Life Sciences 2019 - Multimodal ImagingLS19-018

Deciphering breast cancer heterogeneity and tumor microenvironment with correlative imaging

Principal Investigator:
Co-Principal Investigator(s):
Goran Mitulovic (Medical University of Vienna)
Lukas Kenner (University of Veterinary Medicine Vienna)
Ongoing (01.05.2020 – 30.04.2024)
Funding volume:
€ 698,870

Breast cancer is a disease with different manifestations and disease courses, which are determined by genetic changes and the immediate environment of the tumor. Oxygen deprivation of the tumor leads to the formation of new blood vessels, changes in tumor metabolism, and the development of an aggressive tumor type that often does not respond to therapy and leads to higher mortality rates. Currently, neither surgical nor imaging techniques can fully capture the complexity of the tumor and its environment. The goal of this project is to provide detailed imaging of tissue typing and tumor environment by combining state-of-the-art imaging and innovative microscopic techniques to identify aggressive tumors that require more intensive therapy. This will involve combining non-invasive imaging with PET/MRI with molecular tumor profiling from three state-of-the-art spectrometric (MALDI mass spectrometry (M-MSI), mass cytometry (CyToF) and multispectral imaging (MS)) methods linked by artificial intelligence. In the future, this will allow accurate prediction of breast cancer aggressiveness with imaging alone and lead to a reduction in invasive tissue sampling. The establishment of this visionary concept will also allow a significant step towards individualized breast cancer therapy.

Scientific disciplines: Molecular biology (34%) | Machine learning (33%) | Magnetic resonance imaging [MRI] (33%)

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