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

Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)

Overview

Introduction

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

Summary

Testing the association between copy number variation 73 arm-level results and 10 clinical features across 158 patients, one significant finding detected with Q value < 0.25.

12p loss cnv correlated to 'PATHOLOGY.N'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 73 arm-level results and 10 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, one significant finding detected.


		Clinical Features	Time to Death	AGE	GENDER	HISTOLOGICAL TYPE	PATHOLOGY T	PATHOLOGY N	PATHOLOGICSPREAD(M)	TUMOR STAGE	RADIATIONS RADIATION REGIMENINDICATION	NEOADJUVANT THERAPY
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Chi-square test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
12p loss	12 (8%)	146	0.201 (1.00)	0.825 (1.00)	0.134 (1.00)	0.263 (1.00)	0.225 (1.00)	0.000269 (0.192)	0.526 (1.00)	0.00222 (1.00)	1 (1.00)	1 (1.00)
1p gain	3 (2%)	155		0.59 (1.00)	1 (1.00)	0.821 (1.00)			0.171 (1.00)		1 (1.00)	1 (1.00)
1q gain	19 (12%)	139	0.673 (1.00)	0.513 (1.00)	0.621 (1.00)	0.33 (1.00)	0.463 (1.00)	0.102 (1.00)	0.217 (1.00)	0.286 (1.00)	0.11 (1.00)	0.13 (1.00)
2p gain	12 (8%)	146	0.688 (1.00)	0.19 (1.00)	1 (1.00)	0.42 (1.00)	0.109 (1.00)	0.304 (1.00)	1 (1.00)	0.038 (1.00)	1 (1.00)	1 (1.00)
2q gain	12 (8%)	146	0.42 (1.00)	0.52 (1.00)	0.537 (1.00)	0.42 (1.00)	0.249 (1.00)	0.304 (1.00)	0.8 (1.00)	0.192 (1.00)	1 (1.00)	1 (1.00)
3p gain	3 (2%)	155		0.637 (1.00)	1 (1.00)	0.821 (1.00)	0.58 (1.00)	0.843 (1.00)	1 (1.00)	0.604 (1.00)	1 (1.00)	1 (1.00)
3q gain	14 (9%)	144	0.361 (1.00)	0.0729 (1.00)	0.0817 (1.00)	0.561 (1.00)	0.953 (1.00)	0.589 (1.00)	0.37 (1.00)	0.97 (1.00)	1 (1.00)	1 (1.00)
5p gain	26 (16%)	132	0.987 (1.00)	0.928 (1.00)	0.509 (1.00)	0.144 (1.00)	0.236 (1.00)	0.815 (1.00)	0.329 (1.00)	0.0262 (1.00)	1 (1.00)	1 (1.00)
5q gain	5 (3%)	153	0.246 (1.00)	0.831 (1.00)	0.65 (1.00)	0.00323 (1.00)	0.755 (1.00)	0.658 (1.00)	1 (1.00)	0.407 (1.00)	1 (1.00)	1 (1.00)
6p gain	13 (8%)	145	0.791 (1.00)	0.782 (1.00)	0.243 (1.00)	0.712 (1.00)	0.12 (1.00)	0.725 (1.00)	0.818 (1.00)	0.479 (1.00)	0.353 (1.00)	1 (1.00)
6q gain	12 (8%)	146	0.361 (1.00)	0.84 (1.00)	0.374 (1.00)	0.711 (1.00)	0.272 (1.00)	0.65 (1.00)	0.398 (1.00)	0.698 (1.00)	0.33 (1.00)	0.593 (1.00)
7p gain	51 (32%)	107	0.576 (1.00)	0.0207 (1.00)	0.294 (1.00)	0.2 (1.00)	0.655 (1.00)	0.179 (1.00)	0.819 (1.00)	0.23 (1.00)	0.658 (1.00)	0.747 (1.00)
7q gain	45 (28%)	113	0.821 (1.00)	0.00752 (1.00)	0.474 (1.00)	0.333 (1.00)	0.695 (1.00)	0.257 (1.00)	0.286 (1.00)	0.199 (1.00)	1 (1.00)	1 (1.00)
8p gain	53 (34%)	105	0.395 (1.00)	0.0375 (1.00)	0.118 (1.00)	0.122 (1.00)	0.319 (1.00)	0.731 (1.00)	0.222 (1.00)	0.486 (1.00)	0.335 (1.00)	0.509 (1.00)
8q gain	72 (46%)	86	0.52 (1.00)	0.0284 (1.00)	0.0716 (1.00)	0.303 (1.00)	0.128 (1.00)	0.314 (1.00)	0.249 (1.00)	0.268 (1.00)	0.66 (1.00)	0.55 (1.00)
9p gain	11 (7%)	147	0.807 (1.00)	0.349 (1.00)	0.335 (1.00)	0.657 (1.00)	0.0623 (1.00)	0.0732 (1.00)	1 (1.00)	0.00934 (1.00)	0.306 (1.00)	0.56 (1.00)
9q gain	15 (9%)	143	0.823 (1.00)	0.212 (1.00)	0.578 (1.00)	0.94 (1.00)	0.265 (1.00)	0.0557 (1.00)	0.585 (1.00)	0.215 (1.00)	0.397 (1.00)	1 (1.00)
10p gain	24 (15%)	134	0.978 (1.00)	0.715 (1.00)	1 (1.00)	0.465 (1.00)	0.0346 (1.00)	0.661 (1.00)	0.447 (1.00)	0.0374 (1.00)	1 (1.00)	0.218 (1.00)
10q gain	10 (6%)	148	0.894 (1.00)	0.789 (1.00)	0.743 (1.00)	0.782 (1.00)	0.12 (1.00)	0.716 (1.00)	0.45 (1.00)	0.495 (1.00)	1 (1.00)	1 (1.00)
11p gain	5 (3%)	153		0.989 (1.00)	1 (1.00)	0.591 (1.00)	0.206 (1.00)	0.247 (1.00)	1 (1.00)	0.136 (1.00)	1 (1.00)	1 (1.00)
11q gain	8 (5%)	150	0.241 (1.00)	0.804 (1.00)	1 (1.00)	0.82 (1.00)	0.632 (1.00)	0.828 (1.00)	0.739 (1.00)	0.758 (1.00)	1 (1.00)	1 (1.00)
12p gain	17 (11%)	141	0.735 (1.00)	0.212 (1.00)	0.29 (1.00)	0.99 (1.00)	0.312 (1.00)	0.764 (1.00)	0.112 (1.00)	0.593 (1.00)	1 (1.00)	0.609 (1.00)
12q gain	11 (7%)	147	0.665 (1.00)	0.0384 (1.00)	1 (1.00)	0.249 (1.00)	0.396 (1.00)	0.23 (1.00)	0.63 (1.00)	0.592 (1.00)	0.306 (1.00)	0.56 (1.00)
13q gain	35 (22%)	123	0.332 (1.00)	0.398 (1.00)	0.695 (1.00)	0.483 (1.00)	0.845 (1.00)	0.266 (1.00)	0.649 (1.00)	0.774 (1.00)	1 (1.00)	0.709 (1.00)
14q gain	4 (3%)	154		0.579 (1.00)	0.0195 (1.00)	0.938 (1.00)			0.064 (1.00)		1 (1.00)	1 (1.00)
15q gain	7 (4%)	151	0.19 (1.00)	0.385 (1.00)	0.254 (1.00)	0.27 (1.00)	0.826 (1.00)	0.0358 (1.00)	0.692 (1.00)	0.461 (1.00)	1 (1.00)	1 (1.00)
16p gain	12 (8%)	146	0.565 (1.00)	0.575 (1.00)	1 (1.00)	0.369 (1.00)	0.039 (1.00)	0.072 (1.00)	0.0641 (1.00)	0.00834 (1.00)	0.33 (1.00)	0.0393 (1.00)
16q gain	7 (4%)	151	0.669 (1.00)	0.331 (1.00)	1 (1.00)	0.399 (1.00)	0.00049 (0.35)	0.334 (1.00)	0.0936 (1.00)	0.00701 (1.00)	1 (1.00)	0.403 (1.00)
17p gain	5 (3%)	153	0.0118 (1.00)	0.888 (1.00)	1 (1.00)	0.309 (1.00)	0.375 (1.00)	0.0097 (1.00)	0.0142 (1.00)	0.0866 (1.00)	1 (1.00)	1 (1.00)
17q gain	10 (6%)	148	0.172 (1.00)	0.625 (1.00)	1 (1.00)	0.754 (1.00)	0.324 (1.00)	0.0638 (1.00)	0.0217 (1.00)	0.232 (1.00)	1 (1.00)	1 (1.00)
18p gain	18 (11%)	140	0.662 (1.00)	0.479 (1.00)	0.61 (1.00)	0.819 (1.00)	0.848 (1.00)	0.0219 (1.00)	1 (1.00)	0.344 (1.00)	0.458 (1.00)	1 (1.00)
18q gain	8 (5%)	150	0.65 (1.00)	0.584 (1.00)	0.261 (1.00)	0.325 (1.00)	0.256 (1.00)	0.817 (1.00)	0.128 (1.00)	0.889 (1.00)	1 (1.00)	1 (1.00)
19p gain	10 (6%)	148	0.911 (1.00)	0.472 (1.00)	0.00685 (1.00)	0.216 (1.00)	0.645 (1.00)	0.0532 (1.00)	0.0217 (1.00)	0.0418 (1.00)	1 (1.00)	0.146 (1.00)
19q gain	17 (11%)	141	0.322 (1.00)	0.447 (1.00)	0.0314 (1.00)	0.499 (1.00)	0.165 (1.00)	0.212 (1.00)	0.138 (1.00)	0.0166 (1.00)	0.438 (1.00)	0.0993 (1.00)
20p gain	65 (41%)	93	0.0757 (1.00)	0.818 (1.00)	0.0046 (1.00)	0.647 (1.00)	0.353 (1.00)	0.605 (1.00)	0.156 (1.00)	0.138 (1.00)	0.649 (1.00)	0.761 (1.00)
20q gain	82 (52%)	76	0.0562 (1.00)	0.633 (1.00)	0.0089 (1.00)	0.513 (1.00)	0.0859 (1.00)	0.277 (1.00)	0.0363 (1.00)	0.147 (1.00)	1 (1.00)	0.214 (1.00)
22q gain	4 (3%)	154	0.754 (1.00)	0.244 (1.00)	0.635 (1.00)	0.911 (1.00)	1 (1.00)	0.3 (1.00)	1 (1.00)	0.29 (1.00)	1 (1.00)	1 (1.00)
1p loss	8 (5%)	150	0.121 (1.00)	0.828 (1.00)	0.261 (1.00)	0.617 (1.00)	0.0962 (1.00)	0.205 (1.00)	0.000537 (0.383)	0.00235 (1.00)	1 (1.00)	0.446 (1.00)
1q loss	4 (3%)	154	0.616 (1.00)	0.0837 (1.00)	0.635 (1.00)	0.182 (1.00)	0.58 (1.00)	0.503 (1.00)	0.064 (1.00)	0.245 (1.00)	1 (1.00)	0.253 (1.00)
3p loss	11 (7%)	147	0.627 (1.00)	0.448 (1.00)	0.749 (1.00)	0.693 (1.00)	0.937 (1.00)	0.81 (1.00)	1 (1.00)	0.796 (1.00)	1 (1.00)	0.56 (1.00)
3q loss	7 (4%)	151	0.731 (1.00)	0.511 (1.00)	0.71 (1.00)	0.707 (1.00)	1 (1.00)	0.871 (1.00)	1 (1.00)	0.846 (1.00)	1 (1.00)	1 (1.00)
4p loss	23 (15%)	135	0.874 (1.00)	0.0869 (1.00)	0.25 (1.00)	0.268 (1.00)	0.273 (1.00)	0.839 (1.00)	0.381 (1.00)	0.189 (1.00)	0.154 (1.00)	0.202 (1.00)
4q loss	22 (14%)	136	0.775 (1.00)	0.277 (1.00)	0.815 (1.00)	0.0249 (1.00)	0.115 (1.00)	0.951 (1.00)	0.698 (1.00)	0.281 (1.00)	0.143 (1.00)	0.183 (1.00)
5p loss	8 (5%)	150	0.399 (1.00)	0.556 (1.00)	1 (1.00)	0.0281 (1.00)	0.895 (1.00)	0.504 (1.00)	0.739 (1.00)	0.351 (1.00)	1 (1.00)	1 (1.00)
5q loss	18 (11%)	140	0.123 (1.00)	0.488 (1.00)	0.443 (1.00)	0.00197 (1.00)	0.16 (1.00)	0.886 (1.00)	0.233 (1.00)	0.171 (1.00)	0.458 (1.00)	1 (1.00)
6p loss	8 (5%)	150	0.675 (1.00)	0.0417 (1.00)	0.48 (1.00)	0.0173 (1.00)	0.219 (1.00)	0.0373 (1.00)	0.349 (1.00)	0.379 (1.00)	1 (1.00)	0.446 (1.00)
6q loss	12 (8%)	146	0.801 (1.00)	0.197 (1.00)	1 (1.00)	0.164 (1.00)	0.354 (1.00)	0.266 (1.00)	0.8 (1.00)	0.0908 (1.00)	1 (1.00)	0.593 (1.00)
7p loss	3 (2%)	155	0.232 (1.00)	0.184 (1.00)	0.289 (1.00)	0.421 (1.00)	0.038 (1.00)	0.0712 (1.00)	1 (1.00)	0.464 (1.00)	1 (1.00)	1 (1.00)
7q loss	5 (3%)	153	0.225 (1.00)	0.127 (1.00)	0.157 (1.00)	0.193 (1.00)	0.234 (1.00)	0.56 (1.00)	1 (1.00)	0.927 (1.00)	1 (1.00)	1 (1.00)
8p loss	13 (8%)	145	0.158 (1.00)	0.135 (1.00)	0.768 (1.00)	0.407 (1.00)	0.215 (1.00)	0.426 (1.00)	0.194 (1.00)	0.607 (1.00)	1 (1.00)	0.601 (1.00)
8q loss	4 (3%)	154		0.94 (1.00)	0.635 (1.00)	0.0202 (1.00)			1 (1.00)		1 (1.00)	1 (1.00)
9p loss	28 (18%)	130	0.0591 (1.00)	0.259 (1.00)	0.833 (1.00)	0.345 (1.00)	0.035 (1.00)	0.491 (1.00)	0.6 (1.00)	0.531 (1.00)	1 (1.00)	0.0264 (1.00)
9q loss	12 (8%)	146	0.219 (1.00)	0.233 (1.00)	1 (1.00)	0.544 (1.00)	0.0916 (1.00)	0.216 (1.00)	1 (1.00)	0.901 (1.00)	0.33 (1.00)	0.0393 (1.00)
10p loss	12 (8%)	146	0.219 (1.00)	0.235 (1.00)	0.537 (1.00)	0.0281 (1.00)	0.142 (1.00)	0.36 (1.00)	0.526 (1.00)	0.402 (1.00)	0.0467 (1.00)	0.198 (1.00)
10q loss	11 (7%)	147	0.266 (1.00)	0.899 (1.00)	1 (1.00)	0.0608 (1.00)	0.59 (1.00)	0.556 (1.00)	0.783 (1.00)	0.261 (1.00)	0.306 (1.00)	0.56 (1.00)
11p loss	13 (8%)	145	0.357 (1.00)	0.183 (1.00)	0.243 (1.00)	0.159 (1.00)	0.123 (1.00)	0.765 (1.00)	0.057 (1.00)	0.479 (1.00)	1 (1.00)	1 (1.00)
11q loss	10 (6%)	148	0.337 (1.00)	0.387 (1.00)	0.743 (1.00)	0.407 (1.00)	0.24 (1.00)	0.588 (1.00)	0.45 (1.00)	0.45 (1.00)	1 (1.00)	1 (1.00)
12q loss	8 (5%)	150	0.373 (1.00)	0.901 (1.00)	0.0246 (1.00)	0.591 (1.00)	0.286 (1.00)	0.0155 (1.00)	0.739 (1.00)	0.0948 (1.00)	1 (1.00)	1 (1.00)
13q loss	5 (3%)	153		0.899 (1.00)	1 (1.00)	0.139 (1.00)	0.484 (1.00)	0.303 (1.00)	0.566 (1.00)	0.537 (1.00)	0.15 (1.00)	0.0394 (1.00)
14q loss	10 (6%)	148	0.229 (1.00)	0.0539 (1.00)	0.743 (1.00)	0.854 (1.00)	0.917 (1.00)	0.792 (1.00)	0.766 (1.00)	0.961 (1.00)	1 (1.00)	0.525 (1.00)
15q loss	11 (7%)	147	0.575 (1.00)	0.224 (1.00)	0.749 (1.00)	0.101 (1.00)	0.245 (1.00)	0.246 (1.00)	0.63 (1.00)	0.702 (1.00)	0.0394 (1.00)	0.0307 (1.00)
16p loss	10 (6%)	148	0.602 (1.00)	0.441 (1.00)	0.0905 (1.00)	0.325 (1.00)	0.366 (1.00)	0.656 (1.00)	1 (1.00)	0.866 (1.00)	1 (1.00)	0.525 (1.00)
16q loss	14 (9%)	144	0.585 (1.00)	0.9 (1.00)	0.252 (1.00)	0.224 (1.00)	0.365 (1.00)	0.145 (1.00)	1 (1.00)	0.97 (1.00)	0.375 (1.00)	0.252 (1.00)
17p loss	35 (22%)	123	0.485 (1.00)	0.203 (1.00)	0.695 (1.00)	0.0136 (1.00)	0.33 (1.00)	0.209 (1.00)	0.848 (1.00)	0.561 (1.00)	0.0726 (1.00)	0.0669 (1.00)
17q loss	8 (5%)	150	0.895 (1.00)	0.385 (1.00)	0.48 (1.00)	0.00429 (1.00)	0.917 (1.00)	0.178 (1.00)	0.349 (1.00)	0.76 (1.00)	0.231 (1.00)	0.0982 (1.00)
18p loss	15 (9%)	143	0.27 (1.00)	0.928 (1.00)	1 (1.00)	0.897 (1.00)	0.262 (1.00)	0.283 (1.00)	0.714 (1.00)	0.676 (1.00)	1 (1.00)	0.28 (1.00)
18q loss	29 (18%)	129	0.241 (1.00)	0.227 (1.00)	1 (1.00)	0.365 (1.00)	0.633 (1.00)	0.146 (1.00)	0.165 (1.00)	0.626 (1.00)	0.585 (1.00)	0.0307 (1.00)
19p loss	16 (10%)	142	0.729 (1.00)	0.958 (1.00)	0.293 (1.00)	0.245 (1.00)	0.624 (1.00)	0.185 (1.00)	0.734 (1.00)	0.569 (1.00)	1 (1.00)	1 (1.00)
19q loss	12 (8%)	146	0.817 (1.00)	0.2 (1.00)	0.537 (1.00)	0.277 (1.00)	0.673 (1.00)	0.106 (1.00)	0.659 (1.00)	0.158 (1.00)	1 (1.00)	1 (1.00)
20p loss	4 (3%)	154	0.319 (1.00)	0.892 (1.00)	0.154 (1.00)	0.803 (1.00)	0.072 (1.00)	0.623 (1.00)	0.064 (1.00)	0.376 (1.00)	1 (1.00)	0.253 (1.00)
21q loss	31 (20%)	127	0.992 (1.00)	0.819 (1.00)	0.681 (1.00)	0.266 (1.00)	0.852 (1.00)	0.856 (1.00)	0.62 (1.00)	0.777 (1.00)	1 (1.00)	0.0408 (1.00)
22q loss	24 (15%)	134	0.602 (1.00)	0.323 (1.00)	0.82 (1.00)	0.242 (1.00)	0.798 (1.00)	0.453 (1.00)	0.888 (1.00)	0.639 (1.00)	0.566 (1.00)	0.674 (1.00)
Xq loss	7 (4%)	151	0.165 (1.00)	0.579 (1.00)	0.71 (1.00)	0.732 (1.00)	0.419 (1.00)	0.205 (1.00)	1 (1.00)	0.376 (1.00)	0.205 (1.00)	0.0766 (1.00)

'12p loss mutation analysis' versus 'PATHOLOGY.N'

P value = 0.000269 (Fisher's exact test), Q value = 0.19

Table S1. Gene #57: '12p loss mutation analysis' versus Clinical Feature #6: 'PATHOLOGY.N'

nPatients	N0	N1	N2	N3
ALL	44	57	24	15
12P LOSS MUTATED	9	0	0	1
12P LOSS WILD-TYPE	35	57	24	14

Figure S1. Get High-res Image Gene #57: '12p loss mutation analysis' versus Clinical Feature #6: 'PATHOLOGY.N'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = STAD.clin.merged.picked.txt
Number of patients = 158
Number of significantly arm-level cnvs = 73
Number of selected clinical features = 10
Exclude genes that fewer than K tumors have mutations, 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 tumors with and without gene mutations using 't.test' function in R

Fisher's exact test

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

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

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] 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)

[4] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[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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