyperplexed immunofluorescence imaging.
Spencer S WatsonBenoit DucZiqi KangAxel de TonnacNils ElingLaure FontTristan WhitmarshMatteo Massaranull nullBernd BodenmillerJean HausserJohanna A JoycePublished in: Nature communications (2024)
The tumor microenvironment plays a crucial role in determining response to treatment. This involves a series of interconnected changes in the cellular landscape, spatial organization, and extracellular matrix composition. However, assessing these alterations simultaneously is challenging from a spatial perspective, due to the limitations of current high-dimensional imaging techniques and the extent of intratumoral heterogeneity over large lesion areas. In this study, we introduce a spatial proteomic workflow termed Hyperplexed Immunofluorescence Imaging (HIFI) that overcomes these limitations. HIFI allows for the simultaneous analysis of > 45 markers in fragile tissue sections at high magnification, using a cost-effective high-throughput workflow. We integrate HIFI with machine learning feature detection, graph-based network analysis, and cluster-based neighborhood analysis to analyze the microenvironment response to radiation therapy in a preclinical model of glioblastoma, and compare this response to a mouse model of breast-to-brain metastasis. Here we show that glioblastomas undergo extensive spatial reorganization of immune cell populations and structural architecture in response to treatment, while brain metastases show no comparable reorganization. Our integrated spatial analyses reveal highly divergent responses to radiation therapy between brain tumor models, despite equivalent radiotherapy benefit.
Keyphrases
- radiation therapy
- machine learning
- high resolution
- extracellular matrix
- single cell
- high throughput
- network analysis
- locally advanced
- mouse model
- small cell lung cancer
- brain metastases
- radiation induced
- early stage
- stem cells
- physical activity
- squamous cell carcinoma
- deep learning
- artificial intelligence
- electronic health record
- multiple sclerosis
- fluorescence imaging
- big data
- mesenchymal stem cells
- convolutional neural network
- resting state
- bone marrow
- quantum dots