In this post of our "Ask the Experts" series, we provide comprehensive answers to frequently asked questions regarding the practical applications of HUB Organoid-based immune cell co-cultures in the field of immunotherapy development. Our responses cover a range of pertinent topics, including our co-culture platform for T cell testing, the immuno-oncology biobank we utilize, and our successful collaboration with Gadeta in evaluating the effectiveness of GDT002—an engineered T cell therapy designed to target CD277 in solid tumors.
The questions are expertly addressed by Dr. Sylvia Boj (SB) from HUB Organoids and Dr. Andrea Bisso (AB) from our esteemed partner, Gadeta.
SB: Our immuno-biobanks began recently. In the context of colorectal (CRC) models, we have a dozen models from which we have isolated tumor-infiltrating lymphocytes (TILs), and in non-small cell lung cancer, we have around five models. In a subset of this CRC immuno-oncology (I–O) models, we have isolated cancer-associated fibroblasts (CAFs). We are also interested in indications like bladder and head & neck cancers, where we see a lot of interest in I–O. Patient-derived biobanks are not limited to particular indications – we can develop specific biobanks depending on need.
SB: We have different service offerings. I would advise anyone interested in our services to contact our business development (BD) team and explain the mechanism of action and the area in which your compound is developed. Our team can offer different solutions and approaches, either from existing assets or ones that require further development. Our strong scientific team can address any challenge and offer a solution.
SB: One challenge we face is that when we receive the tissue to establish the organoid, we know that there are interests for different tumor antigens but performing a complete analysis on the tissue to make comparisons is difficult. At a basic level, we must use immunohistochemistry, which is not quantifiable but can confirm that the tissue expresses a specific antigen. Then, we can confirm it is also expressed on organoids with flow analysis. If there is a particular application in which this is an important question, we could run a project in which we get new tissue for PDO generation. While establishing the organoids, we can characterize the original tissue using flow analysis. It is outside our standard activities, but we can address this.
SB: The culture conditions for expanding organoids were first established by culturing healthy cells to ensure we could expand stem cells, proliferative cells, and other cell types. We use the same principles to establish the tumor model. We believe that because there is no high selection pressure, we can maintain the original tumor heterogeneity in organoids. When the first tumor biobanks were generated, original tissue and derived organoids were sequenced. In most cases, there was more than 80% overlap between driver mutations detected in original tissue and organoids. Of course, tumors are, by definition, genetically unstable, but we know that culture conditions do not drive this genetic instability. When working with tumor-derived organoids, we recommend expanding them for a maximum of 5–6 passages, as an average and depending on the model. We do not recommend expanding a tumor model for a year because it can vary too much from the original tumor. However, 2–3 months of expansion and cryopreservation can allow us to preserve the genetic landscape that the original tumor contained.
AB: To characterize γδTCR tumor reactivity we proceed with a step-by-step approach. We start with tumor cell lines in vitro for the first layer of investigation. As soon as possible, we move selected γδTCRs into more clinically relevant models. For this, our collaboration with HUB is beneficial. Most of our γδTCRs can recognize broadly different tumor types, so we want to narrow down the tumor types that can be selected to be used in an initial clinical trial. We also would like to understand whether there is a genetic setting that is preferentially targeted. For both of these aspects, the use of organoid models provides valuable information and will certainly be included in our strategy.
AB: Our first layer of characterization of γδTCRs is a screen for lack of cross-reactivity against a large set of healthy primary cells to ensure there is not recognition of healthy vital tissues. Then, we test a set of tumor models, including organoids, to show that tumor cells are killed. In the next steps, we use mixed toxicology and pharmacology models with primary material from patients, to show specific killing of tumor cells, sparing the normal tissues in the samples.
AB: It is true that in most of the models, there is a potential allogeneic reaction due to human leukocyte antigen mismatch. To control for this, we use either untransduced T cells, or our recently developed set of control TCRs that are engineered to not recognize tumor tissues. These two controls can be used for measuring the background level of possible allogenic activity.
SB: When we perform our screens, the organoids are not single cells but structures. The average size of these organoids in our screening assays is ~50–70 μm in diameter. We use confocal microscopy in a high throughput format for imaging. As we are developing the technology, we are also working on selecting the best imaging platform for our data. There are several publications from different labs that can achieve good-quality imaging data from screens performed on organoids. We do not see imaging as a limitation.
SB: Yes, this is possible. In our co-culture assays, we have control of activated T cells, but we have set up cocultures where, for example, we wanted to evaluate tumor reactivity on TILs isolated from tumors without preactivating the cells. We have seen a response with this, so it is possible to see cell activity.
SB: The developments we are working on in I–O and inflammatory diseases by combining organoids with other cell types is an exciting areas. Our organization is also putting effort into validating the predictive value of organoids to show that organoids can predict patient response. A solution in the industry could be to run ‘avatar’ clinical trials with organoids before moving into patients to identify the patient populations likely to succeed in clinical studies. We believe that our technology will significantly contribute to this, and we are putting great effort into this.