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Disease intelligence · mutation landscape

Head and neck cancer mutation landscape

How often each gene is altered in head and neck 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: hnsc_tcga_pan_can_atlas_2018 · JSON: /disease/head-and-neck-cancer/mutations.json · Back to the briefing

Answer block

In Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas) (515 sequenced patients, exome or genome), the most frequently altered of the 46 genes shown are TP53 68.54%, CDKN2A 30.75% (deep deletion), CCND1 23.21% (amplification), FAT1 21.55%, PIK3CA 17.48%. Each figure divides by the patients on whom that gene could be called.

4 of 515 patients are hypermutated (more than 990 non-silent mutations, ten times the cohort median of 99); every gene's frequency without them is beside the headline.

Of the briefing's 12 curated targets, 1 are altered in under 2% of this cohort (PDCD1): 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%.

Alterationhnsc_tcga_pan_can_atlas_2018
515 pts · exome or genome
hnc_mskcc_2016
151 pts · targeted panel
TP53 SNV / small indel68.54%353/51540.4%61/151
CDKN2A SNV / small indel20.39%105/51514.57%22/151
CDKN2A deep deletion30.75%159/5176.62%10/151
PIK3CA SNV / small indel17.48%90/51512.58%19/151
PIK3CA amplification15.67%81/5172.65%4/151
EGFR SNV / small indel2.52%13/5152.65%4/151
EGFR amplification10.44%54/5174.64%7/151
CD274 SNV / small indel0.39%2/5150%
CD274 amplification4.45%23/5172.65%4/151
PDCD1 SNV / small indel0.39%2/5150.66%1/151
NOTCH1 SNV / small indel17.09%88/51521.85%33/151
FAT1 SNV / small indel21.55%111/51514.57%22/151
FAT1 deep deletion6.77%35/5170.66%1/151
CCND1 SNV / small indel0.39%2/5150.66%1/151
CCND1 amplification23.21%120/5175.3%8/151
HRAS SNV / small indel6.02%31/5155.96%9/151
NFE2L2 SNV / small indel5.44%28/5155.3%8/151
NFE2L2 amplification3.29%17/5170%
TERT SNV / small indel0.58%3/5151.32%2/151
TERT amplification5.03%26/5171.32%2/151
KMT2D SNV / small indel14.95%77/51516.56%25/151
NSD1 SNV / small indel11.65%60/5155.3%8/151
CASP8 SNV / small indel10.68%55/5153.97%6/151
HUWE1 SNV / small indel9.71%50/515·
FAM135B SNV / small indel9.71%50/515·
FAM135B amplification7.16%37/5170%
SI SNV / small indel9.51%49/515·
SI amplification9.67%50/5170%
RELN SNV / small indel9.13%47/515·
RELN amplification3.09%16/5170%
PCDH15 SNV / small indel8.54%44/515·
PCDH11X SNV / small indel7.57%39/515·
LAMA2 SNV / small indel7.57%39/515·
HERC2 SNV / small indel7.38%38/515·
NAV3 SNV / small indel7.18%37/515·
KMT2C SNV / small indel7.18%37/5159.93%15/151
EP300 SNV / small indel7.18%37/5154.64%7/151
UNC13C SNV / small indel6.99%36/515·
VPS13B SNV / small indel6.6%34/515·
VPS13B amplification4.06%21/5170%
PRDM9 SNV / small indel6.6%34/515·
PRDM9 amplification2.9%15/5170%
PKHD1 SNV / small indel6.41%33/515·
PEG3 SNV / small indel6.41%33/515·
NPAP1 SNV / small indel6.41%33/515·
FMN2 SNV / small indel6.41%33/515·
FBXW7 SNV / small indel6.41%33/5152.65%4/151
FAT2 SNV / small indel6.21%32/515·
AKAP9 SNV / small indel6.21%32/515·
AKAP9 amplification3.87%20/5170%
THSD7A SNV / small indel6.02%31/515·
MROH2B SNV / small indel6.02%31/515·
MROH2B amplification3.87%20/5170%
LRP1 SNV / small indel6.02%31/515·
CDH10 SNV / small indel6.02%31/515·
CDH10 amplification2.9%15/5170%
ASPM SNV / small indel6.02%31/515·
SCN1A SNV / small indel5.83%30/515·
RNF213 SNV / small indel5.83%30/515·
MDN1 SNV / small indel5.83%30/515·
DCHS2 SNV / small indel5.83%30/515·
CREBBP SNV / small indel5.83%30/5155.3%8/151

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 353 of 515 patients in Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas).
Numerator: 353 · Denominator: 515 · Frequency: 68.54% · Observed in 2 cohorts · Confidence: moderate · Source: hnsc_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

CDKN2A is deleted in 159 of 517 patients in Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas).
Numerator: 159 · Denominator: 517 · Frequency: 30.75% · Observed in 2 cohorts · Confidence: moderate · Source: hnsc_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

CCND1 is amplified in 120 of 517 patients in Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas).
Numerator: 120 · Denominator: 517 · Frequency: 23.21% · Observed in 2 cohorts · Confidence: moderate · Source: hnsc_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

Gene table — reference cohort

Headline values are from the reference cohort, hnsc_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 353 / 515 68.54% 68.49% 2 / 2 40.4–68.54% R175H (n=12), R282W (n=11), R248Q (n=11), G245S (n=8), R273H (n=8)
CDKN2A curated target deep deletion 159 / 517 30.75% mutation 20.39% 20.16% 2 / 2 14.57–20.39% R80* (n=23), R58* (n=12), W110* (n=10), X153_splice (n=9), E120* (n=5)
PIK3CA curated target SNV / small indel 90 / 515 17.48% 17.42% 2 / 2 12.58–17.48% E545K (n=26), E542K (n=19), H1047R (n=13), E726K (n=2), Q546R (n=2)
EGFR curated target amplification 54 / 517 10.44% mutation 2.52% 2.54% 2 / 2 2.52–2.65% D191N (n=1), G503S (n=1), A419P (n=1), I475V (n=1), P373Q (n=1)
CD274 curated target amplification 23 / 517 4.45% mutation 0.39% 0.39% 1 / 2 0.0–0.39% F259L (n=1), E71K (n=1)
PDCD1 curated target deep deletion 8 / 517 1.55% mutation 0.39% 0.39% 2 / 2 0.39–0.66% R112M (n=1), V239Rfs*6 (n=1)
NOTCH1 curated target SNV / small indel 88 / 515 17.09% 17.03% 2 / 2 17.09–21.85% E455K (n=3), R353C (n=2), A465T (n=2), G481C (n=1), Q513Hfs*116 (n=1)
FAT1 curated target SNV / small indel 111 / 515 21.55% 21.72% 2 / 2 14.57–21.55% S3373* (n=3), R937* (n=2), S2838* (n=2), R3400* (n=2), Q1694* (n=2)
CCND1 curated target amplification 120 / 517 23.21% mutation 0.39% 0.39% 2 / 2 0.39–0.66% P287L (n=1), D282H (n=1)
HRAS curated target SNV / small indel 31 / 515 6.02% 5.87% 2 / 2 5.96–6.02% G13V (n=8), G12S (n=7), G13R (n=3), Q61L (n=3), G12D (n=3)
NFE2L2 curated target SNV / small indel 28 / 515 5.44% 5.48% 2 / 2 5.3–5.44% E79Q (n=3), D29H (n=3), E79K (n=3), D262E (n=1), R34P (n=1)
TERT curated target amplification 26 / 517 5.03% mutation 0.58% 0.59% 2 / 2 0.58–1.32% P771L (n=1), R248W (n=1), G915D (n=1)
KMT2D by frequency SNV / small indel 77 / 515 14.95% 14.68% 2 / 2 14.95–16.56% Q2380* (n=2), R1252* (n=2), H5114Y (n=1), S654Pfs*276 (n=1), S2483C (n=1)
NSD1 by frequency SNV / small indel 60 / 515 11.65% 11.55% 2 / 2 5.3–11.65% R788* (n=2), I1873Kfs*18 (n=2), S707* (n=1), P1665L (n=1), E1575* (n=1)
CASP8 by frequency SNV / small indel 55 / 515 10.68% 10.57% 2 / 2 3.97–10.68% Q524* (n=4), X243_splice (n=3), R494* (n=3), R472* (n=3), R127* (n=2)
HUWE1 by frequency SNV / small indel 50 / 515 9.71% 9.39% 1 / 2 9.71–9.71% E3771K (n=2), E4177K (n=2), K4204del (n=2), H4339Y (n=1), G4370D (n=1)
FAM135B by frequency SNV / small indel 50 / 515 9.71% 9.2% 1 / 2 9.71–9.71% A418E (n=1), E1105Q (n=1), P549L (n=1), E289K (n=1), H1337Y (n=1)
SI by frequency amplification 50 / 517 9.67% mutation 9.51% 9.39% 1 / 2 9.51–9.51% I1343L (n=1), Y1063C (n=1), Q175E (n=1), Q1463H (n=1), I1271Nfs*3 (n=1)
RELN by frequency SNV / small indel 47 / 515 9.13% 8.61% 1 / 2 9.13–9.13% M944K (n=1), V2679L (n=1), V2092M (n=1), G2273D (n=1), D2941V (n=1)
PCDH15 by frequency SNV / small indel 44 / 515 8.54% 8.41% 1 / 2 8.54–8.54% X198_splice (n=1), R1292L (n=1), G794A (n=1), R598T (n=1), I385Tfs*32 (n=1)
PCDH11X by frequency SNV / small indel 39 / 515 7.57% 6.85% 1 / 2 7.57–7.57% A23T (n=2), D458H (n=1), S630* (n=1), M34I (n=1), A942D (n=1)
LAMA2 by frequency SNV / small indel 39 / 515 7.57% 7.05% 1 / 2 7.57–7.57% R2231S (n=1), G542V (n=1), E1637Q (n=1), P63H (n=1), E640* (n=1)
HERC2 by frequency SNV / small indel 38 / 515 7.38% 7.05% 1 / 2 7.38–7.38% I4701T (n=1), R3836W (n=1), R3671* (n=1), G2229* (n=1), T3325P (n=1)
NAV3 by frequency SNV / small indel 37 / 515 7.18% 7.05% 1 / 2 7.18–7.18% K549E (n=1), R855Q (n=1), R832G (n=1), G1148C (n=1), R1529G (n=1)
KMT2C by frequency SNV / small indel 37 / 515 7.18% 6.85% 2 / 2 7.18–9.93% X395_splice (n=2), G1020V (n=1), R196Kfs*9 (n=1), S1867T (n=1), R1698S (n=1)
EP300 by frequency SNV / small indel 37 / 515 7.18% 7.05% 2 / 2 4.64–7.18% D1399N (n=5), C1164Y (n=2), X1224_splice (n=2), E1514K (n=2), N2379H (n=1)
UNC13C by frequency SNV / small indel 36 / 515 6.99% 6.85% 1 / 2 6.99–6.99% Q1248K (n=1), Q817K (n=1), R182Q (n=1), Q958* (n=1), K189N (n=1)
VPS13B by frequency SNV / small indel 34 / 515 6.6% 6.07% 1 / 2 6.6–6.6% X403_splice (n=1), E1879K (n=1), Q3213H (n=1), H1446L (n=1), T1561S (n=1)
PRDM9 by frequency SNV / small indel 34 / 515 6.6% 6.26% 1 / 2 6.6–6.6% R77Q (n=2), G588R (n=1), V889F (n=1), Q400E (n=1), E193* (n=1)
PKHD1 by frequency SNV / small indel 33 / 515 6.41% 6.07% 1 / 2 6.41–6.41% S3977F (n=1), I1120T (n=1), W1248* (n=1), T777M (n=1), D170N (n=1)
PEG3 by frequency SNV / small indel 33 / 515 6.41% 5.87% 1 / 2 6.41–6.41% S792R (n=1), R651G (n=1), D1069Y (n=1), R889S (n=1), G1424R (n=1)
NPAP1 by frequency SNV / small indel 33 / 515 6.41% 5.87% 1 / 2 6.41–6.41% S528F (n=1), L437I (n=1), A134V (n=1), P119L (n=1), V114L (n=1)
FMN2 by frequency SNV / small indel 33 / 515 6.41% 6.07% 1 / 2 6.41–6.41% M1488I (n=1), K1648N (n=1), R94C (n=1), N1505I (n=1), S428L (n=1)
FBXW7 by frequency SNV / small indel 33 / 515 6.41% 6.46% 2 / 2 2.65–6.41% R505G (n=6), R479Q (n=3), R543G (n=2), A502V (n=1), R465C (n=1)
FAT2 by frequency SNV / small indel 32 / 515 6.21% 5.87% 1 / 2 6.21–6.21% F1838L (n=1), Q3697* (n=1), P1884H (n=1), N2102Kfs*35 (n=1), D1272G (n=1)
AKAP9 by frequency SNV / small indel 32 / 515 6.21% 5.87% 1 / 2 6.21–6.21% D3631H (n=1), E1344Q (n=1), Q413R (n=1), R3787* (n=1), E2670Q (n=1)
THSD7A by frequency SNV / small indel 31 / 515 6.02% 5.68% 1 / 2 6.02–6.02% R1046C (n=2), C728F (n=2), X1306_splice (n=2), V1571A (n=1), D1654V (n=1)
MROH2B by frequency SNV / small indel 31 / 515 6.02% 5.48% 1 / 2 6.02–6.02% G532R (n=1), W896L (n=1), Q723E (n=1), T1173I (n=1), R223W (n=1)
LRP1 by frequency SNV / small indel 31 / 515 6.02% 5.87% 1 / 2 6.02–6.02% N615S (n=1), V268M (n=1), S3955L (n=1), V1959L (n=1), G1467D (n=1)
CDH10 by frequency SNV / small indel 31 / 515 6.02% 5.68% 1 / 2 6.02–6.02% D481V (n=1), T495N (n=1), R449L (n=1), P270A (n=1), T298A (n=1)
ASPM by frequency SNV / small indel 31 / 515 6.02% 6.07% 1 / 2 6.02–6.02% E17D (n=1), R1765T (n=1), Q1800H (n=1), V571L (n=1), R1405H (n=1)
SCN1A by frequency SNV / small indel 30 / 515 5.83% 5.68% 1 / 2 5.83–5.83% G1470V (n=1), V1582A (n=1), F1718L (n=1), T1247M (n=1), H698Q (n=1)
RNF213 by frequency SNV / small indel 30 / 515 5.83% 5.68% 1 / 2 5.83–5.83% E4152K (n=1), M2419I (n=1), Q2176K (n=1), Q5080E (n=1), E3844K (n=1)
MDN1 by frequency SNV / small indel 30 / 515 5.83% 5.48% 1 / 2 5.83–5.83% R2957S (n=1), E1802V (n=1), E1542K (n=1), K717T (n=1), V4171I (n=1)
DCHS2 by frequency SNV / small indel 30 / 515 5.83% 5.28% 1 / 2 5.83–5.83% A1138S (n=1), A2536S (n=1), I487L (n=1), Y2860Tfs*10 (n=1), K381* (n=1)
CREBBP by frequency SNV / small indel 30 / 515 5.83% 5.28% 2 / 2 5.3–5.83% R1446C (n=2), L1556V (n=1), Q355Tfs*12 (n=1), E1023K (n=1), L1251M (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
Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas) reference
Head and Neck Squamous Cell Carcinoma (TCGA, PanCancer Atlas)
hnsc_tcga_pan_can_atlas_2018515 observed515 / 523exome or genomeWES (515)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)499
Recurrent and Metastatic Head & Neck Cancer (MSK, JAMA Oncol 2016)
Recurrent and Metastatic Head & Neck Cancer (MSK, JAMA Oncol 2016)
hnc_mskcc_2016151 observed151 / 151targeted panelIMPACT410 (151)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)13

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
CDKN2Adeep deletion15951730.75%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
CCND1amplification12051723.21%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
PIK3CAamplification8151715.67%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
EGFRamplification5451710.44%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
SIamplification505179.67%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
FAM135Bamplification375177.16%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
FAT1deep deletion355176.77%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
CDKN2Adeep deletion101516.62%hnc_mskcc_2016hnc_mskcc_2016_gistic
CCND1amplification81515.3%hnc_mskcc_2016hnc_mskcc_2016_gistic
TERTamplification265175.03%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
EGFRamplification71514.64%hnc_mskcc_2016hnc_mskcc_2016_gistic
CD274amplification235174.45%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
VPS13Bamplification215174.06%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
AKAP9amplification205173.87%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
MROH2Bamplification205173.87%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
NFE2L2amplification175173.29%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
RELNamplification165173.09%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
PRDM9amplification155172.9%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
CDH10amplification155172.9%hnsc_tcga_pan_can_atlas_2018hnsc_tcga_pan_can_atlas_2018_gistic
PIK3CAamplification41512.65%hnc_mskcc_2016hnc_mskcc_2016_gistic
CD274amplification41512.65%hnc_mskcc_2016hnc_mskcc_2016_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)
TP5340.4–68.54%hnsc_tcga_pan_can_atlas_2018: 353/515 (68.54%) · hnc_mskcc_2016: 61/151 (40.4%)
CDKN2A14.57–20.39%hnsc_tcga_pan_can_atlas_2018: 105/515 (20.39%) · hnc_mskcc_2016: 22/151 (14.57%)
PIK3CA12.58–17.48%hnsc_tcga_pan_can_atlas_2018: 90/515 (17.48%) · hnc_mskcc_2016: 19/151 (12.58%)
EGFR2.52–2.65%hnsc_tcga_pan_can_atlas_2018: 13/515 (2.52%) · hnc_mskcc_2016: 4/151 (2.65%)
CD2740.0–0.39%hnsc_tcga_pan_can_atlas_2018: 2/515 (0.39%) · hnc_mskcc_2016: 0/151 (0.0%)
PDCD10.39–0.66%hnsc_tcga_pan_can_atlas_2018: 2/515 (0.39%) · hnc_mskcc_2016: 1/151 (0.66%)
NOTCH117.09–21.85%hnsc_tcga_pan_can_atlas_2018: 88/515 (17.09%) · hnc_mskcc_2016: 33/151 (21.85%)
FAT114.57–21.55%hnsc_tcga_pan_can_atlas_2018: 111/515 (21.55%) · hnc_mskcc_2016: 22/151 (14.57%)
CCND10.39–0.66%hnsc_tcga_pan_can_atlas_2018: 2/515 (0.39%) · hnc_mskcc_2016: 1/151 (0.66%)
HRAS5.96–6.02%hnsc_tcga_pan_can_atlas_2018: 31/515 (6.02%) · hnc_mskcc_2016: 9/151 (5.96%)
NFE2L25.3–5.44%hnsc_tcga_pan_can_atlas_2018: 28/515 (5.44%) · hnc_mskcc_2016: 8/151 (5.3%)
TERT0.58–1.32%hnsc_tcga_pan_can_atlas_2018: 3/515 (0.58%) · hnc_mskcc_2016: 2/151 (1.32%)
KMT2D14.95–16.56%hnsc_tcga_pan_can_atlas_2018: 77/515 (14.95%) · hnc_mskcc_2016: 25/151 (16.56%)
NSD15.3–11.65%hnsc_tcga_pan_can_atlas_2018: 60/515 (11.65%) · hnc_mskcc_2016: 8/151 (5.3%)
CASP83.97–10.68%hnsc_tcga_pan_can_atlas_2018: 55/515 (10.68%) · hnc_mskcc_2016: 6/151 (3.97%)
HUWE19.71–9.71%hnsc_tcga_pan_can_atlas_2018: 50/515 (9.71%) · hnc_mskcc_2016: not assayed
FAM135B9.71–9.71%hnsc_tcga_pan_can_atlas_2018: 50/515 (9.71%) · hnc_mskcc_2016: not assayed
SI9.51–9.51%hnsc_tcga_pan_can_atlas_2018: 49/515 (9.51%) · hnc_mskcc_2016: not assayed
RELN9.13–9.13%hnsc_tcga_pan_can_atlas_2018: 47/515 (9.13%) · hnc_mskcc_2016: not assayed
PCDH158.54–8.54%hnsc_tcga_pan_can_atlas_2018: 44/515 (8.54%) · hnc_mskcc_2016: not assayed
PCDH11X7.57–7.57%hnsc_tcga_pan_can_atlas_2018: 39/515 (7.57%) · hnc_mskcc_2016: not assayed
LAMA27.57–7.57%hnsc_tcga_pan_can_atlas_2018: 39/515 (7.57%) · hnc_mskcc_2016: not assayed
HERC27.38–7.38%hnsc_tcga_pan_can_atlas_2018: 38/515 (7.38%) · hnc_mskcc_2016: not assayed
NAV37.18–7.18%hnsc_tcga_pan_can_atlas_2018: 37/515 (7.18%) · hnc_mskcc_2016: not assayed
KMT2C7.18–9.93%hnsc_tcga_pan_can_atlas_2018: 37/515 (7.18%) · hnc_mskcc_2016: 15/151 (9.93%)
EP3004.64–7.18%hnsc_tcga_pan_can_atlas_2018: 37/515 (7.18%) · hnc_mskcc_2016: 7/151 (4.64%)
UNC13C6.99–6.99%hnsc_tcga_pan_can_atlas_2018: 36/515 (6.99%) · hnc_mskcc_2016: not assayed
VPS13B6.6–6.6%hnsc_tcga_pan_can_atlas_2018: 34/515 (6.6%) · hnc_mskcc_2016: not assayed
PRDM96.6–6.6%hnsc_tcga_pan_can_atlas_2018: 34/515 (6.6%) · hnc_mskcc_2016: not assayed
PKHD16.41–6.41%hnsc_tcga_pan_can_atlas_2018: 33/515 (6.41%) · hnc_mskcc_2016: not assayed
PEG36.41–6.41%hnsc_tcga_pan_can_atlas_2018: 33/515 (6.41%) · hnc_mskcc_2016: not assayed
NPAP16.41–6.41%hnsc_tcga_pan_can_atlas_2018: 33/515 (6.41%) · hnc_mskcc_2016: not assayed
FMN26.41–6.41%hnsc_tcga_pan_can_atlas_2018: 33/515 (6.41%) · hnc_mskcc_2016: not assayed
FBXW72.65–6.41%hnsc_tcga_pan_can_atlas_2018: 33/515 (6.41%) · hnc_mskcc_2016: 4/151 (2.65%)
FAT26.21–6.21%hnsc_tcga_pan_can_atlas_2018: 32/515 (6.21%) · hnc_mskcc_2016: not assayed
AKAP96.21–6.21%hnsc_tcga_pan_can_atlas_2018: 32/515 (6.21%) · hnc_mskcc_2016: not assayed
THSD7A6.02–6.02%hnsc_tcga_pan_can_atlas_2018: 31/515 (6.02%) · hnc_mskcc_2016: not assayed
MROH2B6.02–6.02%hnsc_tcga_pan_can_atlas_2018: 31/515 (6.02%) · hnc_mskcc_2016: not assayed
LRP16.02–6.02%hnsc_tcga_pan_can_atlas_2018: 31/515 (6.02%) · hnc_mskcc_2016: not assayed
CDH106.02–6.02%hnsc_tcga_pan_can_atlas_2018: 31/515 (6.02%) · hnc_mskcc_2016: not assayed
ASPM6.02–6.02%hnsc_tcga_pan_can_atlas_2018: 31/515 (6.02%) · hnc_mskcc_2016: not assayed
SCN1A5.83–5.83%hnsc_tcga_pan_can_atlas_2018: 30/515 (5.83%) · hnc_mskcc_2016: not assayed
RNF2135.83–5.83%hnsc_tcga_pan_can_atlas_2018: 30/515 (5.83%) · hnc_mskcc_2016: not assayed
MDN15.83–5.83%hnsc_tcga_pan_can_atlas_2018: 30/515 (5.83%) · hnc_mskcc_2016: not assayed
DCHS25.83–5.83%hnsc_tcga_pan_can_atlas_2018: 30/515 (5.83%) · hnc_mskcc_2016: not assayed
CREBBP5.3–5.83%hnsc_tcga_pan_can_atlas_2018: 30/515 (5.83%) · hnc_mskcc_2016: 8/151 (5.3%)

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/head-and-neck-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.