Comprehensive Analysis of Recurrence-Associated Small Non-Coding RNAs in Esophageal Cancer [Affymetrix]
Targeted cancer therapy for squamous cell carcinoma (SCC) has made little progress largely due to a lack of knowledge of the driving genomic alterations. Small non-coding RNAs (sncRNAs) as a potential biomarker and therapeutic target to SCC remain a challenge. We analyzed sncRNAs microarray in 108 fresh frozen specimens of esophageal squamous cell carcinoma (ESCC) as discovery set and assessed associations between sncRNAs and recurrence-free survival. SncRNA signature identified was externally...
Provenance — who produced it, who reused it
Linked to 9 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.
- Human umbilical cord mesenchymal stem cells-derived exosomes del... 2020 · 107 cites
- A methyltransferase‐like 14/miR‐99a‐5p/tribble 2 positive feedba... 2021 · 89 cites
- Automatic discovery of 100-miRNA signature for cancer classifica... 2019 · 86 cites
6 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
Scientific quality
Based on hands-on reproduction of the papers that use this dataset. A reproducible paper that stands on this data is positive evidence; a flagged one is a prompt to look closer — never a verdict on the dataset itself without the evidence.