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Thyroid cancer mutation landscape

How often each gene is altered in thyroid 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: thca_tcga_pan_can_atlas_2018 · JSON: /disease/thyroid-cancer/mutations.json · Back to the briefing

Answer block

In Thyroid Carcinoma (TCGA, PanCancer Atlas) (489 sequenced patients, exome or genome), the most frequently altered of the 49 genes shown are BRAF 58.49%, NRAS 7.98%, TG 3.89%, HRAS 3.27%, ZFHX3 1.84%. Each figure divides by the patients on whom that gene could be called.

6 of 489 patients are hypermutated (more than 100 non-silent mutations, ten times the cohort median of 10); every gene's frequency without them is beside the headline.

Of the briefing's 12 curated targets, 9 are altered in under 2% of this cohort (RET, TERT, TP53, NTRK1, ALK, PIK3CA, TSHR, SLC5A5, PAX8): 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%.

Alterationthca_tcga_pan_can_atlas_2018
489 pts · exome or genome
thyroid_mskcc_2016
117 pts · mixed
BRAF SNV / small indel58.49%286/48936.75%43/117
RET SNV / small indel0.2%1/4890%
NRAS SNV / small indel7.98%39/48921.37%25/117
HRAS SNV / small indel3.27%16/4895.13%6/117
TERT SNV / small indel0.61%3/4890.85%1/117
TP53 SNV / small indel0.41%2/48925.64%30/117
TP53 deep deletion0.4%2/4973.42%4/117
NTRK1 SNV / small indel0%0.85%1/117
ALK SNV / small indel0.2%1/4890.85%1/117
PIK3CA SNV / small indel0.82%4/4896.84%8/117
TSHR SNV / small indel0.2%1/4894.27%5/117
SLC5A5 SNV / small indel0.2%1/4890%
PAX8 SNV / small indel0.2%1/4890%
TG SNV / small indel3.89%19/4890%
ZFHX3 SNV / small indel1.84%9/4890%
KMT2A SNV / small indel1.43%7/4895.13%6/117
EIF1AX SNV / small indel1.43%7/48910.26%12/117
COL5A3 SNV / small indel1.43%7/4890%
PIK3R5 SNV / small indel1.23%6/4890%
KMT2C SNV / small indel1.23%6/4892.56%3/117
ITPR2 SNV / small indel1.23%6/4890%
ATM SNV / small indel1.23%6/4898.55%10/117
USP9X SNV / small indel1.02%5/4890%
TENM2 SNV / small indel1.02%5/4890%
TACC2 SNV / small indel1.02%5/4890%
SHROOM2 SNV / small indel1.02%5/4890%
PTPRZ1 SNV / small indel1.02%5/4890%
PKHD1 SNV / small indel1.02%5/4890%
PDZD2 SNV / small indel1.02%5/4890%
NAV3 SNV / small indel1.02%5/4890%
LTBP2 SNV / small indel1.02%5/4890%
LAMA4 SNV / small indel1.02%5/4890%
HSPG2 SNV / small indel1.02%5/4890%
GBF1 SNV / small indel1.02%5/4890%
FBN1 SNV / small indel1.02%5/4890%
DNMT3A SNV / small indel1.02%5/4891.71%2/117
COL7A1 SNV / small indel1.02%5/4890%
BPTF SNV / small indel1.02%5/4890%
BDP1 SNV / small indel1.02%5/4890%
ALPK3 SNV / small indel1.02%5/4890%
AKT1 SNV / small indel1.02%5/4890%
ZC3H13 SNV / small indel0.82%4/4890%
WNK2 SNV / small indel0.82%4/4890%
WDR33 SNV / small indel0.82%4/4890%
VPS13D SNV / small indel0.82%4/4890%
UGGT2 SNV / small indel0.82%4/4890%
UBQLN2 SNV / small indel0.82%4/4890%
THBS2 SNV / small indel0.82%4/4890%
TENM4 SNV / small indel0.82%4/4890%
STOX2 SNV / small indel0.82%4/4890%

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 286 of 489 patients in Thyroid Carcinoma (TCGA, PanCancer Atlas).
Numerator: 286 · Denominator: 489 · Frequency: 58.49% · Observed in 2 cohorts · Confidence: moderate · Source: thca_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

NRAS is mutated in 39 of 489 patients in Thyroid Carcinoma (TCGA, PanCancer Atlas).
Numerator: 39 · Denominator: 489 · Frequency: 7.98% · Observed in 2 cohorts · Confidence: moderate · Source: thca_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

TG is mutated in 19 of 489 patients in Thyroid Carcinoma (TCGA, PanCancer Atlas).
Numerator: 19 · Denominator: 489 · Frequency: 3.89% · Observed in 1 cohorts · Confidence: moderate · Source: thca_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

Gene table — reference cohort

Headline values are from the reference cohort, thca_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 286 / 489 58.49% 58.8% 2 / 2 36.75–58.49% V600E (n=284), K601E (n=2), P490_Q494del (n=1)
RET curated target deep deletion 2 / 497 0.4% mutation 0.2% 0.21% 1 / 2 0.0–0.2% V945M (n=1)
NRAS curated target SNV / small indel 39 / 489 7.98% 7.66% 2 / 2 7.98–21.37% Q61R (n=31), Q61K (n=8)
HRAS curated target SNV / small indel 16 / 489 3.27% 3.11% 2 / 2 3.27–5.13% Q61R (n=13), Q61K (n=3)
TERT curated target SNV / small indel 3 / 489 0.61% 0.62% 2 / 2 0.61–0.85% R470H (n=1), T1113Lfs*62 (n=1), S602L (n=1)
TP53 curated target SNV / small indel 2 / 489 0.41% 0.41% 2 / 2 0.41–25.64% Q375* (n=1), Q192* (n=1)
NTRK1 curated target deep deletion 1 / 497 0.2% mutation 0.0% 0.0% 1 / 2 0.0–0.85% none recurrent
ALK curated target SNV / small indel 1 / 489 0.2% 0.21% 2 / 2 0.2–0.85% P693S (n=1)
PIK3CA curated target SNV / small indel 4 / 489 0.82% 0.83% 2 / 2 0.82–6.84% M1043I (n=1), E110del (n=1), E674* (n=1), G118D (n=1)
TSHR curated target SNV / small indel 1 / 489 0.2% 0.21% 2 / 2 0.2–4.27% M453T (n=1)
SLC5A5 curated target SNV / small indel 1 / 489 0.2% 0.21% 1 / 2 0.0–0.2% A581G (n=1)
PAX8 curated target SNV / small indel 1 / 489 0.2% 0.21% 1 / 2 0.0–0.2% P235Q (n=1)
TG by frequency SNV / small indel 19 / 489 3.89% 3.93% 1 / 2 0.0–3.89% S1619Hfs*12 (n=1), L2282Ifs*61 (n=1), Q1246P (n=1), C1306S (n=1), Q1515del (n=1)
ZFHX3 by frequency SNV / small indel 9 / 489 1.84% 1.86% 1 / 2 0.0–1.84% K1572Rfs*19 (n=2), G1022D (n=1), H1571R (n=1), R2161W (n=1), R2988Efs*33 (n=1)
KMT2A by frequency SNV / small indel 7 / 489 1.43% 1.24% 2 / 2 1.43–5.13% D2721V (n=1), S3518F (n=1), S3518A (n=1), Q3624H (n=1), N1656T (n=1)
EIF1AX by frequency SNV / small indel 7 / 489 1.43% 1.45% 2 / 2 1.43–10.26% G9D (n=2), X113_splice (n=2), A113V (n=1), G9R (n=1), G8R (n=1)
COL5A3 by frequency SNV / small indel 7 / 489 1.43% 1.04% 1 / 2 0.0–1.43% R219W (n=1), P606H (n=1), Q236E (n=1), G1388C (n=1), R1644H (n=1)
PIK3R5 by frequency SNV / small indel 6 / 489 1.23% 1.04% 1 / 2 0.0–1.23% K104E (n=1), Q555H (n=1), A666V (n=1), D76N (n=1), Y291* (n=1)
KMT2C by frequency SNV / small indel 6 / 489 1.23% 1.24% 2 / 2 1.23–2.56% Q3591* (n=1), S3213L (n=1), S888F (n=1), C394S (n=1), K3847N (n=1)
ITPR2 by frequency SNV / small indel 6 / 489 1.23% 1.24% 1 / 2 0.0–1.23% E975V (n=1), M1576I (n=1), V483I (n=1), R780H (n=1), A2351V (n=1)
ATM by frequency SNV / small indel 6 / 489 1.23% 1.24% 2 / 2 1.23–8.55% D2997G (n=1), E16Nfs*18 (n=1), T1908Kfs*9 (n=1), W2845C (n=1), L2132V (n=1)
USP9X by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% K1798T (n=1), P1105Tfs*4 (n=1), X1535_splice (n=1), E61* (n=1), P1083A (n=1)
TENM2 by frequency SNV / small indel 5 / 489 1.02% 0.62% 1 / 2 0.0–1.02% P997Q (n=1), D904Y (n=1), P1801H (n=1), I1803T (n=1), A1538V (n=1)
TACC2 by frequency SNV / small indel 5 / 489 1.02% 0.83% 1 / 2 0.0–1.02% G438_S439dup (n=1), A1255S (n=1), M200V (n=1), R606H (n=1), R2728S (n=1)
SHROOM2 by frequency SNV / small indel 5 / 489 1.02% 0.83% 1 / 2 0.0–1.02% R1452L (n=1), P822Q (n=1), L1585P (n=1), N297S (n=1), P1352T (n=1)
PTPRZ1 by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% T846I (n=1), L1673V (n=1), P818H (n=1), F363V (n=1), E2210Q (n=1)
PKHD1 by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% T2850K (n=1), R2891C (n=1), W664L (n=1), L1190F (n=1), S1066L (n=1)
PDZD2 by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% A1296E (n=1), P680R (n=1), G269S (n=1), T1142* (n=1), G313C (n=1)
NAV3 by frequency SNV / small indel 5 / 489 1.02% 0.83% 1 / 2 0.0–1.02% Q563P (n=1), T1340I (n=1), P2035S (n=1), P208H (n=1), S791Y (n=1)
LTBP2 by frequency SNV / small indel 5 / 489 1.02% 0.62% 1 / 2 0.0–1.02% L1202P (n=1), P843T (n=1), P1471H (n=1), P537T (n=1), A1407V (n=1)
LAMA4 by frequency SNV / small indel 5 / 489 1.02% 0.83% 1 / 2 0.0–1.02% P1785H (n=1), A594E (n=1), N810K (n=1), R392M (n=1), D783V (n=1)
HSPG2 by frequency SNV / small indel 5 / 489 1.02% 0.62% 1 / 2 0.0–1.02% E4141* (n=1), I1056T (n=1), R1523S (n=1), G4345W (n=1), S4171Y (n=1)
GBF1 by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% N1308I (n=1), C360Y (n=1), X1626_splice (n=1), D762* (n=1), X1548_splice (n=1)
FBN1 by frequency SNV / small indel 5 / 489 1.02% 0.83% 1 / 2 0.0–1.02% E571K (n=1), G486V (n=1), G276E (n=1), E806K (n=1), G90W (n=1)
DNMT3A by frequency SNV / small indel 5 / 489 1.02% 0.83% 2 / 2 1.02–1.71% W313* (n=1), K589N (n=1), P195L (n=1), K766Efs*15 (n=1), E240Sfs*8 (n=1)
COL7A1 by frequency SNV / small indel 5 / 489 1.02% 0.62% 1 / 2 0.0–1.02% A2830T (n=1), G316W (n=1), R1724S (n=1), X2180_splice (n=1), Q1924H (n=1)
BPTF by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% M1399V (n=1), D586H (n=1), P1476S (n=1), E2424* (n=1), T778N (n=1)
BDP1 by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% M905T (n=1), P1932A (n=1), P2231S (n=1), Q779* (n=1), Q2571* (n=1)
ALPK3 by frequency SNV / small indel 5 / 489 1.02% 0.62% 1 / 2 0.0–1.02% Q1904K (n=1), Q424* (n=1), A1252T (n=1), H748N (n=1), G1094W (n=1)
AKT1 by frequency SNV / small indel 5 / 489 1.02% 1.04% 1 / 2 0.0–1.02% E17K (n=3), E133D (n=1), L52R (n=1)
ZC3H13 by frequency SNV / small indel 4 / 489 0.82% 0.62% 1 / 2 0.0–0.82% R384G (n=1), P1035H (n=1), E28V (n=1), R646* (n=1)
WNK2 by frequency SNV / small indel 4 / 489 0.82% 0.83% 1 / 2 0.0–0.82% S2123N (n=1), P1555A (n=1), H422Y (n=1), P793L (n=1)
WDR33 by frequency SNV / small indel 4 / 489 0.82% 0.62% 1 / 2 0.0–0.82% P587R (n=1), S1210C (n=1), D1137N (n=1), G980W (n=1)
VPS13D by frequency SNV / small indel 4 / 489 0.82% 0.83% 1 / 2 0.0–0.82% L1671V (n=1), N3247K (n=1), A2597G (n=1), X2733_splice (n=1)
UGGT2 by frequency SNV / small indel 4 / 489 0.82% 0.62% 1 / 2 0.0–0.82% L14Q (n=1), N787T (n=1), W1488C (n=1), E786D (n=1)
UBQLN2 by frequency SNV / small indel 4 / 489 0.82% 0.41% 1 / 2 0.0–0.82% R309S (n=2), P573S (n=1), P414Q (n=1)
THBS2 by frequency SNV / small indel 4 / 489 0.82% 0.41% 1 / 2 0.0–0.82% R460C (n=1), G94C (n=1), G773V (n=1), G247S (n=1)
TENM4 by frequency SNV / small indel 4 / 489 0.82% 0.62% 1 / 2 0.0–0.82% E1004* (n=1), E1162K (n=1), P1510H (n=1), A2587S (n=1)
STOX2 by frequency SNV / small indel 4 / 489 0.82% 0.62% 1 / 2 0.0–0.82% Q70* (n=1), G267W (n=1), S240R (n=1), P638T (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
Thyroid Carcinoma (TCGA, PanCancer Atlas) reference
Thyroid Carcinoma (TCGA, PanCancer Atlas)
thca_tcga_pan_can_atlas_2018489 observed490 / 500exome or genomeWES (490)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)610.0
Poorly-Differentiated and Anaplastic Thyroid Cancers (MSK, JCI 2016)
Poorly-Differentiated and Anaplastic Thyroid Cancers (MSK, JCI 2016)
thyroid_mskcc_2016117 observed117 / 117mixedWES (82), IMPACT341 (35)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)02

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
TP53deep deletion41173.42%thyroid_mskcc_2016thyroid_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)
BRAF36.75–58.49%thca_tcga_pan_can_atlas_2018: 286/489 (58.49%) · thyroid_mskcc_2016: 43/117 (36.75%)
RET0.0–0.2%thca_tcga_pan_can_atlas_2018: 1/489 (0.2%) · thyroid_mskcc_2016: 0/117 (0.0%)
NRAS7.98–21.37%thca_tcga_pan_can_atlas_2018: 39/489 (7.98%) · thyroid_mskcc_2016: 25/117 (21.37%)
HRAS3.27–5.13%thca_tcga_pan_can_atlas_2018: 16/489 (3.27%) · thyroid_mskcc_2016: 6/117 (5.13%)
TERT0.61–0.85%thca_tcga_pan_can_atlas_2018: 3/489 (0.61%) · thyroid_mskcc_2016: 1/117 (0.85%)
TP530.41–25.64%thca_tcga_pan_can_atlas_2018: 2/489 (0.41%) · thyroid_mskcc_2016: 30/117 (25.64%)
NTRK10.0–0.85%thca_tcga_pan_can_atlas_2018: 0/489 (0.0%) · thyroid_mskcc_2016: 1/117 (0.85%)
ALK0.2–0.85%thca_tcga_pan_can_atlas_2018: 1/489 (0.2%) · thyroid_mskcc_2016: 1/117 (0.85%)
PIK3CA0.82–6.84%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 8/117 (6.84%)
TSHR0.2–4.27%thca_tcga_pan_can_atlas_2018: 1/489 (0.2%) · thyroid_mskcc_2016: 5/117 (4.27%)
SLC5A50.0–0.2%thca_tcga_pan_can_atlas_2018: 1/489 (0.2%) · thyroid_mskcc_2016: 0/82 (0.0%)
PAX80.0–0.2%thca_tcga_pan_can_atlas_2018: 1/489 (0.2%) · thyroid_mskcc_2016: 0/82 (0.0%)
TG0.0–3.89%thca_tcga_pan_can_atlas_2018: 19/489 (3.89%) · thyroid_mskcc_2016: 0/82 (0.0%)
ZFHX30.0–1.84%thca_tcga_pan_can_atlas_2018: 9/489 (1.84%) · thyroid_mskcc_2016: 0/82 (0.0%)
KMT2A1.43–5.13%thca_tcga_pan_can_atlas_2018: 7/489 (1.43%) · thyroid_mskcc_2016: 6/117 (5.13%)
EIF1AX1.43–10.26%thca_tcga_pan_can_atlas_2018: 7/489 (1.43%) · thyroid_mskcc_2016: 12/117 (10.26%)
COL5A30.0–1.43%thca_tcga_pan_can_atlas_2018: 7/489 (1.43%) · thyroid_mskcc_2016: 0/82 (0.0%)
PIK3R50.0–1.23%thca_tcga_pan_can_atlas_2018: 6/489 (1.23%) · thyroid_mskcc_2016: 0/82 (0.0%)
KMT2C1.23–2.56%thca_tcga_pan_can_atlas_2018: 6/489 (1.23%) · thyroid_mskcc_2016: 3/117 (2.56%)
ITPR20.0–1.23%thca_tcga_pan_can_atlas_2018: 6/489 (1.23%) · thyroid_mskcc_2016: 0/82 (0.0%)
ATM1.23–8.55%thca_tcga_pan_can_atlas_2018: 6/489 (1.23%) · thyroid_mskcc_2016: 10/117 (8.55%)
USP9X0.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
TENM20.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
TACC20.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
SHROOM20.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
PTPRZ10.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
PKHD10.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
PDZD20.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
NAV30.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
LTBP20.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
LAMA40.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
HSPG20.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
GBF10.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
FBN10.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
DNMT3A1.02–1.71%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 2/117 (1.71%)
COL7A10.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
BPTF0.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
BDP10.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
ALPK30.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/82 (0.0%)
AKT10.0–1.02%thca_tcga_pan_can_atlas_2018: 5/489 (1.02%) · thyroid_mskcc_2016: 0/117 (0.0%)
ZC3H130.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
WNK20.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
WDR330.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
VPS13D0.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
UGGT20.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
UBQLN20.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
THBS20.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
TENM40.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (0.0%)
STOX20.0–0.82%thca_tcga_pan_can_atlas_2018: 4/489 (0.82%) · thyroid_mskcc_2016: 0/82 (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/thyroid-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.