Ovarian serous cystadenocarcinoma OV
Of 60,498 genes, 3,084 are higher in the tumor than in normal ovary and in whole blood, and are not made by blood immune cells. 1,293 are protein-coding, and 1,273 of those have supporting plasma Cell-free RNA (cfRNA)RNA fragments that circulate in blood plasma outside cells. Most come from blood cells; a small share comes from other tissues, including tumors. evidence; the rest are mostly non-coding genes the plasma sources cannot check.
Samples compared
- Tumor
- 419
- TCGA primary tumors
- Normal tissue
- 88
- 88 GTEx ovary
- Whole blood
- 337
- GTEx samples from 328 donors
- Survival
- 417
- patients, 301 events (Survival endpointsCurated TCGA outcomes (Liu et al. 2018): OS is overall survival, PFI the progression-free interval and DSS disease-specific survival. LB2 uses whichever has the most events in each cancer type.)
Results in brief
- 3,084
- candidate genes: 1,273 with plasma cfRNA evidence, 30 protein-coding without, 1,781 non-coding
- 54
- genes in the tissue panel, Held-out AUCHow well an elastic-net model separates tumor from normal tissue, measured with nested cross-validation on samples the model did not train on. It describes tissue, not the accuracy of a blood test. 0.998
- 0
- genes associated with progression-free interval (FDR < 0.05, 150 tested)
Candidates
Filter by plasma evidence or discrimination, find a gene, and select any point or row for its full record. The table holds all 3,084 candidates.
How the candidates were selected
60,498 genes tested; 5,455 higher in tumor than in normal ovary; 4,481 also higher than in whole blood; 3,084 remain after removing genes expressed in blood immune cells; 1,273 of these have plasma cfRNA evidence, 30 protein-coding candidates have none, and 1,781 are non-coding genes the plasma sources cannot list.
Each comparison uses a two-sided Wilcoxon rank-sum test. A gene passes when its q-value is below 0.05, its log2 fold change is at least 1, and the lower bound of the 95% confidence interval for its AUC is at least 0.70.
Genes made by any of 18 sorted blood immune cell types above 1 nTPM are then removed, because blood cells supply most plasma RNA. Genes missing from that reference, mostly non-coding, are kept.
Plasma evidence only reorders the list. A candidate not yet seen in plasma stays in, because every dataset misses genes. Read the full methods.
Tissue classifier panel
- CLDN3+0.17
- FAM181A+0.16
- SYNGR4+0.15
- GLOD5+0.14
- CST1+0.14
- OVOL2+0.14
- FOLR1+0.11
- CNGB1+0.11
- KSR2+0.11
- SMIM22+0.10
- C6orf223+0.10
- MSLNL+0.10
- CDC25C+0.09
- SLC34A2+0.09
- NEIL3+0.07
- KLK8+0.07
- CXCL11+0.07
- FOXQ1+0.06
- CAMK2N2+0.06
- MFSD6L+0.06
Show the other 34 genes
- MAL2+0.05
- RBBP8NL+0.05
- PHOX2A+0.05
- SYT13+0.05
- MYO3B+0.04
- E2F8+0.04
- KLK7+0.04
- EGFL6+0.04
- SKA3+0.04
- EPCAM+0.03
- CENPA+0.03
- LPO+0.03
- PRSS8+0.03
- C1orf106+0.03
- PBK+0.03
- CBLC+0.02
- CTCFL+0.02
- KLRG2+0.02
- SKA1+0.02
- SOX9+0.02
- ADGRF1+0.02
- CLDN4+0.02
- C12orf56+0.02
- KRT7+0.01
- ESRP1+0.01
- DEPDC1+0.01
- UBD+0.01
- PTGER1+0.01
- SAPCD2+0.01
- C2CD4D+0.00
- MISP+0.00
- SLC9A2+0.00
- XDH+0.00
- ALDH3B2+0.00
An elastic-net logistic regression was trained on the 300 top-ranked candidates to tell tumor from normal tissue. Its Held-out AUCHow well an elastic-net model separates tumor from normal tissue, measured with nested cross-validation on samples the model did not train on. It describes tissue, not the accuracy of a blood test. is 0.998, from nested five-fold cross-validation.
Every normal sample here comes from GTEx, so the TCGA-versus-GTEx offset cannot be separated from the tumor/normal contrast and no study correction was possible: the classifier may partly learn study differences.
This number describes tumor and normal tissue, where separation is expected to be near perfect. It is not the accuracy of a blood test: that has to be measured in plasma from patients and controls.
Association with survival
None of the 150 top-ranked candidates is associated with progression-free interval at FDR < 0.05 (417 patients, 301 events). A null result here is informative: these genes mark the presence of the cancer, not necessarily its course.
For the 150 top-ranked candidates, a Cox model relates tumor expression, as a continuous value, to progression-free interval in 417 patients (301 events). No high/low cutpoint is searched for, since optimized cutpoints inflate false positives.
A Hazard ratio per SDFrom a Cox model with the gene’s tumor expression as a continuous variable: the change in hazard for each one-standard-deviation increase. Above 1, higher expression goes with a shorter time to the event; below 1, with a longer one. above 1 means higher expression goes with a shorter progression-free interval. These are associations in tissue, not evidence that a blood level predicts outcome.
Caveats for OV
- Every normal sample comes from GTEx, a different study from the tumors, so study differences cannot be corrected in the tissue comparison.
- With only 88 normal samples, confidence intervals are wide; treat close ranks as ties.
- The blood comparison sets TCGA tumors against GTEx blood. Study and biology cannot be separated there, which is why genes made by blood immune cells are removed as well.