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CRC_FFPE-CODEX_CELLNEIGHS

CRC_FFPE-CODEX_CellNeighs | High-dimensional imaging of colorectal carcinoma and other tumors with 50+ markers

DOI: 10.7937/TCIA.2020.FQN0-0326 | Data Citation Required | Image Collection

Location Species Subjects Data Types Cancer Types Size Supporting Data Status Updated
Colon Human 35 Pathology, High-dimensional CODEX images Colorectal Cancer 2TB Clinical, Image Analyses Public, Complete 2020/08/05

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

Details on image acquisition and processing:

Automated imaging was performed on a Keyence BZ-X710 microscope using a CFI Plan Apo λ 20x/0.75 objective (Nikon), in high-resolution mode, with a lateral resolution of 377.44 nm/pixel. Processed images labeled with “montage” only have half of that resolution, resulting in a 4x smaller image size (used for stitching of large tissue microarrays).

Data Access

Version 1: Updated 2020/08/05

 

Title Data Type Format Access Points Subjects Studies Series Images License
Tissue Slide Images Pathology TIFF
Download requires IBM-Aspera-Connect plugin
35 200 CC BY 4.0
Clinical data: Multi-tumor TMA composition XLS CC BY 4.0
Clinical data: CRC TMA patient annotation XLS CC BY 4.0

Citations & Data Usage Policy

Data Citation Required: Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution must include the following citation, including the Digital Object Identifier:

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

Detailed Description

High-dimensional CODEX images (hyperstacks of immunofluorescence images)

Acknowledgements

This work would not have been possible without the support and efforts of many individuals and organizations.

  • A complete list of acknowledgements can be found here.

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 TCIA’s Helpdesk.

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. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7