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Follicular lymphoma mutation landscape

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

Retrieved 2026-09-26 · Reference cohort: heme_msk_impact_2022 · JSON: /disease/follicular-lymphoma/mutations.json · Back to the briefing

Answer block

In MSK-IMPACT Heme, follicular lymphoma subset (2022) (193 sequenced patients, targeted panel), the most frequently altered of the 45 genes shown are CREBBP 70.98%, KMT2D 66.32%, TNFRSF14 46.63%, BCL2 34.72%, EZH2 20.73%. 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 (CD79B): targets by expression, dependency or drug label, not by mutation. Frequency is not targetability, in either direction.

1 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%.

Alterationheme_msk_impact_2022
193 pts · targeted panel
BCL2 SNV / small indel34.72%67/193
MS4A1 SNV / small indel·
CD19 SNV / small indel·
EZH2 SNV / small indel20.73%40/193
CREBBP SNV / small indel70.98%137/193
CREBBP deep deletion2.07%4/193
KMT2D SNV / small indel66.32%128/193
CD79B SNV / small indel1.55%3/193
PIK3CD SNV / small indel·
BTK SNV / small indel6.22%12/193
CD22 SNV / small indel·
TNFRSF14 SNV / small indel46.63%90/193
TNFRSF14 deep deletion11.4%22/193
STAT6 SNV / small indel20.21%39/193
FOXO1 SNV / small indel18.13%35/193
SOCS1 SNV / small indel15.54%30/193
SOCS1 deep deletion2.07%4/193
H1-4 SNV / small indel15.54%30/193
IRF8 SNV / small indel15.03%29/193
ARID1A SNV / small indel13.47%26/193
MEF2B SNV / small indel11.92%23/193
EP300 SNV / small indel10.88%21/193
CARD11 SNV / small indel10.88%21/193
TNFAIP3 SNV / small indel10.36%20/193
TNFAIP3 deep deletion5.18%10/193
GNA13 SNV / small indel9.84%19/193
TP53 SNV / small indel9.33%18/193
RRAGC SNV / small indel9.33%18/193
ATP6V1B2 SNV / small indel8.29%16/193
BCR SNV / small indel7.77%15/193
SGK1 SNV / small indel7.25%14/193
PIM1 SNV / small indel7.25%14/193
SRSF2 SNV / small indel6.74%13/193
SETD1B SNV / small indel6.74%13/193
H1-2 SNV / small indel6.74%13/193
LTB SNV / small indel6.22%12/193
CCND3 SNV / small indel6.22%12/193
B2M SNV / small indel6.22%12/193
ACTG1 SNV / small indel6.22%12/193
FAT1 SNV / small indel5.7%11/193
FAS SNV / small indel5.7%11/193
FAS deep deletion3.11%6/193
DTX1 SNV / small indel5.18%10/193
BTG1 SNV / small indel4.66%9/193
HLA-A SNV / small indel4.15%8/193
H1-5 SNV / small indel4.15%8/193
H1-3 SNV / small indel4.15%8/193
EPHA5 SNV / small indel4.15%8/193
ATP6AP1 SNV / small indel3.63%7/193
ARID5B SNV / small indel3.63%7/193

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

Key findings

CREBBP is mutated in 137 of 193 patients in MSK-IMPACT Heme, follicular lymphoma subset (2022).
Numerator: 137 · Denominator: 193 · Frequency: 70.98% · Observed in 1 cohorts · Confidence: low · Source: heme_msk_impact_2022 · Retrieved: 2026-09-26

KMT2D is mutated in 128 of 193 patients in MSK-IMPACT Heme, follicular lymphoma subset (2022).
Numerator: 128 · Denominator: 193 · Frequency: 66.32% · Observed in 1 cohorts · Confidence: low · Source: heme_msk_impact_2022 · Retrieved: 2026-09-26

TNFRSF14 is mutated in 90 of 193 patients in MSK-IMPACT Heme, follicular lymphoma subset (2022).
Numerator: 90 · Denominator: 193 · Frequency: 46.63% · Observed in 1 cohorts · Confidence: low · Source: heme_msk_impact_2022 · Retrieved: 2026-09-26

Gene table — reference cohort

Headline values are from the reference cohort, heme_msk_impact_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.

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
BCL2 — curated target SNV / small indel 67 / 193 34.72% — 1 / 1 34.72–34.72% A60V (n=6), A131V (n=6), G47D (n=5), P53S (n=5), A131D (n=3)
MS4A1 — curated target SNV / small indel 0 / null 0.0% — 0 / 1 null–null% none recurrent
CD19 — curated target SNV / small indel 0 / null 0.0% — 0 / 1 null–null% none recurrent
EZH2 FDA biomarker2020 · 1 drug curated target SNV / small indel 40 / 193 20.73% — 1 / 1 20.73–20.73% Y646F (n=14), Y646N (n=13), A692V (n=5), Y646H (n=4), A682G (n=3)
CREBBP — curated target SNV / small indel 137 / 193 70.98% — 1 / 1 70.98–70.98% S1680del (n=20), R1446H (n=12), R1446C (n=10), D1435N (n=4), Y1503D (n=4)
KMT2D — curated target SNV / small indel 128 / 193 66.32% — 1 / 1 66.32–66.32% S2910Rfs*32 (n=5), L1461Tfs*30 (n=3), Q4347Rfs*24 (n=3), L860Rfs*70 (n=3), X1303_splice (n=3)
CD79B — curated target SNV / small indel 3 / 193 1.55% — 1 / 1 1.55–1.55% T205Sfs*6 (n=1), I175Mfs*28 (n=1), Y197D (n=1)
PIK3CD — curated target SNV / small indel 0 / null 0.0% — 0 / 1 null–null% none recurrent
BTK — curated target SNV / small indel 12 / 193 6.22% — 1 / 1 6.22–6.22% T316Sfs*6 (n=2), E301del (n=1), Y545D (n=1), G50D (n=1), R28G (n=1)
CD22 — curated target SNV / small indel 0 / null 0.0% — 0 / 1 null–null% none recurrent
TNFRSF14 — curated target SNV / small indel 90 / 193 46.63% — 1 / 1 46.63–46.63% W12* (n=14), X102_splice (n=7), M1? (n=4), X23_splice (n=3), G60D (n=3)
STAT6 — curated target SNV / small indel 39 / 193 20.21% — 1 / 1 20.21–20.21% D419G (n=13), E377K (n=6), D419N (n=5), D419H (n=4), E372K (n=3)
FOXO1 — by frequency SNV / small indel 35 / 193 18.13% — 1 / 1 18.13–18.13% T24I (n=7), S22P (n=6), M1? (n=6), T24A (n=6), S152R (n=4)
SOCS1 — by frequency SNV / small indel 30 / 193 15.54% — 1 / 1 15.54–15.54% M161_L162delinsKV (n=2), S116N (n=2), A17T (n=2), I126L (n=1), L73R (n=1)
H1-4 — by frequency SNV / small indel 30 / 193 15.54% — 1 / 1 15.54–15.54% A167V (n=3), A170V (n=2), A123T (n=2), A116V (n=2), A65P (n=2)
IRF8 — by frequency SNV / small indel 29 / 193 15.03% — 1 / 1 15.03–15.03% S55A (n=3), T80A (n=3), Y23H (n=3), Q392* (n=2), V426D (n=2)
ARID1A — by frequency SNV / small indel 26 / 193 13.47% — 1 / 1 13.47–13.47% Y195Cfs*48 (n=2), G1137* (n=2), G105Efs*8 (n=2), Q520* (n=1), S1961Rfs*53 (n=1)
MEF2B — by frequency SNV / small indel 23 / 193 11.92% — 1 / 1 11.92–11.92% D83V (n=5), D83A (n=4), R24Q (n=3), T70R (n=3), Y69H (n=2)
EP300 — by frequency SNV / small indel 21 / 193 10.88% — 1 / 1 10.88–10.88% Y1467D (n=3), Y1467F (n=3), Y1467N (n=2), G1375R (n=2), Y1446N (n=2)
CARD11 — by frequency SNV / small indel 21 / 193 10.88% — 1 / 1 10.88–10.88% D357V (n=5), L253P (n=2), S250P (n=2), Q249P (n=2), E134G (n=1)
TNFAIP3 — by frequency SNV / small indel 20 / 193 10.36% — 1 / 1 10.36–10.36% L324Qfs*7 (n=3), V398Efs*8 (n=2), K96Sfs*14 (n=2), X269_splice (n=2), R136Qfs*3 (n=2)
GNA13 — by frequency SNV / small indel 19 / 193 9.84% — 1 / 1 9.84–9.84% V98E (n=3), E33D (n=2), M1? (n=2), K94E (n=1), Q67L (n=1)
TP53 — by frequency SNV / small indel 18 / 193 9.33% — 1 / 1 9.33–9.33% Y234D (n=2), R175H (n=2), R249G (n=1), V274A (n=1), R282W (n=1)
RRAGC — by frequency SNV / small indel 18 / 193 9.33% — 1 / 1 9.33–9.33% P87L (n=3), G119R (n=3), T90N (n=3), S75F (n=1), D116H (n=1)
ATP6V1B2 — by frequency SNV / small indel 16 / 193 8.29% — 1 / 1 8.29–8.29% R400Q (n=13), Y371C (n=2), M234T (n=1), T411I (n=1), T49A (n=1)
BCR — by frequency SNV / small indel 15 / 193 7.77% — 1 / 1 7.77–7.77% P20S (n=2), G6D (n=2), G124D (n=1), P113S (n=1), E141K (n=1)
SGK1 — by frequency SNV / small indel 14 / 193 7.25% — 1 / 1 7.25–7.25% X51_splice (n=3), A48V (n=2), X26_splice (n=1), G259V (n=1), F38* (n=1)
PIM1 — by frequency SNV / small indel 14 / 193 7.25% — 1 / 1 7.25–7.25% S75P (n=2), L80Rfs*7 (n=1), X35_splice (n=1), G28V (n=1), L25V (n=1)
SRSF2 — by frequency SNV / small indel 13 / 193 6.74% — 1 / 1 6.74–6.74% P95R (n=3), P95_R117del (n=2), G93_H100del (n=1), P95L (n=1), Y92N (n=1)
SETD1B — by frequency SNV / small indel 13 / 193 6.74% — 1 / 1 6.74–6.74% H8Pfs*30 (n=4), P452Hfs*57 (n=2), K91N (n=1), L1532Ffs*35 (n=1), S1814N (n=1)
H1-2 — by frequency SNV / small indel 13 / 193 6.74% — 1 / 1 6.74–6.74% A61T (n=2), A171P (n=2), A190T (n=1), S78Rfs*2 (n=1), A101S (n=1)
LTB — by frequency SNV / small indel 12 / 193 6.22% — 1 / 1 6.22–6.22% L46* (n=2), V36L (n=2), L74* (n=1), X55_splice (n=1), P48A (n=1)
CCND3 — by frequency SNV / small indel 12 / 193 6.22% — 1 / 1 6.22–6.22% I290K (n=3), R271Pfs*53 (n=2), P284R (n=1), I290R (n=1), I290T (n=1)
B2M — by frequency SNV / small indel 12 / 193 6.22% — 1 / 1 6.22–6.22% M1? (n=8), L12P (n=2), L43P (n=1), R3Lfs*55 (n=1), X23_splice (n=1)
ACTG1 — by frequency SNV / small indel 12 / 193 6.22% — 1 / 1 6.22–6.22% S60R (n=3), G13D (n=2), I10T (n=2), G20D (n=1), H73N (n=1)
FAT1 — by frequency SNV / small indel 11 / 193 5.7% — 1 / 1 5.7–5.7% P4258L (n=1), K2692E (n=1), V3318I (n=1), R1543P (n=1), V2214G (n=1)
FAS — by frequency SNV / small indel 11 / 193 5.7% — 1 / 1 5.7–5.7% G286E (n=2), M1? (n=2), X218_splice (n=1), K246* (n=1), Q26* (n=1)
DTX1 — by frequency SNV / small indel 10 / 193 5.18% — 1 / 1 5.18–5.18% Q81R (n=2), G58D (n=2), V70L (n=2), N21I (n=1), *35* (n=1)
BTG1 — by frequency SNV / small indel 9 / 193 4.66% — 1 / 1 4.66–4.66% L37M (n=2), S43N (n=2), F25S (n=1), L37Q (n=1), Q36H (n=1)
HLA-A — by frequency SNV / small indel 8 / 193 4.15% — 1 / 1 4.15–4.15% Q78* (n=2), L12Hfs*82 (n=1), Y31* (n=1), L150Q (n=1), L13Pfs*82 (n=1)
H1-5 — by frequency SNV / small indel 8 / 193 4.15% — 1 / 1 4.15–4.15% P203S (n=2), S92N (n=2), K172T (n=1), A131G (n=1), A177T (n=1)
H1-3 — by frequency SNV / small indel 8 / 193 4.15% — 1 / 1 4.15–4.15% A102T (n=1), K131R (n=1), G92D (n=1), A191T (n=1), S87N (n=1)
EPHA5 — by frequency SNV / small indel 8 / 193 4.15% — 1 / 1 4.15–4.15% T944M (n=1), C408R (n=1), A831S (n=1), A890V (n=1), P697Q (n=1)
ATP6AP1 — by frequency SNV / small indel 7 / 193 3.63% — 1 / 1 3.63–3.63% E346K (n=1), D284G (n=1), S335F (n=1), S305F (n=1), A3Rfs*76 (n=1)
ARID5B — by frequency SNV / small indel 7 / 193 3.63% — 1 / 1 3.63–3.63% F21L (n=1), S588Vfs*41 (n=1), S71F (n=1), W61* (n=1), X467_splice (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
MSK-IMPACT Heme, follicular lymphoma subset (2022) reference
MSK-IMPACT Heme Tumors (MSK, 2022)
heme_msk_impact_2022193 observed213 / 2383targeted panelIMPACT-HEME-400 (213)hg19SNV, small indel, amplification, deep deletion09

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
TNFRSF14deep deletion2219311.4%heme_msk_impact_2022heme_msk_impact_2022_cna
TNFAIP3deep deletion101935.18%heme_msk_impact_2022heme_msk_impact_2022_cna
FASdeep deletion61933.11%heme_msk_impact_2022heme_msk_impact_2022_cna
CREBBPdeep deletion41932.07%heme_msk_impact_2022heme_msk_impact_2022_cna
SOCS1deep deletion41932.07%heme_msk_impact_2022heme_msk_impact_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)
BCL234.72–34.72%heme_msk_impact_2022: 67/193 (34.72%)
MS4A1null–null%heme_msk_impact_2022: not assayed
CD19null–null%heme_msk_impact_2022: not assayed
EZH220.73–20.73%heme_msk_impact_2022: 40/193 (20.73%)
CREBBP70.98–70.98%heme_msk_impact_2022: 137/193 (70.98%)
KMT2D66.32–66.32%heme_msk_impact_2022: 128/193 (66.32%)
CD79B1.55–1.55%heme_msk_impact_2022: 3/193 (1.55%)
PIK3CDnull–null%heme_msk_impact_2022: not assayed
BTK6.22–6.22%heme_msk_impact_2022: 12/193 (6.22%)
CD22null–null%heme_msk_impact_2022: not assayed
TNFRSF1446.63–46.63%heme_msk_impact_2022: 90/193 (46.63%)
STAT620.21–20.21%heme_msk_impact_2022: 39/193 (20.21%)
FOXO118.13–18.13%heme_msk_impact_2022: 35/193 (18.13%)
SOCS115.54–15.54%heme_msk_impact_2022: 30/193 (15.54%)
H1-415.54–15.54%heme_msk_impact_2022: 30/193 (15.54%)
IRF815.03–15.03%heme_msk_impact_2022: 29/193 (15.03%)
ARID1A13.47–13.47%heme_msk_impact_2022: 26/193 (13.47%)
MEF2B11.92–11.92%heme_msk_impact_2022: 23/193 (11.92%)
EP30010.88–10.88%heme_msk_impact_2022: 21/193 (10.88%)
CARD1110.88–10.88%heme_msk_impact_2022: 21/193 (10.88%)
TNFAIP310.36–10.36%heme_msk_impact_2022: 20/193 (10.36%)
GNA139.84–9.84%heme_msk_impact_2022: 19/193 (9.84%)
TP539.33–9.33%heme_msk_impact_2022: 18/193 (9.33%)
RRAGC9.33–9.33%heme_msk_impact_2022: 18/193 (9.33%)
ATP6V1B28.29–8.29%heme_msk_impact_2022: 16/193 (8.29%)
BCR7.77–7.77%heme_msk_impact_2022: 15/193 (7.77%)
SGK17.25–7.25%heme_msk_impact_2022: 14/193 (7.25%)
PIM17.25–7.25%heme_msk_impact_2022: 14/193 (7.25%)
SRSF26.74–6.74%heme_msk_impact_2022: 13/193 (6.74%)
SETD1B6.74–6.74%heme_msk_impact_2022: 13/193 (6.74%)
H1-26.74–6.74%heme_msk_impact_2022: 13/193 (6.74%)
LTB6.22–6.22%heme_msk_impact_2022: 12/193 (6.22%)
CCND36.22–6.22%heme_msk_impact_2022: 12/193 (6.22%)
B2M6.22–6.22%heme_msk_impact_2022: 12/193 (6.22%)
ACTG16.22–6.22%heme_msk_impact_2022: 12/193 (6.22%)
FAT15.7–5.7%heme_msk_impact_2022: 11/193 (5.7%)
FAS5.7–5.7%heme_msk_impact_2022: 11/193 (5.7%)
DTX15.18–5.18%heme_msk_impact_2022: 10/193 (5.18%)
BTG14.66–4.66%heme_msk_impact_2022: 9/193 (4.66%)
HLA-A4.15–4.15%heme_msk_impact_2022: 8/193 (4.15%)
H1-54.15–4.15%heme_msk_impact_2022: 8/193 (4.15%)
H1-34.15–4.15%heme_msk_impact_2022: 8/193 (4.15%)
EPHA54.15–4.15%heme_msk_impact_2022: 8/193 (4.15%)
ATP6AP13.63–3.63%heme_msk_impact_2022: 7/193 (3.63%)
ARID5B3.63–3.63%heme_msk_impact_2022: 7/193 (3.63%)

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/follicular-lymphoma.json.

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