Incendia Therapeutics’ Post

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Looking forward to a great #ASCO24 where we will present our poster (Abstract 8539) with PathAI on how H&E-derived immune phenotypes relate to checkpoint inhibitor response in #NSCLC. This important work helps further Incendia Therapeutics' mission of targeting #ImmuneExclusion in cancer. #AI #TME #PrecisionOncology #BreakingBarriers

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This week at #ASCO2024 we will be presenting two posters focused on applying AI-powered pathology for #cancerresearch. Read more about the abstracts and add the posters to your program. 𝘑𝘶𝘯𝘦 2𝘯𝘥, 2024 - 9:00 𝘈𝘔 - 12:00 𝘗𝘔 𝗔𝗯𝘀𝘁𝗿𝗮𝗰𝘁 𝟰𝟱𝟭𝟵: 𝗔𝘀𝘀𝗼𝗰𝗶𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗠𝗟)–𝗱𝗲𝗿𝗶𝘃𝗲𝗱 𝗵𝗶𝘀𝘁𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝘄𝗶𝘁𝗵 𝘁𝗿𝗮𝗻𝘀𝗰𝗿𝗶𝗽𝘁𝗼𝗺𝗶𝗰 𝗺𝗼𝗹𝗲𝗰𝘂𝗹𝗮𝗿 𝘀𝘂𝗯𝘁𝘆𝗽𝗲𝘀 𝗶𝗻 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗿𝗲𝗻𝗮𝗹 𝗰𝗲𝗹𝗹 𝗰𝗮𝗿𝗰𝗶𝗻𝗼𝗺𝗮 (𝗥𝗖𝗖) Presented by: Shima Nofallah Previously, transcriptomic analysis in the Phase 3 IMmotion 151 (Im151) trial identified 7 molecular subtypes that showed differential outcomes to Atezolizumab+Bevacizumab (A+B) vs Sunitinib (S) treatment. In this abstract, in collaboration with Genentech, human interpretable features (HIFs), including blood vessels, immune cells, fibroblasts, tissue morphologies, and nucleus shape, extracted from H&E-stained whole slide images (WSI) from Im151 and Im150, were used to identify positively associated HIFs within each subgroup in the Im151 WSI and then validated in Im150 molecular subgroups. 169 HIFs were differentially enriched across 3 molecular subsets in both datasets. Our results suggest that clinically relevant RCC subtypes may be extracted directly from H&E-stained WSI and may complement gene expression-based patient stratification and selection strategies. Add to your schedule: https://lnkd.in/eK4sSdxw 𝘑𝘶𝘯𝘦 3𝘳𝘥, 2024 - 1:30 𝘗𝘔 - 4:30 𝘗𝘔 𝗔𝗯𝘀𝘁𝗿𝗮𝗰𝘁 𝟴𝟱𝟯𝟵: 𝗖𝗼𝗿𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗶𝗺𝗺𝘂𝗻𝗲 𝗽𝗵𝗲𝗻𝗼𝘁𝘆𝗽𝗲𝘀 𝗱𝗲𝗿𝗶𝘃𝗲𝗱 𝗳𝗿𝗼𝗺 𝗛&𝗘-𝘀𝘁𝗮𝗶𝗻𝗲𝗱 𝘄𝗵𝗼𝗹𝗲 𝘀𝗹𝗶𝗱𝗲 𝗶𝗺𝗮𝗴𝗲𝘀 𝘄𝗶𝘁𝗵 𝗽𝗿𝗼𝗴𝗻𝗼𝘀𝗶𝘀 𝗮𝗻𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝘁𝗼 𝗰𝗵𝗲𝗰𝗸𝗽𝗼𝗶𝗻𝘁 𝗶𝗻𝗵𝗶𝗯𝗶𝘁𝗼𝗿𝘀 𝗶𝗻 𝗡𝗦𝗖𝗟𝗖 Presented by: Bahar Rahsepar, PhD  The classification of tumors as inflamed, excluded or desert based on spatial patterns of tumor infiltrating lymphocytes (TILs) is a potential biomarker of patients likely to respond to checkpoint inhibitors (CPI).  In this abstract, in collaboration with Incendia Therapeutics, PathExplore IOP is used to classify immune-phenotype (IP) based on patch level TIL distribution in tumor core and periphery from H&E images. Survival analysis indicates Immune inflamed phenotype is associated with improved PFS in CPI-treated NSCLC patients independent of PD-L1 status. Add to your schedule: https://lnkd.in/eUZvYYzw #pathology #biotech #AI #digitalpathology #oncology #biotechnology #ASCO #ASCO24

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