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Disease intelligence · mutation landscape

Melanoma mutation landscape

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

Retrieved 2026-09-17 · Reference cohort: skcm_tcga_pan_can_atlas_2018 · JSON: /disease/melanoma/mutations.json · Back to the briefing

Answer block

In TCGA PanCancer Atlas cutaneous melanoma (2018) (438 sequenced patients, exome or genome), the most frequently altered of the 51 genes shown are BRAF 53.2%, MGAM 39.5%, DSCAM 34.47%, MXRA5 32.65%, PCDH15 32.19%. Each figure divides by the patients on whom that gene could be called.

4 of 438 patients are hypermutated (more than 4390 non-silent mutations, ten times the cohort median of 439); every gene's frequency without them is beside the headline.

Of the briefing's 13 curated targets, 1 are altered in under 2% of this cohort (CTLA4): targets by expression, dependency or drug label, not by mutation. Frequency is not targetability, in either direction.

3 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%.

Alterationskcm_tcga_pan_can_atlas_2018
438 pts · exome or genome
mel_mskimpact_2020
696 pts · targeted panel
mel_dfci_2019
144 pts · exome or genome
BRAF SNV / small indel53.2%233/43843.25%301/69638.89%56/144
BRAF amplification4.09%15/3671.72%12/6960.69%1/144
NRAS SNV / small indel28.54%125/43829.74%207/69629.86%43/144
NRAS amplification3.0%11/3671.44%10/6961.39%2/144
NF1 SNV / small indel17.12%75/43827.87%194/69617.36%25/144
KIT SNV / small indel6.85%30/4385.6%39/6964.86%7/144
KIT amplification2.72%10/3671.29%9/6962.78%4/144
MAP2K1 SNV / small indel6.39%28/4388.48%59/6966.94%10/144
CDKN2A SNV / small indel13.47%59/43819.97%139/69611.81%17/144
CDKN2A deep deletion30.52%112/36725.86%180/69622.22%32/144
PTEN SNV / small indel9.82%43/43811.78%82/6967.64%11/144
PTEN deep deletion7.63%28/3673.88%27/6965.56%8/144
TERT SNV / small indel4.11%18/4389.91%69/6964.17%6/144
TERT amplification5.18%19/3672.59%18/6963.47%5/144
PDCD1 SNV / small indel3.65%16/4381.87%13/6962.78%4/144
CTLA4 SNV / small indel1.37%6/4382.3%16/6962.78%4/144
LAG3 SNV / small indel2.74%12/438·4.86%7/144
MITF SNV / small indel2.05%9/4382.16%15/6960.69%1/144
MITF amplification6.54%24/3673.45%24/6960.69%1/144
PMEL SNV / small indel3.88%17/438·0.69%1/144
MGAM SNV / small indel39.5%173/438·31.25%45/144
MGAM amplification3.27%12/3670%0.69%1/144
DSCAM SNV / small indel34.47%151/438·25.0%36/144
MXRA5 SNV / small indel32.65%143/438·33.33%48/144
PCDH15 SNV / small indel32.19%141/438·22.22%32/144
COL4A4 SNV / small indel30.82%135/438·19.44%28/144
SCN11A SNV / small indel29.91%131/438·14.58%21/144
MROH2B SNV / small indel29.68%130/438·19.44%28/144
UNC13C SNV / small indel29.0%127/438·20.14%29/144
SPHKAP SNV / small indel29.0%127/438·22.92%33/144
PTPRT SNV / small indel28.31%124/43836.49%254/69624.31%35/144
SCN10A SNV / small indel27.63%121/438·23.61%34/144
FAM135B SNV / small indel27.63%121/438·17.36%25/144
FAM135B amplification4.36%16/3670%4.17%6/144
ASXL3 SNV / small indel27.63%121/438·22.92%33/144
SVEP1 SNV / small indel27.17%119/438·16.67%24/144
ADGRG4 SNV / small indel27.17%119/438·18.06%26/144
MYH2 SNV / small indel26.94%118/438·23.61%34/144
GRIN2A SNV / small indel26.94%118/43831.18%217/69617.36%25/144
RELN SNV / small indel26.71%117/438·20.14%29/144
ERICH3 SNV / small indel26.71%117/438·20.14%29/144
DCC SNV / small indel26.03%114/438·22.92%33/144
SI SNV / small indel25.8%113/438·18.75%27/144
MYH1 SNV / small indel25.57%112/438·18.06%26/144
TACC2 SNV / small indel25.11%110/438·20.14%29/144
STXBP5L SNV / small indel24.89%109/438·13.89%20/144
CACNA1E SNV / small indel24.89%109/438·24.31%35/144
STAB2 SNV / small indel24.66%108/438·22.92%33/144
TRANK1 SNV / small indel24.43%107/438·23.61%34/144
SCN5A SNV / small indel24.43%107/438·13.89%20/144
NPAP1 SNV / small indel24.43%107/438·19.44%28/144
FCGBP SNV / small indel24.2%106/438·18.75%27/144
FCGBP amplification0%0%3.47%5/144
FRAS1 SNV / small indel23.97%105/438·16.67%24/144
C6 SNV / small indel23.97%105/438·18.06%26/144
ADAMTS20 SNV / small indel23.97%105/438·22.22%32/144
COL7A1 SNV / small indel23.74%104/438·16.67%24/144
COL3A1 SNV / small indel23.74%104/438·19.44%28/144
CMYA5 SNV / small indel23.74%104/438·21.53%31/144
CD163 SNV / small indel23.74%104/438·21.53%31/144
TLL1 SNV / small indel23.52%103/438·15.28%22/144

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

Key findings

BRAF is mutated in 233 of 438 patients in TCGA PanCancer Atlas cutaneous melanoma (2018).
Numerator: 233 · Denominator: 438 · Frequency: 53.2% · Observed in 3 cohorts · Confidence: moderate · Source: skcm_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-17

MGAM is mutated in 173 of 438 patients in TCGA PanCancer Atlas cutaneous melanoma (2018).
Numerator: 173 · Denominator: 438 · Frequency: 39.5% · Observed in 2 cohorts · Confidence: moderate · Source: skcm_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-17

DSCAM is mutated in 151 of 438 patients in TCGA PanCancer Atlas cutaneous melanoma (2018).
Numerator: 151 · Denominator: 438 · Frequency: 34.47% · Observed in 2 cohorts · Confidence: moderate · Source: skcm_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-17

Gene table — reference cohort

Headline values are from the reference cohort, skcm_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
BRAF curated target SNV / small indel 233 / 438 53.2% 53.0% 3 / 3 38.89–53.2% V600E (n=158), V600K (n=35), K601E (n=5), V600R (n=4), G466E (n=4)
NRAS curated target SNV / small indel 125 / 438 28.54% 28.8% 3 / 3 28.54–29.86% Q61R (n=54), Q61K (n=38), Q61L (n=16), Q61H (n=6), G12R (n=2)
NF1 curated target SNV / small indel 75 / 438 17.12% 16.36% 3 / 3 17.12–27.87% R440* (n=5), S2496F (n=2), Q282* (n=2), X69_splice (n=2), Q1070* (n=2)
KIT curated target SNV / small indel 30 / 438 6.85% 6.45% 3 / 3 4.86–6.85% K642E (n=6), V559A (n=3), L576P (n=2), M722I (n=1), W582L (n=1)
MAP2K1 curated target SNV / small indel 28 / 438 6.39% 6.45% 3 / 3 6.39–8.48% P124S (n=13), P124L (n=4), E203K (n=2), K57N (n=2), Q278H (n=1)
CDKN2A curated target deep deletion 112 / 367 30.52% mutation 13.47% 13.13% 3 / 3 11.81–19.97% P114L (n=10), R58* (n=6), W110* (n=5), X51_splice (n=5), Q50* (n=5)
PTEN curated target SNV / small indel 43 / 438 9.82% 9.91% 3 / 3 7.64–11.78% P38S (n=3), V166Sfs*14 (n=3), Q298* (n=2), X342_splice (n=2), R130* (n=1)
TERT curated target amplification 19 / 367 5.18% mutation 4.11% 3.69% 3 / 3 4.11–9.91% G830W (n=1), S802N (n=1), S1095P (n=1), R1105L (n=1), D628N (n=1)
PDCD1 curated target SNV / small indel 16 / 438 3.65% 3.69% 3 / 3 1.87–3.65% H107N (n=2), E211K (n=2), Q88* (n=1), S38F (n=1), S220F (n=1)
CTLA4 curated target SNV / small indel 6 / 438 1.37% 1.38% 3 / 3 1.37–2.78% *224Lext*16 (n=1), Q117* (n=1), G199R (n=1), P137Q (n=1), M91I (n=1)
LAG3 curated target SNV / small indel 12 / 438 2.74% 2.53% 2 / 3 2.74–4.86% G261C (n=1), W16L (n=1), S460F (n=1), I253S (n=1), G365E (n=1)
MITF curated target amplification 24 / 367 6.54% mutation 2.05% 2.07% 3 / 3 0.69–2.16% L106R (n=1), R298S (n=1), L484F (n=1), T127del (n=1), P210Q (n=1)
PMEL curated target SNV / small indel 17 / 438 3.88% 3.92% 2 / 3 0.69–3.88% P214S (n=1), Q583K (n=1), P91T (n=1), E437* (n=1), G228W (n=1)
MGAM by frequency SNV / small indel 173 / 438 39.5% 38.94% 2 / 3 31.25–39.5% P1091L (n=5), R98Q (n=5), R1097C (n=5), E805K (n=3), E435K (n=3)
DSCAM by frequency SNV / small indel 151 / 438 34.47% 33.87% 2 / 3 25.0–34.47% E368K (n=6), E1819K (n=6), D771N (n=5), E1464K (n=5), E1584K (n=4)
MXRA5 by frequency SNV / small indel 143 / 438 32.65% 32.03% 2 / 3 32.65–33.33% E2006K (n=7), G160E (n=4), G1070E (n=4), E886K (n=3), P1005S (n=2)
PCDH15 by frequency SNV / small indel 141 / 438 32.19% 31.57% 2 / 3 22.22–32.19% R764C (n=7), R1522K (n=5), E447K (n=3), R1414Q (n=3), R1273C (n=3)
COL4A4 by frequency SNV / small indel 135 / 438 30.82% 30.18% 2 / 3 19.44–30.82% G757E (n=3), G1204E (n=3), G426W (n=3), P892L (n=3), G1011E (n=3)
SCN11A by frequency SNV / small indel 131 / 438 29.91% 29.26% 2 / 3 14.58–29.91% R1679C (n=4), P1456S (n=3), E923K (n=3), G45E (n=3), E431K (n=3)
MROH2B by frequency SNV / small indel 130 / 438 29.68% 29.03% 2 / 3 19.44–29.68% S1436L (n=6), P173S (n=5), R834W (n=4), D1477N (n=4), E1292K (n=4)
UNC13C by frequency SNV / small indel 127 / 438 29.0% 28.57% 2 / 3 20.14–29.0% E301K (n=4), H2061Y (n=4), E249K (n=3), S1426L (n=3), E1701K (n=3)
SPHKAP by frequency SNV / small indel 127 / 438 29.0% 28.34% 2 / 3 22.92–29.0% E1138K (n=4), E1084K (n=4), G954E (n=4), R285Q (n=3), E1648K (n=3)
PTPRT by frequency SNV / small indel 124 / 438 28.31% 27.88% 3 / 3 24.31–36.49% L695F (n=5), D1285N (n=5), M900I (n=5), E324K (n=5), R328C (n=4)
SCN10A by frequency SNV / small indel 121 / 438 27.63% 26.96% 2 / 3 23.61–27.63% H506Y (n=4), R1782Q (n=4), M374I (n=4), E1239K (n=3), S1820F (n=2)
FAM135B by frequency SNV / small indel 121 / 438 27.63% 26.96% 2 / 3 17.36–27.63% R1211Q (n=3), S1073F (n=3), H92Y (n=3), M1345I (n=3), S657F (n=3)
ASXL3 by frequency SNV / small indel 121 / 438 27.63% 26.96% 2 / 3 22.92–27.63% P1370S (n=10), E453K (n=4), D1725N (n=2), E1645K (n=2), E882K (n=2)
SVEP1 by frequency SNV / small indel 119 / 438 27.17% 26.73% 2 / 3 16.67–27.17% E1165K (n=3), S2365F (n=3), G2786S (n=2), G1320R (n=2), P938L (n=2)
ADGRG4 by frequency SNV / small indel 119 / 438 27.17% 26.5% 2 / 3 18.06–27.17% E873K (n=4), G2695W (n=2), G1557W (n=2), S1414L (n=2), R1086C (n=2)
MYH2 by frequency SNV / small indel 118 / 438 26.94% 26.27% 2 / 3 23.61–26.94% E1382K (n=5), E878K (n=4), P228L (n=3), E347K (n=3), M858I (n=3)
GRIN2A by frequency SNV / small indel 118 / 438 26.94% 26.27% 3 / 3 17.36–31.18% G1322E (n=7), D1153N (n=3), R1067W (n=3), E743K (n=2), D1024N (n=2)
RELN by frequency SNV / small indel 117 / 438 26.71% 26.04% 2 / 3 20.14–26.71% S515F (n=2), W328* (n=2), W2786* (n=2), G804R (n=2), P2345L (n=2)
ERICH3 by frequency SNV / small indel 117 / 438 26.71% 26.04% 2 / 3 20.14–26.71% E1129K (n=3), E773K (n=3), S1524F (n=3), R259C (n=3), P239S (n=2)
DCC by frequency SNV / small indel 114 / 438 26.03% 25.35% 2 / 3 22.92–26.03% R1337* (n=6), R443Q (n=4), R1021* (n=4), G490E (n=4), R501* (n=3)
SI by frequency SNV / small indel 113 / 438 25.8% 25.81% 2 / 3 18.75–25.8% P579S (n=4), W255* (n=3), R157C (n=2), E643K (n=2), R250C (n=2)
MYH1 by frequency SNV / small indel 112 / 438 25.57% 24.88% 2 / 3 18.06–25.57% R791Q (n=6), S1739F (n=5), R24Q (n=4), E1906K (n=3), G1524E (n=3)
TACC2 by frequency SNV / small indel 110 / 438 25.11% 24.42% 2 / 3 20.14–25.11% P2247T (n=3), P781L (n=3), S2397F (n=2), H1486N (n=2), S1920L (n=2)
STXBP5L by frequency SNV / small indel 109 / 438 24.89% 24.19% 2 / 3 13.89–24.89% R696Q (n=4), E320K (n=3), G503E (n=3), R66L (n=2), P397L (n=2)
CACNA1E by frequency SNV / small indel 109 / 438 24.89% 24.19% 2 / 3 24.31–24.89% D1697N (n=4), R2099S (n=3), E1743K (n=3), E462K (n=3), E1690K (n=3)
STAB2 by frequency SNV / small indel 108 / 438 24.66% 23.96% 2 / 3 22.92–24.66% R243Q (n=4), S974L (n=3), G1956E (n=2), S1035F (n=2), G51E (n=2)
TRANK1 by frequency SNV / small indel 107 / 438 24.43% 23.73% 2 / 3 23.61–24.43% E791K (n=3), W2427* (n=3), G2338E (n=3), P2199S (n=3), E1752K (n=3)
SCN5A by frequency SNV / small indel 107 / 438 24.43% 23.73% 2 / 3 13.89–24.43% E431K (n=3), E446K (n=2), E1025K (n=2), G386E (n=2), Q1909* (n=2)
NPAP1 by frequency SNV / small indel 107 / 438 24.43% 23.73% 2 / 3 19.44–24.43% G210E (n=7), S528F (n=5), S887F (n=4), G481R (n=3), D173N (n=2)
FCGBP by frequency SNV / small indel 106 / 438 24.2% 23.5% 2 / 3 18.75–24.2% X5185_splice (n=2), P1427S (n=2), V732I (n=2), R1304Q (n=2), G1482S (n=2)
FRAS1 by frequency SNV / small indel 105 / 438 23.97% 23.73% 2 / 3 16.67–23.97% P1341S (n=2), E3004K (n=2), G2168E (n=2), S1336L (n=2), E2671K (n=2)
C6 by frequency SNV / small indel 105 / 438 23.97% 23.27% 2 / 3 18.06–23.97% R145C (n=6), E871K (n=4), S836F (n=4), S853L (n=3), E170K (n=3)
ADAMTS20 by frequency SNV / small indel 105 / 438 23.97% 23.5% 2 / 3 22.22–23.97% E1019K (n=4), M600I (n=3), S375L (n=3), E1753K (n=3), R359M (n=2)
COL7A1 by frequency SNV / small indel 104 / 438 23.74% 23.27% 2 / 3 16.67–23.74% P1582S (n=3), S430F (n=2), E1923K (n=2), P1410L (n=2), E1535K (n=2)
COL3A1 by frequency SNV / small indel 104 / 438 23.74% 23.04% 2 / 3 19.44–23.74% P80L (n=3), G1014E (n=3), G468R (n=3), P260H (n=3), G609E (n=2)
CMYA5 by frequency SNV / small indel 104 / 438 23.74% 23.04% 2 / 3 21.53–23.74% P478L (n=2), S904L (n=2), P3909H (n=2), E637K (n=2), P2097S (n=2)
CD163 by frequency SNV / small indel 104 / 438 23.74% 23.04% 2 / 3 21.53–23.74% R579K (n=3), S1113F (n=3), G641E (n=3), R584C (n=2), G565E (n=2)
TLL1 by frequency SNV / small indel 103 / 438 23.52% 23.04% 2 / 3 15.28–23.52% Q474* (n=3), E186K (n=3), G220E (n=3), P366S (n=3), R257Q (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
TCGA PanCancer Atlas cutaneous melanoma (2018) reference
Skin Cutaneous Melanoma (TCGA, PanCancer Atlas)
skcm_tcga_pan_can_atlas_2018438 observed440 / 448exome or genomeWES (440)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)4439.0
MSK-IMPACT melanoma (Clin Cancer Res 2021)
Melanoma (MSK, Clin Cancer Res 2021)
mel_mskimpact_2020696 observed696 / 696targeted panelIMPACT468 (437), IMPACT410 (221), IMPACT341 (38)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)417.0
DFCI metastatic melanoma (Nat Med 2019)
Metastatic Melanoma (DFCI, Nature Medicine 2019)
mel_dfci_2019144 observed144 / 144exome or genomeWES (144)hg19SNV, small indel, amplification, deep deletion5246.5

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 deletion11236730.52%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
CDKN2Adeep deletion18069625.86%mel_mskimpact_2020mel_mskimpact_2020_cna
CDKN2Adeep deletion3214422.22%mel_dfci_2019mel_dfci_2019_gistic
PTENdeep deletion283677.63%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
MITFamplification243676.54%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
PTENdeep deletion81445.56%mel_dfci_2019mel_dfci_2019_gistic
TERTamplification193675.18%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
FAM135Bamplification163674.36%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
FAM135Bamplification61444.17%mel_dfci_2019mel_dfci_2019_gistic
BRAFamplification153674.09%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
PTENdeep deletion276963.88%mel_mskimpact_2020mel_mskimpact_2020_cna
TERTamplification51443.47%mel_dfci_2019mel_dfci_2019_gistic
FCGBPamplification51443.47%mel_dfci_2019mel_dfci_2019_gistic
MITFamplification246963.45%mel_mskimpact_2020mel_mskimpact_2020_cna
MGAMamplification123673.27%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
NRASamplification113673.0%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
KITamplification41442.78%mel_dfci_2019mel_dfci_2019_gistic
KITamplification103672.72%skcm_tcga_pan_can_atlas_2018skcm_tcga_pan_can_atlas_2018_gistic
TERTamplification186962.59%mel_mskimpact_2020mel_mskimpact_2020_cna

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)
BRAF38.89–53.2%skcm_tcga_pan_can_atlas_2018: 233/438 (53.2%) · mel_mskimpact_2020: 301/696 (43.25%) · mel_dfci_2019: 56/144 (38.89%)
NRAS28.54–29.86%skcm_tcga_pan_can_atlas_2018: 125/438 (28.54%) · mel_mskimpact_2020: 207/696 (29.74%) · mel_dfci_2019: 43/144 (29.86%)
NF117.12–27.87%skcm_tcga_pan_can_atlas_2018: 75/438 (17.12%) · mel_mskimpact_2020: 194/696 (27.87%) · mel_dfci_2019: 25/144 (17.36%)
KIT4.86–6.85%skcm_tcga_pan_can_atlas_2018: 30/438 (6.85%) · mel_mskimpact_2020: 39/696 (5.6%) · mel_dfci_2019: 7/144 (4.86%)
MAP2K16.39–8.48%skcm_tcga_pan_can_atlas_2018: 28/438 (6.39%) · mel_mskimpact_2020: 59/696 (8.48%) · mel_dfci_2019: 10/144 (6.94%)
CDKN2A11.81–19.97%skcm_tcga_pan_can_atlas_2018: 59/438 (13.47%) · mel_mskimpact_2020: 139/696 (19.97%) · mel_dfci_2019: 17/144 (11.81%)
PTEN7.64–11.78%skcm_tcga_pan_can_atlas_2018: 43/438 (9.82%) · mel_mskimpact_2020: 82/696 (11.78%) · mel_dfci_2019: 11/144 (7.64%)
TERT4.11–9.91%skcm_tcga_pan_can_atlas_2018: 18/438 (4.11%) · mel_mskimpact_2020: 69/696 (9.91%) · mel_dfci_2019: 6/144 (4.17%)
PDCD11.87–3.65%skcm_tcga_pan_can_atlas_2018: 16/438 (3.65%) · mel_mskimpact_2020: 13/696 (1.87%) · mel_dfci_2019: 4/144 (2.78%)
CTLA41.37–2.78%skcm_tcga_pan_can_atlas_2018: 6/438 (1.37%) · mel_mskimpact_2020: 16/696 (2.3%) · mel_dfci_2019: 4/144 (2.78%)
LAG32.74–4.86%skcm_tcga_pan_can_atlas_2018: 12/438 (2.74%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 7/144 (4.86%)
MITF0.69–2.16%skcm_tcga_pan_can_atlas_2018: 9/438 (2.05%) · mel_mskimpact_2020: 15/696 (2.16%) · mel_dfci_2019: 1/144 (0.69%)
PMEL0.69–3.88%skcm_tcga_pan_can_atlas_2018: 17/438 (3.88%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 1/144 (0.69%)
MGAM31.25–39.5%skcm_tcga_pan_can_atlas_2018: 173/438 (39.5%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 45/144 (31.25%)
DSCAM25.0–34.47%skcm_tcga_pan_can_atlas_2018: 151/438 (34.47%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 36/144 (25.0%)
MXRA532.65–33.33%skcm_tcga_pan_can_atlas_2018: 143/438 (32.65%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 48/144 (33.33%)
PCDH1522.22–32.19%skcm_tcga_pan_can_atlas_2018: 141/438 (32.19%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 32/144 (22.22%)
COL4A419.44–30.82%skcm_tcga_pan_can_atlas_2018: 135/438 (30.82%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 28/144 (19.44%)
SCN11A14.58–29.91%skcm_tcga_pan_can_atlas_2018: 131/438 (29.91%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 21/144 (14.58%)
MROH2B19.44–29.68%skcm_tcga_pan_can_atlas_2018: 130/438 (29.68%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 28/144 (19.44%)
UNC13C20.14–29.0%skcm_tcga_pan_can_atlas_2018: 127/438 (29.0%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 29/144 (20.14%)
SPHKAP22.92–29.0%skcm_tcga_pan_can_atlas_2018: 127/438 (29.0%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 33/144 (22.92%)
PTPRT24.31–36.49%skcm_tcga_pan_can_atlas_2018: 124/438 (28.31%) · mel_mskimpact_2020: 254/696 (36.49%) · mel_dfci_2019: 35/144 (24.31%)
SCN10A23.61–27.63%skcm_tcga_pan_can_atlas_2018: 121/438 (27.63%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 34/144 (23.61%)
FAM135B17.36–27.63%skcm_tcga_pan_can_atlas_2018: 121/438 (27.63%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 25/144 (17.36%)
ASXL322.92–27.63%skcm_tcga_pan_can_atlas_2018: 121/438 (27.63%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 33/144 (22.92%)
SVEP116.67–27.17%skcm_tcga_pan_can_atlas_2018: 119/438 (27.17%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 24/144 (16.67%)
ADGRG418.06–27.17%skcm_tcga_pan_can_atlas_2018: 119/438 (27.17%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 26/144 (18.06%)
MYH223.61–26.94%skcm_tcga_pan_can_atlas_2018: 118/438 (26.94%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 34/144 (23.61%)
GRIN2A17.36–31.18%skcm_tcga_pan_can_atlas_2018: 118/438 (26.94%) · mel_mskimpact_2020: 217/696 (31.18%) · mel_dfci_2019: 25/144 (17.36%)
RELN20.14–26.71%skcm_tcga_pan_can_atlas_2018: 117/438 (26.71%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 29/144 (20.14%)
ERICH320.14–26.71%skcm_tcga_pan_can_atlas_2018: 117/438 (26.71%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 29/144 (20.14%)
DCC22.92–26.03%skcm_tcga_pan_can_atlas_2018: 114/438 (26.03%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 33/144 (22.92%)
SI18.75–25.8%skcm_tcga_pan_can_atlas_2018: 113/438 (25.8%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 27/144 (18.75%)
MYH118.06–25.57%skcm_tcga_pan_can_atlas_2018: 112/438 (25.57%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 26/144 (18.06%)
TACC220.14–25.11%skcm_tcga_pan_can_atlas_2018: 110/438 (25.11%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 29/144 (20.14%)
STXBP5L13.89–24.89%skcm_tcga_pan_can_atlas_2018: 109/438 (24.89%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 20/144 (13.89%)
CACNA1E24.31–24.89%skcm_tcga_pan_can_atlas_2018: 109/438 (24.89%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 35/144 (24.31%)
STAB222.92–24.66%skcm_tcga_pan_can_atlas_2018: 108/438 (24.66%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 33/144 (22.92%)
TRANK123.61–24.43%skcm_tcga_pan_can_atlas_2018: 107/438 (24.43%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 34/144 (23.61%)
SCN5A13.89–24.43%skcm_tcga_pan_can_atlas_2018: 107/438 (24.43%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 20/144 (13.89%)
NPAP119.44–24.43%skcm_tcga_pan_can_atlas_2018: 107/438 (24.43%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 28/144 (19.44%)
FCGBP18.75–24.2%skcm_tcga_pan_can_atlas_2018: 106/438 (24.2%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 27/144 (18.75%)
FRAS116.67–23.97%skcm_tcga_pan_can_atlas_2018: 105/438 (23.97%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 24/144 (16.67%)
C618.06–23.97%skcm_tcga_pan_can_atlas_2018: 105/438 (23.97%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 26/144 (18.06%)
ADAMTS2022.22–23.97%skcm_tcga_pan_can_atlas_2018: 105/438 (23.97%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 32/144 (22.22%)
COL7A116.67–23.74%skcm_tcga_pan_can_atlas_2018: 104/438 (23.74%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 24/144 (16.67%)
COL3A119.44–23.74%skcm_tcga_pan_can_atlas_2018: 104/438 (23.74%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 28/144 (19.44%)
CMYA521.53–23.74%skcm_tcga_pan_can_atlas_2018: 104/438 (23.74%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 31/144 (21.53%)
CD16321.53–23.74%skcm_tcga_pan_can_atlas_2018: 104/438 (23.74%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 31/144 (21.53%)
TLL115.28–23.52%skcm_tcga_pan_can_atlas_2018: 103/438 (23.52%) · mel_mskimpact_2020: not assayed · mel_dfci_2019: 22/144 (15.28%)

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/melanoma.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.