← BioTransferKidney cancer briefingAll diseases

Disease intelligence · mutation landscape

Kidney cancer mutation landscape

How often each gene is altered in kidney 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: kirc_tcga_pan_can_atlas_2018 · JSON: /disease/kidney-cancer/mutations.json · Back to the briefing

Answer block

In Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas) (402 sequenced patients, exome or genome), the most frequently altered of the 46 genes shown are VHL 41.29%, PBRM1 35.82%, SETD2 11.94%, BAP1 9.45%, MTOR 7.71%. Each figure divides by the patients on whom that gene could be called.

1 of 402 patients are hypermutated (more than 480 non-silent mutations, ten times the cohort median of 48); every gene's frequency without them is beside the headline.

Of the briefing's 12 curated targets, 6 are altered in under 2% of this cohort (HIF1A, EPAS1, KDR, MET, CD274, CA9): targets by expression, dependency or drug label, not by mutation. Frequency is not targetability, in either direction.

3 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%.

Alterationkirc_tcga_pan_can_atlas_2018
402 pts · exome or genome
kirp_tcga_pan_can_atlas_2018
276 pts · exome or genome
ccrcc_sjuh_2023
943 pts · exome or genome
VHL SNV / small indel41.29%166/4021.09%3/27667.13%633/943
VHL deep deletion2.55%13/5090%·
HIF1A SNV / small indel1.0%4/4020.72%2/2760%
EPAS1 SNV / small indel0.5%2/4021.09%3/2760%
PBRM1 SNV / small indel35.82%144/4024.35%12/27633.72%318/943
PBRM1 deep deletion2.75%14/5090.35%1/283·
SETD2 SNV / small indel11.94%48/4026.16%17/27615.48%146/943
SETD2 deep deletion2.75%14/5090%·
BAP1 SNV / small indel9.45%38/4025.07%14/27611.98%113/943
BAP1 deep deletion2.55%13/5090.35%1/283·
KDM5C SNV / small indel4.98%20/4021.81%5/2767.1%67/943
MTOR SNV / small indel7.71%31/4021.45%4/2760%
KDR SNV / small indel1.24%5/4021.09%3/2760%
MET SNV / small indel0.75%3/4027.97%22/2760%
CD274 SNV / small indel0.25%1/4020%0%
CA9 SNV / small indel0.25%1/4020.36%1/2760%
KMT2C SNV / small indel3.73%15/4026.88%19/2760%
SPEN SNV / small indel3.48%14/4023.26%9/2760%
ATM SNV / small indel3.23%13/4022.17%6/2763.18%30/943
ARID1A SNV / small indel3.23%13/4024.35%12/2760%
PTEN SNV / small indel2.99%12/4022.54%7/2760%
TP53 SNV / small indel2.74%11/4022.17%6/2763.08%29/943
SMARCA4 SNV / small indel2.74%11/4023.62%10/2760%
ROS1 SNV / small indel2.74%11/4021.45%4/2760%
PRPF8 SNV / small indel2.74%11/4021.45%4/2760%
PCDH15 SNV / small indel2.74%11/4021.81%5/2760%
LRP1 SNV / small indel2.74%11/4023.62%10/2760%
FREM2 SNV / small indel2.74%11/4022.9%8/2760%
ERBB4 SNV / small indel2.74%11/4021.45%4/2760%
COL6A6 SNV / small indel2.74%11/4021.81%5/2760%
PTPRZ1 SNV / small indel2.49%10/4021.81%5/2760%
KMT2D SNV / small indel2.49%10/4026.52%18/2760%
DYNC2H1 SNV / small indel2.49%10/4022.9%8/2760%
COL6A3 SNV / small indel2.49%10/4022.17%6/2760%
CENPF SNV / small indel2.49%10/4024.35%12/2760%
AKAP9 SNV / small indel2.49%10/4021.09%3/2760%
ADAMTS12 SNV / small indel2.49%10/4020.72%2/2760%
VWF SNV / small indel2.24%9/4021.45%4/2760%
STAG2 SNV / small indel2.24%9/4022.9%8/2760%
SCAF4 SNV / small indel2.24%9/4020%0%
PKHD1 SNV / small indel2.24%9/4026.52%18/2760%
MYO16 SNV / small indel2.24%9/4020%0%
MYH4 SNV / small indel2.24%9/4022.17%6/2760%
MYH2 SNV / small indel2.24%9/4020.36%1/2760%
LYST SNV / small indel2.24%9/4021.45%4/2760%
KIAA1549L SNV / small indel2.24%9/4021.09%3/2760%
KCNH7 SNV / small indel2.24%9/4020.72%2/2760%
COL4A5 SNV / small indel2.24%9/4021.09%3/2760%
CELSR1 SNV / small indel2.24%9/4021.81%5/2760%
WDFY3 SNV / small indel1.99%8/4025.07%14/2760%

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

Key findings

VHL is mutated in 166 of 402 patients in Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas).
Numerator: 166 · Denominator: 402 · Frequency: 41.29% · Observed in 3 cohorts · Confidence: moderate · Source: kirc_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

PBRM1 is mutated in 144 of 402 patients in Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas).
Numerator: 144 · Denominator: 402 · Frequency: 35.82% · Observed in 3 cohorts · Confidence: moderate · Source: kirc_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

SETD2 is mutated in 48 of 402 patients in Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas).
Numerator: 48 · Denominator: 402 · Frequency: 11.94% · Observed in 3 cohorts · Confidence: moderate · Source: kirc_tcga_pan_can_atlas_2018 · Retrieved: 2026-09-18

Gene table — reference cohort

Headline values are from the reference cohort, kirc_tcga_pan_can_atlas_2018; 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
VHL curated target SNV / small indel 166 / 402 41.29% 41.4% 3 / 3 1.09–67.13% X155_splice (n=12), X114_splice (n=6), H115N (n=4), W117Gfs*42 (n=3), T124Hfs*35 (n=3)
HIF1A curated target SNV / small indel 4 / 402 1.0% 1.0% 2 / 3 0.0–1.0% Q320L (n=1), C337* (n=1), X698_splice (n=1), L54I (n=1)
EPAS1 curated target SNV / small indel 2 / 402 0.5% 0.5% 2 / 3 0.0–1.09% V846Efs*55 (n=1), D508N (n=1)
PBRM1 curated target SNV / small indel 144 / 402 35.82% 35.91% 3 / 3 4.35–35.82% E1197Kfs*5 (n=2), X363_splice (n=2), D748Mfs*27 (n=2), X332_splice (n=2), X239_splice (n=2)
SETD2 curated target SNV / small indel 48 / 402 11.94% 11.72% 3 / 3 6.16–15.48% W1782* (n=2), P1822Qfs*16 (n=1), R2510H (n=1), X2413_splice (n=1), K2545* (n=1)
BAP1 curated target SNV / small indel 38 / 402 9.45% 9.48% 3 / 3 5.07–11.98% M1? (n=3), N78S (n=2), X23_splice (n=2), X41_splice (n=2), K659del (n=1)
KDM5C curated target SNV / small indel 20 / 402 4.98% 4.99% 3 / 3 1.81–7.1% R390L (n=1), E433Gfs*4 (n=1), E1152Kfs*112 (n=1), X321_splice (n=1), G536W (n=1)
MTOR curated target SNV / small indel 31 / 402 7.71% 7.48% 2 / 3 0.0–7.71% T1977R (n=3), L1460P (n=2), C1483F (n=2), M2327I (n=1), R619C (n=1)
KDR curated target SNV / small indel 5 / 402 1.24% 1.25% 2 / 3 0.0–1.24% I456S (n=1), G1108W (n=1), L289* (n=1), R1051Q (n=1), T761R (n=1)
MET curated target SNV / small indel 3 / 402 0.75% 0.75% 2 / 3 0.0–7.97% L1205V (n=1), V1070E (n=1), V504L (n=1)
CD274 curated target SNV / small indel 1 / 402 0.25% 0.25% 1 / 3 0.0–0.25% E188K (n=1)
CA9 curated target SNV / small indel 1 / 402 0.25% 0.25% 2 / 3 0.0–0.36% P216R (n=1)
KMT2C by frequency SNV / small indel 15 / 402 3.73% 3.49% 2 / 3 0.0–6.88% V1881L (n=1), Q3061K (n=1), D1371Ifs*3 (n=1), S1086Vfs*31 (n=1), P2163H (n=1)
SPEN by frequency SNV / small indel 14 / 402 3.48% 3.24% 2 / 3 0.0–3.48% P924S (n=1), S1457A (n=1), P2236S (n=1), I2953T (n=1), E2442V (n=1)
ATM by frequency SNV / small indel 13 / 402 3.23% 3.24% 3 / 3 2.17–3.23% X1370_splice (n=1), T909I (n=1), R2580* (n=1), S496Ifs*16 (n=1), A749T (n=1)
ARID1A by frequency SNV / small indel 13 / 402 3.23% 3.24% 2 / 3 0.0–4.35% P1244H (n=1), Q1098* (n=1), G1139Lfs*21 (n=1), G665Dfs*10 (n=1), P554Hfs*65 (n=1)
PTEN by frequency SNV / small indel 12 / 402 2.99% 2.99% 2 / 3 0.0–2.99% X343_splice (n=2), L146* (n=1), X212_splice (n=1), S170N (n=1), C136Mfs*44 (n=1)
TP53 by frequency SNV / small indel 11 / 402 2.74% 2.49% 3 / 3 2.17–3.08% H178Qfs*3 (n=1), E11* (n=1), X32_splice (n=1), R248L (n=1), R213Q (n=1)
SMARCA4 by frequency SNV / small indel 11 / 402 2.74% 2.49% 2 / 3 0.0–3.62% A1231T (n=1), E365Q (n=1), T910M (n=1), H884R (n=1), X1183_splice (n=1)
ROS1 by frequency SNV / small indel 11 / 402 2.74% 2.74% 2 / 3 0.0–2.74% X1441_splice (n=1), E1905D (n=1), L1445Q (n=1), P1350Q (n=1), L53M (n=1)
PRPF8 by frequency SNV / small indel 11 / 402 2.74% 2.49% 2 / 3 0.0–2.74% N1543I (n=1), A2000V (n=1), A458V (n=1), N1129Y (n=1), W1839C (n=1)
PCDH15 by frequency SNV / small indel 11 / 402 2.74% 2.74% 2 / 3 0.0–2.74% Q1135H (n=1), D1136Y (n=1), A238D (n=1), Q474H (n=1), P464Q (n=1)
LRP1 by frequency SNV / small indel 11 / 402 2.74% 2.74% 2 / 3 0.0–3.62% C3620Y (n=1), R1999H (n=1), F719S (n=1), D4019V (n=1), P2689Q (n=1)
FREM2 by frequency SNV / small indel 11 / 402 2.74% 2.49% 2 / 3 0.0–2.9% Q2235K (n=1), L2110I (n=1), K2955E (n=1), M2878V (n=1), P504S (n=1)
ERBB4 by frequency SNV / small indel 11 / 402 2.74% 2.74% 2 / 3 0.0–2.74% S1037C (n=1), H1303Q (n=1), C593F (n=1), H190R (n=1), Y906F (n=1)
COL6A6 by frequency SNV / small indel 11 / 402 2.74% 2.74% 2 / 3 0.0–2.74% K600Tfs*2 (n=1), G1916D (n=1), S2094R (n=1), R1295Q (n=1), D1116Afs*10 (n=1)
PTPRZ1 by frequency SNV / small indel 10 / 402 2.49% 2.49% 2 / 3 0.0–2.49% K1664I (n=1), A1571T (n=1), P506Q (n=1), P506T (n=1), L379V (n=1)
KMT2D by frequency SNV / small indel 10 / 402 2.49% 2.49% 2 / 3 0.0–6.52% H1319Q (n=1), A262D (n=1), C874* (n=1), S1917G (n=1), S1451C (n=1)
DYNC2H1 by frequency SNV / small indel 10 / 402 2.49% 2.49% 2 / 3 0.0–2.9% G2271R (n=1), N4045S (n=1), Q2312H (n=1), D3619H (n=1), D1091Y (n=1)
COL6A3 by frequency SNV / small indel 10 / 402 2.49% 2.49% 2 / 3 0.0–2.49% A2978T (n=1), G1245E (n=1), M2620I (n=1), G2110A (n=1), V1596M (n=1)
CENPF by frequency SNV / small indel 10 / 402 2.49% 2.49% 2 / 3 0.0–4.35% E542V (n=1), Y1559H (n=1), K363I (n=1), R2702W (n=1), A597V (n=1)
AKAP9 by frequency SNV / small indel 10 / 402 2.49% 2.49% 2 / 3 0.0–2.49% S1549* (n=1), E2362Dfs*11 (n=1), M1049L (n=1), N687K (n=1), K327N (n=1)
ADAMTS12 by frequency SNV / small indel 10 / 402 2.49% 2.49% 2 / 3 0.0–2.49% M275I (n=1), T203Pfs*8 (n=1), P1139S (n=1), A888V (n=1), F282Y (n=1)
VWF by frequency SNV / small indel 9 / 402 2.24% 2.0% 2 / 3 0.0–2.24% E732D (n=1), S1866P (n=1), L2629P (n=1), T1608A (n=1), L1666V (n=1)
STAG2 by frequency SNV / small indel 9 / 402 2.24% 2.24% 2 / 3 0.0–2.9% L995* (n=1), R667W (n=1), E750Dfs*31 (n=1), R604* (n=1), R216Q (n=1)
SCAF4 by frequency SNV / small indel 9 / 402 2.24% 2.24% 1 / 3 0.0–2.24% K1120* (n=1), K124R (n=1), E57Q (n=1), P389L (n=1), X576_splice (n=1)
PKHD1 by frequency SNV / small indel 9 / 402 2.24% 2.24% 2 / 3 0.0–6.52% S2867F (n=1), H216N (n=1), K2085N (n=1), V302M (n=1), K2781E (n=1)
MYO16 by frequency SNV / small indel 9 / 402 2.24% 2.24% 1 / 3 0.0–2.24% T128M (n=1), L273R (n=1), T900I (n=1), N1847K (n=1), S1354R (n=1)
MYH4 by frequency SNV / small indel 9 / 402 2.24% 2.0% 2 / 3 0.0–2.24% D1076Y (n=1), N81I (n=1), E1756* (n=1), A1553V (n=1), T69S (n=1)
MYH2 by frequency SNV / small indel 9 / 402 2.24% 2.24% 2 / 3 0.0–2.24% X422_splice (n=1), X216_splice (n=1), L869F (n=1), G319V (n=1), X7_splice (n=1)
LYST by frequency SNV / small indel 9 / 402 2.24% 2.24% 2 / 3 0.0–2.24% R2261C (n=1), F2993L (n=1), K2703R (n=1), S927Lfs*11 (n=1), F2401V (n=1)
KIAA1549L by frequency SNV / small indel 9 / 402 2.24% 2.0% 2 / 3 0.0–2.24% T1485I (n=1), F1011S (n=1), L410P (n=1), T689R (n=1), Q69R (n=1)
KCNH7 by frequency SNV / small indel 9 / 402 2.24% 2.24% 2 / 3 0.0–2.24% X872_splice (n=1), E969D (n=1), P910R (n=1), R598C (n=1), E701A (n=1)
COL4A5 by frequency SNV / small indel 9 / 402 2.24% 2.24% 2 / 3 0.0–2.24% T1470R (n=1), G1421V (n=1), X1504_splice (n=1), A1650T (n=1), N217H (n=1)
CELSR1 by frequency SNV / small indel 9 / 402 2.24% 2.0% 2 / 3 0.0–2.24% Q1473K (n=1), G1415W (n=1), G614Afs*54 (n=1), R1924C (n=1), X1590_splice (n=1)
WDFY3 by frequency SNV / small indel 8 / 402 1.99% 2.0% 2 / 3 0.0–5.07% S2514T (n=1), I1907V (n=1), T146A (n=1), X3115_splice (n=1), K2368M (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
Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas) reference
Kidney Renal Clear Cell Carcinoma (TCGA, PanCancer Atlas)
kirc_tcga_pan_can_atlas_2018402 observed402 / 512exome or genomeWES (402)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)148.0
Kidney Renal Papillary Cell Carcinoma (TCGA, PanCancer Atlas)
Kidney Renal Papillary Cell Carcinoma (TCGA, PanCancer Atlas)
kirp_tcga_pan_can_atlas_2018276 observed276 / 283exome or genomeWES (276)hg19SNV, small indel, amplification, deep deletion, structural variant (profile present, not read)162.0
Renal Cell Carcinoma (St. James, Clin Cancer Res 2023)
Renal Cell Carcinoma (St. James, Clin Cancer Res 2023)
ccrcc_sjuh_2023943 observed943 / 943exome or genomeWES (943)hg19SNV, small indel01

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
PBRM1deep deletion145092.75%kirc_tcga_pan_can_atlas_2018kirc_tcga_pan_can_atlas_2018_gistic
SETD2deep deletion145092.75%kirc_tcga_pan_can_atlas_2018kirc_tcga_pan_can_atlas_2018_gistic
VHLdeep deletion135092.55%kirc_tcga_pan_can_atlas_2018kirc_tcga_pan_can_atlas_2018_gistic
BAP1deep deletion135092.55%kirc_tcga_pan_can_atlas_2018kirc_tcga_pan_can_atlas_2018_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)
VHL1.09–67.13%kirc_tcga_pan_can_atlas_2018: 166/402 (41.29%) · kirp_tcga_pan_can_atlas_2018: 3/276 (1.09%) · ccrcc_sjuh_2023: 633/943 (67.13%)
HIF1A0.0–1.0%kirc_tcga_pan_can_atlas_2018: 4/402 (1.0%) · kirp_tcga_pan_can_atlas_2018: 2/276 (0.72%) · ccrcc_sjuh_2023: 0/943 (0.0%)
EPAS10.0–1.09%kirc_tcga_pan_can_atlas_2018: 2/402 (0.5%) · kirp_tcga_pan_can_atlas_2018: 3/276 (1.09%) · ccrcc_sjuh_2023: 0/943 (0.0%)
PBRM14.35–35.82%kirc_tcga_pan_can_atlas_2018: 144/402 (35.82%) · kirp_tcga_pan_can_atlas_2018: 12/276 (4.35%) · ccrcc_sjuh_2023: 318/943 (33.72%)
SETD26.16–15.48%kirc_tcga_pan_can_atlas_2018: 48/402 (11.94%) · kirp_tcga_pan_can_atlas_2018: 17/276 (6.16%) · ccrcc_sjuh_2023: 146/943 (15.48%)
BAP15.07–11.98%kirc_tcga_pan_can_atlas_2018: 38/402 (9.45%) · kirp_tcga_pan_can_atlas_2018: 14/276 (5.07%) · ccrcc_sjuh_2023: 113/943 (11.98%)
KDM5C1.81–7.1%kirc_tcga_pan_can_atlas_2018: 20/402 (4.98%) · kirp_tcga_pan_can_atlas_2018: 5/276 (1.81%) · ccrcc_sjuh_2023: 67/943 (7.1%)
MTOR0.0–7.71%kirc_tcga_pan_can_atlas_2018: 31/402 (7.71%) · kirp_tcga_pan_can_atlas_2018: 4/276 (1.45%) · ccrcc_sjuh_2023: 0/943 (0.0%)
KDR0.0–1.24%kirc_tcga_pan_can_atlas_2018: 5/402 (1.24%) · kirp_tcga_pan_can_atlas_2018: 3/276 (1.09%) · ccrcc_sjuh_2023: 0/943 (0.0%)
MET0.0–7.97%kirc_tcga_pan_can_atlas_2018: 3/402 (0.75%) · kirp_tcga_pan_can_atlas_2018: 22/276 (7.97%) · ccrcc_sjuh_2023: 0/943 (0.0%)
CD2740.0–0.25%kirc_tcga_pan_can_atlas_2018: 1/402 (0.25%) · kirp_tcga_pan_can_atlas_2018: 0/276 (0.0%) · ccrcc_sjuh_2023: 0/943 (0.0%)
CA90.0–0.36%kirc_tcga_pan_can_atlas_2018: 1/402 (0.25%) · kirp_tcga_pan_can_atlas_2018: 1/276 (0.36%) · ccrcc_sjuh_2023: 0/943 (0.0%)
KMT2C0.0–6.88%kirc_tcga_pan_can_atlas_2018: 15/402 (3.73%) · kirp_tcga_pan_can_atlas_2018: 19/276 (6.88%) · ccrcc_sjuh_2023: 0/943 (0.0%)
SPEN0.0–3.48%kirc_tcga_pan_can_atlas_2018: 14/402 (3.48%) · kirp_tcga_pan_can_atlas_2018: 9/276 (3.26%) · ccrcc_sjuh_2023: 0/943 (0.0%)
ATM2.17–3.23%kirc_tcga_pan_can_atlas_2018: 13/402 (3.23%) · kirp_tcga_pan_can_atlas_2018: 6/276 (2.17%) · ccrcc_sjuh_2023: 30/943 (3.18%)
ARID1A0.0–4.35%kirc_tcga_pan_can_atlas_2018: 13/402 (3.23%) · kirp_tcga_pan_can_atlas_2018: 12/276 (4.35%) · ccrcc_sjuh_2023: 0/943 (0.0%)
PTEN0.0–2.99%kirc_tcga_pan_can_atlas_2018: 12/402 (2.99%) · kirp_tcga_pan_can_atlas_2018: 7/276 (2.54%) · ccrcc_sjuh_2023: 0/943 (0.0%)
TP532.17–3.08%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 6/276 (2.17%) · ccrcc_sjuh_2023: 29/943 (3.08%)
SMARCA40.0–3.62%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 10/276 (3.62%) · ccrcc_sjuh_2023: 0/943 (0.0%)
ROS10.0–2.74%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 4/276 (1.45%) · ccrcc_sjuh_2023: 0/943 (0.0%)
PRPF80.0–2.74%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 4/276 (1.45%) · ccrcc_sjuh_2023: 0/943 (0.0%)
PCDH150.0–2.74%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 5/276 (1.81%) · ccrcc_sjuh_2023: 0/943 (0.0%)
LRP10.0–3.62%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 10/276 (3.62%) · ccrcc_sjuh_2023: 0/943 (0.0%)
FREM20.0–2.9%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 8/276 (2.9%) · ccrcc_sjuh_2023: 0/943 (0.0%)
ERBB40.0–2.74%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 4/276 (1.45%) · ccrcc_sjuh_2023: 0/943 (0.0%)
COL6A60.0–2.74%kirc_tcga_pan_can_atlas_2018: 11/402 (2.74%) · kirp_tcga_pan_can_atlas_2018: 5/276 (1.81%) · ccrcc_sjuh_2023: 0/943 (0.0%)
PTPRZ10.0–2.49%kirc_tcga_pan_can_atlas_2018: 10/402 (2.49%) · kirp_tcga_pan_can_atlas_2018: 5/276 (1.81%) · ccrcc_sjuh_2023: 0/943 (0.0%)
KMT2D0.0–6.52%kirc_tcga_pan_can_atlas_2018: 10/402 (2.49%) · kirp_tcga_pan_can_atlas_2018: 18/276 (6.52%) · ccrcc_sjuh_2023: 0/943 (0.0%)
DYNC2H10.0–2.9%kirc_tcga_pan_can_atlas_2018: 10/402 (2.49%) · kirp_tcga_pan_can_atlas_2018: 8/276 (2.9%) · ccrcc_sjuh_2023: 0/943 (0.0%)
COL6A30.0–2.49%kirc_tcga_pan_can_atlas_2018: 10/402 (2.49%) · kirp_tcga_pan_can_atlas_2018: 6/276 (2.17%) · ccrcc_sjuh_2023: 0/943 (0.0%)
CENPF0.0–4.35%kirc_tcga_pan_can_atlas_2018: 10/402 (2.49%) · kirp_tcga_pan_can_atlas_2018: 12/276 (4.35%) · ccrcc_sjuh_2023: 0/943 (0.0%)
AKAP90.0–2.49%kirc_tcga_pan_can_atlas_2018: 10/402 (2.49%) · kirp_tcga_pan_can_atlas_2018: 3/276 (1.09%) · ccrcc_sjuh_2023: 0/943 (0.0%)
ADAMTS120.0–2.49%kirc_tcga_pan_can_atlas_2018: 10/402 (2.49%) · kirp_tcga_pan_can_atlas_2018: 2/276 (0.72%) · ccrcc_sjuh_2023: 0/943 (0.0%)
VWF0.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 4/276 (1.45%) · ccrcc_sjuh_2023: 0/943 (0.0%)
STAG20.0–2.9%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 8/276 (2.9%) · ccrcc_sjuh_2023: 0/943 (0.0%)
SCAF40.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 0/276 (0.0%) · ccrcc_sjuh_2023: 0/943 (0.0%)
PKHD10.0–6.52%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 18/276 (6.52%) · ccrcc_sjuh_2023: 0/943 (0.0%)
MYO160.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 0/276 (0.0%) · ccrcc_sjuh_2023: 0/943 (0.0%)
MYH40.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 6/276 (2.17%) · ccrcc_sjuh_2023: 0/943 (0.0%)
MYH20.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 1/276 (0.36%) · ccrcc_sjuh_2023: 0/943 (0.0%)
LYST0.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 4/276 (1.45%) · ccrcc_sjuh_2023: 0/943 (0.0%)
KIAA1549L0.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 3/276 (1.09%) · ccrcc_sjuh_2023: 0/943 (0.0%)
KCNH70.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 2/276 (0.72%) · ccrcc_sjuh_2023: 0/943 (0.0%)
COL4A50.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 3/276 (1.09%) · ccrcc_sjuh_2023: 0/943 (0.0%)
CELSR10.0–2.24%kirc_tcga_pan_can_atlas_2018: 9/402 (2.24%) · kirp_tcga_pan_can_atlas_2018: 5/276 (1.81%) · ccrcc_sjuh_2023: 0/943 (0.0%)
WDFY30.0–5.07%kirc_tcga_pan_can_atlas_2018: 8/402 (1.99%) · kirp_tcga_pan_can_atlas_2018: 14/276 (5.07%) · ccrcc_sjuh_2023: 0/943 (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/kidney-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.