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

Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)

22 February 2013 | analyses__2013_02_22

Maintainer Information

Citation Information

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C16971TV

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.

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] 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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