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 | 611 Views | 6 Citations | Image Collection
| Location | Species | Subjects | Data Types | Cancer Types | Size | Status | Updated | |
|---|---|---|---|---|---|---|---|---|
| Colon | Human | 35 | Histopathology, CODEX images, Diagnosis, Follow-Up, Demographic | Colorectal Cancer | 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 | License | |||
|---|---|---|---|---|---|---|---|---|
| Tissue Slide Images | Histopathology, CODEX images | TIFF | Download requires IBM-Aspera-Connect plugin |
35 | 200 | CC BY 4.0 | ||
| Clinical data: Multi-tumor TMA composition | Diagnosis | XLSX | CC BY 4.0 | |||||
| Clinical data: CRC TMA patient annotation | Diagnosis, Follow-Up, Demographic | XLSX | 35 | 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 |
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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.
Related Publications
Publications by the Dataset Authors
The authors recommended the following as the best source of additional information about this dataset:
Publication Citation |
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Schürch, C. M., Bhate, S. S., Barlow, G. L., Phillips, D. J., Noti, L., Zlobec, I., Chu, P., Black, S., Demeter, J., McIlwain, D. R., Kinoshita, S., Samusik, N., Goltsev, Y., & Nolan, G. P. (2020). Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front. In Cell (Vol. 182, Issue 5, pp. 1341-1359.e19). https://doi.org/10.1016/j.cell.2020.07.005 |
Further details on the study can be obtained in our paper here: https://www.cell.com/cell/fulltext/S0092-8674(20)30870-9
Research Community Publications
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