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Disease intelligence · mutation landscape

Anal cancer mutation landscape

How often each gene is altered in anal 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 2026-09-26 · Reference cohort: msk_impact_50k_2026 · JSON: /disease/anal-cancer/mutations.json · Back to the briefing

Answer block

In MSK-IMPACT 50K, anal carcinoma subset (2026) (139 sequenced patients, targeted panel), the most frequently altered of the 46 genes shown are PIK3CA 29.5%, KMT2D 24.46%, SOX2 18.71% (amplification), FBXW7 13.67%, EP300 12.95%. 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 (PDCD1, TERT): 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%.

Alterationmsk_impact_50k_2026
139 pts · targeted panel
msk_impact_2017
31 pts · targeted panel
CD274 SNV / small indel0%0%
CD274 amplification2.16%3/1393.23%1/31
PDCD1 SNV / small indel0%0%
PIK3CA SNV / small indel29.5%41/13929.03%9/31
PIK3CA amplification17.27%24/1396.45%2/31
CDKN2A SNV / small indel5.04%7/1390%
TP53 SNV / small indel10.07%14/1399.68%3/31
EGFR SNV / small indel2.16%3/1393.23%1/31
KMT2D SNV / small indel24.46%34/13912.9%4/31
FBXW7 SNV / small indel13.67%19/1393.23%1/31
PTEN SNV / small indel10.07%14/13912.9%4/31
PTEN deep deletion3.6%5/1393.23%1/31
SOX2 SNV / small indel0.72%1/1390%
SOX2 amplification18.71%26/1399.68%3/31
TERT SNV / small indel0.72%1/1393.23%1/31
MYC SNV / small indel2.16%3/1390%
MYC amplification2.16%3/1390%
EP300 SNV / small indel12.95%18/13916.13%5/31
KMT2C SNV / small indel10.79%15/1393.23%1/31
CREBBP SNV / small indel10.07%14/1399.68%3/31
STK11 SNV / small indel9.35%13/1396.45%2/31
STK11 deep deletion4.32%6/1390%
ZFHX3 SNV / small indel9.45%12/1275.26%1/19
NOTCH1 SNV / small indel8.63%12/1393.23%1/31
FAT1 SNV / small indel8.63%12/1396.45%2/31
FAT1 deep deletion2.88%4/1390%
NOTCH3 SNV / small indel6.47%9/1390%
NOTCH3 deep deletion0.72%1/1393.23%1/31
KEAP1 SNV / small indel6.47%9/1393.23%1/31
PTPRT SNV / small indel5.76%8/1396.45%2/31
NOTCH4 SNV / small indel5.76%8/1393.23%1/31
FANCA SNV / small indel5.76%8/1393.23%1/31
BRCA1 SNV / small indel5.76%8/1390%
TGFBR2 SNV / small indel5.04%7/1396.45%2/31
TGFBR2 deep deletion4.32%6/1393.23%1/31
TET2 SNV / small indel5.04%7/1390%
PIK3R1 SNV / small indel5.04%7/1393.23%1/31
KMT2A SNV / small indel5.04%7/1396.45%2/31
HLA-B SNV / small indel7.0%7/100·
ERBB2 SNV / small indel5.04%7/1393.23%1/31
ERBB2 deep deletion0.72%1/1393.23%1/31
CASP8 SNV / small indel5.04%7/1393.23%1/31
CASP8 deep deletion0.72%1/1393.23%1/31
APC SNV / small indel5.04%7/1393.23%1/31
STAG2 SNV / small indel4.32%6/1396.45%2/31
RICTOR SNV / small indel4.32%6/1390%
RB1 SNV / small indel4.32%6/1390%
PTPRD SNV / small indel4.32%6/1396.45%2/31
PIK3CG SNV / small indel4.32%6/1393.23%1/31
NSD1 SNV / small indel4.32%6/1390%
NOTCH2 SNV / small indel4.32%6/1396.45%2/31
NFE2L2 SNV / small indel4.32%6/1396.45%2/31
KRAS SNV / small indel4.32%6/1393.23%1/31
KDM6A SNV / small indel4.32%6/1393.23%1/31
KDM6A deep deletion1.44%2/1393.23%1/31
HLA-A SNV / small indel4.72%6/1275.26%1/19
CDK12 SNV / small indel4.32%6/1390%
BRCA2 SNV / small indel4.32%6/1393.23%1/31
BRCA2 amplification2.16%3/1390%

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

Key findings

PIK3CA is mutated in 41 of 139 patients in MSK-IMPACT 50K, anal carcinoma subset (2026).
Numerator: 41 · Denominator: 139 · Frequency: 29.5% · Observed in 2 cohorts · Confidence: low · Source: msk_impact_50k_2026 · Retrieved: 2026-09-26

KMT2D is mutated in 34 of 139 patients in MSK-IMPACT 50K, anal carcinoma subset (2026).
Numerator: 34 · Denominator: 139 · Frequency: 24.46% · Observed in 2 cohorts · Confidence: low · Source: msk_impact_50k_2026 · Retrieved: 2026-09-26

SOX2 is amplified in 26 of 139 patients in MSK-IMPACT 50K, anal carcinoma subset (2026).
Numerator: 26 · Denominator: 139 · Frequency: 18.71% · Observed in 1 cohorts · Confidence: low · Source: msk_impact_50k_2026 · Retrieved: 2026-09-26

Gene table — reference cohort

Headline values are from the reference cohort, msk_impact_50k_2026; 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
CD274 — curated target amplification 3 / 139 2.16% mutation 0.0% — 0 / 2 0.0–0.0% none recurrent
PDCD1 — curated target deep deletion 1 / 139 0.72% mutation 0.0% — 0 / 2 0.0–0.0% none recurrent
PIK3CA FDA biomarker2019 · 1 drug curated target SNV / small indel 41 / 139 29.5% — 2 / 2 29.03–29.5% E545K (n=19), E542K (n=12), H1047R (n=3), E726K (n=3), K111N (n=2)
CDKN2A — curated target SNV / small indel 7 / 139 5.04% — 1 / 2 0.0–5.04% R80* (n=4), R58* (n=2), X153_splice (n=1), R21M (n=1)
TP53 — curated target SNV / small indel 14 / 139 10.07% — 2 / 2 9.68–10.07% E285K (n=3), R342* (n=3), R248W (n=2), R248Q (n=2), R273C (n=1)
EGFR FDA biomarker2004 · 7 drugs curated target SNV / small indel 3 / 139 2.16% — 2 / 2 2.16–3.23% Q32Hfs*46 (n=1), X80_splice (n=1), R149W (n=1), F712L (n=1), L692V (n=1)
KMT2D — curated target SNV / small indel 34 / 139 24.46% — 2 / 2 12.9–24.46% L1461Tfs*30 (n=3), W5395* (n=2), Q3741_Q3745del (n=2), R2830* (n=1), Q4045* (n=1)
FBXW7 — curated target SNV / small indel 19 / 139 13.67% — 2 / 2 3.23–13.67% R505G (n=4), R465C (n=2), S398Y (n=1), W365S (n=1), S25* (n=1)
PTEN — curated target SNV / small indel 14 / 139 10.07% — 2 / 2 10.07–12.9% R130* (n=2), R335* (n=2), R130Q (n=1), D107Y (n=1), V217F (n=1)
SOX2 — curated target amplification 26 / 139 18.71% mutation 0.72% — 1 / 2 0.0–0.72% E282K (n=1)
TERT — curated target amplification 2 / 139 1.44% mutation 0.72% — 2 / 2 0.72–3.23% T714M (n=1)
MYC — curated target SNV / small indel 3 / 139 2.16% — 1 / 2 0.0–2.16% S161L (n=2), N19D (n=1)
EP300 — by frequency SNV / small indel 18 / 139 12.95% — 2 / 2 12.95–16.13% D1399N (n=4), D1218N (n=1), G1109R (n=1), G1443A (n=1), V1512F (n=1)
KMT2C — by frequency SNV / small indel 15 / 139 10.79% — 2 / 2 3.23–10.79% R56* (n=1), X197_splice (n=1), L2036V (n=1), S2053C (n=1), S2059* (n=1)
CREBBP — by frequency SNV / small indel 14 / 139 10.07% — 2 / 2 9.68–10.07% R1446H (n=2), D1435N (n=2), S1172Qfs*7 (n=1), Q503* (n=1), R1169C (n=1)
STK11 — by frequency SNV / small indel 13 / 139 9.35% — 2 / 2 6.45–9.35% Q100* (n=2), S216F (n=2), X155_splice (n=1), E121K (n=1), E98K (n=1)
ZFHX3 — by frequency SNV / small indel 12 / 127 9.45% — 2 / 2 5.26–9.45% A2433V (n=1), P1348L (n=1), S3601L (n=1), Q2057* (n=1), E2412K (n=1)
NOTCH1 — by frequency SNV / small indel 12 / 139 8.63% — 2 / 2 3.23–8.63% S1511T (n=1), D1348Efs*97 (n=1), E360* (n=1), G394V (n=1), D1246Y (n=1)
FAT1 — by frequency SNV / small indel 12 / 139 8.63% — 2 / 2 6.45–8.63% A1419S (n=1), R1262* (n=1), G2221A (n=1), A1470V (n=1), P4055S (n=1)
NOTCH3 — by frequency SNV / small indel 9 / 139 6.47% — 1 / 2 0.0–6.47% R1510C (n=1), C1405G (n=1), L33del (n=1), A88T (n=1), M1722_D1723delinsIY (n=1)
KEAP1 — by frequency SNV / small indel 9 / 139 6.47% — 2 / 2 3.23–6.47% C368Y (n=1), R116W (n=1), K303N (n=1), R470S (n=1), R362Q (n=1)
PTPRT — by frequency SNV / small indel 8 / 139 5.76% — 2 / 2 5.76–6.45% D1424E (n=1), V1143F (n=1), L708F (n=1), F1302L (n=1), R546Q (n=1)
NOTCH4 — by frequency SNV / small indel 8 / 139 5.76% — 2 / 2 3.23–5.76% E1977K (n=2), P1970Y (n=1), P958Qfs*90 (n=1), G1998V (n=1), D1947V (n=1)
FANCA — by frequency SNV / small indel 8 / 139 5.76% — 2 / 2 3.23–5.76% P806L (n=1), R52Q (n=1), E712* (n=1), A1434T (n=1), Q549* (n=1)
BRCA1 FDA biomarker2014 · 4 drugs by frequency SNV / small indel 8 / 139 5.76% — 1 / 2 0.0–5.76% S1796L (n=1), G911A (n=1), E1794Q (n=1), V8D (n=1), S1580F (n=1)
TGFBR2 — by frequency SNV / small indel 7 / 139 5.04% — 2 / 2 5.04–6.45% R497* (n=2), R460H (n=1), E526K (n=1), S69R (n=1), M1? (n=1)
TET2 — by frequency SNV / small indel 7 / 139 5.04% — 1 / 2 0.0–5.04% R1383K (n=1), R1966H (n=1), Q1632E (n=1), K700* (n=1), E1477* (n=1)
PIK3R1 — by frequency SNV / small indel 7 / 139 5.04% — 2 / 2 3.23–5.04% S709_L710del (n=1), D578Pfs*23 (n=1), T701Lfs*39 (n=1), E555* (n=1), Q435_D440del (n=1)
KMT2A — by frequency SNV / small indel 7 / 139 5.04% — 2 / 2 5.04–6.45% S1232C (n=1), G2321R (n=1), D1972Y (n=1), I233M (n=1), S261F (n=1)
HLA-B — by frequency SNV / small indel 7 / 100 7.0% — 1 / 2 7.0–7.0% D61H (n=1), E113* (n=1), F60L (n=1), D262N (n=1), M1? (n=1)
ERBB2 FDA biomarker1998 · 9 drugs by frequency SNV / small indel 7 / 139 5.04% — 2 / 2 3.23–5.04% S310F (n=2), R678Q (n=1), I767M (n=1), S1078Y (n=1), D1012Y (n=1)
CASP8 — by frequency SNV / small indel 7 / 139 5.04% — 2 / 2 3.23–5.04% P291R (n=1), R127P (n=1), Q482* (n=1), R494* (n=1), Q398* (n=1)
APC — by frequency SNV / small indel 7 / 139 5.04% — 2 / 2 3.23–5.04% L572F (n=1), D605N (n=1), K2051Efs*9 (n=1), V2659M (n=1), R2204* (n=1)
STAG2 — by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 4.32–6.45% L264I (n=1), A533S (n=1), L716F (n=1), P160S (n=1), M796I (n=1)
RICTOR — by frequency SNV / small indel 6 / 139 4.32% — 1 / 2 0.0–4.32% R1609C (n=1), S1373F (n=1), D247H (n=1), R293* (n=1), A3T (n=1)
RB1 — by frequency SNV / small indel 6 / 139 4.32% — 1 / 2 0.0–4.32% R251* (n=1), R579* (n=1), D85Efs*25 (n=1), Q217* (n=1), S576* (n=1)
PTPRD — by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 4.32–6.45% R232H (n=1), V720I (n=1), E1459K (n=1), D76N (n=1), Q67* (n=1)
PIK3CG — by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 3.23–4.32% E781K (n=1), T380K (n=1), R226C (n=1), A57V (n=1), V759I (n=1)
NSD1 — by frequency SNV / small indel 6 / 139 4.32% — 1 / 2 0.0–4.32% D2298H (n=1), E2284Q (n=1), F1947L (n=1), Q1856* (n=1), Q1221* (n=1)
NOTCH2 — by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 4.32–6.45% G598R (n=2), S1660L (n=1), C691Sfs*51 (n=1), C335R (n=1), D682G (n=1)
NFE2L2 — by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 4.32–6.45% D29Y (n=1), G31R (n=1), Q26H (n=1), L30F (n=1), L562Rfs*8 (n=1)
KRAS FDA, wild-type2009 · 3 drugs by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 3.23–4.32% G12D (n=2), G12C (n=2), G12A (n=1), G13C (n=1), G13D (n=1)
KDM6A — by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 3.23–4.32% Q301* (n=1), S531L (n=1), Q641* (n=1), R519* (n=1), L83Nfs*5 (n=1)
HLA-A — by frequency SNV / small indel 6 / 127 4.72% — 2 / 2 4.72–5.26% L10Vfs*90 (n=1), E113* (n=1), X115_splice (n=1), G124D (n=1), R7L (n=1)
CDK12 FDA biomarker2020 · 1 drug by frequency SNV / small indel 6 / 139 4.32% — 1 / 2 0.0–4.32% Q547* (n=1), S332F (n=1), S283L (n=1), W719* (n=1), S826C (n=1)
BRCA2 FDA biomarker2014 · 1 drug by frequency SNV / small indel 6 / 139 4.32% — 2 / 2 3.23–4.32% X2659_splice (n=1), S270L (n=1), I1556M (n=1), S3245L (n=1), T3165N (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 50K, anal carcinoma subset (2026) reference
MSK-IMPACT 50K Clinical Sequencing Cohort (MSK, Cancer Cell 2026)
msk_impact_50k_2026139 observed143 / 54331targeted panelIMPACT468 (71), IMPACT505 (31), IMPACT410 (29), IMPACT341 (12)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)06
MSK-IMPACT 2017, anal carcinoma subset
MSK-IMPACT Clinical Sequencing Cohort (MSK, Nat Med 2017)
msk_impact_201731 observed32 / 10945targeted panelIMPACT410 (20), IMPACT341 (12)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)03.0

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
SOX2amplification2613918.71%msk_impact_50k_2026msk_impact_50k_2026_gistic
PIK3CAamplification2413917.27%msk_impact_50k_2026msk_impact_50k_2026_gistic
SOX2amplification3319.68%msk_impact_2017msk_impact_2017_cna
PIK3CAamplification2316.45%msk_impact_2017msk_impact_2017_cna
STK11deep deletion61394.32%msk_impact_50k_2026msk_impact_50k_2026_gistic
TGFBR2deep deletion61394.32%msk_impact_50k_2026msk_impact_50k_2026_gistic
PTENdeep deletion51393.6%msk_impact_50k_2026msk_impact_50k_2026_gistic
CD274amplification1313.23%msk_impact_2017msk_impact_2017_cna
PTENdeep deletion1313.23%msk_impact_2017msk_impact_2017_cna
NOTCH3deep deletion1313.23%msk_impact_2017msk_impact_2017_cna
TGFBR2deep deletion1313.23%msk_impact_2017msk_impact_2017_cna
ERBB2deep deletion1313.23%msk_impact_2017msk_impact_2017_cna
CASP8deep deletion1313.23%msk_impact_2017msk_impact_2017_cna
KDM6Adeep deletion1313.23%msk_impact_2017msk_impact_2017_cna
FAT1deep deletion41392.88%msk_impact_50k_2026msk_impact_50k_2026_gistic
CD274amplification31392.16%msk_impact_50k_2026msk_impact_50k_2026_gistic
MYCamplification31392.16%msk_impact_50k_2026msk_impact_50k_2026_gistic
BRCA2amplification31392.16%msk_impact_50k_2026msk_impact_50k_2026_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)
CD2740.0–0.0%msk_impact_50k_2026: 0/139 (0.0%) · msk_impact_2017: 0/31 (0.0%)
PDCD10.0–0.0%msk_impact_50k_2026: 0/139 (0.0%) · msk_impact_2017: 0/31 (0.0%)
PIK3CA29.03–29.5%msk_impact_50k_2026: 41/139 (29.5%) · msk_impact_2017: 9/31 (29.03%)
CDKN2A0.0–5.04%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 0/31 (0.0%)
TP539.68–10.07%msk_impact_50k_2026: 14/139 (10.07%) · msk_impact_2017: 3/31 (9.68%)
EGFR2.16–3.23%msk_impact_50k_2026: 3/139 (2.16%) · msk_impact_2017: 1/31 (3.23%)
KMT2D12.9–24.46%msk_impact_50k_2026: 34/139 (24.46%) · msk_impact_2017: 4/31 (12.9%)
FBXW73.23–13.67%msk_impact_50k_2026: 19/139 (13.67%) · msk_impact_2017: 1/31 (3.23%)
PTEN10.07–12.9%msk_impact_50k_2026: 14/139 (10.07%) · msk_impact_2017: 4/31 (12.9%)
SOX20.0–0.72%msk_impact_50k_2026: 1/139 (0.72%) · msk_impact_2017: 0/31 (0.0%)
TERT0.72–3.23%msk_impact_50k_2026: 1/139 (0.72%) · msk_impact_2017: 1/31 (3.23%)
MYC0.0–2.16%msk_impact_50k_2026: 3/139 (2.16%) · msk_impact_2017: 0/31 (0.0%)
EP30012.95–16.13%msk_impact_50k_2026: 18/139 (12.95%) · msk_impact_2017: 5/31 (16.13%)
KMT2C3.23–10.79%msk_impact_50k_2026: 15/139 (10.79%) · msk_impact_2017: 1/31 (3.23%)
CREBBP9.68–10.07%msk_impact_50k_2026: 14/139 (10.07%) · msk_impact_2017: 3/31 (9.68%)
STK116.45–9.35%msk_impact_50k_2026: 13/139 (9.35%) · msk_impact_2017: 2/31 (6.45%)
ZFHX35.26–9.45%msk_impact_50k_2026: 12/127 (9.45%) · msk_impact_2017: 1/19 (5.26%)
NOTCH13.23–8.63%msk_impact_50k_2026: 12/139 (8.63%) · msk_impact_2017: 1/31 (3.23%)
FAT16.45–8.63%msk_impact_50k_2026: 12/139 (8.63%) · msk_impact_2017: 2/31 (6.45%)
NOTCH30.0–6.47%msk_impact_50k_2026: 9/139 (6.47%) · msk_impact_2017: 0/31 (0.0%)
KEAP13.23–6.47%msk_impact_50k_2026: 9/139 (6.47%) · msk_impact_2017: 1/31 (3.23%)
PTPRT5.76–6.45%msk_impact_50k_2026: 8/139 (5.76%) · msk_impact_2017: 2/31 (6.45%)
NOTCH43.23–5.76%msk_impact_50k_2026: 8/139 (5.76%) · msk_impact_2017: 1/31 (3.23%)
FANCA3.23–5.76%msk_impact_50k_2026: 8/139 (5.76%) · msk_impact_2017: 1/31 (3.23%)
BRCA10.0–5.76%msk_impact_50k_2026: 8/139 (5.76%) · msk_impact_2017: 0/31 (0.0%)
TGFBR25.04–6.45%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 2/31 (6.45%)
TET20.0–5.04%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 0/31 (0.0%)
PIK3R13.23–5.04%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 1/31 (3.23%)
KMT2A5.04–6.45%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 2/31 (6.45%)
HLA-B7.0–7.0%msk_impact_50k_2026: 7/100 (7.0%) · msk_impact_2017: not assayed
ERBB23.23–5.04%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 1/31 (3.23%)
CASP83.23–5.04%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 1/31 (3.23%)
APC3.23–5.04%msk_impact_50k_2026: 7/139 (5.04%) · msk_impact_2017: 1/31 (3.23%)
STAG24.32–6.45%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 2/31 (6.45%)
RICTOR0.0–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 0/31 (0.0%)
RB10.0–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 0/31 (0.0%)
PTPRD4.32–6.45%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 2/31 (6.45%)
PIK3CG3.23–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 1/31 (3.23%)
NSD10.0–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 0/31 (0.0%)
NOTCH24.32–6.45%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 2/31 (6.45%)
NFE2L24.32–6.45%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 2/31 (6.45%)
KRAS3.23–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 1/31 (3.23%)
KDM6A3.23–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 1/31 (3.23%)
HLA-A4.72–5.26%msk_impact_50k_2026: 6/127 (4.72%) · msk_impact_2017: 1/19 (5.26%)
CDK120.0–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 0/31 (0.0%)
BRCA23.23–4.32%msk_impact_50k_2026: 6/139 (4.32%) · msk_impact_2017: 1/31 (3.23%)

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/anal-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.