Background The Tumor Microenvironment (TME) can orchestrate tumor progression, metastasis and the development of therapeutic resistance through a variety of mechanisms. Specifically, TME can impair response to therapy by modulating evasion of tumor cells from immune surveillance. Improving our understanding of how different immune cell populations shape the TME and impact therapeutic response becomes crucial to improve patient outcomes.

When an immunotherapy test agent reaches pre-clinical stages, the use of clinically and biologically relevant models is crucial. However, current preclinical models may suffer from the lack of a comprehensive characterization of the TME of the selected cancer models.

In order to overcome this limitation, Champions Oncology leveraged transcriptomic data from its proprietary bank of TumorGraft models to develop a signature to predict immune infiltration. This signature was validated by confirming the predicted immune infiltration phenotype through histological analysis of PDX models grown in humanized mice, harboring a fully reconstituted human immune system.

Among the variety of pre-clinical models, patient derived xenograft (PDX) models are recognized as an accurate and clinically relevant system for pre-clinical studies.^{1 2}

Methods For these reasons Champions Oncology built the pre-clinical research on a deeply characterized PDX bank. The characterization through multi-omic datasets includes cutting edge technologies such as next generation sequencing (WES and RNAseq) proteomics, phosphor-proteomics, kinase activity and patient’s historical treatment data.

To identify a molecular signature predictive of immune infiltration, we analyzed Champions PDX by leveraging proprietary and public computational methods. Among the different computational tools, we leveraged xCell³ to perform cell type enrichment analysis on 64 immune and stroma cell types. In parallel, mice were humanized using different strategies⁴ and PDXs were implanted in hosts harboring a fully reconstituted human immune system. Then, PDX tissues were collected from humanized mice and stained for the major immune populations.

Results Immunohistochemistry analyses confirmed a strong correlation between predicted infiltration and positive staining.

The application of this method to Champions bank of models enabled a comprehensive knowledge of the immune profile of our entire bank, and the definition of a gene signature predictive of immune infiltration. The histological analysis of the different identified populations composing the TME validated the computational findings, therefore providing an immune atlas of our PDX bank.

Conclusions These data support the use of our pre-defined molecular signature allowing the paring of ideal model systems with appropriate humanized hosts for future preclinical studies.

References

1. Proietto M, et al. Tumor heterogeneity: preclinical models, emerging technologies, and future applications. Front Oncol 2023;13:1164535.

2. Izumchenko E, et al. Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors. Ann Oncol 2017;28:2595–2605.

3. Aran D, Hu Z, Butte AJ. xCell: Digitally portraying the tissue cellular heterogeneity landscape. Genome Biol 2017;18:1–14.

4. De La Rochere P, et al. Humanized Mice for the Study of Immuno-Oncology. Trends Immunol 2018;39:748–763.

Ethics Approval All human biological samples utilized for the research described in this abstract have been procured or collected after an Informed Consent form has been issued according to the current local legislation. All animals studies described in this abstract have been conducted under Champions’ approved IACUC.