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  • Nascent prostate cancer heterogeneity drives evolution and resistance to intense hormonal therapy (NADT-Prostate)
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Summary

In order to assess mechanisms predictive of response or resistance to intense neoadjuvant therapy, we performed automated immunohistochemistry on targeted biopsies from patients with intermediate or high risk prostate cancer. All biopsy were stained with H&E or antibodies against: p53, PTEN, AR, PSA, GR, Ki67, SYP and PIN4-cocktail (p63+CK5+K18+AMACR). We further performed automated immunohistochemistry on whole mount radical prostatectomy tissues containing residual tumor. RP tissues were stained with H&E or antibodies against: PTEN, AR, AR-V7, PSA, PSMA, GR, Ki67, SYP and PIN4-cocktail (p63+CK5+K18+AMACR), with some slides stained for other markers of residual tumor, to include NKX3.1 and CAM5.2. Slides were scanned at 20x magnification. For each patient, response to intense neoadjuvant therapy is known. As biopsies were targeted to MRI-visible lesions, lesion-level response to therapy is also known. For each biopsy, gene expression profile by RNA-seq and exome sequencing were performed on tumor tissue laser capture microdissected from serial sections. Up to 4 foci were dissected per biopsy. Whole-genome sequencing of germline DNA from each patient was also performed.

Exome and gene expression data corresponding to pre-treatment biopsy tissues has been deposited in dbGaP and GEO. Genome, exome and expression data from post-treatment radical prostatectomy tissues is underway. As slides were stained using an automated slide stainer, this is a rich resource for performing data mining for assessing histogenomic correlates or signatures of treatment response or resistance.

Acknowledgements

The authors gratefully acknowledge the patients and the families of patients who contributed to this study.

Data Access

Data TypeDownload all or Query/Filter
Tissue Biopsy Slide Images (TIFF, 1.4 TB)

Clinical data (XLS)

Exome, genome, & RNA-seq datadbGaP
Summarized gene expression dataGEO

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Detailed Description

Image Statistics


Modalities

Pathology

Number of Patients

37

Number of Images

1401

Images Size (TB)1.4



Citations & Data Usage Policy

Users of this data must abide by the TCIA Data Usage Policy and the Creative Commons Attribution 4.0 International License under which it has been published. Attribution should include references to the following citations:

Data Citation

Wilkinson, S., Ye, H., Karzai, F., Harmon, S. A., Terrigino, N. T., VanderWelle, D. J., Bright, J. R., Atway, R., Trostel, S. Y., Carrabba, N. V., Whitlock, N. C., Walker, S. M., Lis, R. T., Sater, H. A., Capaldo, B. J., Madan, R. A., Gulley, J. L., Chun, G., Merino, M. J., … Sowalsky, A. G. (2020). Nascent prostate cancer heterogeneity drives evolution and resistance to intense hormonal therapy [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/TCIA.JHQD-FR46

Publication Citation

Wilkinson, S., Ye, H., Karzai, F., Harmon, S. A., Terrigino, N. T., VanderWeele, D. J., Bright, J. R., Atway, R., Trostel, S. Y., Carrabba, N. V., Whitlock, N. C., Walker, S. M., Lis, R. T., Abdul Sater, H., Capaldo, B. J., Madan, R. A., Gulley, J. L., Chun, G., Merino, M. J., … Sowalsky, A. G. (2021). Nascent Prostate Cancer Heterogeneity Drives Evolution and Resistance to Intense Hormonal Therapy. European Urology. https://doi.org/10.1016/j.eururo.2021.03.009

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. 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

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Version 1 (Current): Updated 2021/10/08

Data TypeDownload all or Query/Filter
Tissue Biopsy Slide Images (TIFF, 1.4 TB)
Clinical Data (XLS)
Exome, genome, & RNA-seq datadbGaP
Summarized gene expression dataGEO



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