SPRINTR-Retro

SPRINTR-Retro uses completed studies and trials to identify, optimize, and validate biomarkers in well characterized cohorts with defined outcomes. Biomarkers can be based on liquid-biopsies, tissue or imaging.

Included studies and trials: 

SPCG-13

Adjuvant Docetaxel Versus Surveillance in Intermediate- or High-risk Prostate Cancer After 

SPCG-14

Docetaxel added to bicalutamide in Hormone-Naïve non-metastatic prostate cancer with rising PSA

SPCG-15

Primary radical prostatectomy vs. primary radiotherapy plus androgen deprivation therapy for locally advanced prostate cancer

PAMP 1 and 2

PAMP is a multidisciplinary study of the relationship between in vivo PSMA/acetate PET, mpMRI, and histopathology in localized prostate cancer.

Ongoing and planned studies in SPRINTR-Retro



 
RNA profiling as a treatment predictive tool for docetaxel in non-metastatic
prostate cancer (SPCG-14)

The primary analysis of the SPCG‑14 showed a benefit in progression-free survival with the addition of docetaxel to the standard of care in patients with PSA relapse after curative intent (Josefsson et al). RNA profiling showing a high Decipher score has shown promising results to identify men with the most benefit of adding docetaxel in metastatic settings. In this study, transcriptomic-based analysis will be performed to identify biomarkers that help guide treatment decisions and improve patient selection for chemotherapy. Martin Sjöström (Lund University), Andreas Josefsson (Umeå University), Karin Welén (University of Gothenburg), Pernilla Wikström (Umeå University)



RNA profiling as a treatment predictive tool for radical prostactomy and radiotherapy (SPCG-15)

SPCG‑15 is a randomized trial in men with locally advanced, non‑metastatic prostate cancer, comparing primary radical prostatectomy (with multimodal treatment if needed) versus radiotherapy combined with androgen deprivation therapy (Stranne et al). Emerging biomarker data, including transcriptomic profiling, show potential to guide treatment selection in prostate cancer. In SPCG‑15, molecular and transcriptomic analyses will be used to identify biomarkers to inform treatment decisions and improve patient selection for multimodal therapy. Olof Akre (Karolinska Institutet), Anders Petterson (Karolinska Institute), Johan Stranne (University of Gothenburg), Per Vincent (Karolinska institutet), Martin Sjöström (Lund University), Andreas Josefsson (Umeå University)



Automatic scoring and classification in digital pathology from biopsies for precision medicine  

Ki-67 and PSA immunohistochemical scoring are promising markers with prognostic potential and potential for treatment prediction (Spyratou et al.). The scoring of Ki-67 and PSA is associated with inter-individual discrepancies between pathologists and is also time-consuming. An AI-based tool for automatic or semi-automatic scoring would lower the threshold for testing these markers in a large prospective cohort such as the SPRINTR study. In this study, a tool will be developed and tested.  Vasiliki Spyratou (University of Gothenburg), Carolina Wählby (Uppsala University), Andreas Josefsson (Umeå University), Anders Bergh (Umeå University)



PAMP

PAMP is a multidisciplinary study of localized prostate cancer in which PSMA‑PET, acetate‑PET and mpMRI are correlated with whole‑mount histopathology using a high‑precision registration workflow. The study has shown that PSMA‑PET and mpMRI outperform acetate‑PET for the detection of clinically significant lesions, and that combining imaging modalities improves lesion delineation and grading compared with single modalities alone (Sandgren et al). Together, these results support the use of integrated imaging to better detect, characterize and target clinically important intraprostatic tumors. Tufve Nyholm (Umeå University), Anders Bergh (Umeå University), Sara Strandberg (Umeå University), Kristina Sandgren (Umeå University), Katrin Riklund (Umeå University), Elin Trägårdh (Lunds University),