Genomic Multivariate Predictors of Response to Adjuvant Chemotherapy in Ovarian Carcinoma: Predicting Platinum Resistance
Purpose: Despite advances in radical surgery and chemotherapy delivery, ovarian cancer is the most lethal gynecologic malignancy. Most of these patients are treated with platinum-based chemotherapies, but there is no biomarker model to guide their responses to these therapeutic agents. We have developed and independently tested our novel multivariate molecular predictors for forecasting patients' responses to individual drugs on a cohort of 58 ovarian cancer patients. Experimental Design: W...
Provenance — who produced it, who reused it
Linked to 57 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.
- curatedOvarianData: clinically annotated data for the ovarian ca... 2013 · 213 cites
- High-grade serous tubo-ovarian cancer refined with single-cell R... 2021 · 195 cites
- Open source machine-learning algorithms for the prediction of op... 2017 · 122 cites
- The Long Noncoding RNA MALAT-1 is A Novel Biomarker in Various C... 2016 · 112 cites
- RNA demethylase ALKBH5 promotes ovarian carcinogenesis in a simu... 2020 · 112 cites
- EZH2-mediated epigenetic silencing of TIMP2 promotes ovarian can... 2017 · 88 cites
51 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.