Acute Myeloid Leukemia: Correlation between gene mutation status and molecular subtypes
(primary blood tumor (peripheral) cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Overview
Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and molecular subtypes.

Summary

Testing the association between mutation status of 24 genes and 6 molecular subtypes across 197 patients, 23 significant findings detected with P value < 0.05 and Q value < 0.25.

  • WT1 mutation correlated to 'METHLYATION_CNMF'.

  • RUNX1 mutation correlated to 'MRNASEQ_CNMF' and 'MIRSEQ_CHIERARCHICAL'.

  • DNMT3A mutation correlated to 'METHLYATION_CNMF',  'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • FLT3 mutation correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • IDH1 mutation correlated to 'METHLYATION_CNMF'.

  • IDH2 mutation correlated to 'METHLYATION_CNMF'.

  • NPM1 mutation correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • TP53 mutation correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • FAM5C mutation correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 24 genes and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 23 significant findings detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL
nMutated (%) nWild-Type Chi-square test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
NPM1 54 (27%) 143 0.000935
(0.11) 		3.11e-18
(4.25e-16) 		1.79e-13
(2.44e-11) 		0.00649
(0.746) 		2.17e-20
(2.99e-18) 		1.79e-21
(2.49e-19)
TP53 15 (8%) 182 1.52e-10
(2.05e-08) 		2.81e-09
(3.74e-07) 		0.000687
(0.0817) 		0.0625
(1.00) 		0.000668
(0.0802) 		0.000144
(0.0176)
FLT3 56 (28%) 141 0.0164
(1.00) 		4.52e-05
(0.00565) 		1.86e-07
(2.42e-05) 		0.0209
(1.00) 		0.000285
(0.0345) 		1.28e-05
(0.00162)
DNMT3A 51 (26%) 146 0.978
(1.00) 		3.03e-05
(0.00382) 		0.0122
(1.00) 		0.195
(1.00) 		5.71e-05
(0.00702) 		5.45e-06
(0.000698)
RUNX1 18 (9%) 179 0.381
(1.00) 		0.011
(1.00) 		0.00152
(0.178) 		0.0926
(1.00) 		0.00649
(0.746) 		5.1e-05
(0.00632)
WT1 12 (6%) 185 0.581
(1.00) 		2.19e-06
(0.000282) 		0.0817
(1.00) 		1
(1.00) 		0.666
(1.00) 		0.516
(1.00)
IDH1 19 (10%) 178 0.968
(1.00) 		7.04e-09
(9.3e-07) 		0.423
(1.00) 		0.268
(1.00) 		0.307
(1.00) 		0.236
(1.00)
IDH2 20 (10%) 177 0.269
(1.00) 		1.31e-09
(1.76e-07) 		0.725
(1.00) 		1
(1.00) 		0.896
(1.00) 		0.895
(1.00)
FAM5C 5 (3%) 192 1.15e-07
(1.51e-05) 		0.611
(1.00) 		0.729
(1.00) 		0.665
(1.00) 		1
(1.00) 		1
(1.00)
NRAS 15 (8%) 182 0.0145
(1.00) 		0.571
(1.00) 		0.645
(1.00) 		0.539
(1.00) 		0.938
(1.00) 		0.878
(1.00)
U2AF1 8 (4%) 189 0.776
(1.00) 		0.24
(1.00) 		0.232
(1.00) 		0.426
(1.00) 		0.176
(1.00) 		0.171
(1.00)
KRAS 8 (4%) 189 0.533
(1.00) 		0.925
(1.00) 		0.326
(1.00) 		0.225
(1.00) 		0.0996
(1.00) 		0.063
(1.00)
PTPN11 9 (5%) 188 0.485
(1.00) 		0.903
(1.00) 		0.0476
(1.00) 		1
(1.00) 		0.176
(1.00) 		0.447
(1.00)
TET2 17 (9%) 180 0.464
(1.00) 		0.534
(1.00) 		0.256
(1.00) 		0.776
(1.00) 		0.512
(1.00) 		0.428
(1.00)
KIT 8 (4%) 189 0.885
(1.00) 		0.00779
(0.88) 		0.326
(1.00) 		0.688
(1.00) 		0.115
(1.00) 		0.113
(1.00)
PHF6 6 (3%) 191 0.317
(1.00) 		0.396
(1.00) 		0.729
(1.00) 		0.17
(1.00) 		0.515
(1.00) 		0.148
(1.00)
SMC1A 7 (4%) 190 0.826
(1.00) 		0.359
(1.00) 		0.37
(1.00) 		0.043
(1.00) 		0.153
(1.00) 		0.106
(1.00)
SMC3 7 (4%) 190 0.77
(1.00) 		0.564
(1.00) 		0.552
(1.00) 		0.426
(1.00) 		0.426
(1.00) 		0.48
(1.00)
RAD21 5 (3%) 192 0.757
(1.00) 		0.543
(1.00) 		0.608
(1.00) 		1
(1.00) 		0.373
(1.00) 		0.287
(1.00)
STAG2 6 (3%) 191 0.776
(1.00) 		0.0344
(1.00) 		0.132
(1.00) 		0.17
(1.00) 		0.852
(1.00) 		0.222
(1.00)
EZH2 3 (2%) 194 0.00614
(0.713) 		0.261
(1.00) 		1
(1.00) 		0.222
(1.00) 		0.229
(1.00)
ASXL1 5 (3%) 192 0.757
(1.00) 		0.187
(1.00) 		0.261
(1.00) 		0.552
(1.00) 		0.222
(1.00) 		0.229
(1.00)
PHACTR1 3 (2%) 194 0.424
(1.00) 		1
(1.00) 		0.222
(1.00) 		0.229
(1.00)
DIS3 3 (2%) 194 0.553
(1.00) 		1
(1.00) 		0.089
(1.00) 		0.0958
(1.00)
'WT1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 2.19e-06 (Chi-square test), Q value = 0.00028

Table S1.  Gene #2: 'WT1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 48 18 26 39 48 12
WT1 MUTATED 1 0 2 3 0 5
WT1 WILD-TYPE 47 18 24 36 48 7

Figure S1.  Get High-res Image Gene #2: 'WT1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'RUNX1 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.00152 (Fisher's exact test), Q value = 0.18

Table S2.  Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 73 52 45
RUNX1 MUTATED 13 3 0
RUNX1 WILD-TYPE 60 49 45

Figure S2.  Get High-res Image Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'RUNX1 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 5.1e-05 (Fisher's exact test), Q value = 0.0063

Table S3.  Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 38 81 65
RUNX1 MUTATED 4 0 12
RUNX1 WILD-TYPE 34 81 53

Figure S3.  Get High-res Image Gene #3: 'RUNX1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'DNMT3A MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 3.03e-05 (Chi-square test), Q value = 0.0038

Table S4.  Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 48 18 26 39 48 12
DNMT3A MUTATED 25 0 5 6 12 1
DNMT3A WILD-TYPE 23 18 21 33 36 11

Figure S4.  Get High-res Image Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'DNMT3A MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 5.71e-05 (Fisher's exact test), Q value = 0.007

Table S5.  Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 40 60
DNMT3A MUTATED 33 3 9
DNMT3A WILD-TYPE 51 37 51

Figure S5.  Get High-res Image Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'DNMT3A MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 5.45e-06 (Fisher's exact test), Q value = 7e-04

Table S6.  Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 38 81 65
DNMT3A MUTATED 3 34 8
DNMT3A WILD-TYPE 35 47 57

Figure S6.  Get High-res Image Gene #4: 'DNMT3A MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'FLT3 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 4.52e-05 (Chi-square test), Q value = 0.0056

Table S7.  Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 48 18 26 39 48 12
FLT3 MUTATED 26 5 3 8 7 6
FLT3 WILD-TYPE 22 13 23 31 41 6

Figure S7.  Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'FLT3 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 1.86e-07 (Fisher's exact test), Q value = 2.4e-05

Table S8.  Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 73 52 45
FLT3 MUTATED 6 20 23
FLT3 WILD-TYPE 67 32 22

Figure S8.  Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'FLT3 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 0.000285 (Fisher's exact test), Q value = 0.034

Table S9.  Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 40 60
FLT3 MUTATED 36 4 14
FLT3 WILD-TYPE 48 36 46

Figure S9.  Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'FLT3 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.28e-05 (Fisher's exact test), Q value = 0.0016

Table S10.  Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 38 81 65
FLT3 MUTATED 4 38 12
FLT3 WILD-TYPE 34 43 53

Figure S10.  Get High-res Image Gene #5: 'FLT3 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'IDH1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 7.04e-09 (Chi-square test), Q value = 9.3e-07

Table S11.  Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 48 18 26 39 48 12
IDH1 MUTATED 4 0 12 0 3 0
IDH1 WILD-TYPE 44 18 14 39 45 12

Figure S11.  Get High-res Image Gene #6: 'IDH1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'IDH2 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 1.31e-09 (Chi-square test), Q value = 1.8e-07

Table S12.  Gene #7: 'IDH2 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 48 18 26 39 48 12
IDH2 MUTATED 0 0 12 2 4 0
IDH2 WILD-TYPE 48 18 14 37 44 12

Figure S12.  Get High-res Image Gene #7: 'IDH2 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'NPM1 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.000935 (Chi-square test), Q value = 0.11

Table S13.  Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 139 15 15 18 1
NPM1 MUTATED 50 0 1 1 0
NPM1 WILD-TYPE 89 15 14 17 1

Figure S13.  Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'NPM1 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 3.11e-18 (Chi-square test), Q value = 4.3e-16

Table S14.  Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 48 18 26 39 48 12
NPM1 MUTATED 36 0 11 0 2 4
NPM1 WILD-TYPE 12 18 15 39 46 8

Figure S14.  Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'NPM1 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 1.79e-13 (Fisher's exact test), Q value = 2.4e-11

Table S15.  Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 73 52 45
NPM1 MUTATED 1 22 25
NPM1 WILD-TYPE 72 30 20

Figure S15.  Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'NPM1 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 2.17e-20 (Fisher's exact test), Q value = 3e-18

Table S16.  Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 40 60
NPM1 MUTATED 50 0 1
NPM1 WILD-TYPE 34 40 59

Figure S16.  Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'NPM1 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.79e-21 (Fisher's exact test), Q value = 2.5e-19

Table S17.  Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 38 81 65
NPM1 MUTATED 0 50 1
NPM1 WILD-TYPE 38 31 64

Figure S17.  Get High-res Image Gene #8: 'NPM1 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'TP53 MUTATION STATUS' versus 'CN_CNMF'

P value = 1.52e-10 (Chi-square test), Q value = 2.1e-08

Table S18.  Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 139 15 15 18 1
TP53 MUTATED 0 3 6 6 0
TP53 WILD-TYPE 139 12 9 12 1

Figure S18.  Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

'TP53 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 2.81e-09 (Chi-square test), Q value = 3.7e-07

Table S19.  Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 48 18 26 39 48 12
TP53 MUTATED 0 0 0 0 15 0
TP53 WILD-TYPE 48 18 26 39 33 12

Figure S19.  Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #2: 'METHLYATION_CNMF'

'TP53 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.000687 (Fisher's exact test), Q value = 0.082

Table S20.  Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 73 52 45
TP53 MUTATED 12 1 0
TP53 WILD-TYPE 61 51 45

Figure S20.  Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 0.000668 (Fisher's exact test), Q value = 0.08

Table S21.  Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 40 60
TP53 MUTATED 2 9 3
TP53 WILD-TYPE 82 31 57

Figure S21.  Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'TP53 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000144 (Fisher's exact test), Q value = 0.018

Table S22.  Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 38 81 65
TP53 MUTATED 9 1 4
TP53 WILD-TYPE 29 80 61

Figure S22.  Get High-res Image Gene #10: 'TP53 MUTATION STATUS' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'FAM5C MUTATION STATUS' versus 'CN_CNMF'

P value = 1.15e-07 (Chi-square test), Q value = 1.5e-05

Table S23.  Gene #20: 'FAM5C MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 139 15 15 18 1
FAM5C MUTATED 4 0 0 0 1
FAM5C WILD-TYPE 135 15 15 18 0

Figure S23.  Get High-res Image Gene #20: 'FAM5C MUTATION STATUS' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

  • Mutation data file = LAML-TB.mutsig.cluster.txt

  • Molecular subtypes file = LAML-TB.transferedmergedcluster.txt

  • Number of patients = 197

  • Number of significantly mutated genes = 24

  • Number of Molecular subtypes = 6

  • Exclude genes that fewer than K tumors have mutations, K = 3

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.test' function in R

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[2] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[3] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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