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Diffuse large B-cell lymphoma mutation landscape

How often each gene is altered in diffuse large b-cell 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 2026-09-18 · Reference cohort: dlbcl_duke_2017 · JSON: /disease/diffuse-large-b-cell-lymphoma/mutations.json · Back to the briefing

Answer block

In Diffuse Large B-Cell Lymphoma (Duke, Cell 2017) (1001 sequenced patients, exome or genome), the most frequently altered of the 46 genes shown are KMT2D 24.68%, MYD88 17.18%, PIM1 14.59%, CREBBP 11.49%, H1-4 10.49%. 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 (MS4A1, CD19): 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%.

Alterationdlbcl_duke_2017
1001 pts · exome or genome
dlbcl_dfci_2018
135 pts · exome or genome
MS4A1 SNV / small indel0%0%
CD19 SNV / small indel0%1.48%2/135
CD79B SNV / small indel4.7%47/100114.81%20/135
BCL2 SNV / small indel9.69%97/100122.22%30/135
BCL6 SNV / small indel4.5%45/10018.89%12/135
MYC SNV / small indel4.5%45/10016.67%9/135
EZH2 SNV / small indel6.09%61/10016.67%9/135
MYD88 SNV / small indel17.18%172/100116.3%22/135
CREBBP SNV / small indel11.49%115/100120.74%28/135
KMT2D SNV / small indel24.68%247/100125.93%35/135
TP53 SNV / small indel9.29%93/100122.96%31/135
BTK SNV / small indel2.8%28/10012.96%4/135
PIM1 SNV / small indel14.59%146/100122.96%31/135
H1-4 SNV / small indel10.49%105/100110.37%14/135
SPEN SNV / small indel10.09%101/10014.44%6/135
ARID1A SNV / small indel9.59%96/10012.96%4/135
SOCS1 SNV / small indel9.19%92/10013.7%5/135
CARD11 SNV / small indel8.89%89/100113.33%18/135
SETD1B SNV / small indel8.29%83/10010%
GNA13 SNV / small indel8.29%83/10018.89%12/135
ARID1B SNV / small indel8.29%83/10012.22%3/135
TNFRSF14 SNV / small indel7.79%78/100112.59%17/135
DUSP2 SNV / small indel7.59%76/10012.96%4/135
SMARCA4 SNV / small indel7.49%75/10010.74%1/135
MGA SNV / small indel7.49%75/10010.74%1/135
NOTCH2 SNV / small indel7.29%73/10015.93%8/135
ATM SNV / small indel7.19%72/10012.96%4/135
SGK1 SNV / small indel6.69%67/100114.07%19/135
KLHL6 SNV / small indel6.69%67/10018.89%12/135
MTOR SNV / small indel6.39%64/10012.22%3/135
IRF8 SNV / small indel6.39%64/10016.67%9/135
BIRC6 SNV / small indel6.39%64/10015.19%7/135
PIK3CD SNV / small indel6.29%63/10012.96%4/135
TET2 SNV / small indel6.19%62/10012.22%3/135
SETD2 SNV / small indel6.19%62/10012.22%3/135
BTG2 SNV / small indel5.79%58/10012.96%4/135
EP300 SNV / small indel5.69%57/10016.67%9/135
KMT2C SNV / small indel5.59%56/10013.7%5/135
CD70 SNV / small indel5.59%56/10019.63%13/135
B2M SNV / small indel5.59%56/10015.93%8/135
MEF2B SNV / small indel5.49%55/10018.89%12/135
TBL1XR1 SNV / small indel5.29%53/10019.63%13/135
STAT6 SNV / small indel5.29%53/10011.48%2/135
KLHL14 SNV / small indel5.19%52/10015.19%7/135
CHD8 SNV / small indel5.0%50/10014.44%6/135
INO80 SNV / small indel4.9%49/10012.22%3/135

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

Key findings

KMT2D is mutated in 247 of 1001 patients in Diffuse Large B-Cell Lymphoma (Duke, Cell 2017).
Numerator: 247 · Denominator: 1001 · Frequency: 24.68% · Observed in 2 cohorts · Confidence: moderate · Source: dlbcl_duke_2017 · Retrieved: 2026-09-18

MYD88 is mutated in 172 of 1001 patients in Diffuse Large B-Cell Lymphoma (Duke, Cell 2017).
Numerator: 172 · Denominator: 1001 · Frequency: 17.18% · Observed in 2 cohorts · Confidence: moderate · Source: dlbcl_duke_2017 · Retrieved: 2026-09-18

PIM1 is mutated in 146 of 1001 patients in Diffuse Large B-Cell Lymphoma (Duke, Cell 2017).
Numerator: 146 · Denominator: 1001 · Frequency: 14.59% · Observed in 2 cohorts · Confidence: moderate · Source: dlbcl_duke_2017 · Retrieved: 2026-09-18

Gene table — reference cohort

Headline values are from the reference cohort, dlbcl_duke_2017; 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
MS4A1 — curated target SNV / small indel 0 / 1001 0.0% — 0 / 2 0.0–0.0% none recurrent
CD19 — curated target SNV / small indel 0 / 1001 0.0% — 1 / 2 0.0–1.48% none recurrent
CD79B — curated target SNV / small indel 47 / 1001 4.7% — 2 / 2 4.7–14.81% Y197S (n=18), Y197H (n=15), A55V (n=2), I162L (n=2), I202T (n=2)
BCL2 — curated target SNV / small indel 97 / 1001 9.69% — 2 / 2 9.69–22.22% A131V (n=14), A60V (n=12), P59S (n=9), R129H (n=7), L86F (n=5)
BCL6 — curated target SNV / small indel 45 / 1001 4.5% — 2 / 2 4.5–8.89% A587G (n=5), A587T (n=4), R678H (n=2), T48M (n=2), P629L (n=2)
MYC — curated target SNV / small indel 45 / 1001 4.5% — 2 / 2 4.5–6.67% L164V (n=6), E54D (n=4), Q50L (n=2), S107N (n=2), S129N (n=2)
EZH2 FDA biomarker2020 · 1 drug curated target SNV / small indel 61 / 1001 6.09% — 2 / 2 6.09–6.67% Y646N (n=33), Y646F (n=24), V707G (n=1), T144I (n=1), C647S (n=1)
MYD88 — curated target SNV / small indel 172 / 1001 17.18% — 2 / 2 16.3–17.18% L265P (n=110), S243N (n=17), S219C (n=13), M232T (n=8), V217F (n=5)
CREBBP — curated target SNV / small indel 115 / 1001 11.49% — 2 / 2 11.49–20.74% R1446H (n=6), R1446C (n=5), P1943L (n=4), Y1503F (n=4), Y1503D (n=3)
KMT2D — curated target SNV / small indel 247 / 1001 24.68% — 2 / 2 24.68–25.93% S4907L (n=6), R5154Q (n=4), R2915* (n=4), R2072C (n=4), R4282* (n=4)
TP53 — curated target SNV / small indel 93 / 1001 9.29% — 2 / 2 9.29–22.96% R175H (n=10), R248Q (n=9), G245D (n=4), G245S (n=4), N239D (n=3)
BTK — curated target SNV / small indel 28 / 1001 2.8% — 2 / 2 2.8–2.96% R236Q (n=3), R332C (n=3), R288W (n=2), N530Y (n=2), P642S (n=1)
PIM1 — by frequency SNV / small indel 146 / 1001 14.59% — 2 / 2 14.59–22.96% E135K (n=22), L2F (n=19), S97N (n=18), G28D (n=17), L184F (n=16)
H1-4 — by frequency SNV / small indel 105 / 1001 10.49% — 2 / 2 10.37–10.49% A164V (n=11), A120T (n=11), A65T (n=7), S104F (n=7), P118S (n=5)
SPEN — by frequency SNV / small indel 101 / 1001 10.09% — 2 / 2 4.44–10.09% R243Q (n=5), G3378S (n=5), R637* (n=4), R2081* (n=4), G3375S (n=3)
ARID1A — by frequency SNV / small indel 96 / 1001 9.59% — 2 / 2 2.96–9.59% G85D (n=5), R1721* (n=4), S357N (n=3), V5I (n=3), R693* (n=3)
SOCS1 — by frequency SNV / small indel 92 / 1001 9.19% — 2 / 2 3.7–9.19% S125T (n=12), S116N (n=7), H129Q (n=4), A16T (n=4), P19S (n=4)
CARD11 — by frequency SNV / small indel 89 / 1001 8.89% — 2 / 2 8.89–13.33% D230N (n=8), L251P (n=6), R337Q (n=5), C49Y (n=4), R967C (n=4)
SETD1B — by frequency SNV / small indel 83 / 1001 8.29% — 1 / 2 0.0–8.29% V1907I (n=4), P749L (n=4), A1858T (n=3), A654T (n=3), A804T (n=3)
GNA13 — by frequency SNV / small indel 83 / 1001 8.29% — 2 / 2 8.29–8.89% G60D (n=5), Q27* (n=4), Q28* (n=4), F252L (n=2), K61M (n=2)
ARID1B — by frequency SNV / small indel 83 / 1001 8.29% — 2 / 2 2.22–8.29% A44T (n=5), A43V (n=3), S30N (n=3), R1102* (n=3), M429V (n=3)
TNFRSF14 — by frequency SNV / small indel 78 / 1001 7.79% — 2 / 2 7.79–12.59% W12* (n=9), M1? (n=4), P146L (n=4), C127R (n=3), N173S (n=3)
DUSP2 — by frequency SNV / small indel 76 / 1001 7.59% — 2 / 2 2.96–7.59% G134D (n=6), P152S (n=5), C143Y (n=5), G131D (n=4), R41H (n=4)
SMARCA4 — by frequency SNV / small indel 75 / 1001 7.49% — 2 / 2 0.74–7.49% R425Q (n=5), G239S (n=4), D1381N (n=4), G231S (n=4), D1177N (n=3)
MGA — by frequency SNV / small indel 75 / 1001 7.49% — 2 / 2 0.74–7.49% R2425C (n=5), R971Q (n=5), R984C (n=4), S841N (n=3), R1467H (n=3)
NOTCH2 — by frequency SNV / small indel 73 / 1001 7.29% — 2 / 2 5.93–7.29% R2400* (n=12), A1867V (n=4), E723K (n=4), S1804L (n=3), R1838* (n=3)
ATM FDA biomarker2020 · 1 drug by frequency SNV / small indel 72 / 1001 7.19% — 2 / 2 2.96–7.19% N429S (n=13), A1309T (n=5), R337H (n=4), R720C (n=3), V1468I (n=3)
SGK1 — by frequency SNV / small indel 67 / 1001 6.69% — 2 / 2 6.69–14.07% A121V (n=8), H146Y (n=7), A143V (n=6), A228G (n=3), Q125* (n=2)
KLHL6 — by frequency SNV / small indel 67 / 1001 6.69% — 2 / 2 6.69–8.89% E568K (n=11), L65P (n=10), L90F (n=5), D442N (n=3), V602I (n=3)
MTOR — by frequency SNV / small indel 64 / 1001 6.39% — 2 / 2 2.22–6.39% E2536A (n=17), R2348C (n=5), R604C (n=4), T588M (n=3), R619H (n=2)
IRF8 — by frequency SNV / small indel 64 / 1001 6.39% — 2 / 2 6.39–6.67% Y23H (n=6), T80A (n=6), A257T (n=4), K66R (n=4), V287M (n=3)
BIRC6 — by frequency SNV / small indel 64 / 1001 6.39% — 2 / 2 5.19–6.39% T4672M (n=4), P1680S (n=2), H3668Q (n=2), N3709S (n=2), Q3184* (n=2)
PIK3CD — by frequency SNV / small indel 63 / 1001 6.29% — 2 / 2 2.96–6.29% R38C (n=22), E1021K (n=9), A849T (n=4), G245S (n=4), E200K (n=3)
TET2 — by frequency SNV / small indel 62 / 1001 6.19% — 2 / 2 2.22–6.19% N767D (n=2), M600V (n=2), M611K (n=2), Q1903* (n=2), H1817N (n=2)
SETD2 — by frequency SNV / small indel 62 / 1001 6.19% — 2 / 2 2.22–6.19% V768L (n=4), E639K (n=3), T928R (n=3), M1889T (n=3), R329W (n=3)
BTG2 — by frequency SNV / small indel 58 / 1001 5.79% — 2 / 2 2.96–5.79% G28D (n=9), L10F (n=6), L35F (n=5), S31N (n=5), R34K (n=3)
EP300 — by frequency SNV / small indel 57 / 1001 5.69% — 2 / 2 5.69–6.67% L415P (n=5), G194S (n=3), R1405H (n=3), Y1467D (n=2), S848N (n=2)
KMT2C — by frequency SNV / small indel 56 / 1001 5.59% — 2 / 2 3.7–5.59% C4883R (n=4), A2223T (n=3), D2092V (n=3), R3252H (n=3), C3460G (n=3)
CD70 — by frequency SNV / small indel 56 / 1001 5.59% — 2 / 2 5.59–9.63% Q47* (n=6), G66R (n=6), R83H (n=5), R157H (n=3), Q61* (n=3)
B2M — by frequency SNV / small indel 56 / 1001 5.59% — 2 / 2 5.59–5.93% M1? (n=16), L7* (n=7), L10R (n=3), L12R (n=3), L59* (n=2)
MEF2B — by frequency SNV / small indel 55 / 1001 5.49% — 2 / 2 5.49–8.89% P318L (n=4), E77K (n=3), K4E (n=3), T20M (n=2), P325L (n=2)
TBL1XR1 — by frequency SNV / small indel 53 / 1001 5.29% — 2 / 2 5.29–9.63% Y446S (n=5), A295T (n=4), R513Q (n=3), Y395C (n=2), G267C (n=2)
STAT6 — by frequency SNV / small indel 53 / 1001 5.29% — 2 / 2 1.48–5.29% D419G (n=9), N417Y (n=5), E377K (n=3), D419N (n=3), I700T (n=2)
KLHL14 — by frequency SNV / small indel 52 / 1001 5.19% — 2 / 2 5.19–5.19% W245* (n=6), L139F (n=5), R560* (n=3), L177F (n=2), S242P (n=2)
CHD8 — by frequency SNV / small indel 50 / 1001 5.0% — 2 / 2 4.44–5.0% R1797Q (n=4), R912C (n=4), R1580Q (n=3), R938C (n=3), D1870N (n=3)
INO80 — by frequency SNV / small indel 49 / 1001 4.9% — 2 / 2 2.22–4.9% R1212C (n=5), R1281W (n=4), R1212H (n=3), R1112W (n=3), A1461T (n=3)

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
Diffuse Large B-Cell Lymphoma (Duke, Cell 2017) reference
Diffuse Large B-Cell Lymphoma (Duke, Cell 2017)
dlbcl_duke_20171001 observed1001 / 1001exome or genomeWES (1001)hg19SNV, small indel06
Diffuse Large B cell Lymphoma (DFCI, Nat Med 2018)
Diffuse Large B cell Lymphoma (DFCI, Nat Med 2018)
dlbcl_dfci_2018135 observed135 / 135exome or genomeWES (135)hg19SNV, small indel, structural variant (profile present, not read)172

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)
MS4A10.0–0.0%dlbcl_duke_2017: 0/1001 (0.0%) · dlbcl_dfci_2018: 0/135 (0.0%)
CD190.0–1.48%dlbcl_duke_2017: 0/1001 (0.0%) · dlbcl_dfci_2018: 2/135 (1.48%)
CD79B4.7–14.81%dlbcl_duke_2017: 47/1001 (4.7%) · dlbcl_dfci_2018: 20/135 (14.81%)
BCL29.69–22.22%dlbcl_duke_2017: 97/1001 (9.69%) · dlbcl_dfci_2018: 30/135 (22.22%)
BCL64.5–8.89%dlbcl_duke_2017: 45/1001 (4.5%) · dlbcl_dfci_2018: 12/135 (8.89%)
MYC4.5–6.67%dlbcl_duke_2017: 45/1001 (4.5%) · dlbcl_dfci_2018: 9/135 (6.67%)
EZH26.09–6.67%dlbcl_duke_2017: 61/1001 (6.09%) · dlbcl_dfci_2018: 9/135 (6.67%)
MYD8816.3–17.18%dlbcl_duke_2017: 172/1001 (17.18%) · dlbcl_dfci_2018: 22/135 (16.3%)
CREBBP11.49–20.74%dlbcl_duke_2017: 115/1001 (11.49%) · dlbcl_dfci_2018: 28/135 (20.74%)
KMT2D24.68–25.93%dlbcl_duke_2017: 247/1001 (24.68%) · dlbcl_dfci_2018: 35/135 (25.93%)
TP539.29–22.96%dlbcl_duke_2017: 93/1001 (9.29%) · dlbcl_dfci_2018: 31/135 (22.96%)
BTK2.8–2.96%dlbcl_duke_2017: 28/1001 (2.8%) · dlbcl_dfci_2018: 4/135 (2.96%)
PIM114.59–22.96%dlbcl_duke_2017: 146/1001 (14.59%) · dlbcl_dfci_2018: 31/135 (22.96%)
H1-410.37–10.49%dlbcl_duke_2017: 105/1001 (10.49%) · dlbcl_dfci_2018: 14/135 (10.37%)
SPEN4.44–10.09%dlbcl_duke_2017: 101/1001 (10.09%) · dlbcl_dfci_2018: 6/135 (4.44%)
ARID1A2.96–9.59%dlbcl_duke_2017: 96/1001 (9.59%) · dlbcl_dfci_2018: 4/135 (2.96%)
SOCS13.7–9.19%dlbcl_duke_2017: 92/1001 (9.19%) · dlbcl_dfci_2018: 5/135 (3.7%)
CARD118.89–13.33%dlbcl_duke_2017: 89/1001 (8.89%) · dlbcl_dfci_2018: 18/135 (13.33%)
SETD1B0.0–8.29%dlbcl_duke_2017: 83/1001 (8.29%) · dlbcl_dfci_2018: 0/135 (0.0%)
GNA138.29–8.89%dlbcl_duke_2017: 83/1001 (8.29%) · dlbcl_dfci_2018: 12/135 (8.89%)
ARID1B2.22–8.29%dlbcl_duke_2017: 83/1001 (8.29%) · dlbcl_dfci_2018: 3/135 (2.22%)
TNFRSF147.79–12.59%dlbcl_duke_2017: 78/1001 (7.79%) · dlbcl_dfci_2018: 17/135 (12.59%)
DUSP22.96–7.59%dlbcl_duke_2017: 76/1001 (7.59%) · dlbcl_dfci_2018: 4/135 (2.96%)
SMARCA40.74–7.49%dlbcl_duke_2017: 75/1001 (7.49%) · dlbcl_dfci_2018: 1/135 (0.74%)
MGA0.74–7.49%dlbcl_duke_2017: 75/1001 (7.49%) · dlbcl_dfci_2018: 1/135 (0.74%)
NOTCH25.93–7.29%dlbcl_duke_2017: 73/1001 (7.29%) · dlbcl_dfci_2018: 8/135 (5.93%)
ATM2.96–7.19%dlbcl_duke_2017: 72/1001 (7.19%) · dlbcl_dfci_2018: 4/135 (2.96%)
SGK16.69–14.07%dlbcl_duke_2017: 67/1001 (6.69%) · dlbcl_dfci_2018: 19/135 (14.07%)
KLHL66.69–8.89%dlbcl_duke_2017: 67/1001 (6.69%) · dlbcl_dfci_2018: 12/135 (8.89%)
MTOR2.22–6.39%dlbcl_duke_2017: 64/1001 (6.39%) · dlbcl_dfci_2018: 3/135 (2.22%)
IRF86.39–6.67%dlbcl_duke_2017: 64/1001 (6.39%) · dlbcl_dfci_2018: 9/135 (6.67%)
BIRC65.19–6.39%dlbcl_duke_2017: 64/1001 (6.39%) · dlbcl_dfci_2018: 7/135 (5.19%)
PIK3CD2.96–6.29%dlbcl_duke_2017: 63/1001 (6.29%) · dlbcl_dfci_2018: 4/135 (2.96%)
TET22.22–6.19%dlbcl_duke_2017: 62/1001 (6.19%) · dlbcl_dfci_2018: 3/135 (2.22%)
SETD22.22–6.19%dlbcl_duke_2017: 62/1001 (6.19%) · dlbcl_dfci_2018: 3/135 (2.22%)
BTG22.96–5.79%dlbcl_duke_2017: 58/1001 (5.79%) · dlbcl_dfci_2018: 4/135 (2.96%)
EP3005.69–6.67%dlbcl_duke_2017: 57/1001 (5.69%) · dlbcl_dfci_2018: 9/135 (6.67%)
KMT2C3.7–5.59%dlbcl_duke_2017: 56/1001 (5.59%) · dlbcl_dfci_2018: 5/135 (3.7%)
CD705.59–9.63%dlbcl_duke_2017: 56/1001 (5.59%) · dlbcl_dfci_2018: 13/135 (9.63%)
B2M5.59–5.93%dlbcl_duke_2017: 56/1001 (5.59%) · dlbcl_dfci_2018: 8/135 (5.93%)
MEF2B5.49–8.89%dlbcl_duke_2017: 55/1001 (5.49%) · dlbcl_dfci_2018: 12/135 (8.89%)
TBL1XR15.29–9.63%dlbcl_duke_2017: 53/1001 (5.29%) · dlbcl_dfci_2018: 13/135 (9.63%)
STAT61.48–5.29%dlbcl_duke_2017: 53/1001 (5.29%) · dlbcl_dfci_2018: 2/135 (1.48%)
KLHL145.19–5.19%dlbcl_duke_2017: 52/1001 (5.19%) · dlbcl_dfci_2018: 7/135 (5.19%)
CHD84.44–5.0%dlbcl_duke_2017: 50/1001 (5.0%) · dlbcl_dfci_2018: 6/135 (4.44%)
INO802.22–4.9%dlbcl_duke_2017: 49/1001 (4.9%) · dlbcl_dfci_2018: 3/135 (2.22%)

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/diffuse-large-b-cell-lymphoma.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.