Multi-modal image analysis for large scale cancer tissue studies within IMMUcan: multiplex immunofluorescence images
Multi-modal image analysis for large scale cancer tissue studies within IMMUcan: multiplex immunofluorescence images
In cancer research, multiplexed imaging has enabled the in-depth characterization of the tumor microenvironment (TME) and how it relates to patient prognosis. However, standardized, multi-modal data from large numbers of patients to identify robust biomarkers is missing. To provide such data across five cancer indications, the IMMUcan consortium performs broad molecular and cellular spatial profiling of thousands of cancer samples. Two reproducible and scalable workflows have been developed for whole slide multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) to overcome challenges of reproducibility and scalability. For mIF we developed IFQuant, a web-based tool optimized for user-friendliness and reproducibility. This Zenodo record contains the mIF images and IFQuant settings to reproduce the results presented in the referenced publication. The companion IMC dataset is available as a joint Zenodo record.
- University Hospital of Lausanne Switzerland
- University of Lausanne Switzerland
- SIB Swiss Institute of Bioinformatics Switzerland
Breast cancer, multiplex immunofluorescence, Lung cancer, Head and neck cancer, Colorectal cancer, Liver cancer
Breast cancer, multiplex immunofluorescence, Lung cancer, Head and neck cancer, Colorectal cancer, Liver cancer
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