Correlation between gene mutation status and molecular subtypes
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.

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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