Published January 9, 2024 | Version v2
Dataset Open

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

Creators

  • 1. Department of Biomedical Engineering; The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
  • 2. Department of Cell, Developmental & Cancer Biology; The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA
  • 3. The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA; Current affiliation: Akoya Biosciences, 100 Campus Drive, 6th Floor, Marlborough, MA USA
  • 4. Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, OR USA
  • 5. The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA; Immune Monitoring and Cancer Omics Services, Oregon Health & Science University, Portland, OR USA
  • 6. 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
  • 7. Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA USA
  • 8. Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA USA
  • 9. Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA; Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
  • 10. Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR USA; The Knight Cancer Institute, Oregon Health & Science University, Portland, OR USA; Current affiliation: Department of Machine Learning, H. Lee Moffitt Cancer Center, Tampa, FL USA; Current affiliation: Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center, Tampa, FL USA

Description

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.

Files

data.zip

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