A Molecular Profile of Colorectal Cancer to Guide Therapy [PDCCEs]
The ability to dissect heterogeneity in colorectal cancer (CRC) is a critical step in developing predictive biomarkers. The goal of this study was to develop a gene expression based molecular subgrouping model, which predicts the likelihood that patients will respond to specific therapies. Using microarray data compiled from 848 CRC patients, we developed a subgrouping model based on 23 activated oncogenic pathway expression signatures. Stability of the model was validated in two independent da...
Provenance — who produced it, who reused it
Linked to 15 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.
- Cross-talk of four types of RNA modification writers defines tum... 2021 · 268 cites
- Enhancing cancer‐associated fibroblast fatty acid catabolism wit... 2021 · 123 cites
- FGF19‐Induced Inflammatory CAF Promoted Neutrophil Extracellular... 2023 · 76 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