PathAI Showcases AI-Powered Precision Pathology at AACR Annual Meeting

PathAI, a pioneering AI-powered precision pathology company, is set to showcase its cutting-edge research at the upcoming AACR Annual Meeting from April 7-10, 2024, in San Diego, CA. The company’s presentations will highlight how its machine learning models, developed to analyze the tumor microenvironment (TME) from routine hematoxylin and eosin (H&E)-stained whole slide images (WSIs), can drive advancements in biomarker development and precision medicine strategies.

One of the key presentations will feature PathAI’s commercially available product, PathExplore, which was deployed on head and neck squamous cell carcinoma (HNSCC) and non-small cell lung cancer (NSCLC) samples to characterize the cell and tissue composition of the TME, as well as compute immune phenotypes directly from H&E WSI (Poster #905).

In collaboration with Incendia Therapeutics, researchers developed a continuous scoring method for Discoidin Domain Receptor 1 (DDR1), revealing widespread immune exclusion in tumors based on the spatial distribution of lymphocytes, CD8+ T cells, and CD45+ immune cells from H&E and multiplex immunofluorescence (mIF) images. This study provides insights into the role of DDR1 in human cancers and may aid in patient stratification for DDR1-targeted therapies (Poster #2916).

Another highlight includes the discovery of three distinct cancer-associated stroma (CAS) phenotypes with distinct patterns of association with survival and gene expression signatures, facilitated by PathExplore’s features and a novel collagen fiber detection imaging technology. This categorization of CAS-tumor interaction may be useful for patient stratification (Poster #4912).

PathAI’s AI-powered models were also employed by Foundation Medicine researchers to investigate digital pathology TME features of immunotherapy outcomes among NSCLC patients, indicating the potential utility of the TME composition in identifying responders to first-line immune checkpoint inhibitors beyond established biomarkers (Poster #4969).

In collaboration with EMD Serono, PathAI’s TME models were used to analyze H&E WSI of NSCLC from a randomized Phase 3 trial comparing two immunotherapies. The researchers identified candidate prognostic immunotherapy biomarkers by associating immune and stromal cell abundance features with gene expression data and clinical data (Poster #6179).

Additionally, Incendia Therapeutics researchers illustrated that morphologic features derived from H&E images using PathExplore can effectively predict CD8-defined immune exclusion, providing an option for patient stratification by immune phenotype using widely available H&E images (Poster #7392).

PathAI’s pan-tumor foundation models were also utilized to identify tissue regions and cell types on H&E WSI to quantify tumor purity across multiple tumor types. The model-derived tumor purity estimates correlated with three orthogonal molecular methods, providing evidence of how AI can improve the efficiency of molecular testing and enhance precision diagnostic strategies (Poster #7402).

Follow PathAI on LinkedIn and X for more updates from #AACR24 and visit them at booth #1549.

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