CRC_FFPE-CODEX_CellNeighs | High-dimensional imaging of colorectal carcinoma and other tumors with 50+ markers
DOI: 10.7937/TCIA.2020.FQN0-0326 | Page Accessibility: Public | Collection
| Location | Species | Subjects | Data Types | Cancer Types | Status | Updated | |
|---|---|---|---|---|---|---|---|
| Colon | Human | 35 | Pathology, High-dimensional CODEX images | Colorectal Cancer | Clinical, Image Analyses | Public, Complete | 2023/09/13 |
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).
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.
Data Access
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Please contact [email protected] with any questions regarding usage.
| Title | Data Type | Format | Access Points | License | |||
|---|---|---|---|---|---|---|---|
| Tissue Slide Images | Pathology | TIFF | Requires IBM-Aspera-Connect plugin |
200 | CC BY 4.0 | ||
| Clinical data | XLS | CC BY 4.0 | |||||
| Clinical data | XLS | CC BY 4.0 |
Detailed Description
High-dimensional CODEX images (hyperstacks of immunofluorescence images)
Citations & Data Usage Policy
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 |
Publication Citation |
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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 |
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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 |
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