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Portrai Insights

Insights on data analysis, AI, and the platform we're building at Portrai.

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15 articles
AACR

Detecting cancer microbiota using unmapped RNA reads on spatial transcriptomics

Recently, the study of microbiota has emerged as a novel area in cancer research. While next-generation sequencing (NGS) technologies are becoming more prevalent in the area, the acquisition of spa...

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AACR

Data-driven discovery of cancer-specific targets for hepatocellular carcinoma using spatial transcriptomics

Hepatocellular carcinoma (HCC) is frequently diagnosed in advanced stages, with limited options available for systemic treatment. Given the significant investment of time, the high costs, and the...

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AACR

Deep learning-based mapping of tertiary lymphoid structure scores from H&E images of renal cell carcinoma trained by spatial transcriptomics data

Tertiary lymphoid structures are organized aggregates of immune cells present in the tumor microenvironment (TME) in which novel targets as well as beneficial biomarkers for immunotherapy in cancer...

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AACR

Peptide-based theranostics targeting ANTXR1 in cancer stroma Available

ANTXR1 is one of the pancreatic ductal adenocarcinoma (PDAC) stroma-specific cell surface markers (Ref 1), which is also overexpressed in the stroma of various cancer types. Radiotheranostics refers..

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AACR

Discovery of stromal targets in pancreatic cancer Available

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with limited treatment options. Development of stroma targeting therapeutics for PDAC is gaining attention because…

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AACR

Deep learning-based tumor microenvironment cell types mapping from H&E images of lung adenocarcinoma using spatial transcriptomic data

Spatial characterization of cell types of the tumor microenvironment (TME) is a key to finding new targets as well as developing biomarkers for immuno-oncology treatment.

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