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Minimally invasive bio marker-based cancer diagnostics and treatment prediction

Reference number
Coordinator Karolinska Institutet - Cancer Center Karolinska
Funding from Vinnova SEK 498 000
Project duration April 2016 - January 2017
Status Completed
Venture Challenge-Driven Innovation – Stage 1 initiation

Purpose and goal

The overarching purpose of this project is to improve diagnostics and therapy prediction for patients with breast cancer using methods that provide minimal discomfort for the patient. The specific goal was to investigate a combination of a well-established method to extract cells from tumors (fine needle aspiration, FNA) and new ultra-sensitive methods for multiplexed molecular profiling. We have achieved proof of concept for the applicability of minimal FNA samples for protein analysis by proximity extension assay (PEA), and also by using NanoString (NS) technology (mRNA).

Expected results and effects

Clinical material from >60 patients has been collected and results are very promising. Samples were analyzed using PEA and the NS technology and we show that: (1) FNA-based HER2, ER and Ki67 data is correlated with clinical routine based methodology (benchmarking), (2) that it may be possible to distinguish between cancer and benign lesions in patients who initially had unclear diagnosis, and (3) that it is possible to measure potentially therapy related immune and inflammatory proteins in FNA samples (publishable data), which may pave the way for collaborations with ´Big Pharma´.

Planned approach and implementation

We have identified and worked with key collaboration partners, clinical needs, customers, logistics and ethical demands. Despite structural and organizational obstacles, we have then conducted clinical sampling and analysis and finally achieved technical proof of concept for a new diagnostic and potentially therapy predictive process. Thereby, we have identified significant opportunities for the implementation of new diagnostics, new services and a process for individualized diagnostics and therapy prediction that may be health economically efficient.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 25 November 2019

Reference number 2016-00595

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