Gene signatures of progression and metastasis in renal cell cancer
In order to address the progression, metastasis, and clinical heterogeneity of renal cell cancer (RCC), transcriptional profiling with oligonucleotide microarrays (22,283 genes) was done on 49 RCC tumors, 20 non-RCC renal tumors, and 23 normal kidney samples. Samples were clustered based on gene expression profiles and specific gene sets for each renal tumor type were identified. Gene expression was correlated to disease progression and a metastasis gene signature was derived. Gene signatures we...
Provenance — who produced it, who reused it
Linked to 59 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.
- HIF2α-Dependent Lipid Storage Promotes Endoplasmic Reticulum Hom... 2015 · 406 cites
- Suppression of PGC-1α Is Critical for Reprogramming Oxidative Me... 2015 · 188 cites
- Histone methyltransferase SETDB1 regulates liver cancer cell gro... 2015 · 169 cites
- Gene set enrichment for reproducible science: comparison of CERN... 2019 · 136 cites
- A Transcriptional and Metabolic Signature of Primary Aneuploidy... 2013 · 107 cites
- Integration of Lipidomics and Transcriptomics Reveals Reprogramm... 2020 · 104 cites
- The roles of ferroptosis regulatory gene SLC7A11 in renal cell c... 2021 · 81 cites
- Ranking metrics in gene set enrichment analysis: do they matter? 2017 · 80 cites
- Tumor-Specific Isoform Switch of the Fibroblast Growth Factor Re... 2013 · 77 cites
50 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
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently