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Portrai Insights

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17 articles
AACR

Development of human antibodies targeting a novel cancer-associated fibroblast protein identified from spatial transcriptomics

Cancer-associated fibroblasts (CAFs) are key components of the tumor microenvironment and play a critical role in tumor progression and therapy resistance. Recent advances in spatial transcriptomics..

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AACR

High-resolution AI-based spatial biology tool for lung cancer trained by image-based spatial transcriptomics data to analyze tumor microenvironmnet

Spatial biology enables the analysis of tumor microenvironments by revealing cellular relationships within the heterogeneous tumor landscape, which are closely associated with tumor characteristics...

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AACR

Biologically informed cell typing in the tumor microenvironment with lightweight LLMs

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types that interact dynamically, influencing tumor development and therapy response. Accurate cell type annotation in the TME...

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AACR

Estimation of homologous recombination deficiency map from spatial transcriptomics

Homologous recombination deficiency (HRD) is a predictive biomarker for various anti-cancer drugs such as poly(ADP-ribose) polymerase inhibitors (PARPi) and platinum-based chemotherapeutic agents...

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AACR

Unveiling the tumor microenvironment of hepatocellular carcinoma using AI trained by spatial transcriptomics: A preliminary study to predict response to immunotherapy

Immune checkpoint inhibitors (ICIs), particularly targeting the PD-1 pathway, are promising in treating hepatocellular carcinoma (HCC). However, their variable effectiveness among individuals calls...

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AACR

Cancer region definition using spatial gene expression patterns by super resolution reconstruction algorithm for spatial transcriptomics data

Spatially resolved transcriptomics (ST) has enabled a variety of cancer research on the heterogeneity of tumor microenvironment. However, when identifying cancer boundaries based on ST, the limited...

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AACR

IAMSAM: Image-based analysis of molecular signatures using the Segment-anything model - Integrative analysis tool for tumor microenvironment

Spatial transcriptomics (ST) is a powerful approach for investigating gene expression patterns in tissues while preserving their spatial context. However, working with ST data presents challenges...

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AACR

Comparative spatial transcriptomic analysis of monoclonal antibodies targeting the same molecule: A comparison between cetuximab and panitumumab

In recent years, multiple therapeutic monoclonal antibodies have been developed that target the same molecules. Examples include trastuzumab and pertuzumab for HER2, cetuximab (CTX) and panitumumab...

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AACR

Automated tumor microenvironment analysis for multiple samples by image-based spatial transcriptomics on tissue microarray

Tissue Microarrays (TMAs), widely utilized in the field of pathology, have now found a powerful ally in Image-based Spatial Transcriptomics (ST). By analyzing various gene expression data with high...

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