Research database

REAP - Revealing drug tolerant persister cells in cancer using contrast enhanced optical coherence and photoacoustic tomography

Duration:
48 months (2021 - 2024)
Principal investigator(s):
Project type:
UE-funded research - H2020 - Industrial Leadership – LEIT - ICT
Funding body:
COMMISSIONE EUROPEA
Project identification number:
PoliTo role:
Partner

Abstract

Cancer treatment faces a major problem: it ultimately stops working for many patients because the tumor becomes resistant. The cellular origin of relapse is often linked to drug tolerant persister (DTP) cells, which survive treatment and can remain for years. Because of their scarcity and heterogeneity, the detection of DTP cells remains a technological challenge of enormous clinical importance. The objective of REAP is to develop two next generation multimodal imaging systems to reveal DTPs. A triple modal two-photon laser scanning optical coherence photoacoustic microscopy system will be built for the in vitro characterization of cancer organoids. Additionally, a dual-modality optical coherence photoacoustic tomography system will be implemented to visualize tumors in vivo in a mouse model. To enable greatly increased sensitivity and specificity, a new type of contrast agent based on biofunctionalized nanoparticles with tailor-made optical properties will be fabricated to specifically label DTPs. For improved imaging performance, several further technological advancements are targeted. Photoacoustic excitation will be realized using innovative microchip lasers addressing the needs for high-energy pulses, high-repetition rate, and multi-wavelength emission. To achieve the required resolution, novel photoacoustic detectors based on integrated optical micro-ring resonator technology will be developed with the potential to completely replace conventional piezoelectric ultrasound transducers. Furthermore, image acquisition speed will be increased by an order of magnitude with the help of an innovative laser source based on photonic integrated circuits at 780 nm. Finally, real-time data handling will be explored along with deep learning-based automatic analysis algorithms. The combined innovation in laser sources, detector technology, nanoparticles, and deep learning-based algorithms will create radically new imaging solutions reaching numerous applications.

People involved

Departments

Partners

  • Medical University of Vienna - Coordinator
  • AUSTRIAN INSTITUTE OF TECHNOLOGY GMBH
  • INNOLAS LASER GMBH
  • LAVISION GMBH
  • LIONIX INTERNATIONAL BV
  • PICOPHOTONICS Oy
  • POLITECNICO DI TORINO
  • TAMPERE UNIVERSITY FOUNDATION SR
  • UNIVERSIDAD DE SANTIAGO DE COMPOSTELA

Keywords

ERC sectors

LS4_6 - Cancer and its biological basis
LS7_2 - Diagnostic tools (e.g. genetic, imaging)
PE2_9 - Optics, non-linear optics and nano-optics

Sustainable Development Goals

Obiettivo 3. Assicurare la salute e il benessere per tutti e per tutte le età

Budget

Total cost: € 6,185,978.75
Total contribution: € 6,185,978.75
PoliTo total cost: € 480,151.25
PoliTo contribution: € 480,151.25

Communication activities