Child pages
  • High-dimensional imaging of colorectal carcinoma and other tumors with 50+ markers (CRC_FFPE-CODEX_CellNeighs)

Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

Excerpt

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:

...

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.


Localtab Group


Localtab
activetrue
titleData Access

Data Access

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

Tcia button generator
urlhttps://faspex.cancerimagingarchive.net/aspera/faspex/external_deliveries/18?passcode=2442106c1a03f1b911073d97f323130a67aa5d54

Clinical data (XLS, DOC)

Click the Versions tab for more info about data releases.

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


Localtab
titleDetailed Description

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)


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy

Tcia license 4 international

Info
titleData 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


Info
titlePublication 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


Info
titleTCIA 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.


Localtab
titleVersions

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

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

Tcia button generator
urlhttps://faspex.cancerimagingarchive.net/aspera/faspex/external_deliveries/18?passcode=2442106c1a03f1b911073d97f323130a67aa5d54

Clinical Data (XLS, DOC)

Details_on_image_acquisition_and_processing.docx

Multi-tumor_TMA_composition.xlsx

CRC_TMAs_patient_annotations.xlsx



...