Discovery and validation of a prostate cancer genomic classifier that predicts early metastasis following radical prostatectomy
Purpose: Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis. Methods: A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry that underwent radical pr...
Provenance — who produced it, who reused it
Linked to 17 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- Integrative analyses reveal a long noncoding RNA-mediated sponge... 2016 · 325 cites
- FOXA1 mutations alter pioneering activity, differentiation and p... 2019 · 280 cites
- RNA biomarkers associated with metastatic progression in prostat... 2014 · 270 cites
- Altered interactions between unicellular and multicellular genes... 2017 · 227 cites
- The long noncoding RNA H19 regulates tumor plasticity in neuroen... 2021 · 104 cites
12 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
No quantitative QC rubric exists for this data type yet, so it is deliberately left unscored — this is an honest "not applicable", not a poor rating.
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently