Abstract C065: PlastiNet: Understanding the Epithelial - Mesenchymal Transition Through Graphical Attention in Spatial Transcriptomics
Authors: Zamora Izabella L , Parikh Milan , Wright Samuel , Bi Lynn , Patel Bidish , Pe’er Dana , Ting David , Hacohen Nir , Mehta Arnav 
Published: September 2024

Abstract
Plasticity in tumor cells represents the ability of cancer cells to transition between different phenotypic states, including epithelial and mesenchymal states, known as the epithelial-mesenchymal transition (EMT). This transition is critical for processes such as invasion, metastasis, and resistance to therapy. Understanding the dynamics of plasticity and the extrinsic factors influencing state transitions may be crucial for improving therapeutic strategies and patient outcomes. However, deciphering the complex interactions and factors driving these state changes remains challenging. We introduce PlastiNet, a graphical attention-based network (GAT) designed to create spatially aware embeddings that enable the identification of cellular neighborhoods and the plasticity spectrum, despite gene panel limitations. PlastiNet incorporates both self-attention and neighbor-attention mechanisms in its GAT. This approach allows us to account for the influence of surrounding cells in determining the state of a target cell. We validated our model by constructing differentiation paths in healthy colon data, starting from stem cell signatures. The attention mechanisms highlighted known interactions, such as those between fibroblasts and epithelial cells. When applied to pancreatic ductal adenocarcinoma (PDAC) tumors, PlastiNet identified the SPP1-CD44 axis as a potential mediator in the classical-to-basal transition of tumor cells. To further explore the impact of CD44, particularly the isoform switch that occurs during EMT, we studied a patient-derived a PDAC cell line using single-cell RNA sequencing (scRNAseq) and Multiplexed Arrays Isoform Sequencing (Mas-Iso-Seq) to analyze cells spanning a range of the plasticity spectrum. Looping this analysis back to spatial transcriptomics data, we observed that the signature associated with CD44v8-10 or CD44s isoforms is co-localized with the SPP1 ligand, suggesting a spatially confined interaction. This finding underscores the potential of PlastiNet to generate hypotheses directly from patient-derived samples, offering new insights into the cellular mechanisms driving tumor plasticity. PlastiNet effectively constructs spatially aware embeddings that capture the dynamics of tumor cell plasticity. By identifying key interactions and extrinsic factors, this method opens new avenues for understanding and potentially targeting the mechanisms underlying tumor progression and treatment resistance.
Citation Format: Izabella L Zamora, Milan Parikh, Samuel Wright, Lynn Bi, Bidish Patel, Dana Pe’er, David Ting, Nir Hacohen, Arnav Mehta. PlastiNet: Understanding the Epithelial - Mesenchymal Transition Through Graphical Attention in Spatial Transcriptomics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C065.