Biomechanics in health and disease:
advanced physical tools for innovative early diagnosis
H2020-MSCA-ITN-2018 n. 812772


Mechanical and rheological phenotype of cells and tissues: medical aspects of mechanics in diseases

Duration: months 2-40

Lead beneficiary: IBEC

Objectives: To provide a comprehensive assessment and evaluation of the mechanical and rheological phenotypes of cells, ECMs, and tissues, and their relation to diseases.

Task 1.1. Determination of diseases, in which mechanics plays a crucial role, and characterization of the mechanical features.

Task leader: OSR

This task will be initially based on neoplastic diseases known by the clinical partners, from human lung, colon, kidney, liver, bladder, breast, and prostate. Solid tumours will be classified based on TNM staging system (UICC 8th edition), and grouped as invasive vs non-invasive phenotype. This first classification will be used for associating nano-rheological measurements of bio-specimens (Tasks 1.2-7) with invasion; further sub-classification of tumour might be applied to identify whether rheological measurements associate with the progression of tumour through the tissue layers. Paired neoplastic and non-neoplastic tissues will be used; both will be divided and used i) as tissue (fresh), or ii) to isolate tissue-derived extracellular matrix (ECM) for the nano-mechanical/rheological measurements, and also iii) stored for different complementary analysis, as needed, such as gene analysis and/or gene expression (exploiting the link of IFJPAN and JUMC with the Omicron project in Collegium Medicum in Krakow:, as well as for localized proteomic analysis using the MALDI Imaging unit at UB. Samples will be prepared – here and in the following tasks - according to indications emerging from WP3, including advanced fixation strategies, and possibly allowing comparative nano-rheological studies. This task will allow identifying rheological parameters to be associated with tumour invasion, and eventually with the genetic signature of the non-invasive/invasive phenotype, thus validating the identification of rheological parameters as diagnostic and prognostic tools. This approach will be advantageously completed by a future clinical study confronting these approaches to Ultrasonic Elastography or Magnetic Resonance Elastography. 

Task 1.2. Determination of the rheological phenotype of cells, tissues and ECMs.

Task leader: IBEC

The viscoelastic response will be assessed using small amplitude oscillations at constant indentation at various frequencies. This task will be carried out on sample bio-specimens (cell lines, animal models, tissues...). This will provide fundamental understanding of the micro-rheology of cells and tissues associated with diseases. This task is complementary to task 6.2, but will provide more basic, yet complementary, information about the bio-specimens. 

Task 1.3. Determination of the effect of the microenvironment (substrate elasticity, confinement, biochemical composition, density...) on the mechanical response of the cell.

Task leader: CNRS

Different cell culture strategies will be used to mimicking both physiological and clinical environments. In parallel with WP3. 

Task 1.4. Identification of parameters beyond Young’s modulus to describe viscoelastic properties.

Task leader: IBEC

Identification of parameters such as storage and loss moduli, loss tangent, power law exponent..., and their representation and interpretation as possible markers. This task is complementary to WP2, WP5 and WP6.

Task 1.5. Determination of time dependent alterations of Young`s moduli.

Task leader: WWU

Mechanical dynamics will be assessed using repetitive loadings (0.1-10Hz). The resulting Young’s moduli-time relation could serve as a mechanical marker (amplitude / frequency, phase shift) reflecting cellular dynamics in a more complex and quantitative way. Different cell lines and tissues will be tested in various conditions to gain insight in mechanical characteristics and to discriminate between normal and diseased cells.

Task 1.6. Collection of viscoelastic parameters of particular bio-specimens to form a database of the mechanical fingerprint of diseases.

Task leader: CNRS

Viscoelastic data will be assessed for incorporation as a complement to the mechanical fingerprint database described in WP6.