PECAN RESEARCH PROJECT

Parameterisation of large scale cancer models for personalised therapy of triple negative breast cancer

ABOUT THE PROJECT

The overall goal of PeCaN is the systematic improvement/parameterisation of computer models required to truly personalise drug therapy in cancer and their preclinical validation and clinical evaluation for future clinical trials.

Artificial Intelligence (AI)

Single-cell transcriptomics/proteomics

CRISPR-based cell genetics

The overall goal of PeCaN is the systematic improvement/parameterisation of computer models required to truly personalise drug therapy in cancer and their preclinical validation and clinical evaluation for future clinical trials.

With a focus on TNBC, a tumour entity with a high socio-economic impact and high unmet medical need, PeCaN will combine Artificial Intelligence (AI), single-cell transcriptomics/proteomics and CRISPR-based cell genetics to parameterise a large-scale computational model for personalising therapy choice in individual patients, and to identify new drug targets and biomarkers.

Candidates and predictions will be validated clinically, using patients from multiple clinical sites to evaluate the new clinical decision support system, and to initiate future prospective trials for TNBC for validating relevant biomarker/drug combinations.

To support the translation of the proposed model-based approach, an in-depth Health Technology Assessment (HTA) will be carried out, covering normative, regulatory and economic aspects.

READ ABOUT THE PROJECT

Specific objectives of the PeCaN project

Generation of knockout and overexpression variants

Generation of knockout and overexpression variants of all genes coding for components of our current tumour models (ModCell^TM), within TNBC-derived cell lines using CRISPR-based techniques.

Analysis of gene knockout/overexpression effect

Analysis of gene knockout/overexpression effects using single cell guide RNA, transcriptome and model ‘surfaceome’ sequencing (CROPseq, REAPseq).

Parametrisation of the tumour models

Parametrisation of the tumour models using project generated and publically available data (CCLE, Broad etc.), and identification of the parameter sub-space providing optimal predictions of all data in a test set.

Identification of potential drug targets

Identification of potential drug targets and response biomarkers using sensitivity analysis/systematic analysis of knockout/overexpression effects, for preclinical and clinical evaluation.

Clinical evaluation of predictions

Clinical evaluation of predictions using prospective patient data, as a basis for future clinical trials.

Investigation of the clinical translation

Investigation of the clinical translation potential of PeCaN, including development of a Health Technology Assessment (HTA) encompassing normative, regulatory and economic aspects.

PeCaN Consortium: 6 partners from 4 different countries

The PeCaN consortium is led by the Transilvavia University Brașov, and comprises 6 partners from 4 different countries, including two universities, a research organisation, a university hospital, a clinical centre and an SME. Together these partners provide the required inter-disciplinary and complementary expertise covering the full value chain from the basic science, technology development, computational modelling to clinical expertise required for the project.