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Disease intelligence · mutation landscape

Endometrial cancer mutation landscape

How often each gene is altered in endometrial 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: ucec_tcga_pan_can_atlas_2018 · JSON: /disease/endometrial-cancer/mutations.json · Back to the briefing

Answer block

In Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas) (517 sequenced patients, exome or genome), the most frequently altered of the 47 genes shown are PTEN 65.18%, PIK3CA 50.1%, ARID1A 43.91%, TP53 37.14%, PIK3R1 30.56%. Each figure divides by the patients on whom that gene could be called.

96 of 517 patients are hypermutated (more than 740 non-silent mutations, ten times the cohort median of 74); every gene's frequency without them is beside the headline.

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%.

Alterationucec_tcga_pan_can_atlas_2018
517 pts · exome or genome
ucec_ancestry_cds_msk_2023
1882 pts · targeted panel
PTEN SNV / small indel65.18%337/51749.95%940/1882
PTEN deep deletion3.63%19/5230.28%5/1812
PIK3CA SNV / small indel50.1%259/51743.78%824/1882
PIK3CA amplification6.69%35/5232.37%43/1812
TP53 SNV / small indel37.14%192/51745.16%850/1882
POLE SNV / small indel15.67%81/5174.84%91/1882
MLH1 SNV / small indel6.38%33/5171.75%33/1882
MSH2 SNV / small indel7.93%41/5173.72%70/1882
MSH6 SNV / small indel11.22%58/5174.62%87/1882
ARID1A SNV / small indel43.91%227/51742.08%792/1882
CTNNB1 SNV / small indel25.53%132/51715.73%296/1882
ESR1 SNV / small indel5.42%28/5173.08%58/1882
ESR1 amplification2.68%14/5230.28%5/1812
PGR SNV / small indel5.8%30/5170.16%3/1824
ERBB2 SNV / small indel7.16%37/5172.76%52/1882
ERBB2 amplification5.16%27/5234.64%84/1812
PIK3R1 SNV / small indel30.56%158/51725.72%484/1882
KMT2D SNV / small indel27.66%143/51712.27%231/1882
CTCF SNV / small indel24.56%127/51716.21%305/1882
ZFHX3 SNV / small indel23.79%123/51712.99%237/1824
ZFHX3 deep deletion2.49%13/5230.99%18/1812
KMT2B SNV / small indel21.86%113/51712.52%208/1661
KMT2B amplification3.25%17/5233.86%70/1812
CHD4 SNV / small indel21.86%113/517·
CHD4 amplification2.1%11/5230%
TAF1 SNV / small indel20.12%104/517·
FAT1 SNV / small indel19.92%103/5174.84%91/1882
ARHGAP35 SNV / small indel19.73%102/5171.26%6/476
KMT2C SNV / small indel19.54%101/5175.05%95/1882
ATM SNV / small indel19.15%99/5177.39%139/1882
KRAS SNV / small indel18.96%98/51718.97%357/1882
HUWE1 SNV / small indel18.76%97/517·
MDN1 SNV / small indel18.38%95/517·
FBXW7 SNV / small indel18.38%95/51714.67%276/1882
NSD1 SNV / small indel17.99%93/5175.47%103/1882
HERC2 SNV / small indel17.99%93/517·
MED12 SNV / small indel17.79%92/5174.73%89/1882
FAT2 SNV / small indel17.79%92/517·
CACNA1E SNV / small indel17.41%90/517·
LRP1 SNV / small indel17.02%88/517·
LAMA2 SNV / small indel17.02%88/517·
UBR4 SNV / small indel16.83%87/517·
PRKDC SNV / small indel16.83%87/517·
PRKDC amplification2.29%12/5230%
PPP2R1A SNV / small indel16.83%87/51712.01%226/1882
PCDH15 SNV / small indel16.83%87/517·
NBEA SNV / small indel16.83%87/517·
BCOR SNV / small indel16.83%87/5179.78%184/1882
DYNC2H1 SNV / small indel16.63%86/517·
MKI67 SNV / small indel16.44%85/517·
DCHS1 SNV / small indel16.44%85/517·
CHD3 SNV / small indel16.44%85/517·
FCGBP SNV / small indel16.25%84/517·
FCGBP amplification2.87%15/5230%
DYNC1H1 SNV / small indel16.25%84/517·
CEP290 SNV / small indel16.25%84/517·

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

Key findings

PTEN is mutated in 337 of 517 patients in Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas).
Numerator: 337 · Denominator: 517 · Frequency: 65.18% · Observed in 2 cohorts · Confidence: moderate · Source: ucec_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

PIK3CA is mutated in 259 of 517 patients in Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas).
Numerator: 259 · Denominator: 517 · Frequency: 50.1% · Observed in 2 cohorts · Confidence: moderate · Source: ucec_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

ARID1A is mutated in 227 of 517 patients in Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas).
Numerator: 227 · Denominator: 517 · Frequency: 43.91% · Observed in 2 cohorts · Confidence: moderate · Source: ucec_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

Gene table — reference cohort

Headline values are from the reference cohort, ucec_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
PTEN curated target SNV / small indel 337 / 517 65.18% 59.14% 2 / 2 49.95–65.18% R130G (n=41), R130Q (n=34), R233* (n=25), T319* (n=14), R130* (n=12)
PIK3CA curated target SNV / small indel 259 / 517 50.1% 45.13% 2 / 2 43.78–50.1% R88Q (n=36), H1047R (n=29), E542K (n=17), E545K (n=15), G118D (n=10)
TP53 curated target SNV / small indel 192 / 517 37.14% 38.72% 2 / 2 37.14–45.16% R273C (n=11), R273H (n=10), R248Q (n=8), R248W (n=7), R175H (n=7)
POLE curated target SNV / small indel 81 / 517 15.67% 3.09% 2 / 2 4.84–15.67% P286R (n=20), V411L (n=13), S297F (n=3), L424I (n=3), P916L (n=3)
MLH1 curated target SNV / small indel 33 / 517 6.38% 1.19% 2 / 2 1.75–6.38% R385C (n=2), A623T (n=1), G189D (n=1), G98V (n=1), R265C (n=1)
MSH2 curated target SNV / small indel 41 / 517 7.93% 0.48% 2 / 2 3.72–7.93% X426_splice (n=2), E580* (n=2), D352Y (n=1), R219I (n=1), R524C (n=1)
MSH6 curated target SNV / small indel 58 / 517 11.22% 2.14% 2 / 2 4.62–11.22% E946* (n=4), E1322* (n=3), R1076H (n=3), R959H (n=3), E1234* (n=3)
ARID1A curated target SNV / small indel 227 / 517 43.91% 36.34% 2 / 2 42.08–43.91% R1989* (n=23), D1850Tfs*33 (n=12), F2141Sfs*59 (n=7), K1072Nfs*21 (n=7), R1721* (n=6)
CTNNB1 curated target SNV / small indel 132 / 517 25.53% 22.57% 2 / 2 15.73–25.53% S37F (n=11), S37C (n=10), S33F (n=9), S33C (n=9), T41I (n=7)
ESR1 curated target SNV / small indel 28 / 517 5.42% 2.38% 2 / 2 3.08–5.42% D538G (n=3), R555H (n=2), D218N (n=2), A551V (n=1), C188R (n=1)
PGR curated target SNV / small indel 30 / 517 5.8% 2.85% 2 / 2 0.16–5.8% F591del (n=3), R740* (n=2), R788W (n=2), R740Q (n=2), A701T (n=1)
ERBB2 curated target SNV / small indel 37 / 517 7.16% 2.85% 2 / 2 2.76–7.16% R678Q (n=5), V842I (n=4), L755S (n=3), E1195K (n=1), X76_splice (n=1)
PIK3R1 by frequency SNV / small indel 158 / 517 30.56% 27.08% 2 / 2 25.72–30.56% R348* (n=15), X582_splice (n=11), N564D (n=6), R461* (n=6), R642* (n=5)
KMT2D by frequency SNV / small indel 143 / 517 27.66% 16.63% 2 / 2 12.27–27.66% G1235Vfs*95 (n=9), P2354Lfs*30 (n=7), R3707* (n=4), P647Hfs*283 (n=3), P1460Hfs*46 (n=2)
CTCF by frequency SNV / small indel 127 / 517 24.56% 18.29% 2 / 2 16.21–24.56% T204Nfs*26 (n=14), T204Qfs*18 (n=8), R448* (n=7), R377C (n=6), P378L (n=4)
ZFHX3 by frequency SNV / small indel 123 / 517 23.79% 13.54% 2 / 2 12.99–23.79% R1893Gfs*35 (n=8), E763Sfs*61 (n=5), Q2557Efs*21 (n=4), A3407Lfs*78 (n=4), R1439Q (n=3)
KMT2B by frequency SNV / small indel 113 / 517 21.86% 13.06% 2 / 2 12.52–21.86% G1879Vfs*16 (n=5), R1911Dfs*23 (n=3), P1201Rfs*154 (n=3), R1109Efs*73 (n=2), E1620K (n=2)
CHD4 by frequency SNV / small indel 113 / 517 21.86% 12.59% 1 / 2 21.86–21.86% R1105W (n=7), R975H (n=7), R1338I (n=5), R1162W (n=5), K73Rfs*129 (n=4)
TAF1 by frequency SNV / small indel 104 / 517 20.12% 9.5% 1 / 2 20.12–20.12% R869C (n=6), R539Q (n=5), R843W (n=4), R1163H (n=3), R843Q (n=3)
FAT1 by frequency SNV / small indel 103 / 517 19.92% 7.84% 2 / 2 4.84–19.92% R2597* (n=6), D3120N (n=3), E528K (n=3), R1795* (n=3), R1627* (n=3)
ARHGAP35 by frequency SNV / small indel 102 / 517 19.73% 9.74% 2 / 2 1.26–19.73% R997* (n=10), R433* (n=5), R109* (n=3), R1145* (n=3), R529* (n=3)
KMT2C by frequency SNV / small indel 101 / 517 19.54% 9.03% 2 / 2 5.05–19.54% R190Q (n=4), R4693Q (n=4), R4806* (n=4), S836Y (n=3), R56Q (n=3)
ATM by frequency SNV / small indel 99 / 517 19.15% 8.08% 2 / 2 7.39–19.15% R2598* (n=3), R250* (n=3), R248Q (n=3), R1086C (n=2), R2993* (n=2)
KRAS by frequency SNV / small indel 98 / 517 18.96% 17.58% 2 / 2 18.96–18.97% G12D (n=32), G12V (n=19), G13D (n=11), G12A (n=8), G12C (n=6)
HUWE1 by frequency SNV / small indel 97 / 517 18.76% 6.89% 1 / 2 18.76–18.76% F1592L (n=2), Y147C (n=2), R1780H (n=2), R2545C (n=2), R3990C (n=2)
MDN1 by frequency SNV / small indel 95 / 517 18.38% 6.89% 1 / 2 18.38–18.38% K1989Rfs*65 (n=6), S3113L (n=4), E1663* (n=3), R2204* (n=3), R1273C (n=2)
FBXW7 by frequency SNV / small indel 95 / 517 18.38% 12.35% 2 / 2 14.67–18.38% R465H (n=10), R465C (n=8), R505C (n=8), R689W (n=7), R658* (n=6)
NSD1 by frequency SNV / small indel 93 / 517 17.99% 8.31% 2 / 2 5.47–17.99% M1531Cfs*43 (n=12), V1486* (n=3), R2117* (n=2), R1914C (n=2), T545M (n=2)
HERC2 by frequency SNV / small indel 93 / 517 17.99% 5.46% 1 / 2 17.99–17.99% R3906C (n=4), E3913K (n=3), A330T (n=3), R1744Q (n=3), R746H (n=2)
MED12 by frequency SNV / small indel 92 / 517 17.79% 7.6% 2 / 2 4.73–17.79% R521H (n=4), E79D (n=3), E716D (n=2), X68_splice (n=2), R1266H (n=2)
FAT2 by frequency SNV / small indel 92 / 517 17.79% 6.65% 1 / 2 17.79–17.79% E1795* (n=3), R543H (n=3), E928* (n=2), G3018D (n=2), R1445Q (n=2)
CACNA1E by frequency SNV / small indel 90 / 517 17.41% 6.18% 1 / 2 17.41–17.41% D87N (n=3), L1006* (n=3), A1307T (n=2), S1937L (n=2), R938Q (n=2)
LRP1 by frequency SNV / small indel 88 / 517 17.02% 8.08% 1 / 2 17.02–17.02% R1026C (n=3), G3360R (n=2), R2707H (n=2), E4146K (n=2), R3702H (n=2)
LAMA2 by frequency SNV / small indel 88 / 517 17.02% 6.65% 1 / 2 17.02–17.02% R553* (n=3), S971Y (n=3), R84Q (n=2), F1085L (n=2), R1844H (n=2)
UBR4 by frequency SNV / small indel 87 / 517 16.83% 5.94% 1 / 2 16.83–16.83% M2803Cfs*16 (n=6), R5060W (n=3), R3425C (n=2), R3748* (n=2), R325H (n=2)
PRKDC by frequency SNV / small indel 87 / 517 16.83% 6.65% 1 / 2 16.83–16.83% R2521Q (n=6), E3638* (n=3), R1136H (n=3), R2597Q (n=3), N3604Kfs*3 (n=3)
PPP2R1A by frequency SNV / small indel 87 / 517 16.83% 14.73% 2 / 2 12.01–16.83% P179R (n=26), R183W (n=8), S256F (n=7), S256Y (n=3), E101K (n=2)
PCDH15 by frequency SNV / small indel 87 / 517 16.83% 6.41% 1 / 2 16.83–16.83% X436_splice (n=2), R683H (n=2), L1025I (n=2), E456* (n=2), S1509Y (n=2)
NBEA by frequency SNV / small indel 87 / 517 16.83% 5.94% 1 / 2 16.83–16.83% N1121Mfs*9 (n=6), E1710K (n=5), R2080* (n=3), R2756W (n=3), R1308* (n=3)
BCOR by frequency SNV / small indel 87 / 517 16.83% 9.03% 2 / 2 9.78–16.83% N1459S (n=27), L7Cfs*9 (n=2), S1667L (n=2), R1514* (n=2), R993W (n=2)
DYNC2H1 by frequency SNV / small indel 86 / 517 16.63% 4.28% 1 / 2 16.63–16.63% E883D (n=5), R3053Q (n=3), V2574I (n=2), R2015Q (n=2), E436* (n=2)
MKI67 by frequency SNV / small indel 85 / 517 16.44% 3.8% 1 / 2 16.44–16.44% E1374K (n=4), I1857Yfs*30 (n=4), N233Mfs*12 (n=3), P2590Hfs*4 (n=2), F1524L (n=2)
DCHS1 by frequency SNV / small indel 85 / 517 16.44% 5.46% 1 / 2 16.44–16.44% D2269N (n=5), R235Gfs*9 (n=4), D1677N (n=3), R2962W (n=2), R2127H (n=2)
CHD3 by frequency SNV / small indel 85 / 517 16.44% 7.84% 1 / 2 16.44–16.44% R540Vfs*16 (n=16), S861L (n=4), T376M (n=2), R1511C (n=2), R1381H (n=2)
FCGBP by frequency SNV / small indel 84 / 517 16.25% 6.18% 1 / 2 16.25–16.25% R487H (n=3), E1539K (n=3), L2306I (n=2), A4187T (n=2), A3420T (n=2)
DYNC1H1 by frequency SNV / small indel 84 / 517 16.25% 5.94% 1 / 2 16.25–16.25% R2398C (n=3), E97* (n=3), R1226W (n=3), L774I (n=2), F161Lfs*52 (n=2)
CEP290 by frequency SNV / small indel 84 / 517 16.25% 4.75% 1 / 2 16.25–16.25% R151Q (n=4), N2290Ifs*11 (n=3), N212Tfs*14 (n=3), E440* (n=3), R1926Q (n=3)

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
Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas) reference
Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)
ucec_tcga_pan_can_atlas_2018517 observed517 / 529exome or genomeWES (517)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)9674
Endometrial Cancer (MSK, Cancer Discovery 2023)
Endometrial Cancer (MSK, Cancer Discovery 2023)
ucec_ancestry_cds_msk_20231882 observed1882 / 1882targeted panelIMPACT468 (1185), IMPACT505 (476), IMPACT410 (163), IMPACT341 (58)hg19SNV, small indel, amplification, deep deletion05.0

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
PIK3CAamplification355236.69%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
ERBB2amplification275235.16%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
ERBB2amplification8418124.64%ucec_ancestry_cds_msk_2023ucec_ancestry_cds_msk_2023_cna
KMT2Bamplification7018123.86%ucec_ancestry_cds_msk_2023ucec_ancestry_cds_msk_2023_cna
PTENdeep deletion195233.63%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
KMT2Bamplification175233.25%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
FCGBPamplification155232.87%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
ESR1amplification145232.68%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
ZFHX3deep deletion135232.49%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
PIK3CAamplification4318122.37%ucec_ancestry_cds_msk_2023ucec_ancestry_cds_msk_2023_cna
PRKDCamplification125232.29%ucec_tcga_pan_can_atlas_2018ucec_tcga_pan_can_atlas_2018_gistic
CHD4amplification115232.1%ucec_tcga_pan_can_atlas_2018ucec_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)
PTEN49.95–65.18%ucec_tcga_pan_can_atlas_2018: 337/517 (65.18%) · ucec_ancestry_cds_msk_2023: 940/1882 (49.95%)
PIK3CA43.78–50.1%ucec_tcga_pan_can_atlas_2018: 259/517 (50.1%) · ucec_ancestry_cds_msk_2023: 824/1882 (43.78%)
TP5337.14–45.16%ucec_tcga_pan_can_atlas_2018: 192/517 (37.14%) · ucec_ancestry_cds_msk_2023: 850/1882 (45.16%)
POLE4.84–15.67%ucec_tcga_pan_can_atlas_2018: 81/517 (15.67%) · ucec_ancestry_cds_msk_2023: 91/1882 (4.84%)
MLH11.75–6.38%ucec_tcga_pan_can_atlas_2018: 33/517 (6.38%) · ucec_ancestry_cds_msk_2023: 33/1882 (1.75%)
MSH23.72–7.93%ucec_tcga_pan_can_atlas_2018: 41/517 (7.93%) · ucec_ancestry_cds_msk_2023: 70/1882 (3.72%)
MSH64.62–11.22%ucec_tcga_pan_can_atlas_2018: 58/517 (11.22%) · ucec_ancestry_cds_msk_2023: 87/1882 (4.62%)
ARID1A42.08–43.91%ucec_tcga_pan_can_atlas_2018: 227/517 (43.91%) · ucec_ancestry_cds_msk_2023: 792/1882 (42.08%)
CTNNB115.73–25.53%ucec_tcga_pan_can_atlas_2018: 132/517 (25.53%) · ucec_ancestry_cds_msk_2023: 296/1882 (15.73%)
ESR13.08–5.42%ucec_tcga_pan_can_atlas_2018: 28/517 (5.42%) · ucec_ancestry_cds_msk_2023: 58/1882 (3.08%)
PGR0.16–5.8%ucec_tcga_pan_can_atlas_2018: 30/517 (5.8%) · ucec_ancestry_cds_msk_2023: 3/1824 (0.16%)
ERBB22.76–7.16%ucec_tcga_pan_can_atlas_2018: 37/517 (7.16%) · ucec_ancestry_cds_msk_2023: 52/1882 (2.76%)
PIK3R125.72–30.56%ucec_tcga_pan_can_atlas_2018: 158/517 (30.56%) · ucec_ancestry_cds_msk_2023: 484/1882 (25.72%)
KMT2D12.27–27.66%ucec_tcga_pan_can_atlas_2018: 143/517 (27.66%) · ucec_ancestry_cds_msk_2023: 231/1882 (12.27%)
CTCF16.21–24.56%ucec_tcga_pan_can_atlas_2018: 127/517 (24.56%) · ucec_ancestry_cds_msk_2023: 305/1882 (16.21%)
ZFHX312.99–23.79%ucec_tcga_pan_can_atlas_2018: 123/517 (23.79%) · ucec_ancestry_cds_msk_2023: 237/1824 (12.99%)
KMT2B12.52–21.86%ucec_tcga_pan_can_atlas_2018: 113/517 (21.86%) · ucec_ancestry_cds_msk_2023: 208/1661 (12.52%)
CHD421.86–21.86%ucec_tcga_pan_can_atlas_2018: 113/517 (21.86%) · ucec_ancestry_cds_msk_2023: not assayed
TAF120.12–20.12%ucec_tcga_pan_can_atlas_2018: 104/517 (20.12%) · ucec_ancestry_cds_msk_2023: not assayed
FAT14.84–19.92%ucec_tcga_pan_can_atlas_2018: 103/517 (19.92%) · ucec_ancestry_cds_msk_2023: 91/1882 (4.84%)
ARHGAP351.26–19.73%ucec_tcga_pan_can_atlas_2018: 102/517 (19.73%) · ucec_ancestry_cds_msk_2023: 6/476 (1.26%)
KMT2C5.05–19.54%ucec_tcga_pan_can_atlas_2018: 101/517 (19.54%) · ucec_ancestry_cds_msk_2023: 95/1882 (5.05%)
ATM7.39–19.15%ucec_tcga_pan_can_atlas_2018: 99/517 (19.15%) · ucec_ancestry_cds_msk_2023: 139/1882 (7.39%)
KRAS18.96–18.97%ucec_tcga_pan_can_atlas_2018: 98/517 (18.96%) · ucec_ancestry_cds_msk_2023: 357/1882 (18.97%)
HUWE118.76–18.76%ucec_tcga_pan_can_atlas_2018: 97/517 (18.76%) · ucec_ancestry_cds_msk_2023: not assayed
MDN118.38–18.38%ucec_tcga_pan_can_atlas_2018: 95/517 (18.38%) · ucec_ancestry_cds_msk_2023: not assayed
FBXW714.67–18.38%ucec_tcga_pan_can_atlas_2018: 95/517 (18.38%) · ucec_ancestry_cds_msk_2023: 276/1882 (14.67%)
NSD15.47–17.99%ucec_tcga_pan_can_atlas_2018: 93/517 (17.99%) · ucec_ancestry_cds_msk_2023: 103/1882 (5.47%)
HERC217.99–17.99%ucec_tcga_pan_can_atlas_2018: 93/517 (17.99%) · ucec_ancestry_cds_msk_2023: not assayed
MED124.73–17.79%ucec_tcga_pan_can_atlas_2018: 92/517 (17.79%) · ucec_ancestry_cds_msk_2023: 89/1882 (4.73%)
FAT217.79–17.79%ucec_tcga_pan_can_atlas_2018: 92/517 (17.79%) · ucec_ancestry_cds_msk_2023: not assayed
CACNA1E17.41–17.41%ucec_tcga_pan_can_atlas_2018: 90/517 (17.41%) · ucec_ancestry_cds_msk_2023: not assayed
LRP117.02–17.02%ucec_tcga_pan_can_atlas_2018: 88/517 (17.02%) · ucec_ancestry_cds_msk_2023: not assayed
LAMA217.02–17.02%ucec_tcga_pan_can_atlas_2018: 88/517 (17.02%) · ucec_ancestry_cds_msk_2023: not assayed
UBR416.83–16.83%ucec_tcga_pan_can_atlas_2018: 87/517 (16.83%) · ucec_ancestry_cds_msk_2023: not assayed
PRKDC16.83–16.83%ucec_tcga_pan_can_atlas_2018: 87/517 (16.83%) · ucec_ancestry_cds_msk_2023: not assayed
PPP2R1A12.01–16.83%ucec_tcga_pan_can_atlas_2018: 87/517 (16.83%) · ucec_ancestry_cds_msk_2023: 226/1882 (12.01%)
PCDH1516.83–16.83%ucec_tcga_pan_can_atlas_2018: 87/517 (16.83%) · ucec_ancestry_cds_msk_2023: not assayed
NBEA16.83–16.83%ucec_tcga_pan_can_atlas_2018: 87/517 (16.83%) · ucec_ancestry_cds_msk_2023: not assayed
BCOR9.78–16.83%ucec_tcga_pan_can_atlas_2018: 87/517 (16.83%) · ucec_ancestry_cds_msk_2023: 184/1882 (9.78%)
DYNC2H116.63–16.63%ucec_tcga_pan_can_atlas_2018: 86/517 (16.63%) · ucec_ancestry_cds_msk_2023: not assayed
MKI6716.44–16.44%ucec_tcga_pan_can_atlas_2018: 85/517 (16.44%) · ucec_ancestry_cds_msk_2023: not assayed
DCHS116.44–16.44%ucec_tcga_pan_can_atlas_2018: 85/517 (16.44%) · ucec_ancestry_cds_msk_2023: not assayed
CHD316.44–16.44%ucec_tcga_pan_can_atlas_2018: 85/517 (16.44%) · ucec_ancestry_cds_msk_2023: not assayed
FCGBP16.25–16.25%ucec_tcga_pan_can_atlas_2018: 84/517 (16.25%) · ucec_ancestry_cds_msk_2023: not assayed
DYNC1H116.25–16.25%ucec_tcga_pan_can_atlas_2018: 84/517 (16.25%) · ucec_ancestry_cds_msk_2023: not assayed
CEP29016.25–16.25%ucec_tcga_pan_can_atlas_2018: 84/517 (16.25%) · ucec_ancestry_cds_msk_2023: not assayed

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/endometrial-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.