检查表
多路复用
标准化
医学
最佳实践
医学物理学
免疫疗法
数据科学
计算机科学
生物标志物
病理
计算生物学
数据挖掘
聚类分析
梅德林
生物信息学
临床实习
知情同意
临床试验
空间分析
一般化
补语(音乐)
癌症
作者
Sam Sater,Carlo B Bifulco,Jaime Rodriguez-Canales,Joe Yeong,Guray Akturk,Michael Angelo,Carmen Ballesteros-Merino,Peter Bankhead,Subham Basu,Jorge M Blando,Saska Brajkovic,Marco Cassano,Benjamin J Chen,Ahmet F Coskun,Tricia R Cottrell,Carlos E De Andrea,Robin H Edwards,Colt Egelston,Logan L Engle,Marc S Ernstoff
标识
DOI:10.1136/jitc-2025-012280
摘要
Multiplex immunofluorescence and immunohistochemistry (mIF/IHC) are increasingly employed antibody-based technologies that use tissue sparingly and facilitate the detection of co-localized or neighboring biomarkers. Specifically, these platforms enable spatial analyses of the tumor microenvironment as well as extended applications, for example, describing normal tissue anatomy, autoimmunity, infectious diseases, etc. mIF/IHC has greatly enhanced biomarker discovery efforts, and a growing number of studies suggest superiority to traditional IHC. Standardization of staining approaches, reporting of image analysis strategies and resultant data is critical for facilitating cross-study comparisons, validation, deployment, and generalization of findings. To address this challenge, The Society for Immunotherapy of Cancer (SITC) previously published two articles providing best practice guidelines for mIF/IHC staining, image analysis, and data sharing. Here, SITC convened stakeholders to develop the third article in the series, a consensus checklist for scientific reporting of mIF/IHC data to support and complement the best practice guidelines. The checklist includes critical components of mIF/IHC applications to be defined within publications such as detailed descriptions of analytical validation; image acquisition, selection, and registration methods; and cell clustering and spatial analysis strategies, amongst others. Such information will help with data reproducibility and comparison across studies towards future drug and assay development.
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