For the MACAROM project, a biobank of breast cancer PDOs was generated using a protocol that was optimized during one year.
Several experiments were then performed in order to demonstrate the closeness of these PDOs to their tissue of origin, which is an essential condition to their use in a preclinical setting. Precisely, we performed a comparison of breast cancer PDOs with their tissues of origin using a technology called ‘mass cytometry’ that allows to quantify the protein expression of each sample at the single-cell level. This approach revealed that breast cancer PDOs recapitulate the main protein expression features of their tissues of origin and that PDOs formation can be predicted using the expression of only two proteins of the primary tissue.
Single-cell RNA sequencing of the breast cancer PDOs was also performed in order to better capture the whole expression profile of the generated tissues. This experiment uncovered the fact that every PDOs sample had a unique expression profile which is reminiscent of the intertumor heterogeneity observed in primary tumors. Moreover, comparison to our breast cancer PDOs dataset to external primary tissues datasets revealed that breast cancer PDOs recapitulate the main breast cancer lineages expression profiles observed all breast cancer primary tissues datasets tested.
We also inferred the CNV profiles of our generated PDOs to perform a quality control aiming at ensuring that our PDOs are cancer tissues. This experiment confirmed that breast cancer PDOs contained massive CNV alterations compared to the healthy breast tissues that was used in control.
After performing all these quality checks to ensure that our generated PDOs samples are of the highest quality, we did a screening using 43 drugs targeting the main cancer-related proteins. This experiment will show the ability of each breast cancer PDOs to respond or resist to these 43 anticancer drugs, and will make allow us to study the drug response of cancer models that recapitulate their tissue of origin at the single-cell level. Moreover, this study will also include the RNA profile of the untreated breast cancer PDOs and the clinical data of each patient to evaluate if these data can be used to predict the response to specific drugs.
The results of the MACAROM project were presented in different conferences and events. I attended the ETH retreat in Davos and Single-cell Genomics 2022 in Utrecht which gave me the opportunity to communicate my results and get the scientific community’s attention. I also presented my work in regular meetings in the University of Zurich department seminars, the ETH department seminars and the PATH ‘Patients Tumors Bank of Hope’ meetings which all allowed me to directly reach the potential users of the results of the project as the audience was mostly made of clinicians and researchers in cancer biology.
More international conferences will be attended to ensure the international dissemination of the MACAROM project.
The results of the project will also be published in different scientific journals. We will be split the results into two different manuscripts which will be submitted for publication in the coming months. The first study will be about the generation of high-quality breast cancer PDOs and is almost ready to be submitted. The second study will be about the screening and will take more time to be prepared and submitted, it will be submitted at the end of this year.
Other planned dissemination activities will be implemented once the results of the project are finalized. A website will be created as the core of the ‘mapping’ concept. This will allow anyone to access the data in a simple and interactive way in order to see the correspondence between sample information, RNA profiles, drug response and clinical data. This will be presented in a way that is easily understandable and that highlights the fact that results can be referenced in order to help guide future patients’ treatments.
