Correlation between copy number variations of arm-level result and selected clinical features
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between subtypes identified by 79 different clustering approaches and 5 clinical features across 447 patients, 57 significant findings detected with Q value < 0.25.

  • 2 subtypes identified in current cancer cohort by '1p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '1q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '2p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '2q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '3p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '3q gain mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '4p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '5p gain mutation analysis'. These subtypes correlate to 'Time to Death' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '5q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '6p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '6q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '7p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '7q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '8p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '8q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '9p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '9q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '10p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '10q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '11p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '11q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '12p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '12q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '13q gain mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '14q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '15q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '16p gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '16q gain mutation analysis'. These subtypes correlate to 'COMPLETENESS.OF.RESECTION'.

  • 2 subtypes identified in current cancer cohort by '17p gain mutation analysis'. These subtypes correlate to 'Time to Death'.

  • 2 subtypes identified in current cancer cohort by '17q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '18p gain mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '18q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '19p gain mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '19q gain mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '20p gain mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '20q gain mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '21q gain mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '22q gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by 'Xq gain mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '1p loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '1q loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '2p loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '2q loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '3p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '3q loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '4p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '4q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '5p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '5q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '6p loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '6q loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '7p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '7q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '8p loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '8q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '9p loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '9q loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '10p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '10q loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '11p loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '11q loss mutation analysis'. These subtypes correlate to 'Time to Death',  'AGE', and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '12p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '12q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '13q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '14q loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '15q loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '16p loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '16q loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '17p loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '17q loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '18p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '18q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '19p loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '19q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '20p loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '20q loss mutation analysis'. These subtypes do not correlate to any clinical features.

  • 2 subtypes identified in current cancer cohort by '21q loss mutation analysis'. These subtypes correlate to 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by '22q loss mutation analysis'. These subtypes correlate to 'AGE' and 'HISTOLOGICAL.TYPE'.

  • 2 subtypes identified in current cancer cohort by 'Xq loss mutation analysis'. These subtypes do not correlate to any clinical features.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between subtypes identified by 79 different clustering approaches and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 57 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE HISTOLOGICAL
TYPE 		RADIATIONS
RADIATION
REGIMENINDICATION 		COMPLETENESS
OF
RESECTION
Statistical Tests logrank test t-test Chi-square test Fisher's exact test Chi-square test
1p gain 0.0626
(1.00) 		0.0554
(1.00) 		0.0288
(1.00) 		0.417
(1.00) 		0.72
(1.00)
1q gain 0.576
(1.00) 		0.0491
(1.00) 		0.00183
(0.603) 		0.569
(1.00) 		0.0778
(1.00)
2p gain 0.0962
(1.00) 		0.0406
(1.00) 		0.0949
(1.00) 		0.614
(1.00) 		0.709
(1.00)
2q gain 0.112
(1.00) 		0.208
(1.00) 		0.13
(1.00) 		0.574
(1.00) 		0.335
(1.00)
3p gain 0.487
(1.00) 		0.413
(1.00) 		0.401
(1.00) 		0.0666
(1.00) 		0.505
(1.00)
3q gain 0.0467
(1.00) 		0.163
(1.00) 		0.000338
(0.116) 		0.602
(1.00) 		0.0792
(1.00)
4p gain 0.602
(1.00) 		0.0246
(1.00) 		0.00116
(0.387) 		0.637
(1.00) 		0.792
(1.00)
5p gain 2.87e-05
(0.0103) 		0.102
(1.00) 		1.6e-08
(6.02e-06) 		0.675
(1.00) 		0.0279
(1.00)
5q gain 0.322
(1.00) 		0.929
(1.00) 		0.00348
(1.00) 		1
(1.00) 		0.00647
(1.00)
6p gain 0.683
(1.00) 		0.404
(1.00) 		0.00206
(0.675) 		1
(1.00) 		0.677
(1.00)
6q gain 0.971
(1.00) 		0.411
(1.00) 		0.00587
(1.00) 		0.523
(1.00) 		0.648
(1.00)
7p gain 0.322
(1.00) 		0.714
(1.00) 		0.0961
(1.00) 		0.102
(1.00) 		0.792
(1.00)
7q gain 0.0185
(1.00) 		0.606
(1.00) 		0.783
(1.00) 		0.138
(1.00) 		0.379
(1.00)
8p gain 0.00124
(0.411) 		0.383
(1.00) 		0.812
(1.00) 		0.588
(1.00) 		0.257
(1.00)
8q gain 0.00654
(1.00) 		0.871
(1.00) 		0.0116
(1.00) 		0.714
(1.00) 		0.128
(1.00)
9p gain 0.793
(1.00) 		0.784
(1.00) 		0.446
(1.00) 		0.0388
(1.00) 		0.136
(1.00)
9q gain 0.797
(1.00) 		0.783
(1.00) 		0.0219
(1.00) 		0.558
(1.00)
10p gain 0.7
(1.00) 		0.513
(1.00) 		0.35
(1.00) 		0.894
(1.00) 		0.98
(1.00)
10q gain 0.848
(1.00) 		0.681
(1.00) 		0.355
(1.00) 		1
(1.00) 		0.417
(1.00)
11p gain 0.446
(1.00) 		0.648
(1.00) 		0.0434
(1.00) 		0.637
(1.00) 		0.287
(1.00)
11q gain 0.556
(1.00) 		0.705
(1.00) 		0.55
(1.00) 		1
(1.00) 		0.459
(1.00)
12p gain 0.59
(1.00) 		0.68
(1.00) 		0.0031
(1.00) 		0.845
(1.00) 		0.434
(1.00)
12q gain 0.713
(1.00) 		0.485
(1.00) 		0.443
(1.00) 		1
(1.00) 		0.369
(1.00)
13q gain 0.451
(1.00) 		0.000813
(0.274) 		5.47e-07
(0.000202) 		0.456
(1.00) 		0.528
(1.00)
14q gain 0.198
(1.00) 		0.634
(1.00) 		0.0176
(1.00) 		0.0476
(1.00) 		0.634
(1.00)
15q gain 0.0101
(1.00) 		0.508
(1.00) 		0.895
(1.00) 		0.328
(1.00) 		0.0669
(1.00)
16p gain 0.317
(1.00) 		0.126
(1.00) 		0.00479
(1.00) 		0.519
(1.00) 		0.798
(1.00)
16q gain 0.67
(1.00) 		0.482
(1.00) 		0.865
(1.00) 		0.323
(1.00) 		0.000419
(0.143)
17p gain 0.00055
(0.186) 		0.773
(1.00) 		0.55
(1.00) 		0.369
(1.00) 		0.162
(1.00)
17q gain 0.0785
(1.00) 		0.163
(1.00) 		0.501
(1.00) 		0.493
(1.00) 		0.0578
(1.00)
18p gain 0.0968
(1.00) 		0.000394
(0.135) 		5e-10
(1.9e-07) 		0.689
(1.00) 		0.0201
(1.00)
18q gain 0.00528
(1.00) 		0.0679
(1.00) 		0.00264
(0.864) 		0.413
(1.00) 		0.528
(1.00)
19p gain 0.0511
(1.00) 		4.84e-05
(0.0172) 		1.82e-05
(0.00658) 		0.175
(1.00) 		0.0897
(1.00)
19q gain 0.00766
(1.00) 		1.14e-05
(0.00411) 		1.44e-09
(5.44e-07) 		0.814
(1.00) 		0.22
(1.00)
20p gain 0.0118
(1.00) 		0.00541
(1.00) 		3.14e-07
(0.000117) 		0.0154
(1.00) 		0.0391
(1.00)
20q gain 0.0672
(1.00) 		0.0043
(1.00) 		1.46e-12
(5.65e-10) 		0.0154
(1.00) 		0.0124
(1.00)
21q gain 0.838
(1.00) 		0.00859
(1.00) 		3.88e-05
(0.0138) 		1
(1.00) 		0.984
(1.00)
22q gain 0.521
(1.00) 		0.0184
(1.00) 		0.00649
(1.00) 		1
(1.00) 		0.279
(1.00)
Xq gain 0.0894
(1.00) 		0.343
(1.00) 		0.0213
(1.00) 		1
(1.00) 		0.428
(1.00)
1p loss 0.266
(1.00) 		0.26
(1.00) 		0.00912
(1.00) 		0.316
(1.00) 		0.622
(1.00)
1q loss 0.013
(1.00) 		0.182
(1.00) 		0.0161
(1.00) 		0.323
(1.00) 		0.0628
(1.00)
2p loss 0.53
(1.00) 		0.071
(1.00) 		0.431
(1.00) 		0.186
(1.00) 		0.0321
(1.00)
2q loss 0.349
(1.00) 		0.0304
(1.00) 		0.373
(1.00) 		0.109
(1.00) 		0.0752
(1.00)
3p loss 0.118
(1.00) 		0.0183
(1.00) 		2.61e-05
(0.00938) 		0.828
(1.00) 		0.928
(1.00)
3q loss 0.228
(1.00) 		0.147
(1.00) 		0.0108
(1.00) 		0.523
(1.00) 		0.514
(1.00)
4p loss 0.0541
(1.00) 		0.00183
(0.604) 		5e-14
(1.95e-11) 		0.32
(1.00) 		0.075
(1.00)
4q loss 0.0357
(1.00) 		0.00949
(1.00) 		7.36e-10
(2.79e-07) 		0.0609
(1.00) 		0.756
(1.00)
5p loss 0.424
(1.00) 		0.89
(1.00) 		3.33e-07
(0.000124) 		0.807
(1.00) 		0.152
(1.00)
5q loss 0.945
(1.00) 		0.0199
(1.00) 		2.55e-12
(9.84e-10) 		0.338
(1.00) 		0.302
(1.00)
6p loss 0.208
(1.00) 		0.169
(1.00) 		0.0213
(1.00) 		0.43
(1.00) 		0.741
(1.00)
6q loss 0.671
(1.00) 		0.182
(1.00) 		0.0102
(1.00) 		0.461
(1.00) 		0.691
(1.00)
7p loss 0.361
(1.00) 		0.0105
(1.00) 		2.01e-05
(0.00722) 		1
(1.00) 		0.494
(1.00)
7q loss 0.839
(1.00) 		0.000941
(0.315) 		1.39e-10
(5.34e-08) 		1
(1.00) 		0.479
(1.00)
8p loss 0.509
(1.00) 		8.76e-05
(0.0308) 		8.42e-22
(3.31e-19) 		0.591
(1.00) 		0.718
(1.00)
8q loss 0.694
(1.00) 		0.609
(1.00) 		6.41e-08
(2.4e-05) 		0.68
(1.00) 		0.177
(1.00)
9p loss 0.846
(1.00) 		2.7e-06
(0.00098) 		1.5e-17
(5.88e-15) 		1
(1.00) 		0.391
(1.00)
9q loss 0.185
(1.00) 		4.23e-10
(1.62e-07) 		7.98e-15
(3.11e-12) 		0.423
(1.00) 		0.72
(1.00)
10p loss 0.0173
(1.00) 		0.0658
(1.00) 		0.00039
(0.134) 		1
(1.00) 		0.389
(1.00)
10q loss 0.364
(1.00) 		0.0313
(1.00) 		0.0852
(1.00) 		0.787
(1.00) 		0.686
(1.00)
11p loss 0.000927
(0.311) 		0.000108
(0.0377) 		2.02e-08
(7.59e-06) 		0.399
(1.00) 		0.586
(1.00)
11q loss 0.000216
(0.0748) 		0.00012
(0.0419) 		1.84e-07
(6.86e-05) 		0.205
(1.00) 		0.118
(1.00)
12p loss 0.178
(1.00) 		0.00777
(1.00) 		5.47e-07
(0.000202) 		0.608
(1.00) 		0.983
(1.00)
12q loss 0.454
(1.00) 		0.0255
(1.00) 		0.000479
(0.163) 		1
(1.00) 		0.507
(1.00)
13q loss 0.114
(1.00) 		0.00144
(0.477) 		8.93e-05
(0.0313) 		0.519
(1.00) 		0.695
(1.00)
14q loss 0.285
(1.00) 		0.000234
(0.0809) 		9.6e-11
(3.7e-08) 		1
(1.00) 		0.129
(1.00)
15q loss 0.754
(1.00) 		3.28e-05
(0.0117) 		7.09e-13
(2.75e-10) 		0.241
(1.00) 		0.911
(1.00)
16p loss 0.0273
(1.00) 		6.56e-05
(0.0232) 		4.52e-10
(1.72e-07) 		0.643
(1.00) 		0.0313
(1.00)
16q loss 0.0369
(1.00) 		2.36e-06
(0.000862) 		5.36e-16
(2.09e-13) 		0.254
(1.00) 		0.0608
(1.00)
17p loss 0.163
(1.00) 		1.53e-06
(0.000562) 		3.45e-23
(1.36e-20) 		0.431
(1.00) 		0.204
(1.00)
17q loss 0.977
(1.00) 		0.000598
(0.202) 		5.2e-07
(0.000193) 		0.162
(1.00) 		0.336
(1.00)
18p loss 0.227
(1.00) 		0.138
(1.00) 		0.000224
(0.0777) 		0.673
(1.00) 		0.196
(1.00)
18q loss 0.509
(1.00) 		0.0492
(1.00) 		1.54e-06
(0.000562) 		0.287
(1.00) 		0.507
(1.00)
19p loss 0.341
(1.00) 		0.861
(1.00) 		6.64e-09
(2.5e-06) 		1
(1.00) 		0.113
(1.00)
19q loss 0.564
(1.00) 		0.673
(1.00) 		6.49e-05
(0.023) 		0.814
(1.00) 		0.232
(1.00)
20p loss 0.647
(1.00) 		0.0805
(1.00) 		0.0153
(1.00) 		0.22
(1.00) 		0.514
(1.00)
20q loss 0.478
(1.00) 		0.238
(1.00) 		0.00112
(0.373) 		0.369
(1.00) 		0.741
(1.00)
21q loss 0.248
(1.00) 		0.449
(1.00) 		2.51e-06
(0.000915) 		0.376
(1.00) 		0.359
(1.00)
22q loss 0.00753
(1.00) 		0.000208
(0.0725) 		3.56e-10
(1.36e-07) 		0.33
(1.00) 		0.898
(1.00)
Xq loss 0.628
(1.00) 		0.164
(1.00) 		0.0153
(1.00) 		0.12
(1.00) 		0.0505
(1.00)
Clustering Approach #1: '1p gain mutation analysis'

Table S1.  Get Full Table Description of clustering approach #1: '1p gain mutation analysis'

Cluster Labels 1P GAIN MUTATED 1P GAIN WILD-TYPE
Number of samples 17 430
Clustering Approach #2: '1q gain mutation analysis'

Table S2.  Get Full Table Description of clustering approach #2: '1q gain mutation analysis'

Cluster Labels 1Q GAIN MUTATED 1Q GAIN WILD-TYPE
Number of samples 129 318
Clustering Approach #3: '2p gain mutation analysis'

Table S3.  Get Full Table Description of clustering approach #3: '2p gain mutation analysis'

Cluster Labels 2P GAIN MUTATED 2P GAIN WILD-TYPE
Number of samples 47 400
Clustering Approach #4: '2q gain mutation analysis'

Table S4.  Get Full Table Description of clustering approach #4: '2q gain mutation analysis'

Cluster Labels 2Q GAIN MUTATED 2Q GAIN WILD-TYPE
Number of samples 37 410
Clustering Approach #5: '3p gain mutation analysis'

Table S5.  Get Full Table Description of clustering approach #5: '3p gain mutation analysis'

Cluster Labels 3P GAIN MUTATED 3P GAIN WILD-TYPE
Number of samples 24 423
Clustering Approach #6: '3q gain mutation analysis'

Table S6.  Get Full Table Description of clustering approach #6: '3q gain mutation analysis'

Cluster Labels 3Q GAIN MUTATED 3Q GAIN WILD-TYPE
Number of samples 43 404
'3q gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 0.000338 (Chi-square test), Q value = 0.12

Table S7.  Clustering Approach #6: '3q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
3Q GAIN MUTATED 24 2 17
3Q GAIN WILD-TYPE 326 16 62

Figure S1.  Get High-res Image Clustering Approach #6: '3q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #7: '4p gain mutation analysis'

Table S8.  Get Full Table Description of clustering approach #7: '4p gain mutation analysis'

Cluster Labels 4P GAIN MUTATED 4P GAIN WILD-TYPE
Number of samples 5 442
Clustering Approach #8: '5p gain mutation analysis'

Table S9.  Get Full Table Description of clustering approach #8: '5p gain mutation analysis'

Cluster Labels 5P GAIN MUTATED 5P GAIN WILD-TYPE
Number of samples 29 418
'5p gain mutation analysis' versus 'Time to Death'

P value = 2.87e-05 (logrank test), Q value = 0.01

Table S10.  Clustering Approach #8: '5p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 442 41 0.0 - 187.1 (15.9)
5P GAIN MUTATED 28 8 0.1 - 59.0 (11.1)
5P GAIN WILD-TYPE 414 33 0.0 - 187.1 (16.2)

Figure S2.  Get High-res Image Clustering Approach #8: '5p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'5p gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.6e-08 (Chi-square test), Q value = 6e-06

Table S11.  Clustering Approach #8: '5p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
5P GAIN MUTATED 11 1 17
5P GAIN WILD-TYPE 339 17 62

Figure S3.  Get High-res Image Clustering Approach #8: '5p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #9: '5q gain mutation analysis'

Table S12.  Get Full Table Description of clustering approach #9: '5q gain mutation analysis'

Cluster Labels 5Q GAIN MUTATED 5Q GAIN WILD-TYPE
Number of samples 8 439
Clustering Approach #10: '6p gain mutation analysis'

Table S13.  Get Full Table Description of clustering approach #10: '6p gain mutation analysis'

Cluster Labels 6P GAIN MUTATED 6P GAIN WILD-TYPE
Number of samples 33 414
Clustering Approach #11: '6q gain mutation analysis'

Table S14.  Get Full Table Description of clustering approach #11: '6q gain mutation analysis'

Cluster Labels 6Q GAIN MUTATED 6Q GAIN WILD-TYPE
Number of samples 28 419
Clustering Approach #12: '7p gain mutation analysis'

Table S15.  Get Full Table Description of clustering approach #12: '7p gain mutation analysis'

Cluster Labels 7P GAIN MUTATED 7P GAIN WILD-TYPE
Number of samples 40 407
Clustering Approach #13: '7q gain mutation analysis'

Table S16.  Get Full Table Description of clustering approach #13: '7q gain mutation analysis'

Cluster Labels 7Q GAIN MUTATED 7Q GAIN WILD-TYPE
Number of samples 38 409
Clustering Approach #14: '8p gain mutation analysis'

Table S17.  Get Full Table Description of clustering approach #14: '8p gain mutation analysis'

Cluster Labels 8P GAIN MUTATED 8P GAIN WILD-TYPE
Number of samples 79 368
Clustering Approach #15: '8q gain mutation analysis'

Table S18.  Get Full Table Description of clustering approach #15: '8q gain mutation analysis'

Cluster Labels 8Q GAIN MUTATED 8Q GAIN WILD-TYPE
Number of samples 103 344
Clustering Approach #16: '9p gain mutation analysis'

Table S19.  Get Full Table Description of clustering approach #16: '9p gain mutation analysis'

Cluster Labels 9P GAIN MUTATED 9P GAIN WILD-TYPE
Number of samples 11 436
Clustering Approach #17: '9q gain mutation analysis'

Table S20.  Get Full Table Description of clustering approach #17: '9q gain mutation analysis'

Cluster Labels 9Q GAIN MUTATED 9Q GAIN WILD-TYPE
Number of samples 3 444
Clustering Approach #18: '10p gain mutation analysis'

Table S21.  Get Full Table Description of clustering approach #18: '10p gain mutation analysis'

Cluster Labels 10P GAIN MUTATED 10P GAIN WILD-TYPE
Number of samples 82 365
Clustering Approach #19: '10q gain mutation analysis'

Table S22.  Get Full Table Description of clustering approach #19: '10q gain mutation analysis'

Cluster Labels 10Q GAIN MUTATED 10Q GAIN WILD-TYPE
Number of samples 77 370
Clustering Approach #20: '11p gain mutation analysis'

Table S23.  Get Full Table Description of clustering approach #20: '11p gain mutation analysis'

Cluster Labels 11P GAIN MUTATED 11P GAIN WILD-TYPE
Number of samples 5 442
Clustering Approach #21: '11q gain mutation analysis'

Table S24.  Get Full Table Description of clustering approach #21: '11q gain mutation analysis'

Cluster Labels 11Q GAIN MUTATED 11Q GAIN WILD-TYPE
Number of samples 6 441
Clustering Approach #22: '12p gain mutation analysis'

Table S25.  Get Full Table Description of clustering approach #22: '12p gain mutation analysis'

Cluster Labels 12P GAIN MUTATED 12P GAIN WILD-TYPE
Number of samples 33 414
Clustering Approach #23: '12q gain mutation analysis'

Table S26.  Get Full Table Description of clustering approach #23: '12q gain mutation analysis'

Cluster Labels 12Q GAIN MUTATED 12Q GAIN WILD-TYPE
Number of samples 26 421
Clustering Approach #24: '13q gain mutation analysis'

Table S27.  Get Full Table Description of clustering approach #24: '13q gain mutation analysis'

Cluster Labels 13Q GAIN MUTATED 13Q GAIN WILD-TYPE
Number of samples 19 428
'13q gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 5.47e-07 (Chi-square test), Q value = 2e-04

Table S28.  Clustering Approach #24: '13q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
13Q GAIN MUTATED 6 1 12
13Q GAIN WILD-TYPE 344 17 67

Figure S4.  Get High-res Image Clustering Approach #24: '13q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #25: '14q gain mutation analysis'

Table S29.  Get Full Table Description of clustering approach #25: '14q gain mutation analysis'

Cluster Labels 14Q GAIN MUTATED 14Q GAIN WILD-TYPE
Number of samples 16 431
Clustering Approach #26: '15q gain mutation analysis'

Table S30.  Get Full Table Description of clustering approach #26: '15q gain mutation analysis'

Cluster Labels 15Q GAIN MUTATED 15Q GAIN WILD-TYPE
Number of samples 5 442
Clustering Approach #27: '16p gain mutation analysis'

Table S31.  Get Full Table Description of clustering approach #27: '16p gain mutation analysis'

Cluster Labels 16P GAIN MUTATED 16P GAIN WILD-TYPE
Number of samples 11 436
Clustering Approach #28: '16q gain mutation analysis'

Table S32.  Get Full Table Description of clustering approach #28: '16q gain mutation analysis'

Cluster Labels 16Q GAIN MUTATED 16Q GAIN WILD-TYPE
Number of samples 4 443
'16q gain mutation analysis' versus 'COMPLETENESS.OF.RESECTION'

P value = 0.000419 (Chi-square test), Q value = 0.14

Table S33.  Clustering Approach #28: '16q gain mutation analysis' versus Clinical Feature #5: 'COMPLETENESS.OF.RESECTION'

nPatients R0 R1 R2 RX
ALL 307 24 15 24
16Q GAIN MUTATED 1 2 0 0
16Q GAIN WILD-TYPE 306 22 15 24

Figure S5.  Get High-res Image Clustering Approach #28: '16q gain mutation analysis' versus Clinical Feature #5: 'COMPLETENESS.OF.RESECTION'

Clustering Approach #29: '17p gain mutation analysis'

Table S34.  Get Full Table Description of clustering approach #29: '17p gain mutation analysis'

Cluster Labels 17P GAIN MUTATED 17P GAIN WILD-TYPE
Number of samples 6 441
'17p gain mutation analysis' versus 'Time to Death'

P value = 0.00055 (logrank test), Q value = 0.19

Table S35.  Clustering Approach #29: '17p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 442 41 0.0 - 187.1 (15.9)
17P GAIN MUTATED 6 2 3.0 - 15.8 (12.1)
17P GAIN WILD-TYPE 436 39 0.0 - 187.1 (16.2)

Figure S6.  Get High-res Image Clustering Approach #29: '17p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

Clustering Approach #30: '17q gain mutation analysis'

Table S36.  Get Full Table Description of clustering approach #30: '17q gain mutation analysis'

Cluster Labels 17Q GAIN MUTATED 17Q GAIN WILD-TYPE
Number of samples 10 437
Clustering Approach #31: '18p gain mutation analysis'

Table S37.  Get Full Table Description of clustering approach #31: '18p gain mutation analysis'

Cluster Labels 18P GAIN MUTATED 18P GAIN WILD-TYPE
Number of samples 32 415
'18p gain mutation analysis' versus 'AGE'

P value = 0.000394 (t-test), Q value = 0.13

Table S38.  Clustering Approach #31: '18p gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
18P GAIN MUTATED 32 69.8 (9.2)
18P GAIN WILD-TYPE 414 63.1 (11.3)

Figure S7.  Get High-res Image Clustering Approach #31: '18p gain mutation analysis' versus Clinical Feature #2: 'AGE'

'18p gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 5e-10 (Chi-square test), Q value = 1.9e-07

Table S39.  Clustering Approach #31: '18p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
18P GAIN MUTATED 11 2 19
18P GAIN WILD-TYPE 339 16 60

Figure S8.  Get High-res Image Clustering Approach #31: '18p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #32: '18q gain mutation analysis'

Table S40.  Get Full Table Description of clustering approach #32: '18q gain mutation analysis'

Cluster Labels 18Q GAIN MUTATED 18Q GAIN WILD-TYPE
Number of samples 16 431
Clustering Approach #33: '19p gain mutation analysis'

Table S41.  Get Full Table Description of clustering approach #33: '19p gain mutation analysis'

Cluster Labels 19P GAIN MUTATED 19P GAIN WILD-TYPE
Number of samples 25 422
'19p gain mutation analysis' versus 'AGE'

P value = 4.84e-05 (t-test), Q value = 0.017

Table S42.  Clustering Approach #33: '19p gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
19P GAIN MUTATED 25 70.9 (7.7)
19P GAIN WILD-TYPE 421 63.1 (11.3)

Figure S9.  Get High-res Image Clustering Approach #33: '19p gain mutation analysis' versus Clinical Feature #2: 'AGE'

'19p gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.82e-05 (Chi-square test), Q value = 0.0066

Table S43.  Clustering Approach #33: '19p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
19P GAIN MUTATED 12 0 13
19P GAIN WILD-TYPE 338 18 66

Figure S10.  Get High-res Image Clustering Approach #33: '19p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #34: '19q gain mutation analysis'

Table S44.  Get Full Table Description of clustering approach #34: '19q gain mutation analysis'

Cluster Labels 19Q GAIN MUTATED 19Q GAIN WILD-TYPE
Number of samples 22 425
'19q gain mutation analysis' versus 'AGE'

P value = 1.14e-05 (t-test), Q value = 0.0041

Table S45.  Clustering Approach #34: '19q gain mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
19Q GAIN MUTATED 22 72.4 (7.6)
19Q GAIN WILD-TYPE 424 63.1 (11.2)

Figure S11.  Get High-res Image Clustering Approach #34: '19q gain mutation analysis' versus Clinical Feature #2: 'AGE'

'19q gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.44e-09 (Chi-square test), Q value = 5.4e-07

Table S46.  Clustering Approach #34: '19q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
19Q GAIN MUTATED 7 0 15
19Q GAIN WILD-TYPE 343 18 64

Figure S12.  Get High-res Image Clustering Approach #34: '19q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #35: '20p gain mutation analysis'

Table S47.  Get Full Table Description of clustering approach #35: '20p gain mutation analysis'

Cluster Labels 20P GAIN MUTATED 20P GAIN WILD-TYPE
Number of samples 52 395
'20p gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 3.14e-07 (Chi-square test), Q value = 0.00012

Table S48.  Clustering Approach #35: '20p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
20P GAIN MUTATED 26 3 23
20P GAIN WILD-TYPE 324 15 56

Figure S13.  Get High-res Image Clustering Approach #35: '20p gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #36: '20q gain mutation analysis'

Table S49.  Get Full Table Description of clustering approach #36: '20q gain mutation analysis'

Cluster Labels 20Q GAIN MUTATED 20Q GAIN WILD-TYPE
Number of samples 61 386
'20q gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.46e-12 (Chi-square test), Q value = 5.7e-10

Table S50.  Clustering Approach #36: '20q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
20Q GAIN MUTATED 27 3 31
20Q GAIN WILD-TYPE 323 15 48

Figure S14.  Get High-res Image Clustering Approach #36: '20q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #37: '21q gain mutation analysis'

Table S51.  Get Full Table Description of clustering approach #37: '21q gain mutation analysis'

Cluster Labels 21Q GAIN MUTATED 21Q GAIN WILD-TYPE
Number of samples 20 427
'21q gain mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 3.88e-05 (Chi-square test), Q value = 0.014

Table S52.  Clustering Approach #37: '21q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
21Q GAIN MUTATED 9 0 11
21Q GAIN WILD-TYPE 341 18 68

Figure S15.  Get High-res Image Clustering Approach #37: '21q gain mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #38: '22q gain mutation analysis'

Table S53.  Get Full Table Description of clustering approach #38: '22q gain mutation analysis'

Cluster Labels 22Q GAIN MUTATED 22Q GAIN WILD-TYPE
Number of samples 6 441
Clustering Approach #39: 'Xq gain mutation analysis'

Table S54.  Get Full Table Description of clustering approach #39: 'Xq gain mutation analysis'

Cluster Labels XQ GAIN MUTATED XQ GAIN WILD-TYPE
Number of samples 7 440
Clustering Approach #40: '1p loss mutation analysis'

Table S55.  Get Full Table Description of clustering approach #40: '1p loss mutation analysis'

Cluster Labels 1P LOSS MUTATED 1P LOSS WILD-TYPE
Number of samples 11 436
Clustering Approach #41: '1q loss mutation analysis'

Table S56.  Get Full Table Description of clustering approach #41: '1q loss mutation analysis'

Cluster Labels 1Q LOSS MUTATED 1Q LOSS WILD-TYPE
Number of samples 4 443
Clustering Approach #42: '2p loss mutation analysis'

Table S57.  Get Full Table Description of clustering approach #42: '2p loss mutation analysis'

Cluster Labels 2P LOSS MUTATED 2P LOSS WILD-TYPE
Number of samples 6 441
Clustering Approach #43: '2q loss mutation analysis'

Table S58.  Get Full Table Description of clustering approach #43: '2q loss mutation analysis'

Cluster Labels 2Q LOSS MUTATED 2Q LOSS WILD-TYPE
Number of samples 7 440
Clustering Approach #44: '3p loss mutation analysis'

Table S59.  Get Full Table Description of clustering approach #44: '3p loss mutation analysis'

Cluster Labels 3P LOSS MUTATED 3P LOSS WILD-TYPE
Number of samples 26 421
'3p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.61e-05 (Chi-square test), Q value = 0.0094

Table S60.  Clustering Approach #44: '3p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
3P LOSS MUTATED 11 3 12
3P LOSS WILD-TYPE 339 15 67

Figure S16.  Get High-res Image Clustering Approach #44: '3p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #45: '3q loss mutation analysis'

Table S61.  Get Full Table Description of clustering approach #45: '3q loss mutation analysis'

Cluster Labels 3Q LOSS MUTATED 3Q LOSS WILD-TYPE
Number of samples 12 435
Clustering Approach #46: '4p loss mutation analysis'

Table S62.  Get Full Table Description of clustering approach #46: '4p loss mutation analysis'

Cluster Labels 4P LOSS MUTATED 4P LOSS WILD-TYPE
Number of samples 49 398
'4p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 5e-14 (Chi-square test), Q value = 1.9e-11

Table S63.  Clustering Approach #46: '4p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
4P LOSS MUTATED 18 3 28
4P LOSS WILD-TYPE 332 15 51

Figure S17.  Get High-res Image Clustering Approach #46: '4p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #47: '4q loss mutation analysis'

Table S64.  Get Full Table Description of clustering approach #47: '4q loss mutation analysis'

Cluster Labels 4Q LOSS MUTATED 4Q LOSS WILD-TYPE
Number of samples 46 401
'4q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 7.36e-10 (Chi-square test), Q value = 2.8e-07

Table S65.  Clustering Approach #47: '4q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
4Q LOSS MUTATED 19 4 23
4Q LOSS WILD-TYPE 331 14 56

Figure S18.  Get High-res Image Clustering Approach #47: '4q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #48: '5p loss mutation analysis'

Table S66.  Get Full Table Description of clustering approach #48: '5p loss mutation analysis'

Cluster Labels 5P LOSS MUTATED 5P LOSS WILD-TYPE
Number of samples 21 426
'5p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 3.33e-07 (Chi-square test), Q value = 0.00012

Table S67.  Clustering Approach #48: '5p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
5P LOSS MUTATED 8 0 13
5P LOSS WILD-TYPE 342 18 66

Figure S19.  Get High-res Image Clustering Approach #48: '5p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #49: '5q loss mutation analysis'

Table S68.  Get Full Table Description of clustering approach #49: '5q loss mutation analysis'

Cluster Labels 5Q LOSS MUTATED 5Q LOSS WILD-TYPE
Number of samples 35 412
'5q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.55e-12 (Chi-square test), Q value = 9.8e-10

Table S69.  Clustering Approach #49: '5q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
5Q LOSS MUTATED 12 1 22
5Q LOSS WILD-TYPE 338 17 57

Figure S20.  Get High-res Image Clustering Approach #49: '5q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #50: '6p loss mutation analysis'

Table S70.  Get Full Table Description of clustering approach #50: '6p loss mutation analysis'

Cluster Labels 6P LOSS MUTATED 6P LOSS WILD-TYPE
Number of samples 7 440
Clustering Approach #51: '6q loss mutation analysis'

Table S71.  Get Full Table Description of clustering approach #51: '6q loss mutation analysis'

Cluster Labels 6Q LOSS MUTATED 6Q LOSS WILD-TYPE
Number of samples 9 438
Clustering Approach #52: '7p loss mutation analysis'

Table S72.  Get Full Table Description of clustering approach #52: '7p loss mutation analysis'

Cluster Labels 7P LOSS MUTATED 7P LOSS WILD-TYPE
Number of samples 25 422
'7p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.01e-05 (Chi-square test), Q value = 0.0072

Table S73.  Clustering Approach #52: '7p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
7P LOSS MUTATED 11 1 13
7P LOSS WILD-TYPE 339 17 66

Figure S21.  Get High-res Image Clustering Approach #52: '7p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #53: '7q loss mutation analysis'

Table S74.  Get Full Table Description of clustering approach #53: '7q loss mutation analysis'

Cluster Labels 7Q LOSS MUTATED 7Q LOSS WILD-TYPE
Number of samples 23 424
'7q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.39e-10 (Chi-square test), Q value = 5.3e-08

Table S75.  Clustering Approach #53: '7q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
7Q LOSS MUTATED 6 1 16
7Q LOSS WILD-TYPE 344 17 63

Figure S22.  Get High-res Image Clustering Approach #53: '7q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #54: '8p loss mutation analysis'

Table S76.  Get Full Table Description of clustering approach #54: '8p loss mutation analysis'

Cluster Labels 8P LOSS MUTATED 8P LOSS WILD-TYPE
Number of samples 41 406
'8p loss mutation analysis' versus 'AGE'

P value = 8.76e-05 (t-test), Q value = 0.031

Table S77.  Clustering Approach #54: '8p loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
8P LOSS MUTATED 41 68.3 (7.0)
8P LOSS WILD-TYPE 405 63.1 (11.5)

Figure S23.  Get High-res Image Clustering Approach #54: '8p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'8p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 8.42e-22 (Chi-square test), Q value = 3.3e-19

Table S78.  Clustering Approach #54: '8p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
8P LOSS MUTATED 9 2 30
8P LOSS WILD-TYPE 341 16 49

Figure S24.  Get High-res Image Clustering Approach #54: '8p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #55: '8q loss mutation analysis'

Table S79.  Get Full Table Description of clustering approach #55: '8q loss mutation analysis'

Cluster Labels 8Q LOSS MUTATED 8Q LOSS WILD-TYPE
Number of samples 7 440
'8q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 6.41e-08 (Chi-square test), Q value = 2.4e-05

Table S80.  Clustering Approach #55: '8q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
8Q LOSS MUTATED 0 0 7
8Q LOSS WILD-TYPE 350 18 72

Figure S25.  Get High-res Image Clustering Approach #55: '8q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #56: '9p loss mutation analysis'

Table S81.  Get Full Table Description of clustering approach #56: '9p loss mutation analysis'

Cluster Labels 9P LOSS MUTATED 9P LOSS WILD-TYPE
Number of samples 65 382
'9p loss mutation analysis' versus 'AGE'

P value = 2.7e-06 (t-test), Q value = 0.00098

Table S82.  Clustering Approach #56: '9p loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
9P LOSS MUTATED 65 68.9 (8.9)
9P LOSS WILD-TYPE 381 62.7 (11.4)

Figure S26.  Get High-res Image Clustering Approach #56: '9p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'9p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.5e-17 (Chi-square test), Q value = 5.9e-15

Table S83.  Clustering Approach #56: '9p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
9P LOSS MUTATED 25 4 36
9P LOSS WILD-TYPE 325 14 43

Figure S27.  Get High-res Image Clustering Approach #56: '9p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #57: '9q loss mutation analysis'

Table S84.  Get Full Table Description of clustering approach #57: '9q loss mutation analysis'

Cluster Labels 9Q LOSS MUTATED 9Q LOSS WILD-TYPE
Number of samples 82 365
'9q loss mutation analysis' versus 'AGE'

P value = 4.23e-10 (t-test), Q value = 1.6e-07

Table S85.  Clustering Approach #57: '9q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
9Q LOSS MUTATED 82 69.7 (8.7)
9Q LOSS WILD-TYPE 364 62.2 (11.3)

Figure S28.  Get High-res Image Clustering Approach #57: '9q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'9q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 7.98e-15 (Chi-square test), Q value = 3.1e-12

Table S86.  Clustering Approach #57: '9q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
9Q LOSS MUTATED 38 5 39
9Q LOSS WILD-TYPE 312 13 40

Figure S29.  Get High-res Image Clustering Approach #57: '9q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #58: '10p loss mutation analysis'

Table S87.  Get Full Table Description of clustering approach #58: '10p loss mutation analysis'

Cluster Labels 10P LOSS MUTATED 10P LOSS WILD-TYPE
Number of samples 17 430
'10p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 0.00039 (Chi-square test), Q value = 0.13

Table S88.  Clustering Approach #58: '10p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
10P LOSS MUTATED 7 1 9
10P LOSS WILD-TYPE 343 17 70

Figure S30.  Get High-res Image Clustering Approach #58: '10p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #59: '10q loss mutation analysis'

Table S89.  Get Full Table Description of clustering approach #59: '10q loss mutation analysis'

Cluster Labels 10Q LOSS MUTATED 10Q LOSS WILD-TYPE
Number of samples 16 431
Clustering Approach #60: '11p loss mutation analysis'

Table S90.  Get Full Table Description of clustering approach #60: '11p loss mutation analysis'

Cluster Labels 11P LOSS MUTATED 11P LOSS WILD-TYPE
Number of samples 47 400
'11p loss mutation analysis' versus 'AGE'

P value = 0.000108 (t-test), Q value = 0.038

Table S91.  Clustering Approach #60: '11p loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
11P LOSS MUTATED 47 69.2 (9.7)
11P LOSS WILD-TYPE 399 62.9 (11.3)

Figure S31.  Get High-res Image Clustering Approach #60: '11p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'11p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.02e-08 (Chi-square test), Q value = 7.6e-06

Table S92.  Clustering Approach #60: '11p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
11P LOSS MUTATED 21 4 22
11P LOSS WILD-TYPE 329 14 57

Figure S32.  Get High-res Image Clustering Approach #60: '11p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #61: '11q loss mutation analysis'

Table S93.  Get Full Table Description of clustering approach #61: '11q loss mutation analysis'

Cluster Labels 11Q LOSS MUTATED 11Q LOSS WILD-TYPE
Number of samples 39 408
'11q loss mutation analysis' versus 'Time to Death'

P value = 0.000216 (logrank test), Q value = 0.075

Table S94.  Clustering Approach #61: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 442 41 0.0 - 187.1 (15.9)
11Q LOSS MUTATED 37 8 0.0 - 91.0 (11.8)
11Q LOSS WILD-TYPE 405 33 0.0 - 187.1 (16.3)

Figure S33.  Get High-res Image Clustering Approach #61: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'11q loss mutation analysis' versus 'AGE'

P value = 0.00012 (t-test), Q value = 0.042

Table S95.  Clustering Approach #61: '11q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
11Q LOSS MUTATED 39 69.7 (9.3)
11Q LOSS WILD-TYPE 407 63.0 (11.3)

Figure S34.  Get High-res Image Clustering Approach #61: '11q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'11q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.84e-07 (Chi-square test), Q value = 6.9e-05

Table S96.  Clustering Approach #61: '11q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
11Q LOSS MUTATED 17 5 17
11Q LOSS WILD-TYPE 333 13 62

Figure S35.  Get High-res Image Clustering Approach #61: '11q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #62: '12p loss mutation analysis'

Table S97.  Get Full Table Description of clustering approach #62: '12p loss mutation analysis'

Cluster Labels 12P LOSS MUTATED 12P LOSS WILD-TYPE
Number of samples 19 428
'12p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 5.47e-07 (Chi-square test), Q value = 2e-04

Table S98.  Clustering Approach #62: '12p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
12P LOSS MUTATED 6 1 12
12P LOSS WILD-TYPE 344 17 67

Figure S36.  Get High-res Image Clustering Approach #62: '12p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #63: '12q loss mutation analysis'

Table S99.  Get Full Table Description of clustering approach #63: '12q loss mutation analysis'

Cluster Labels 12Q LOSS MUTATED 12Q LOSS WILD-TYPE
Number of samples 12 435
'12q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 0.000479 (Chi-square test), Q value = 0.16

Table S100.  Clustering Approach #63: '12q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
12Q LOSS MUTATED 4 1 7
12Q LOSS WILD-TYPE 346 17 72

Figure S37.  Get High-res Image Clustering Approach #63: '12q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #64: '13q loss mutation analysis'

Table S101.  Get Full Table Description of clustering approach #64: '13q loss mutation analysis'

Cluster Labels 13Q LOSS MUTATED 13Q LOSS WILD-TYPE
Number of samples 52 395
'13q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 8.93e-05 (Chi-square test), Q value = 0.031

Table S102.  Clustering Approach #64: '13q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
13Q LOSS MUTATED 29 3 20
13Q LOSS WILD-TYPE 321 15 59

Figure S38.  Get High-res Image Clustering Approach #64: '13q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #65: '14q loss mutation analysis'

Table S103.  Get Full Table Description of clustering approach #65: '14q loss mutation analysis'

Cluster Labels 14Q LOSS MUTATED 14Q LOSS WILD-TYPE
Number of samples 37 410
'14q loss mutation analysis' versus 'AGE'

P value = 0.000234 (t-test), Q value = 0.081

Table S104.  Clustering Approach #65: '14q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
14Q LOSS MUTATED 37 69.2 (8.7)
14Q LOSS WILD-TYPE 409 63.1 (11.3)

Figure S39.  Get High-res Image Clustering Approach #65: '14q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'14q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 9.6e-11 (Chi-square test), Q value = 3.7e-08

Table S105.  Clustering Approach #65: '14q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
14Q LOSS MUTATED 13 3 21
14Q LOSS WILD-TYPE 337 15 58

Figure S40.  Get High-res Image Clustering Approach #65: '14q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #66: '15q loss mutation analysis'

Table S106.  Get Full Table Description of clustering approach #66: '15q loss mutation analysis'

Cluster Labels 15Q LOSS MUTATED 15Q LOSS WILD-TYPE
Number of samples 65 382
'15q loss mutation analysis' versus 'AGE'

P value = 3.28e-05 (t-test), Q value = 0.012

Table S107.  Clustering Approach #66: '15q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
15Q LOSS MUTATED 65 69.0 (10.8)
15Q LOSS WILD-TYPE 381 62.6 (11.1)

Figure S41.  Get High-res Image Clustering Approach #66: '15q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'15q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 7.09e-13 (Chi-square test), Q value = 2.8e-10

Table S108.  Clustering Approach #66: '15q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
15Q LOSS MUTATED 28 6 31
15Q LOSS WILD-TYPE 322 12 48

Figure S42.  Get High-res Image Clustering Approach #66: '15q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #67: '16p loss mutation analysis'

Table S109.  Get Full Table Description of clustering approach #67: '16p loss mutation analysis'

Cluster Labels 16P LOSS MUTATED 16P LOSS WILD-TYPE
Number of samples 56 391
'16p loss mutation analysis' versus 'AGE'

P value = 6.56e-05 (t-test), Q value = 0.023

Table S110.  Clustering Approach #67: '16p loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
16P LOSS MUTATED 56 68.9 (9.8)
16P LOSS WILD-TYPE 390 62.8 (11.3)

Figure S43.  Get High-res Image Clustering Approach #67: '16p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'16p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 4.52e-10 (Chi-square test), Q value = 1.7e-07

Table S111.  Clustering Approach #67: '16p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
16P LOSS MUTATED 25 5 26
16P LOSS WILD-TYPE 325 13 53

Figure S44.  Get High-res Image Clustering Approach #67: '16p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #68: '16q loss mutation analysis'

Table S112.  Get Full Table Description of clustering approach #68: '16q loss mutation analysis'

Cluster Labels 16Q LOSS MUTATED 16Q LOSS WILD-TYPE
Number of samples 93 354
'16q loss mutation analysis' versus 'AGE'

P value = 2.36e-06 (t-test), Q value = 0.00086

Table S113.  Clustering Approach #68: '16q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
16Q LOSS MUTATED 93 68.0 (9.4)
16Q LOSS WILD-TYPE 353 62.4 (11.4)

Figure S45.  Get High-res Image Clustering Approach #68: '16q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'16q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 5.36e-16 (Chi-square test), Q value = 2.1e-13

Table S114.  Clustering Approach #68: '16q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
16Q LOSS MUTATED 44 6 43
16Q LOSS WILD-TYPE 306 12 36

Figure S46.  Get High-res Image Clustering Approach #68: '16q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #69: '17p loss mutation analysis'

Table S115.  Get Full Table Description of clustering approach #69: '17p loss mutation analysis'

Cluster Labels 17P LOSS MUTATED 17P LOSS WILD-TYPE
Number of samples 86 361
'17p loss mutation analysis' versus 'AGE'

P value = 1.53e-06 (t-test), Q value = 0.00056

Table S116.  Clustering Approach #69: '17p loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
17P LOSS MUTATED 86 68.4 (9.5)
17P LOSS WILD-TYPE 360 62.4 (11.3)

Figure S47.  Get High-res Image Clustering Approach #69: '17p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'17p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 3.45e-23 (Chi-square test), Q value = 1.4e-20

Table S117.  Clustering Approach #69: '17p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
17P LOSS MUTATED 33 7 46
17P LOSS WILD-TYPE 317 11 33

Figure S48.  Get High-res Image Clustering Approach #69: '17p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #70: '17q loss mutation analysis'

Table S118.  Get Full Table Description of clustering approach #70: '17q loss mutation analysis'

Cluster Labels 17Q LOSS MUTATED 17Q LOSS WILD-TYPE
Number of samples 57 390
'17q loss mutation analysis' versus 'AGE'

P value = 0.000598 (t-test), Q value = 0.2

Table S119.  Clustering Approach #70: '17q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
17Q LOSS MUTATED 57 68.4 (10.8)
17Q LOSS WILD-TYPE 389 62.9 (11.2)

Figure S49.  Get High-res Image Clustering Approach #70: '17q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'17q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 5.2e-07 (Chi-square test), Q value = 0.00019

Table S120.  Clustering Approach #70: '17q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
17Q LOSS MUTATED 29 5 23
17Q LOSS WILD-TYPE 321 13 56

Figure S50.  Get High-res Image Clustering Approach #70: '17q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #71: '18p loss mutation analysis'

Table S121.  Get Full Table Description of clustering approach #71: '18p loss mutation analysis'

Cluster Labels 18P LOSS MUTATED 18P LOSS WILD-TYPE
Number of samples 28 419
'18p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 0.000224 (Chi-square test), Q value = 0.078

Table S122.  Clustering Approach #71: '18p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
18P LOSS MUTATED 16 5 7
18P LOSS WILD-TYPE 334 13 72

Figure S51.  Get High-res Image Clustering Approach #71: '18p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #72: '18q loss mutation analysis'

Table S123.  Get Full Table Description of clustering approach #72: '18q loss mutation analysis'

Cluster Labels 18Q LOSS MUTATED 18Q LOSS WILD-TYPE
Number of samples 41 406
'18q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 1.54e-06 (Chi-square test), Q value = 0.00056

Table S124.  Clustering Approach #72: '18q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
18Q LOSS MUTATED 20 6 15
18Q LOSS WILD-TYPE 330 12 64

Figure S52.  Get High-res Image Clustering Approach #72: '18q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #73: '19p loss mutation analysis'

Table S125.  Get Full Table Description of clustering approach #73: '19p loss mutation analysis'

Cluster Labels 19P LOSS MUTATED 19P LOSS WILD-TYPE
Number of samples 29 418
'19p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 6.64e-09 (Chi-square test), Q value = 2.5e-06

Table S126.  Clustering Approach #73: '19p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
19P LOSS MUTATED 10 2 17
19P LOSS WILD-TYPE 340 16 62

Figure S53.  Get High-res Image Clustering Approach #73: '19p loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #74: '19q loss mutation analysis'

Table S127.  Get Full Table Description of clustering approach #74: '19q loss mutation analysis'

Cluster Labels 19Q LOSS MUTATED 19Q LOSS WILD-TYPE
Number of samples 22 425
'19q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 6.49e-05 (Chi-square test), Q value = 0.023

Table S128.  Clustering Approach #74: '19q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
19Q LOSS MUTATED 9 2 11
19Q LOSS WILD-TYPE 341 16 68

Figure S54.  Get High-res Image Clustering Approach #74: '19q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #75: '20p loss mutation analysis'

Table S129.  Get Full Table Description of clustering approach #75: '20p loss mutation analysis'

Cluster Labels 20P LOSS MUTATED 20P LOSS WILD-TYPE
Number of samples 13 434
Clustering Approach #76: '20q loss mutation analysis'

Table S130.  Get Full Table Description of clustering approach #76: '20q loss mutation analysis'

Cluster Labels 20Q LOSS MUTATED 20Q LOSS WILD-TYPE
Number of samples 6 441
Clustering Approach #77: '21q loss mutation analysis'

Table S131.  Get Full Table Description of clustering approach #77: '21q loss mutation analysis'

Cluster Labels 21Q LOSS MUTATED 21Q LOSS WILD-TYPE
Number of samples 26 421
'21q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.51e-06 (Chi-square test), Q value = 0.00092

Table S132.  Clustering Approach #77: '21q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
21Q LOSS MUTATED 10 3 13
21Q LOSS WILD-TYPE 340 15 66

Figure S55.  Get High-res Image Clustering Approach #77: '21q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #78: '22q loss mutation analysis'

Table S133.  Get Full Table Description of clustering approach #78: '22q loss mutation analysis'

Cluster Labels 22Q LOSS MUTATED 22Q LOSS WILD-TYPE
Number of samples 73 374
'22q loss mutation analysis' versus 'AGE'

P value = 0.000208 (t-test), Q value = 0.072

Table S134.  Clustering Approach #78: '22q loss mutation analysis' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 446 63.6 (11.3)
22Q LOSS MUTATED 73 67.5 (9.1)
22Q LOSS WILD-TYPE 373 62.8 (11.5)

Figure S56.  Get High-res Image Clustering Approach #78: '22q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'22q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 3.56e-10 (Chi-square test), Q value = 1.4e-07

Table S135.  Clustering Approach #78: '22q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

nPatients ENDOMETRIOID ENDOMETRIAL ADENOCARCINOMA MIXED SEROUS AND ENDOMETRIOID SEROUS ENDOMETRIAL ADENOCARCINOMA
ALL 350 18 79
22Q LOSS MUTATED 36 6 31
22Q LOSS WILD-TYPE 314 12 48

Figure S57.  Get High-res Image Clustering Approach #78: '22q loss mutation analysis' versus Clinical Feature #3: 'HISTOLOGICAL.TYPE'

Clustering Approach #79: 'Xq loss mutation analysis'

Table S136.  Get Full Table Description of clustering approach #79: 'Xq loss mutation analysis'

Cluster Labels XQ LOSS MUTATED XQ LOSS WILD-TYPE
Number of samples 13 434
Methods & Data
Input

  • Cluster data file = broad_values_by_arm.mutsig.cluster.txt

  • Clinical data file = UCEC-TP.clin.merged.picked.txt

  • Number of patients = 447

  • Number of clustering approaches = 79

  • Number of selected clinical features = 5

  • Exclude small clusters that include fewer than K patients, K = 3

Survival analysis

For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between two tumor subtypes using 't.test' function in R

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 clinical features, 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] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[4] 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)
[5] 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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