RESISTANCE UNDER COMBINATORIAL TREATMENT IN ER+ AND ER- BREAST CANCER.

Projektinformationen

RESCUER

ID Finanzhilfevereinbarung: 847912

DOI

10.3030/847912

Projekt abgeschlossen

EK-Unterschriftsdatum 22 November 2019

Startdatum 1 Januar 2020

Enddatum 31 Dezember 2025

Finanziert unter

• SOCIETAL CHALLENGES - Health, demographic change and well-being

Gesamtkosten

€ 6 283 250,00

EU-Beitrag

€ 6 000 000,00

Koordiniert durch

UNIVERSITETET I OSLO
Norway

Periodic Reporting for period 3 - RESCUER (RESISTANCE UNDER COMBINATORIAL TREATMENT IN ER+ AND ER- BREAST CANCER.)

Berichtszeitraum: 2023-01-01 bis 2024-06-30

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

What is the problem/issue being addressed?
Some patients do and others do not benefit from combination therapies (chemotherapy combined with immune therapy or with targeted anti-angiogenesis treatment). We will study this by integrating multi-omics data from clinical trials (treatment resistance signatures) and use this information to predict response up front and to design effective combination therapies.

Why is it important for society?
Breast cancer is the most common type of cancer among women. A fraction of the breast cancers has either no good therapeutic offer (TNBC) or experience a late relapse often presenting with metastatic disease. This is a small fraction of all breast cancers, but on the overall a large number of cases. Our trial study the most common treatment modalities, chemotherapy and hormonal therapy. The revenue of Arimidex alone is millions of US dollars yearly. The most expensive drug is the one that does not work. Identifying the best combination and dosage for every woman will safe money and lives.

What are the overall objectives?
The general objective of this project is to discover effective treatment combinations for individual/subgroups of breast cancer patients through the assessment and validation in vivo, in vitro, and in silico of mechanisms of treatment resistance at cellular/sub-cellular level. RESCUER will integrate and analyze existing and newly generated clinical and multi-omic data and biological samples from ongoing clinical trials to identify the physiological characteristics of non-responders vs. responders and to suggest clinically effective personalized drugs combinations.

Identify which new combinations of existing drugs have a high probability to work on individual or thin strata of patients and propose them for further investigation.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

During the third reporting period we have produced signatures of response based on integrating the clinical and molecular data studies of chemotherapy, immune and hormonal therapy of breast cancer. Following the principles of open-source methodology we selected Open Microscope Environment Remote Objects (OMERO) software as the data management database infrastructure. Mass spectrometry data independent analysis (DIA) proteomics has been generated for clinical trials with immunotherapy. (ALICE and ICON) We have started and performed method called thermal protein profiling (TPP) to identify off-targets of the aromatase inhibitors from the NeoLetExe clinical trial.

We have established a platform of hormone receptor (HR) positive or HR-negative PDX models showing different sensitivity towards standard therapies. For mechanistic studies we have established/got access to isogenic pairs of TNBC PDXs showing sensitivity or resistance, respectively, to commonly used chemotherapies. We have also adjusted the PDEC platform for clinical biopsy samples by utilizing a biopsy system (Semi-Automatic Biopsy System - Adria Medical healthcare products) for the primary breast cancer specimen in the lab.

Several important publications were finalised in this third reporting period on modelling through a validated a mechanistic model for combined aromatase and cdkCDK4/6 inhibitor treatment of ER+ breast cancer. A number of approaches for Bayesian modelling of synergistic interaction effects in in vitro drug combination experiments have been published and validated in custom drug libraries in this period. All these achievements are either published in high rated journals or in a form of manuscript. This gives a good ground for the next reporting period.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

What we want to achieve ultimately is treatment decision based on response predictions based on mathematical modeling of tumor imaging and molecular measurements, which will come in addition to the current guidelines and are therefore beyond the current state of the art. We have finalized four such models and other five for synergy prediction of combinatorial treatment, which we hope to move forward into implementation through innovation initiatives of the health authorities or innovation grow houses at the University of Oslo.

Rescuer Semi-Annual Spring Meeting 2023, Venice, 02-04.05.23

RESCUER kick-off 26-28.01.20

RESCUER Annual meeting 2024, June 9-11, Balchik, Bulgaria

RESCUER Semi-Annual meeting 2022 Barcelona 27-29.04