がん組織分析を向上させるAIツールを開発(Mount Sinai Scientists Create AI-Powered Tool to Improve Cancer Tissue Analysis)

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2025-08-25 マウントサイナイ医療システム(MSHS)

マウントサイナイ医学校の研究者らは、がん組織スライドの全体像を迅速かつ高精度に解析できるAIツール「MARQO(Multi-Analytical Robust Quantitative Observation)」を開発しました。従来は膨大な画像を切り貼りし高性能コンピュータで処理する必要がありましたが、MARQOは標準的なGPUで数分以内に免疫組織染色や蛍光免疫染色スライドを解析可能です。細胞位置やマーカー強度を自動抽出し、病理医の検証と組み合わせることで診断の精度と再現性が向上します。バイオマーカー発見や個別化医療を加速させる可能性があり、成果は『Nature Biomedical Engineering』に掲載されました。

がん組織分析を向上させるAIツールを開発(Mount Sinai Scientists Create AI-Powered Tool to Improve Cancer Tissue Analysis)

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がん組織病変における多パラメトリックな細胞および空間的組織化を簡素化されたパイプラインで解析 Multiparametric cellular and spatial organization in cancer tissue lesions with a streamlined pipeline

Mark Buckup,Igor Figueiredo,Giorgio Ioannou,Sinem Ozbey,Rafael Cabal,Alexandra Tabachnikova,Leanna Troncoso,Jessica Le Berichel,Zhen Zhao,Stephen C. Ward,Clotilde Hennequin,Guray Akturk,Steve Hamel,Maria Isabel Fiel,Rachel Brody,Myron Schwartz,Thomas U. Marron,Seunghee Kim-Schulze,Vladimir Roudko,Edgar Gonzalez-Kozlova,Pauline Hamon,Miriam Merad & Sacha Gnjatic
Nature Biomedical Engineering  Published:25 August 2025
DOI:https://doi.org/10.1038/s41551-025-01475-9

Abstract

Multiplex immunostaining analysis remains fragmented, underperforming and labour intensive despite tissue proteomic methodologies achieving ever-increasing marker complexity. Here we propose an open-source, user-guided automated pipeline that streamlines start-to-finish, single-cell resolution analysis of whole-slide tissue, named multiplex-imaging analysis, registration, quantification and overlaying (MARQO). MARQO integrates elastic image registration, iterative nuclear segmentation, unsupervised clustering with mini-batch k-means and user-guided cell classification through a graphical interface. We compare and validate MARQO using multiplexed immunohistochemical consecutive staining on a single slide using human tumour and adjacent normal tissue samples. Performance is compared with manually curated pathologist determinations and quantification of multiple markers. We optimize MARQO to analyse diverse tissue sizes from whole tissue, biopsy, and tissue microarray and staining approaches, such as singleplex immunohistochemistry and 20-colour multiplex immunofluorescence, to determine marker co-expression patterns in multiple human solid cancer types. Lastly, we validate CD8+ T cell enrichment in hepatocellular carcinoma responders to neoadjuvant cemiplimab in a phase 2 clinical trial, further showing the ability of MARQO to identify spatially resolved in situ mechanisms by providing multiplex whole-slide single-cell resolution data.

医療・健康
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