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Glioblastoma mutation landscape

How often each gene is altered in glioblastoma, 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: gbm_tcga_pan_can_atlas_2018 · JSON: /disease/glioblastoma/mutations.json · Back to the briefing

Answer block

In TCGA PanCancer Atlas glioblastoma (2018) (390 sequenced patients, exome or genome), the most frequently altered of the 45 genes shown are CDKN2A 56.0% (deep deletion), EGFR 44.35% (amplification), PTEN 32.82%, TP53 30.77%, CDK4 14.26% (amplification). Each figure divides by the patients on whom that gene could be called.

6 of 390 patients are hypermutated (more than 510 non-silent mutations, ten times the cohort median of 51); 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 (TERT, MGMT): 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%.

Alterationgbm_tcga_pan_can_atlas_2018
390 pts · exome or genome
gbm_cptac_2021
99 pts · exome or genome
gbm_columbia_2019
32 pts · exome or genome
EGFR SNV / small indel23.33%91/39017.17%17/993.12%1/32
EGFR amplification44.35%255/57548.96%47/96·
PDGFRA SNV / small indel4.1%16/3903.03%3/990%
PDGFRA amplification13.04%75/57512.5%12/96·
PTEN SNV / small indel32.82%128/39027.27%27/9915.62%5/32
PTEN deep deletion9.57%55/57512.5%12/96·
TP53 SNV / small indel30.77%120/39032.32%32/999.38%3/32
NF1 SNV / small indel11.79%46/39015.15%15/999.38%3/32
NF1 deep deletion1.57%9/5754.17%4/96·
CDK4 SNV / small indel0%0%0%
CDK4 amplification14.26%82/57514.58%14/96·
MDM2 SNV / small indel0.77%3/3902.02%2/990%
MDM2 amplification8.17%47/5757.29%7/96·
CDKN2A SNV / small indel1.03%4/3901.01%1/990%
CDKN2A deep deletion56.0%322/57558.33%56/96·
RB1 SNV / small indel9.74%38/39010.1%10/993.12%1/32
RB1 deep deletion2.61%15/5754.17%4/96·
PIK3CA SNV / small indel9.23%36/39011.11%11/999.38%3/32
PIK3CA amplification2.78%16/5753.12%3/96·
TERT SNV / small indel1.28%5/3901.01%1/990%
TERT amplification0.7%4/5753.12%3/96·
MGMT SNV / small indel0.77%3/3900%0%
MGMT deep deletion0.17%1/5753.12%3/96·
PIK3R1 SNV / small indel10.0%39/3907.07%7/990%
ATRX SNV / small indel9.23%36/39010.1%10/993.12%1/32
PKHD1 SNV / small indel6.67%26/3905.05%5/996.25%2/32
COL6A3 SNV / small indel6.41%25/3901.01%1/990%
IDH1 SNV / small indel6.15%24/3907.07%7/9912.5%4/32
HRNR SNV / small indel5.38%21/3903.03%3/990%
FAT2 SNV / small indel5.38%21/3901.01%1/996.25%2/32
RELN SNV / small indel5.13%20/3901.01%1/993.12%1/32
LAMA1 SNV / small indel5.13%20/3900%3.12%1/32
CFAP47 SNV / small indel5.13%20/3902.02%2/990%
RIMS2 SNV / small indel4.87%19/3901.01%1/990%
KMT2C SNV / small indel4.87%19/3904.04%4/990%
KMT2C amplification2.26%13/5751.04%1/96·
CNTNAP2 SNV / small indel4.87%19/3903.03%3/990%
CNTNAP2 amplification2.43%14/5752.08%2/96·
TCHH SNV / small indel4.62%18/3900%0%
STAG2 SNV / small indel4.62%18/3901.01%1/990%
SDK1 SNV / small indel4.62%18/3901.01%1/993.12%1/32
KEL SNV / small indel4.62%18/3902.02%2/990%
KEL amplification1.39%8/5752.08%2/96·
HSPG2 SNV / small indel4.62%18/3900%0%
MXRA5 SNV / small indel4.36%17/3905.05%5/990%
MXRA5 amplification0.17%1/5752.08%2/96·
LZTR1 SNV / small indel4.36%17/3901.01%1/990%
GALNT17 SNV / small indel4.36%17/3902.02%2/990%
GALNT17 amplification1.57%9/5752.08%2/96·
DOCK5 SNV / small indel4.36%17/3901.01%1/990%
TAF1L SNV / small indel4.1%16/3902.02%2/990%
SCN9A SNV / small indel4.1%16/3902.02%2/990%
MROH2B SNV / small indel4.1%16/3902.02%2/990%
KIF2B SNV / small indel4.1%16/3901.01%1/993.12%1/32
FRAS1 SNV / small indel4.1%16/3905.05%5/993.12%1/32
FBN3 SNV / small indel4.1%16/3904.04%4/990%
DSP SNV / small indel4.1%16/3901.01%1/990%
SLIT3 SNV / small indel3.85%15/3901.01%1/990%
PIK3CG SNV / small indel3.85%15/3901.01%1/990%
GRIN2A SNV / small indel3.85%15/3901.01%1/990%
FCGBP SNV / small indel3.85%15/3900%0%

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

Key findings

CDKN2A is deleted in 322 of 575 patients in TCGA PanCancer Atlas glioblastoma (2018).
Numerator: 322 · Denominator: 575 · Frequency: 56.0% · Observed in 2 cohorts · Confidence: moderate · Source: gbm_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-17

EGFR is amplified in 255 of 575 patients in TCGA PanCancer Atlas glioblastoma (2018).
Numerator: 255 · Denominator: 575 · Frequency: 44.35% · Observed in 3 cohorts · Confidence: moderate · Source: gbm_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-17

PTEN is mutated in 128 of 390 patients in TCGA PanCancer Atlas glioblastoma (2018).
Numerator: 128 · Denominator: 390 · Frequency: 32.82% · Observed in 3 cohorts · Confidence: moderate · Source: gbm_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-17

Gene table — reference cohort

Headline values are from the reference cohort, gbm_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
EGFR curated target amplification 255 / 575 44.35% mutation 23.33% 22.92% 3 / 3 3.12–23.33% A289V (n=16), G598V (n=15), R222C (n=6), A289T (n=6), A289D (n=5)
PDGFRA curated target amplification 75 / 575 13.04% mutation 4.1% 3.65% 2 / 3 0.0–4.1% E229K (n=2), W349C (n=1), P1021L (n=1), E372K (n=1), L655F (n=1)
PTEN curated target SNV / small indel 128 / 390 32.82% 32.55% 3 / 3 15.62–32.82% R233* (n=5), T319* (n=5), G132D (n=4), R335* (n=3), R173H (n=3)
TP53 curated target SNV / small indel 120 / 390 30.77% 30.21% 3 / 3 9.38–32.32% R248Q (n=8), R175H (n=8), R282W (n=5), Y220C (n=5), R248W (n=5)
NF1 curated target SNV / small indel 46 / 390 11.79% 10.94% 3 / 3 9.38–15.15% K1661Gfs*36 (n=3), R192* (n=2), X2657_splice (n=2), X1445_splice (n=1), L844F (n=1)
CDK4 curated target amplification 82 / 575 14.26% mutation 0.0% 0.0% 0 / 3 0.0–0.0% none recurrent
MDM2 curated target amplification 47 / 575 8.17% mutation 0.77% 0.26% 2 / 3 0.0–2.02% D86Y (n=1), S127F (n=1), I303M (n=1)
CDKN2A curated target deep deletion 322 / 575 56.0% mutation 1.03% 0.78% 2 / 3 0.0–1.03% W110* (n=2), L78Hfs*41 (n=1), G111D (n=1)
RB1 curated target SNV / small indel 38 / 390 9.74% 8.85% 3 / 3 3.12–10.1% R445* (n=3), X830_splice (n=2), X654_splice (n=2), S318Nfs*13 (n=2), Q702* (n=1)
PIK3CA curated target SNV / small indel 36 / 390 9.23% 8.85% 3 / 3 9.23–11.11% M1043V (n=3), E545K (n=3), R38H (n=2), E81K (n=2), R88Q (n=2)
TERT curated target SNV / small indel 5 / 390 1.28% 0.78% 2 / 3 0.0–1.28% G641* (n=1), P219L (n=1), N571S (n=1), R889Q (n=1), R951Q (n=1)
MGMT curated target SNV / small indel 3 / 390 0.77% 0.26% 1 / 3 0.0–0.77% A82V (n=1), V186M (n=1), A226V (n=1)
PIK3R1 by frequency SNV / small indel 39 / 390 10.0% 9.64% 2 / 3 0.0–10.0% G376R (n=6), X582_splice (n=2), K379N (n=2), X583_splice (n=2), R574Kfs*27 (n=1)
ATRX by frequency SNV / small indel 36 / 390 9.23% 8.07% 3 / 3 3.12–10.1% Q177* (n=2), R1803H (n=2), W2001Cfs*14 (n=1), E886Lfs*18 (n=1), L1827Cfs*9 (n=1)
PKHD1 by frequency SNV / small indel 26 / 390 6.67% 6.25% 3 / 3 5.05–6.67% L1989F (n=2), R1624W (n=1), F2516S (n=1), G3676E (n=1), T849N (n=1)
COL6A3 by frequency SNV / small indel 25 / 390 6.41% 5.99% 2 / 3 0.0–6.41% S2492L (n=2), L1723F (n=1), V987M (n=1), A1094T (n=1), G542S (n=1)
IDH1 by frequency SNV / small indel 24 / 390 6.15% 6.25% 3 / 3 6.15–12.5% R132H (n=22), R132G (n=2), R132C (n=1)
HRNR by frequency SNV / small indel 21 / 390 5.38% 4.95% 2 / 3 0.0–5.38% S245T (n=2), S2035G (n=1), R571H (n=1), R1053* (n=1), S316L (n=1)
FAT2 by frequency SNV / small indel 21 / 390 5.38% 4.95% 3 / 3 1.01–6.25% T3563M (n=2), R2117Q (n=1), P2269T (n=1), V3619M (n=1), Y2911* (n=1)
RELN by frequency SNV / small indel 20 / 390 5.13% 4.17% 3 / 3 1.01–5.13% D365N (n=1), N1761S (n=1), Q176* (n=1), R3018* (n=1), A2036V (n=1)
LAMA1 by frequency SNV / small indel 20 / 390 5.13% 4.17% 2 / 3 0.0–5.13% X256_splice (n=1), R1180H (n=1), S1051L (n=1), F2643L (n=1), E844K (n=1)
CFAP47 by frequency SNV / small indel 20 / 390 5.13% 4.95% 2 / 3 0.0–5.13% I324N (n=2), R554H (n=2), D304Y (n=1), K257I (n=1), R458I (n=1)
RIMS2 by frequency SNV / small indel 19 / 390 4.87% 4.43% 2 / 3 0.0–4.87% R1003H (n=2), R977Q (n=2), R998* (n=2), S511L (n=1), R683* (n=1)
KMT2C by frequency SNV / small indel 19 / 390 4.87% 4.17% 2 / 3 0.0–4.87% K395E (n=1), D2714H (n=1), G964V (n=1), N2339K (n=1), E4271G (n=1)
CNTNAP2 by frequency SNV / small indel 19 / 390 4.87% 4.43% 2 / 3 0.0–4.87% R283H (n=1), R483Q (n=1), R1032I (n=1), F689L (n=1), F1281L (n=1)
TCHH by frequency SNV / small indel 18 / 390 4.62% 4.17% 1 / 3 0.0–4.62% R233Q (n=1), P978L (n=1), P265L (n=1), R1111W (n=1), R1483H (n=1)
STAG2 by frequency SNV / small indel 18 / 390 4.62% 4.43% 2 / 3 0.0–4.62% M803Vfs*5 (n=1), E675D (n=1), E6* (n=1), L791M (n=1), Y815* (n=1)
SDK1 by frequency SNV / small indel 18 / 390 4.62% 4.17% 3 / 3 1.01–4.62% S1074P (n=1), P972S (n=1), V1229I (n=1), S1208F (n=1), G929E (n=1)
KEL by frequency SNV / small indel 18 / 390 4.62% 4.43% 2 / 3 0.0–4.62% X75_splice (n=2), R130W (n=2), V411M (n=2), V336M (n=1), S187Y (n=1)
HSPG2 by frequency SNV / small indel 18 / 390 4.62% 3.65% 1 / 3 0.0–4.62% R187* (n=1), G759S (n=1), G3637D (n=1), P1449A (n=1), A1410V (n=1)
MXRA5 by frequency SNV / small indel 17 / 390 4.36% 3.65% 2 / 3 0.0–5.05% R2119H (n=1), I1326T (n=1), V2022I (n=1), R1280K (n=1), L602V (n=1)
LZTR1 by frequency SNV / small indel 17 / 390 4.36% 3.65% 2 / 3 0.0–4.36% R810W (n=1), W105R (n=1), G248R (n=1), C560R (n=1), L591R (n=1)
GALNT17 by frequency SNV / small indel 17 / 390 4.36% 3.39% 2 / 3 0.0–4.36% V544I (n=2), E485V (n=1), A46T (n=1), K200R (n=1), K382* (n=1)
DOCK5 by frequency SNV / small indel 17 / 390 4.36% 3.65% 2 / 3 0.0–4.36% R211W (n=2), T282R (n=1), R1019H (n=1), V715I (n=1), G408S (n=1)
TAF1L by frequency SNV / small indel 16 / 390 4.1% 3.39% 2 / 3 0.0–4.1% T1673R (n=1), R1252W (n=1), D1667N (n=1), D6N (n=1), A1430T (n=1)
SCN9A by frequency SNV / small indel 16 / 390 4.1% 3.91% 2 / 3 0.0–4.1% D1828Y (n=1), N1353Y (n=1), R1368H (n=1), R1903P (n=1), T1633M (n=1)
MROH2B by frequency SNV / small indel 16 / 390 4.1% 3.65% 2 / 3 0.0–4.1% R181* (n=2), T456N (n=1), R54* (n=1), R390Q (n=1), P554L (n=1)
KIF2B by frequency SNV / small indel 16 / 390 4.1% 3.65% 3 / 3 1.01–4.1% A112T (n=1), E378Rfs*24 (n=1), E62D (n=1), K143N (n=1), R160W (n=1)
FRAS1 by frequency SNV / small indel 16 / 390 4.1% 3.65% 3 / 3 3.12–5.05% H1855N (n=1), R1891H (n=1), T2578I (n=1), A3021V (n=1), R3768H (n=1)
FBN3 by frequency SNV / small indel 16 / 390 4.1% 3.91% 2 / 3 0.0–4.1% V886I (n=2), A1730T (n=1), R2108C (n=1), P2396Q (n=1), V697M (n=1)
DSP by frequency SNV / small indel 16 / 390 4.1% 3.12% 2 / 3 0.0–4.1% R270Q (n=2), X1793_splice (n=1), T496M (n=1), S610F (n=1), K441T (n=1)
SLIT3 by frequency SNV / small indel 15 / 390 3.85% 2.86% 2 / 3 0.0–3.85% V596M (n=2), R744C (n=1), A1174T (n=1), D1370N (n=1), R469* (n=1)
PIK3CG by frequency SNV / small indel 15 / 390 3.85% 2.86% 2 / 3 0.0–3.85% V165I (n=2), C936S (n=1), A156V (n=1), D571Y (n=1), P424S (n=1)
GRIN2A by frequency SNV / small indel 15 / 390 3.85% 3.39% 2 / 3 0.0–3.85% T1064M (n=1), Q891R (n=1), W7* (n=1), F253L (n=1), C399R (n=1)
FCGBP by frequency SNV / small indel 15 / 390 3.85% 3.39% 1 / 3 0.0–3.85% R4260P (n=1), G1100D (n=1), R434Q (n=1), C2688S (n=1), L1464I (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
TCGA PanCancer Atlas glioblastoma (2018) reference
Glioblastoma Multiforme (TCGA, PanCancer Atlas)
gbm_tcga_pan_can_atlas_2018390 observed397 / 592exome or genomeWES (397)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)651
CPTAC glioblastoma (Cell 2021)
Glioblastoma (CPTAC, Cell 2021)
gbm_cptac_202199 observed99 / 99exome or genomeWES (99)hg19SNV, small indel, amplification, deep deletion142
Columbia glioblastoma (Nat Med 2019)
Glioblastoma (Columbia, Nat Med. 2019)
gbm_columbia_201932 observed32 / 42exome or genomeWES (32)hg19SNV, small indel00.0

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
CDKN2Adeep deletion569658.33%gbm_cptac_2021gbm_cptac_2021_gistic
CDKN2Adeep deletion32257556.0%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
EGFRamplification479648.96%gbm_cptac_2021gbm_cptac_2021_gistic
EGFRamplification25557544.35%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
CDK4amplification149614.58%gbm_cptac_2021gbm_cptac_2021_gistic
CDK4amplification8257514.26%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
PDGFRAamplification7557513.04%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
PDGFRAamplification129612.5%gbm_cptac_2021gbm_cptac_2021_gistic
PTENdeep deletion129612.5%gbm_cptac_2021gbm_cptac_2021_gistic
PTENdeep deletion555759.57%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
MDM2amplification475758.17%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
MDM2amplification7967.29%gbm_cptac_2021gbm_cptac_2021_gistic
NF1deep deletion4964.17%gbm_cptac_2021gbm_cptac_2021_gistic
RB1deep deletion4964.17%gbm_cptac_2021gbm_cptac_2021_gistic
PIK3CAamplification3963.12%gbm_cptac_2021gbm_cptac_2021_gistic
TERTamplification3963.12%gbm_cptac_2021gbm_cptac_2021_gistic
MGMTdeep deletion3963.12%gbm_cptac_2021gbm_cptac_2021_gistic
PIK3CAamplification165752.78%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
RB1deep deletion155752.61%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
CNTNAP2amplification145752.43%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
KMT2Camplification135752.26%gbm_tcga_pan_can_atlas_2018gbm_tcga_pan_can_atlas_2018_gistic
CNTNAP2amplification2962.08%gbm_cptac_2021gbm_cptac_2021_gistic
KELamplification2962.08%gbm_cptac_2021gbm_cptac_2021_gistic
MXRA5amplification2962.08%gbm_cptac_2021gbm_cptac_2021_gistic
GALNT17amplification2962.08%gbm_cptac_2021gbm_cptac_2021_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)
EGFR3.12–23.33%gbm_tcga_pan_can_atlas_2018: 91/390 (23.33%) · gbm_cptac_2021: 17/99 (17.17%) · gbm_columbia_2019: 1/32 (3.12%)
PDGFRA0.0–4.1%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 3/99 (3.03%) · gbm_columbia_2019: 0/32 (0.0%)
PTEN15.62–32.82%gbm_tcga_pan_can_atlas_2018: 128/390 (32.82%) · gbm_cptac_2021: 27/99 (27.27%) · gbm_columbia_2019: 5/32 (15.62%)
TP539.38–32.32%gbm_tcga_pan_can_atlas_2018: 120/390 (30.77%) · gbm_cptac_2021: 32/99 (32.32%) · gbm_columbia_2019: 3/32 (9.38%)
NF19.38–15.15%gbm_tcga_pan_can_atlas_2018: 46/390 (11.79%) · gbm_cptac_2021: 15/99 (15.15%) · gbm_columbia_2019: 3/32 (9.38%)
CDK40.0–0.0%gbm_tcga_pan_can_atlas_2018: 0/390 (0.0%) · gbm_cptac_2021: 0/99 (0.0%) · gbm_columbia_2019: 0/32 (0.0%)
MDM20.0–2.02%gbm_tcga_pan_can_atlas_2018: 3/390 (0.77%) · gbm_cptac_2021: 2/99 (2.02%) · gbm_columbia_2019: 0/32 (0.0%)
CDKN2A0.0–1.03%gbm_tcga_pan_can_atlas_2018: 4/390 (1.03%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
RB13.12–10.1%gbm_tcga_pan_can_atlas_2018: 38/390 (9.74%) · gbm_cptac_2021: 10/99 (10.1%) · gbm_columbia_2019: 1/32 (3.12%)
PIK3CA9.23–11.11%gbm_tcga_pan_can_atlas_2018: 36/390 (9.23%) · gbm_cptac_2021: 11/99 (11.11%) · gbm_columbia_2019: 3/32 (9.38%)
TERT0.0–1.28%gbm_tcga_pan_can_atlas_2018: 5/390 (1.28%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
MGMT0.0–0.77%gbm_tcga_pan_can_atlas_2018: 3/390 (0.77%) · gbm_cptac_2021: 0/99 (0.0%) · gbm_columbia_2019: 0/32 (0.0%)
PIK3R10.0–10.0%gbm_tcga_pan_can_atlas_2018: 39/390 (10.0%) · gbm_cptac_2021: 7/99 (7.07%) · gbm_columbia_2019: 0/32 (0.0%)
ATRX3.12–10.1%gbm_tcga_pan_can_atlas_2018: 36/390 (9.23%) · gbm_cptac_2021: 10/99 (10.1%) · gbm_columbia_2019: 1/32 (3.12%)
PKHD15.05–6.67%gbm_tcga_pan_can_atlas_2018: 26/390 (6.67%) · gbm_cptac_2021: 5/99 (5.05%) · gbm_columbia_2019: 2/32 (6.25%)
COL6A30.0–6.41%gbm_tcga_pan_can_atlas_2018: 25/390 (6.41%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
IDH16.15–12.5%gbm_tcga_pan_can_atlas_2018: 24/390 (6.15%) · gbm_cptac_2021: 7/99 (7.07%) · gbm_columbia_2019: 4/32 (12.5%)
HRNR0.0–5.38%gbm_tcga_pan_can_atlas_2018: 21/390 (5.38%) · gbm_cptac_2021: 3/99 (3.03%) · gbm_columbia_2019: 0/32 (0.0%)
FAT21.01–6.25%gbm_tcga_pan_can_atlas_2018: 21/390 (5.38%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 2/32 (6.25%)
RELN1.01–5.13%gbm_tcga_pan_can_atlas_2018: 20/390 (5.13%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 1/32 (3.12%)
LAMA10.0–5.13%gbm_tcga_pan_can_atlas_2018: 20/390 (5.13%) · gbm_cptac_2021: 0/99 (0.0%) · gbm_columbia_2019: 1/32 (3.12%)
CFAP470.0–5.13%gbm_tcga_pan_can_atlas_2018: 20/390 (5.13%) · gbm_cptac_2021: 2/99 (2.02%) · gbm_columbia_2019: 0/32 (0.0%)
RIMS20.0–4.87%gbm_tcga_pan_can_atlas_2018: 19/390 (4.87%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
KMT2C0.0–4.87%gbm_tcga_pan_can_atlas_2018: 19/390 (4.87%) · gbm_cptac_2021: 4/99 (4.04%) · gbm_columbia_2019: 0/32 (0.0%)
CNTNAP20.0–4.87%gbm_tcga_pan_can_atlas_2018: 19/390 (4.87%) · gbm_cptac_2021: 3/99 (3.03%) · gbm_columbia_2019: 0/32 (0.0%)
TCHH0.0–4.62%gbm_tcga_pan_can_atlas_2018: 18/390 (4.62%) · gbm_cptac_2021: 0/99 (0.0%) · gbm_columbia_2019: 0/32 (0.0%)
STAG20.0–4.62%gbm_tcga_pan_can_atlas_2018: 18/390 (4.62%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
SDK11.01–4.62%gbm_tcga_pan_can_atlas_2018: 18/390 (4.62%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 1/32 (3.12%)
KEL0.0–4.62%gbm_tcga_pan_can_atlas_2018: 18/390 (4.62%) · gbm_cptac_2021: 2/99 (2.02%) · gbm_columbia_2019: 0/32 (0.0%)
HSPG20.0–4.62%gbm_tcga_pan_can_atlas_2018: 18/390 (4.62%) · gbm_cptac_2021: 0/99 (0.0%) · gbm_columbia_2019: 0/32 (0.0%)
MXRA50.0–5.05%gbm_tcga_pan_can_atlas_2018: 17/390 (4.36%) · gbm_cptac_2021: 5/99 (5.05%) · gbm_columbia_2019: 0/32 (0.0%)
LZTR10.0–4.36%gbm_tcga_pan_can_atlas_2018: 17/390 (4.36%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
GALNT170.0–4.36%gbm_tcga_pan_can_atlas_2018: 17/390 (4.36%) · gbm_cptac_2021: 2/99 (2.02%) · gbm_columbia_2019: 0/32 (0.0%)
DOCK50.0–4.36%gbm_tcga_pan_can_atlas_2018: 17/390 (4.36%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
TAF1L0.0–4.1%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 2/99 (2.02%) · gbm_columbia_2019: 0/32 (0.0%)
SCN9A0.0–4.1%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 2/99 (2.02%) · gbm_columbia_2019: 0/32 (0.0%)
MROH2B0.0–4.1%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 2/99 (2.02%) · gbm_columbia_2019: 0/32 (0.0%)
KIF2B1.01–4.1%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 1/32 (3.12%)
FRAS13.12–5.05%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 5/99 (5.05%) · gbm_columbia_2019: 1/32 (3.12%)
FBN30.0–4.1%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 4/99 (4.04%) · gbm_columbia_2019: 0/32 (0.0%)
DSP0.0–4.1%gbm_tcga_pan_can_atlas_2018: 16/390 (4.1%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
SLIT30.0–3.85%gbm_tcga_pan_can_atlas_2018: 15/390 (3.85%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
PIK3CG0.0–3.85%gbm_tcga_pan_can_atlas_2018: 15/390 (3.85%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
GRIN2A0.0–3.85%gbm_tcga_pan_can_atlas_2018: 15/390 (3.85%) · gbm_cptac_2021: 1/99 (1.01%) · gbm_columbia_2019: 0/32 (0.0%)
FCGBP0.0–3.85%gbm_tcga_pan_can_atlas_2018: 15/390 (3.85%) · gbm_cptac_2021: 0/99 (0.0%) · gbm_columbia_2019: 0/32 (0.0%)

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/glioblastoma.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.