Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer

Zenodo2024-01-09 更新2026-04-07 收录

肿瘤免疫微环境分析

癌症治疗反应预测

数据链接：

https://zenodo.org/doi/10.5281/zenodo.10476868 数据链接链接失效反馈

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资源简介：

Data supporting the findings of "Machine learning links T cell function and spatial localization to neoadjuvant immunotherapy and clinical outcome in pancreatic cancer" publication. Files include patient and tissue region metadata (in metadata folder) and output of multiplex immunohistochemistry computational image processing workflow for each tissue region (in mIHC_files folder). The code used to produce the results of this study is available at: https://github.com/kblise/PDAC_mIHC_paper.

提供机构：

Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA; Department of Cell, Developmental & Cancer Biology; The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA; Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, PA USA; Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA; Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA USA; The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA; Immune Monitoring and Cancer Omics Services, Oregon Health & Science University, Portland, OR USA; Department of Biomedical Engineering; The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA; The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA; Department of Cell, Developmental & Cancer Biology, Orego

创建时间：

2024-01-09