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Summary

We have used CODEX to image 56 proteins simultaneously in 140 tissue regions from the tumor invasive front of 35 advanced-stage colorectal cancer (CRC) patients (17 patients with Crohn's-like reaction (CLR) - leading to high amount of tertiary lymphoid structures (TLS); and 18 patients with diffuse inflammatory infiltration (DII) and no TLS). These patients were selected from an initial cohort of 715 CRC patients. Patients with low-stage CRC (pTNM 0-2), pre-operative chemotherapy, insufficient material, and low immune infiltration were excluded. The 35 resulting patients were matched for age, sex and tumor characteristics. CLR patients had a much better survival compared to DII patients.  We expect that making this dataset publicly available will stimulate broad research endeavors into the immune tumor microenvironment of colorectal cancer and allow computational scientists to discover new biomarkers and features. Further details on the study can be obtained in our paper here: https://www.cell.com/cell/fulltext/S0092-8674(20)30870-9

Acknowledgement

We would like to acknowledge the individuals and institutions that have provided data for this collection:

  • Angelica Trejo, Han Chen, Kenyi Donoso, Nilanjan Mukherjee, Vishal Venkataraaman, and Gustavo Vazquez (Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA) for excellent technical assistance.
  • Sandrine Ruppen, Carmen Cardozo, and Dr. José Galván (Institute of Pathology, University of Bern, Switzerland) for help with creating the TMAs.
  • Dr. Anna Seigal (Mathematical Institute, University of Oxford, Oxford, UK University) for helpful discussions regarding tensor decomposition.
  • Dr. Julian Schardt (Department of Medical Oncology, Inselspital, University Hospital Bern, Switzerland) for helping obtain patient clinical information.
  • Prof. Paul Bollyky (Department of Infectious Diseases, Stanford University School of Medicine, Stanford, CA, USA) for providing the biotinylated VG1 hyaluronan-detection reagent.
  • The patients for their consent to use their tissues for research.
  • Dr. Sizun Jiang and Dr. Xavier Rovira-Clavé (Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA) for critical comments on the manuscript.

We would also like to acknowledge the following institutions and companies for their grants and awards given for this collection:

  • US National Institutes of Health grants and sub awards: (2U19AI057229-16) (5P01HL10879707) (5R01GM10983604) (5R33CA18365403) (5U01AI101984-07) (5UH2AR06767604) (5R01CA19665703) (5U54CA20997103) (5F99CA212231-02) (1F32CA233203-01) (5U01AI140498-02) (1U54HG010426-01) (5U19AI100627-07) (1R01HL120724-01A1) (R33CA183692) (R01HL128173-04) (5P01AI131374-02) (5UG3DK114937-02) (1U19AI135976-01) (IDIQ17X149) (1U2CCA233238-01) (1U2CCA233195-01)
  • The Department of Defense: (W81XWH-14-1-0180 and W81XWH-12-1-0591)
  • The Food and Drug Administration: (HHSF223201610018C and DSTL/AGR/00980/01)
  • Cancer Research UK: (C27165/A29073)
  • The Bill and Melinda Gates Foundation: (OPP1113682)
  • The Cancer Research Institute
  • The Parker Institute for Cancer Immunotherapy
  • The Kenneth Rainin Foundation: (2018-575)
  • The Silicon Valley Community Foundation: (2017-175329 and 2017-177799-5022)
  • The Beckman Center for Molecular and Genetic Medicine
  • Juno Therapeutics, Inc. : (122401)
  • Pfizer, Inc. : (123214)
  • Celgene, Inc. : (133826 and 134073)
  • Vaxart, Inc. : (137364)
  • The Rachford & Carlotta A. Harris Endowed Chair (G.P.N.)
  • C.M.S. was supported by an Advanced Postdoc Mobility Fellowship from the Swiss National Science Foundation (P300PB_171189 and P400PM_183915), and an International Award for Research in Leukemia from the Lady Tata Memorial Trust, London, UK.
  • D.J.P. was supported by an NIH T32 Fellowship through Stanford’s Department of Epithelial Biology (AR007422), an NIH F32 Fellowship (CA233203), a Stanford Dean’s Postdoctoral Fellowship, and Stanford’s Dermatology Department.
  • S.S.B. was supported by a Bio-X Stanford Interdisciplinary Graduate Fellowship and Stanford’s Bioengineering Department.
  • G.L.B was supported by an NIH T32 Fellowship through Stanford’s Molecular and Cellular Immunobiology Program (5T32AI007290-34).


Data Access

Data TypeDownload all or Query/Filter
Tissue Slide Images (TIFF, 2.0TB)
Clinical data (XLS, DOC)

Click the Versions tab for more info about data releases.

Please contact help@cancerimagingarchive.net  with any questions regarding usage.

Detailed Description

Image Statistics


Modalities

Pathology

Number of Subjects

35

Number of Images

200

Images Size (TB)2.0

High-dimensional CODEX images (hyperstacks of immunofluorescence images)

Citations & Data Usage Policy

Users of this data must abide by the TCIA Data Usage Policy and the Creative Commons Attribution 4.0 International License under which it has been published. Attribution should include references to the following citations:

Data Citation

Schürch, C. M., Bhate, S., Barlow, G., Phillips, D., Noti, L., Zlobec, I., Chu, P., Black, S., Demeter, J., McIlwain, D., Samusik, N., Goltsev, Y., & Nolan, G. (2020). High-dimensional imaging of colorectal carcinoma and other tumors with 50+ markers [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.2020.FQN0-0326

Publication Citation

Schürch et al., Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front, Cell (2020), https://doi.org/10.1016/j.cell.2020.07.005

TCIA Citation

Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. DOI: 10.1007/s10278-013-9622-7

Other Publications Using This Data

TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

Version 1 (Current): Updated 2020/08/05

Data TypeDownload all or Query/Filter
Images (TIFF, 2.0TB)
Clinical Data (XLS, DOC)

Details_on_image_acquisition_and_processing.docx

Multi-tumor_TMA_composition.xlsx

CRC_TMAs_patient_annotations.xlsx




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