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Disease intelligence · mutation landscape

Ovarian cancer mutation landscape

How often each gene is altered in ovarian cancer, in each sequenced cohort, over the patients on whom it could have been called. Copy number is its own row. Nothing is pooled.

Retrieved 2026-09-18 · Reference cohort: ov_tcga_pan_can_atlas_2018 · JSON: /disease/ovarian-cancer/mutations.json · Back to the briefing

Answer block

In Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas) (523 sequenced patients, exome or genome), the most frequently altered of the 48 genes shown are TP53 70.94%, TG 29.02% (amplification), PIK3CA 20.28% (amplification), CCNE1 19.58% (amplification), SI 15.73% (amplification). Each figure divides by the patients on whom that gene could be called.

3 of 523 patients are hypermutated (more than 560 non-silent mutations, ten times the cohort median of 56); every gene's frequency without them is beside the headline.

Of the briefing's 12 curated targets, 2 are altered in under 2% of this cohort (MSLN, ARID1A): targets by expression, dependency or drug label, not by mutation. Frequency is not targetability, in either direction.

2 cohorts are shown and none are pooled; overlap between them has not been checked and there is no disease-wide percentage.

Evidence boundary: frequency here is a count in a named cohort. Whether an alteration is a driver, is actionable, or has a drug is the briefing's question and is not inferred from these numbers.

What is altered, by cohort

One row per alteration, not per gene: a gene that is amplified and rarely mutated (ERBB2, MYCN, EGFR) gets a row for each. Every cell divides by its own denominator — the patients in that cohort on whom that gene could be called. Copy-number rows are shown only where at least one cohort reaches 2%.

Alterationov_tcga_pan_can_atlas_2018
523 pts · exome or genome
ovary_cptac_gdc
95 pts · exome or genome
TP53 SNV / small indel70.94%371/52377.89%74/95
BRCA1 SNV / small indel3.44%18/5236.32%6/95
BRCA2 SNV / small indel2.87%15/5233.16%3/95
CCNE1 SNV / small indel0.38%2/5230%
CCNE1 amplification19.58%112/572·
FOLR1 SNV / small indel0.57%3/5230%
FOLR1 amplification4.72%27/572·
MUC16 SNV / small indel7.84%41/52312.63%12/95
MUC16 amplification4.2%24/572·
MSLN SNV / small indel0%0%
KRAS SNV / small indel1.15%6/5232.11%2/95
KRAS amplification9.44%54/572·
ARID1A SNV / small indel0.76%4/5234.21%4/95
PIK3CA SNV / small indel1.53%8/5233.16%3/95
PIK3CA amplification20.28%116/572·
PTEN SNV / small indel1.34%7/5233.16%3/95
PTEN deep deletion4.55%26/572·
NF1 SNV / small indel5.74%30/5233.16%3/95
NF1 deep deletion6.29%36/572·
KMT2C SNV / small indel4.59%24/5235.26%5/95
KMT2C amplification7.34%42/572·
SI SNV / small indel4.21%22/5233.16%3/95
SI amplification15.73%90/572·
MDN1 SNV / small indel4.02%21/5233.16%3/95
FCGBP SNV / small indel4.02%21/5235.26%5/95
FCGBP amplification8.74%50/572·
COL6A3 SNV / small indel4.02%21/5232.11%2/95
TG SNV / small indel3.82%20/5238.42%8/95
TG amplification29.02%166/572·
MYH4 SNV / small indel3.82%20/5234.21%4/95
MYH1 SNV / small indel3.82%20/5233.16%3/95
LRP1 SNV / small indel3.82%20/5232.11%2/95
TOP2A SNV / small indel3.63%19/5231.05%1/95
SPEN SNV / small indel3.63%19/5233.16%3/95
PKHD1 SNV / small indel3.63%19/5233.16%3/95
PKHD1 amplification2.45%14/572·
LRRK2 SNV / small indel3.63%19/5233.16%3/95
LRRK2 amplification2.27%13/572·
CDK12 SNV / small indel3.63%19/5233.16%3/95
VPS13B SNV / small indel3.44%18/5233.16%3/95
VPS13B amplification10.84%62/572·
PEG3 SNV / small indel3.44%18/5233.16%3/95
DYNC1H1 SNV / small indel3.44%18/5231.05%1/95
DYNC1H1 amplification2.27%13/572·
TACC2 SNV / small indel3.25%17/5232.11%2/95
TACC2 amplification2.27%13/572·
RELN SNV / small indel3.25%17/5231.05%1/95
RELN amplification3.32%19/572·
PTPRZ1 SNV / small indel3.25%17/5232.11%2/95
PTPRZ1 amplification4.2%24/572·
PDE4DIP SNV / small indel3.25%17/5231.05%1/95
PDE4DIP amplification6.64%38/572·
RB1 SNV / small indel3.06%16/5234.21%4/95
RB1 deep deletion8.57%49/572·
PRUNE2 SNV / small indel3.06%16/5232.11%2/95
PCDH15 SNV / small indel3.06%16/5234.21%4/95
MYCBP2 SNV / small indel3.06%16/5233.16%3/95
KMT2A SNV / small indel3.06%16/5237.37%7/95
HUWE1 SNV / small indel3.06%16/5237.37%7/95
HUWE1 amplification2.97%17/572·
HIVEP3 SNV / small indel3.06%16/5232.11%2/95
HIVEP3 amplification7.87%45/572·
DYSF SNV / small indel3.06%16/5231.05%1/95
VWF SNV / small indel2.87%15/5234.21%4/95
VWF amplification5.77%33/572·
SZT2 SNV / small indel2.87%15/5231.05%1/95
SZT2 amplification6.64%38/572·
NOTCH4 SNV / small indel2.87%15/5232.11%2/95
NOTCH4 amplification3.32%19/572·
CACNA1C SNV / small indel2.87%15/5235.26%5/95
CACNA1C amplification7.17%41/572·
VPS13C SNV / small indel2.68%14/5232.11%2/95
UBR4 SNV / small indel2.68%14/5232.11%2/95
RNF213 SNV / small indel2.68%14/5233.16%3/95
RNF213 amplification3.85%22/572·

observed — shade scales with frequency, full at 30% assayed, none found not on this cohort's panel cohort not readable

Key findings

TP53 is mutated in 371 of 523 patients in Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas).
Numerator: 371 · Denominator: 523 · Frequency: 70.94% · Observed in 2 cohorts · Confidence: moderate · Source: ov_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

TG is amplified in 166 of 572 patients in Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas).
Numerator: 166 · Denominator: 572 · Frequency: 29.02% · Observed in 2 cohorts · Confidence: moderate · Source: ov_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

PIK3CA is amplified in 116 of 572 patients in Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas).
Numerator: 116 · Denominator: 572 · Frequency: 20.28% · Observed in 2 cohorts · Confidence: moderate · Source: ov_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

Gene table — reference cohort

Headline values are from the reference cohort, ov_tcga_pan_can_atlas_2018; the matrix above keeps every cohort separate. "Curated" marks a gene the disease briefing lists as a target; the rest are here because they are among the most frequently mutated genes in the reference cohort. Recurrent changes are the reference cohort's commonest protein changes.

GeneWhy listedLargest alterationAltered / testedFrequencyWithout hypermutatedCohorts observedRange across cohortsRecurrent changes
TP53 curated target SNV / small indel 371 / 523 70.94% 71.15% 2 / 2 70.94–77.89% R175H (n=15), R248Q (n=10), X187_splice (n=10), R273H (n=9), R248W (n=9)
BRCA1 curated target SNV / small indel 18 / 523 3.44% 3.46% 2 / 2 3.44–6.32% I1108* (n=1), Q1538* (n=1), W1718* (n=1), N1265Kfs*4 (n=1), Y655Vfs*18 (n=1)
BRCA2 curated target SNV / small indel 15 / 523 2.87% 2.5% 2 / 2 2.87–3.16% C711* (n=1), N1906I (n=1), Q1934K (n=1), S1882* (n=1), K1406Nfs*3 (n=1)
CCNE1 curated target amplification 112 / 572 19.58% mutation 0.38% 0.38% 1 / 2 0.0–0.38% I298V (n=1), L161V (n=1)
FOLR1 curated target amplification 27 / 572 4.72% mutation 0.57% 0.38% 1 / 2 0.0–0.57% H43N (n=1), E191K (n=1), A64T (n=1)
MUC16 curated target SNV / small indel 41 / 523 7.84% 7.69% 2 / 2 7.84–12.63% P2968H (n=1), M10796I (n=1), G7334W (n=1), L2900F (n=1), G10957C (n=1)
MSLN curated target amplification 11 / 572 1.92% mutation 0.0% 0.0% 0 / 2 0.0–0.0% none recurrent
KRAS curated target amplification 54 / 572 9.44% mutation 1.15% 1.15% 2 / 2 1.15–2.11% G12V (n=4), G12R (n=1), Q61L (n=1)
ARID1A curated target deep deletion 5 / 572 0.87% mutation 0.76% 0.77% 2 / 2 0.76–4.21% S664* (n=1), Q1708* (n=1), W1073Mfs*32 (n=1), E1766* (n=1)
PIK3CA curated target amplification 116 / 572 20.28% mutation 1.53% 1.35% 2 / 2 1.53–3.16% H1047R (n=2), E545K (n=1), E545A (n=1), E849K (n=1), E545G (n=1)
PTEN curated target deep deletion 26 / 572 4.55% mutation 1.34% 1.35% 2 / 2 1.34–3.16% Y188D (n=1), V175L (n=1), R233Dfs*23 (n=1), X212_splice (n=1), Y138S (n=1)
NF1 curated target deep deletion 36 / 572 6.29% mutation 5.74% 5.77% 2 / 2 3.16–5.74% K1444E (n=1), Q112* (n=1), Y80Lfs*27 (n=1), E1583* (n=1), G2816A (n=1)
KMT2C by frequency amplification 42 / 572 7.34% mutation 4.59% 4.42% 2 / 2 4.59–5.26% R1861L (n=1), Y366S (n=1), H2604N (n=1), N3347S (n=1), K4229M (n=1)
SI by frequency amplification 90 / 572 15.73% mutation 4.21% 4.23% 2 / 2 3.16–4.21% P1202T (n=1), K206N (n=1), E1730D (n=1), T1017N (n=1), I1034F (n=1)
MDN1 by frequency SNV / small indel 21 / 523 4.02% 3.85% 2 / 2 3.16–4.02% R3561M (n=1), V4613D (n=1), K2999M (n=1), S5086F (n=1), D5192H (n=1)
FCGBP by frequency amplification 50 / 572 8.74% mutation 4.02% 4.04% 2 / 2 4.02–5.26% V5330M (n=1), C2750F (n=1), G321D (n=1), E4382V (n=1), R5092H (n=1)
COL6A3 by frequency SNV / small indel 21 / 523 4.02% 3.85% 2 / 2 2.11–4.02% Q348L (n=1), Q788H (n=1), G35C (n=1), X1946_splice (n=1), K1861M (n=1)
TG by frequency amplification 166 / 572 29.02% mutation 3.82% 3.85% 2 / 2 3.82–8.42% V478L (n=1), R2336Q (n=1), G2341V (n=1), Q1299L (n=1), S430T (n=1)
MYH4 by frequency SNV / small indel 20 / 523 3.82% 3.65% 2 / 2 3.82–4.21% A200S (n=1), G686C (n=1), G763C (n=1), Q1708E (n=1), E1709D (n=1)
MYH1 by frequency SNV / small indel 20 / 523 3.82% 3.65% 2 / 2 3.16–3.82% K1169T (n=1), R1867G (n=1), Q911K (n=1), T628M (n=1), Q806R (n=1)
LRP1 by frequency SNV / small indel 20 / 523 3.82% 3.46% 2 / 2 2.11–3.82% D919N (n=1), R1768S (n=1), S3977* (n=1), R1423C (n=1), R2457H (n=1)
TOP2A by frequency SNV / small indel 19 / 523 3.63% 3.65% 2 / 2 1.05–3.63% T215P (n=7), E212Qfs*30 (n=1), L1166F (n=1), X160_splice (n=1), M204Ifs*20 (n=1)
SPEN by frequency SNV / small indel 19 / 523 3.63% 3.27% 2 / 2 3.16–3.63% A3363S (n=1), A995E (n=1), R3185L (n=1), G2788R (n=1), G462E (n=1)
PKHD1 by frequency SNV / small indel 19 / 523 3.63% 3.46% 2 / 2 3.16–3.63% L3496W (n=1), G3454W (n=1), G1563C (n=1), V712L (n=1), V1141Dfs*49 (n=1)
LRRK2 by frequency SNV / small indel 19 / 523 3.63% 3.27% 2 / 2 3.16–3.63% L829I (n=1), P2095A (n=1), I952T (n=1), P1212Q (n=1), Q116K (n=1)
CDK12 by frequency SNV / small indel 19 / 523 3.63% 3.65% 2 / 2 3.16–3.63% S363* (n=1), X343_splice (n=1), S587Y (n=1), D121Efs*5 (n=1), H835N (n=1)
VPS13B by frequency amplification 62 / 572 10.84% mutation 3.44% 3.08% 2 / 2 3.16–3.44% H303R (n=1), A3720S (n=1), A1013S (n=1), R1926K (n=1), G1637C (n=1)
PEG3 by frequency SNV / small indel 18 / 523 3.44% 3.46% 2 / 2 3.16–3.44% Q496H (n=1), R193W (n=1), I472Tfs*107 (n=1), R1138Q (n=1), E1497D (n=1)
DYNC1H1 by frequency SNV / small indel 18 / 523 3.44% 3.46% 2 / 2 1.05–3.44% H2637D (n=1), T4067S (n=1), D1436G (n=1), L2889* (n=1), E2587K (n=1)
TACC2 by frequency SNV / small indel 17 / 523 3.25% 3.27% 2 / 2 2.11–3.25% A2629V (n=1), D2268V (n=1), R606H (n=1), E1084G (n=1), S872F (n=1)
RELN by frequency amplification 19 / 572 3.32% mutation 3.25% 3.08% 2 / 2 1.05–3.25% X158_splice (n=1), D3348E (n=1), G1788D (n=1), C1347Y (n=1), C1347S (n=1)
PTPRZ1 by frequency amplification 24 / 572 4.2% mutation 3.25% 3.08% 2 / 2 2.11–3.25% D2178N (n=1), D866Y (n=1), G1739V (n=1), A1698V (n=1), G667* (n=1)
PDE4DIP by frequency amplification 38 / 572 6.64% mutation 3.25% 3.08% 2 / 2 1.05–3.25% E1315K (n=2), P993L (n=1), L2282M (n=1), E1147* (n=1), R419Vfs*21 (n=1)
RB1 by frequency deep deletion 49 / 572 8.57% mutation 3.06% 2.88% 2 / 2 3.06–4.21% A562P (n=1), I441Lfs*16 (n=1), R787* (n=1), Q702K (n=1), L486Ffs*9 (n=1)
PRUNE2 by frequency SNV / small indel 16 / 523 3.06% 3.08% 2 / 2 2.11–3.06% T758R (n=1), P289L (n=1), K1733N (n=1), A1525P (n=1), K350R (n=1)
PCDH15 by frequency SNV / small indel 16 / 523 3.06% 2.88% 2 / 2 3.06–4.21% I1063N (n=1), T1258N (n=1), P315Q (n=1), T250N (n=1), D1521N (n=1)
MYCBP2 by frequency SNV / small indel 16 / 523 3.06% 2.69% 2 / 2 3.06–3.16% S2691* (n=1), L1599I (n=1), L934V (n=1), L1521F (n=1), G2042A (n=1)
KMT2A by frequency SNV / small indel 16 / 523 3.06% 2.69% 2 / 2 3.06–7.37% S2088R (n=1), L3344F (n=1), D1693H (n=1), E1863Gfs*12 (n=1), R2480Tfs*4 (n=1)
HUWE1 by frequency SNV / small indel 16 / 523 3.06% 2.69% 2 / 2 3.06–7.37% S2184N (n=1), R3739L (n=1), G3139W (n=1), S1903* (n=1), L3707Q (n=1)
HIVEP3 by frequency amplification 45 / 572 7.87% mutation 3.06% 2.88% 2 / 2 2.11–3.06% I151M (n=1), R2171L (n=1), L1250I (n=1), S1504L (n=1), L2169V (n=1)
DYSF by frequency SNV / small indel 16 / 523 3.06% 2.69% 2 / 2 1.05–3.06% K1598N (n=1), N401K (n=1), T900A (n=1), G407C (n=1), W857L (n=1)
VWF by frequency amplification 33 / 572 5.77% mutation 2.87% 2.69% 2 / 2 2.87–4.21% S2435N (n=1), I1416M (n=1), H1419N (n=1), P828H (n=1), V775L (n=1)
SZT2 by frequency amplification 38 / 572 6.64% mutation 2.87% 2.5% 2 / 2 1.05–2.87% Y205* (n=1), V1546I (n=1), G2532C (n=1), R1681C (n=1), E3126V (n=1)
NOTCH4 by frequency amplification 19 / 572 3.32% mutation 2.87% 2.5% 2 / 2 2.11–2.87% A1175T (n=1), X813_splice (n=1), Q1982Sfs*3 (n=1), N1996Kfs*7 (n=1), M252I (n=1)
CACNA1C by frequency amplification 41 / 572 7.17% mutation 2.87% 2.88% 2 / 2 2.87–5.26% V1247I (n=1), L933M (n=1), A71E (n=1), A1747S (n=1), R462Q (n=1)
VPS13C by frequency SNV / small indel 14 / 523 2.68% 2.31% 2 / 2 2.11–2.68% E994D (n=1), Q268K (n=1), Q623K (n=1), M3080I (n=1), S1022C (n=1)
UBR4 by frequency SNV / small indel 14 / 523 2.68% 2.31% 2 / 2 2.11–2.68% R4115T (n=1), P2610Q (n=1), R1336L (n=1), E3604* (n=1), P2467L (n=1)
RNF213 by frequency amplification 22 / 572 3.85% mutation 2.68% 2.69% 2 / 2 2.68–3.16% I3332F (n=1), K2668N (n=1), D4440N (n=1), Q973H (n=1), Q197L (n=1)

Cohorts

Listed in the disease profile, not searched: a name search returns the same patients under several accessions. Patients are unique patient ids in the study's sequenced sample list. Hypermutated: more than ten times the cohort's median non-silent mutations per sample, and at least 100.

CohortAccessionPatientsSamples sequenced / in studyAssayPanels (samples)BuildProfiles readHypermutated patientsMedian mutations / sample
Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas) reference
Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)
ov_tcga_pan_can_atlas_2018523 observed523 / 585exome or genomeWES (523)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)356
Ovarian Cancer (CPTAC GDC, 2025)
Ovarian Cancer (CPTAC GDC, 2025)
ovary_cptac_gdc95 observed95 / 112exome or genomeWES (95)hg38SNV, small indel162

Copy-number events

Discrete calls from each study's copy-number profile: 2 is high-level amplification, −2 deep deletion. Gains and shallow losses are not counted. Denominators are the cohort's copy-number sample list, which differs from its sequenced list. Rows at 2% or more.

GeneEventObserved patientsTested patientsFrequencyCohortProfile
TGamplification16657229.02%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
PIK3CAamplification11657220.28%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
CCNE1amplification11257219.58%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
SIamplification9057215.73%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
VPS13Bamplification6257210.84%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
KRASamplification545729.44%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
FCGBPamplification505728.74%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
RB1deep deletion495728.57%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
HIVEP3amplification455727.87%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
KMT2Camplification425727.34%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
CACNA1Camplification415727.17%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
PDE4DIPamplification385726.64%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
SZT2amplification385726.64%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
NF1deep deletion365726.29%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
VWFamplification335725.77%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
FOLR1amplification275724.72%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
PTENdeep deletion265724.55%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
MUC16amplification245724.2%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
PTPRZ1amplification245724.2%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
RNF213amplification225723.85%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
RELNamplification195723.32%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
NOTCH4amplification195723.32%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
HUWE1amplification175722.97%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
PKHD1amplification145722.45%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
LRRK2amplification135722.27%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
DYNC1H1amplification135722.27%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic
TACC2amplification135722.27%ov_tcga_pan_can_atlas_2018ov_tcga_pan_can_atlas_2018_gistic

Cohort-aware frequencies

Each row is calculated from unique patients in that study's sequenced sample list. The range is descriptive; no pooled estimate is shown because cross-study overlap and assay comparability have not been checked.

GeneRangePer cohort (altered / tested)
TP5370.94–77.89%ov_tcga_pan_can_atlas_2018: 371/523 (70.94%) · ovary_cptac_gdc: 74/95 (77.89%)
BRCA13.44–6.32%ov_tcga_pan_can_atlas_2018: 18/523 (3.44%) · ovary_cptac_gdc: 6/95 (6.32%)
BRCA22.87–3.16%ov_tcga_pan_can_atlas_2018: 15/523 (2.87%) · ovary_cptac_gdc: 3/95 (3.16%)
CCNE10.0–0.38%ov_tcga_pan_can_atlas_2018: 2/523 (0.38%) · ovary_cptac_gdc: 0/95 (0.0%)
FOLR10.0–0.57%ov_tcga_pan_can_atlas_2018: 3/523 (0.57%) · ovary_cptac_gdc: 0/95 (0.0%)
MUC167.84–12.63%ov_tcga_pan_can_atlas_2018: 41/523 (7.84%) · ovary_cptac_gdc: 12/95 (12.63%)
MSLN0.0–0.0%ov_tcga_pan_can_atlas_2018: 0/523 (0.0%) · ovary_cptac_gdc: 0/95 (0.0%)
KRAS1.15–2.11%ov_tcga_pan_can_atlas_2018: 6/523 (1.15%) · ovary_cptac_gdc: 2/95 (2.11%)
ARID1A0.76–4.21%ov_tcga_pan_can_atlas_2018: 4/523 (0.76%) · ovary_cptac_gdc: 4/95 (4.21%)
PIK3CA1.53–3.16%ov_tcga_pan_can_atlas_2018: 8/523 (1.53%) · ovary_cptac_gdc: 3/95 (3.16%)
PTEN1.34–3.16%ov_tcga_pan_can_atlas_2018: 7/523 (1.34%) · ovary_cptac_gdc: 3/95 (3.16%)
NF13.16–5.74%ov_tcga_pan_can_atlas_2018: 30/523 (5.74%) · ovary_cptac_gdc: 3/95 (3.16%)
KMT2C4.59–5.26%ov_tcga_pan_can_atlas_2018: 24/523 (4.59%) · ovary_cptac_gdc: 5/95 (5.26%)
SI3.16–4.21%ov_tcga_pan_can_atlas_2018: 22/523 (4.21%) · ovary_cptac_gdc: 3/95 (3.16%)
MDN13.16–4.02%ov_tcga_pan_can_atlas_2018: 21/523 (4.02%) · ovary_cptac_gdc: 3/95 (3.16%)
FCGBP4.02–5.26%ov_tcga_pan_can_atlas_2018: 21/523 (4.02%) · ovary_cptac_gdc: 5/95 (5.26%)
COL6A32.11–4.02%ov_tcga_pan_can_atlas_2018: 21/523 (4.02%) · ovary_cptac_gdc: 2/95 (2.11%)
TG3.82–8.42%ov_tcga_pan_can_atlas_2018: 20/523 (3.82%) · ovary_cptac_gdc: 8/95 (8.42%)
MYH43.82–4.21%ov_tcga_pan_can_atlas_2018: 20/523 (3.82%) · ovary_cptac_gdc: 4/95 (4.21%)
MYH13.16–3.82%ov_tcga_pan_can_atlas_2018: 20/523 (3.82%) · ovary_cptac_gdc: 3/95 (3.16%)
LRP12.11–3.82%ov_tcga_pan_can_atlas_2018: 20/523 (3.82%) · ovary_cptac_gdc: 2/95 (2.11%)
TOP2A1.05–3.63%ov_tcga_pan_can_atlas_2018: 19/523 (3.63%) · ovary_cptac_gdc: 1/95 (1.05%)
SPEN3.16–3.63%ov_tcga_pan_can_atlas_2018: 19/523 (3.63%) · ovary_cptac_gdc: 3/95 (3.16%)
PKHD13.16–3.63%ov_tcga_pan_can_atlas_2018: 19/523 (3.63%) · ovary_cptac_gdc: 3/95 (3.16%)
LRRK23.16–3.63%ov_tcga_pan_can_atlas_2018: 19/523 (3.63%) · ovary_cptac_gdc: 3/95 (3.16%)
CDK123.16–3.63%ov_tcga_pan_can_atlas_2018: 19/523 (3.63%) · ovary_cptac_gdc: 3/95 (3.16%)
VPS13B3.16–3.44%ov_tcga_pan_can_atlas_2018: 18/523 (3.44%) · ovary_cptac_gdc: 3/95 (3.16%)
PEG33.16–3.44%ov_tcga_pan_can_atlas_2018: 18/523 (3.44%) · ovary_cptac_gdc: 3/95 (3.16%)
DYNC1H11.05–3.44%ov_tcga_pan_can_atlas_2018: 18/523 (3.44%) · ovary_cptac_gdc: 1/95 (1.05%)
TACC22.11–3.25%ov_tcga_pan_can_atlas_2018: 17/523 (3.25%) · ovary_cptac_gdc: 2/95 (2.11%)
RELN1.05–3.25%ov_tcga_pan_can_atlas_2018: 17/523 (3.25%) · ovary_cptac_gdc: 1/95 (1.05%)
PTPRZ12.11–3.25%ov_tcga_pan_can_atlas_2018: 17/523 (3.25%) · ovary_cptac_gdc: 2/95 (2.11%)
PDE4DIP1.05–3.25%ov_tcga_pan_can_atlas_2018: 17/523 (3.25%) · ovary_cptac_gdc: 1/95 (1.05%)
RB13.06–4.21%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 4/95 (4.21%)
PRUNE22.11–3.06%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 2/95 (2.11%)
PCDH153.06–4.21%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 4/95 (4.21%)
MYCBP23.06–3.16%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 3/95 (3.16%)
KMT2A3.06–7.37%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 7/95 (7.37%)
HUWE13.06–7.37%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 7/95 (7.37%)
HIVEP32.11–3.06%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 2/95 (2.11%)
DYSF1.05–3.06%ov_tcga_pan_can_atlas_2018: 16/523 (3.06%) · ovary_cptac_gdc: 1/95 (1.05%)
VWF2.87–4.21%ov_tcga_pan_can_atlas_2018: 15/523 (2.87%) · ovary_cptac_gdc: 4/95 (4.21%)
SZT21.05–2.87%ov_tcga_pan_can_atlas_2018: 15/523 (2.87%) · ovary_cptac_gdc: 1/95 (1.05%)
NOTCH42.11–2.87%ov_tcga_pan_can_atlas_2018: 15/523 (2.87%) · ovary_cptac_gdc: 2/95 (2.11%)
CACNA1C2.87–5.26%ov_tcga_pan_can_atlas_2018: 15/523 (2.87%) · ovary_cptac_gdc: 5/95 (5.26%)
VPS13C2.11–2.68%ov_tcga_pan_can_atlas_2018: 14/523 (2.68%) · ovary_cptac_gdc: 2/95 (2.11%)
UBR42.11–2.68%ov_tcga_pan_can_atlas_2018: 14/523 (2.68%) · ovary_cptac_gdc: 2/95 (2.11%)
RNF2132.68–3.16%ov_tcga_pan_can_atlas_2018: 14/523 (2.68%) · ovary_cptac_gdc: 3/95 (3.16%)

What this page does not do

Structural variants
Read the structural-variant profiles the studies carry; fusions are the defining event in several of these diseases.

Context
Stage, subtype, age and treatment line are not attached to any count; the cohorts differ on all four.

Interpretation
Activating versus inactivating, actionable versus not, and evidence level are not inferred here; the briefing's target table carries the drug and trial facts.

Limitations

How a machine should read this page

  1. Denominators: every frequency divides by the patients in one named cohort on whom the gene could be called; there is no disease-wide figure.
  2. Missing values: not_assayed (the panel did not carry the gene), not_observed (assayed, none found) and not_evaluable (the cohort could not be read) are three different facts and are never converted to zero.
  3. Counting: patients, not samples; several samples from one patient count once. Non-silent calls only.
  4. Copy number: a separate assay with a separate roster; discrete calls at ±2 only.
  5. Hypermutation: flagged per cohort; the headline keeps all patients and the frequency without them is reported beside it.
  6. Provenance: every value carries the study id, the retrieval date and the processing version; the source is the cBioPortal public API.

Machine endpoints: full landscape · genes · cohorts · the disease's own facts: /disease/ovarian-cancer.json.

Built by the BioTransfer briefings pipeline from the cBioPortal public API. The neuroblastoma page was assembled by hand and set the rules this page follows; how these are built.