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Disease intelligence · mutation landscape

Gallbladder cancer mutation landscape

How often each gene is altered in gallbladder 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: gbc_mskcc_2022 · JSON: /disease/gallbladder-cancer/mutations.json · Back to the briefing

Answer block

In Gallbladder Cancer (MSK, 2022) (233 sequenced patients, targeted panel), the most frequently altered of the 43 genes shown are TP53 63.95%, SMAD4 21.89%, ARID1A 20.6%, CDKN2A 15.02% (deep deletion), ELF3 10.75%. Each figure divides by the patients on whom that gene could be called.

Of the briefing's 12 curated targets, 2 are altered in under 2% of this cohort (FGFR2, IDH1): 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%.

Alterationgbc_mskcc_2022
233 pts · targeted panel
gbc_shanghai_2014
32 pts · exome or genome
ERBB2 SNV / small indel7.3%17/2339.38%3/32
ERBB2 amplification10.3%24/233·
TP53 SNV / small indel63.95%149/23325.0%8/32
KRAS SNV / small indel7.73%18/2330%
KRAS amplification4.29%10/233·
PIK3CA SNV / small indel10.73%25/2336.25%2/32
CDKN2A SNV / small indel9.87%23/2330%
CDKN2A deep deletion15.02%35/233·
ARID1A SNV / small indel20.6%48/2336.25%2/32
ERBB3 SNV / small indel6.44%15/2339.38%3/32
ERBB3 amplification5.15%12/233·
EGFR SNV / small indel1.29%3/2333.12%1/32
EGFR amplification3.43%8/233·
CTNNB1 SNV / small indel6.44%15/2330%
SMAD4 SNV / small indel21.89%51/2333.12%1/32
SMAD4 deep deletion4.72%11/233·
FGFR2 SNV / small indel1.29%3/2330%
IDH1 SNV / small indel0.43%1/2330%
STK11 SNV / small indel9.44%22/2330%
KMT2C SNV / small indel8.58%20/2339.38%3/32
ELF3 SNV / small indel10.75%20/1866.25%2/32
ARID2 SNV / small indel8.58%20/2336.25%2/32
KMT2D SNV / small indel6.87%16/2333.12%1/32
ATM SNV / small indel6.87%16/2333.12%1/32
BRCA2 SNV / small indel5.58%13/2330%
RBM10 SNV / small indel4.72%11/2330%
RB1 SNV / small indel4.29%10/2333.12%1/32
RB1 deep deletion3.0%7/233·
PBRM1 SNV / small indel4.29%10/2330%
NF1 SNV / small indel4.29%10/2330%
KMT2A SNV / small indel4.29%10/2330%
SLX4 SNV / small indel4.84%9/1863.12%1/32
PREX2 SNV / small indel4.84%9/1863.12%1/32
KEAP1 SNV / small indel3.86%9/2330%
FBXW7 SNV / small indel3.86%9/2333.12%1/32
AXIN1 SNV / small indel3.86%9/2330%
ATRX SNV / small indel3.86%9/2333.12%1/32
RASA1 SNV / small indel3.43%8/2330%
PTPRD SNV / small indel3.43%8/2330%
NOTCH3 SNV / small indel3.43%8/2330%
JAK1 SNV / small indel3.43%8/2330%
IKZF1 SNV / small indel3.43%8/2330%
EP300 SNV / small indel3.43%8/2330%
CDK12 SNV / small indel3.43%8/2330%
CDK12 amplification6.87%16/233·
ARID1B SNV / small indel3.43%8/2330%
ARID1B deep deletion2.15%5/233·
APC SNV / small indel3.43%8/2330%
ZFHX3 SNV / small indel3.11%7/2250%
RNF43 SNV / small indel3.0%7/2330%
PTPRS SNV / small indel3.0%7/2333.12%1/32
PTEN SNV / small indel3.0%7/2330%

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 149 of 233 patients in Gallbladder Cancer (MSK, 2022).
Numerator: 149 · Denominator: 233 · Frequency: 63.95% · Observed in 2 cohorts · Confidence: low · Source: gbc_mskcc_2022 · Retrieved: 2026-09-18

SMAD4 is mutated in 51 of 233 patients in Gallbladder Cancer (MSK, 2022).
Numerator: 51 · Denominator: 233 · Frequency: 21.89% · Observed in 2 cohorts · Confidence: low · Source: gbc_mskcc_2022 · Retrieved: 2026-09-18

ARID1A is mutated in 48 of 233 patients in Gallbladder Cancer (MSK, 2022).
Numerator: 48 · Denominator: 233 · Frequency: 20.6% · Observed in 2 cohorts · Confidence: low · Source: gbc_mskcc_2022 · Retrieved: 2026-09-18

Gene table — reference cohort

Headline values are from the reference cohort, gbc_mskcc_2022; 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
ERBB2 curated target amplification 24 / 233 10.3% mutation 7.3% 2 / 2 7.3–9.38% S310F (n=5), S310Y (n=5), D769Y (n=3), L755S (n=2), R678Q (n=2)
TP53 curated target SNV / small indel 149 / 233 63.95% 2 / 2 25.0–63.95% R248Q (n=9), R175H (n=7), R273H (n=5), Y234C (n=4), R306* (n=3)
KRAS curated target SNV / small indel 18 / 233 7.73% 1 / 2 0.0–7.73% G13D (n=5), G12D (n=5), Q61H (n=2), G12C (n=2), G12A (n=2)
PIK3CA curated target SNV / small indel 25 / 233 10.73% 2 / 2 6.25–10.73% E542K (n=6), E545K (n=4), H1047R (n=4), E81K (n=2), E726K (n=2)
CDKN2A curated target deep deletion 35 / 233 15.02% mutation 9.87% 1 / 2 0.0–9.87% R80* (n=3), R29_A34del (n=2), D84N (n=2), E120* (n=2), E10* (n=2)
ARID1A curated target SNV / small indel 48 / 233 20.6% 2 / 2 6.25–20.6% Y551Lfs*72 (n=2), D322Y (n=2), Q1095del (n=2), Q515* (n=2), A1978Sfs*36 (n=1)
ERBB3 curated target SNV / small indel 15 / 233 6.44% 2 / 2 6.44–9.38% T355I (n=2), G914R (n=2), V104L (n=2), G284R (n=2), G994D (n=1)
EGFR curated target amplification 8 / 233 3.43% mutation 1.29% 2 / 2 1.29–3.12% V742I (n=1), V769_D770insG (n=1), N808D (n=1)
CTNNB1 curated target SNV / small indel 15 / 233 6.44% 1 / 2 0.0–6.44% S45P (n=5), S37F (n=2), S45F (n=2), D32V (n=1), S33F (n=1)
SMAD4 curated target SNV / small indel 51 / 233 21.89% 2 / 2 3.12–21.89% R361C (n=4), R361H (n=4), G386R (n=3), Q448* (n=2), D493G (n=2)
FGFR2 curated target SNV / small indel 3 / 233 1.29% 1 / 2 0.0–1.29% F798L (n=1), G182E (n=1), T762Hfs*6 (n=1)
IDH1 curated target SNV / small indel 1 / 233 0.43% 1 / 2 0.0–0.43% M18I (n=1)
STK11 by frequency SNV / small indel 22 / 233 9.44% 1 / 2 0.0–9.44% L117Ifs*45 (n=1), S216F (n=1), C134_V143del (n=1), G251R (n=1), F255Sfs*32 (n=1)
KMT2C by frequency SNV / small indel 20 / 233 8.58% 2 / 2 8.58–9.38% Q2539* (n=1), P4655Sfs*5 (n=1), S2984Ffs*18 (n=1), Y4161Sfs*3 (n=1), R2307K (n=1)
ELF3 by frequency SNV / small indel 20 / 186 10.75% 2 / 2 6.25–10.75% M324Nfs*147 (n=2), K304Qfs*167 (n=2), N83Kfs*9 (n=2), F92Mfs*2 (n=1), X334_splice (n=1)
ARID2 by frequency SNV / small indel 20 / 233 8.58% 2 / 2 6.25–8.58% Q1016* (n=1), S319F (n=1), E12Wfs*38 (n=1), I37Nfs*29 (n=1), Q609* (n=1)
KMT2D by frequency SNV / small indel 16 / 233 6.87% 2 / 2 3.12–6.87% G1235Vfs*95 (n=2), E1159Q (n=1), S2719N (n=1), P647Hfs*283 (n=1), P3131del (n=1)
ATM by frequency SNV / small indel 16 / 233 6.87% 2 / 2 3.12–6.87% R35Q (n=1), R2138Kfs*8 (n=1), D2725H (n=1), F2571Yfs*4 (n=1), I149del (n=1)
BRCA2 by frequency SNV / small indel 13 / 233 5.58% 1 / 2 0.0–5.58% R2520* (n=1), L1387F (n=1), I3171R (n=1), K1691Nfs*15 (n=1), E1641K (n=1)
RBM10 by frequency SNV / small indel 11 / 233 4.72% 1 / 2 0.0–4.72% M731I (n=1), R21H (n=1), X68_splice (n=1), A421Rfs*19 (n=1), A553Hfs*73 (n=1)
RB1 by frequency SNV / small indel 10 / 233 4.29% 2 / 2 3.12–4.29% Y655Lfs*13 (n=1), X406_splice (n=1), P2R (n=1), E817del (n=1), X737_splice (n=1)
PBRM1 by frequency SNV / small indel 10 / 233 4.29% 1 / 2 0.0–4.29% E52* (n=1), S892_T895delinsKNI (n=1), I279Nfs*8 (n=1), R365C (n=1), N258Mfs*25 (n=1)
NF1 by frequency SNV / small indel 10 / 233 4.29% 1 / 2 0.0–4.29% X2274_splice (n=1), R304* (n=1), R416Q (n=1), X574_splice (n=1), H1494Qfs*7 (n=1)
KMT2A by frequency SNV / small indel 10 / 233 4.29% 1 / 2 0.0–4.29% S2201F (n=1), P3522A (n=1), Q554Pfs*27 (n=1), K2658T (n=1), E2533* (n=1)
SLX4 by frequency SNV / small indel 9 / 186 4.84% 2 / 2 3.12–4.84% T102Nfs*18 (n=1), R1468C (n=1), L1256V (n=1), S1134* (n=1), T162M (n=1)
PREX2 by frequency SNV / small indel 9 / 186 4.84% 2 / 2 3.12–4.84% K60N (n=1), E550Q (n=1), Y758H (n=1), S1551C (n=1), F1318L (n=1)
KEAP1 by frequency SNV / small indel 9 / 233 3.86% 1 / 2 0.0–3.86% R362Q (n=2), S102L (n=1), Y567* (n=1), L179R (n=1), D422N (n=1)
FBXW7 by frequency SNV / small indel 9 / 233 3.86% 2 / 2 3.12–3.86% R479Q (n=2), R278* (n=1), S668Vfs*39 (n=1), R83K (n=1), L283Afs*3 (n=1)
AXIN1 by frequency SNV / small indel 9 / 233 3.86% 1 / 2 0.0–3.86% E548* (n=1), E716* (n=1), W85* (n=1), E407* (n=1), Y148* (n=1)
ATRX by frequency SNV / small indel 9 / 233 3.86% 2 / 2 3.12–3.86% S1996G (n=1), D1211E (n=1), Q2348* (n=1), R1803H (n=1), D699Gfs*2 (n=1)
RASA1 by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% R679* (n=1), R589H (n=1), A753T (n=1), R903* (n=1), S69L (n=1)
PTPRD by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% G203* (n=1), P516L (n=1), A395T (n=1), V330I (n=1), I476S (n=1)
NOTCH3 by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% A198G (n=1), R2207Q (n=1), T424A (n=1), G1105Afs*167 (n=1), A957T (n=1)
JAK1 by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% Q387Lfs*66 (n=1), V658Pfs*50 (n=1), Q986Rfs*29 (n=1), P733Gfs*3 (n=1), X663_splice (n=1)
IKZF1 by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% G151R (n=2), E387K (n=1), S445P (n=1), D399Efs*18 (n=1), S364W (n=1)
EP300 by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% K1569R (n=1), Q738H (n=1), P732del (n=1), Y1467C (n=1), T151A (n=1)
CDK12 by frequency amplification 16 / 233 6.87% mutation 3.43% 1 / 2 0.0–3.43% S102L (n=1), S176L (n=1), K132Sfs*5 (n=1), R981C (n=1), E189K (n=1)
ARID1B by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% X1115_splice (n=1), R1075* (n=1), Q905Hfs*6 (n=1), S736Ifs*27 (n=1), P735Hfs*10 (n=1)
APC by frequency SNV / small indel 8 / 233 3.43% 1 / 2 0.0–3.43% Q358* (n=1), Q1541* (n=1), I1574V (n=1), G1499* (n=1), *2844Eext*27 (n=1)
ZFHX3 by frequency SNV / small indel 7 / 225 3.11% 1 / 2 0.0–3.11% X1177_splice (n=2), S1658T (n=1), A3407Lfs*78 (n=1), G3521S (n=1), P3218A (n=1)
RNF43 by frequency SNV / small indel 7 / 233 3.0% 1 / 2 0.0–3.0% G659Vfs*41 (n=3), R371* (n=2), P369T (n=1), I186F (n=1), S121* (n=1)
PTPRS by frequency SNV / small indel 7 / 233 3.0% 2 / 2 3.0–3.12% R148Q (n=2), Q1009H (n=1), R1696C (n=1), P1809L (n=1), E1928K (n=1)
PTEN by frequency SNV / small indel 7 / 233 3.0% 1 / 2 0.0–3.0% R130Q (n=1), D19Gfs*25 (n=1), Q245* (n=1), K267Rfs*9 (n=1), R130* (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
Gallbladder Cancer (MSK, 2022) reference
Gallbladder Cancer (MSK, 2022)
gbc_mskcc_2022233 observed244 / 244targeted panelIMPACT468 (151), IMPACT410 (44), IMPACT505 (40), IMPACT341 (9)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)05.0
Gallbladder Carcinoma (Shanghai, Nat Genet 2014)
Gallbladder Carcinoma (Shanghai, Nat Genet 2014)
gbc_shanghai_201432 observed32 / 32exome or genomeWES (32)hg19SNV, small indel029.0

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 deletion3523315.02%gbc_mskcc_2022gbc_mskcc_2022_cna
ERBB2amplification2423310.3%gbc_mskcc_2022gbc_mskcc_2022_cna
CDK12amplification162336.87%gbc_mskcc_2022gbc_mskcc_2022_cna
ERBB3amplification122335.15%gbc_mskcc_2022gbc_mskcc_2022_cna
SMAD4deep deletion112334.72%gbc_mskcc_2022gbc_mskcc_2022_cna
KRASamplification102334.29%gbc_mskcc_2022gbc_mskcc_2022_cna
EGFRamplification82333.43%gbc_mskcc_2022gbc_mskcc_2022_cna
RB1deep deletion72333.0%gbc_mskcc_2022gbc_mskcc_2022_cna
ARID1Bdeep deletion52332.15%gbc_mskcc_2022gbc_mskcc_2022_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)
ERBB27.3–9.38%gbc_mskcc_2022: 17/233 (7.3%) · gbc_shanghai_2014: 3/32 (9.38%)
TP5325.0–63.95%gbc_mskcc_2022: 149/233 (63.95%) · gbc_shanghai_2014: 8/32 (25.0%)
KRAS0.0–7.73%gbc_mskcc_2022: 18/233 (7.73%) · gbc_shanghai_2014: 0/32 (0.0%)
PIK3CA6.25–10.73%gbc_mskcc_2022: 25/233 (10.73%) · gbc_shanghai_2014: 2/32 (6.25%)
CDKN2A0.0–9.87%gbc_mskcc_2022: 23/233 (9.87%) · gbc_shanghai_2014: 0/32 (0.0%)
ARID1A6.25–20.6%gbc_mskcc_2022: 48/233 (20.6%) · gbc_shanghai_2014: 2/32 (6.25%)
ERBB36.44–9.38%gbc_mskcc_2022: 15/233 (6.44%) · gbc_shanghai_2014: 3/32 (9.38%)
EGFR1.29–3.12%gbc_mskcc_2022: 3/233 (1.29%) · gbc_shanghai_2014: 1/32 (3.12%)
CTNNB10.0–6.44%gbc_mskcc_2022: 15/233 (6.44%) · gbc_shanghai_2014: 0/32 (0.0%)
SMAD43.12–21.89%gbc_mskcc_2022: 51/233 (21.89%) · gbc_shanghai_2014: 1/32 (3.12%)
FGFR20.0–1.29%gbc_mskcc_2022: 3/233 (1.29%) · gbc_shanghai_2014: 0/32 (0.0%)
IDH10.0–0.43%gbc_mskcc_2022: 1/233 (0.43%) · gbc_shanghai_2014: 0/32 (0.0%)
STK110.0–9.44%gbc_mskcc_2022: 22/233 (9.44%) · gbc_shanghai_2014: 0/32 (0.0%)
KMT2C8.58–9.38%gbc_mskcc_2022: 20/233 (8.58%) · gbc_shanghai_2014: 3/32 (9.38%)
ELF36.25–10.75%gbc_mskcc_2022: 20/186 (10.75%) · gbc_shanghai_2014: 2/32 (6.25%)
ARID26.25–8.58%gbc_mskcc_2022: 20/233 (8.58%) · gbc_shanghai_2014: 2/32 (6.25%)
KMT2D3.12–6.87%gbc_mskcc_2022: 16/233 (6.87%) · gbc_shanghai_2014: 1/32 (3.12%)
ATM3.12–6.87%gbc_mskcc_2022: 16/233 (6.87%) · gbc_shanghai_2014: 1/32 (3.12%)
BRCA20.0–5.58%gbc_mskcc_2022: 13/233 (5.58%) · gbc_shanghai_2014: 0/32 (0.0%)
RBM100.0–4.72%gbc_mskcc_2022: 11/233 (4.72%) · gbc_shanghai_2014: 0/32 (0.0%)
RB13.12–4.29%gbc_mskcc_2022: 10/233 (4.29%) · gbc_shanghai_2014: 1/32 (3.12%)
PBRM10.0–4.29%gbc_mskcc_2022: 10/233 (4.29%) · gbc_shanghai_2014: 0/32 (0.0%)
NF10.0–4.29%gbc_mskcc_2022: 10/233 (4.29%) · gbc_shanghai_2014: 0/32 (0.0%)
KMT2A0.0–4.29%gbc_mskcc_2022: 10/233 (4.29%) · gbc_shanghai_2014: 0/32 (0.0%)
SLX43.12–4.84%gbc_mskcc_2022: 9/186 (4.84%) · gbc_shanghai_2014: 1/32 (3.12%)
PREX23.12–4.84%gbc_mskcc_2022: 9/186 (4.84%) · gbc_shanghai_2014: 1/32 (3.12%)
KEAP10.0–3.86%gbc_mskcc_2022: 9/233 (3.86%) · gbc_shanghai_2014: 0/32 (0.0%)
FBXW73.12–3.86%gbc_mskcc_2022: 9/233 (3.86%) · gbc_shanghai_2014: 1/32 (3.12%)
AXIN10.0–3.86%gbc_mskcc_2022: 9/233 (3.86%) · gbc_shanghai_2014: 0/32 (0.0%)
ATRX3.12–3.86%gbc_mskcc_2022: 9/233 (3.86%) · gbc_shanghai_2014: 1/32 (3.12%)
RASA10.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
PTPRD0.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
NOTCH30.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
JAK10.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
IKZF10.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
EP3000.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
CDK120.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
ARID1B0.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
APC0.0–3.43%gbc_mskcc_2022: 8/233 (3.43%) · gbc_shanghai_2014: 0/32 (0.0%)
ZFHX30.0–3.11%gbc_mskcc_2022: 7/225 (3.11%) · gbc_shanghai_2014: 0/32 (0.0%)
RNF430.0–3.0%gbc_mskcc_2022: 7/233 (3.0%) · gbc_shanghai_2014: 0/32 (0.0%)
PTPRS3.0–3.12%gbc_mskcc_2022: 7/233 (3.0%) · gbc_shanghai_2014: 1/32 (3.12%)
PTEN0.0–3.0%gbc_mskcc_2022: 7/233 (3.0%) · gbc_shanghai_2014: 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/gallbladder-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.