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Myelodysplastic syndromes mutation landscape

How often each gene is altered in myelodysplastic syndromes, 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: mds_iwg_2022 · JSON: /disease/myelodysplastic-syndromes/mutations.json · Back to the briefing

Answer block

In IWG-PM myelodysplastic syndromes (NEJM Evidence 2022) (3323 sequenced patients, targeted panel), the most frequently altered of the 41 genes shown are TET2 31.39%, ASXL1 28.41%, SF3B1 22.69%, SRSF2 17.39%, DNMT3A 16.04%. Each figure divides by the patients on whom that gene could be called.

Of the briefing's 12 curated targets, 1 are altered in under 2% of this cohort (BCL2): 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%.

Alterationmds_iwg_2022
3323 pts · targeted panel
mds_mskcc_2020
4231 pts · mixed
SF3B1 SNV / small indel22.69%754/33238.93%378/4231
TP53 SNV / small indel11.74%390/33239.41%398/4231
TET2 SNV / small indel31.39%1043/332316.12%682/4231
ASXL1 SNV / small indel28.41%944/332310.26%434/4231
DNMT3A SNV / small indel16.04%533/332320.14%852/4231
RUNX1 SNV / small indel13.99%465/33239.57%405/4231
SRSF2 SNV / small indel17.39%578/33239.81%415/4231
U2AF1 SNV / small indel8.7%289/33234.77%202/4231
EZH2 SNV / small indel7.22%240/33233.99%169/4231
STAG2 SNV / small indel9.3%309/33234.4%186/4231
IDH2 SNV / small indel5.39%179/33238.48%359/4231
BCL2 SNV / small indel0.06%2/33230%
KMT2D SNV / small indel6.68%222/33232.08%75/3601
BCOR SNV / small indel6.62%220/33233.71%157/4231
ZRSR2 SNV / small indel6.02%200/33232.15%91/4231
CBL SNV / small indel5.99%199/33233.17%134/4231
CUX1 SNV / small indel5.66%188/33231.2%43/3598
NF1 SNV / small indel5.57%185/33232.67%96/3601
SETBP1 SNV / small indel5.39%179/33232.25%51/2265
NRAS SNV / small indel5.39%179/332311.63%492/4231
KMT2C SNV / small indel5.03%167/33231.97%71/3601
SRCAP SNV / small indel4.6%153/33230.58%6/1026
NOTCH1 SNV / small indel4.06%135/33230.87%37/4231
JAK2 SNV / small indel4.06%135/33237.94%336/4231
EP300 SNV / small indel3.91%130/33232.47%89/3601
MGA SNV / small indel3.88%129/33230.49%8/1638
KRAS SNV / small indel3.76%125/33234.35%184/4231
DDX41 SNV / small indel3.73%124/33230.78%8/1026
YLPM1 SNV / small indel3.61%120/33230.29%3/1026
PHF6 SNV / small indel3.46%115/33232.65%112/4228
KMT2A SNV / small indel3.4%113/33230.99%42/4231
CREBBP SNV / small indel3.31%110/33231.14%41/3601
IDH1 SNV / small indel3.28%109/33236.22%263/4231
SMG1 SNV / small indel3.16%105/33230.61%10/1635
NOTCH2 SNV / small indel3.16%105/33230.67%11/1638
SH2B3 SNV / small indel3.04%101/33230.53%19/3601
ARID1A SNV / small indel3.01%100/33230.49%8/1638
MPL SNV / small indel2.92%97/33231.11%47/4231
SETD2 SNV / small indel2.89%96/33230.79%13/1638
PHIP SNV / small indel2.86%95/33230.97%10/1026
ETNK1 SNV / small indel2.74%91/33230.37%6/1635

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

Key findings

TET2 is mutated in 1043 of 3323 patients in IWG-PM myelodysplastic syndromes (NEJM Evidence 2022).
Numerator: 1043 · Denominator: 3323 · Frequency: 31.39% · Observed in 2 cohorts · Confidence: low · Source: mds_iwg_2022 · Retrieved: 2026-09-17

ASXL1 is mutated in 944 of 3323 patients in IWG-PM myelodysplastic syndromes (NEJM Evidence 2022).
Numerator: 944 · Denominator: 3323 · Frequency: 28.41% · Observed in 2 cohorts · Confidence: low · Source: mds_iwg_2022 · Retrieved: 2026-09-17

SF3B1 is mutated in 754 of 3323 patients in IWG-PM myelodysplastic syndromes (NEJM Evidence 2022).
Numerator: 754 · Denominator: 3323 · Frequency: 22.69% · Observed in 2 cohorts · Confidence: low · Source: mds_iwg_2022 · Retrieved: 2026-09-17

Gene table — reference cohort

Headline values are from the reference cohort, mds_iwg_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
SF3B1 curated target SNV / small indel 754 / 3323 22.69% 2 / 2 8.93–22.69% K700E (n=426), H662Q (n=55), K666N (n=41), R625C (n=38), E622D (n=30)
TP53 curated target SNV / small indel 390 / 3323 11.74% 2 / 2 9.41–11.74% R273H (n=28), Y220C (n=17), R248Q (n=16), R175H (n=12), R248W (n=12)
TET2 curated target SNV / small indel 1043 / 3323 31.39% 2 / 2 16.12–31.39% I1873T (n=25), R550* (n=21), R1516* (n=19), N275Ifs*18 (n=18), H1380Y (n=15)
ASXL1 curated target SNV / small indel 944 / 3323 28.41% 2 / 2 10.26–28.41% G646Wfs*12 (n=371), E635Rfs*15 (n=114), R693* (n=40), Y591* (n=25), R1068* (n=12)
DNMT3A curated target SNV / small indel 533 / 3323 16.04% 2 / 2 16.04–20.14% R882H (n=81), R882C (n=32), Y735C (n=10), R635Q (n=8), X866_splice (n=7)
RUNX1 curated target SNV / small indel 465 / 3323 13.99% 2 / 2 9.57–13.99% R201Q (n=27), R201* (n=15), R320* (n=15), R166* (n=14), R107C (n=10)
SRSF2 curated target SNV / small indel 578 / 3323 17.39% 2 / 2 9.81–17.39% P95H (n=246), P95L (n=147), P95R (n=84), P95_R102del (n=60), P95A (n=9)
U2AF1 curated target SNV / small indel 289 / 3323 8.7% 2 / 2 4.77–8.7% Q157P (n=102), S34F (n=97), Q157R (n=38), S34Y (n=19), R156H (n=13)
EZH2 curated target SNV / small indel 240 / 3323 7.22% 2 / 2 3.99–7.22% R690H (n=10), X732_splice (n=6), R690C (n=6), X243_splice (n=5), R207* (n=5)
STAG2 curated target SNV / small indel 309 / 3323 9.3% 2 / 2 4.4–9.3% R259* (n=17), R614* (n=16), R216* (n=13), R1012* (n=10), R953* (n=8)
IDH2 curated target SNV / small indel 179 / 3323 5.39% 2 / 2 5.39–8.48% R140Q (n=142), R172K (n=13), R140W (n=8), Y179D (n=1), V147I (n=1)
BCL2 curated target SNV / small indel 2 / 3323 0.06% 1 / 2 0.0–0.06% R109C (n=1), P40S (n=1)
KMT2D by frequency SNV / small indel 222 / 3323 6.68% 2 / 2 2.08–6.68% A2379V (n=4), L2610P (n=3), E749G (n=3), P2146L (n=3), Q3899K (n=2)
BCOR by frequency SNV / small indel 220 / 3323 6.62% 2 / 2 3.71–6.62% X1476_splice (n=7), L1646Pfs*6 (n=5), N1495S (n=4), X1659_splice (n=4), R1547* (n=4)
ZRSR2 by frequency SNV / small indel 200 / 3323 6.02% 2 / 2 2.15–6.02% X276_splice (n=20), X68_splice (n=9), R126* (n=8), R295* (n=6), R290* (n=5)
CBL by frequency SNV / small indel 199 / 3323 5.99% 2 / 2 3.17–5.99% R420Q (n=24), C404Y (n=15), L380P (n=12), R149* (n=6), C384R (n=6)
CUX1 by frequency SNV / small indel 188 / 3323 5.66% 2 / 2 1.2–5.66% P431Sfs*16 (n=7), R996* (n=5), R1261* (n=5), X688_splice (n=3), L784V (n=3)
NF1 by frequency SNV / small indel 185 / 3323 5.57% 2 / 2 2.67–5.57% I679Dfs*21 (n=21), K2547Qfs*9 (n=13), R1276Q (n=6), Y2264* (n=4), L2690Cfs*28 (n=3)
SETBP1 by frequency SNV / small indel 179 / 3323 5.39% 2 / 2 2.25–5.39% D868N (n=62), G870S (n=26), I871T (n=10), S869N (n=5), M1319T (n=5)
NRAS by frequency SNV / small indel 179 / 3323 5.39% 2 / 2 5.39–11.63% G12D (n=67), G13D (n=25), G12S (n=21), G12V (n=20), G13V (n=12)
KMT2C by frequency SNV / small indel 167 / 3323 5.03% 2 / 2 1.97–5.03% S321N (n=5), D372V (n=5), G824D (n=4), S784Y (n=4), N2830H (n=3)
SRCAP by frequency SNV / small indel 153 / 3323 4.6% 2 / 2 0.58–4.6% D81H (n=2), R1025* (n=2), N1078S (n=2), P2217S (n=2), A1591V (n=2)
NOTCH1 by frequency SNV / small indel 135 / 3323 4.06% 2 / 2 0.87–4.06% V2536I (n=3), V726I (n=3), R2313Q (n=3), L2457V (n=2), G2300R (n=2)
JAK2 by frequency SNV / small indel 135 / 3323 4.06% 2 / 2 4.06–7.94% V617F (n=84), G571S (n=4), I899T (n=4), R564L (n=2), E543_D544del (n=2)
EP300 by frequency SNV / small indel 130 / 3323 3.91% 2 / 2 2.47–3.91% Y638C (n=7), P784L (n=4), P747L (n=3), L1520V (n=3), L2393V (n=3)
MGA by frequency SNV / small indel 129 / 3323 3.88% 2 / 2 0.49–3.88% V599L (n=5), H1325Q (n=3), S1629F (n=2), V2842I (n=2), N1279T (n=2)
KRAS by frequency SNV / small indel 125 / 3323 3.76% 2 / 2 3.76–4.35% G12R (n=14), G12D (n=14), K117N (n=9), G13D (n=9), T58I (n=8)
DDX41 by frequency SNV / small indel 124 / 3323 3.73% 2 / 2 0.78–3.73% R525H (n=34), M1? (n=18), D140Gfs*2 (n=9), G530D (n=7), P321L (n=6)
YLPM1 by frequency SNV / small indel 120 / 3323 3.61% 2 / 2 0.29–3.61% G255Wfs*3 (n=8), R784C (n=3), R789C (n=2), P593Q (n=2), T1989A (n=2)
PHF6 by frequency SNV / small indel 115 / 3323 3.46% 2 / 2 2.65–3.46% I314T (n=11), R274* (n=5), R319* (n=5), R225* (n=5), R274Q (n=5)
KMT2A by frequency SNV / small indel 113 / 3323 3.4% 2 / 2 0.99–3.4% K895R (n=2), L1303V (n=2), R3564Q (n=2), G3439S (n=2), S1861R (n=2)
CREBBP by frequency SNV / small indel 110 / 3323 3.31% 2 / 2 1.14–3.31% S1934P (n=6), W1745* (n=5), E1709* (n=4), W1718* (n=4), Y1204F (n=4)
IDH1 by frequency SNV / small indel 109 / 3323 3.28% 2 / 2 3.28–6.22% R132C (n=38), R132H (n=36), R132G (n=7), R132L (n=4), R314H (n=3)
SMG1 by frequency SNV / small indel 105 / 3323 3.16% 2 / 2 0.61–3.16% Y1547H (n=2), A3141V (n=2), P2247A (n=2), N1636S (n=2), A1331T (n=2)
NOTCH2 by frequency SNV / small indel 105 / 3323 3.16% 2 / 2 0.67–3.16% P287A (n=2), Q1791H (n=2), V1666I (n=2), L775V (n=2), R285H (n=2)
SH2B3 by frequency SNV / small indel 101 / 3323 3.04% 2 / 2 0.53–3.04% E208Q (n=12), E523Rfs*23 (n=11), R308* (n=2), D231Y (n=2), R392W (n=2)
ARID1A by frequency SNV / small indel 100 / 3323 3.01% 2 / 2 0.49–3.01% P1560A (n=3), N2220S (n=3), A167dup (n=2), G127dup (n=2), V1982I (n=2)
MPL by frequency SNV / small indel 97 / 3323 2.92% 2 / 2 1.11–2.92% W515L (n=12), Y591D (n=8), V556F (n=6), R592* (n=6), R592Q (n=5)
SETD2 by frequency SNV / small indel 96 / 3323 2.89% 2 / 2 0.79–2.89% K629E (n=5), N1943K (n=2), P2057S (n=2), G1967D (n=2), G508V (n=2)
PHIP by frequency SNV / small indel 95 / 3323 2.86% 2 / 2 0.97–2.86% R110C (n=2), X14_splice (n=2), I1622V (n=2), X509_splice (n=2), R797C (n=2)
ETNK1 by frequency SNV / small indel 91 / 3323 2.74% 2 / 2 0.37–2.74% N244S (n=61), G245D (n=3), N244Y (n=2), S124R (n=2), P248R (n=2)

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
IWG-PM myelodysplastic syndromes (NEJM Evidence 2022) reference
Myelodysplastic Syndromes (MDS IWG, IPSSM, NEJM Evidence 2022)
mds_iwg_20223323 observed3323 / 3323targeted panelMDSIWG152 (3323)hg19SNV, small indel04
MSK myelodysplastic syndromes (2020)
Myelodysplastic (MSK, 2020)
mds_mskcc_20204231 observed4231 / 4231mixedPapaemmanuil_NEJM_2016_MDS_2013_panel (1963), WES (1026), RDTB49 (630), IMPACT-HEME-400 (609), IMPACT468 (2), IMPACT410 (1)hg19SNV, small indel223

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
No copy-number profile reached 2% for any listed gene, or no cohort carries one.

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)
SF3B18.93–22.69%mds_iwg_2022: 754/3323 (22.69%) · mds_mskcc_2020: 378/4231 (8.93%)
TP539.41–11.74%mds_iwg_2022: 390/3323 (11.74%) · mds_mskcc_2020: 398/4231 (9.41%)
TET216.12–31.39%mds_iwg_2022: 1043/3323 (31.39%) · mds_mskcc_2020: 682/4231 (16.12%)
ASXL110.26–28.41%mds_iwg_2022: 944/3323 (28.41%) · mds_mskcc_2020: 434/4231 (10.26%)
DNMT3A16.04–20.14%mds_iwg_2022: 533/3323 (16.04%) · mds_mskcc_2020: 852/4231 (20.14%)
RUNX19.57–13.99%mds_iwg_2022: 465/3323 (13.99%) · mds_mskcc_2020: 405/4231 (9.57%)
SRSF29.81–17.39%mds_iwg_2022: 578/3323 (17.39%) · mds_mskcc_2020: 415/4231 (9.81%)
U2AF14.77–8.7%mds_iwg_2022: 289/3323 (8.7%) · mds_mskcc_2020: 202/4231 (4.77%)
EZH23.99–7.22%mds_iwg_2022: 240/3323 (7.22%) · mds_mskcc_2020: 169/4231 (3.99%)
STAG24.4–9.3%mds_iwg_2022: 309/3323 (9.3%) · mds_mskcc_2020: 186/4231 (4.4%)
IDH25.39–8.48%mds_iwg_2022: 179/3323 (5.39%) · mds_mskcc_2020: 359/4231 (8.48%)
BCL20.0–0.06%mds_iwg_2022: 2/3323 (0.06%) · mds_mskcc_2020: 0/1638 (0.0%)
KMT2D2.08–6.68%mds_iwg_2022: 222/3323 (6.68%) · mds_mskcc_2020: 75/3601 (2.08%)
BCOR3.71–6.62%mds_iwg_2022: 220/3323 (6.62%) · mds_mskcc_2020: 157/4231 (3.71%)
ZRSR22.15–6.02%mds_iwg_2022: 200/3323 (6.02%) · mds_mskcc_2020: 91/4231 (2.15%)
CBL3.17–5.99%mds_iwg_2022: 199/3323 (5.99%) · mds_mskcc_2020: 134/4231 (3.17%)
CUX11.2–5.66%mds_iwg_2022: 188/3323 (5.66%) · mds_mskcc_2020: 43/3598 (1.2%)
NF12.67–5.57%mds_iwg_2022: 185/3323 (5.57%) · mds_mskcc_2020: 96/3601 (2.67%)
SETBP12.25–5.39%mds_iwg_2022: 179/3323 (5.39%) · mds_mskcc_2020: 51/2265 (2.25%)
NRAS5.39–11.63%mds_iwg_2022: 179/3323 (5.39%) · mds_mskcc_2020: 492/4231 (11.63%)
KMT2C1.97–5.03%mds_iwg_2022: 167/3323 (5.03%) · mds_mskcc_2020: 71/3601 (1.97%)
SRCAP0.58–4.6%mds_iwg_2022: 153/3323 (4.6%) · mds_mskcc_2020: 6/1026 (0.58%)
NOTCH10.87–4.06%mds_iwg_2022: 135/3323 (4.06%) · mds_mskcc_2020: 37/4231 (0.87%)
JAK24.06–7.94%mds_iwg_2022: 135/3323 (4.06%) · mds_mskcc_2020: 336/4231 (7.94%)
EP3002.47–3.91%mds_iwg_2022: 130/3323 (3.91%) · mds_mskcc_2020: 89/3601 (2.47%)
MGA0.49–3.88%mds_iwg_2022: 129/3323 (3.88%) · mds_mskcc_2020: 8/1638 (0.49%)
KRAS3.76–4.35%mds_iwg_2022: 125/3323 (3.76%) · mds_mskcc_2020: 184/4231 (4.35%)
DDX410.78–3.73%mds_iwg_2022: 124/3323 (3.73%) · mds_mskcc_2020: 8/1026 (0.78%)
YLPM10.29–3.61%mds_iwg_2022: 120/3323 (3.61%) · mds_mskcc_2020: 3/1026 (0.29%)
PHF62.65–3.46%mds_iwg_2022: 115/3323 (3.46%) · mds_mskcc_2020: 112/4228 (2.65%)
KMT2A0.99–3.4%mds_iwg_2022: 113/3323 (3.4%) · mds_mskcc_2020: 42/4231 (0.99%)
CREBBP1.14–3.31%mds_iwg_2022: 110/3323 (3.31%) · mds_mskcc_2020: 41/3601 (1.14%)
IDH13.28–6.22%mds_iwg_2022: 109/3323 (3.28%) · mds_mskcc_2020: 263/4231 (6.22%)
SMG10.61–3.16%mds_iwg_2022: 105/3323 (3.16%) · mds_mskcc_2020: 10/1635 (0.61%)
NOTCH20.67–3.16%mds_iwg_2022: 105/3323 (3.16%) · mds_mskcc_2020: 11/1638 (0.67%)
SH2B30.53–3.04%mds_iwg_2022: 101/3323 (3.04%) · mds_mskcc_2020: 19/3601 (0.53%)
ARID1A0.49–3.01%mds_iwg_2022: 100/3323 (3.01%) · mds_mskcc_2020: 8/1638 (0.49%)
MPL1.11–2.92%mds_iwg_2022: 97/3323 (2.92%) · mds_mskcc_2020: 47/4231 (1.11%)
SETD20.79–2.89%mds_iwg_2022: 96/3323 (2.89%) · mds_mskcc_2020: 13/1638 (0.79%)
PHIP0.97–2.86%mds_iwg_2022: 95/3323 (2.86%) · mds_mskcc_2020: 10/1026 (0.97%)
ETNK10.37–2.74%mds_iwg_2022: 91/3323 (2.74%) · mds_mskcc_2020: 6/1635 (0.37%)

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/myelodysplastic-syndromes.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.