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  • Proteogenomic analysis of chemo-refractory high grade serous ovarian cancer (PTRC-HGSOC)

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Summary

In our study, we have generated proteomic and genomic (RNA sequencing and whole genome sequencing) profiles from high grade serous ovarian cancer (HGSOC) tumor biopsies. All biospecimens are formalin-fixed, parrafin-embedded (FFPE) tissues and annotated for patient sensitivity to platinum chemotherapy (refractory or sensitive). For all 174 tumors that were analyzed, we have H&E-stained and imaged the first and last sections (“bookend”) cut from each FFPE block to allow study of tumor pathology. These H&E pathology images are uploaded in this dataset. The bookend FFPE slides were cut at 4 μm thickness using a microtome and mounted on glass slides (Leica Biosystems Cat# 3800040) for H&E staining. Digital images of the H&E slides were recorded using a ScanScope AT Slide Scanner (Leica Aperio Technologies, Vista, CA, USA) under 20X objective magnification (0.5 μm resolution). Images were analyzed by HALO Image Analysis Platform software (Indicta Labs, Albuquerque, New Mexico, USA).

The following clinical data are also provided for these subjects: 

  • Chemotherapy response status: (sensitive/refractory; refractory is defined in our study as clinical ovarian cancer that progresses while on platinum-based therapy or within 4 weeks)
  • neo-adjuvant treatment (yes/no)
  • Tumor location
  • Tumor grade, stage, substage
  • Patient age
  • Patient ethnicity
  • Patient race
  • Age of sample

The goals of the study were to understand mechanisms of platinum resistance in epithelial ovarian cancers (EOCs) in order to: i) predict EOCs that will respond to DNA-damaging platinum therapy, and ii) identify potential new drug targets in resistant disease to point to desperately needed new therapeutic approaches. The ability to predict platinum-resistant/refractory disease would be clinically impactful by enabling the immediate triage of patients with refractory disease to clinical trials of experimental therapies, avoiding use of ineffective standard of care chemotherapy and helping to identify novel treatments. In this study, we generated proteomic and genomic (RNA sequencing and whole genome sequencing) profiling datasets and H&E images from high grade serous ovarian cancer (HGSOC) tumor biopsies representing platinum-sensitive and platinum-refractory disease.

Acknowledgements

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

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Data Access

Data TypeDownload all or Query/FilterLicense
Tissue Slide Images (SVS, 120.5 GB)

   

(Download requires Aspera plugin)
Clinical data (CSV)

Click the Versions tab for more info about data releases.

Clinical Data notes:

A note about the values in CSV spreadsheet "PTRC-HGSOC_List_clinical_data" Patient Age column, there are some ages that were anonymized in accordance with TCIA policy, that is, to bin any age over 89 into a common age group "90+". Please be aware that some of these are not actual ages of patients.

Detailed Description

Image Statistics

Pathology Image Statistics

Modalities

Pathology

Number of Patients

174

Number of Images

348

Images Size (GB)120.5

Clinical Data notes:

A note about the values in CSV spreadsheet "PTRC-HGSOC_List_clinical_data" Patient Age column, there are some ages that were anonymized in accordance with TCIA policy, that is, to bin any age over 89 into a common age group "90+". Please be aware that some of these are not actual ages of patients.

Citations & Data Usage Policy

Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:

Data Citation

Chowdhury, S., Kennedy, J. J., Ivey, R. G., Murillo, O., Hosseini, N., Song, X., Petralia, F., Calinawan, A., Voytovich, U. J., Savage, S. R., Berry, A., Reva, B., Ozbek, U., Krek, A., Ma, W., da Veiga Leprevost, F., Ji, J., Yoo, S., Lin, C., … Paulovich, A. G. (2023). Proteogenomic analysis of chemo-refractory high grade serous ovarian cancer (PTRC-HGSOC) (Version 1) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/6RDA-P940

Publication Citation

Coming Soon

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

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 2023/03/29

Data TypeDownload all or Query/FilterLicense
Tissue Slide Images (SVS, 120.5 GB)
Clinical data (CSV)



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