Challenge: Extensive characterization of tumors is central to the development of personalized therapies such as immunotherapy, now considered one of the most promising approaches to cancer treatment. The capability to detect a multitude of biomarkers simultaneously on the same tissue section would provide unprecedented headways in the field of cancer research and particularly on tumor profiling. While allowing a greater understanding of disease heterogeneity and a better characterization of the mechanisms that drive disease course and resistance to therapy, it will also allow to correctly select and adapt the right therapy.

Solution: Here, the team proposes a novel approach to provide an improved method to study multiple molecules, simultaneously in the same tissue section. The research team aims to develop a Raman-based multiplex histopathology platform to simultaneously detect up to 15 breast cancer and immunotherapy-related biomarkers to guide personalized treatments for breast cancer patients. The platform will be composed of Raman labels-single walled carbon nanotubes coupled to specific antibodies targeting proteins implicated in breast cancer. The team will also develop an imaging system to detect all 15 unique Raman signals simultaneously. The multiplex Raman imaging data will be validated against pathological staining of the same tissues using regular immunohistochemistry or immunofluorescence.

Expected Achievements/Impact: This novel multiplex immunohistochemistry platform will offer many advantages over existing technologies including cost reduction and a reduced quantity of biological material required. Mostly, this novel platform will be a new tool for researchers and pathologists to provide improved diagnostic classification, guidance on clinical outcome and further develop personalized therapy for breast cancer tumors. This project is part of a larger development led by Photon etc. that will provide a complete platform for multiplexed tumor profiling. Photon etc. will develop the automated instrument and complement the development of the 15 Raman labels proposed in this project.