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Lower-grade glioma mutation landscape

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

Retrieved 2026-09-28 · Reference cohort: lgg_tcga_pan_can_atlas_2018 · JSON: /disease/lower-grade-glioma/mutations.json · Back to the briefing

Answer block

In Brain Lower Grade Glioma (TCGA, PanCancer Atlas) (514 sequenced patients, exome or genome), the most frequently altered of the 44 genes shown are IDH1 76.85%, TP53 48.25%, ATRX 37.55%, CIC 21.01%, CDKN2A 10.76% (deep deletion). Each figure divides by the patients on whom that gene could be called.

4 of 514 patients are hypermutated (more than 270 non-silent mutations, ten times the cohort median of 27); 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.

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%.

Alterationlgg_tcga_pan_can_atlas_2018
514 pts · exome or genome
glioma_mskcc_2019
924 pts · targeted panel
IDH1 SNV / small indel76.85%395/51434.09%315/924
IDH2 SNV / small indel4.09%21/5142.49%23/924
TP53 SNV / small indel48.25%248/51440.58%375/924
ATRX SNV / small indel37.55%193/51422.08%204/924
ATRX deep deletion2.15%11/5110.65%6/924
CIC SNV / small indel21.01%108/51413.1%121/924
FUBP1 SNV / small indel8.95%46/5145.02%41/816
CDKN2A SNV / small indel0.58%3/5141.95%18/924
CDKN2A deep deletion10.76%55/51130.63%283/924
TERT SNV / small indel0.39%2/51468.38%558/816
TERT promoter·67.16%548/816
PIK3CA SNV / small indel8.17%42/51411.69%108/924
NOTCH1 SNV / small indel7.39%38/5147.25%67/924
MGMT SNV / small indel0%·
PDGFRA SNV / small indel1.56%8/5144.76%44/924
PDGFRA amplification3.72%19/5117.03%65/924
EGFR SNV / small indel6.81%35/51414.94%138/924
EGFR amplification7.63%39/51122.84%211/924
NF1 SNV / small indel6.03%31/51414.5%134/924
SMARCA4 SNV / small indel4.86%25/5145.41%50/924
PTEN SNV / small indel4.47%23/51424.68%228/924
PTEN deep deletion0.98%5/5116.6%61/924
PIK3R1 SNV / small indel4.28%22/5148.66%80/924
ZBTB20 SNV / small indel3.89%20/514·
ARID1A SNV / small indel3.7%19/5144.65%43/924
NIPBL SNV / small indel3.5%18/514·
BCOR SNV / small indel2.92%15/5143.79%35/924
TCF12 SNV / small indel2.72%14/514·
FAT2 SNV / small indel2.53%13/514·
PKHD1 SNV / small indel2.33%12/514·
MYH8 SNV / small indel2.33%12/514·
MYH2 SNV / small indel2.33%12/514·
HSPG2 SNV / small indel2.33%12/514·
FRAS1 SNV / small indel2.33%12/514·
DNMT3A SNV / small indel2.33%12/5142.81%26/924
COL6A3 SNV / small indel2.33%12/514·
COL6A3 deep deletion3.52%18/5110%
NPAP1 SNV / small indel2.14%11/514·
KMT2D SNV / small indel2.14%11/5144.76%44/924
KAT6B SNV / small indel2.14%11/514·
ARID2 SNV / small indel2.14%11/5144.33%40/924
ANKRD30A SNV / small indel2.14%11/514·
ZAN SNV / small indel1.95%10/514·
SPATA31E1 SNV / small indel1.95%10/514·
SETD2 SNV / small indel1.95%10/5145.41%50/924
ROS1 SNV / small indel1.95%10/5142.6%24/924
MYO15A SNV / small indel1.95%10/514·
MYH1 SNV / small indel1.95%10/514·
ITIH6 SNV / small indel1.95%10/514·
ITIH6 amplification2.74%14/5110%
FLNC SNV / small indel1.95%10/514·
EPPK1 SNV / small indel1.95%10/514·
EPPK1 amplification3.52%18/5110%

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

Key findings

IDH1 is mutated in 395 of 514 patients in Brain Lower Grade Glioma (TCGA, PanCancer Atlas).
Numerator: 395 · Denominator: 514 · Frequency: 76.85% · Observed in 2 cohorts · Confidence: moderate · Source: lgg_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-28

TP53 is mutated in 248 of 514 patients in Brain Lower Grade Glioma (TCGA, PanCancer Atlas).
Numerator: 248 · Denominator: 514 · Frequency: 48.25% · Observed in 2 cohorts · Confidence: moderate · Source: lgg_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-28

ATRX is mutated in 193 of 514 patients in Brain Lower Grade Glioma (TCGA, PanCancer Atlas).
Numerator: 193 · Denominator: 514 · Frequency: 37.55% · Observed in 2 cohorts · Confidence: moderate · Source: lgg_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-28

Gene table — reference cohort

TERT: The headline is coding change only: Brain Lower Grade Glioma (TCGA, PanCancer Atlas) reports no promoter calls, and whole-exome sequencing does not cover the TERT promoter. Where it is assayed the figure is 548/816 (67.16%) in Glioma (MSK, Clin Cancer Res 2019). The two are not pooled and the headline is not adjusted.

Headline values are from the reference cohort, lgg_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.

FDA biomarker marks a gene the FDA recognises as a biomarker of response to an approved drug; FDA, tumour-agnostic marks the five that apply whatever the primary site. Hover for the drug, the tumour type and the year. This is level 1 only, United States only, and frozen at November 2022 — a dash means the gene was not FDA-recognised on that date, not that it is undruggable, and not that no trial exists. The frequency beside it is how often the gene is altered in this disease, which is a different question from whether these patients are eligible for the drug. Source: Quantifying the Expanding Landscape of Clinical Actionability for Patients with Cancer. Cancer Discovery 2024;14(1):49-65. doi:10.1158/2159-8290.CD-23-0467, Table 1

GeneFDA statusWhy listedLargest alterationAltered / testedFrequencyWithout hypermutatedCohorts observedRange across cohortsRecurrent changes
IDH1 FDA biomarker2018 · 1 drug curated target SNV / small indel 395 / 514 76.85% 77.06% 2 / 2 34.09–76.85% R132H (n=358), R132C (n=17), R132G (n=11), R132S (n=9)
IDH2 FDA biomarker2017 · 1 drug curated target SNV / small indel 21 / 514 4.09% 4.12% 2 / 2 2.49–4.09% R172K (n=12), R172M (n=3), R172G (n=2), R172W (n=2), R172S (n=1)
TP53 — curated target SNV / small indel 248 / 514 48.25% 48.04% 2 / 2 40.58–48.25% R273C (n=54), R273H (n=11), Y220C (n=10), R175H (n=8), R248Q (n=8)
ATRX — curated target SNV / small indel 193 / 514 37.55% 37.45% 2 / 2 22.08–37.55% R1426* (n=6), F2113Sfs*9 (n=5), L359Tfs*3 (n=3), S2094* (n=2), E886Lfs*18 (n=2)
CIC — curated target SNV / small indel 108 / 514 21.01% 20.78% 2 / 2 13.1–21.01% R215W (n=10), R202W (n=5), R201W (n=5), R1515C (n=4), R215Q (n=4)
FUBP1 — curated target SNV / small indel 46 / 514 8.95% 9.02% 2 / 2 5.02–8.95% X83_splice (n=3), I443Rfs*47 (n=3), X314_splice (n=2), G182* (n=1), W537* (n=1)
CDKN2A — curated target deep deletion 55 / 511 10.76% mutation 0.58% 0.39% 2 / 2 0.58–1.95% P48R (n=1), R107H (n=1), W110* (n=1)
TERT — curated target amplification 3 / 511 0.59% mutation 0.39%coding only 0.39% 2 / 2 0.39–68.38% V251I (n=1), R858W (n=1)
PIK3CA FDA biomarker2019 · 1 drug curated target SNV / small indel 42 / 514 8.17% 7.84% 2 / 2 8.17–11.69% G118D (n=4), E110del (n=4), H1047R (n=4), E453K (n=3), E453del (n=3)
NOTCH1 — curated target SNV / small indel 38 / 514 7.39% 7.06% 2 / 2 7.25–7.39% F357del (n=7), D338del (n=2), R448L (n=2), N454del (n=2), X481_splice (n=1)
MGMT — curated target deep deletion 10 / 511 1.96% mutation 0.0% 0.0% 0 / 2 0.0–0.0% none recurrent
PDGFRA FDA biomarker2006 · 2 drugs curated target amplification 19 / 511 3.72% mutation 1.56% 1.18% 2 / 2 1.56–4.76% S1057F (n=1), P519T (n=1), E387K (n=1), G390S (n=1), L580P (n=1)
EGFR FDA biomarker2004 · 7 drugs by frequency amplification 39 / 511 7.63% mutation 6.81% 6.67% 2 / 2 6.81–14.94% G598V (n=6), A289V (n=6), R252C (n=3), L62R (n=3), R252P (n=2)
NF1 FDA biomarker2020 · 1 drug by frequency SNV / small indel 31 / 514 6.03% 5.69% 2 / 2 6.03–14.5% F1247Ifs*18 (n=4), R2450* (n=2), W1314* (n=1), Y2285Tfs*5 (n=1), L650* (n=1)
SMARCA4 — by frequency SNV / small indel 25 / 514 4.86% 4.51% 2 / 2 4.86–5.41% K546del (n=4), H884R (n=1), R1192C (n=1), D1177G (n=1), L682M (n=1)
PTEN — by frequency SNV / small indel 23 / 514 4.47% 4.31% 2 / 2 4.47–24.68% T319Nfs*6 (n=2), A121T (n=2), R173C (n=1), S170G (n=1), Y346H (n=1)
PIK3R1 — by frequency SNV / small indel 22 / 514 4.28% 4.31% 2 / 2 4.28–8.66% N564D (n=3), G376R (n=2), D464_Y467del (n=2), A185T (n=1), A98Gfs*8 (n=1)
ZBTB20 — by frequency SNV / small indel 20 / 514 3.89% 3.53% 1 / 2 3.89–3.89% N650S (n=2), M625I (n=1), R654C (n=1), S245L (n=1), Y244C (n=1)
ARID1A — by frequency SNV / small indel 19 / 514 3.7% 3.53% 2 / 2 3.7–4.65% R1335* (n=1), P459L (n=1), H203Rfs*196 (n=1), A1757S (n=1), R1980C (n=1)
NIPBL — by frequency SNV / small indel 18 / 514 3.5% 3.33% 1 / 2 3.5–3.5% A1792D (n=1), S1443* (n=1), P2056A (n=1), F2180V (n=1), K353N (n=1)
BCOR — by frequency SNV / small indel 15 / 514 2.92% 2.75% 2 / 2 2.92–3.79% R1131Q (n=1), E1382Ifs*26 (n=1), Q1058Rfs*55 (n=1), N1584S (n=1), E1386D (n=1)
TCF12 — by frequency SNV / small indel 14 / 514 2.72% 2.75% 1 / 2 2.72–2.72% E524Rfs*14 (n=2), X229_splice (n=1), P292Nfs*44 (n=1), D229Afs*9 (n=1), X372_splice (n=1)
FAT2 — by frequency SNV / small indel 13 / 514 2.53% 2.35% 1 / 2 2.53–2.53% P733S (n=1), Q678H (n=1), V2620A (n=1), I1543M (n=1), A3754T (n=1)
PKHD1 — by frequency SNV / small indel 12 / 514 2.33% 2.35% 1 / 2 2.33–2.33% V3043L (n=1), V1181F (n=1), W2290S (n=1), N1602H (n=1), P3762Q (n=1)
MYH8 — by frequency SNV / small indel 12 / 514 2.33% 1.96% 1 / 2 2.33–2.33% A770P (n=1), A199V (n=1), R1139H (n=1), A586S (n=1), R1423Q (n=1)
MYH2 — by frequency SNV / small indel 12 / 514 2.33% 2.16% 1 / 2 2.33–2.33% R1181C (n=2), R1199S (n=1), R793Q (n=1), R1426W (n=1), E1139K (n=1)
HSPG2 — by frequency SNV / small indel 12 / 514 2.33% 1.76% 1 / 2 2.33–2.33% V3202M (n=1), R1200W (n=1), R2992H (n=1), G2065W (n=1), P1596H (n=1)
FRAS1 — by frequency SNV / small indel 12 / 514 2.33% 2.35% 1 / 2 2.33–2.33% F2731C (n=1), A3904V (n=1), N3064S (n=1), V3453I (n=1), C379* (n=1)
DNMT3A — by frequency SNV / small indel 12 / 514 2.33% 1.76% 2 / 2 2.33–2.81% R183W (n=1), E667* (n=1), C540Y (n=1), F732L (n=1), A259G (n=1)
COL6A3 — by frequency deep deletion 18 / 511 3.52% mutation 2.33% 1.96% 1 / 2 2.33–2.33% R1331H (n=2), A2611V (n=1), R1798H (n=1), R494K (n=1), A2536V (n=1)
NPAP1 — by frequency SNV / small indel 11 / 514 2.14% 1.76% 1 / 2 2.14–2.14% G183R (n=1), E155D (n=1), S331L (n=1), T512A (n=1), P237S (n=1)
KMT2D — by frequency SNV / small indel 11 / 514 2.14% 1.57% 2 / 2 2.14–4.76% A16T (n=1), R1312C (n=1), E559D (n=1), G1059E (n=1), M581V (n=1)
KAT6B — by frequency SNV / small indel 11 / 514 2.14% 1.96% 1 / 2 2.14–2.14% T1203Rfs*21 (n=4), T1279Hfs*9 (n=1), P1607H (n=1), A2034T (n=1), I763M (n=1)
ARID2 — by frequency SNV / small indel 11 / 514 2.14% 1.96% 2 / 2 2.14–4.33% T56Rfs*8 (n=2), S1426* (n=1), K1350* (n=1), H1017Y (n=1), L449M (n=1)
ANKRD30A — by frequency SNV / small indel 11 / 514 2.14% 2.16% 1 / 2 2.14–2.14% T306M (n=1), T1295K (n=1), E1140* (n=1), A328T (n=1), E1099D (n=1)
ZAN — by frequency SNV / small indel 10 / 514 1.95% 1.37% 1 / 2 1.95–1.95% D1554N (n=1), K1977N (n=1), P1814L (n=1), P563H (n=1), G79E (n=1)
SPATA31E1 — by frequency SNV / small indel 10 / 514 1.95% 1.76% 1 / 2 1.95–1.95% R1133H (n=1), P656L (n=1), G957E (n=1), Q1440H (n=1), D442G (n=1)
SETD2 — by frequency SNV / small indel 10 / 514 1.95% 1.76% 2 / 2 1.95–5.41% L2081Kfs*4 (n=1), Q2347Hfs*23 (n=1), H1603R (n=1), S917Kfs*18 (n=1), S784Y (n=1)
ROS1 FDA biomarker2016 · 2 drugs by frequency SNV / small indel 10 / 514 1.95% 1.76% 2 / 2 1.95–2.6% G1137E (n=1), T16Lfs*15 (n=1), X866_splice (n=1), I1900V (n=1), R1035* (n=1)
MYO15A — by frequency SNV / small indel 10 / 514 1.95% 1.57% 1 / 2 1.95–1.95% G2423S (n=2), A2874T (n=1), E494D (n=1), D247N (n=1), S449Y (n=1)
MYH1 — by frequency SNV / small indel 10 / 514 1.95% 1.76% 1 / 2 1.95–1.95% E99K (n=1), I1580S (n=1), R191H (n=1), F1089L (n=1), A1255T (n=1)
ITIH6 — by frequency amplification 14 / 511 2.74% mutation 1.95% 1.76% 1 / 2 1.95–1.95% S1165P (n=1), D289G (n=1), T1156A (n=1), V1270M (n=1), G403S (n=1)
FLNC — by frequency SNV / small indel 10 / 514 1.95% 1.37% 1 / 2 1.95–1.95% V2658M (n=1), A29V (n=1), A1551T (n=1), G2420V (n=1), Q2212K (n=1)
EPPK1 — by frequency amplification 18 / 511 3.52% mutation 1.95% 1.76% 1 / 2 1.95–1.95% R686C (n=1), R2032K (n=1), S1332A (n=1), E1962K (n=1), P36T (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
Brain Lower Grade Glioma (TCGA, PanCancer Atlas) reference
Brain Lower Grade Glioma (TCGA, PanCancer Atlas)
lgg_tcga_pan_can_atlas_2018514 observed514 / 514exome or genomeWES (514)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)427.0
Glioma (MSK, Clin Cancer Res 2019)
Glioma (MSK, Clin Cancer Res 2019)
glioma_mskcc_2019924 observed1004 / 1004targeted panelIMPACT410 (505), IMPACT468 (207), IMPACT341 (125), glioma_mskcc_2019_fmi_t5 (122), glioma_mskcc_2019_fmi_t7 (45)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)134.0

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 deletion28392430.63%glioma_mskcc_2019glioma_mskcc_2019_gistic
EGFRamplification21192422.84%glioma_mskcc_2019glioma_mskcc_2019_gistic
CDKN2Adeep deletion5551110.76%lgg_tcga_pan_can_atlas_2018lgg_tcga_pan_can_atlas_2018_gistic
EGFRamplification395117.63%lgg_tcga_pan_can_atlas_2018lgg_tcga_pan_can_atlas_2018_gistic
PDGFRAamplification659247.03%glioma_mskcc_2019glioma_mskcc_2019_gistic
PTENdeep deletion619246.6%glioma_mskcc_2019glioma_mskcc_2019_gistic
PDGFRAamplification195113.72%lgg_tcga_pan_can_atlas_2018lgg_tcga_pan_can_atlas_2018_gistic
COL6A3deep deletion185113.52%lgg_tcga_pan_can_atlas_2018lgg_tcga_pan_can_atlas_2018_gistic
EPPK1amplification185113.52%lgg_tcga_pan_can_atlas_2018lgg_tcga_pan_can_atlas_2018_gistic
ITIH6amplification145112.74%lgg_tcga_pan_can_atlas_2018lgg_tcga_pan_can_atlas_2018_gistic
ATRXdeep deletion115112.15%lgg_tcga_pan_can_atlas_2018lgg_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)
IDH134.09–76.85%lgg_tcga_pan_can_atlas_2018: 395/514 (76.85%) · glioma_mskcc_2019: 315/924 (34.09%)
IDH22.49–4.09%lgg_tcga_pan_can_atlas_2018: 21/514 (4.09%) · glioma_mskcc_2019: 23/924 (2.49%)
TP5340.58–48.25%lgg_tcga_pan_can_atlas_2018: 248/514 (48.25%) · glioma_mskcc_2019: 375/924 (40.58%)
ATRX22.08–37.55%lgg_tcga_pan_can_atlas_2018: 193/514 (37.55%) · glioma_mskcc_2019: 204/924 (22.08%)
CIC13.1–21.01%lgg_tcga_pan_can_atlas_2018: 108/514 (21.01%) · glioma_mskcc_2019: 121/924 (13.1%)
FUBP15.02–8.95%lgg_tcga_pan_can_atlas_2018: 46/514 (8.95%) · glioma_mskcc_2019: 41/816 (5.02%)
CDKN2A0.58–1.95%lgg_tcga_pan_can_atlas_2018: 3/514 (0.58%) · glioma_mskcc_2019: 18/924 (1.95%)
TERT0.39–68.38%lgg_tcga_pan_can_atlas_2018: 2/514 (0.39%) · glioma_mskcc_2019: 558/816 (68.38%)
PIK3CA8.17–11.69%lgg_tcga_pan_can_atlas_2018: 42/514 (8.17%) · glioma_mskcc_2019: 108/924 (11.69%)
NOTCH17.25–7.39%lgg_tcga_pan_can_atlas_2018: 38/514 (7.39%) · glioma_mskcc_2019: 67/924 (7.25%)
MGMT0.0–0.0%lgg_tcga_pan_can_atlas_2018: 0/514 (0.0%) · glioma_mskcc_2019: not assayed
PDGFRA1.56–4.76%lgg_tcga_pan_can_atlas_2018: 8/514 (1.56%) · glioma_mskcc_2019: 44/924 (4.76%)
EGFR6.81–14.94%lgg_tcga_pan_can_atlas_2018: 35/514 (6.81%) · glioma_mskcc_2019: 138/924 (14.94%)
NF16.03–14.5%lgg_tcga_pan_can_atlas_2018: 31/514 (6.03%) · glioma_mskcc_2019: 134/924 (14.5%)
SMARCA44.86–5.41%lgg_tcga_pan_can_atlas_2018: 25/514 (4.86%) · glioma_mskcc_2019: 50/924 (5.41%)
PTEN4.47–24.68%lgg_tcga_pan_can_atlas_2018: 23/514 (4.47%) · glioma_mskcc_2019: 228/924 (24.68%)
PIK3R14.28–8.66%lgg_tcga_pan_can_atlas_2018: 22/514 (4.28%) · glioma_mskcc_2019: 80/924 (8.66%)
ZBTB203.89–3.89%lgg_tcga_pan_can_atlas_2018: 20/514 (3.89%) · glioma_mskcc_2019: not assayed
ARID1A3.7–4.65%lgg_tcga_pan_can_atlas_2018: 19/514 (3.7%) · glioma_mskcc_2019: 43/924 (4.65%)
NIPBL3.5–3.5%lgg_tcga_pan_can_atlas_2018: 18/514 (3.5%) · glioma_mskcc_2019: not assayed
BCOR2.92–3.79%lgg_tcga_pan_can_atlas_2018: 15/514 (2.92%) · glioma_mskcc_2019: 35/924 (3.79%)
TCF122.72–2.72%lgg_tcga_pan_can_atlas_2018: 14/514 (2.72%) · glioma_mskcc_2019: not assayed
FAT22.53–2.53%lgg_tcga_pan_can_atlas_2018: 13/514 (2.53%) · glioma_mskcc_2019: not assayed
PKHD12.33–2.33%lgg_tcga_pan_can_atlas_2018: 12/514 (2.33%) · glioma_mskcc_2019: not assayed
MYH82.33–2.33%lgg_tcga_pan_can_atlas_2018: 12/514 (2.33%) · glioma_mskcc_2019: not assayed
MYH22.33–2.33%lgg_tcga_pan_can_atlas_2018: 12/514 (2.33%) · glioma_mskcc_2019: not assayed
HSPG22.33–2.33%lgg_tcga_pan_can_atlas_2018: 12/514 (2.33%) · glioma_mskcc_2019: not assayed
FRAS12.33–2.33%lgg_tcga_pan_can_atlas_2018: 12/514 (2.33%) · glioma_mskcc_2019: not assayed
DNMT3A2.33–2.81%lgg_tcga_pan_can_atlas_2018: 12/514 (2.33%) · glioma_mskcc_2019: 26/924 (2.81%)
COL6A32.33–2.33%lgg_tcga_pan_can_atlas_2018: 12/514 (2.33%) · glioma_mskcc_2019: not assayed
NPAP12.14–2.14%lgg_tcga_pan_can_atlas_2018: 11/514 (2.14%) · glioma_mskcc_2019: not assayed
KMT2D2.14–4.76%lgg_tcga_pan_can_atlas_2018: 11/514 (2.14%) · glioma_mskcc_2019: 44/924 (4.76%)
KAT6B2.14–2.14%lgg_tcga_pan_can_atlas_2018: 11/514 (2.14%) · glioma_mskcc_2019: not assayed
ARID22.14–4.33%lgg_tcga_pan_can_atlas_2018: 11/514 (2.14%) · glioma_mskcc_2019: 40/924 (4.33%)
ANKRD30A2.14–2.14%lgg_tcga_pan_can_atlas_2018: 11/514 (2.14%) · glioma_mskcc_2019: not assayed
ZAN1.95–1.95%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: not assayed
SPATA31E11.95–1.95%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: not assayed
SETD21.95–5.41%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: 50/924 (5.41%)
ROS11.95–2.6%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: 24/924 (2.6%)
MYO15A1.95–1.95%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: not assayed
MYH11.95–1.95%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: not assayed
ITIH61.95–1.95%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: not assayed
FLNC1.95–1.95%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: not assayed
EPPK11.95–1.95%lgg_tcga_pan_can_atlas_2018: 10/514 (1.95%) · glioma_mskcc_2019: 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/lower-grade-glioma.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.